Dartmouth Undergraduate Journal of Science - Spring and Summer, 2021 by dartmouthjournalofscience

DUJS

Dartmouth Undergraduate Journal of Science SP R I N G A N D SUM M E R 2 0 2 1

VO L . X X I I I

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DISCONNECT

REALIGNING THE WORLD IN A FRAC TURED TIME

Bibbidi Bobbidy Bone: Exploring the Magic Behind Bone Tissue Engineering

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Gut Microbiota: An Alternative Approach to Treating Depression

pg. 110

An Introduction to the Medicinal Uses of Marijuana

pg. 242 DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Letter From the Editor in Chief With this being my first “Letter From the Editor in Chief,” I sought out to make it as good as I could. I read every word from the letters in past journals that I had access to, studying their structure, word choice, subject, and more. I went through countless drafts trying to find the right hook, the right phrase, the right topic, to write about, and yet nothing compared to what I read from the past. I thought my words had to be perfect. Until I realized – they don’t. To be frank, little has been perfect during my time as Editor in Chief. Just in the past two terms, the President and I have had to go through the awkwardness of a leadership change while running the journal remotely, in-person, and even hybrid formats. While we’ve succeeded in some respects, the transition hasn’t been close to perfect. And while many of our writers and editors have enjoyed getting to see and know each other, virtually one week and maybe in-person the next, they will attest that it hasn’t been perfect. Nothing seems to compare to the library rooms that seemed most welcoming from eight to nine on Thursdays, where we could freely bond with fellow members of the group and share our ideas, both those journal related and those not. But despite all of this, it is clear to me, as I hope it will be to you after you take the time to explore this edition, that the writing of the Dartmouth Undergraduate Journal of Science has never been stronger. I could not be prouder of our writers for continuing to exceed expectations. With both the opportunity to expand our editorial board and more interest in the Journal than ever, we have had articles whose quality rivals and even exceeds the greats I have seen from journals past. Looking at the topics this term, it is clear the articles in this edition have pushed the bounds of what past editions have traditionally interpreted as science to include areas of modern science that are being analyzed in today’s world. Writers have touched the controversial, such as the medical benefits of medical marijuana, and explored the conventional, such as the exploration of the history of muscular dystrophy. With the scientific community having a revolution on what has traditionally bound it in, it has been inspiring to see many of our writers rise to the challenge to communicate some of the most important questions that face the community. This depth and breadth of the journal, however, has expanded beyond the traditional Dartmouth contributions that we have seen in the past. This year, we held our first annual Building the Modern MD competition, in which high school students around the world submitted literature reviews on topics in medicine and one of eight subjects in the humanities. I would like to extend my sincerest congratulations to the eight winners that earned the prize of being featured in our journal: ChaeGhang Jeong, Doyeol Kim, Jioh In, Julianna Lian, Natalia Pahlavan, Sajid Huq, Stephanie Park, and Zainab Neemuchwala. Our editing teams very much enjoyed reading your work and are confident that you all have bring futures in medicine awaiting you if you so choose to pursue them. And, to address the DUJS team that put together this exciting new venture, we cannot wait to build upon the success this upcoming year and mimic the success in other new projects our group will take on. And so, while I understand that neither the words that I have written in this letter nor the words I will write in future letters are perfect, it does not matter to anyone except my mother. The only words that really matter in these 280 pages are the ones by those writers listed to the side of this page that continue to push the definition of perfection with each edition. And it is with these final sentences that I thank you, the reader, for making our journal a success for over two decades and hope you enjoy what we have in store for this issue.

The Dartmouth Undergraduate Journal of Science aims to increase scientific awareness within the Dartmouth community and beyond by providing an interdisciplinary forum for sharing undergraduate research and enriching scientific knowledge. EXECUTIVE BOARD President: Anahita Kodali '23 Editor-in-Chief: Dev Kapadia '23 Chief Copy Editors: Aditi Gupta '23, Daniel Cho '22, Dina Rabadi '22, Kristal Wong '22, Maddie Brown '22 EDITORIAL BOARD Managing Editors: Alex Gavitt '23, Andrew Sasser '23, Audrey Herrald '23, Carolina Guerrero '23, Eric Youth '23, Georgia Dawahare '23, Jillian Troth '24 Assistant Editors: Callie Moody '24, Caroline Conway '24, Grace Nguyen '24, Jennifer Chen '23, Matthew Lutchko '23, Miranda Yu '24, Owen Seiner '24 STAFF WRITERS Aarun Devgan '23

Abenezer Sheberu '24

Abigail Fischer '23

Advaita Chaudhari '24

Amritha Anup '22

Anahita Kodali '23

Angel Ugo-Nwauwa

Anna Gundlach '23

Anna Kölln '22

Anushka Bhatia '24

Ashna Kumar '24

Ayushya Ajmani '24

Brooklyn Schroeder '22

Cady Rancourt '24

Caroline Conway '24

Chae-Chang Jeong

Daniel Kotrebai '24

Dev Kapadia '23

Doyeol Kim

Evan Craft

Frankie Carr '22

Georgia Dawahare '23

Grace Nguyen '24

Isabelle Wilson '23

Jioh In

John Zavras '24

Julianna Lian

Justin Chong '24

Justin Fajar

Lauren Ferridge '23

Love Tsai '23

Maeen Arslan '24

Matthew Lutchko '23

Natalia Pahlavan

Rujuta Purohit '24

Sajid Huq

Sarah Lamson '24

Soyeon (Sophie) Cho '24

Stephanie Park

Suchitra Sudarshan

Tim Strang '22

Tyler Chen '24

Vaishnavi Katragadda '24

Varun Lingadal '23

Varun Malladi '23

Veda Sane '23

Victoria Faustin '23

Zainab Neemuchwala

Sincerely, Dev Kapadia

SPECIAL THANKS Dean of Faculty Associate Dean of Sciences Thayer School of Engineering Office of the Provost Office of the President Undergraduate Admissions R.C. Brayshaw & Company

Individual Articles

Table of Contents

Effects of Exercise on Mental Health Aarun Devgan '23, Pg. 6 Bibbidi Bobbidy Bone: Exploring the Magic Behind Bone Tissue Engineering Amritha Anup '23, Pg. 10

Challenges in the Clinical Treatment of Obese Cancer Patients Anahita Kodali '23, Pg. 18 Addressing the Plastic Waste Problem with Chemical Upcycling Anna Kölln '22, Pg. 26 Healthcare Inequality for Unauthorized Immigrants Anushka Bhatia '24, Pg. 32

Mutant p53 and its Isoforms in the Onset & Treatment of Breast Cancer Brooklyn Schroeder '22, Pg. 38 Health and Heat Waves: Harbingers of What's to Come with Anthropogenic Climate Change Cady Rancourt '24, Pg. 44 When Hands Are Tied Instead of Tubes: The Barriers Women Face in Accessing Tubal Ligations Caroline Conway '24, Pg. 50

On the Structure of Field Theories III Evan Craft, Pg. 56 Natural Selection on Humans by Pathogens Frankie Carr '22, Pg. 62 The Impact of Mozart's Music on Epileptic Patients Georgia Dawahare '23, Pg. 70

Big Pharma Sustainability John Zavras '24, Pg. 76 The Role of Alarm Signal Design in Antipredator Defense in Conspecific Communication Justin Chong '24, Pg. 82 The Current State of Immunotherapy: Checkpoint Inhibitor Drugs Matthew Lutchko '23, Pg. 90 Quantum Entanglement and its Applications Rujuta Purohit '24, Pg. 100

116

Gut Microbiota: An Alternative Approach to Treating Depression Sarah Lamson '24, Pg. 110 Gene Therapy as a Treatment for Malignant Brain Tumors Soyeon (Sophie) Cho '24, Pg. 116

Pharmacogenetic Testing: Using the Serotonin Transporter Gene to Predict Selective Serotonin Reuptake Inhibitor Response Suchitra Sudarshan, Pg. 130

DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Individual Articles

Table of Contents

The Quantum Playing Field: Qubits and the Supremacy Question Tim Strang '24, Pg. 138 Effects of Public Transportation Development Tyler Chen '24, Pg. 146 mRNA Vaccinology Perspectives Varun Lingadal '23, Pg. 152 A (co-)End Approach to Day Convolution Varun Malladi '23, Pg. 158

146

Building the Modern MD Winner Articles Holistic Overview and Discussion of Homosexuality and Genetics Chae-Chang Jeong, Pg. 164 COVID-19: Non-Equitable Healthcare and the Challenges of Achieving Equity Doyeol Kim, Pg. 170

170

Medical Ethics of Artificial Intelligence for Diabetic Retinopathy Screenings Jioh In, Pg. 176 Cultural, Regional Diets and Understanding Cancer Distribution Julianna Lian, Pg. 184 From Beaked Masks to Bandanas: The Evolution of PPE in the Fight Against Infectious Diseases Natalia Pahlavan, Pg. 194

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A Brief Review of the Evidence on the Health Benefits of Meditative Prayer and Active Gratitude Sajid Huq, Pg. 202 Medicine and the Modern Media Stephanie Park, Pg. 208 Utilizing Interpersonal Psychotherapy as a Prominent Treatment Option for Lower Socioeconomic Ranking Pregnant Mothers Diagnosed with Postpartum Depression Disorder Zainab Neemuchwala, Pg. 216

222

Team Articles Overview of Inequities in Cancer Composition, Mortality, and Treatment Pg. 222 An Introduction to the Medicinal Uses of Marijuana Pg. 242 U.S. Health Insurance Inefficiencies and Improvements Pg. 248

248

An Overview of Duchenne's Muscular Dystrophy: Molecular Mechanisms, Clinical Manifestations, and Treatments Pg. 262 SPRING AND SUMMER 2021

Effects of Exercise on Mental Health BY AARUN DEVGAN ’23 Cover Image: Man going on an early morning jog. Image Source: Pixabay

Introduction

Effects of Exercise on Depression

Simply put, the current status of mental health in America is quite poor. According to Mental Health America’s 2021 report “The State of Mental Health in America,” youth and adult mental health is declining and there is still an unmet need for mental health treatment. The statistical measures used in the report show a clear trend of worsening mental health in the United States over the last twenty years. Over the 5-year span from 2012 to 2017, the prevalence of a Major Depressive Episode (MDE) has increased from 8.66% to 13.01% among children ages 1217 (Mental Health America, 2021). Additionally, while the prevalence of mental health issues in adults has remained constant, however suicide and suicidal thoughts are increasing. Mental Health America’s report explains that suicidal ideation has increased from 3.77% to 4.19% over the study’s 5-year span. Among that group, young adults ages 18-25 experienced the highest rates of suicide ideation. The worsening status of mental health in America is a pressing issue that must be combatted from all sides. An often-overlooked method in the fight against worsening mental health is the effects of exercise, which have surprisingly positive effects on mental health.

Depression is the leading cause of disability in the United States, causing an estimated $40 billion due to the associated with the loss of work productivity and medical treatment (Murray, 1996). Most people who suffer from depression look towards their primary care physician for help. However, primary care physicians often prescribe medications without considering nonpharmacologic methods for fighting depression. Research shows that exercise is directly correlated to the treatment of clinical depression. Additionally, clinically depressed patients are often less physically fit than 80-90% of age predicted normality (Craft, 2004). For both reasons, it is crucial to inform both primary care physicians and depressed patients about the significant benefits exercise can have on their quality of life. Many studies have demonstrated that exercise reduces symptoms of depression. One that is quite notable is a study involving 30 moderately depressed men and women who were assigned randomly to one of 3 groups: an exercise intervention group, a social support group, and a control group (McNeil, 1991). The exercise DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 1: Man doing weighted exercises. Source: Pixabay

intervention group engaged in 3 30-minute walks a week for 6 weeks. The results show a reduction of somatic symptoms of depression quantified as 2.4 compared to a 0.9 reduction in the social support group, and a 0.4 reduction in the control group (McNeil, 1991). Other research has shown the long-term benefits of exercise on mental health. After twelve weeks of fitness training, depressed adults deceived a BDI reduction of 5.1 compared to the control BDI reduction of 0.9 (McNeil, 1991). The participants retained these benefits throughout a 12 month follow up period.

156 moderately depressed men and women to an exercise only group, a medication only group, and an exercise and medication group (Blumenthal, 1999). The exercise group walked on a treadmill for 30 minutes at 70-85% of their maximum heart rate 3 times a week for 16 weeks. Those in the medication group received sertraline where the dosage was monitored by a psychiatrist at 2, 6, 10, and 14 weeks. Participants in both the exercise

"After twelve weeks of fitness training, depressed adults deceived a BDI reduction of 5.1 compared to the control BDI reduction of 0.9" Figure 2: Man receiving therapy from a professional. Source: Pixabay

Comparing of the Benefits of Exercise with the Benefits of Therapy and Medication Many studies have demonstrated the benefits of exercise and therapy on mental health individually. However, it is important to compare these two methods and if increased benefits are experienced when used together. Participants in this study were randomly assigned to a running group only, a therapy group only, or a running and therapy group. The treatment lasted for 10 weeks with the exercise group consisting of 20-minute sessions 3 times a week and the therapy aspect lasting 60 minutes once a week. There was no significant difference between the groups, but they all experienced significant reduction in symptoms of depression (Craft, 2004). Additionally, the beneficial effects of exercise on one’s mental health have also been studied in comparison to the effects of medication. Blumenthal and colleagues randomly assigned SPRING AND SUMMER 2021

Figure 3: Group cardio class. Image Source: Pixabay

"However, an important difference is that 10 months of regular exercise led to significantly lower rates of depression compared to 10 months of medication"

and medication category simply received both treatments mentioned above. The results conclude that there is no significant difference between any of the 3 groups in the study (Blumenthal, 1999). They were all similarly effective in reducing the effects of depression. It is important to note that the medication works faster at first to reduce symptoms. However, an important difference is that 10 months of regular exercise led to significantly lower rates of depression compared to 10 months of medication (Blumenthal, 1999). Thus, while at first medication may result in quicker results, the better long-term option is consistent exercise.

Cardio vs. Weight Training for Mental Health Benefits Most studies that have investigated the effects of exercise on one’s mental health employ aerobic exercises such as walking or jogging. However, it is important to consider the benefits of nonaerobic exercises such as resistance and weight training. Doyne and colleagues did just that as she compared the efficacy of running versus weightlifting for improvement of mental health and a decrease in the symptoms of depression. Her study involved 40 depressed women who were randomly assigned to either running, weightlifting, or a wait-list control group. The study was an 8-week program with 4 training sessions per week for both the running and weightlifting group. Measurements of depression were taken at the mid-way, end of treatment, and 1, 7, and 12 months afterwards. The results of the study indicate that there is no significant difference in the beneficial effects for running

vs weightlifting. They both significantly reduced the symptoms of depression in the participants (Doyne, 1983). Ultimately, the decision to do aerobic vs anerobic exercises should lie in the personal preference of the patient and suggestions from their primary care provider.

Effects of Exercise on Stress and Anxiety Aerobic exercise is very important for one’s mind. It can help to relieve tension and improve one’s mood. It can help to relax and exhilarate, and it can also help people manage stress. It is also used to treat depression and anxiety disorders. Aerobic exercise helps reduce stress hormones and boost the production of endorphins, which are the body's natural painkillers. Your body's response to exercise can also improve your self-image. It can help you feel powerful and confident. Sports and exercise can also help you get away from daily stress associated with school or work and allow you to find a new passion (Harvard Health, 2020).

Conclusion Through various studies, it has clearly been established that exercise is the most beneficial treatment to mental health. Additionally, it can be combined with therapy or medication for added benefits without any additional risks. The problem lies in the fact that despite the immense benefits, prescribing a structured exercise plan is often overlooked by doctors. These problems become more prominent across certain aspects of the population as there is often a lack of mental health and exercise resources for those people DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

with lower socioeconomic statuses. They often look at mental health as not a real or urgent health problem and thus can not reason spending money to see a specialist to get help. Additionally, gym memberships have a fee that people with lower socioeconomic statuses often cannot justify. Furthermore, lack of wealth can make it harder for people to be physically fit due to the stress of living paycheck to paycheck and often eating fast food, as it is cheap (Drewnoski). It is important that doctors emphasize the benefits of exercise on mental health, especially to the lower socioeconomic class and encourage them to go for walks or runs outside – where a gym membership is not needed.

Science (New York, N.Y.), 274(5288), 740–743. https://doi. org/10.1126/science.274.5288.740

References 2021 State of Mental Health in America. Mental Health America. (n.d.). https://www.mhanational.org/researchreports/2021-state-mental-health-america. Blumenthal, J. A., Babyak, M. A., Moore, K. A., Craighead, W. E., Herman, S., Khatri, P., Waugh, R., Napolitano, M. A., Forman, L. M., Appelbaum, M., Doraiswamy, P. M., & Krishnan, K. R. (1999). Effects of exercise training on older patients with major depression. Archives of internal medicine, 159(19), 2349–2356. https://doi.org/10.1001/ archinte.159.19.2349 Craft, L. L., & Perna, F. M. (2004). The Benefits of Exercise for the Clinically Depressed. Primary care companion to the Journal of clinical psychiatry, 6(3), 104–111. https://doi. org/10.4088/pcc.v06n0301 Doyne EJ, Chambless DL, Beutler LE. Aerobic exercise as a treatment for depression in women. Behav Ther. 1983;14:434– 440 Drewnowski, A., & Eichelsdoerfer, P. (2010, May 14). The economics of OBESITY: Why are poor people fat? Obesity Prevention. Retrieved September 15, 2021, from https://www. sciencedirect.com/science/article/pii/B9780123743879000581. Haspel, T. (2018, July 23). Perspective | the true connection between poverty and obesity isn't what you probably think. The Washington Post. Retrieved September 15, 2021, from https://www.washingtonpost.com/lifestyle/food/the-trueconnection-between-class-and-obesity-isnt-what-you-probablythink/2018/07/19/8d3a61e4-8ac8-11e8-a345-a1bf7847b375_ story.html. Exercising to Relax - Harvard Health Publishing. Harvard Health. (2020, July 7). https://www.health.harvard.edu/stayinghealthy/exercising-to-relax. McNeil, J. K., LeBlanc, E. M., & Joyner, M. (1991). The effect of exercise on depressive symptoms in the moderately depressed elderly. Psychology and aging, 6(3), 487–488. https://doi. org/10.1037//0882-7974.6.3.487 McWilliams, J. (2014, August 4). Why are so many low-income people so overweight? Pacific Standard. Retrieved September 15, 2021, from https://psmag.com/social-justice/many-lowincome-people-overweight-87379. Murray, C. J., & Lopez, A. D. (1996). Evidence-based health policy--lessons from the Global Burden of Disease Study.

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Bibbidi Bobbidy Bone: Exploring the Magic Behind Bone Tissue Engineering BY AMRITHA ANUP '23 Cover Image: Flowchart depicting foundational steps making up the tissue engineering model. First, a biopsy is used to collect cells and tissue with regenerative potential. This is then cultivated and grown outside of the body under optimal conditions. A scaffold that is compatible with the body is developed. The collected tissue and cells are then integrated with the scaffold that can be stimulated externally to promote organized growth. This is then implanted into the patient Image Source: Wikimedia Commons

Musculoskeletal disorders are conditions that impair locomotive abilities. Many factors cause these disorders, including repetitive motions and unnatural body positions exacerbated by the modern-day workplace (Malik et al., 2018). They are estimated to affect every 1 in 2 Americans, with osteoporosis and osteoarthritis becoming more widespread (Briggs et al., 2018). Osteoarthritis is the most common form of arthritis in the U.S. (Neogi, 2013). It involves degeneration of the cartilage that lubricates joints in areas such as the hips, knees, and fingers [Figure 1A]. Another condition, rheumatoid arthritis [Figure 1A], results from an autoimmune disease in which the immune system attacks the joints. The outcome of both conditions is joint syndromes. Osteoporosis causes flash, or unannounced, fractures that are especially common in older women [Figure 1B]. Osteoporosis is estimated to cause 2 million bone fractures per year in the U.S. (Morrell et al., 2021). The chronic forms of these conditions do not have cures; treatments only work for some people, and they provide only short-term relief. Surgeries, such as joint replacement and bone grafting procedures, come with concerns of immune

rejection, are not widely available, and have a high risk of infection due to potential pathogen transfer (Seong et al., 2010; Henkel et al., 2013). Bone tissue engineering introduces a personalized approach to treating these conditions and aims to replicate and stimulate the body’s healing process through the introduction of biocompatible materials. These are materials that mimic or come from living tissues and they do not cause undesirable effects (Kowalczuk, 2020). These cells are collected from the patient and grown in an organized manner outside of the body using a scaffold [Figure 2]. A scaffold is critical in supporting the transformation from a twodimensional layer of cells to a three-dimensional tissue (Swenson, 2013). They are typically made of a biocompatible material, or a material that is safe to put into the body, such as the polyester scaffold poly(ε-caprolactone), or PCL (Dwivedi et al., 2020). This tissue is then implanted into the patient. The final tissue product requires the integration of three components (Quarto & Giannoni, 2016): 1. an osteogenic or osteoinductive environment – this is an environment that supports bone formation and communication between DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 1: (A) Progression of osteoporosis and its effect on bones. As osteoporosis becomes more severe, excessive bone loss and/or reduced bone growth causes the bone microstructure to become more brittle. This results in bones that are prone to fracturing under stress (Image Source: Wikimedia Commons). (B) How osteoarthritis and rheumatoid arthritis affect the joint. A healthy joint consists of intact cartilage (shown in blue). Osteoarthritis develops when the cartilage at the joint becomes damaged due to mechanical wear. Rheumatoid arthritis is characterized by joint inflammation caused by an overactive immune system that attacks the joints

Image Source: Wikimedia Commons

different cells (Albrektsson & Johansson, 2001); 2. growth factors, or molecules that can stimulate cell growth; 3. and a biomaterial matrix that supports osteoconduction (Albrektsson & Johansson, 2001), which means bone growth on the matrix surface through processes such as cellular attachment, migration, and proliferation.

Why Bone Tissue Engineering? Bone is the second most transplanted material and about 3.5 million bone grafts are performed each year (Henkel et al., 2013). Bone, unlike most other types of tissue, can heal and regenerate itself to fix minor fractures and defects without forming fibrous scar tissue (Sheen & Garla, 2021). This process consists of the formation of a hematoma, or blood clot, followed by collagenous tissue formation. This collagenous growth will become more calcified over time, and the bone undergoes a process called remodeling. Remodeling consists of a balance between removing damaged bone and forming the new bone, and the process can span years. Large bone defects, on the other hand, cannot be repaired by bones alone (Qu et al., 2019). Since bones have the potential to self-regenerate in some capacity, they are a great SPRING AND SUMMER 2021

organ system to explore bone tissue engineering. The field aims to develop external scaffolds, harvest and apply cells, and use biologically active molecules to induce proper healing of the bone tissue when the damage is severe. Bone is a connective tissue network made of a complex mixture of inorganic and organic materials such as hydroxyapatite and collagen proteins (Feng, 2009; Henkel et al., 2013). The skeleton is a dynamic system that provides structural integrity, protection, and acts as a chemical reservoir. These characteristics are made possible by the structural organization and mechanical properties of bone. The outer surface of bone is made of a hard shell called compact, or cortical bone [Figure 3]. Making up the insides of the shell is spongy, trabecular bone, which forms a network through the core of the bone that consists of bone marrow. Bone is known to be mechanoreceptive, which means it adapts to applied mechanical stimuli (Qu et al., 2019). The exterior cortical layer and porous trabecular bone adapt or remodel in response to mechanical stresses and strains (Manzini et al., 2021) by the actions of highly specialized cells.

"The skeleton is a dynamic system that provides structural integrity, protection, and acts as a chemical reservoir."

Remodeling, or coupled bone removal and formation, begins with the activation of 11

the 1800s, Plaster of Paris, also known as calcium sulfate, was used to fill bone cavities.

Figure 2: Here, the crisscross patterns are made of polycaprolactone or poly(εcaprolactone), also known as PCL, which is a material that can be used for bone tissue engineered scaffolds. It was introduced as a reference material by the National Institute of Standards and Technology (NISD) in 2013. The fluorescent regions on the image mark cells that have proliferated. Image Source: Wikimedia Commons

"The idea of bone regeneration is not new, and the field of bone tissue engineering has a rich history."

osteoclasts, which are cells that resorb or dissolve bone. Once osteoclasts undergo apoptosis, osteoblasts begin forming new bones (Langdahl et al., 2016). Osteocytes are star-shaped cells derived from osteoblasts, and they work with osteoclasts to regulate bone repair (Creecy et al., 2021). Resorption and formation must be balanced for bone structures to retain their quality and function. When bone experiences a small injury, such as a hairline fracture, the bone can heal on its own. For larger injuries, or if the patient has a condition that prevents the natural bone regenerative process, bone cannot fix itself (Dimitriou et al., 2011). While attempting the healing process, the injured region succumbs to issues such as insufficient blood supply due to vascular damage and healing cannot be completed.

A Snapshot of the Rich History of Bone Tissue Engineering and Regeneration The idea of bone regeneration is not new, and the field of bone tissue engineering has a rich history. In Peru, a skull from 2000 BC was discovered with a 1 mm thick plate of gold masking a bone defect that was likely caused by trepanation, which involves drilling a hole into the skull to relieve symptoms of neurological conditions (Henkel et al., 2013). During 600 BC, ancient Egyptians developed skills used in orthopedic surgeries as mummies have been found to have iron prostheses implanted for knee joint replacement (Henkel et al., 2013). Around the same period, the Indian surgeon Susruta wrote an account of skin graft techniques for reconstructing the nose using skin from the forehead, and this account was included in one of the first textbooks on surgery (Willyard, 2016). In 1668, Dutch surgeon Job Janszoon van Meerkenen performed the first bone xenograft. A xenograft is a piece of tissue that originates from a species different from the recipient. Janszoon van Meerkenen repaired a skull defect using a bone xenograft from a deceased dog and the graft was successfully incorporated into the patient. In

Philips von Walters performed the first bone autograft in 1820 using tibial bone wedges from three donors to reconstruct the humerus bone in a 3-year-old affected by rickets, which is a debilitating musculoskeletal disorder that causes weak bones due to reduced calcium or phosphate levels in the blood. These reduced levels can contribute to delayed bone mineralization (Carpenter et al., 2017). During the later years of the 19th century, Louis Léopold Ollier coined the term ‘bone graft’, and he along with German surgeon Arthur Barth contributed to the foundation of current bone grafting procedures. In 1986, the Masquelet technique for bone reconstruction was introduced. This technique leads to a particular immune system reaction that favors the healing process (Henkel et al., 2013). This process is commonly used for treating long bone defects that are greater than 5 cm in length (Bosemark et al., 2015; Sivakumar et al., 2016). First the damaged bone tissue is removed. Then the defect site is filled with a polymethylmethacrylate (PMMA) plastic spacer. The spacer triggers a ‘foreign body reaction’ and the formation of a thick membrane. This membrane has desirable properties for bone regeneration (Henkel et al., 2013), such as rich vascularization and the presence of growth factors. Once the soft tissue in the damaged area has regenerated, the PMMA spacer can be removed. A bone graft, more specifically an autograft, is inserted into the cavity and the body’s healing process begins expanding on the graft.

Current Bone Regeneration Treatments are Insufficient Current bone regeneration treatments fall into one of two main categories: autografts and allografts. These types of grafts provide mechanical support and a source of regenerative cells (Goldberg & Stevenson, 1987). For bone defects that are smaller than 5 cm, an autograft is commonly used (Bosemark et al., 2015). An autograft procedure is a two-surgery process. First, the patient’s tissue is surgically transferred from one part of a patient’s body to another part of the patient’s body. Bone cells are commonly harvested from the iliac crest, located on the pelvis, because the region has a high amount of bone (Robinson et al., 2018), and the cancellous bone in this region contains many osteoblasts, or bone forming cells. These cells are then implanted at the site of bone injury. Autografts are the gold standard of currently available bone DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

tissue engineering techniques because it is nonimmunogenic. This means the patient’s immune system is unlikely to reject the implant since the graft tissue is not foreign to the patient (Amini et al., 2012). However, the additional surgery to extract graft material for the treatment takes an added toll on the patient’s body, and the amount of available bone graft varies per patient. There is an 8.6% chance patients will develop serious conditions during or due to the graft collection procedure. One example of a condition is a hematoma (Baldwin et al., 2019), which occurs when there is a buildup of blood caused by ruptured blood vessels. Allografts, on the other hand, involve taking tissue from another person’s body and transferring this to the patient implantation site. They account for about one-third of all bone grafts in the U.S. (Baldwin et al., 2019). Allografts are an optimal solution for patients who cannot undergo a second surgery or those who do not have enough graft tissue in their bodies. The main concern with this procedure is reduced efficacy due to storage and sanitation limitations. The grafts are stored by freeze drying, which is a process that removes all water from the tissue. This method makes the graft mechanically weaker and can destroy cells (Baldwin et al., 2019).

In addition to autografts and allografts, another bone regeneration treatment is xenografts. These are grafts derived from animal tissue. The major disadvantages of xenografts are that they will likely cause graft rejection similar to allografts, however, consequences may be more drastic with xenografts because the graft comes from another species. These also have the risk of transmitting zoonotic diseases (Oryan et al., 2014) to both the patient and the wider human population (Fishman et al., 2012). The risk of infection depends on the graft species, amount of tissue grafted, and the patient immune system. A benefit of xenografts is that they may support a timely procedure, especially when allografts are not available.

Tissue Engineering is Filling Voids in Current Bone Regeneration Treatments Tissue engineering combines the use of engineered scaffolds, growth factors, and cells from the patient to bolster the body’s natural healing process. Scaffolds or artificial extracellular matrices are foundational in tissue engineering. They are responsible for supporting a system that promotes proliferation, differentiation, and growth of cells. They must be biocompatible, or not cause ill effects to the body, to ensure safe implantation into the host as well as porous to support the spreading of cells and development of a vascular network and made in a geometry that allows cells to interact with each other. These scaffolds are temporary (Abbasi et al., 2020); the scaffold degradation rate must be fast enough to make room for newly growing tissue, though slow enough to provide enough support during the tissue regeneration process. The process of engineering scaffolds requires significant biomaterial and architectural design. The development of biomaterials has evolved in three generations in the last 30 years. A goal of the first generation of biomaterials was to have them closely match the host’s body to reduce the chances of triggering an immune system response. Examples of biomaterials include titanium metal, synthetic polymers such as (PMMA), and ceramics (Henkel et al., 2013). Second generation materials are more biocompatible, and they positively interacted with the host environment. For example, these bioactive materials can degrade in vivo, or in the patient’s body. Third generation materials are more powerful, and they can stimulate the treatment site in response to biological factors and external stimuli.

Figure 3: Long bone biology. The outer shell of bone is compact or cortical bone. The periosteum is a thin sheet that covers compact bone. Near the top and bottom ends of the bone, there is a large volume of cancellous or spongy bone. Integrated into this spongy matrix is red bone marrow. Near the middle of the bone, the core is made up of yellow bone marrow Image Source: Wikimedia Commons

One of the challenges facing third generation, bioactive materials is that they are less SPRING AND SUMMER 2021

Figure 4: The top left image shows the lower jaw which contains the ramus-condyle unit; highlighted in blue is the temporomandibular joint condyle. The lower left image shows a decellularized bone (DCB) and polycaprolactone (PCL) hybrid scaffold. Both images on the right are zoomed in images of the scaffold, with the top right image showing bone cells stained in red. Image Source: NIH Image Gallery

"One of the challenges facing third generation, bioactive materials is that they are less manufacturable than synthetics, such as those that fall under first generation materials"

manufacturable than synthetics, such as those that fall under first generation materials (Hung et al., 2016). There has been limited success in incorporating growth factors into synthetics to make them more bioactive, but in 2016, a group of researchers at Johns Hopkins University combined decellularized bone (DCB) matrix particles with the synthetic polyester polycaprolactone (PCL) to make a manufacturable and bioactive alternative for bone tissue engineering applications [Figure 4]. DCB’s are a type of allogeneic source of osteoinductive and osteoconductive properties that work well for bone tissue engineering applications. The group then implanted these scaffolds into mouse models with defects on the calvaria or top part of the skull. It was observed that the hybrid DCB and PCL material grew about double the volume compared to the PCL only control. After the scaffold has been designed, cells that are osteogenic, or capable of forming bone, are seeded into the matrix material (Henkel et al., 2013). In the past 20 years, significant progress has been made in gathering information about

stem cells. Stem cells are unspecialized cells that have self-renewing capabilities (Seong et al., 2010), and they can be stimulated to specialize into osteogenic, bone forming cells. Therefore, stem cells can be used in bone tissue engineering. Osteoprogenitor stem cells can be collected from the periosteum (the thin outer layer of bone), bone marrow, spleen, or thymus. These cells are then isolated, cultured, and stimulated to develop into bone.

Modern Day Technical Applications Over the past decade, the need for bone grafting has become more pronounced and this trend is continuing. With an aging Baby Boomer population, cases of joint diseases, back pain, osteoporotic fractures are rapidly increasing, and there is a significant demand for joint and bone restoring procedures (Baroli, 2009). Each year about 0.5 million bone grafts surgeries are performed in the United States (Baldwin et al., 2019). Bone tissue engineering research continues to evolve, and there have been several significant modern-day developments in the field. Two prominent examples of bone tissue engineering

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companies are epiBone and Cerapedics. epiBone is a biomedical engineering startup that originated from Columbia University and specializes in bone reconstruction. The epiBone technology was developed from tissue engineered grafts for facial bone reconstruction (Bhumiratana et al., 2016). Facial bones have complex geometries, so using standard auto or allografts to treat facial deformities come with significant comorbidities. The aim of work at epiBone is to engineer the ramus-condyle unit bone in the skull making up the jaws. This bone was engineered using stem cells and a scaffold, using the Yucatan minipig as a preclinical animal model. The novel workflow starts with a CT scan of the bone region that needs to be replicated. Then, a scaffold is prepared from bovine bone. The scaffold is shaped into the complex geometry of the facial bone using micromilling technology, which involves detailed milling of the scaffold. Milling is guided by computer tomography (CT) images of the pig’s jaw. Stem cells derived from adipose tissue of the minipigs were then collected and cultured within these scaffolds using a perfusion bioreactor. The bioreactor serves to provide an optimal environment for the growing tissue engineered graft. The system supports the exchange of nutrients and oxygen between the tissue and the surrounding environment. This work was the first to demonstrate the reconstruction of a large load bearing facial bone as well as the possibility of implanting the tissue engineered construct into the minipig animal model. epiBone is currently running Phase 1 and Phase 2 clinical trials that are expected to be completed in 2023 (Epibone, Inc., 2021). Cerapedics is another bone tissue engineering company, and they have developed a new bone graft called i-FACTOR. i-FACTOR is made of a material that combines the inorganic bone mineral hydroxyapatite with P-15, a polypeptide that can attach to osteogenic cells to stimulate bone formation (Lauweryns & Raskin, 2015). It synergistically works with the body’s natural healing process to stimulate bone formation, and ensures bone formation is restricted only to the injury site since the polypeptide is anchored to the surface of the hydroxyapatite (Science, n.d.). Originally this product was developed as a dental application, but there are several clinical trials that are testing its use for treating other conditions such as those that affect the spine.

Challenges Despite the advancements in bone tissue engineering, there are still no readily available

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clinical solutions for doctors to use to treat their patients. One reason for the lack of treatments is the increased number of variables in clinical settings. For example, in the emergency room, different patients can have varying health histories, causes of the incident, and affected locations on the body; bone tissue engineering treatment eligibility depends on all these factors. For companies like epiBone and Cerapedics, the road to obtaining FDA approval is a long, complex process that requires time to ensure medical products are safe. There are also challenges in designing optimal scaffolds that support bone tissue regeneration throughout the scaffold; this is an issue that is exacerbated by achieving less vascularization than desired (Amini et al., 2012). To circumvent this problem, scientists have been applying growth factors and anti-inflammatory agents to the scaffold to support a more seamless integration of the tissue engineered material to the patient’s body. Despite the many developments in the field, no routine clinical applications exist and most surgeons still use more traditional treatments for musculoskeletal injuries such as autografts and allografts (Quarto & Giannoni, 2016). Time also limits the usefulness of these therapies. Cells need time to grow in an organized manner and communicate with the cells around them to elicit the appropriate body responses that allow for the successful integration of the implanted tissue with the host tissue.

Concluding Remarks Bone tissue engineering holds potential in solving the shortcomings of current grafting procedures. It can be personalized or made highly compatible with the patient’s body with the combination of patient stem cells, thus reducing the probability of evoking an immunogenic response. It also avoids the problem of bone graft shortages. Future advancements in the field are necessary to bring these bone tissue engineered technologies to the clinical space. References Abbasi, N., Hamlet, S., Love, R. M., & Nguyen, N.-T. (2020). Porous scaffolds for bone regeneration. Journal of Science: Advanced Materials and Devices, 5(1), 1–9. https://doi.org/10.1016/j.jsamd.2020.01.007 Albrektsson, T., & Johansson, C. (2001). Osteoinduction, osteoconduction and osseointegration. European Spine Journal: Official Publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society, 10 Suppl 2, S96-101. https://doi.org/10.1007/ s005860100282

Amini, A. R., Laurencin, C. T., & Nukavarapu, S. P. (2012). Bone Tissue Engineering: Recent Advances and Challenges. Critical Reviews in Biomedical Engineering, 40(5), 363. Baldwin, P., Li, D. J., Auston, D. A., Mir, H. S., Yoon, R. S., & Koval, K. J. (2019). Autograft, Allograft, and Bone Graft Substitutes: Clinical Evidence and Indications for Use in the Setting of Orthopaedic Trauma Surgery. Journal of Orthopaedic Trauma, 33(4), 203–213. https://doi.org/10.1097/BOT.0000000000001420 Baroli, B. (2009). From natural bone grafts to tissue engineering therapeutics: Brainstorming on pharmaceutical formulative requirements and challenges. Journal of Pharmaceutical Sciences, 98(4), 1317–1375. https://doi.org/10.1002/jps.21528 Bhumiratana, S., Bernhard, J. C., Alfi, D. M., Yeager, K., Eton, R. E., Bova, J., Shah, F., Gimble, J. M., Lopez, M. J., Eisig, S. B., & Vunjak-Novakovic, G. (2016). Tissue-Engineered Autologous Grafts for Facial Bone Reconstruction. Science Translational Medicine, 8(343), 343ra83. https://doi.org/10.1126/scitranslmed.aad5904 Bosemark, P., Perdikouri, C., Pelkonen, M., Isaksson, H., & Tägil, M. (2015). The masquelet induced membrane technique with BMP and a synthetic scaffold can heal a rat femoral critical size defect. Journal of Orthopaedic Research, 33(4), 488–495. https://doi. org/10.1002/jor.22815 Briggs, A. M., Woolf, A. D., Dreinhöfer, K., Homb, N., Hoy, D. G., Kopansky-Giles, D., Åkesson, K., & March, L. (2018). Reducing the global burden of musculoskeletal conditions. Bulletin of the World Health Organization, 96(5), 366. https://doi.org/10.2471/BLT.17.204891 Creecy, A., Damrath, J. G., & Wallace, J. M. (2021). Control of Bone Matrix Properties by Osteocytes. Frontiers in Endocrinology, 0. https://doi. org/10.3389/fendo.2020.578477 Dimitriou, R., Jones, E., McGonagle, D., & Giannoudis, P. V. (2011). Bone regeneration: Current concepts and future directions. BMC Medicine, 9(1), 66. https://doi.org/10.1186/1741-7015-9-66 Dwivedi, R., Kumar, S., Pandey, R., Mahajan, A., Nandana, D., Katti, D. S., & Mehrotra, D. (2020). Polycaprolactone as biomaterial for bone scaffolds: Review of literature. Journal of Oral Biology and Craniofacial Research, 10(1), 381. https://doi.org/10.1016/j.jobcr.2019.10.003 Epibone, Inc. (2021). An Open-Label, First-in-Human, Single Intervention Study for Evaluation of EpiBone-CMF Engineered Living Bone Graft for Mandibular Ramus Reconstruction (Clinical Trial Registration No. NCT03678467). clinicaltrials.gov. https://clinicaltrials.gov/ ct2/show/NCT03678467 Fishman, J. A., Scobie, L., & Takeuchi, Y. (2012). Xenotransplantation-associated infectious risk: A WHO consultation. Xenotransplantation, 19(2), 72. https://doi.org/10.1111/j.1399-3089.2012.00693.x Goldberg, V. M., & Stevenson, S. (1987). Natural history of autografts and allografts. Clinical Orthopaedics and Related Research, 225, 7–16. Henkel, J., Woodruff, M. A., Epari, D. R., Steck, R., Glatt, V.,

Dickinson, I. C., Choong, P. F. M., Schuetz, M. A., & Hutmacher, D. W. (2013). Bone Regeneration Based on Tissue Engineering Conceptions—A 21st Century Perspective. Bone Research, 1(1), 216–248. https:// doi.org/10.4248/BR201303002 Hung, B. P., Naved, B. A., Nyberg, E. L., Dias, M., Holmes, C. A., Elisseeff, J. H., Dorafshar, A. H., & Grayson, W. L. (2016). Three-Dimensional Printing of Bone Extracellular Matrix for Craniofacial Regeneration. ACS Biomaterials Science & Engineering, 2(10), 1806. https://doi.org/10.1021/acsbiomaterials.6b00101 Kowalczuk, M. (2020). Intrinsically Biocompatible Polymer Systems. Polymers, 12(2). https://doi.org/10.3390/polym12020272 Lauweryns, P., & Raskin, Y. (2015). Prospective Analysis of a New Bone Graft in Lumbar Interbody Fusion: Results of a 2- Year Prospective Clinical and Radiological Study. International Journal of Spine Surgery, 9. https://doi.org/10.14444/2002 Malik, K. M., Beckerly, R., & Imani, F. (2018). Musculoskeletal Disorders a Universal Source of Pain and Disability Misunderstood and Mismanaged: A Critical Analysis Based on the U.S. Model of Care. Anesthesiology and Pain Medicine, 8(6). https://doi. org/10.5812/aapm.85532 Morrell, A. E., Robinson, S. T., Ke, H. Z., Holdsworth, G., & Guo, X. E. (2021). Osteocyte mechanosensing following short-term and long-term treatment with sclerostin antibody. Bone, 149, 115967. https:// doi.org/10.1016/j.bone.2021.115967 Neogi, T. (2013). The Epidemiology and Impact of Pain in Osteoarthritis. Osteoarthritis and Cartilage / OARS, Osteoarthritis Research Society, 21(9), 1145. https://doi.org/10.1016/j.joca.2013.03.018 Oryan, A., Alidadi, S., Moshiri, A., & Maffulli, N. (2014). Bone regenerative medicine: Classic options, novel strategies, and future directions. Journal of Orthopaedic Surgery and Research, 9(1), 18. https://doi. org/10.1186/1749-799X-9-18 Qu, H., Fu, H., Han, Z., & Sun, Y. (2019). Biomaterials for bone tissue engineering scaffolds: A review. RSC Advances, 9(45), 26252–26262. https:// doi.org/10.1039/C9RA05214C Quarto, R., & Giannoni, P. (2016). Bone Tissue Engineering: Past–Present–Future. In M. Gnecchi (Ed.), Mesenchymal Stem Cells: Methods and Protocols (pp. 21–33). Springer. https://doi.org/10.1007/978-14939-3584-0_2 Robinson, B. T., Metcalfe, D., Cuff, A. V., Pidgeon, T. E., Hewitt, K. J., Gibbs, V. N., Rossiter, D. J., & Griffin, X. L. (2018). Surgical techniques for autologous bone harvesting from the iliac crest in adults. The Cochrane Database of Systematic Reviews, 2018(4). https://doi. org/10.1002/14651858.CD011783.pub2 Science. (n.d.). Cerapedics. Retrieved August 23, 2021, from https://cerapedics.com/science Seong, J. M., Kim, B.-C., Park, J.-H., Kwon, I. K., Mantalaris, A., & Hwang, Y.-S. (2010). Stem cells in bone tissue engineering. Biomedical

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Materials, 5(6), 062001. https://doi.org/10.1088/17486041/5/6/062001 Sheen, J. R., & Garla, V. V. (2021). Fracture Healing Overview. In StatPearls [Internet]. StatPearls Publishing. https://www.ncbi.nlm.nih.gov/books/ NBK551678/ Sivakumar, R., Mohideen, M. G., Chidambaram, M., Vinoth, T., Singhi, P. K., & Somashekar, V. (2016). Management of Large Bone Defects in Diaphyseal Fractures by Induced Membrane Formation by Masquelet’s Technique. Journal of Orthopaedic Case Reports, 6(3), 59. https://doi.org/10.13107/jocr.2250-0685.508 swenson. (2013, June 25). NIST Announces New Scaffold Reference Material for Tissue Engineering Research [Text]. NIST. https://www.nist.gov/newsevents/news/2013/06/nist-announces-new-scaffold-referencematerial-tissue-engineering-research Willyard, C. (2016). Timeline: Regrowing the body. Nature, 540(7632), S50–S51. https://doi.org/10.1038/540S50a

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Challenges in the Clinical Treatment of Obese Cancer Patients BY ANAHITA KODALI ’23 Cover image: This graph represents the percentage of the population that was obese in OECD countries (an intergovernmental economic organization with 38 countries in its membership) plus the Czech Republic, Hungary, Mexico, Poland, and Slovakia as of 2005. Even 15 years ago, America had a significantly higher rate of obesity than the rest of the nations. This difference has persisted over time. Image Source: Wikimedia Commons

Introduction Cancer is one of the leading causes of death in the US and presents significant challenges to the healthcare systems of every country. In the US alone, there were about 1,806,590 new cancer cases in 2015 (“Cancer Statistics—National Cancer Institute,” 2015). In 2021, projected estimates for America have slightly increased – there will likely be about 1,898,160 new cancer cases (Siegel et al., 2021). Though the mortality of cancer in the US has decreased in the past 30 years due to advances in clinical and preventative medicine, its prevalence is on the rise and will probably continue to increase over the next several years (Weir et al., 2015). The increase in cancer prevalence may be somewhat puzzling at first glance, given that there have been many advances made in medicine over the past few years and that many risk factors, such as smoking, are becoming less common (“WHO launches new report on global tobacco use trends,” 2019). However, several factors outweigh these positive changes. The first is population growth – as the population grows, more people are alive to be afflicted with disease. Additionally, the world’s

population is aging. Between 1990 and 2019, the portion of the global population 65 years or older increased from 6% to 9%, and estimates suggest that by 2050, the proportion will have risen to 16% (United Nations et al., 2020). The risk of developing most cancers increases as people get older, though there are ways that people can modify their behaviors to decrease this likelihood (White et al., 2014). Finally, while the prevalence of many risk factors is decreasing, the prevalence of others is increasing; this includes obesity. Obesity refers to the condition in which patients have accumulated abnormally excessive amounts of fat in their adipose tissue. The fat distribution can be varied – some patients have abdominal obesity, in which there is significant fat accumulation in the waist and torso, while others have gynoid obesity, in which there is significant fat accumulation peripherally around the body. There are several health consequences of obesity (regardless of type). For one, it increases the chance of type II diabetes, hypertension, coronary heart disease, stroke, disability, and premature mortality (Ofei, 2005). It also increases risk of several types of cancer: esophageal adenocarcinoma, meningioma, DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 1: Insulin, a hormone produced by the pancreas, has been implicated in pathways connecting obesity and cancer. Image Source: Flickr

multiple myeloma, and cancers of the breast, colon, gallbladder, kidney, liver, ovaries, pancreas, prostate, thyroid, and uterus; this idea is further explored in the following section (CDC Press Releases, 2016). It is no coincidence that many of these cancers are extremely common. Of the 19.3 million new cancer cases in 2020, breast cancer was the most commonly diagnosed, making up 11.7% of all diagnoses. Additionally, 10.0% were colorectal cancer, 7.3% were prostate cancer, and 5.6% were stomach cancer (Sung et al., 2021). Worryingly, obesity rates are also on the rise. On a global scale, obesity has nearly tripled since 1975; as of 2016, more than 650 million adults were obese (“Obesity and overweight,” 2020). In the US, obesity is a particularly pressing problem. American obesity rates for adults have been rising since the 1980s; during the past decade alone, adult obesity rates grew from 33.7% to 39.6% (Hales et al., 2018). The rate of growth is not projected to slow in the coming years; some researchers estimate that by just 2030, nearly half of the American adult population will be obese, with the burden of disease falling heavily on women, Black adults, and low-income individuals (Ward et al., 2019). Given the significant health effects of both cancer and obesity and their projected rises in the coming years, it has become increasingly important to understand the relationships between the two diseases. This paper aims to review the effects of obesity on cancer patients by looking at how obesity physically affects the body of cancer patients and impacts their treatment.

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The Biological Relationship Between Obesity and Cancer As discussed previously, obesity increases the risk of several types of cancer. Though the correlation between the two is clear, researchers are still not completely sure how obesity leads to cancer. Since both cancer and obesity result from a wide range of physiological factors, the relationship between the two diseases has been particularly difficult to pinpoint. One such factor is sex – several obesityrelated cancers have sex-specific differences due to differences in hormonal levels. Race is another factor; for example, Black people have a significantly higher cancer risk in obesity as compared to Hispanic people, and Asian-Pacific populations have particularly high correlations between BMI and breast cancer (De Pergola & Silvestris, 2013). Given the complexities and variances in the relationship between the two diseases, it is clear that multiple biological mechanisms are at play. The three sources of interaction between cancer and obesity that have been well-studied and described in the literature are insulin and insulin-like growth factors (IGFs), sex hormones, and adipokines.

“Researchers have found that there is a direct correlation between the time since a person quit smoking and the benefits they reap from doing so."

Insulin is a peptide hormone that is produced by the pancreas; it regulates metabolism by promoting absorption of glucose from blood into the liver, fat, and muscle cells. IGFs are growth factors involved in several processes, including glucose metabolism and cell proliferation, differentiation, and survival. The insulinIGF pathway is complex and involves several components, including insulin, IGF1, IGF2, six receptors, and seven IGF-binding proteins 19

Figure 2: Adipose tissue produces adipokines, many of which have been significantly linked to increasing the risk of certain cancers . Image Source: Wikimedia Commons

"The pathway is triggered in the hyperinsulinemic condition, or the condition in which there is a significantly hgiher than normal amount of insulin in the blood. Hyperinsulinemia has been linked to obesity and obesity-related complications."

(IGFBPs) (LeRoith et al., 2011; Basen-Engquist & Chang, 2013). The pathway is triggered in the hyperinsulinemic condition, or the condition in which there is a significantly higher than normal amount of insulin in the blood. Hyperinsulinemia has been linked to obesity and obesity-related complications (Lee et al., 2014). There are a couple of mechanisms accounting for this relationship, the main one being that obesity can lead to insulin resistance, which is a state in which fat and muscle and liver cells do not respond well to insulin, and subsequently hyperinsulinemia. This occurs because adipose tissue (which obese individuals have an excess of) releases a number of proteins, one of which is retinol-binding protein-4 (RBF4). An increase in RBF4 can induce insulin resistance by reducing activation of the phosphatidylinositol3-OH kinase signaling pathway. The result is twofold: for one, the under-activation promotes insulin resistance, which causes the pancreas to secrete excess insulin into the blood stream, inducing hyperinsulinemia. Secondly, since this pathway is critical in modulation of cell growth, differentiation, proliferation, motility, and survival, disruptions to its signaling can directly result in tumor growth. RBF4 also enhances expression of phosphoenolpyruvate carboxykinase, an enzyme in the liver that functions in gluconeogenesis (the metabolic generation of glucose from non-carbohydrate carbon substrates). Changes in both the insulin and gluconeogenesis processes can result in insulin resistance and therefore an increase in blood insulin levels (Kahn et al., 2006). Though it is still not completely understood exactly how hyperinsulinemia is linked to cancer, one leading hypothesis is that an increase of blood

insulin leads to a decrease in IGFBPs. This, in turn, causes a change in the cell environment that promotes tumor growth. Additionally, the decrease in IGFBPs increases the amount of IGF1, which plays an important role in childhood growth and adulthood anabolism (the process of producing complex molecules from simpler ones). IGF1 increases have been associated with increased risk of certain cancers, including breast and prostate cancers; for older men, higher IGF1 levels also increase the risk of death from cancer. The mechanisms underlying IGF1’s relationship to cancer risk are still being explored (BasenEngquist & Chang, 2013). Sex hormones, particularly estrogens, also play a role in linking obesity and cancer; the role of estrogens is especially significant for hormonedependent cancers (including breast, endometrial, ovarian, prostate, and uterine cancers). Increases in weight cause increases in the levels of circulating estrogen, which has several implications (De Pergola & Silvestris, 2013). When estrogens bind to estrogen receptors, they activate intracellular pathways that stimulate cell division. Estrogens also interact with IGFs to inhibit apoptosis; combined, these significantly increase the rate of tumor growth (Basen-Engquist & Chang, 2013). Finally, estrogens, along with free radicals (highly reactive and unstable molecular species), have been known to induce DNA damage, genetic instability, and gene mutations, all of which can induce and promote tumor growth (De Pergola & Silvestris, 2013). Adipokines, or hormones produced by adipose tissue, are also a significant factor in cancer. Obesity results in an excess of adipose tissue

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found throughout the body. Thus, in the obese condition, there is a significantly high number of adipokines in the blood (Zorena et al., 2020). Perhaps the most well-known adipokine is leptin, a hormone involved in energy balance regulation via hunger inhibition. There are several reasons for this: leptin inhibits apoptosis and promotes cell division, inflammation, and development of blood vessels, all of which work in tandem to cause tumor proliferation (De Pergola & Silvestris, 2013). The role of leptin has been extensively studied in breast cancer, though increased blood serum levels of leptin have also been associated with increased risk of colon and prostate cancers (De Pergola & Silvestris, 2013; Basen-Engquist & Chang, 2013). Leptin is particularly significant in the onset and growth of tumors in breast cancer because breast epithelial cells contain leptin receptors, and leptin increases estrogen production. Interestingly, adiponectin, the most abundant adipokine, plays a protective role against cancer; the greater circulating levels of adiponectin caused by obesity are inversely related to cancer risk. There are two main reasons for this. The first is that it enhances insulin sensitivity, lowering the effects of insulin resistance and hyperinsulinemia. Additionally, it activates the AMPK pathway, which regulates energy homeostasis by inducing glucose and fatty uptake by cells (De Pergola & Silvestris, 2013). The AMPK pathway inhibits virtually all of the anabolic pathways in the body that promote cell growth, so increased activation of the pathway through increased circulation of adiponectin reduces cancer growth (Li et al., 2015). These competing effects are complex and need to be studied in more detail to be better understood. In addition to insulin, sex hormones, and adipokines, several other factors relate obesity to tumor growth. One is that obesity tends to generate chronic inflammation of adipose tissue. This results in excessive adipose tissue expansion, which in turn causes an increase in cancer-related adipocytes and adipose-derived stem cells. Both will enter the tumor microenvironment and execute protumor action (Deng et al., 2016). Additionally, obesity may reduce the body’s antioxidant activities (activities that limit the number of free radicals in the body), thus increasing oxidative stress, which may cause DNA damage that can increase cancer risk. In line with this genetic effect, there are certain genetic predispositions to obesity that may also predispose development of cancer (De Pergola & Silvestris, 2013). As more research is done on obesity and cancer, it is more than likely that more links between the two will be found.

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In addition to cancer initiation and growth, obesity is related to worsened quality of life for cancer patients and increased mortality risk. In a study done on breast cancer patients, obesity was related to worse tumor characteristics in obese individuals compared to normal-weight controls. Obese patients’ tumors were typically diagnosed at later stages, were larger, and were more likely to spread than those of normal-weight individuals; additionally, lymph nodes were more likely to contain cancer. In turn, obesity was related to a higher likelihood that the cancers were fatal, accounting for obesity-related risks of mortality (Blair et al., 2019). Though more studies need to be done on the direct impacts of obesity on other types of obesity-related cancers, obesity tends to elevate mortality rates for all comorbidities (Abdelaal et al., 2017).

The Effect of Obesity on the Therapeutic Approach In addition to the relationship between obesity and the onset, progression, symptoms, and mortality rates of cancer, researchers are working to understand the role that obesity may play in the clinical treatment of cancer. Three common types of cancer treatment are surgery, radiation therapy, and chemotherapy; often, a combination of the three is used. For patients who undergo cancerremoval surgery, the data on the correlation between obesity and outcome is somewhat unclear. In terms of mortality and major complications, there seems to be no association with BMI. However, there is a significant increase in minor surgical complications correlated with an increase in BMI; these can include infection and wound dehiscence (wounds splitting open). Lymphedema, or excess fluid collection in tissues, is also a major issue after surgery for obese cancer patients, and issues with wounds and fluid buildup are due to a variety of reasons, including increased wound tension and tissue pressure and decreases in vascularity around adipose tissue. Though minor complications may not be as devastating as major complications, they can result in increased surgery time and increased blood loss, which can lead to longer recovery times, greater costs for patients, and delays in additional cancer treatments (like chemotherapy and radiation). Additionally, obese cancer patients have a higher risk of having surgical margins that are positive for cancer cells; in other words, when the doctors tries to cut away the cancer, they leave cancerous cells behind. This results in poorer outcomes and higher chances of cancer recurrence (Ross et al., 2019).

“Obese patients’ tumors were typically diagnosed at later stages, were larger, and were more likely to spread than those of normalweight individuals; additionally, lymph nodes were more likely to contain cancer."

"Obese patients who undergo chemotherapy typically have worse outcomes than nonobese patients. The main reason for this may be issues in properly dosing patients."

Figure 3: CT visualization of cancer can be complicated by obesity.

Patient obesity also impacts radiation therapy practice. For one, it can be difficult to properly image an obese patient in the computed tomography (CT) scanner before the radiation is applied; CT scans are necessary to visualize the cancer so that the radiation beams can be aligned correctly. Once the cancer has been visualized, it can be difficult to precisely target radiation beams on obese patients, both because tattooing the patient (to properly line up the beams) can be challenging and because moving the patient into the proper position in the radiation therapy treatment unit is difficult (Winters & Poole, 2020). These issues can all lead to inferior treatment outcomes and reduce the efficacy of treatment (Ross et al., 2019). Furthermore, for patients with certain cancers, including cervical and endometrial, obesity may increase radiotherapyinduced toxicity posttreatment through mechanisms still being explored. Radiotherapyinduced toxicity cause adverse effects in patients (Ross et al., 2019; Dandapani et al., 2015). Some of these effects are short-term, like inflammation of the gut and mouth, while longer term effects, including fibrosis, are largely irreversible (De

can have a significant impact on the efficacy of chemotherapy. Patient dosing is calculated using body surface area (BSA) in adult patients. It is critically important that all patients receive a dosage based on their BSA; however, up to 40% of obese patients may receive a smaller dosage that is based on a doctor’s calculation using an arbitrarily capped BSA in order to reduce chemotherapy-related toxicity, as the decision up to the doctor’s own judgement (Ross et al., 2019). This reduction in dosing is correlated with reduced overall survival (OS) and progressionfree survival (PFS); indeed, in studies done with gynecological cancer patients, properly dosing patients using their BSA found that there was no difference in OS or PFS between obese and nonobese patients for most chemotherapy drugs, demonstrating that proper dosage intensity for obese patients improves outcomes (Ross et al., 2019; Horowitz & Wright, 2015).

Ruysscher et al., 2019).

in weaker patient-doctor relationships, which in turn can make patients less likely to adhere to medication plans and can decrease the effectiveness of behavior modification therapies (Gudzune et al., 2013). There is a consensus among medical staff that obese cancer patients may be unintentionally treated with a lack of dignity. For example, radiotherapy technicians have reported that patients seem to be conscious and apologetic of their bodies while undergoing imaging; they also report feeling frustrated with obese patients, even on first visits, due to the difficulty of treating

This brings up an important issue: patient-doctor relations. Researchers have found that generally, doctors build lower levels of emotional rapport with overweight and obese patients. This results

Image Source: Flickr

Obese patients who undergo chemotherapy typically have worse outcomes than non-obese patients. The main reason for this may be issues in properly dosing patients. Obese patients can have issues with metabolic regulation and with pharmacokinetics (the movement of drugs throughout the body), which can lower the efficacy of chemotherapy (Horowitz & Wright, 2015). Perhaps more significantly, doctors’ choices in how to dose obese patients

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obese cancer patients (Winters & Poole, 2020). Thus, moving forward, it is important for medical staff treating obese patients to be mindful of not just the therapeutic challenges that obesity can cause in cancer treatment but of their demeanor towards cancer patients. The patient-doctor relationship in particular is especially powerful in patient outcomes – more positive patient-doctor relationships lead to greater patient satisfaction, better patient understanding of their disease, and higher patient compliance with treatment (“The Importance of Physician-Patient Relationships,” 2019). Each of these factors may improve the efficacy of cancer treatment and may lead to better OS and PFS in obese cancer patients.

Management of Obesity During and After Cancer Treatment As discussed previously, obesity is caused by (and causes) dysregulation of several bodily processes, many of which are still not entirely understood. One of the most widely studied theories has been set-point theory, which argues that the body’s natural weight is maintained in a stable range called the set-point through various homeostatic mechanisms and feedback loops; the set-point is thought to be strongly influenced by genetics (Müller et al., 2018). Especially important is that the body seems to be much more efficient at preventing weight loss than weight gain (Farias et al., 2011). This model explains why many obese patients are resistant to weight loss just by caloric restriction. As such, many treatments for obesity try to influence the body’s natural weight set-point in order to allow the patient to lose weight sustainably. However, for obese cancer patients, treatment focuses on both cancer and obesity. Interventions for obesity during and after cancer treatment are complicated, as doctors need to make sure that they are not exacerbating the patient’s cancerrelated symptoms. There are several areas of intervention for obese patients. Perhaps the most well studied currently are dietary interventions, which are critical to managing the weight of all obese patients; it becomes particularly important in the context of cancer treatment because cancer patients require nutritional management to avoid excessive weight loss. Adequate nutrition for all cancer patients – both normal-weight and obese – maximizes efficacy of treatment and reduces negative side effects. Generally, nutrition is not well managed for cancer patients, further emphasizing the special attention needed for obese cancer patients (Ravasco, 2019). During cancer treatment, weight loss of obese patients is associated with malnutrition; thus, it is critical to maintain lean mass while in treatment so in order

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to preserve patient functionality and quality of life, both of which may mitigate the side effects of cancer treatment. Diets should lower “empty” calories (calories from saturated fats and refined sugars) and emphasize protein from dairy, fish, eggs, meat, and legumes. After treatment, dietary intervention is still critical, especially because patients are at higher risk for obesity after recovering from one illness (Pérez-Segura et al., 2017). Less research has been done on other interventions. One important area may be physical activity. It is known that regular physical activity has a protective effect against several types of cancer (Schrack et al., 2017). Additionally, after cancer treatment, regular exercise can help alleviate several physical and mental health issues, including fatigue, anxiety, and depression (Schmitz et al., 2019). For obese cancer patients especially, regular physical activity during and after treatment can lower recurrence of certain cancer and increase survivability; additionally, it can increase muscle mass and strength, lower fat, and improve self-esteem. As such, emphasizing the importance of physical activity for obese cancer patients may significantly improve outcomes, and in the coming years, it is likely that doctors will place greater significance on regular exercise as a part of cancer treatment for all cancer patients. Additionally, bariatric surgery after cancer treatment is a viable option for many cancer patients once the patient is cancer free. Finally, providing strong therapeutic support for obese cancer patients can improve patients emotional and physical states and improve quality of life both during and after treatment (Pérez-Segura et al., 2017).

"more positive patientdoctor relationships lead to greater patient satisfaction, better patient understanding of their disease, and higher patient compliance with treatment"

Conclusions Cancer treatment is difficult in the best of circumstances. For obese cancer patients, treatment can be variable; as such, the patients require special care and attention from medical staff. As the current rate of obesity, both in the US and around the world, continues to grow, it is likely that the number of obese cancer patients will rise, too. Thus, it is important for doctors to learn how to effectively treat obese cancer patients and to develop interventions for obesity both during and after treatment. As treatment plans and interventions are better researched, patient outcomes for obese cancer patients will hopefully improve. References Abdelaal, M., le Roux, C. W., & Docherty, N. G. (2017). Morbidity and mortality associated with obesity. Annals of

Translational Medicine, 5(7), 161–161. https://doi.org/10.21037/ atm.2017.03.107 Basen-Engquist, K., & Chang, M. (2011). Obesity and Cancer Risk: Recent Review and Evidence. Current Oncology Reports, 13(1), 71–76. https://doi.org/10.1007/s11912-010-0139-7 Blair, C. K., Wiggins, C. L., Nibbe, A. M., Storlie, C. B., Prossnitz, E. R., Royce, M., Lomo, L. C., & Hill, D. A. (2019). Obesity and survival among a cohort of breast cancer patients is partially mediated by tumor characteristics. Npj Breast Cancer, 5(1), 33. https://doi.org/10.1038/s41523-019-0128-4 Broom, A., Kenny, K., Page, A., Cort, N., Lipp, E. S., Tan, A. C., Ashley, D. M., Walsh, K. M., & Khasraw, M. (2020). The Paradoxical Effects of COVID-19 on Cancer Care: Current Context and Potential Lasting Impacts. Clinical Cancer Research, 26(22), 5809–5813. https://doi.org/10.1158/10780432.CCR-20-2989 Cancer Statistics—National Cancer Institute (nciglobal,ncienterprise). (2015, April 2). [CgvArticle]. https:// www.cancer.gov/about-cancer/understanding/statistics CDC Press Releases. (2016, January 1). CDC. https://www.cdc. gov/media/releases/2017/p1003-vs-cancer-obesity.html Dandapani, S. V., Zhang, Y., Jennelle, R., & Lin, Y. G. (2015). Radiation-Associated Toxicities in Obese Women with Endometrial Cancer: More Than Just BMI? The Scientific World Journal, 2015, 1–6. https://doi.org/10.1155/2015/483208 De Pergola, G., & Silvestris, F. (2013). Obesity as a Major Risk Factor for Cancer. Journal of Obesity, 2013. https://doi. org/10.1155/2013/291546 De Ruysscher, D., Niedermann, G., Burnet, N. G., Siva, S., Lee, A. W. M., & Hegi-Johnson, F. (2019). Radiotherapy toxicity. Nature Reviews Disease Primers, 5(1), 13. https://doi. org/10.1038/s41572-019-0064-5 Deng, T., Lyon, C. J., Bergin, S., Caligiuri, M. A., & Hsueh, W. A. (2016). Obesity, Inflammation, and Cancer. Annual Review of Pathology: Mechanisms of Disease, 11(1), 421–449. https://doi. org/10.1146/annurev-pathol-012615-044359 Farias, M. M., Cuevas, A. M., & Rodriguez, F. (2011). SetPoint Theory and Obesity. Metabolic Syndrome and Related Disorders, 9(2), 85–89. https://doi.org/10.1089/met.2010.0090 Gudzune, K. A., Beach, M. C., Roter, D. L., & Cooper, L. A. (2013). Physicians build less rapport with obese patients: Rapport Building Obesity. Obesity, 21(10), 2146–2152. https:// doi.org/10.1002/oby.20384 Hales, C. M., Fryar, C. D., Carroll, M. D., Freedman, D. S., & Ogden, C. L. (2018). Trends in Obesity and Severe Obesity Prevalence in US Youth and Adults by Sex and Age, 2007-2008 to 2015-2016. JAMA, 319(16), 1723. https://doi.org/10.1001/ jama.2018.3060 Horowitz, N. S., & Wright, A. A. (2015). Impact of obesity on chemotherapy management and outcomes in women with gynecologic malignancies. Gynecologic Oncology, 138(1), 201–206. https://doi.org/10.1016/j.ygyno.2015.04.002 Kahn, S. E., Hull, R. L., & Utzschneider, K. M. (2006). Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature, 444(7121), 840–846. https://doi.org/10.1038/ nature05482

Lee, Y., Berglund, E. D., Yu, X., Wang, M.-Y., Evans, M. R., Scherer, P. E., Holland, W. L., Charron, M. J., Roth, M. G., & Unger, R. H. (2014). Hyperglycemia in rodent models of type 2 diabetes requires insulin-resistant alpha cells. Proceedings of the National Academy of Sciences, 111(36), 13217–13222. https:// doi.org/10.1073/pnas.1409638111 LeRoith, D., Scheinman, E. J., & Bitton-Worms, K. (2011). The Role of Insulin and Insulin-like Growth Factors in the Increased Risk of Cancer in Diabetes. Rambam Maimonides Medical Journal, 2(2). https://doi.org/10.5041/RMMJ.10043 Li, W., Saud, S. M., Young, M. R., Chen, G., & Hua, B. (2015). Targeting AMPK for cancer prevention and treatment. Oncotarget, 6(10), 7365–7378. https://doi.org/10.18632/ oncotarget.3629 Müller, M. J., Geisler, C., Heymsfield, S. B., & Bosy-Westphal, A. (2018). Recent advances in understanding body weight homeostasis in humans. F1000Research, 7, 1025. https://doi. org/10.12688/f1000research.14151.1 Obesity and overweight. (n.d.). Retrieved March 26, 2021, from https://www.who.int/news-room/fact-sheets/detail/obesity-andoverweight Ofei, F. (2005). Obesity—A Preventable Disease. Ghana Medical Journal, 39(3), 98–101. Pérez-Segura, P., Palacio, J. E., Vázquez, L., Monereo, S., de las Peñas, R., de Icaya, P. M., Grávalos, C., Lecube, A., Blasco, A., García-Almeida, J. M., Barneto, I., & Goday, A. (2017). Peculiarities of the obese patient with cancer: A national consensus statement by the Spanish Society for the Study of Obesity and the Spanish Society of Medical Oncology. Clinical and Translational Oncology, 19(6), 682–694. https://doi. org/10.1007/s12094-016-1601-2 Ravasco, P. (2019). Nutrition in Cancer Patients. Journal of Clinical Medicine, 8(8), 1211. https://doi.org/10.3390/ jcm8081211 Ross, K. H., Gogineni, K., Subhedar, P. D., Lin, J. Y., & McCullough, L. E. (2019). Obesity and cancer treatment efficacy: Existing challenges and opportunities. Cancer, 125(10), 1588–1592. https://doi.org/10.1002/cncr.31976 Schmitz, K. H., Campbell, A. M., Stuiver, M. M., Pinto, B. M., Schwartz, A. L., Morris, G. S., Ligibel, J. A., Cheville, A., Galvão, D. A., Alfano, C. M., Patel, A. V., Hue, T., Gerber, L. H., Sallis, R., Gusani, N. J., Stout, N. L., Chan, L., Flowers, F., Doyle, C., … Matthews, C. E. (2019). Exercise is medicine in oncology: Engaging clinicians to help patients move through cancer. CA: A Cancer Journal for Clinicians, 69(6), 468–484. https://doi. org/10.3322/caac.21579 Schrack, J. A., Gresham, G., & Wanigatunga, A. A. (2017). Understanding physical activity in cancer patients and survivors: New methodology, new challenges, and new opportunities. Molecular Case Studies, 3(4), a001933. https:// doi.org/10.1101/mcs.a001933 Siegel, R. L., Miller, K. D., Fuchs, H. E., & Jemal, A. (2021). Cancer Statistics, 2021. CA: A Cancer Journal for Clinicians, 71(1), 7–33. https://doi.org/10.3322/caac.21654 Sung, H., Ferlay, J., Siegel, R. L., Laversanne, M., Soerjomataram, I., Jemal, A., & Bray, F. (n.d.). Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: A Cancer Journal for Clinicians, n/a(n/a). https://doi.org/10.3322/caac.21660

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The Importance of Physician-Patient Relationships Communication and Trust in Health Care. (2019, March 11). Duke Personalized Health Care. https://dukepersonalizedhealth. org/2019/03/the-importance-of-physician-patient-relationshipscommunication-and-trust-in-health-care/ United Nations, Department of Economic and Social Affairs, & Population Division. (2020). World population ageing, 2019 highlights. Ward, Z. J., Bleich, S. N., Cradock, A. L., Barrett, J. L., Giles, C. M., Flax, C., Long, M. W., & Gortmaker, S. L. (2019). Projected U.S. State-Level Prevalence of Adult Obesity and Severe Obesity. New England Journal of Medicine, 381(25), 2440–2450. https:// doi.org/10.1056/NEJMsa1909301 Weir, H. K., Thompson, T. D., Soman, A., Møller, B., & Leadbetter, S. (2015). The Past, Present, and Future of Cancer Incidence in the United States: 1975 Through 2020. Cancer, 121(11), 1827–1837. https://doi.org/10.1002/cncr.29258 White, M. C., Holman, D. M., Boehm, J. E., Peipins, L. A., Grossman, M., & Henley, S. J. (2014). Age and Cancer Risk. American Journal of Preventive Medicine, 46(3 0 1), S7-15. https://doi.org/10.1016/j.amepre.2013.10.029 WHO launches new report on global tobacco use trends. (n.d.). Retrieved March 24, 2021, from https://www.who.int/news/ item/19-12-2019-who-launches-new-report-on-global-tobaccouse-trends Winters, E., & Poole, C. (2020). Challenges and impact of patient obesity in radiation therapy practice. Radiography, 26(3), e158–e163. https://doi.org/10.1016/j.radi.2020.01.005 Zorena, K., Jachimowicz-Duda, O., Ślęzak, D., Robakowska, M., & Mrugacz, M. (2020). Adipokines and Obesity. Potential Link to Metabolic Disorders and Chronic Complications. International Journal of Molecular Sciences, 21(10), 3570. https://doi.org/10.3390/ijms21103570

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Addressing the Plastic Waste Problem with Chemical Upcycling BY ANNA KÖLLN '22 Cover image: A display of plastic bottles. Image Source: Tony Webster, Wikimedia Commons

The Plastic Waste Problem Since their development for large-scale production around 1950, plastics have become a vital part of daily life and are used in a wide spectrum of applications, including food packaging, healthcare, and construction. Due to the widespread usage of plastics, an estimated 8300 million metric tons (Mt) of virgin plastics have been produced in total as of 2017 (Figure 1). Many plastic products are designed for single use, so a significant proportion enter the waste stream shortly after their consumption, resulting in the generation of a cumulative 6300 Mt of plastic waste (Geyer et al., 2017). A large amount of plastic waste is mismanaged, meaning it is openly incinerated, discarded at a dumpsite, or allowed to enter terrestrial or aquatic ecosystems as pollution (Lau et al., 2020). In 2016, it is estimated that 19-23 Mt of plastic waste entered aquatic ecosystems, a figure that could more than triple by 2030 under business-as-usual scenarios (Borrelle et al., 2020). Because the majority of these plastics are not biodegradable and can be harmful to animals when ingested, their entry

to these aquatic environments causes extreme detriment. In order to tackle this global problem, a multifaceted approach involving both pre- and post-consumption mitigation strategies will be necessary (Lau et al., 2020). Structurally, plastics are polymeric materials made primarily of carbon, with some varieties containing other elements such as oxygen or chlorine (Figure 2). The stability of carbon-carbon bonds makes plastics durable but difficult to break down, rendering them nonbiodegradable. Their repetitive structure also results in thousands of virtually identical chemical bonds in a single macromolecule, making it challenging to differentiate between specific bonds. Mechanical recycling, the conventional method for repurposing plastic waste, involves the subsequent separation, sorting, washing, grinding, and pelletizing of plasticsfor reuse based on their designated recycling code. The thermal and mechanical stressors present during a plastic’s lifetime and throughout the mechanical recycling process causes the polymers to undergo DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 1: Cumulative global plastic production from 1950 to 2015. Image Source: Hannah Ritchie and Max Roser, Our World in Data

breakage and branching, ultimately degrading the materials and their physical properties. This doesn’t necessarily mean recycled plastics can only be used in “lower–value” applications; for example, polyethylene terephthalate (PET) collected from bottles can be converted to textile fibers (Ragaert et al., 2017). However, the degradation of the plastics ultimately limits their applications, and they will eventually reenter the waste stream once their uses have been exhausted. Of all plastics ever produced, only 9% have been recycled (Geyer et al., 2017). However, despite the logistical and economic challenges associated with collecting and recycling plastic waste, it is an increasingly economically viable alternative to virgin plastic production and landfill waste disposal. Since virgin plastics are produced directly from fossil fuels, their cost of production fluctuates based on oil prices, which have ultimately been increasing over time (García, 2016). Additionally, recycling is less energy intensive than virgin plastic production, and it is estimated that recycling one-third of plastic waste in the United States could reduce overall energy consumption by 1% (Britt et al., 2019). While mechanical recycling will certainly play an important role in the future in mitigating plastic waste, it is still flawed in its current state as it yields a product of decreased quality (Lau et al., 2020). Thus, other strategies must be developed in addition to current recycling systems to divert more plastics from waste streams and the environment.

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One alternative strategy for mitigating plastic waste is chemical upcycling, or the conversion of plastics into other products. Because it can yield value-added products, upcycling provides an economically attractive route to a circular plastic life cycle (Tennakoon et al., 2020). Chemical upcycling can be used to break down plastic polymers into a wide variety of carbon-based products. A number of upcycling methods have been developed, with the most common being pyrolysis, solvolysis, and hydrogenolysis. Pyrolysis uses heat to deconstruct plastic polymers. Although it is currently the most common upcycling method, it is not a controlled process and results in a wide distribution of products (C. Kosloski-Oh et al., 2021). In solvolysis, or chemolysis, a chemical solvent such as water or methanol is used to cleave the bonds within the plastic polymer. This method has been most extensively studied for the upcycling of PET, which can be converted into a variety of resins and chemical precursors (Ragaert et al., 2017). Hydrogenolysis, or the cleavage of carbon-carbon or carbon-heteroatom bonds by molecular hydrogen, can be used to deconstruct the long polymer chains of plastics into smaller products. Ideally, catalytic hydrogenolysis selectively targets specific C-C bonds, resulting in as narrow of a product distribution as possible, so that the products require minimal post-reaction separation (Britt et al., 2019). Overall, all of these upcycling methods can be useful, and can be selected and optimized based on the plastic precursors and desired products.

"recycling is less energy intensive than virgin plastic production, and it is estimated that recycling one-third of plastic waste in the United States could reduce overall energy consumption by 1%"

Figure 2: Types of plastic by recycling code, name, and monomeric structure. Image Source: Created by author in ChemDraw and Microsoft PowerPoint

"Some upcycling reactions require catalysts that can withstand especially harsh reaction conditions, such as the breakdown of polyvinyl chloride (PVC), which generates corrosive hydrochloric acid"

In recent years, researchers have shown that plastics can be converted into many different industrially relevant products. For example, Pol used pyrolysis to convert polyethylene (PE) and polystyrene (PS) into carbon microspheres, which could potentially be used in colorants, batteries, and tires (2010). Carbon nanotubes (CNTs) are another highly attractive product, as they are currently being developed in many applications such as battery electrodes and sensor devices. CNT synthesis has been investigated by pyrolyzing all varieties of plastic listed in Figure 2 (Zhuo & Levendis, 2014). Alkylaromatics, chemicals comprised of a benzene ring with alkyl substituents, are another advantageous product, due to their uses as surfactants, lubricants, and insulating oils. Researchers have shown that PE can be converted to alkylaromatic products via tandem hydrogenolysis and aromatization reactions (Zhang et al., 2020). Celik et al. demonstrated the conversion via hydrogenolysis of PE to “high–quality liquids” (HQLs), including motor oil, lubricants, and waxes, as shown in Figure 3 (2019). These are just a few examples of the many useful carbon-based products that can be derived from plastics.

Developments in Catalysts In recent years, researchers have put significant effort into developing catalysts to break down plastics more effectively. For example, catalysts can be designed to lower the temperature for pyrolysis, reduce the activation energy for hydrogenolysis, or facilitate more selective breakdown of polymers into desirable products. The catalysts are ideally made up of inexpensive materials that are stable at high temperatures and when exposed to contaminants that may be present in plastic waste (García, 2016). Some upcycling reactions require catalysts that can withstand especially harsh reaction conditions, such as the breakdown of polyvinyl chloride (PVC), which generates corrosive hydrochloric acid (Britt et al., 2019). A variety of materials can serve as catalysts for the various upcycling methods. For pyrolysis reactions, acid catalysts such as silica or zeolites are commonly used to facilitate the catalytic cracking of plastic polymers into smaller components. Some pyrolysis methods also incorporate active metal sites into the acid catalyst materials. In hydrogenolysis, supported metal nanoparticles such as platinum, iridium, and rhodium have been shown to be

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effective in splicing plastic polymeric chains (Britt et al., 2019). Although these metals are rare and expensive, the use of nanoparticle or even single-atom constructions maximizes the peratom reactivity of the catalysts.

and reducing plastic consumption, chemical upcycling can help transform our harmful openloop plastic cycle for a sustainable future.

Particular attention has been given to the catalytic breakdown of PE, as it accounts for 36% of plastic production and is used in many single-use packaging applications (Geyer et al., 2017). Celik et al. utilized platinum nanoparticles supported on SrTiO3 nanocuboids to deconstruct PE via hydrogenolysis (Figure 3). With this catalyst, the PE chains were found to selectively bind to the platinum sites rather than the SrTiO3 support material. It was hypothesized that the ordering and distance between the platinum particles could influence the size of the reaction products (Celik et al., 2019). This finding is highly promising since it shows that catalysts could be designed to

Borrelle, S. B., Ringma, J., Law, K. L., Monnahan, C. C., Lebreton, L., McGivern, A., Murphy, E., Jambeck, J., Leonard, G. H., Hilleary, M. A., Eriksen, M., Possingham, H. P., De Frond, H., Gerber, L. R., Polidoro, B., Tahir, A., Bernard, M., Mallos, N., Barnes, M., & Rochman, C. M. (2020). Predicted growth in plastic waste exceeds efforts to mitigate plastic pollution. Science, 369(6510), 1515–1518. https://doi.org/10.1126/science. aba3656

References

Britt, P. F., Coates, G. W., Winey, K. I., Byers, J., Chen, E., Coughlin, B., Ellison, C., Garcia, J., Goldman, A., Guzman, J., Hartwig, J., Helms, B., Huber, G., Jenks, C., Martin, J., McCann, M., Miller, S., O’Neill, H., Sadow, A., … Waymouth, R. (2019). Report of the Basic Energy Sciences Roundtable on Chemical Upcycling of Polymers. USDOE Office of Science (SC) (United States). https://doi.org/10.2172/1616517 Celik, G., Kennedy, R. M., Hackler, R. A., Ferrandon, M., Figure 3: Scheme of the conversin of PE to HQLs via hydrogenolysis.

cleave plastic polymers into products of a certain size. Tennakoon et al. took this concept further with a complex catalyst constructed of platinum nanoparticles supported on a silica core and encapsulated by a mesoporous silica shell. This catalyst was shown to selectively break down PE into fragments in a manner inspired by the enzymatic breakdown of biochemical polymers (2020). These examples demonstrate the promise of chemical research in developing multifaceted catalysts for plastic upcycling, especially with the ever-increasing synthetic control at the nanoscale.

Conclusion The sheer amount of plastic waste produced by humans poses a significant threat to ecosystems and the environment. Although conventional recycling methods play an important role in repurposing plastic from the waste stream, additional methods are needed to holistically confront this problem. One such method is chemical upcycling, which breaks down plastic polymers into valuable products such as carbon nanomaterials, oils, lubricants, and waxes. Recently, scientists have developed several promising catalysts to make chemical upcycling reactions more efficient and selective. Together, with other strategies such as improving recycling systems, substituting other materials for plastics,

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Tennakoon, A., Patnaik, S., LaPointe, A. M., Ammal, S. C., Heyden, A., Perras, F. A., Pruski, M., Scott, S. L., Poeppelmeier, K. R., Sadow, A. D., & Delferro, M. (2019). Upcycling SingleUse Polyethylene into High-Quality Liquid Products. ACS Central Science, 5(11), 1795–1803. https://doi.org/10.1021/ acscentsci.9b00722

Image Source: Celik, G., Kennedy, R. M., Hackler, R. A., Ferrandon, M., Tennakoon, A., Patnaik, S., LaPointe, A. M., Ammal, S. C., Heyden, A., Perras, F. A., Pruski, M., Scott, S. L., Poeppelmeier, K. R., Sadow, A. D., & Delferro, M. (2019). Upcycling Single-Use Polyethylene into High-Quality Liquid Products. ACS Central Science, 5(11), 1795–1803. https://doi.org/10.1021/ acscentsci.9b00722

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Healthcare Inequality for Unauthorized Immigrants BY ANUSHKA BHATIA '24 Cover image: People using mobile phones. Mobile computing and communication is one of the modern technologies driving innovation in developing and least-developed countries. Image Source: Wikimedia Commons

An Introduction to the Impact of Unauthorized Status on Health As immigration into the United States increases, so does the number of unauthorized immigrants. Immigrants make up over 43.2 million of the U.S. population, and over 10.7 million have unauthorized status (Fortuny et al., 2010). Over the last two decades, there has been an increased focus on immigration status, with Immigration and Customs Enforcement (ICE) officials heavily focused on enacting workplace raids, detention, and deportation. 77.1% of likely undocumented immigrants reported deportation fears on average from 2007 to 2018 (Asad, 2020). Immigrant families are already at a higher risk for health issues due to the inaccessibility of health insurance, but other factors resulting from their undocumented status play into their exacerbated risk such as lack of knowledge, confusion over regulations, and discrimination (Karp et al., 2007). The tension surrounding immigration status

has created an anxious climate for unauthorized immigrants, with fears of deportation manifesting themselves both physically and mentally. A study of providers who care for unauthorized immigrants found that over 40% of medical practitioners reported negative health effects of ICE activities on their unauthorized immigrant patients. This pervasive fear of ICE leads to healthcare avoidance, stress, and anxiety, which all contribute to mental health issues and physical manifestations of stress (Hacker et al., 2012). However, ICE is not the only factor that may have negative effects on physical health. Unauthorized immigrants often work jobs with poor conditions, leading to injuries or long-term health issues like joint pain or chemical inhalation. They may also have to switch jobs often or face long commutes to get to work, increasing the amount of strain on their body. The fatality rate of agricultural farm workers, 55 percent of which are immigrants (“Farm Labor”, USDA), is over five times that of all workers, and conditions like chronic pain, heart disease, and many cancers are higher in this DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 1: A world map showing the distribution of countries classified as developed, developing, and least-developed. Developed countries fall under the “advanced economies” and “in transition” labels (dark blue and light blue), developing countries fall under the “less developed,” (orange) and leastdeveloped economies fall under the “least developed” (red) labels respectively. Image Source: Wikimedia Commons

population (Slesinger, 1992). For example, studies on agricultural workers in California reported rates of musculoskeletal disorder incidence ranking among the highest risk industries as well as 100 times greater than rates suggested by the National Institute for Occupational Safety and Health (Meyers, et al, 1998, 2000). Besides working conditions or deportation fears, underlying and structural inequality related to immigration status prevents access to healthcare and receiving high-quality treatment. As a result of the social, structural, political, and economic forces that act on unauthorized immigrants, researchers suggest that immigration should be considered a social determinant of health (Castañeda et al., 2015), among others such as socioeconomic status, education, and employment. This means that immigration status is a very significant factor that needs to be considered by healthcare workers to predict the chance of developing severe conditions like heart disease and others mentioned above.

Issues with Doctor-Patient Interaction and Hospital Structure If unauthorized immigrants seek access to healthcare for physical or mental issues, as a result of their unauthorized status, there are often structural barriers within hospitals and clinics which limit the quality of care they are given. With doctor-patient interactions, language barriers pose a significant problem, with some clinicians needing a translator with foreign language-speaking patients. Many physicians do not have easy access to a translator or do not want to put in enough effort to call over a translator, SPRING AND SUMMER 2021

thus resorting to conduct the appointment in English so the patient cannot understand or with an untrained interpreter like a patient’s family member or a Spanish-speaking medical student. Scheduling appointments is complicated as well due to a lack of flexibility in farm schedules for migrant workers and difficulty in missing work to visit the doctor. Unauthorized immigrants may also have patchy medical records if they need to travel to different locations for their jobs (Holmes et al., 2012). Furthermore, there are cultural barriers that make it difficult for doctors to understand and make recommendations to their patients. For example, in Mexican culture, there are different beliefs about pain and medicine, and individuals often receive treatment from traditional healers near them. This can lead to problems with workers’ compensation, damages that must be paid to an employee for an injury occurring on the job, as doctors have to conduct tests assessing patients’ injuries that align with cultural norms that differ from those of unauthorized immigrants. Because of these differences in their view of pain, migrant patients often pull away during particular aspects of workers’ compensation tests, which can be “interpreted as faking pain, while in reality, it is fear of pain” (Holmes et al., 2012), causing them to receive less compensation for their injury. Racial bias can also play a role when clinicians have different perceptions of people based on their immigration status or racial makeup. In a study at migrant health clinics, a doctor mentioned that she sees a high rate of premarital pregnancy in the migrant population. Most couples that make up their patients, members of the Triqui tribe,

"immigration status is a very significant factor that needs to be considered by healthcare workers to predict the chance of developing severe conditions like heart disease and others mentioned"

Figure 2: Many unauthorized immigrants work jobs that increase the likelihood for physical issues like joint pain and chemical inhalation or have long hours that prevent workers from being able to reach clinics to receive treatment. Image Source: Flickr, Creator: Bob Jagendorf

engage in traditional practices distinct from a Church of state wedding, thus making premarital pregnancies more complex than the doctor stated (Holmes et al., 2012).

"In a systematic review of legislation, several laws were found to prohibit or restrict undocumented immigrants from accessing basic health services, including emergency care, HIV, and STI treatments"

Within hospitals or clinics, there are resource constraints that make it harder for unauthorized immigrants to obtain proper care. In free clinics or reduced-price clinics especially, healthcare workers have heavy workloads and short appointment times that increase difficulty in communication, and there can be shortages of skilled psychotherapy or mental health workers to assist with issues more common to the unauthorized immigrant population. Besides a lack of quality interpreters, there is also a lack of diversity in the ethnic backgrounds of healthcare staff, contributing to the language and cultural issues mentioned earlier. Service guidelines in healthcare centers often contradict or do not match the attitudes and beliefs of migrant patients, such as practices concerning the disclosure of HIV status (Suphanchaimat et al., 2015). This can lead to increased stress and discomfort in patients and perhaps an increased likelihood that they will not return to these centers as frequently as they should.

Barriers to Healthcare Access Resulting from Immigration Policy Regulation surrounding immigration places restrictions on unauthorized immigrant access to healthcare. Anti-immigration laws lead to changes in legal practice, which in turn lead to changes in social institutions and environments by decreasing available resources or reducing 34

rights. These laws can affect health behaviors directly or shift environmental conditions to make certain behavioral choices more or less attractive, in the end leading to changes in health status. In a systematic review of legislation, several laws were found to prohibit or restrict undocumented immigrants from accessing basic health services, including emergency care, HIV, and STI treatments (Martinez et al., 2015). General immigration policy bars access to healthcare through fear and isolation. Many unauthorized immigrants are afraid to receive healthcare, even from free clinics, as a result of fears of checking documentation and being deported (Martinez et al., 2015). Immigration policy can also have an impact on the attitude of healthcare providers when offering services. Anti-immigrant legislature and policies in certain geographic areas can cause healthcare workers to discriminate against unauthorized immigrants and deny or delay services. Multiple states continue to refuse to expand their Medicaid programs to provide insurance to all incomeeligible children, regardless of their immigration status. Limited access to health insurance acts as a substantial barrier to receiving help. The Personal Responsibility and Work Opportunity Reconciliation Act of 1996 placed significant restrictions on unauthorized immigrants, declaring them ineligible for “any…health… benefit for which payments or assistance are provided to an individual, household, or family eligibility unit by an agency of a State or local

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government or by appropriated funds of a State or local government” except for in cases of emergency medical condition (Kullgren, 2003). This means that unauthorized immigrants are barred from participating in Medicare, Medicaid, and more. Some states are able to use funds to provide Medicaid coverage to income-eligible children regardless of immigration status, but many families continue to stay home due to fears of deportation (Gostin, 2019).

Disproportionate Impacts of COVID and Exacerbated Disparities for Unauthorized Immigrants These gaps in access and treatment impact the current COVID-19 pandemic and the vulnerability that unauthorized immigrants face in particular. To begin with, many unauthorized immigrants work in jobs like essential services that have an increased exposure to COVID and crowded working conditions. These jobs could include inadequate access or inappropriate use of personal protective equipment or the need to continue working while sick due to economic pressures. This can also extend to living conditions, since unauthorized immigrants may live in crowded multi-generational households that have an increased risk of transmission (Greenaway et al., 2020). Unauthorized immigrants who continue to work are also more likely to use public transit to get to their jobs, increasing their risk of exposure. The lack of access to undocumented immigrants

healthcare for heavily affects

them during the pandemic. Early diagnosis and monitoring of people with COVID are critical to optimize patient outcome and prevent further transmission. Unauthorized immigrants depend on free clinics or other safety-net public health systems that are underfunded and thus have limited resources to provide testing, management, and follow-up services. Also, a lack of access to preventive medicine in general leads to an increased risk of underlying health conditions like obesity, hypertension, and diabetes, which are linked to more severe COVID manifestations. Unauthorized immigrants also may be at risk for excessive stress due to fears of deportation, poverty, and trauma, which may be worsened during a pandemic, especially for those with limited healthcare, high risk of exposure, or high risk of job loss (Clark et al., 2020). Since unauthorized immigrants were excluded from the Patient Protection and Affordable Care Act, they are not able to receive primary care and thus needed to seek treatment in emergency rooms that are more crowded, increasing their risk or exposure to COVID (Greenaway et al., 2020). The increased vulnerability of unauthorized immigrants due to work and home conditions is exacerbated by the structural issues with access and quality of healthcare. This leads to increased health disparities for unauthorized immigrants among other minority populations, and the presence of COVID has revealed these disparities more clearly. Undocumented immigrants have increased barriers of access to vaccines because of these reasons, and although they are legally able to get the vaccine, the government has still needed to put out extra effort in order to encourage these

"unauthorized immigrants are barred from participating in Medicare, Medicaid, and more."

Figure 3: Advocates rally for a bill to provide healthcare to undocumented (unauthorized) immigrants. Unauthorized immigrants receive limited access to health insurance as a result of specific immigration policy. Image Source: Hartford Courant, Creator: Hector Amezcua

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individuals to receive their vaccines as a result of these barriers.

Potential Structural Changes and Recommendations In terms of COVID, urgent actions should be taken to support disadvantaged communities like immigrants, especially those that are unauthorized. This needs to take place at the local, state, and national levels, especially through legislation and policy change. Healthcare facilities should be designated as locations where immigration enforcement is prohibited, thus being able to reduce fears concerning deportation or government association. Furthermore, COVID testing and vaccination appointments should be made widely available and accessible for unauthorized immigrants that have a hard time taking time off from work, and policy changes should be introduced to prevent large healthcare costs for uninsured patients with COVID. Ways to create safer jobs for low-income workers would reduce their transmission risk but also allow them to continue to support themselves or their families (Clark et al., 2020). For doctor-patient communication, more materials and resources need to be allocated for translation services to ensure that proper communication is occurring and that unauthorized immigrants feel safe. There needs to be increased training on how to mediate cultural differences and understand potential bias by physicians, potentially including more intercultural mediators during appointments (Sandín-Vázquez et al., 2014). A study suggested that co-production, the concept of how to collaboratively create valuable healthcare service for the patient, with unauthorized immigrant patients can be successful if both the system and professionals are interested and prepared (RadlKarimi et al., 2020).

Asad, A. L. (2020). Latinos’ deportation fears by citizenship and legal status, 2007 to 2018. Proceedings of the National Academy of Sciences, 117(16), 8836-8844. Castañeda, H., Holmes, S. M., Madrigal, D. S., Young, M. E. D., Beyeler, N., & Quesada, J. (2015). Immigration as a social determinant of health. Annual review of public health, 36, 375-392. Clark, E., Fredricks, K., Woc-Colburn, L., Bottazzi, M. E., & Weatherhead, J. (2020). Disproportionate impact of the COVID-19 pandemic on immigrant communities in the United States. PLoS Neglected Tropical Diseases, 14(7), e0008484. Fortuny, K., Chaudry, A., & Jargowsky, P. A. (2010). Immigration trends in metropolitan America: 1980-2007 (pp. 1-18). Washington, DC: Urban Institute. Gostin, L. O. (2019). Is Affording Undocumented Immigrants Health Coverage a Radical Proposal?. JAMA, 322(15), 14381439. Greenaway, C., Hargreaves, S., Barkati, S., Coyle, C. M., Gobbi, F., Veizis, A., & Douglas, P. (2020). COVID-19: Exposing and addressing health disparities among ethnic minorities and migrants. Journal of travel medicine, 27(7), taaa113. Hacker, K., Chu, J., Arsenault, L., & Marlin, R. P. (2012). Provider’s perspectives on the impact of Immigration and Customs Enforcement (ICE) activity on immigrant health. Journal of health care for the poor and underserved, 23(2), 651. Holmes, S. M. (2012). The clinical gaze in the practice of migrant health: Mexican migrants in the United States. Social science & medicine, 74(6), 873-881. Karp, R. J., Rhee, D., Feldman, D., & Bouchkouj, N. (2007). Outreach to immigrant communities: teaching pediatric residents about access to health care. Journal of health care for the poor and underserved, 18(3), 510-515. Kullgren, J. T. (2003). Restrictions on undocumented immigrants’ access to health services: the public health implications of welfare reform. American journal of public health, 93(10), 1630-1633. Martinez, O., Wu, E., Sandfort, T., Dodge, B., Carballo-Dieguez, A., Pinto, R., ... & Chavez-Baray, S. (2015). Evaluating the impact of immigration policies on health status among undocumented immigrants: a systematic review. Journal of immigrant and minority health, 17(3), 947-970.

Healthcare policy in general should be modified so that more states opt into the Children’s Healthcare Insurance Program to have children considered for Medicaid regardless of their immigration status. Free clinics should be given more support and resources, especially in the number of interpreters required and the hours needed to stay open for unauthorized immigrants working long jobs throughout the day. This shows the need for collaboration between the healthcare system and NGOs, which provide help to disadvantaged groups in society (SandínVázquez et al., 2014).

Meyers J, Miles. J., Faucett J, Janowitz I, Tejeda D, Duraj V, Kabashima J, Smith , & R, W. E. (1998). High risk tasks for musculoskeletal disorders in agricultural field work. Paper presented at the American Public Health Association, Washington, DC.

References

Slesinger, D. P. (1992). Health status and needs of migrant farm

Radl-Karimi, C., Nicolaisen, A., Sodemann, M., Batalden, P., & von Plessen, C. (2020). Under what circumstances can immigrant patients and healthcare professionals co-produce health?-an interpretive scoping review. International Journal of Qualitative Studies on Health and Well-being, 15(1), 1838052 Sandín-Vázquez, M., Larraz-Antón, R., & Río-Sánchez, I. (2014). Immigrant patient care inequalities: the importance of the intercultural approach. Procedia-Social and Behavioral Sciences, 132, 277-284.

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workers in the United States: a literature review. The Journal of rural health: official journal of the American Rural Health Association and the National Rural Health Care Association, 8(3), 227-234. Suphanchaimat, R., Kantamaturapoj, K., Putthasri, W., & Prakongsai, P. (2015). Challenges in the provision of healthcare services for migrants: a systematic review through providers’ lens. BMC health services research, 15(1), 1-14. USDA Economic Research Service. (2020). Farm Labor. USDA ERS - Farm Labor.

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Mutant p53 and its Isoforms in the Onset & Treatment of Breast Cancer BY BROOKLYN SCHROEDER ’22 Cover Image: P53 is a tetramer tumor suppressor protein. The above depicts the crystal structure of the p53 binding domains which are attached to the respective DNA binding site. Image Source: Wikimedia Commons

Introduction The molecular mysteries of tumor onset and progression and their role in the development of a variety of cancers still perplex the modern world of science. Breast cancer, the most frequently diagnosed cancer in women in the United States, is no exception to this enigma. The manner in which a breast tumor develops is unique to a case-by-case basis. With this being said, regulation of cellular pathways, and especially their tumor suppressing properties, are critical in preventing this onset. The p53 protein, a tumor suppressor protein, is an essential transcription factor encoded by the TP53 gene and is essential in the regulation of a variety of cellular processes associated with apoptosis (a form of programmed cell death), cellular proliferation, cellular senescence (the ceasing of cell division), and also plays a critical role in DNA replication and repair activity. Most notably, in consideration of the development of cancerous tumors, especially in light of breast cancer, mutations in the p53 protein are characteristic of a considerable

fraction of breast cancer cases (Ziyaie et al., 2000). The p53 protein is a vitally important point of molecular focus in recognizing the onset of tumor development and can therefore be a biological marker for breast cancer treatments.

p53 Structure & Function The molecular structure of the p53 protein gives it characteristic function in the regulation of cell cycle arrest, DNA repair, and apoptotic pathways. By dissecting the structure of the p53 protein and its various domains, one can further recognize the extent to which this protein becomes nonfunctional by structural mutation. The p53 protein contains 393 amino acids, which are divided into various domains: the functional domain, which consists of a specific region called the transactivation region, a sequence-specific DNA binding region, oligomerization region, and a nuclear localization sequence (Harris, 1996). The other two key domains are categorized as evolutionary conserved domains deemed to be hotspots of mutational events (Harris, 1996). DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

As previously mentioned, the p53 protein is an essential component within cell cycle checkpoints and apoptotic pathways. Depending on the type of signaling, p53 can respond in various ways. The p53 protein plays an essential role in controlling the transition from G1/S to G2/M phases in the cell cycle in addition to its role in DNA repair, cellular senescence, apoptosis, autophagy and mitotic catastrophe (Varna et al., 2011). However, to focus upon the implications of such processes on oncogenic activity, one must identify the importance of p53 activation in inducing cell cycle arrest and the process by which damaged DNA is repaired. One critical target of p53 is p21, which binds to cyclin E/ Cdk2 and cyclin D/Cdk4 complexes to cause G1 arrest in the cell cycle (Chen, 2016). As a result of inhibited Cdk2 and Cdk4, pRb is unable to be phosphorylated, and therefore binds to E2F1, which silences its downstream targets that are essential for the process of DNA replication and progression through the cell cycle (Chen, 2016). In the case of DNA damage, a variety of protein kinases, whether that be Cdc2, protein kinase C, casein kinase II, etc., become activated and can then phosphorylate the p53 protein (Maclaine & Hupp, 2009). The phosphorylation of p53 allows

it to act as an active, stable transcription factor capable of binding upstream regulatory regions of various genes and promoting their transcription, while non-phosphorylated p53 would be targeted for degradation by its interaction with the protein MDM2 (Maclaine & Hupp, 2009). In summary, it becomes evident that as long as there is damage present, a cascade of events beginning with the phosphorylation of p53 and the subsequent translation of p21 will ensure the cell cycle does not proceed into the S phase until any detectable damage is repaired (in which case, this described signaling pathway would not be active). In relevance to carcinogenesis, if there was a case in which p53 is mutated, the cell cycle would then proceed into S phase with the DNA damage present. This would result in proliferation of this mutation, which not only amplifies this damage but can also lead to a variety of new mutations.

"it becomes evident that as long as there is damage present, a cascade of events beginning with the phosphorylation of p53 and the subsequent translation of p21 will ensure the cell cycle does not proceed into the S phase until any detectable damage is repaired"

In the context of generalized mutations, there is no case in which one mutation accurately depicts all that occur. Rather, within the p53 protein there are a variety of mutations that can occur, and the extent to which they contribute to carcinogenesis can either be attributed to loss of function (LOF) or gain of function (GOF) characteristics. LOF mutations include mutations Figure 1: The activated p53 protein plays a critical role in establishing the outcome of the cell cycle arrest and apoptosis processes. This activated p53 protein depends heavily on the relationship between p53 and mdm2. Image Source: Wikimedia Commons

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that diminish p53’s ability to bind DNA sequence motifs, which are key in directing transcription of genes regulated by p53 (Baugh et al., 2018). The idea that mutant p53 proteins could actually acquire GOF capabilities was not discovered until much after those LOF cases. A study conducted by Dittmer et al. in 1993, om which cDNA was added to a TP53 mutant, revealed this acquisition of oncogenic activity in mice, such as more rapid cell proliferation, loss of contact inhibition activities, larger tumorigenic potential, and larger tumor outcomes (Baugh et al., 2018).

"Numerous recent studies over the course of the last decade have recognized increasing rates of p53 mutations in cancers specific to carriers of germ-line BRCA1 & BRCA2 mutations – genes that are of utmost focus in breast cancer discussions."

DNA sequencing has revealed 74% of p53 mutations in cancers to be missense mutations which most notably occur within the protein’s centralized DNA binding domain (amongst amino acids 102-292), in which more of 30% of said mutations occur in the aforementioned “hotspot” regions of the p53 protein (Goh et al., 2011). Nearly 10% of p53 mutations are LOF, and result in no protein being translated at all (Baugh et al., 2018). As previously stated, there are a wide array of outcomes that can occur as a result of the p53 mutant, and the majority of such possibilities are strategically outlined in the study conducted by Muller & Vousden, 2013, in which four overarching models are: 1) alterations in the DNA binding abilities of p53 2) changes in the interaction of mutant p53 with other proteins 3) changes in the interaction of mutant p53 with other transcription factors and 4) proteins not related to the general regulation of gene expression (Muller & Vousden, 2013). It is universally acknowledged that carcinogens, aside from being genetically predisposed, bear momentous implications upon the potential of carcinogenesis and oncogenic activity in humans. Carcinogens, which are agents capable of causing cancer in human tissues, hold a notable relationship with mutations in the p53 protein. To illustrate this relationship, let us consider the most commonly recognized carcinogens -aflatoxin B1, tobacco smoke, and UV radiation associated with sun exposure. In the case of aflatoxin B1, multiple studies have shown evidence for aflatoxin B1 to cause a G:C to T:A transversion within codon 249 of the p53 gene (Rivlin et al., 2011). Similarly, tobacco smokers are frequently found to have an abundance of G to T transversions, while UV radiation exposure induced C to T and CC to TT transitions within nearly 50% of cases (Rivlin et al., 2011). Needless to say, there is indeed an evident correlation between carcinogens and p53 protein mutations.

The TP53 mutations, specifically missense mutations, are the most common mutation in human cancers (Baugh et al., 2018). This review will take a concentrated view looking at the frequency and implications of these previously discussed p53 mutations in breast cancer (Bellazzo et al., 2018). Interestingly, although much discussion has been given to missense mutations in light of p53 due to their frequency in nature, germ-line mutations in p53 occur most frequently in humans with Li-Fraumeni cancer susceptibility syndrome, which actually bestows a higher risk of developing breast cancer (Gasco et al., 2002). The prevalence of p53 mutations in breast cancer, at 20%, is not necessarily considerable (Gasco et al., 2002), but these mutations have significant ties to particular germ-line meaning they have the capability to be passed on to progeny. Numerous recent studies over the course of the last decade have recognized increasing rates of p53 mutations in cancers specific to carriers of germ-line BRCA1 & BRCA2 mutations – genes that are of utmost focus in breast cancer discussions. In fact, modern biological study has deemed BRCA1 as “the breast cancer gene” (Gasco et al., 2002). We have seen the general consequences of p53 alteration in cancer, and these observations remain consistent with breast cancer as well; specifically, loss of p53 wildtype activity has been posited as a primary element in breast cancer onset (Ziyaie et al., 2000). Most, notably though, what differentiates p53 mutations in breast cancers, versus those of other human cancers, is their ability to radically alter the severity and outcomes of breast cancer patients. Gasco et al. revealed that those p53 mutations acting directly upon amino acids essential for DNA binding, were most prevalent in the most aggressive cases of cancer (2002). Missense mutations and other null mutations were more closely associated with an undetermined phenotype (Gasco et al., 2002). In essence, though, the importance of a clear-cut focus upon p53 mutations and their ubiquity in human breast cancers is the general association of such mutations with worse survival rates amongst these individuals.

p53 Isoforms in Breast Cancer The modern field of breast cancer oncology has paid a great deal of attention toward expression of p53 isoforms proteins that have comparable functionality but differ in their amino acid sequencing) , and the varying extent to which these isoforms contribute to the regulation of

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Figure 2: There are increasing cases of p53 mutations within carriers of germline BRCA 1 and BRCA 2 mutations. BRCA 1 has most recently been recognized to be the “breast cancer gene”. Image Source: Wikimedia Commons

normal-functioning cells and cells with oncogenic activity in response to stressors (Kim & An, 2016). The TP53 gene undergoes translation to encode 12 distinguished p53 isoforms. These isoforms are produced through varying means: alternative promoter usage, alternative splicing and alternative initiation of translation (Avery-Kiejda et al., 2014). Milićević et a.l (2014) concluded that ΔNp53 (47 kDa) and Δ133p53𝛽 (35 kDa) (which are dominant-negative repressors of p53 function) were the most frequently occurring isoforms in invasive breast carcinoma cells, and Avery-Kiejda et al. (2014) found Δ40p53 to be the most expressed p53 isoform within breast cancer. Indeed, Milićević et al. used thirty random breast tumors for analysis of p53 isoforms through use of a classic Western blot analysis, which revealed that none of the tumors had the same p53 isoform expression pattern (2014). These results can contribute to the general conclusion of a multitude of studies that the implications of p53 upon molecular processes in breast cancer is still not completely known. However, with data supporting particular isoforms to be highly expressed compared to others, this provides a starting point for further focus within p53 mutant studies and target treatment in breast cancers in the future.

Targeting p53 for Treatment of Breast Cancer Since the p53 mutation has been consistently identified across numerous forms of human cancers, it is a reasonable area of focus in terms of biomarkers for cancer treatments. The unique fact about p53, and its complex nature, is that it had been considered “undruggable” until recent

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years. Since then, there have been a couple notable compounds that are believed to have a potential impact on mutant p53 -- PRIMA-1 and APR-246 (a methylated derivative and structural analogue of PRIMA-1) (Duffy et al., 2017). Both compounds reactivate mutant p53, allowing it to regain its wild-type characteristics. Aside from the general acquisition of wildtype properties, other approaches for restoring function in p53 entail depletion of the mutation p53 altogether, blocking negative regulator proteins MDM2 and MDM4, and treatments that promote close assessment of premature termination codes (Duffy et al., 2017). The revolutionary characteristic of PRIMA-1 in its ability to restore the wildtype function of p53 is restoration of sequence-specific DNA binding and ability to induce the apoptotic pathway (Duffy et al., 2018). The overarching outcome to focus on with PRIMA-1 is the biological evidence supporting its ability to inhibit p53 mutant breast cancer cells. Similarly, APR-246 is also characteristic of inhibiting excessive cell proliferation and promoting the occurrence of the apoptotic pathway (Duffy et al., 2014). Given the recent discovery that p53 is not in fact undruggable, there are minimal options in terms of chemicals to specifically target p53 mutants (Fedorova et al., 2020). PRIMA-1 and APR-246 are considered as the first mutant p53 reactivating compounds that progressed to clinical trials (Duffy et al., 2017). On a broader scale of common cancer treatments, it has been consistently concluded that p53 mutations are frequently associated with poor responses to the realms of chemotherapy, hormonal therapy and radiotherapy (Varna et al., 2011).

"other approaches for restoring function in p53 entail depletion of the mutation p53 altogether, blocking negative regulator proteins MDM2 and MDM4, and treatments that promote close assessment of premature termination codes"

"However, there is a promising future in terms of targeting p53 as a biomarker in breast cancer treatments given the recent rise of compounds to reactivate p53 mutant protein to regain its wildtype properties."

While on a surface level it seems unfathomable that there are infinite layers in terms of targeting p53 as a biomarker for cancer therapies, there is immeasurable complexity associated with this protein and its mutant form(s). In the case that a given chemical is able to target mutated p53, it shall still be considered that such findings may be confined to those bearing very specific molecular subtypes of breast cancer or to those receiving this chemical in addition to a specific form of cancer therapy (Duffy et al., 2017). With this being said, as has been previously determined, individuals may have their p53 mutation present on a different region of the TP53 gene, which then makes it that much more specified in discerning a targeting therapy. In addition to this, the isoforms of mutated p53 add another level of specificity to breast cancer patients. In a study conducted by Marcel et al., their findings suggest that in the presence of p53γ, but not p53β in breast cancer patients, there are comparable survival rates overall compared to those with wildtype p53 (2011). However, in another study, results show that expression of p53β but not the p53γ isoform was discovered to be protective in patients with p53 mutant tumors (Avery-Kiejda et al., 2014).

Conclusion Although recognized as the most prevalent mutation in human cancers, there is evidently still a great deal of complexity associated with the mutated p53 protein. Especially in light of breast cancer, there are a multitude of factors that go alongside these aforementioned p53 mutations as they can occur at varying locations along the TP53 gene. Not only this, but the twelve isoforms of the p53 protein make the approach to potential treatments and therapies that much more difficult given their respective specificities. However, there is a promising future in terms of targeting p53 as a biomarker in breast cancer treatments given the recent rise of compounds to reactivate p53 mutant protein to regain its wildtype properties. References

Avery-Kiejda, K. A., Morten, B., Wong-Brown, M. W., Mathe, A., & Scott, R. J. (2014). The relative mRNA expression of p53 isoforms in breast cancer is associated with clinical features and outcome. Carcinogenesis, 35(3), 586–596. https://doi. org/10.1093/carcin/bgt411 Baugh, E. H., Ke, H., Levine, A. J., Bonneau, R. A., & Chan, C. S. (2018). Why are there hotspot mutations in the TP53 gene in human cancers? Cell Death & Differentiation, 25(1), 154–160. https://doi.org/10.1038/cdd.2017.180 Bellazzo, A., Sicari, D., Valentino, E., Sal, G. D., & Collavin, L. (2018). Complexes formed by mutant p53 and their roles in breast cancer. Breast Cancer: Targets and Therapy, 10, 101–112. https://doi.org/10.2147/BCTT.S145826

Chen, J. (2016). The Cell-Cycle Arrest and Apoptotic Functions of p53 in Tumor Initiation and Progression. Cold Spring Harbor Perspectives in Medicine, 6(3). https://doi.org/10.1101/ cshperspect.a026104 Duffy, M. J., Synnott, N. C., & Crown, J. (2018). Mutant p53 in breast cancer: Potential as a therapeutic target and biomarker. Breast Cancer Research and Treatment, 170(2), 213–219. https://doi.org/10.1007/s10549-018-4753-7 Duffy, M. J., Synnott, N. C., McGowan, P. M., Crown, J., O’Connor, D., & Gallagher, W. M. (2017). P53 as a target for the treatment of cancer. Cancer Treatment Reviews, 40(10), 1153–1160. https://doi.org/10.1016/j.ctrv.2014.10.004 Fedorova, O., Daks, A., Shuvalov, O., Kizenko, A., Petukhov, A., Gnennaya, Y., & Barlev, N. (2020). Attenuation of p53 mutant as an approach for treatment of Her2-positive cancer. Cell Death Discovery, 6(1), 1–8. https://doi.org/10.1038/s41420-020-003374 Gasco, M., Shami, S., & Crook, T. (2002). The p53 pathway in breast cancer. Breast Cancer Research : BCR, 4(2), 70–76. https://doi.org/10.1186/bcr426 Goh, A. M., Coffill, C. R., & Lane, D. P. (2011). The role of mutant p53 in human cancer. The Journal of Pathology, 223(2), 116–126. https://doi.org/10.1002/path.2784 Harris, C. C. (1996). Structure and Function of the p53 Tumor Suppressor Gene: Clues for Rational Cancer Therapeutic Strategies. JNCI: Journal of the National Cancer Institute, 88(20), 1442–1455. https://doi.org/10.1093/jnci/88.20.1442 Kim, S., & An, S. S. A. (2016). Role of p53 isoforms and aggregations in cancer. Medicine, 95(26), e3993. https://doi. org/10.1097/MD.0000000000003993 Maclaine, N. J., & Hupp, T. R. (2009). The regulation of p53 by phosphorylation: A model for how distinct signals integrate into the p53 pathway. Aging, 1(5), 490–502. Marcel V, Dichtel-Danjoy ML, Sagne C, Hafsi H, Ma D, OrtizCuaran S, Olivier M, Hall J, Mollereau B, Hainaut P, Bourdon JC (2011). Biological functions of p53 isoforms through evolution: lessons from animal and cellular models. Cell Death Differ 18:1815–1824 Milićević, Z., Bajić, V., Živković, L., Kasapović, J., Andjelković, U., & Spremo-Potparević, B. (2014). Identification of p53 and Its Isoforms in Human Breast Carcinoma Cells. The Scientific World Journal, 2014, e618698. https://doi. org/10.1155/2014/618698 Muller, P. A. J., & Vousden, K. H. (2013). P53 mutations in cancer. Nature Cell Biology, 15(1), 2–8. https://doi.org/10.1038/ ncb2641 Rivlin, N., Brosh, R., Oren, M., & Rotter, V. (2011). Mutations in the p53 Tumor Suppressor Gene. Genes & Cancer, 2(4), 466–474. https://doi.org/10.1177/1947601911408889 Varna, M., Bousquet, G., Plassa, L.-F., Bertheau, P., & Janin, A. (2011). TP53 Status and Response to Treatment in Breast Cancers. Journal of Biomedicine and Biotechnology, 2011, e284584. https://doi.org/10.1155/2011/284584 Ziyaie, D., Hupp, T. R., & Thompson, A. M. (2000). P53 and breast cancer. The Breast, 9(5), 239–246. https://doi.org/10.1054/ brst.2000.0199

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Health and Heat Waves: Harbingers of What's to Come with Anthropogenic Climate Change BY CADY RANCOURT '24 Cover Image: A car dash displays an outside temperature of 106°F. Image Source: Flickr; Creator: Geremy F

Introduction The hottest days of summer bring feelings of exhaustion, discomfort, and longing for cooler days ahead. People flock to beaches and airconditioned buildings seeking respite from the oppressive heat, passing unfavorably updated Smokey the Bear fire danger signs. Even worse, though, is when the hottest days of summer occur consecutively and at abnormally high temperatures as a heat wave. Historically, heat waves have proven powerfully damaging, resulting in thousands of deaths, amplifying drought, and catalyzing wildfires (Union of Concerned Scientists, 2018a). The infamous European heat wave of 2003 took the lives of over 70,000 people and served as a “turning point” for how nations in Europe and beyond perceive, prepare for, and respond to heat waves (Di Napoli et al., 2019). While the 2003 heat wave was extraordinary and triggered a muchneeded response, it also garnered attention as a once-in-a-lifetime event. This mindset, however, is dangerous and unsustainable. Heat waves are becoming more frequent, while simultaneously

climbing to increasingly higher temperatures and growing in duration (Rastogi et al., 2020). They are anticipated to continue along that trend, which has been attributed to anthropogenic (human-caused) climate change (Rastogi et al., 2020). Because heat waves are only projected to worsen, the seemingly unbearable heat waves we currently endure are a preview of the kind of temperatures that may one day seem less extreme or even preferable. If—among other lasting and harmful impacts—the heat waves of the past and present have already garnered a dreadful death toll, what is to be expected for heat-related human health outcomes in the coming decades?

The Struggle to Define Heat Waves The general concept of a heat wave is not difficult to understand and—through lived experiences—is already grasped by many. Even so, problems emerge when researchers seek to study them. Varying definitions of heat waves create incongruence and prevent “comparison and synthesis of results” across literature (Anderson & Bell, 2011). Conceptually, a heat wave is a meteorological event lasting a few DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

consecutive days characterized by exceptionally high temperatures. But “a few consecutive days” and “exceptionally high temperatures” are phrases far too ambiguous for study, leaving much to question: how many days are “a few,” and what temperatures classify as “exceptionally high”? How many standard deviations away from normal does “exceptionally” demand? One could endlessly descend into a rabbit hole of questions and understand just how daunting a task researchers face. What is clear, though, is just how malleable to locations a heat wave definition must be. Different parts of the world naturally have vastly different 1) temperature and deviation thresholds that define extreme heat and 2) levels of preparedness to withstand extreme heat. For example, a 4-day, 5-degree increase from normal in Juneau, Alaska might be substantially threatening to citizens if natural variability is low due to coastal proximity, which narrows the range of temperatures experienced (Lutgens & Tarbuck, 2016). Conversely, it might be only a slight inconvenience in inland Omaha, Nebraska, where people may be used to a wider range of temperatures and are likely more prepared to handle various weather conditions, whether that preparedness comes in the form of adequate healthcare, access to air-conditioning, knowledge of handling heat, or otherwise (Union of Concerned Scientists, 2018a). There have been multiple approaches to defining heat waves for study, each with its own drawbacks. Some researchers, including Kent and colleagues (2014), argued a “mean-temperatureonly” definition as the most suitable for Alabama, where a heat wave was defined as 2 or more consecutive days where the mean temperature was at or above the 98th percentile of non-heatwave control days. Several definitions claim that high daily minimum temperature is the primary indicator of a heat wave, while others say daily maximum temperature is what matters. Some deem the 90th percentile as useful, or the 95th, or 85th, and so on and so forth (Kent et al., 2014). However, these definitions take only one SPRING AND SUMMER 2021

component of a heat wave into account: temperature. Of course, high temperatures constitute the essence of a heat wave, but other factors play a role in how people actually experience heat waves. Wind speeds, solar radiation, and humidity can exacerbate the extent of effects on human health (Di Napoli et al., 2019). Some definitions use heat index or apparent temperature (see Figure 1) (Anderson & Bell, 2011), which comes a step closer to fully representing heat waves by incorporating humidity but still falls short. Because researchers studying heat waves focus on human health impacts, there is a dire need to utilize a comprehensive, health-centered definition (Di Napoli et al., 2019) that takes all those nontemperature factors into account, in addition to analyzing how preparedness of a community (e.g., access to healthcare, spaces equipped with A/C, knowledge of and experience with extreme heat) alters heat-related health outcomes. One of the most promising health-centered approaches to defining heat waves involves the universal thermal climate index (UTCI). The UTCI is a “bioclimate index elaborated via an advanced model of human thermoregulation that estimates the thermal stress induced by air temperature, wind speed, moisture, and radiation on the human physiology” (Di Napoli et al., 2019). Di Napoli and colleagues (2019) examined 30 years of mortality data from five French cities in conjunction with meteorological data to examine the correlation between excess deaths (the number of deaths over what is considered typical) and UTCI values (Di Napoli et al., 2019). The group discovered that stretches of three or more consecutive days at or above the 95th percentile of UTCI values were most strongly associated with increased “all-cause” deaths (Di Napoli et al., 2019), which covers any type of death, including directly heat-related deaths and deaths from pre-existing conditions that heat worsens (McGregor et al. 2015). Essentially, the group was able to calculate daily UTCI values using the cities’ meteorological data, then crossexamine the daily UTCI values with the cities’ daily excess death values. From there, they were able to find that the best definition for a heat wave in those cities was a stretch of three or more days at or above the 95th percentile of UTCI values. This definition is considered “best” because it defines a heat wave such that under those conditions, people have the most cause for health-related concern, since those conditions are associated with the strongest health effects.

Figure 1: This table displays the National Weather Service’s heat index, or apparent temperature, by combining temperature and relative humidity to determine a “feels like” temperature and corresponding “likelihood of heat disorders with prolonged exposure or strenuous activity.” Image Source: NOAA

"The group discovered that stretches of three or more consecutive days at or above the 95th percentile of UTCI values were most strongly associated with increased 'all-cause' deaths"

Calculating UTCI values from local weather data and comparing with local health data allows 45

Figure 2: Emergency room visits increase with heat waves, with patients presenting a variety of conditions heat-related and otherwise (McElroy et al., 2020). Image Source: Flickr; Creator: Rob Nguyen

"As expected, heatrelated mortality and morbidity, manifesting in ambulance calls, emergency department visits, and hospitalizations, increase significantly during heat waves"

researchers to find a health-centered definition of a heat wave specific to a community. Under this method, heat wave definitions are standardized through the use of a consistent metric (the UTCI) while remaining loyal to a location’s individualities. Additionally, this method indirectly encapsulates the preparedness of a community to handle extreme heat, since the health data being used is a reflection of the community’s preparedness (because preparedness in any form affects health data, e.g., an area with adequate healthcare will likely result in less negative health outcomes). The one major drawback of the heat wave definition proposed by Di Napoli and colleagues (2019) is that it only considers mortality, while morbidity—the suffering of any medical condition without resulting in death— hospitalizations also increase during heat waves (Hayhoe et al., 2010). Integrating morbidity into heat wave research remains far more complicated than mortality because of morbidity’s fluctuating definitions between nations and complex nature (Di Napoli et al., 2019). Thus, it is hard to find datasets of morbidity that could be used to find correlations between UTCI values and morbidity in the way that was done with mortality in the five French cities. While deaths are understandably of primary concern, the UTCI used by Di Napoli et al. (2019) still underestimates the overall impact of heat waves on human health by neglecting to account for morbidity.

Heat Waves and Health Impacts Despite the inconsistency among heat wave definitions, many studies have characterized the health impacts (known as morbidity and mortality) of extreme and sustained heat. In the past, heat waves have put healthcare facilities under pressure due to surging emergency department visits and hospitalizations, with patients facing a variety of ailments (McElroy et al., 2020). In analyzing a 2006 heat wave, researchers found “16,166 excess ED visits and 1,182 excess hospitalizations” across California,

a 3.3% increase from normal (Knowlton et al., 2009). A 2011 heat wave in Sydney, Australia produced a 2% increase in all-cause emergency department visits and a 14% increase in all-cause ambulance calls (Shaffer et al., 2012). Tong and colleagues (2010) examined emergency hospital admissions across ten different heat wave definitions and found significant increase in each. While the extent of increase varies across regions due to varying community preparedness, many studies have consistently shown an increase in emergency department visits, ambulance calls, and hospitalizations during heat waves across several heat wave definitions (Li et al., 2015). Under one umbrella of common heat-related medical conditions—called heat stress—are heat cramps, heat exhaustion, and heat stroke (Union of Concerned Scientists, 2018a). In that order, they go from least to most medically concerning. Heat cramps bring on “muscle pains and spasms,” heat exhaustion causes “dizziness, a weak pulse, nausea, and fainting,” and heat stroke—the most fatal—produces similar symptoms to heat exhaustion and cramps as well as a quick heartbeat and fever over 103°F (Union of Concerned Scientists, 2018a). As expected, heatrelated mortality and morbidity, manifesting in ambulance calls, emergency department visits, and hospitalizations, increase significantly during heat waves (Li et al., 2015). Aside from heat stress, pre-existing conditions can be intensified with heat. Studies have shown that both morbidity and mortality increase in patients with respiratory and cardiovascular conditions (McGregor et al., 2015). Heart attacks also spike during heat waves (Union of Concerned Scientists, 2018a). In an Alabama study that sought to compare health outcomes across differing heat wave definitions, pregnancies resulting in preterm births rose by as much as 35% under one definition and had positive associations with heat in 9 out of 15 definitions. (Kent et al., 2014). Renal disease and mental illness hospitalizations have also shown increases during heat waves in some studies, although more research is needed to establish a strong association (Li et al., 2015). There is plenty of evidence to suggest that particularly humid heat waves are the most disastrous to human health (Rastogi et al., 2020). High humidity prevents the sweat on the surface of the skin from evaporating, a process required to cool the body (Union of Concerned Scientists, 2018a). This process is also why it’s often easier to sit for longer periods of time in a 185°F dry sauna compared to a 185°F wet sauna, where

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Figure 3: NOAA graphs display how heat waves have changed in frequency, duration, season length, and intensity since the 1960s. Image Source: NOAA

steam fills the air and prevents the body from cooling. If the body cannot cool and regulate temperature properly, negative health effects are bound to occur, whether in a sauna or a heatwave-riddled atmosphere. However, humid heat waves have not always been more harmful to humans when compared to dry heat waves (Montero et al., 2012). According to Montero and colleagues (2012), the highest mortalities in Spain are actually correlated with lower humidity, and the correlation between humidity and mortality varies from city to city in the United States. Health effects vary considerably among different populations. Elderly people, particularly those aged 75 or higher, remain most vulnerable across most heat-related health impacts (Li et al., 2015). However, in some heat waves and some specific illnesses, children and youth have been most affected (Li et al., 2015). Most heat-related health impacts are experienced more frequently by men of all ages than women, whereas women only outrank men in a few, such as renal disease (Li et al., 2015). Those in predominantly outdoor careers are at high-risk, especially Latino men working for smaller companies less equipped to adequately care for employees during heat waves (e.g., sufficient time off, proper protective gear,

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informing employees of heat-related risks and how to mitigate them, etc.) (Union of Concerned Scientists, 2018a). Urban residents endure more intense heat wave effects compared to rural residents due to the urban heat island effect, which describes the increased and sustained heat observed in cities on account of their heat-trapping materials like asphalt (Union of Concerned Scientists, 2018a). People with preexisting conditions are more susceptible to heat exacerbating their illnesses, and low-income individuals are also disproportionately affected due to lack of access to both healthcare and airconditioning (Union of Concerned Scientists, 2018a). Understanding the various heat-related health impacts—morbidity and mortality—and how different demographics experience them is key to understanding the future of human health during future heat waves.

"Health effects vary considerably among different populations. Elderly people, particularly those aged 75 or higher, remain most vulnerable across most heat-related health impacts"

Forecasting the Future of Heat Waves Heat waves are already starting to get longer, hotter, and more frequent; they are only expected to continue along that path (Rastogi et al., 2020). With that in mind, we can reasonably expect that

Figure 4: Protesters raise signs to bring awareness to and demand action regarding anthropogenic climate change. People in cities—like protesters in London, pictured here—are most affected by high temperatures due to the urban heat island effect (Union of Concerned Scientists, 2018a). Image Source: Flickr; Creator: Valerio Donfrancesco

the health effects of heat waves we observe in the past will persist, but with increasing ferocity as years go on. Likely there will be more deaths, more pre-term births, and more hospitalizations of all kinds. Keeping those most vulnerable to heat wave impacts is also a necessary and interdisciplinary strategy for preventing negative heat-related health outcomes. More people are expected to move from rural areas to cities (Li et al., 2013), which are already more impacted by heat waves due to the urban heat island effect (Union of Concerned Scientists, 2018a) and thus we can anticipate higher rates overall of negative heat-related health outcomes during heat waves. Other hard-hit demographics, like outdoor workers and those in low-income communities will likely continue to be the most affected. Ultimately, there remains a need for highly localized yet standardized definition methods in research on heat-induced mortality and especially morbidity (Li et al., 2015) to better predict just how severe the coming decades will be on human health. Finding ways to standardize morbidity data would allow for morbidity’s integration into heat wave definitions. Furthermore, heathealth watch warning systems have the potential to significantly reduce heat-related health complications during future heat waves (McElroy et al., 2020). Current systems have proven useful, but much improvement can be made with the use of a better health-oriented heat wave definition (McElroy et al., 2020) like the UTCI. The UTCI “proved successful in detecting hazardous heat stress levels up to 10 days in advance” and, if more widely used in the future, has great potential to

help define heat waves and improve warning systems and therefore lessen the worst effects of human-caused climate change. (Di Napoli et al., 2019). Lastly, while definitions and warning systems are necessary tools for understanding and handling heat from anthropogenic climate change, the best tool humans could utilize going forward is slowing the process that started it all and reducing emissions, a strategy that seems— with enough effort and optimism—just as possible as defining heat waves. References Brooke Anderson, G., & Bell, M. L. (2011). Heat waves in the United States: Mortality risk during heat waves and effect modification by heat wave characteristics in 43 U.S. communities. Environmental Health Perspectives, 119(2), 210–218. https://doi.org/10.1289/ehp.1002313 Di Napoli, C., Pappenberger, F., & Cloke, H. L. (2019). Verification of heat stress thresholds for a health-based heat-wave definition. Journal of Applied Meteorology and Climatology, 58(6), 1177–1194. https://doi.org/10.1175/ JAMC-D-18-0246.1 Hayhoe, K., Sheridan, S., Kalkstein, L., & Greene, S. (2010). Climate change, heat waves, and mortality projections for Chicago. Journal of Great Lakes Research, 36, 65–73. https://doi. org/10.1016/j.jglr.2009.12.009 Kent, S. T., McClure, L. A., Zaitchik, B. F., Smith, T. T., & Gohlke, J. M. (2014). Heat waves and health outcomes in Alabama (USA): The importance of heat wave definition. Environmental Health Perspectives, 122(2), 151–158. https://doi.org/10.1289/ ehp.1307262 Knowlton, K., Rotkin-Ellman, M., King, G., Margolis, H. G., Smith, D., Solomon, G., Trent, R., & English, P. (2009). The 2006 California heat wave: Impacts on hospitalizations and emergency department visits. Environmental Health

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Perspectives, 117(1), 61–67. https://doi.org/10.1289/ehp.11594 Li, D., & Bou-Zeid, E. (2013). Synergistic interactions between urban heat islands and heat waves: The impact in cities is larger than the sum of its parts. Journal of Applied Meteorology and Climatology, 52(9), 2051–2064. https://doi.org/10.1175/ JAMC-D-13-02.1 Li, M., Gu, S., Bi, P., Yang, J., & Liu, Q. (2015). Heat waves and morbidity: current knowledge and further direction-a comprehensive literature review. International Journal of Environmental Research and Public Health, 12(5), 5256–5283. https://doi.org/10.3390/ijerph120505256 Lutgens, F. K., & Tarbuck, E. J. (2016). The atmosphere: An introduction to meteorology (13e. ed.). Pearson. McElroy, S., Schwarz, L., Green, H., Corcos, I., Guirguis, K., Gershunov, A., & Benmarhnia, T. (2020). Defining heat waves and extreme heat events using sub-regional meteorological data to maximize benefits of early warning systems to population health. The Science of the Total Environment, 721, 137678– 137678. https://doi.org/10.1016/j.scitotenv.2020.137678 Montero, J. C., Miron, I. J., Criado, J. J., Linares, C., & Díaz, J. (2013). Difficulties of defining the term, “heat wave”, in public health. International Journal of Environmental Health Research, 23(5), 377–379. https://doi.org/10.1080/09603123.2012.733941 Rastogi, D., Lehner, F., & Ashfaq, M. (2020). Revisiting recent U.S. heat waves in a warmer and more humid climate. Geophysical Research Letters, 47(9). https://doi. org/10.1029/2019GL086736 Schaffer, A., Muscatello, D., Broome, R., Corbett, S., & Smith, W. (2012). Emergency department visits, ambulance calls, and mortality associated with an exceptional heat wave in Sydney, Australia, 2011: a time-series analysis. Environmental Health, 11(1), 3–3. https://doi.org/10.1186/1476-069X-11-3 Tong, S., Wang, X. Y., & Guo, Y. (2012). Assessing the shortterm effects of heatwaves on mortality and morbidity in Brisbane, Australia: comparison of case-crossover and time series analyses. PloS One, 7(5), e37500–e37500. https://doi. org/10.1371/journal.pone.0037500 Union of Concerned Scientists. (2018a). Heat waves and climate change: The effects of worsening heat on people, communities, and infrastructure. Union of Concerned Scientists. (2018b). Heat waves and climate change: What the science tells us about extreme heat events

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When Hands Are Tied Instead of Tubes: The Barriers Women Face in Accessing Tubal Ligations BY CAROLINE CONWAY ’24 Cover Image: A baby lying in its crib. The decision to have a child carries significant emotional, financial, and professional implications, yet current medical policies can deny women access to one of the most effective forms of birth control, leaving them without the resources necessary to act on the decision to not have children. Source: Wikimedia Commons

Motivations for Childlessness and a Brief Introduction to Tubal Ligations According to the U.S. Census Bureau, roughly twenty percent of American women will remain childless for the entirety of their lives (Dye, 2010). Only about half of these childless women are infertile (Richie, 2013). These statistics counter the social perception that childbearing is an inevitable part of female adulthood. For the purposes of this article, “women” refers to femaleidentifying individuals with the biological means to bear children, and “childlessness” describes the absence of biological children without accounting for surrogacy. Women decide against having children for myriad reasons. One motivation is to avoid the substantial economic burden of children — the United States Department of Agriculture (2013) found that the average middle-class family pays over 300,000 dollars to raise just one child to adulthood. Furthermore, this figure fails to account for the cost of college

and potential medical emergencies. Thus, the apprehension women may feel due to this cost, particularly single women and/or women with a lower or unstable income, is understandable. Other women choose childlessness to avoid passing on hereditary diseases. Additionally, some women see childlessness as an altruistic choice that reduces their carbon footprint and prevents them from contributing to the adverse effects of population growth. Other women choose not to have children to avoid dangerous pregnancy complications or to evade the general disruption pregnancy/child-rearing might pose to their professional and/or personal lives (Richie, 2013). This is a non-exhaustive list of common reasons women cite for choosing childlessness, but it is essential to note that no one “reason” is necessary to justify such a choice. Some women simply do not want children, and that is reason enough not to have them. It follows that sexually active, voluntarily childless adults should have access to effective, long-term contraception. DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Some voluntarily childless women turn to tubal ligations. A tubal ligation is a permanent sterilization procedure for women intended to prevent future fertilization by blocking the fallopian tubes. Generally, this surgery involves tying each fallopian tube with suture material and severing it. One primary tubal ligation method is the Pomeroy technique, in which a 2-cm loop of the tube’s midsection is tied off and the portion of the tube above the ties is then removed. Another common method is the Parkland technique, which involves tying the tube in two places and cutting away the portion in between these ties (EngenderHealth, 2002). This surgery is common; from 2006 to 2008, sterilization was second only to the pill as a form of contraception in American women ages fifteen through forty-four (Mosher & Jones, 2010). Globally, sterilization (including vasectomies as well as tubal ligations) is the most common method of contraception (EngenderHealth, 2002). The popularity of tubal ligations is unsurprising given the difficulty of accessing abortions in parts of the country and around the globe. Not all women are comfortable with the ethical implications of terminating a pregnancy or have the means to terminate a pregnancy, since state laws within the United States can make such terminations next to impossible. Therefore, some women who wish to remain childless identify preventing all future pregnancies as their best choice. This is easier

said than done, however, as tubal ligation access remains a controversial topic in the medical field. Due to the prevalence of medical paternalism in tubal ligation consultations, the choice to undergo this operation may not be a choice at all.

Medical Paternalism and Tubal Ligations The issue of tubal ligation access for voluntarily childless women has a historical basis in the U.S. — the American College of Obstetricians and Gynecologists codified pronatalist bias in the 1960s with the “120 rule.” According to this guideline, a woman qualified for sterilization if the product of her age and current number of children was at least 120, meaning that a childless woman could undergo the procedure at the age of 120. This standard was repealed in 1969 but was promptly replaced with requirements of a minimum age of twenty-one and the need for a doctor’s approval to undergo a tubal ligation (Lalonde, 2018). Today, despite the widespread use of sterilization as a safe and effective form of birth control, the path to tubal ligation procedures is often a challenging one for women to navigate, since doctors can choose to bar a patient access to a tubal ligation on the grounds of medical paternalism (Mertes, 2017).

"some women who wish to remain childless identify preventing all future pregnancies as their best choice. This is easier said than done, however, as tubal ligation access remains a controversial topic in the medical field."

Medical paternalism is the phenomenon in which a medical professional decides which treatments Figure 1: An illustration of various surgical procedures on the Fallopian tubes. Though invasive, tubal ligations are considered a safe and highly effective form of birth control. Image Source: Wikimedia Commons

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"One study found that 20.3 percent of voluntarily sterilized women ages thirty and younger regretted their sterilizations, and 5.9 percent of women older than thirty reported regret"

to offer a patient based on the doctor’s opinion of what is in the patient’s best interests. Generally, this is intended to utilize doctors' extensive training to maximize patient well-being (Mertes, 2017). For example, if a medical professional was approached by a patient who wanted an amputation, but the doctor knew they could instead save the limb in question, that doctor would likely refuse to perform the amputation and would offer the treatment they considered more appropriate instead. Essentially, medical paternalism is a gray area in medicine in which physicians might have the option to disregard patients’ desires. When a doctor disagrees with a female patient about whether a tubal ligation is justified, conflict results. In the absence of specific guidelines determining who can and cannot get a tubal ligation, individual doctors are relatively free to act on their personal judgments, essentially turning the consultation process for tubal ligations into a battle of wills. Because medical paternalism grants a doctor the last word on the matter, childless women often lose this battle. This is evident from the fundamental gap between the population of women who wish to be childless and the population of women who would be granted a tubal ligation upon request (Mertes, 2017). Even women with children demonstrate this access gap, as one study found that 31 percent of women who requested a postpartum tubal ligation were denied the procedure and that 46.7 percent of these women became pregnant within the next year (Thurman & Janecek, 2010). The practice of medical paternalism can often mean that childless women are unable to undergo tubal ligation procedures even in the absence of substantial health risks related to the operation. The need to obtain a doctor’s approval effectively bars many childless women from having tubal ligations, as their doctors can deny them access to the procedure based solely on the doctors’ belief that the women will eventually want children.

denying a woman access to a tubal ligation is in her best interests, since she might regret the procedure later. However, the reality of the nature and frequency of regret related to tubal ligations renders such arguments hollow. The women regretting their sterilization procedures represent relatively low proportions of the patient population. Hillis et al. (1999) found that over 79 percent of women thirty and under who had a tubal ligation expressed no regret regarding their decisions, and over 94 percent of women expressed no regret in the age group over thirty. Additionally, some permanent procedures with considerably higher regret rates are far less regulated. For example, one study found that 37 percent of patients regretted getting a tattoo, yet 24 percent of patients were able to access a tattoo procedure while under the legal age limit (Aslam & Owen, 2013). This suggests that doctors’ concerns about regret are not well supported, as regret is a problem with relatively few women who have had a tubal ligation performed and does not seem to factor as heavily into policy enforcement for other permanent procedures.

Before rejecting the application of medical paternalism to tubal ligation requests, one must understand why doctors feel that such paternalism is necessary. One of the primary justifications doctors cite for medical paternalism in tubal ligation procedures is the concern that patients may come to regret the procedure and be powerless to do anything about it, as it is meant to be permanent. Evidence suggests that this concern is not entirely unfounded. One study found that 20.3 percent of voluntarily sterilized women ages thirty and younger regretted their sterilizations, and 5.9 percent of women older than thirty reported regret (Hillis et al., 1999). Physicians can use such statistics to argue that

Researcher Cristina Richie (2013) found that one of the most common reasons doctors provide for denying women tubal ligations is that the women are too young. Consequently, many doctors opt to impose a minimum age limit of twentythree on the procedure (Richie, 2013). This is a judgment on the doctors’ part; United States law allows women to get tubal ligations at and above the age of twenty-one. This restriction rests on the assumption that women requesting tubal ligations will come to regret their decision with age.

In contrast, the denial of tubal ligation access carries a substantial risk of regret. One study found that 47 percent of women denied sterilization regretted not being sterilized — a percentage more than twice as high as the 20.3 percent regret rate in women thirty and younger who were granted the procedure (Lalonde, 2018). This suggests that doctors not only place excessive emphasis on regret in women who undergo tubal ligations, but also that doctors fail to consider the regret women suffer from as a result of being denied the procedure. If doctors truly seek to minimize patient regret, they should arguably find a 47 percent regret rate more compelling than a mere 20.3 percent, especially considering that biological parenthood remains possible via in vitro fertilization after a tubal ligation.

Another reason doctors choose to deny women tubal ligations is a lack of spousal consent.

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Figure 2: Anti-abortion protestors outside a Planned Parenthood facility in Portland, Maine. Legal and social opposition to abortion can leave women unable to choose childlessness in the case of an unwanted pregnancy resulting from tubal ligation denial. Image Source: Wikimedia Commons

Richie (2013) found that fifty percent of doctors performing female sterilizations required spousal consent before agreeing to perform the procedure. This restriction, like the one on age, is meant to protect the patient from the possibility of future regret, assuming that a disagreeing spouse would expect children in the future and that the patient should plan accordingly. The effects of this policy are that unmarried childless women face extensive difficulty in accessing tubal ligations because doctors might assume that their future spouses will want children, and married women lack full bodily autonomy when their spouses are unsupportive of their decisions regarding sterilization. Finally, the application of medical paternalism to matters of tubal ligations today reflects the “120 rule” from the 1960s –many doctors require the woman trying to receive a tubal ligation to have at least one child before the operation is performed (Richie, 2013). This restriction is based on the assumption that women will regret having a low number of children less than they will regret having no children at all. Many of the requirements to get a tubal ligation reflect the assumption that all women want to be and should be mothers. Take, for instance, the argument of regret. Fertility treatment, like a tubal ligation, will significantly impact a woman’s ability to bring a child into the world and requires careful consideration. However, researcher Heidi Mertes (2017) notes that regret is not emphasized comparably for fertility treatments: “If regrets are talked about at all in the fertility clinic, it is mainly in the sense that infertile couples should do everything they can to conceive a child in order to prevent future regrets” (p. 315). Some individuals might argue that this discrepancy is partially due to the permanence of tubal ligations,

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but the process of parenting a child is arguably as long-lasting as tubal ligation effects. Additionally, tubal ligations can be reversed in some cases, and parenthood remains possible through means such as surrogacy or adoption. The stark contrast in concern over regret between tubal ligations and fertility treatments reflects a societal pressure on women to have children. Medical paternalism can allow this pressure to be incorporated into medical care.

The Consequences of Tubal Ligation Denial Philosophy professor Martha Nussbaum (2008) created a list of “central human capabilities” necessary to achieve a state of well-being: life, bodily health, bodily integrity, senses/ imagination/thought, emotions, practical reason, affiliation, other species, play, and control over one’s environment. Nussbaum (2008) describes bodily integrity in part as “having opportunities…for choice in matters of reproduction” (p. S110). It is easy to see how a tubal ligation would aid a woman in the pursuit of such autonomy. Undergoing a tubal ligation not only grants women the reproductive choice Nussbaum describes, but also removes the economic, physiological, and psychological factors of parenthood that might prevent them from achieving a state of personal flourishing. Denying women tubal ligation access alters their ability to achieve happiness on the most fundamental level by limiting their capacities for long and healthy lives. In addition to bodily integrity, Nussbaum (2008) includes both life and physical health in her list of central human capabilities that are key to well-being. Pregnancy complications can negatively impact a woman’s health. For example, pregnancy has been linked to high blood pressure and increased risk of cardiovascular diseases in some women,

"Philosophy professor Martha Nussbaum (2008) created a list of “central human capabilities” necessary to achieve a state of well-being: life, bodily health, bodily integrity, senses/ imagination/thought, emotions, practical reason, affiliation, other species, play, and control over one’s environment."

"Considering these dangers of pregnancy, medical paternalism as a basis for denying tubal ligation access does not seem consistent with the Hippocratic Oath’s requirement that doctors “do no harm” to their patients."

especially in those who are younger when they give birth to their first child (Parikh et al., 2017). In other cases, pregnancies can be mortal. According to Dr. Adrian Brown, pregnancy/ childbirth mortality is the leading cause of death for fertile women in developing countries (Eaton, 2003). The risk for complications and death due to pregnancy varies from woman to woman but can be evaded with the avoidance of pregnancy itself. Tubal ligations are tied to patient health in relation to cancer risk as well. One study reported that tubal ligations were associated with a twenty percent reduction in ovarian cancer risk and in peritoneal cancer risk, and the study also found that tubal ligations were associated with a general decrease in the risk of cancers of the fallopian tubes (Gaitskell et al., 2016). Granting women tubal ligations upon request with informed consent, therefore, could save and/or prolong those women’s lives. Most other areas of life allow individuals to assess the risk of injury or death and reach their own conclusion about whether the relevant activity is worth that risk, and people are given the freedom to opt out of activities that they consider too high-risk. Take donating an organ, for instance. One does so at their own risk, accepting personal responsibility for the outcome. Societal standards allow such responsibility to fall on the individual alone. However, medical paternalism can allow pregnancy to be treated as an exception to this rule. Medical paternalism is based on the Hippocratic Oath’s mandate that physicians “do no harm.” However, physicians using paternalism to deny their patients tubal ligations may inadvertently harm those patients. Take, for instance, the testimony of one voluntarily childless woman researcher Kristin Park (2002) interviewed: “It’s like you’ve done something wrong, or somehow you’re not matching up, or you’re a failure in some way” (p. 30). This description of being a voluntarily childless woman reflects the toll pronatalist societal expectations have taken on the woman’s well-being. She feels judged and out of place as a result of her decision to not have children. When doctors perpetuate childbearing expectations by refusing to perform tubal ligations on childless women, they can contribute to harmful stigmas that depict voluntary childlessness as a moral wrong. Kristin Park (2002) found that many voluntarily childless interviewees felt that they were viewed as more materialistic, cold, and self-centered than their peers with children. These perceptions are evidence that voluntary childlessness is a stigmatized identity like any other, requiring individuals to find coping mechanisms in the face of negative stereotypes

and social pressures (Park, 2002). The tubal ligation is considered one of the most effective forms of birth control, with a failure rate below one percent (Mosher & Jones, 2010). In denying childless women access to such an effective birth control measure, doctors risk exposing women to unwanted pregnancies and unwanted abortions — both experiences associated with emotional and physical pain. Such pain might result from pregnancy complications, as previously discussed, or could stem from postpartum psychiatric disorders. For instance, one in seven women who recently gave birth experience significantly disruptive depressive episodes. New mothers are also prone to postpartum recurrence of prior psychiatric illnesses. For example, 21.4% of new mothers with a previous diagnosis of bipolar disorder and 13.3% with a previous depressive illness require postpartum admission for these conditions (Wisner et al., 2006). Considering these dangers of pregnancy, medical paternalism as a basis for denying tubal ligation access does not seem consistent with the Hippocratic Oath’s requirement that doctors “do no harm” to their patients.

Conclusion The issue of how medical paternalism impacts tubal ligation access is more than a question of mere birth control convenience; the decision to deny someone the procedure can rob them of their bodily autonomy and have lasting impacts on their well-being. This suggests that a policy change is necessary — patients, rather than their doctors, need to be responsible for weighing the risks of potential regret and making informed decisions. One of the voluntarily childless women Park (2002) interviewed demonstrated the conviction that could drive tubal ligation consultations going forward: “It’s my life. It’s what I want to do. I think I’ve learned not to apologize for it anymore” (p. 36). References Aslam, A., & Owen, C. M. (2013). Fashions change but tattoos are forever: Time to regret. British Journal of Dermatology, 169(6), 1364–1366. https://doi.org/10.1111/bjd.12489 Dye, J. L. (2010). Fertility of American women: June 2008. U.S. Census Bureau. https://www.census.gov/content/dam/Census/ library/publications/2010/demo/p20-563.pdf Eaton, L. (2003). African women at high risk of death in pregnancy. Student BMJ, 326(Suppl S4), 93–. https://doi. org/10.1136/sbmj.030493b EngenderHealth. (2002). Contraceptive sterilization: Global issues and trends. https://www.engenderhealth.org/pubs/family-

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planning/contraceptive-sterilization-factbook Gaitskell, K., Coffey, K., Green, J., Pirie, K., Reeves, G. K., Ahmed, A. A., Barnes, I., & Beral, V. (2016). Tubal ligation and incidence of 26 site-specific cancers in the Million Women Study. British Journal of Cancer, 114(9), 1033–1037. https://doi. org/10.1038/bjc.2016.80 Hillis, S. D., Marchbanks, P. A., Tylor, L. R., & Peterson, H. B. (1999). Poststerilization regret: Findings from the United States collaborative review of sterilization. Obstetrics & Gynecology, 93(6), 889–895. https://doi.org/10.1016/S0029-7844(98)00539-0 Lalonde, D. (2018). Regret, shame, and denials of women’s voluntary sterilization. Bioethics, 32(5), 281–288. https://doi. org/10.1111/bioe.12431 Mertes, H. (2017). The role of anticipated decision regret and the patient’s best interest in sterilisation and medically assisted reproduction. Journal of Medical Ethics, 43(5), 314–318. https:// doi.org/10.1136/medethics-2016-103551 Mosher, W. D., & Jones, J. (2010). Use of contraception in the United States: 1982-2008. U.S. Dept. of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics. https://www.cdc.gov/nchs/data/ series/sr_23/sr23_029.pdf Nussbaum, M. C. (2008). Who is the happy warrior: Philosophy poses questions to psychology. Journal of Legal Studies, 37(2), S81–S114. https://doi.org/10.1086/587438 Parikh, N., Norberg, M., Ingelsson, E., Cnattingius, S., Vasan, R., Domellöf, M., Jansson, J., & Bonamy, A. (2017). Association of pregnancy complications and characteristics with future risk of elevated blood pressure: The Västerbotten Intervention Program. Hypertension, 69(3), 475–483. doi: 10.1161/ HYPERTENSIONAHA.116.08121 Park, K. (2002). Stigma management among the voluntarily childless. Sociological Perspectives, 45(1), 21–45. https://doi. org/10.1525/sop.2002.45.1.21 Richie, C. (2013). Voluntary sterilization for childfree women: Understanding patient profiles, evaluating accessibility, examining legislation. The Hastings Center Report, 43(6), 36–44. https://doi.org/10.1002/hast.216 Thurman, A. R., & Janecek, T. (2010). One-year follow-up of women with unfulfilled postpartum sterilization requests. Obstetrics and Gynecology, 116(5), 1071–1077. https://doi. org/10.1097/AOG.0b013e3181f73eaa United States Department of Agriculture, Center for Nutrition Policy and Promotion. (2013). Expenditures on children by families, 2012. https://fns-prod.azureedge.net/sites/default/files/ expenditures_on_children_by_families/crc2012.pdf Wisner, K. L., Chambers, C., & Sit, D. K. Y. (2006). Postpartum Depression: A Major Public Health Problem. JAMA, 296(21), 2616. https://doi.org/10.1001/jama.296.21.2616

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On the Structure of Field Theories III BY EVAN CRAFT, PHD STUDENT, YALE UNIVERSITY Cover Image: Photo of the massive mural of the ATLAS detector at CERN Point 1 Image Source: CERN

Abstract We show that in Minkowski space, the gamma matrices are invariant under a certain group of permutations. This symmetry is then projected up to the curved geometry using the vierbein. We use this permutation group to construct a Galois corres-pondence which can also be projected up to the curved geometry using the vierbein.

Preliminary Remarks Galois theory is the study of symmetries. In particular, given a group of objects, it turns out that the set of all symmetries of that group of objects can be used to convey a message about the objects themselves. A simple example of a system with symmetries is that of a simple square. Rotating by 180, 270, and 360 degrees will leave the square invariant. There are a number of more complex examples in physics which are of interest. Notably are Noether’s symmetries of the action which make their way into Lagrangian Mechanics. Later, when 56

Feynman generalized to the Path Integral, we could then derive symmetries of this new action. More on this can be found in the references.

Symmetry in Flat Space The gamma matrices are invariant under a certain group of discrete permutations. In particular, we can define a permutation on the set of gamma matrices to be (2.1) Pγa = γb This is really just a permutation of the spacial indices so that (2.2) Pγa = γp(a) where of course in this example, (2.3) p(a) = b In general, the commutation relation will then become

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Figure 1: One of the early collision events with stable beams recorded by ATLAS on 23 April 2016, with two reconstructed muon candidates. Image Source: CERN

(2.4a) {Pγa, Pγb} = {γp(a), γp(b)}

(2.9b) {γμP, γvP} ≡ {eμaPγa, evbPγb}

(2.4b) {Pγa, Pγb} = 2ɳp(a)p(b)I

(2.9c) {γμP, γvP} ≡ eμaevb{Pγa, Pγb}

Now, if we focus on permutations which fix the time coordinate, i.e. where Pγt=γt [rather ρ(t) = t] then we have

(2.9d) {γμP, γvP} ≡ 2gμvI

(2.5) {Pγa, Pγb} = 2ɳabI since of course ɳxx = ɳyy= ɳzz and all of the off diagonal terms are zero. By the fixing of the spacial matrix, we also have that this relation is consistent. The set of all such permutations is the symmetric group S3. The general relation then becomes

So that each permutation of the flat space gamma matrices maps to the same spacetime. Failure of this symmetry in curved space One would wonder if the discrete symmetry of flat space can be projected up to curved space. In order for (2.10) {Pγμ, Pγv} = {γμ, γv}

(2.6) {Pγa, Pγb} = {γa, γb}

we must have

Hence these permutations are a symmetry of flat space in the sense that they preserve the anticommutation relation. Now the curved space gamma matrices are defined as

(2.11) gp(μ)p(v) = gμv

(2.7) γμ ≡ eμaγa

Isomorphisms

And we can derive that

(2.8) {γμ γv} ≡ 2gμvI Notice that this is invariant under permutations as (2.9) γμP ≡ eμaPγa

but this is only necessarily true for a certain class of metrics.

How could we then produce a symmetry of curved space? First, we can show that the flat space gamma matrices are linearly independent as assume (3.1) Aaγa = 0 then use the commutation relation implies (3.2) Aa = 0

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This proves that both the flat and curved space gamma matrices are linearly independent sets. Next, we have that the vierbien map is invertible by definition. in particular, if (3.3) e ⊢ Pγ = e ⊢ P'γ a

Operations Notice that each set of gamma matrices can be associated to an operator, namely (3.8) ∂ ⊢ {γa} ≡ {γa ∂a} or rather in a general curved space we have

then by invertibility

(3.9) D ⊢ {γμ} ≡ {γμDμ}

(3.4) Pγa = P'γa

where each derivative operator is the covariant derivative in that coordinate. In the flat case, we know that ∂ induces a one to one correspondence so that if P is a symmetry of the set of gamma matrices then ∂P∂-1 will be a symmetry of the set of derivative operators. This will therefore leave the object

so that (3.5) γp(a) = γp'(a) but since the gamma matrices are linearly independent this means (3.6) p(a) = p'(a) so that ρ = ρ'. What we have shown is that the set map {Pγa} → {e ⊢ Pγa} is a one to one correspondence. We can now find a symmetry of the second group as being (3.7) {γa} → {e ⊢ γa} so that if P is a symmetry of the first set then ePe1 will be a symmetry of the second set; rather, it will preserve the curved space anti-commutation relation. Hence the curved space gamma matrices also have a discrete symmetry group. These symmetry groups are isomorphic.

(3.10) D⋅ D ≡ (γa∂a)(γb∂b) = 1/2 {γa, γb}∂a∂b invariant, since the anti-commutation relation is left invariant. In a general curved space we will have (3.11) D⋅ D ≡ (Dμγμ)(Dvγv) = 1/2 {γμ, γv}DμDv + 1/2 γμ, γv[DμDv] The first term will be invariant permutations. And hence we know

under

(3.12) Sym(D⋅ D) ≡ 1/2 {γμ, γv}DμDv will be left invariant in any coordinate system, with symmetry group {DPD-1}.

Figure 2: Still from a numerical relativity simulation for GW190521 showing the gravitational waves just after merger, with the trajectories of the initial black holes and the horizon of the final black hole just visible in the center. Image Source: LIGO

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Galois Theory One could then look at subgroups of S3 and notice that certain permutations of gamma matrices are invariant under this group. In particular, look at the subgroup of S which fixes the first spatial coordinate. The invariant subgroup would be {γx , γy, γz} ∪ {γx , γy, γz}. Every subgroup of S corresponds to a specific set of gamma matrices. In particular, it is the image of that subgroup on the normal ordering of gamma matrices. So given the symmetry group, we can now turn the set of all permutations of gamma matrices into a sort of “field”. In particular, we must define the “product” of two sets of gamma matrices (4.1a) {γx , γy, γz} ★ {γx , γz, γy}

(4.8) 1/2 {γp(μ), γp'(μ)} DμDv = 1/2 {γp(μ) Dμ, γp'(μ) Dv} = 1/2 {γp'(μ) Dv, γp(μ) Dμ} = 1/2 {γp'(μ), γp(μ)} DvDμ And hence the Dirac operators are the solutions to the polynomials (4.9) Sym(D⋅ D) = DμDμ Notice that this product can be restricted solely to the gamma matrices by defining (4.10) γμ ★ γv ≡ 1/2 {γμ, γv} and hence (4.11) Sym(D⋅ D) = (γμ ★ γv)Dμ Dv and this is our polynomial

(4.1b) {γx , γy, γz} + {γx , γz, γy}

Field Operators

so that this product is abelian. One way to accomplish this is to define (4.2) q ∈ C(γ) = (αI, βγt) ⊗ ∑cabc(γa , γb, γc) | abc ∈ σ{a, b, c} where a normal Ô ∈ Ĉ = cI is simply some complex multiple of the identity matrix. From here, we define (4.3) D ⊢ q = αI + βγt + ∑cabc(γ ∂x, γ ∂y, γ ∂z) | abc ∈ σ{a, b, c} a

We will call this the operator representation. And we will later give meaning to the set C. Here, addition is naturally defined. For the rest of this section, we will work with simpleton objects such as (4.4) D ⊢ q = γp(μ)Dμ Building the Product To define the product of say D★D where of course we mean

We can consider the field Ĉ(γ) to be the set of all complex multiples of the identity operator, namely Ô ∈ Ĉ = cI. We can think of the gamma matrices extending this field to C so that the equation (4.12) γμ ★ γv ≡ 1/2 gμvI can be solved. In another light, we can think of this field being extended by the Dirac operators to Ĉ(D) so that the equation (4.13) D ★ D = DμDμ is solved.

Further Symmetries Notice that the gamma matrices are also invariant under uniform multiplication by -1. We can consider the set {-γt,-γz,-γx,-γy} to correspond to (x,z,y)(+,-) and hence the symmetry group S3 can be elevated to S5. References

(4.5) D = γp(μ)Dμ

Dirac, Paul Adrien Maurice. (1928). The Quantum Theory of the Electron. Proc. R. Soc. London A117, 610.

and

E. Wigner, Z. Phys. 53, 592.

(4.6) D' = γp'(μ)Dμ

Einstein, Albert. Sitz. Preuss. Akad. Wiss. Berlin 217.

we can take

Feynman, Richard P. (1948). Space-Time Approach to NonRelatavistic Quantum Mechanics. Rev. Mod. Phys. 20, 367.

(4.7) D ★ D' ≡ Sym (D⋅ D') = 1/2 {γp(μ), γp'(μ)} Dμ Dv

Feynman, Richard P. (1948). Space-Time Approach to Quantum Electrodynamics. Phys. Rev. 76, 769.

which is commutative since

Galois, Evariste. (2012). Ouvres mathematiques d’Evariste Galois. Société mathématique de France.

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Infeld, L., van der Waerden, B. (1933). Die Wellengleichung des Elektrons in der allgemeinen Relativitätstheorie. Sitz. Preuss. Akad. Wiss. Berlin 380. Noether, Emmy. Invariante Variationsprobleme, Nachr. d. Konig. Gesellsch. d. Wiss. zu Gottingen, Math-phys. Klasse, 235–257. Schrödinger, Erwin, Diracsches Elektron im Schwerefeld I, Sitz. Preuss. Akad. Wiss. Berlin 105. Tetrode, Hugo. (1928). Allgemein-relativistische Quantentheorie des Elektrons. Z. Phys. 50, 336.

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Natural Selection on Humans by Pathogens BY FRANKIE CARR ’22 Cover Image: A simplified scheme of human evolution from lower primates to modern man. Image Source: Wikimedia Commons

Natural Selection For many, the ideas of evolution and natural selection began with Charles Darwin. That, however, is not quite right. Among the first to argue the concept of species changing over time was Jean-Baptiste Lamarck in the early 1800s. Lamarck claimed that species reacted to their environments and used or neglected certain traits, strengthening those used and weakening those neglected. These strengthened traits would then be passed on to their descendants, causing species to become more complex over time (i.e., complex vertebrates arose from simpler creatures, like insects) (Burkhardt, 1970). After much debate and development of ideas, two British scientists, Charles Darwin and Alfred Russel Wallace, separately developed the idea of Natural Selection and eventually published a joint article on the matter (which included excerpts of Darwin’s soon to be famous On the Origin of Species) (Darwin & Wallace, 1858). Simply put, natural selection is an expansion and reevaluation of Lamarck’s idea of developed traits being passed onto future generations. However, instead of those traits being developed by the intentional actions of organisms, these traits are

a result of natural variation within a population. The environment (both abiotic and biotic) of the population will apply selective pressures, causing some traits to be more favorable than others. These organisms with these traits are deemed more fit and may be able to (1) survive due to their traits and/or (2) experience more reproductive success compared to organisms without the relevant trait(s). Thus, those who are more fit will live longer and have more children, causing the traits that contributed to their fitness to be passed on and eventually become the predominant version of those traits within the population (Darwin & Wallace, 1858). There are different kinds of natural selection. The selection can be described by the way in which the most common version of a given trait shifts. If the average shifts towards one extreme or the other (e.g., the development of incredibly large or small beaks), then the selection is said to be directional. If the average becomes more and more moderate and extreme versions of the trait are not preferred (e.g., the development of medium beaks), then the selection is said to be stabilizing. If the distribution becomes multimodal and versions of the trait at either extreme are common (e.g., DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

the development of incredibly large and small beaks), then the selection is said to be disruptive. The selection can also be described in the way in which the change in trait prevalence affects the population. If the trait shift results in longer lives and/or higher fertility, the selection is said to be positive. If the trait shift results in the death and/ or sterility of those bearing a trait, the selection is said to be negative. If the trait shift results in heterozygosity (i.e., an individual having two different alleles of a given gene), the selection is said to be balancing (Karlsson et al., 2014; Wade & Kalisz, 1990). A sudden, drastic change within an environment will likely cause some individuals within the population to perish. Those with favorable traits may survive, causing those favorable traits to become the most common ones within a single generation (Wade & Kalisz, 1990). One prevalent cause of such changes in an environment is the presence of pathogens. If a disease is able to exert selective pressure on a population (either by causing individuals to die before producing progeny and/or to not be able to produce progeny), resistance to such a disease is going to be advantageous and selected for. Using this idea, Fumagalli et al. demonstrated that pathogen-induced disease has been the most effective selection pressure in causing natural selection in the human population, resulting in the development and proliferation of diseaseresistant traits throughout the human population (Fumagalli et al., 2011). The ways that researchers have detected these traits include (1) comparing the allelic distribution of populations that are/ were affected by a given pathogen with those that are/were not (Karlsson et al., 2013, 2014; Kwiatkowski, 2005; Schliekelman et al., 2001) and (2) comparing the allelic distribution of a population in an area after an epidemic event with the distribution before that event (Immel et al., 2021; Karlsson et al., 2014).

Malaria Malaria is a blood-borne disease caused by the transmission of Plasmodium parasites (including P. vivax, P. ovale, and P. malariae; P. falciparum is responsible for the lethal condition) when an individual is bitten by an infected mosquito from the family Anopheles. Plasmodium organisms are protozoa (unicellular eukaryotes) and are obligate intracellular parasites that first infect liver cells and subsequently red blood cells (erythrocytes) where the parasites spend the rest of their life cycle. (Haldar & Mohandas, 2009; Karlsson et al., 2014; Kwiatkowski, 2005; Tuteja, 2007). Infected erythrocytes can accumulate in organs, placental tissue (leading to major SPRING AND SUMMER 2021

complications in pregnant women), and blood vessels. Additionally, the infection of these oxygen-transporting cells with the parasites occasionally results in anemia (a decrease in total erythrocytes or the amount of hemoglobin, the oxygen-binding molecule present in the cells, in the blood). These, combined with other complications, can lead to flu-like symptoms, difficulty breathing, vomiting and diarrhea, and even death (Haldar & Mohandas, 2009; Tuteja, 2007). Endemics of malaria have long plagued especially humid environments, where the Anopheles mosquito thrives. For example, in 2019, 94% of the world’s cases of malaria were in Sub-Saharan Africa (WHO, 2021). It has been estimated that Plasmodium parasites have been inflicting malaria on humans for the last 100,000 years. Having caused so many deaths for so long, the disease has impressed tremendous selection pressure on humans in affected areas (Karlsson et al., 2014; Kwiatkowski, 2005). One well-known result from the thousands of years of this selection pressure is the proliferation of Sickle Cell Anemia. Sickle Cell Anemia is common in those of African descent and is caused by having the HbS allele in the β-globin gene (HBB) gene. If a person is homozygous (i.e., both copies of the gene are the given allele) for the HbS allele, they suffer from Sickle Cell Anemia and their erythrocytes take on a characteristic sickle shape due to the severe misshaping of the hemoglobin molecules (see Figure 1 below). This sickling of the erythrocytes is quite dangerous and can lead to the accumulation of erythrocytes in blood vessels, potentially causing episodes of oxygen-deprivation. If a person is heterozygous for the allele, there is a low chance of suffering the consequences of developing malformed erythrocytes (due to only one copy of the gene producing the problematic version of the protein), but the amount of affected protein is still enough to hinder the infection of the cells with the Plasmodium parasites. Sickle Cell Anemia is a classic example of balancing selection, as it is beneficial for individuals to be heterozygous for the HbS allele (Karlsson et al., 2014; Kwiatkowski, 2005; Luzzatto, 2012). In addition to HbS, other alleles of HBB have arisen in response to malaria’s selection pressure and confer some resistance to the disease via balancing selection. One is HbC (which causes a disorder called Hemoglobin C Disease when a person is homozygous for the allele, resulting in mild anemia) and is somewhat common in those of Southeast and East Asian descent. Another is HbE (which causes Hemoglobin E Disease

"A sudden, drastic change within an environment will likely cause some individuals within the population to perish. Those with favorable traits may survive, causing those favorable traits to become the most common ones within a single generation"

Figure 1: Images of sickled (leftmost cell) and normal (right cells) red blood cells. Image Source: Wikimedia Commons

"Different MHC molecules (produced by different alleles of the different HLA and HLB genes) can present different kinds of antigens based on their amino acid components."

when a person is homozygous for the allele, resulting in mild hemolytic anemia and enlarged spleens) and is common amongst those with West African ancestry. The fact that these similar traits have arisen multiple times in places where malaria is endemic, provides evidence that their development and proliferation were driven by malaria (Kwiatkowski, 2005). Other examples of natural selection due to malaria’s selective pressure are the proliferation of G6PD Deficiency and Duffy Negative Blood. G6PD encodes the Glucose-6-Phosphate Dehydrogenase enzyme which is used in glycolysis and to help remediate oxidative stress by producing the electron donor/acceptor pair, NADP/NADPH. Throughout the protozoa’s growth cycle within the erythrocytes, they cause much oxidative stress to the cell. If a person is deficient in G6PD, due to any number of alleles (multiple have arisen in different places with heavy prevalence of malaria), the oxidative stress is too great and the infected erythrocytes die, preventing the proliferation of the parasites and thus the spreading of the disease to additional cells. In addition to the more-well known ABO and Rh+/- blood types, there are many other blood types, one of which relies on the presence of the Duffy antigen. This antigen is encoded by the FY gene and is a receptor for extracellular signals. Many people with ancestral ties to Sub-Saharan Africa (and, due to a newer, separate allele, Papua New Guinea) do not display this antigen due to deficiencies in the FY gene, resulting in Duffy Negative Blood. This is likely because P. vivax requires this antigen for entry into the cell, so those with Duffy Negative Blood are immune to infection with that parasite (Kwiatkowski, 2005).

Some immunologically important examples of selected traits include those in antigen presentation via MHC molecules. Antigens are individual molecules or pieces of molecules from foreign cells that infected cells as well as cells of the immune system display. They do so by attaching them to MHC molecules and presenting them on their cell surface. From there, the antibodyproducing B cells and infected cell-lysing T cells can recognize these antigens and mount an adaptive immune response. While erythrocytes do not display antigens on MHC molecules, the liver cells infected during the beginning of a malarial infection do. The HLA-B gene encodes a portion of one such MHC molecule. An allele of the gene, HLA-B53, is extremely common in West Africa and has an associated phenotype of heavily reduced chances of malaria infection. HLA-DRB1 is another such gene that produces a portion of an MHC molecule. HLA-DRB1*1302-DQB1*0501 is an allele prevalent in the West African nation of Gambia that confers some resistance to malaria. Different MHC molecules (produced by different alleles of the different HLA and HLB genes) can present different kinds of antigens based on their amino acid components. Thus, it is likely that these alleles confer the liver cells the ability to display a Plasmodium antigen more effectively and thus produce a robust immune response, helping to curtail the infection before it reaches the erythrocytes (Kwiatkowski, 2005). Further research should be conducted in nations where malaria is less prevalent (e.g., the United States, the United Kingdom, etc.) to investigate whether the lack of selection pressure by the disease, coupled with the selection pressure against the deleterious effects of Sickle Cell Anemia and its related diseases, has/will result in a decreased prevalence of these alleles.

Cholera Cholera is a disease caused by the bacterium Vibrio cholerae and presents as bouts of acute diarrhea, frequently leading to death by dehydration (historical data show a mortality rate of 50% and between 5-10% in more recent outbreaks) (Karlsson et al., 2013). Cholera is spread through ingestion of contaminated water, generally from the diarrheal fluids of the infected. The disease has historically plagued the Ganges River Delta and the Bay of Bengal, and much research has been done on the effects of the disease’s prevalence in this area (Deen et al., 2020; Karlsson et al., 2013). It has previously been shown that there is a connection between heightened risk of

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developing a severe case of choleric diarrhea and the possession of the O blood type (Barua & Paguio, 1977; Glass et al., 1985; Karlsson et al., 2013). Additionally, those with type A and B are at the lowest risk (Barua & Paguio, 1977; Deen et al., 2020), and those with type AB are at an intermediate level of risk (Deen et al., 2020). The exact reason for this connection is unknown, but it has been shown that in the Ganges River Delta, the prevalence of type O blood is the lowest in the world, serving as evidence of negative selection of the trait by Cholera (Karlsson et al., 2013, 2014). Other traits that seem to have been selected in the Ganges River Delta population include changes in the NF-kB pathway and inflammasome activation. These changes are seen in the genes PYCARD, IKBKG, RPS6KB2, and SNRNP200. Both systems are used by cells of the innate immune system for the detection of bacteria like V. cholerae in the body via TLR4 (a PPR, or Pattern Recognition Receptor, which is an extracellular receptor on innate immune cells used to detect pathogens). Additionally, there is evidence of selection within cAMP-mediated chloride ion secretion within the genes of three voltage-gated chloride ion channels: KCND2, KCNH5, and KCNH7. The activation of these and other similar channels by a toxin secreted by the bacterium is the mechanism behind the onset of the diarrhea. Thus, the development of these traits is an example of positive selection, possibly resulting in the development of quicker detection of the bacteria and the prevention of its method for bringing on its deadly diarrheal episodes (Karlsson et al., 2013, 2014).

Plague The Black Death epidemic that decimated AfroEurasia during the 14th century was caused by the bacterium Yersinia pestis (see Figure 2 below). Infection with this bacterium can result in one of three diseases (differentiated by their most characteristic symptom): bubonic plague, pneumonic plague, or septicemic plague. The Black Death epidemic ravaged Afro-Eurasia, resulting in the loss of approximately half of the population. While modern sanitation methods and antibiotics have vastly reduced the infection and mortality rates of these diseases, they still appear sporadically across the world (Immel et al., 2021; Prentice & Rahalison, 2007). Recent research compared the genomes of modern citizens of the small town of Ellwangen in Southern Germany with those from ancient samples of apparent plague victims buried there. In doing this analysis, the researchers discovered that the two populations were nearly

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genetically identical, except for differential allelic distributions in the immunologically important genes of FCN2 and NLRP14 genes along with the HLA and HLB complexes of genes, serving as evidence of positive selection on these newer traits and/or negative selection against the traits possessed by the plague victims (Immel et al., 2021). Much like what Karlsson et al. showed in their analysis of cholera, FCN2 and NLRP14 are genes related to a PRR and inflammasome complex, respectively, and thus the differential expression is likely related to developing a better detection of and activation against Y. pestis by the innate immune system (Immel et al., 2021; Karlsson et al., 2013, 2014). Similarly, selective pressure applied by the Black Plague to the HLA and HLB genes complexes is mirrored in the changes to the HLA genes which was seen in natural selection applied by Malaria in the Gambian population. Thus, the changes to these gene complexes also alter the MHC molecules seen on cells in this European population likely allowed for more effective presentation of antigens from Y. pestis to the T cells of the adaptive immune system (Immel et al., 2021; Kwiatkowski, 2005). Essentially, all the traces of natural selection detected by the researchers seem to have granted the immune systems of the affected individuals a better ability to sense and mount a defense against the offending bacterium (Immel et al., 2021).

HIV AIDS (Acquired Immunodeficiency Syndrome) is a disease that is defined as a near total loss of CD4+ T cells (with levels dropping from 1200800 cells/mm3 blood to less than 200 cells/mm3 blood). These cells are also called Helper T Cells and are responsible for activating and supporting other T and B cells during an immune response. Thus, this disease results in an incredible susceptibility to infection. The cause of AIDS is the infection of these CD4+ T cells with HIV (Human Immunodeficiency Virus; see Figure 3 below) resulting in the lysis of these cells due to the virus’s replication process (Klimas et al., 2008; Reiner, 2007; Schliekelman et al., 2001).

"Essentially, all the traces of natural selection detected by the researchers seem to have granted the immune systems of the affected individuals a better ability to sense and mount a defense against the offending bacterium"

HIV is a relatively new combatant to the field of immunological warfare, with it likely first infecting humans sometime in the early 1900s (Keele et al., 2006). In 1981, it was declared a pandemic and, unfortunately, it is still considered an ongoing pandemic today (Klimas et al., 2008). Due to this relatively short time frame, there has not been ample time for natural selection to occur. However, we may soon see the first signs of

Figure 2: An image of the Yersinia pestis bacterium from the digestive tract of an infected flea. Image Source: Wikimedia Commons

such selection in the predicted rise of prevalence of various alleles in the CCR5 gene (Lopalco, 2010; Schliekelman et al., 2001). CCR5 is a protein present on the extracellular membrane of CD4+ T cells (amongst others) and functions as a chemokine (a signaling molecule secreted by cells of the immune system) receptor. It also functions as one of the main entry points of HIV into these cells (Lopalco, 2010). The ∆32 allele is a version of the CCR5 gene that arose in the European population, possibly in response to the Black Death (although the previous study on natural selection by that disease yielded no evidence of a change in prevalence). The allele consists of a deletion of 32 nucleotides in the gene, resulting in a completely nonfunctional

CCR5 protein. It has been shown that individuals homozygous for this allele display significant decreased susceptibility (but not full immunity) to infection with HIV without any obvious drawbacks (Immel et al., 2021; Lopalco, 2010; Schliekelman et al., 2001). One team of researchers has predicted that similarly resistant alleles may proliferate in African populations, rising to a homozygous prevalence of 0.53 (and thus over half of the population being resistant to HIV infection) by the 22nd century (Schliekleman et al., 2001). Additionally, the ability of the ∆32 to confer resistance to infection has inspired some to try to develop anti-HIV therapies involving anti-CCR5 antibodies (Lopalco, 2010).

Conclusion

Figure 3: A colored microscopic image of an HIV-infected CD4+ T cell. Image Source: Wikimedia Commons

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What has been shown here is that many epidemic and pandemic level diseases have applied sufficient selection pressure (by killing and/or preventing reproduction by individuals) on the human population to cause natural selection. This natural selection generally presents itself in traits related to the immune system’s detection of the disease-causing pathogen or inhibiting the pathogen’s mechanism of entry/damage. However, what was not mentioned in this paper, and merits further research by others, is that these changed traits then applied/are applying selection pressure against the pathogens, driving them to develop traits that allow them to escape detection by the immune system or to regain their ability to enter and/or damage the body’s cells. Additionally, it is very likely that future research will be done on the effects of the ongoing COVID-19 pandemic on the human genome. Unfortunately, at least 4 million lives have already been lost to this disease. In spite of this loss, almost 200 million have been able to recover from the infection (WHO, 2021). While this is not meant to downplay the danger of the virus in any way, it is likely that many of the survivors of the disease possess slight differences in immunologically important genes or genes relating to the virus’s mechanism of infection/damage that helped them to survive. In surviving, they may pass those differences to their descendants, thus helping to shield future generations from the same desolation we have faced during the last year by deafening them from the SARS-CoV-2 virus (and, hopefully, related viruses that may arise). References Barua, D., & Paguio, A. S. (1977). ABO blood groups and cholera. Annals of Human Biology, 4(5), 489–492. https://doi. org/10.1080/03014467700002481 Burkhardt, R. W. (1970). Lamarck, evolution, and the politics of science. Journal of the History of Biology, 3(2), 275–298. https:// doi.org/10.1007/BF00137355 Darwin, C., & Wallace, A. (1858). On the Tendency of Species to form Varieties; and on the Perpetuation of Varieties and Species by Natural Means of Selection. Zoological Journal of the Linnean Society, 3(9), 45–62. https://doi. org/10.1111/j.1096-3642.1858.tb02500.x Deen, J., Mengel, M. A., & Clemens, J. D. (2020). Epidemiology of cholera—ScienceDirect. Vaccine, 38(Supplement 1), A31– A40. https://doi.org/10.1016/j.vaccine.2019.07.078 Fumagalli, M., Sironi, M., Pozzoli, U., Ferrer-Admettla, A., Pattini, L., & Nielsen, R. (2011). Signatures of Environmental Genetic Adaptation Pinpoint Pathogens as the Main Selective Pressure through Human Evolution. PLOS Genetics, 7(11), e1002355. https://doi.org/10.1371/journal.pgen.1002355

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Glass, R. I., Holmgren, J., Haley, C. E., Khan, M. R., Svennerholm, A., Stoll, B. J., Hossain, K. M. B., Black, R. E., Yunus, M., & Barua, D. (1985). Predisposition For Cholera of Individuals With O Blood Group Possible Evolutionary Significance. American Journal of Epidemiology, 121(6), 791–796. https://doi.org/10.1093/oxfordjournals.aje.a114050 Haldar, K., & Mohandas, N. (2009). Malaria, erythrocytic infection, and anemia. Hematology / the Education Program of the American Society of Hematology. American Society of Hematology. Education Program, 87–93. https://doi. org/10.1182/asheducation-2009.1.87 Immel, A., Key, F. M., Szolek, A., Barquera, R., Robinson, M. K., Harrison, G. F., Palmer, W. H., Spyrou, M. A., Susat, J., KrauseKyora, B., Bos, K. I., Forrest, S., Hernández-Zaragoza, D. I., Sauter, J., Solloch, U., Schmidt, A. H., Schuenemann, V. J., Reiter, E., Kairies, M. S., … Krause, J. (2021). Analysis of genomic DNA from medieval plague victims suggests long-term effect of Yersinia pestis on human immunity genes. Molecular Biology and Evolution, msab147. https://doi.org/10.1093/molbev/ msab147 Karlsson, E. K., Harris, J. B., Tabrizi, S., Rahman, A., Shlyakhter, I., Patterson, N., O’DusHLAine, C., Schaffner, S. F., Gupta, S., Chowdhury, F., Sheikh, A., Shin, O. S., Ellis, C., Becker, C. E., Stuart, L. M., Calderwood, S. B., Ryan, E. T., Qadri, F., Sabeti, P. C., & LaRocque, R. C. (2013). Natural Selection in a Bangladeshi Population from the Cholera-Endemic Ganges River Delta. Science Translational Medicine, 5(192), 192ra86. https://doi.org/10.1126/scitranslmed.3006338 Karlsson, E. K., Kwiatkowski, D. P., & Sabeti, P. C. (2014). Natural selection and infectious disease in human populations. Nature Reviews Genetics, 15(6), 379–393. https://doi. org/10.1038/nrg3734 Keele, B. F., Van Heuverswyn, F., Li, Y., Bailes, E., Takehisa, J., Santiago, M. L., Bibollet-Ruche, F., Chen, Y., Wain, L. V., Liegeois, F., Loul, S., Ngole, E. M., Bienvenue, Y., Delaporte, E., Brookfield, J. F. Y., Sharp, P. M., Shaw, G. M., Peeters, M., & Hahn, B. H. (2006). Chimpanzee Reservoirs of Pandemic and Nonpandemic HIV-1. Science (New York, N.Y.), 313(5786), 523–526. https://doi.org/10.1126/science.1126531 Klimas, N., Koneru, A. O., & Fletcher, M. A. (2008). Overview of HIV. Psychosomatic Medicine, 70(5), 523–530. https://doi. org/10.1097/PSY.0b013e31817ae69f Kwiatkowski, D. P. (2005). How Malaria Has Affected the Human Genome and What Human Genetics Can Teach Us about Malaria. American Journal of Human Genetics, 77(2), 171–192. Lopalco, L. (2010). CCR5: From Natural Resistance to a New Anti-HIV Strategy. Viruses, 2(2), 574–600. https://doi. org/10.3390/v2020574 Luzzatto, L. (2012). Sickle Cell Anaemia and Malaria. Mediterranean Journal of Hematology and Infectious Diseases, 4(1), e2012065. https://doi.org/10.4084/MJHID.2012.065 Prentice, M. B., & Rahalison, L. (2007). Plague. The Lancet, 369(9568), 1196–1207. https://doi.org/10.1016/S01406736(07)60566-2 Reiner, S. L. (2007). Development in Motion: Helper T Cells at Work. Cell, 129(1), 33–36. https://doi.org/10.1016/j. cell.2007.03.019

Schliekelman, P., Garner, C., & Slatkin, M. (2001). Natural selection and resistance to HIV. Nature, 411(6837), 545–546. https://doi.org/10.1038/35079176 Tuteja, R. (2007). Malaria − an overview. The FEBS Journal, 274(18), 4670–4679. https://doi.org/10.1111/j.17424658.2007.05997.x Wade, M. J., & Kalisz, S. (1990). The Causes of Natural Selection. Evolution, 44, 1947–1955. https://doi. org/10.1111/j.1558-5646.1990.tb04301.x WHO. (2021). Fact sheet about Malaria. https://www.who.int/ news-room/fact-sheets/detail/malaria WHO. (2021). WHO Coronavirus (COVID-19) Dashboard. From https://covid19.who.int

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The Impact of Mozart’s Music on Epileptic Patients BY GEORGIA DAWAHARE ’23 Cover Image: Portrait of Wolfgang Amadeus Mozart (1756-1791). Mozart is one of the greatest musical composers of all time, and his music continues to influence the world today. In 1993, Rauscher et al. found surprising research results that suggested that Mozart’s music (K448) improves spatial reasoning skills and has aptly been named the Mozart Effect Source: Wikimedia Commons, Created by: Edward Lehmann

Introduction Wolfgang Amadeus Mozart is widely considered one of the greatest musical composers of all time. Starting his career as a four-fold infant prodigy (harpsichordist, violinist, organist, composer), Mozart composed more than 600 pieces during his short lifetime of 35 years (TIME, 1938; Britannica, n.d.). While Mozart was indeed a genius whose music inspired many, he could never have predicted the effect his work would one day have on babies and epileptic patients. In 1993, Rauscher, Shaw, and Ky made the claim that after listening to the first movement “allegro con spirito” of the Mozart Sonata for Two Pianos in D major (K448), subjects with epilepsy showed significantly better spatial reasoning skills. In the years following, commercial shelves were flooded with products incorporating Mozart’s music, targeting eager parents-to-be and promising improved childhood intelligence. In 1998, the governor of Georgia, Zell Miller, escalated matters by mandating that mothers of newborns in the state be given classical music CDs to foster their offspring’s intelligence (Swaminathan,

n.d., Pietschnig et al., 2010). Several studies have attempted to replicate Rauscher et al.’s study since then, but they have produced mixed results. However, while there is little evidence for a specific, performance-enhancing Mozart effect, two researchers have recently conducted a systematic review of works related to the effect of Mozart’s music on epilepsy. Based on the review, the researchers found music therapy to be a legitimate non-invasive approach that could serve as a complementary form of treatment for epilepsy and epileptiform discharges (Sesso & Sicca, 2020).

The Mozart Effect In the original study that gave birth to the Mozart effect, three scientists at the Center for the Neurobiology of Learning and Memory at the University of California performed an experiment in which 36 college students were each given three sets of standard IQ spatial reasoning tasks (Rauscher et al., 1993). Each task was preceded by 10 minutes of either (1) listening to Mozart’s DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

sonata for two pianos in D major (K448), (2) listening to a relaxation tape, or (3) silence. The researchers observed improved performance for the three tasks immediately following the Mozart tape compared to the second two treatments. The students’ spatial reasoning skills were tested using the Stanford-Binet intelligence scale. To assess the impact of the scores, Rauscher et al. translated the mean standard age scores (SAS) to spatial IQ scores, concluding with a score of 119 for the first group, 111 for the second, and 110 for the third (1993). These results indicate that the IQs of subjects participating in the music condition were 8 - 9 points above their IQ in the other two conditions. The researchers acknowledged that since they only used one musical sample by one composer, a variety of composers and pieces should be an area of future study to corroborate their findings (Rauscher et al., 1993). After the publication of this controversial study, the Mozart effect has been subject to intense skepticism. A meta-analysis published by Pietschnig et al. in 2010 looked at 39 different studies on the Mozart effect to determine whether or not a Mozart effect exists. The study found little support for a Mozart effect in published and unpublished work. While the results of the published works indicate a positive, significant effect of exposure to K448 when compared to no stimulus at all on spatial task performance, observed effects were small in size. Additionally, exposure to other musical stimuli compared to exposure to no stimulus at all yielded an overall effect of about the same size as K448’s effect (Pietschnig et al., 2010). More importantly, however, the study found strong evidence for publication bias for the magnitude of the effect of studies that compared samples exposed to the Mozart sonata and samples exposed to no stimulus at all. Overall effects seem to be inflated in published and popular studies when compared to unpublished studies and those with less attention that use the same conditions. This discrepancy suggests that studies showing strong effects in expected directions tend to be published more often, quicker, and more prominently (Pietschnig et al., 2010). In the process of attempting to prove the positive effect of Mozart’s music on spatial-temporal reasoning, scientists stumbled upon a totally unrelated but groundbreaking finding in studies with epileptic patients. In 1998, 23 of 29 patients with focal discharges (bursts of generalized spike and wave complexes on electroencephalograms, or EEGs) who listened to the Mozart piano sonata K448 experienced a significant decrease in epileptiform activity (Hughes et al., 2016).

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The Science of Epilepsy Epilepsy is one of the most common neurological diseases of the brain and is characterized by an enduring predisposition to generate seizures. Those suffering from the condition face the neurobiological, cognitive, psychological, and social consequences of seizure recurrences. The prevalence and incidence of epilepsy are slightly higher in men compared to women and tend to peak in the elderly, reflecting the higher frequency of stroke, neurodegenerative diseases, and tumors in this age-group (Beghi, 2020). Epileptic seizures are recurrent paroxysmal events characterized by stereotyped behavioral alterations resulting from underlying neural mechanisms of the disease (Beghi, 2020). While all people with epilepsy experience seizures, not all individuals with seizures have epilepsy. According to the International League against Epilepsy (ILAE), epilepsy is defined by any of the following conditions: (1) at least two seizures without apparent cause occurring more than 24 hours apart, (2) one unprovoked seizure and a probability of further seizures similar to the general recurrence risk (at least 60%) after two unprovoked seizures, occurring over the next ten years, and (3) diagnosis of epilepsy syndrome (Fisher et al., 2014). Seizure onset can be focal (seizures arising in one hemisphere of the brain), generalized (seizures originating in both hemispheres simultaneously), or unknown (Fisher et al., 2017). Core to the pathology of epilepsy is the atypical increase or decrease in neural activity that provokes abnormal brain function. Regional fluctuations in neuronal activity tend to vary between generalized, absence, and focal seizures (Cavanna & Ali, 2011).

"In the process of attempting to prove the positive effect of Mozart’s music on spatial-temporal reasoning, scientists stumbled upon a totally unrelated but groundbreaking finding in studies with epileptic patients."

Generalized tonic-clonic seizures (GTCS) or “grand mal” seizures are characterized by abnormal bi-hemispheric neuronal discharge generating complete unresponsiveness and convulsions. The sudden tonic phase of these seizures comprises of sustained axial muscle (muscles of the trunk or head) contraction, upward eye deviation, and pupillary dilation, represented by by 10-20 seconds of high frequency electroencephalographic (EEG) activity which is indicative of abnormal brain activity. The “clonic” portion refers to rhythmic limb contractions accompanied by repetitive spikes in EEG activity (Cavanna & Ali, 2011). Blood flow and metabolic mappings of GTCS indicate that specific brain regions intensely reject the idea of participating with the whole brain. Signal photon emission computerized tomography (SPECT) studies of 71

cerebral blood flow found increased blood flow in the thalamus, brainstem, and portions of the cortex during GTCS, indicating significant stress in these areas (Figure 1). The thalamus and cortex play a large role in sensation and sensation interpretation while the brain stem functions to relay information from the brain to the body and vice versa. Conversely, decreases in cerebral blood flow were seen during the seizure period in the cingulate gyrus which helps regulate emotions and pain (Cavanna & Ali, 2011). The focal disruption in GTCS of these loci, together with effects on related sub-cortical structures, yield the intense and persevering impaired consciousness typical of GTCS. Despite these disruptions, there is relative sparing of the intervening regions of the primary sensory and motor cortices (Cavanna & Ali, 2011). Absence seizures are typified by sudden onset of blank staring and unresponsiveness, usually lasting 5-10 seconds. Eyelid fluttering and quick, involuntary muscle jerks called myoclonic jerks are common. Yet, the motor manifestations of absence seizures are subtle, allowing absence seizures to pose as the most “transparent” or unnoticeable form of seizure, or ictal, impaired consciousness (Cavanna & Ali, 2011). Absences are generated through abnormal EEG oscillations in the cortico-thalamic network (Figure 2). Although absences are regarded as highly similar to generalized seizures, preliminary investigation through functional magnetic resonance imaging (fMRI) with simultaneous EEG recordings (EEGfMRI) has verified that generalized spike-wave seizures (seizures which produce a specific type of EEG signature that is indicative of absence epilepsy episodes) selectively involve particular networks whilst sparing others. Specifically, improved spatial and temporal resolution has led to the identification of bilateral thalamic activation, and cortical signal decrease in various association areas (areas that form connections between sensory and motor areas) (Cavanna & Ali, 2011). Complex partial seizures usually last between 15 seconds and 3 minutes. Characteristically, consciousness is initially spared, but seizure progression brings variable loss of contact with the environment; the most profound impairment typically occurs late in the seizure, persisting for several minutes post-ictally. The temporal lobe, most commonly associated with auditory processing and memory encoding, is the original seizure focus in ~80% of patients with complex partial seizures (Cavanna & Ali, 2011). As the seizure evolves, epileptic patients

experience clinical manifestations ranging from affective, mnemonic, and composite perceptual phenomena. Certain components of the medial temporal lobe such as the amygdala have been related to the affective component of experiential phenomena. However, the vast array of experiential phenomena indicates the recruitment of wider neural networks beyond the temporal lobe (Cavanna & Ali, 2011). Scientists hypothesize that abnormal activity, which disseminates into diffuse inhibition of the frontoparietal cortex, in the midline cortical structures (upper brainstem-diencephalon activating systems like the thalamus and hypothalamus) causes loss of consciousness during temporal lobe seizures (Cavanna & Ali, 2011).

Neurostimulation through Sonatas In an attempt to understand the relation between the Mozart effect and epileptic treatment, studies have found that exposure to K448 effectively decreases interictal spikes in children with different epileptic seizure types. One study in 2010 enrolled 58 Taiwanese children with epilepsy and used a continuous EEG to record and compare the frequencies of discharge before, during, and after exposure to K448 (Lin et al., 2010). Interictal discharges were reduced in most (81%) patients as they listened to K448. Patients with generalized or central discharge showed the most improvement. In most patients (76.1%), the decrease in epileptiform discharges continued after the music ended (Lin et al., 2010). Despite positive results, Lin et al. neglected to use control music, casting a marginal amount of doubt on their results and attempt to remove a possible placebo effect. Fortunately, other studies have investigated the effect of Mozart music as well as control music on epilepsy. In 2018, 45 children (with a range of 2-18 years and a mean of 7 years 10 months) were recruited based on previous EEGs performed while the children were awake in which the report stated that frequent epileptic discharges were present (focal or generalized; Grylls et al.). Patients had to try and maintain a constant state of awareness while they were exposed to five musical treatments with no breaks in between, each lasting five minutes: 1) before Mozart music (baseline), 2) during Mozart music (K448), 3) after Mozart music/before control music, 4) during control music, and 5) after control music. Experimenters used age-appropriate control music depending on what parents listed as music the children would like to listen to in

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order to make enjoyment of control music as constant a factor as possible. Of the 45 patients included in the study, 23 female and 22 male, 24 had epilepsy with structural/unknown etiology and 21 had genetic etiology (Grylls et al., 2018). The researchers found a significant decrease in epileptic activity in children during the Mozart listening period compared to the baseline. More interestingly, the study found no significant decrease in epileptiform EEG activity during or after listening to the control music compared to the baseline. This ultimately supports the idea that this effect is unique to Mozart, or at least to similarly structured music (Grylls et al., 2018). The studies discussed provide significant evidence supporting the existence of a Mozart effect related to epilepsy, but studies of the Mozart effect often produce conflicting results. Two Italian researchers, Dr. Gianluca Sesso and Dr. Federico Sicca from the University of Pisa have recently conducted a systematic review of works related to the effect of Mozart’s music on epilepsy. Working according to accepted standard methods for analyzing clinical treatment, the scientists studied 147 published research articles and ultimately selected 12 pieces of research that represented the best available science on the effect of Mozart’s music on epilepsy (Neuroscience News, 2020). Nine meta-analyses showed significant reductions in seizures and IED (interictal epileptiform discharge) frequencies after long-term music treatment and in IED frequency during and after a single music stimulus (Sesso & Sicca, 2020). They found that listening to Mozart, especially on a daily basis, led to a significant reduction in epileptic seizures and also to a reduced frequency of abnormal brain activities (interictal epileptiform discharges) in epileptic patients. These effects occurred after a single listening session and were maintained after a prolonged period of treatment. The metaanalysis indicates that a period of listening to Mozart can cause an average reduction in epileptic seizures ranging from between 31% and 66%, but this varies from person to person and according to the music stimulus used (Neuroscience News, 2020).

sex and race (Beghi, 2020; Neuroscience News, 2020). A recent meta-analysis revealed that Mozart music could be an effective, non-invasive, and prolonged method of neurostimulation, reducing the frequency of epileptic seizures, even in hard-to-treat patients (Neuroscience News, 2020). Dr. Sesso, one of the authors of the metaanalysis, explained that “All cultures have music, so it obviously fulfills some psychological need. The mechanisms of the Mozart effect are poorly understood. Obviously, other music may have similar effects, but it may be that Mozart’s sonatas have distinctive rhythmic structures which are particularly suited to working on epilepsy” (Neuroscience News, 2020). Indeed, other studies have used Mozart’s K448 to demonstrate the power of music to produce positive effects in epileptic patients, particularly children. In order to harness the Mozart effect as a brain stimulation technique in the treatment of epilepsy in clinical settings, however, the exact mechanism of the Mozart effect on the brain must be understood (Neuroscience News, 2020). In the near future, more consistent and reproducible results will have to determine the effects of music on the mind. References Beghi, E. (2020). The Epidemiology of Epilepsy. Neuroepidemiology, 54(2), 185–191. https://doi. org/10.1159/000503831 Cavanna, A. E., & Ali, F. (2011). Epilepsy: The Quintessential Pathology of Consciousness. Behavioural Neurology, 24(1), 3–10. https://doi.org/10.1155/2011/374507 Fisher, R. S., Acevedo, C., Arzimanoglou, A., Bogacz, A., Cross, J. H., Elger, C. E., Engel, J., Forsgren, L., French, J. A., Glynn, M., Hesdorffer, D. C., Lee, B. I., Mathern, G. W., Moshé, S. L., Perucca, E., Scheffer, I. E., Tomson, T., Watanabe, M., & Wiebe, S. (2014). ILAE official report: A practical clinical definition of epilepsy. Epilepsia, 55(4), 475–482. https://doi.org/10.1111/epi.12550 Fisher, R. S., Cross, J. H., French, J. A., Higurashi, N., Hirsch, E., Jansen, F. E., Lagae, L., Moshé, S. L., Peltola, J., Roulet Perez, E., Scheffer, I. E., & Zuberi, S. M. (2017). Operational classification of seizure types by the International League Against Epilepsy: Position Paper of the ILAE Commission for Classification and Terminology. Epilepsia, 58(4), 522–530. https://doi.org/10.1111/ epi.13670 Grylls, E., Kinsky, M., Baggott, A., Wabnitz, C., & McLellan, A. (2018). Study of the Mozart effect in children with epileptic electroencephalograms. Seizure, 59, 77–81. https://doi. org/10.1016/j.seizure.2018.05.006

Conclusion Epilepsy is a surprisingly common neurological disease, affecting just under 1 person for every hundred worldwide. It is characterized by chronic seizures and affects all populations regardless of

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Hughes, D. J. R., Daaboul, Y., Fino, J. J., & Shaw, G. L. (2016). The “Mozart Effect” on Epileptiform Activity: Clinical Electroencephalography. https://doi. org/10.1177/155005949802900301 Is the “Mozart Effect” Real? New Analysis Indicates That Music Can Help Epilepsy. (2020, September 12). Neuroscience News.

https://neurosciencenews.com/mozart-effect-epilepsy-17012/ Lin, L.-C., Lee, W.-T., Wu, H.-C., Tsai, C.-L., Wei, R.-C., Jong, Y.-J., & Yang, R.-C. (2010). Mozart K.448 and epileptiform discharges: Effect of ratio of lower to higher harmonics. Epilepsy Research, 89(2), 238–245. https://doi.org/10.1016/j. eplepsyres.2010.01.007 Mozart Biography. (1938). TIME Magazine, 32(13), 32–32. Pietschnig, J., Voracek, M., & Formann, A. K. (2010). Mozart effect–Shmozart effect: A meta-analysis. Intelligence, 38(3), 314–323. https://doi.org/10.1016/j.intell.2010.03.001 Rauscher, F. H., Shaw, G. L., & Ky, C. N. (1993). Music and spatial task performance. Nature, 365(6447), 611–611. https:// doi.org/10.1038/365611a0 Sesso, G., & Sicca, F. (2020). Safe and sound: Meta-analyzing the Mozart effect on epilepsy. Clinical Neurophysiology, 131(7), 1610–1620. https://doi.org/10.1016/j clinph.2020.03.039 Swaminathan, N. (n.d.). Fact or Fiction?: Babies Exposed to Classical Music End Up Smarter. Scientific American. Retrieved October 13, 2020, from https://www.scientificamerican.com/ article/fact-or-fiction-babies-ex/ Torrico, T. J., & Munakomi, S. (2020). Neuroanatomy, Thalamus. In StatPearls. StatPearls Publishing. http://www.ncbi. nlm.nih.gov/books/NBK542184/ Wolfgang Amadeus Mozart | Biography, Facts, & Works. (n.d.). Encyclopedia Britannica. Retrieved October 13, 2020, from https://www.britannica.com/biography/Wolfgang-AmadeusMozart

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Big Pharma Sustainability BY JOHN ZAVRAS '24 Cover Image: Sustainability In the Pharmaceutical Industry Image Source: Flickr; Creator: Joshua Eaves

Introduction Sustainability is a broad term. In its most basic form, it entails meeting the needs of the present without compromising the needs of future generations (UCLA). Although it used to be a strictly environmental concept and was centered around maintaining an ecological balance, today it means far more to a much larger audience, ranging from common citizen to companies and corporations all over the world (UCLA). Gone are the days where sustainability was just a worry of energy companies, governments, and environmentalists. Sustainability now has three working parts: environmental sustainability, social sustainability, and economic sustainability (UCLA). Each division is unique, but all three are interconnected and necessary in creating a “thriving, healthy, diverse and resilient” world (UCLA). One of the largest industries affected by this shift in sustainability is the pharmaceutical industry. Sustainability is built on the principle that resources are finite (Catino). For far too long, drug development was not only extremely resource-exhausting, but also evaded criticism due to its essential role in human health and safety (Catino). It was not until recently that

the healthcare sector faced increased demands to change their ways and make sustainability an industry norm (Catino). This publication provides a glimpse into the bright future of pharmaceutical sustainability and will explain why sustainability is of upmost importance, as well as address the leading motivations that spurred change in the pharmaceutical industry. The major trends will be outlined, and a case study of one particular company paving the way for the pharmaceutical industry will be explored.

Environmental Sustainability Drugs and medicine have been around for many millennia. From the use of pomegranates to kill parasitic worms in Ancient Egypt, to the development of advanced mRNA vaccines to combat the COVID-19 global pandemic, medicine has always been used to preserve human life (Arnold). As is generally the case, at least in modern times, there are strict rules and regulations about putting foreign substances in someone’s body to make sure medications are safe and effective for humans (Arnold). But what about the environment?

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Figure 1: The Three Spheres of Sustainability: Environmental, Social, and Economic Image Source: Johann Dréo

Most pharmaceuticals are chemically potent, as they are created to deliver biological and physiological effects (Arnold). Human medications may act on non-target species, and pharmaceuticals have already infiltrated a variety of habitats and ecological communities (Arnold). The near extinction of Asian vultures following unintended consumption of Diclofenac (short description of what this drug is in these parentheses) and other similar cases act as proof of the environmental dangers of pharmaceutic chemicals (Arnold). There is a need to protect not just ourselves, but also the Earth at large. This realization has spurred many industry trends surrounding environmental sustainability. First among these is achieving carbon neutrality and using renewable energy resources (*). Many companies have announced ambitious commitments to become carbon neutral and shift to 100% renewable resources in the near future (Zavras, 2021). One notable pharmaceutical giant that has made the commitment is Johnson & Johnson, which hopes to achieve carbon neutrality by 2030 (Zavras, 2021). Managing and limiting water resources is also a major trend. This stems from the fact that water is a critical material used in all phases of pharmaceutical manufacturing, such as “formulation, rinsing, sanitizing and cleaning” (Watertechonline). Water is also a direct ingredient in many drugs (Watertechonline). Companies are increasingly becoming conscious of the amount of water they use and vowing to reduce water usage whenever possible(Zavras, 2021). Making sure the water used in this process does not runoff and adversely impact nearby communities is another major industry goal (Zavras, 2021). More generally, the ethical disposure of waste and SPRING AND SUMMER 2021

toxic materials is also a major concern (Zavras, 2021). According to the U.S. Geological Survey, many of the 4,000 prescribed human and animal health medications end up in the environment (USGS). Big pharmaceutical companies are investing a lot of research and development into risk assessments and creating the most ethically sound disposal techniques, especially when dealing with antibiotics (Zavras, 2021). A good example of this is Pfizer, a key member of the antimicrobial resistance industry, which is actively running wastewater analysis campaigns in all of its major powerplants around the world (Zavras, 2021). Another issue with pharmaceutical pollution is that pharmaceutical production plants are not the only way pharmaceuticals infiltrate ecosystems. Antibiotics and drugs are used in the livestock industry, and drugs like acetaminophen, caffeine, cotinine, diphenhydramine, and carbamazepine have been found in bodies of water that are downstream from animal-feeding centers (USGS). Also, drugs that are not completely metabolized by humans are excreted, and many of these drugs pass through sewage-treatment plants and end up in communities (USGS).

"A good example of this is Pfizer, a key member of the antimicrobial resistance industry, which is actively running wastewater analysis campaigns in all of its major powerplants around the world"

Social Sustainability But, as stated earlier, sustainability does not just refer to the environment. A new division of sustainability, known as social sustainability, has everything to do with people. According to the UN global compact, social sustainability is about controlling the effects of business outcomes on people. Social sustainability first became popular after the 2005 World Summit of Social Development, where sustainability was considered in three separate categories (World Energy Foundation). Companies have a lot 77

Figure 2: While sunrays can be truly beautiful, the UV rays emitted from the hits the DNA in the skin cells and can break at connection points. This changes the message of the DNA to reproduce over and over, leading to a tumor. Image Source: Pixabay

"A remarkable amount of the top pharmaceutical companies in the E.U. have pledged to meet all seventeen E.U. SDG’s, which target a wide array of social issues designed to make the world a better place"

of impact on people, namely their employees, customers, and competitors. They have a duty to satisfy the needs of the humans they serve. This means that external social pressure can also be a way of incentivizing pharmaceutical companies to adopt more sustainable practices. One movement in the pharmaceutical industry regarding social sustainability is engagement in global and local communities (Zavras, 2021). Many pharmaceutical companies are committed to delivering their products to under-served communities across the globe to contribute to a healthier and more informed world (Zavras, 2021). Companies are also actively promoting and encouraging volunteering and philanthropy amongst their employees, which creates a positive impact on society (Zavras, 2021). Diversity and inclusion is another topic that falls under social sustainability (Zavras, 2021). Treating employees and customers with fairness is critical for a business to be sustainable (Zavras, 2021). Some of the methods companies employ include factoring in diversity into the recruiting process and making sure there is an even split between men and women in key leadership positions and corporate executive committees (Zavras, 2021). As of now, most pharmaceutical companies have not met these goals but have plans on meeting them within the next decade. Sanofi pharmaceuticals, for example, has a goal to have a 50:50 split between men and women in the company’s top 2,000 leadership positions by 2025 (Zavras, 2021). The European Union lists seventeen sustainability goals that participating companies must work toward, and many of these goals pertain to social

sustainability (UNSDG). Among these include ensuring peace, justice, and strong institutions; reduced inequalities; and decent work conditions (UNSDG). A remarkable amount of the top pharmaceutical companies in the E.U. have pledged to meet all seventeen E.U. SDG’s, which target a wide array of social issues designed to make the world a better place (Zavras, 2021).

Economic Sustainability Economic sustainability, the third division of sustainability, promotes the efficient and responsible use of monetary resources, which is critical to a business’ livelihood in a competitive market (Tatum). Because economic growth lies under economic sustainability, investing profits back into research and development benefits both healthcare and the capitalistic economy (Tatum). A business that is trustworthy, promotes quality ethics, and helps the local and global economy has a greater chance at remaining stable and continuing to grow as time goes on. One key trend involving economic sustainability in the pharmaceutical industry is transparency (Cromer). Disclosing trial information helps promote a stronger understanding of drugs and diseases (Cromer). This information can then strengthen pharmaceutical advancement and optimize the efficiency of clinical trial participants, meaning there would be fewer patients having to volunteer in clinical trials that are destined to fail (Cromer). Not only are companies abiding by the legal and global registry requirements, but many have made promises to disclose more information than required and have done so (*). This is especially commendable when sharing negative or poor trial results, as no company enjoys publicizing their failures (Cromer).

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Figure 3: United Nations 17 Sustainable Development Goals. Image Source: Flickr

Finally, moral and trusting partnerships are becoming an industry standard (Zavras, 2021). Pharmaceutical companies have the ability to control the environmental impact and ecological footprint of their own operations, but it is difficult for them to oversee the entirety of their supply chains, which do not fall solely under their jurisdiction (Zavras, 2021). Ensuring that company partners adopt the same sustainability programs is one way to ensure that company sustainability goals are being met – not just internally, but in all facets of the drug distribution process (Zavras, 2021). Auditing business-critical suppliers is another way to accomplish this (Zavras, 2021).

Case Study - Informa Now that the major industry trends have been established, it is important to take a look at one company putting these trends to practice. Informa, a pharmaceutical intelligence company based out of the U.K., has over twenty products aimed at helping pharmaceutical and biotech companies get drugs to market faster (Informa). As an intern at Informa, I had a lot of exposure to the industry trends, as I had the opportunity to work for Informa’s Head of Insight who also leads their sustainability efforts. I was able to see firsthand the positive impact Informa’s sustainability efforts have on the environment, its employees, and global communities. Informa recently created “Faster Forward,” a project aimed at accelerating the sustainable change in its business and the specialist markets it serves (FasterForward). This project including many initiatives that will be

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discussed in the following paragraph. Some of these initiatives include becoming carbon neutral, enabling one million disconnected people around the world to access their networks and knowledge, and contributing $5 billion per year in value for host cities (FasterForward). These goals are designed to be met by 2025, and Informa is continuously working to make these goals a reality (FasterForward). Informa’s pharma intelligence, highly specialized data and information about the pharmaceutical industry, was a key reason why Moderna was able to receive Emergency Authorization by the FDA for their COVID-19 vaccine in such little time. Moderna received their authorization in only a couple of months, while it usually takes companies multiple years to receive full FDA approval.

Conclusion In conclusion, the pharmaceutical industry has taken several huge steps forward to address sustainability. These efforts fall within three divisions of sustainability – environmental, social, and economic. While the industry is trending in the right direction, it is important that it continues to improve sustainability practices. The pharmaceutical industry alone still spends more than $1 billion on energy consumption annually, which is about 55% more energy than the energy used by the automotive industry (centrica). In

order to make serious progress, pharmaceutical companies will need to exceed the ambitious goals they have set for the next decade and continue setting more milestones for the future. References A brief history of sustainability. The World Energy Foundation. (2014, August 20). https://theworldenergyfoundation.org/abrief-history-of-sustainability/. Arnold, K. (2013). Assessing the exposure risk and impacts of pharmaceuticals in the environment on individuals and ecosystems. Biology Letters. https://royalsocietypublishing.org/ doi/10.1098/rsbl.2013.0492. Catino, Alex. THE Pharmaceutical Industry’s Role in the Global- Aptar. www.aptar.com/wp-content/uploads/2020/10/ Oct_2020_ACatino_The-Pharma-industry-role-in-the-globalenvironmental-sustainability-movement.pdf. Cromer, T. (2020, December 8). Importance of sharing clinical trial data for drug development. PK / PD and Clinical Pharmacology Consultants. http://www.nuventra.com/ resources/blog/clinical-trial-data-transparency/. Defining social sustainability. INSS. (2016, November 8). https:// pages.uncc.edu/inss/what-is-social-sustainability/. Informa Sustainability Report, Faster Forward. FasterForward. (n.d.). https://www.informa.com/sustainability/faster-forward/. John Zavras, JPZ. (2021, July 1). An Analysis of Informa’s Clients [PowerPoint Slides]. Informa. Sustainability Final Project - An Analysis of Informa's Clients.pptx Pharmaceuticals in water. (n.d.). https://www.usgs.gov/specialtopic/water-science-school/science/pharmaceuticals-water. Pharma companies cutting energy consumption to gain a competitive advantage. Centrica Business Solutions. (n.d.). https://www.centricabusinesssolutions.com/us/blogpost/ pharma-companies-cutting-energy-consumption-gaincompetitive-advantage. Social sustainability: UN Global Compact. Social Sustainability | UN Global Compact. (n.d.). http://www.unglobalcompact.org/ what-is-gc/our-work/social. Tatum, Malcolm, et al. “What Is Economic Sustainability? (with Pictures).” Info Bloom, www.infobloom.com/what-is-economicsustainability.htm. Water Treatment: Chemical and Pharmaceutical Industries. StackPath. (n.d.). https://www.watertechonline.com/processwater/article/16211579/water-treatment-chemical-andpharmaceutical-industries. “What Is Sustainability?” UCLA Sustainability, www.sustain. ucla.edu/what-is-sustainability/#:~:text=In%20the%20 charter%20for%20the%20UCLA%20Sustainability%20 Committee%2C,communities%20for%20this%20 generation%20and%20generations%20to%20come.

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The Role of Alarm Signal Design in Antipredator Defense in Conspecific Communication BY JUSTIN CHONG '24 Cover Image: Meerkats, or Suricata suricatta, scan the skies for predators in order to give a preemptive alarm call to warn nearby conspecifics for potential predator threats. Image Source: Google Images

Introduction Alarm signals are signals emitted by senders, who first detect a predator, to produce a response in conspecific receivers, who can flee, hide, or come to the aid of the alarmer (Jan & Smith 1992). These signals convey specific, useful information about the predator and orient and direct the response of the receiver. Although alarm signals transcend the binary relationship between sender and recipient and involve heterospecific eavesdroppers and even predators, this literature review will focus on alarm signal systems intended to increase the fitness of conspecifics by permitting them to take preemptive action against potential predation. Alarm signal systems can be extremely complex and allow receivers to know about the type of predator and the level of urgency of the threat (Manser 2001). Signals that refer to predator class are known as functionally referential signals, as they function as if they encode information about the predator as an object in the external environment (Evans 1997). Natural selection and predation pressure favor these signals when the different hunting strategies of predators demand

different ways of escape, defense, or response from the receiver (Manser et al. 2001). Alarm signals that indicate response urgency, usually informed by the speed, intent, and proximity of the predator, are favored by selective forces when a species has a universal mode of escape or action that protects them from all kinds of predation, irrespective of predator type. Many species balance and integrate these two features to elicit catered responses to predation situations. In predation events across several species, alarm signals encode urgency through predictable changes in duration and frequency in a more gradated, variable fashion, whereas predator class is encoded by more broad, distinct, categorical call types.

Risk-Based Urgency Risk-based urgency is encoded in acoustic parameters such as signal duration and frequency across several species, most likely because these signal features can be modified on a gradient scale with great precision, allowing receivers to evaluate the level of urgency that a predator DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 1: New Holland honeyeater bird, or Phylidonyris novaehollandiae, is a type of bird that encodes predator information in call frequency and repetition to notify nearby conspecifics of differing threats of airborne predators. Image Source: Google Images

poses. New Holland honeyeater birds use long, multi-element, high-frequency calls to alert conspecifics to the presence of a predator (Klump et al. 1986). They use both frequency and duration to denote the urgency of a predation threat based on the intrinsic aggressiveness of the predator and predator proximity. The lower the frequency, the higher the urgency level; this is functional since lower frequency sounds attenuate slower due to their diffraction around vegetation and environmental obstructions (Naguib & Wiley 2001). This allows distant conspecifics to be alerted to more dangerous, fast-moving predators who can reach speeds of up to 50 meters/second (Hart et al. 2018). The longer the duration of the call, the more urgent the threat because repetition of call elements increases the probability of signal detection and message redundancy and reinforcement (Johnstone 1997). In these acoustic and temporal aspects, signal frequency and duration are modified accordingly to response urgency level. Suricates, which are meerkats native to open, semi-desert areas in southern Africa, are another species that manipulates frequency and duration to encode urgency. They use acoustic calls to notify conspecifics that a predator is nearby, and receivers respond by standing bipedally, hiding in a hole, or moving to a burrow system (Manser et al. 2001). A discriminant function analysis (DFA)—a statistical method to determine which variables distinguish certain groups of unknown individuals—revealed that variation in response urgency was encoded in predictable, consistent increases or decreases in five acoustic parameters: amplitude variation, call duration, noise, minimum difference between dominant frequency bands 1 and 2, SPRING AND SUMMER 2021

and maximum difference in peak frequency in two consecutive time-segments. Across all predator types, low urgency calls were shorter compared to high urgency ones, consistent with the pattern seen with honeyeaters. As the level of urgency increases, calls become noisier and less harmonic, which is also noted in birds like herring gulls, which communicate threat urgency by manipulating frequency and time parameters (Shah et al. 2015). In addition to denoting greater threats through higher calling rates, more noisy calls are mediated by higher levels of frequency discontinuity, through frequency jumps of 0.5 kHz or higher and biphonation, which is the simultaneous appearance of two independent frequencies produced by the two sets of paired oscillators in bird syrinxes (Zollinger at al. 2008). Frequency unpredictability and lack of harmonic structures discourage habituation and elevate the response of receivers to more dangerous threats.

"In addition to denoting greater threats through higher calling rates, more noisy calls are mediated by higher levels of frequency discontinuity"

Even in non-acoustic modalities like vibrational ones, frequency and duration are highly correlated with response urgency. Asian honeybees, which are highly socially cohesive and exhibit group coordinated defense, transmit brief vibrational pulses called stop signals by headbutting foragers, which encode information about danger level through fundamental frequency and danger context through pulse duration (Ken et al. 2016). Increasing frequency indicates a more dangerous hornet is attacking, and increasing pulse duration communicates that the attacker is closer to the nest rather than foraging locations. By increasing frequency and duration, alarmers decrease departure from the safe interior of the nest and cause receivers to stop transmitting the location of compromised food sources to other bees.

"This evidence supports the proposal that vervet monkeys transmit information beyond just the acoustic features of the call, but through some form of semantic communication as well in perhaps an arbitrary coding scheme."

Differences in how signal duration is modified are influenced by environmental and predation context. Honeyeater birds and Asian honeybees increase signal duration for greater urgency since this increases message repetition and redundancy and doesn’t reveal the location of the alarmer to predators. Contrarily, suricates denote greater urgency by shortening their calls since predators can easily detect and approach suricates in this habitat with minimal cover and vegetation for concealment. Frequency is another reliable marker of urgency since lower frequency calls transmit better over longer distances. For species that increase frequency for greater urgency, this may be due to an increased state of fear and the affective and emotional state of the caller. Communicating response urgency is critical because it maximizes antipredator behavior efficiency and minimizes energy expenditure in costly and potentially unnecessary defense mechanisms (Lima & Dill 1990).

and duration, features thought to be correlated with the alarmer’s arousal state, did not elicit different responses in receivers, indicating that these calls are functionally referential, as they refer to specific external objects in the environment. Whether the leopard was sleeping, attacking, hunting, or moving away from the alarmer, leopard alarm calls were given. Laboratory experiments by Owren (1990) showed that vervet monkeys readily discriminate between eagle and snake alarms, even though these calls are acoustically similar. Furthermore, experiments by Seyfarth and Cheney (1984) demonstrated that vervets can discriminate between various types of grunts, despite their high acoustic similarity. This evidence supports the proposal that vervet monkeys transmit information beyond just the acoustic features of the call, but through some form of semantic communication as well in perhaps an arbitrary coding scheme.

Unlike the acute nature of urgency, predator type is encoded in distinct call types, and, in some cases, is more arbitrary than meaningful or physiologically functional. Vervet monkeys use three different alarm calls to distinguish

The encoding of predator type in call type is also seen in male domestic chickens that use loud, conspicuous, broadband, pulsatile alarms for terrestrial predators like dogs and raccoons and sustained, low amplitude, borderline inaudible alarms for aerial predators like hawks (Evans et al. 1993). Aerial alarms cause receivers to flee to

predator types: leopards, eagles, and snakes (Seyfarth et al. 1980). The leopard alarm causes receivers to run high up into the trees, the eagle alarm elicits skyward scanning and descent from trees into bushes for cover, and the snake alarm causes recipients to stand bipedally and scan the ground around them (Macedonia & Evans 1993). Playback experiments by Seyfarth et al. (1980) demonstrated that variations in call amplitude

cover, crouch, and look upward, and terrestrial alarms elicit highly erect, vigilant postures with high levels of horizontal scanning. As no intergrades were found between the alarms, these two structurally distinct call types denote two very different types of predators, eliciting appropriate antipredator responses in the absence of visual contextual cues in receivers, supporting a model of functional reference for

Predator Type

Figure 2: Vervet monkeys, or Chlorocebus pygerythrus, are a well-studied primate model for alarm call systems that denote predator type and signal for flight, heightened awareness, and recruitment events among conspecifics. Image Source: Google Images

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how these call types associate with predator class stimuli. Red squirrels also use call types to denote predator class and exhibit low rates of crosstaxon calling (Greene & Meagher 1998). The narrow, high-frequency range aerial alarms are perceived poorly by airborne predators, allowing alarmers to be cryptic to fast-moving birds. Loud, explosive, broadband terrestrial alarms in both these species are highly conspicuous and easy to localize. Red squirrels and most species that employ predator type-specific alarms live in structurally complex, three-dimensional environments so predator type information hones and frames optimal escape behavior. Predator type seems to be more encoded into broad call types that are distinct rather than those that are gradated, allowing sufficient and rapid predator categorization upon detection so receivers can escape or respond in a manner appropriate to the type of predator. Some of these, as in vervet monkeys, are more arbitrarily coded in a somewhat semantic manner, whereas others are more functional and practical.

Combinatorial Alarm Call Systems Some species use combinatorial alarm call systems, in which note composition, element sequence, and call ordering convey information, many of which are birds, possibly because their more complex syrinx allows them to produce more elegant, specific, and controlled vocalizations. Black-capped chickadees are small, common songbirds that discriminate between morphologically similar predators through the varying degrees of threat they pose (Templeton et al. 2005). Response urgency is informed by

predator maneuverability and proximity. The smaller the predator body size and wingspan, and therefore the more agile, the higher the risk, which is encoded through more D notes per alarm call and longer D notes, which elicit longer, more intense mobbing behavior with more conspecific recruitment. Predator distance is encoded in A and B note composition as the closer and more immediate the predator is, the lower the number of A syllables and the higher the number of B syllables (Baker & Becker 2002). This kind of signaling is not limited to avian species. Adult male putty-nosed monkeys create unique combinations of two call types, pyows and hacks, to inform receiver response (Arnold & Zuberbuhler 2006). Aerial predators elicit a significantly greater proportion of hacks to pyows, whereas terrestrial predators elicit relatively equal amounts of hacks and pyows. The insertion of pyow-hack units (1-3 pyows followed by 1-4 hacks) followed certain rules in which these units generally followed four to five consecutive hacks and were flanked by conspicuous pauses. Distinguishing these predators is important because more dangerous crowned eagles launch surprise attacks compared to stealth-based leopards who generally abandon a hunt after being detected. These calls are unlikely to be response urgency-based, functionally referential, or affective, so this assembly-based alarm system has the possibility to be arbitrarily coded. Some birds express the principle of compositionality, in which individual calls that each hold meaning are combined in a syntactically meaningful way such that receiver response derives from the individual elements themselves and the sequence in which they are Figure 3: The black-capped chickadee, or Poecile atricapillus, is a common songbird found in North America, noted for its ability to produce complex vocalizations that vary note composition to convey specific information about predators like wingspan and proximity. Image Source: Google Images

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ordered (Suzuki et al. 2019). In Japanese tits, ABC calls elicit alertness and scanning for a predator while D calls recruit conspecifics for nondangerous social contexts. They combine them into an ABC-D call, which produces the expected combination “approach while scanning” and a novel response of collectively mobbing a predator, which is not seen when ABC calls and D calls are played separately. When ABC-D calls are artificially reversed into D-ABC calls, lower levels of scanning, recruitment, and mobbing are observed, indicating that changes in ordering possibly translate to different meanings or a loss in grammatical structure, similar to human syntax.

"Overall, note composition and call sequencing allow the specific properties or behavior of a predator to be communicated, unlike the broad categorizations for predator type."

Overall, note composition and call sequencing allow the specific properties or behavior of a predator to be communicated, unlike the broad categorizations for predator type. Birds, especially, use these combinatorial systems as their bipartite syrinx confers them precise control over airflow dynamics, sound production, and multi-note succession (Suthers 1990). These intricate signals may have evolved from selective pressures of vocal efficiency as avian species could better evade predation and increase direct and indirect fitness.

Current Limitations and Proposed Experiments in the Study of Alarm Signals Despite the sizable body of research conducted regarding alarm signaling, several gaps in understanding remain. One is the lack of a clear delineation of what predator type means. From the current literature, there are no obvious, discernable rules that govern how animals tune their signals to convey predator class to conspecifics. Evans (1997) suggests that predator type is not categorized by taxonomic description, since that is irrelevant when a population is under attack. When altering alarm signals for specificity, is predator type informed by predator appearance or hunting strategy? One study that addresses this is a field experiment following groups of suricates in an open, semi-desert area in southern Africa. The hypothesis is that suricates integrate information about the hunting strategy of the predator to encode information in their acoustic signals about predator type. To test this, the identification of two aerial predators that look physically similar but have distinct hunting styles when hunting meerkats is necessary. One predator would use stealth and fly low to the ground to conceal its approach, while the other would dive to the ground using sheer

speed to catch meerkats. These predators would look similar and be difficult for meerkats to distinguish to confirm that hunting style dictates predator type, not appearance. Two treatments would be carried out, each with a predator with a different hunting tactic. Calls would be recorded with a digital tape recorder and a directional microphone, with only sufficiently high-quality recordings being analyzed. Manser’s experiment with the suricates exposed a lack of rules controlling acoustic parameters encoding predator type when predator type was defined as assignment into aerial and terrestrial. If DFA analysis reveals a consistent increase or decrease in each of the five most important acoustic parameters for predator type across both treatments, it suggests that suricates do not transmit information about the appearance of a predator, but rather its hunting strategy. Another limit to current research has been the need for more investigatory studies on the integration of other factors outside of the sole alarm signaling context. For example, Tan et al.’s experiment with Asian honeybees suggests that if receiving stop signals was enough to cause the receiver to stop signal to other bees, a stop signaling cascade would have been observed in the colony that exponentially increased the number of signals produced as the number of initial foragers attacked by the hornet increased. However, this was not the case as receivers did not stop signal to other bees after receiving a stop signal, irrespective of predator threat level, suggesting that if a bee does not directly experience the peril, they won’t stop signal to other bees. This seems counterintuitive since signaling to more bees would cause more foragers to remain in the nest protected from danger, which raises the question as to whether receiver responses to alarm signals differ depending on context. The hypothesis is that receivers integrate external information about the costs and benefits of responding because it minimizes the impact of false detections, which would cause the entire colony to hide in the nest for a long period of time, consuming valuable foraging time and threatening the food resources of the colony. An experiment to test this would be done using four different observation hives, each with a different treatment: low amounts of stored honey and starved bees as the control, high honey levels and starved bees, low honey levels and well-fed bees, and high honey levels and well-fed bees. Bees would be starved by feeding them 30% sucrose solution until satiation and then placing them in

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Figure 4: The Asian honeybee, or Apis cerana, is a type of honeybee native to southeast and mainland Asia that alters vibrational signals to convey information about the location of a hornet predator as in relation to its proximity to the hive and the danger level of the hornet. Image Source: Google Images

an incubator for 24 hours (Mayack & Naug 2015). Tethered hornets of similar body size would attack the same number of foragers at the nest entrance at all hives. I predict that the starving bee receivers with low honey levels will express fewer to no stop signals as continued foraging is a priority. Starved bees with high honey levels and well-fed bees with low honey levels would have an intermediate amount of stop signals, but if starved bees with high honey levels expressed fewer stop signals than well-fed bees with low honey levels, this would suggest that the internal hunger state of the bee is more important than colony resource levels in their decision to stop signal to others. Well-fed bees with high honey levels would express the most stop signals because the external threat is greater than the risk of starvation if foraging ceases. If this is observed, it suggests that nutritional state and aggregate amount of stored honey influence bees’ receiver decision rule to produce stop signals, implicating the possibility of other species using context to shape their response in addition to conspecific alarms. In addition to external contexts, it is important to address what role altruism and group relatedness play in whether alarmers signal to conspecifics. In many of the previous example species, alarm signaling poses no threat to the individual fitness of the alarmer. For example, high-frequency honeyeater calls cannot be detected by its natural predators. The hypothesis is that if alarm signaling decreases the fitness of alarmers, then selfishness overcomes the benefit of indirect fitness and the probability and duration of signals decrease, and this is exacerbated in species with less group relatedness. For the experiment, treatments

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would consist of a sparrowhawk control, which cannot detect the signaler’s location, and an aerial predator that poses a similar threat as the sparrowhawk but has high sensitivity in those alarm call frequency ranges. Within each treatment, two types of prey birds with alarm calls of similar fundamental frequencies and amplitudes would be used: one with high social cohesion and one with minimal social cohesion. Calls would be recorded with a digital recorder and shotgun microphone 10-20 meters from the focal subject. An acclimatization period before the trials begin would allow prey birds to learn that the sparrowhawk cannot track the signaler’s location and the other predator can. I predict that the probability and mean duration of alarm calls will be highest in the treatment with the sparrowhawk attacking closely related birds and lowest in the treatment with the other predator attacking birds with low relatedness. These features will be intermediate in the other two treatments, but if they are lower in the treatment with the sparrowhawk attacking birds with low relatedness compared to the treatment with the other predator attacking closely related birds, it suggests that the benefit of indirect fitness and kin selection may rescue, although not completely, the impact of selfishness and self-preservation.

"If this is observed, it suggests that nutritional state and aggregate amount of stored honey influence bees’ receiver decision rule to produce stop signals, implicating the possibility of other species using context to shape their response in addition to conspecific alarms.

Conclusion Alarm signaling, through acoustic, temporal, and patterning features, can convey information about predator type and urgency, whose encoding is determined by the very nature of the information being transmitted from categories to spectrums, respectively, in addition to environmental and predation context. While future research should broaden the scope of factors shaping receiver

response, it should also elucidate whether informational content is encoded arbitrarily or in a manner that targets specific sensory systems for a functional purpose. References Arnold, K., & Zuberbühler, K. (2006). The alarm-calling system of adult male putty-nosed monkeys, Cercopithecus nictitans martini. Animal Behaviour, 72(3), 643–653. https://doi. org/10.1016/j.anbehav.2005.11.017. Baker, M. C., & Becker A.M. (2002). Mobbing calls of blackcapped chickadees: effects of urgency on call production. The Wilson Bulletin 114(4): 510-516. https://doi.org/10.1676/00435643(2002)114[0510:MCOBCC]2.0.CO;2. Blumstein, D. T., & Armitage, K. B. (1997). Does sociality drive the evolution of communicative complexity? A comparative test with ground-dwelling sciurid alarm calls. The American naturalist, 150(2), 179–200. https://doi.org/10.1086/286062.

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Greene, E., & Meagher, T. (1998). Red squirrels, Tamiasciurus hudsonicus, produce predator-class specific alarm calls. Animal Behaviour, 55(3), 511–518. https://doi.org/10.1006/ anbe.1997.0620. Hart, L. A. et al. (2018). Hunting flight speeds of five southern African raptors. Ostrich 89(3): 251-258. https://doi.org/10.2989/ 00306525.2018.1455754. Smith, R.J.F. Alarm signals in fishes. Rev Fish Biol Fisheries 2, 33–63 (1992). https://doi.org/10.1007/BF00042916. Johnstone, R. A. (1997). The evolution of animal signals. In: Krebs JR, Davies (eds) Behavioural ecology: an evolutionary approach. Blackwell, Oxford, pp 155-178. Ken, T. et al. (2016). Honey bee inhibitory signaling is tuned to threat severity and can act as a colony alarm signal. PLoS Biology 14(3): e1002423. https://doi.org/10.1371/journal. pbio.1002496. Klump, G. M., Kretzschmar, E., & Curio, E. (1986). The hearing of an avian predator and its avian prey. Behavioral Ecology and Sociobiology, 18(5), 317–323. https://doi.org/10.1007/ BF00299662. Lima, S. L., & Dill, L.M. (1990). Behavioral decisions made under the risk of predation: a review and prospectus. Canadian Journal of Zoology 68: 619-640. https://doi.org/10.1139/z90092. Macedonia, J. M. (1993). The vocal repertoire of the ring-tailed lemur (Lemur catta). Folia Primatol 61: 186-217. https://doi. org/10.1159/000156749.

Macedonia, J. M., & Evans, C. S. (1993). Variation among mammalian alarm call systems and the problem of meaning in animal signals. Ethology, 93(3), 177–197. https://doi. org/10.1111/j.1439-0310.1993.tb00988.x.

Owren, M. J. (1990). Acoustic classification of alarm calls by vervet monkeys (Cercopithecus aethiops) and humans (Homo sapiens): I. Natural calls. Journal of Comparative Psychology, 104(1), 20–28. https://doi.org/10.1037/0735-7036.104.1.20. Seyfarth, R. M. & Cheney, D. L. (1984). The acoustic features of vervet monkey grunts. The Journal of the Acoustical Society of America 75: 1623. https://doi.org/10.1121/1.390872. Seyfarth, R. M., Cheney, D. L., & Marler, P. (1980). Vervet monkey alarm calls: Semantic communication in a free-ranging primate. Animal Behaviour, 28(4), 1070–1094. https://doi. org/10.1016/S0003-3472(80)80097-2. Seyfarth, R. M., Cheney, D. L., & Marler, P. (1980). Monkey responses to three different alarm calls: Evidence of predator classification and semantic communication. Science, 210(4471), 801–803. https://doi.org/10.1126/science.7433999. Shah, S. S. et al. (2015). Risk-based alarm calling in a nonpasserine bird. Animal Behaviour 106: 129-136. https://doi. org/10.1016/j.anbehav.2015.05.011. Suthers, R. (1990). Contributions to birdsong from the left and right sides of the intact syrinx. Nature 347, 473–477. https://doi. org/10.1038/347473a0. Suzuki, T. N., Griesser, M., & Wheatcroft, D. (2019). Syntactic rules in avian vocal sequences as a window into the evolution of compositionality. Animal Behaviour, 151, 267–274. https://doi. org/10.1016/j.anbehav.2019.01.009. Templeton, C. N., Greene, K., & Davis, K. (2005). Allometry of alarm calls: black-capped chickadees encode information about predator size. Science 308: 1934-1937. https://doi.org/10.1126/ science.1108841.

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Thom, C. et al. (2007). The scent of the waggle dance. PLoS Biology 5(9): e228. https://doi.org/10.1371/journal. pbio.0050228. Zollinger, S. A., Riede, T., Suthers, R. A. (2008). Two-voice complexity from a single side of the syrinx in northern mockingbird (Mimus polyglottos) vocalizations. Journal of Experimental Biology 211: 1978-1991. https://doi.org10.1242/ jeb.014092.

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The Current State of Immunotherapy: Checkpoint Inhibitor Drugs BY MATTHEW LUTCHKO ’23 Cover Image: A depiction of antibody drug ipilimumab (blue) binding to its target cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) (pale green). Typically, CTLA-4 activity interferes with the immune response to cancer by inhibiting T lymphocytes, which serve to destroy cells that are infected with a pathogen or otherwise dangerous, like cancer cells. Upon binding with ipilimumab, CTLA-4’s suppressive function is disabled and the T lymphocyte activity is restored. Image Source: Wikimedia Commons

Introduction More than one hundred diseases are broadly categorized as cancers. Cancer was the second leading global cause of death in 2017 (National Institutes of Health, 2007; Ritchie & Roser, 2018). In 2020 alone, there were an estimated 1.8 million new cancer diagnoses and 600,000 cancer-related deaths in the United States (National Cancer Institute, 2020). Essentially, the first step in cancer initiation involves the transformation of a normal cell upon the introduction of mutations in genes that play important roles in controlling cell growth and division. As a result, the descendants of that original cell are able to circumvent the regulatory mechanisms normally employed to keep them from becoming too large or dividing too quickly. These cells accumulate and eventually develop tumors, which can interfere with bodily functions and cause the symptoms associated with cancer (National Institutes of Health, 2007). There are many types of cancer treatment; some

of the most well-known include chemotherapy, radiation therapy, and surgery (Falzone et al., 2018).Recently, researchers and doctors have turned their focus to a relatively new form of cancer treatment: immunotherapy. Immunotherapy refers to the use of drugs and other biologics to increase the ability of a patient’s immune system to carry out the responses necessary to recognize and kill cancer cells (Vaillant et al., 2020). A common assumption is that all immunotherapies aim to directly upregulate some component of the immune system. However, certain activities of the immune system--although important in general--may be negative in the context of cancer. Critically, regulatory T cells work to shut down the immune response; in cancer, their activity leads to a decreased ability of immune cells to fight cancer cells (Plitas & Rudensky, 2016). These functions are typically referred to as “immunosuppressive” features of the immune system (Wan, 2010). In understanding immunotherapy and checkpoint inhibitors in particular, it is important to keep in mind that such treatments often aim to downregulate immunosuppressive components of the immune system, with hopes of achieving DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

a net increase in the response against the cancer. Within immunotherapy there are different types of treatment; molecular and cellular therapies target specific molecules or cell identities, while cancer vaccines contain information derived either from DNA/RNA or molecules expressed on the surface of cancer cells (Liu & Guo, 2018). This paper, however, will specifically examine the biology, clinical outcomes, and future considerations of checkpoint inhibitors. Rather than targeting the cancer cells, these therapeutics aim to inhibit checkpoint signals that keep cytotoxic T lymphocytes from executing their important cancer cell-fighting functions. First, this review will consider the two classes of checkpoint inhibitors currently in clinical use, each of which target a separate checkpoint (Meyers & Banerji, 2020). Then, it will shift to explore progress relating to V-type immunoglobulin domain-containing suppressor of T cell activation (VISTA), an additional checkpoint which is the focus of current experimental therapies (EITanbouly et al., 2020).

CTLA-4 Checkpoint Ipilimumab Ipilimumab is an anti-CTLA-4 antibody, and the sole CTLA-4 targeting therapy approved by the FDA (American Cancer Society, 2021; Saad & Kasi, 2020). It was first approved for treatment of advanced melanoma in March 2011, and has since been approved for use against other types of cancer, including colorectal cancer, renal cell cancer, and non-small cell lung cancer (“FDA Approves New Immunotherapy for Metastatic Melanoma, 2011; Saad & Kasi, 2020). Biology of CTLA-4 & Ipilimumab Cytotoxic T lymphocytes, immune cells with the ability to kill cells that may be dangerous, require two signals before executing their function. To achieve specificity, cytotoxic T cells must recognize information derived from antigen they are specific for; generally, antigen peptides are presented by molecules on the surface of antigen presenting cells (APC) that can be engaged and read by T cells (Tai et al., 2018). Though necessary, this interaction is not sufficient for activation. A molecule called CD28 on T cells must be bound to antigen-independent molecules CD80 or CD86 on the surface of APCs; this second signal is referred to as costimulation (Sharpe, 2009). Upon costimulation by an antigen presenting cell, a T cell will undergo changes that upregulate the immune response, including proliferation and the production of certain cytokines--signaling molecules important for communication in the immune system (Esensten, 2016). This is where SPRING AND SUMMER 2021

Cytotoxic T Lymphocyte antigen 4 (CTLA4) comes in; after interaction with APCs, its concentration on the surface of T cells begins to increase. CTLA-4 is a homologue of CD28 that provides an inhibitory signal rather than a stimulatory one, and binds to CD80 and CD86 with much higher affinity; over time, it outcompetes CD28 for binding and works to shut down the T cell response (Rowshanravan et al., 2018). Normally, inhibitory signaling via CTLA4 serves an important role in keeping T cells from becoming too active and doing unnecessary damage to tissue (Jain et al., 2010). In cancer, its signaling is a limiting factor in the ability of cytotoxic T cells to kill cancer cells. In reality, the biology of CTLA-4 is more involved. Not only is it able to downregulate the immune response via cytotoxic T cells, but it is also found on immunosuppressive regulatory T cells, or Tregs. In this scenario, its ability to outcompete CD28 for binding to CD80/CD86 keeps cytotoxic T cells from interacting with antigen presenting cells altogether, thus arriving at the same outcome: inability for activation (Buchbinder & Desai, 2016). However, studies have shown compromising CTLA-4 function does not deplete Tregs in the tumor environment (Sharma et al., 2019). In other words, this mechanism is not as important in the context of ipilimumab.

"Normally, inhibitory signaling via CTLA-4 serves an important role in keeping T cells from becoming too active and doing unnecessary damage to tissue (Jain et al., 2010). In cancer, its signaling is a limiting factor in the ability of cytotoxic T cells to kill cancer cells."

In understanding the effect of CTLA-4 in cancer, it is clear that antagonizing it could yield clinical benefit; this is where checkpoint inhibitors come in. Ipilimumab is an anti-CTLA-4 antibody, meaning its structural specificity allows it to bind to CTLA-4. Thus, CTLA-4 on cytotoxic T cells is no longer free, or able to bind CD80/CD86 and induce an inhibitory response. Instead, T cells are able to proliferate and serve their effector functions (e.g. direct killing) in the immune response. As a result of prolonged cytotoxic T cell activation, the idea is that a cancer patient’s T lymphocytes will be more equipped to battle tumor cells (Tarhini et al., 2010). History By the late 1980’s, there was an understanding of CD28 and B7 as they related to costimulation for the activation of cytotoxic T cells. However, a poorly understood T cell surface molecule--later identified as CTLA-4--was of growing interest; it mapped to the same chromosomal region as CD28, and DNA sequencing revealed a very high similarity between the two. At first, CTLA-4 was thought to serve the same function as CD28 in that both were promoters of costimulation and T cell activation (Bashyam, 2007). However, in the early 1990’s the role of CTLA-4 91

"In a 1995 experiment, the generation of CTLA4 knockout mice (i.e. mice who were not able to express CTLA4) caused them to develop a disorder associated with the rapid proliferation of T cells."

was becoming increasingly unclear for two main reasons, among others. It had a much higher binding affinity than CD28 for CD80/CD86 and was different in that it was not expressed on the cell surface until after activation (Auchincloss & Turka, 2012). One experiment included the incorporation of soluble CTLA-4 into a mixture of T cells, which resulted in the inhibition of proliferation. A possible interpretation suggested that CTLA-4 was a stimulatory signal, and the binding of soluble CTLA-4 to CD80/CD86 kept it from binding to cell-surface CTLA-4 and inducing costimulation in the T cell. In a 1995 experiment, the generation of CTLA4 knockout mice (i.e. mice who were not able to express CTLA-4) caused them to develop a disorder associated with the rapid proliferation of T cells. These results made it clear that CTLA4 was important in preventing overactive T cell proliferation, making it an inhibitory signal (Bashyam, 2007). Efficacy, Side Effects, & Future Considerations By 2011, ipilimumab was changing the therapeutic landscape for melanoma; it became the first immunotherapy to demonstrate an increase in overall survival (OS) in melanoma patients with advanced or metastatic disease (Camacho, 2015). One phase I trial including seven patients with surgically unresectable advanced melanoma yielded strong evidence of tumor necrosis (death) in three of seven participants. It is important to note, however, that a separate phase I trial established that escalating ipilimumab dosage (from 5 mg/kg to 9 mg/kg) led to an increase in autoimmune side effects without a meaningful impact on tumor response. Many phase II trials analyzed ipilimumab treatment alone or in combination with other cytotoxic agents, particularly dacarbazine, a melanoma drug that had already been FDA approved. They continued to show promising results for effects on overall survival (Letendre et al., 2017). A similar phase III ipilimumab trial used Gp100, a vaccine containing melanoma antigen-derived peptide, with the goal of activating T lymphocytes to find and destroy melanoma cells with greater success (Schwartzentruber et al., 2012). The trial separated advanced melanoma patients into three groups; one received gp100 vaccine alone, one received gp100 in combination with ipilimumab, with the last receiving ipilimumab alone. After follow up, results showed that median OS was 10.0 months for patients receiving ipilimumab compared to 6.4 months for those who had received gp100 vaccine alone,

suggesting ipilimumab’s potential as a more effective therapeutic (Letendre et al., 2016). Disease control rates (the proportion of patients in a given group who exhibited partial response, complete response, or stable disease) were also convincing: 28.5% for ipilimumab alone, 20% for ipilimumab + vaccine, and 11.1% for vaccine alone (Fellner, 2012). Because ipilimumab is an immunotherapy, it often comes with autoimmune side effects; essentially, the stimulation of the immune system by CTLA-4 blocking activity results in excessive immune response that manifests as side effects (e.g. inflammation). Ipilimumab studies have shown that, in general, patients who experience autoimmune side effects also exhibit a stronger clinical response to their cancer (Letendre et al., 2017). The biological justification for this is consistent with scientific knowledge. Autoimmune effects are caused by greater activity of T lymphocytes, so it is reasonable that the T cells of the patients with those side effects are responding at higher levels and thus allowing for greater tumor necrosis. Some of these autoimmune effects include inflammation of the small intestine and colon which occurred at a severe or fatal level in 6.7% of ipilimumab recipients, and dermatitis--skin inflammation--which occurred at a severe level in 2.5% of ipilimumab recipients (Fellner, 2012). Generally, these types of effects are treated-often successfully--with corticosteroids, which suppress inflammation-mediated disease by repressing transcription of pro-inflammatory genes and stimulating transcription of antiinflammatory genes (Caramori et al., 2019). Those in the science community and beyond have been excited about ipilimumab, as it is a first-in-class immunotherapy. However, is relatively expensive and can cause severe autoimmune reactions despite efforts to combat them (e.g. decreased dosage and increased time between treatments); these factors are significant especially when taking into consideration that ipilimumab’s best overall response rate is only 11%. As other treatment options are developed and explored, one future possibility in the context of ipilimumab is more widespread research into identifying biomarkers predictive for successful response to treatment (Fellner, 2012).

PD-1/PD-L1 Checkpoint PD-1/PD-L1 Blockers Though immunotherapies that block programmed cell death protein 1 (PD-1) or its ligand (PD-L1) are similar to ipilimumab in

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their checkpoint-inhibiting nature, the molecular target is different and consequently warrants an entirely separate discussion. Pembrolizumab was the first PD-1 inhibitor to be approved for

treatment of advanced melanoma by the FDA in September 2014, with nivolumab being approved soon after in December 2014 (Raedler, 2015). Biology of PD-1/PD-L1 & Their Blockers The PD-1/PD-L1 checkpoint is similar to CTLA4 in that it is a negative regulator of the immune response. PD-1 is expressed on T lymphocytes, among several other cells of the immune system; when bound by its ligand PD-L1, subsequent

signaling inhibits T cell activation and cytokine production, ultimately limiting proliferation and reducing the quantitative strength of a T cell response (Seliger, 2019). In a general biological context, PD-1/PD-L1 is beneficial and necessary in that it helps keep the immune system from attacking antigens from the host’s own body, especially by putting an end to immune responses that are harmful or ineffective (Han et al., 2020). In cancer, however, PD-1 plays a dangerous role. There is often abnormally high expression of PDL1 on the surface of both cancer cells and antigenpresenting cells in the tumor microenvironment (Jiang et al., 2019). As a result, the PD-1 expressed on T cells in the area is constantly bound by PDL1 and thus inhibiting an immune response. Essentially, T cells are falsely informed that there is no need to carry out their cytotoxic function and thus fail to do so.

Figure 1: Dermatitis, one of the immune-mediated side effects commonly resulting from immunotherapy like ipilimumab. Image Source: Wikimedia Commons

Checkpoint inhibitors targeting either PD-1 or PD-L1 serve to combat this issue. In a method similar to ipilimumab’s, the relevant drugs are antibodies specific to whichever molecule they are targeting (e.g. anti-PD-1 or anti-PD-L1). The net biological effect is consistent regardless of which of the two molecules is being targeted. The binding of incorporated antibody blocks the Figure 2: Nivolumab antibody (blue) binding to its target (purple), the extracellular domain of the programmed cell death protein 1 (PD-1). Upon blockage, PD-1 fails to interact with its ligand PD-L1 and is unable to provide immunosuppressive signals for the cytotoxic T cell. Image Image Source: Wikimedia Commons

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interaction; either antibody-bound PD-1 cannot be signaled by PD-L1 or antibody-bound PD-L1 is unable to signal to PD-1 (Boussiotis, 2017). Thus, inhibition of T cells is reduced and their cytotoxic anti-tumor activity is restored (Alsaab et al., 2017).

"In a subsequent larger study, 17% of nivolumab-treated non-small cell lung cancer (NSCLC) responded to the antibody, with half of this group exhibiting decrease in tumor size within two months"

It is important to note that there are many inhibitors targeting the PD-1/PD-L1 checkpoint. PD-1 inhibitors include nivolumab, pembrolizumab, and cemiplimab while atezolizumab, avelumab, and durvalumab are among the PD-L1 inhibitors (American Cancer Society, 2021). Although in practice it is important to distinguish between these, an exhaustive description considering each inhibitor separately is unnecessarily beyond the scope of this review and its goal. Instead, later sections on the PD-1/PD-L1 topic will specifically consider nivolumab, chosen in order to more suitably discuss combination treatment with ipilimumab and nivolumab. History In 1992, scientists led by Dr. Tasuku Honjo at Kyoto University in Japan performed an experiment to identify genes important in apoptosis (programmed cell death) and identified PD-1 as an apoptosis-associated molecule. They also demonstrated its immune-inhibitory effect by experimenting with PD-1 deficient mice--who developed autoimmune disease--in 1999; they worked with Genetics Institute in Cambridge, Massachusetts in an effort to identify its ligand. At roughly the same time, a research group led by Lieping Chen identified PD-L1. However, they had not discovered that it was the ligand for PD1; only that it acted on T cells through a receptor different from the common ones identified. A separate research group reached out to Genetics Institute with hopes to identify the receptor for PD-L1, knowing it did not interact with CD28 or CTLA-4. The Genetics institute was able to establish PD-1/PD-L1 as the receptor-ligand pair. Lieping Chen, now a professor at Yale, showed as early as 2002 that blocking the pair’s interaction via antibody could result in decrease of tumor size (Bardhan et al., 2016). Nivolumab Efficacy, Side Effects & Future Considerations Preliminary findings from a first-in-human phase I study of nivolumab suggested that it was well tolerated, had prolonged effects on PD-1 occupancy for a long period of time showing the antibody was high affinity for its target, and response was shown in twelve of thirty nine recipients. In a subsequent larger study, 17% of nivolumab-treated non-small cell lung cancer

(NSCLC) responded to the antibody, with half of this group exhibiting decrease in tumor size within two months (Sundar et al., 2015). In a phase III trial for nivolumab against NSCLC, 541 of 1325 enrollees underwent randomization, with 78% of the randomized participants expressing PD-L1 levels of 5% or higher and thus making up the primary efficacy analysis group. This group was randomized to nivolumab treatment and chemotherapy treatment. Although many aspects of the follow-up results comparing the two treatment groups ended up not being significant, it is of value to note that the median length of treatment-stimulated response in nivolumab-treated patients was twice as long as that of chemotherapy-treated patients. It is also worth noting that certain baseline characteristics associated with better prognosis likely favored the chemotherapy group; they had fewer liver metastases, smaller tumor burden, and a higher proportion of women. Then again, there were fewer proportions of participants with PD-L1 expression over 50% and high tumor-mutation in the nivolumab group (Carbone et al., 2017). As far as safety and toxicity, available data has suggested that nivolumab--compared to ipilimumab--comes with less risk of severe and fatal adverse effects (AEs). However, there are two central points significant in this context. First, much of the data for AEs in ipilimumabtreated patients had come out before much of the data pertaining to AEs in nivolumab-treated patients. Although there may have only been up to a few years difference between the timeline of the two drugs, this fact alone could have made comparison of AEs from the two drugs significantly different. Because ipilimumab was developed first, there was less knowledge about the associated AEs as well as less efficient ways to manage them (Zhao et al., 2018). Another important idea in comparing AEs associated with the two drugs is the molecular differences of their targets. CTLA-4 is upregulated immediately following T cell activation, while PD-1 is generally more active toward the end of a T cell response. Thus, because nivolumab blocks an inhibitor that acts later in the cycle of a T cell and is thus more restrictive to T cell reactivity, it is more easily tolerated by the immune system (Zhao et al., 2018). In other words, blocking CTLA-4 could be associated more with activating a higher volume of T cells while blocking PD-1/ PD-L1 might have more to do with keeping already active T cells from shutting down; the former would have a higher propensity for

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Figure 3: Shown is enterocolitis (inflammation of the digestive tract), one of the common immune-mediated side effects of PD-1 inhibitors (e.g. nivolumab, pembrolizumab, & cemiplimab). Image Source: Wikimedia Commons

autoimmune effects than the latter. With that being said, results of one clinical trial suggested that the most common toxicity for nivolumab treatment was skin irritation, which occurred in 31% of those treated (Sundar et al., 2015). Incidence of enterocolitis--inflammation of the digestive tract--can also be as high as 30% for patients treated with PD-1 inhibitors (Bajwa et al., 2019). Otherwise, as the net effect of nivolumab is very similar to ipilimumab, the two have a similar profile of side effects and adverse events. Many of these can be managed with corticosteroids; as mentioned previously, these are hormones that induce transcriptional changes in the cell to inhibit inflammation and the effects of the immune response (Heinzerling et al., 2019). As with ipilimumab, one area worth exploring moving forward is the identification of biomarkers that would be a good indication of whether or not specific patients are likely to respond to PD-1/ PD-L1 inhibitors in order to more suitably choose a treatment plan (Sundar et al., 2015). Also, existing reports have suggested that there could be a correlation between tumor bulk and ability to execute a tumor-specific response (Stewart & Abbrams, 2007). Accordingly, Sundar et al. suggest that it could be worthwhile to explore methods such as tumor resection followed by the administering of PD-1/PD-L1 inhibitors to target minimal residual disease.

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Nivolumab Combined with Ipilimumab Many patients do not benefit from treatment by one checkpoint inhibitor. For instance, a cancer patient who does not specifically present with overactive PD-1/PD-L1 is less likely to benefit from a drug (nivolumab) that works to stop it. One method to overcome this downfall has been the exploration of combined therapies-nivolumab plus ipilimumab has been a recently explored option (Kooshkaki et al., 2020). One meta-analysis investigating nivolumab and ipilimumab combined treatment collected data from eleven clinical trials of varying phases and across several types of cancers, totaling nearly 2500 participants. The communicated results are exciting, with the rate of complete response-disappearance of all detectable signs of cancer-reaching almost five times greater among the combined treatment groups as compared to patients who received ipilimumab alone. Overall response rate, which includes the proportion of patients who saw either a complete or partial response, was 3.3 times higher in combined groups versus those treated with ipilimumab monotherapy (Chen et al., 2020).

"Many patients do not benefit from treatment by one checkpoint inhibitor... One method to overcome this downfall has been the exploration of combined therapies"

In another trial, advanced melanoma patients who had received either combined treatment with nivolumab and ipilimumab or one of them alone were followed up after sixty months. Recorded median overall survival length was approximately twenty months for patients receiving ipilimumab and thirty-seven months for those receiving nivolumab. Excitingly, median

survival duration still had not been reached for those receiving combined treatment; more than 50% of participants were still alive after sixty months (Larkin et al., 2019). Unfortunately, combined treatments seems to also yield a higher risk for adverse events. Side effects that are severe or life threatening arise in about 17-21% of patients who receive anti-PD-1 treatment (includes nivolumab) and in 20-28% of patients who receive ipilimumab. However, the proportion jumps to 59% for those being treated with a combination of nivolumab and ipilimumab (Heinzerling et al., 2019).

"Unfortunately, combined treatments seems to also yield a higher risk for adverse events"

Combining these molecular targets likely yields a higher incidence of T cell activity than use of either drug alone, allowing more opportunity for overactive immune response causing inflammation and other side effects. Rash presents in 40% of combined therapy recipients, while it only presents in 25% of ipilimumab monotherapy patients and 15% of nivolumab monotherapy patients. Endocrine effects, including hypophysitis--inflammation of the pituitary gland which can lead to its failure-present in 30% of combination therapy patients but 14% or 11% in nivolumab and ipilimumab respectively (Kooshkaki et al., 2020). While combination therapy has proven itself to be generally more efficacious than either monotherapy alone, it is important to keep in mind its potentially more severe side effects. Many patients can be sufficiently treated with corticosteroids as in the case of either treatment alone, but those experiencing extreme adverse events that are not appropriately treated with corticosteroids must often go off treatment and consider alternatives.

VISTA Checkpoint V domain immunoglobulin suppressor of T cell activation (VISTA) is a more recently identified checkpoint in the immune response, whose blockage has an impact on restoration of antitumor activity. Some early results have been promising, and additional research and trials in the near future will likely provide a much better idea of the role anti-VISTA therapeutics could play in the cancer landscape (Tagliamento et al., 2020). Biology of VISTA The particular molecular mechanisms of the VISTA checkpoint are not very well understood. Currently, researchers know that VISTA serves as a negative checkpoint similar to CTLA-4

and PD-1/PD-L1. While ligand on a cytotoxic T lymphocyte is bound to VISTA, the induced signal inhibits proliferation and cytokine production, preventing an immune response. VISTA can provide an inhibitory signal to T lymphocytes either extrinsically via expression on antigen presenting cells, or intrinsically via expression on T cells themselves (Xu et al., 2018). Within the T cell identity, VISTA is more highly expressed on regulatory T cells--which serve an immunosuppressive function--than on cytotoxic T cells (EITanbouly et al., 2019). This is consistent with its activity as an inhibitory signal. Due to its suppressive activity, the VISTA checkpoint--similar to both CTLA-4 and PD-1/ PD-L1--plays an important role in the previously introduced immune tolerance. Mice deficient in VISTA have an increased propensity to develop autoimmunity (Ceeraz et al., 2017). Also, humans with systemic lupus erythematosus (SLE)—an autoimmune disease in which the immune system attacks healthy tissue--were found to have less VISTA expression than healthy humans (EITanbouly et al., 2020). As SLE is an autoimmune disease, this is consistent with the classifying of VISTA as an immunosuppressive factor. SLE patients are more prone to have less VISTA activity that maintains immune tolerance and prevents autoimmune disease. In the same sense as other checkpoints, antagonizing VISTA could be of use in the context of cancer. Inhibiting its function via a blocking antibody, two of which are to be mentioned, could allow for restoration of cytotoxic T cell activity. Interestingly, one experiment sought to understand VISTA effect duration by culturing T cells in the presence of VISTA for a period of time, and afterward culturing them in the presence only of a stimulatory molecule. The T cells were not lifted from their suppressive state, showing that VISTA-induced suppression is long-lasting even after exposure (Lines et al., 2014). This result further supports the possibility that antagonizing VISTA in cancer could have profound effects. History The VISTA checkpoint regulator was discovered by the lab of Randolph Noelle, a Professor of Immunology at the Geisel School of Medicine at Dartmouth. As Professor Noelle puts it, “blocking VISTA … may enhance the host’s ability to make tumor-specific immune responses,” (“Researchers Investigate Molecule, VISTA, Which Keeps the Immune System Quiet Against Cancer,” 2020). In recent years, many in the community have directed efforts both to elucidate the molecular

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mechanisms of VISTA as well as launch studies and clinical trials to evaluate the antitumor response-restoring ability of VISTA antagonists.

yield less propensity for triggering autoimmune side effects and how such side effects, especially severe ones, could be better managed.

Clinical Potential & Considerations A Dartmouth start-up biotechnology company, ImmuNext--of which Randolph Noelle is a cofounder--has partnered with Curis to evaluate their developed monoclonal anti-VISTA antibody, branded CI-8993, and results are currently being awaited (Liu, 2020).

Meanwhile, it is certainly possible that the cancer treatment landscape could eventually see the approval and official introduction of VISTAantagonist-based immunotherapies. However, it is important to note that the checkpoints of interest are not limited to VISTA or the other two covered in depth throughout this review. Known inhibitory T cell checkpoints also include LAG3, TIM-3, and TIGIT, among others (Qin et al., 2019). Antibodies antagonizing such molecules are currently undergoing clinical trials and are of equal interest to monitor and learn more about.

Otherwise, another interesting process to watch is biologic CA-170, a checkpoint inhibitor that is administered orally and is actually specific for both VISTA and PD-L1. In primary results from a phase II trial, 52% of participants with at least one response evaluation showed solid-tumor clinical benefit rate (CBR). CBR represents those who exhibited either stable disease, partial response, or clinical response (Tagliamento et al., 2019). CI-8993 and CA-170 are both worth watching as responses are evaluated and new results are reported. As for CA-170, oral administration is potentially of great benefit as it largely reduces certain risks that would present to the patient via more common means of administration. Research to understand the molecular pathways involving VISTA is ongoing and is sure to contribute greatly to exploration and development of cancer therapeutics that work to antagonize it.

Discussion The field of immunotherapy has seen impressive progress in recent years, especially with the introduction of, as well as continued interest and work in, the checkpoint inhibitor field. Antibodies that function to antagonize CTLA4 and PD-1/PD-L1 are able to help restore the immune response in many cancer patients and the treatments derived from them have been approved by the FDA for use against differing stages of many types of cancers. Combination therapy of these inhibitors is shown to be even more efficacious as far as helping the immune system battle tumors and increasing survival outcomes for the patients burdened by them. Immune-mediated adverse events are common in many patients who receive checkpoint inhibitor treatment and can often be severe, life threatening, or fatal; those who can be treated accordingly (e.g. with corticosteroids) should be, and those whose side effects are severe and cannot be treated must consider alternative therapeutic options. It is important that ongoing and future research aims to understand both how these types of therapies could be engineered to

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As far as future directions in immunotherapy, there seems to be a limitless number of research questions whose answers will allow a deeper understanding of mechanisms regarding the immune response, how tumors have evolved to escape it, and anything in between. Fascinatingly, Sundar et al. 2015 mentions the possibility of elucidating interactions between pathways that regulate immune escape and factors that control tumor-infiltrating cells; such information would be of critical value in the field. Ultimately, this developing knowledge--especially in combination with a better understanding of whether a certain patient is likely to respond to a treatment, experience severe adverse events, etc.--will likely yield immunotherapies, as well as other cancer treatments, that become more efficacious and decreasingly less risky.

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Quantum Entanglement and its Applications BY RUJUTA PUROHIT ’24 Cover Image: The world's first photograph of quantum entanglement - a phenomenon so strange, Einstein famously dubbed it 'spooky action at a distance'. The image shows a composite of two entangled photons as they go through a series of four phase transitions. Image Source: Moreau et al., Science Advances, 2019

Introduction The discovery of wave-matter duality spearheaded the study of quantum mechanics in the 20th century. The fact that particles behaved like waves and light waves behaved like particles gave rise to new experiments and theories, leading to breakthroughs such as the photoelectric effect, the de Broglie hypothesis and blackbody radiation. While the particle nature of light answered many long-standing questions, the wave nature of matter opened up room for new questions. A wave function is a mathematical construct that encodes all quantum properties of an object. It is a complex valued function whose solutions give information about the position or momentum, among other physical properties, of the object at any given time (Eisberg & Resnick, 1985). The wave function is a description of the quantum state of the object and is represented by the Greek letterΨ. In 1926, Erwin Schrödinger published an equation – the Schrödinger equation – to govern the behavior and evolution of wave functions (i.e., matter waves) over time (Schrödinger, 1926): A quantum state describes the probability of measuring a certain physical property of a

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particle, such as its position or momentum. Since the foundations of quantum physics is a probabilistic theory, a quantum state is the most accurate one can be when it comes to describing particles. This is due to a variety of factors, like the Heisenberg Uncertainty Principle, which states that a particle’s position and momentum cannot be known accurately simultaneously, and wave function collapse, a phenomenon that occurs when a several state wave function - a superposition of many single state functions - is reduced to a single state wave function. All fundamental particles have a physical property called spin. Spin is an entirely quantum mechanical phenomenon and has no classical counterpart. It is the intrinsic angular momentum associated with quantum particles. Angular momentum, however, is not associated with any internally rotating parts of the particle but comes from the rotation of the particle itself. Spin is defined relative to its direction of measurement. If the spin of a particle aligns with the direction of its measurement, the particle has spin “up”. If the spin is opposite to the direction of DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

measurement, the particle has spin “down”. This is expressed by the spin quantum number, s, that has values of the form n2, which means that it is quantized and can only have discrete values. n is the principal quantum number and represents the energy state of a particle. For example, n = 1 is the ground state and n = 2 is the first excited state. Furthermore, with the Bohr model of the atom, n is used to denote the orbit occupied by an electron. Particles with half-integer spin values are called fermions (e.g., electrons, protons, neutrons) and particles with full-integer spin values are called bosons (e.g., photons, gluons) (Eisberg & Resnick, 1985). After the measurement of its spin, the particle maintains the original direction, meaning that spin itself is not affected by the process of measurement. Interestingly, the measurement biases the spin. If spin is measured horizontally, the probability of being up or down is both 50%. If spin is measured at an angle of 60° from the vertical, the probability of being up is 75% and that of being down is 25%. Mathematically, the probability of being spin up is given by:

The formula above implies that the act of measuring a particle’s spin actually changes the spin itself since the direction of measurement biases the outcome. The property of spin is essential in characterizing the quantum states of particles and is at the foundation of quantum entanglement.

Quantum Entanglement and the Einstein-Rosen-Poldosky Paradox Quantum entanglement is a phenomenon in which the quantum states of particles have to be described in reference to each other. This happens even though the individual particles may be spatially separated and have no physical proximity with each other. The group of particles interact with each other or are generated in a manner that mathematically results in their inter-dependent quantum states. By virtue of the interaction, the particles become entangled (Griffiths, 2004). The physical properties of entangled particles such as position, momentum, and spin are correlated. Therefore, the relationship between entangled particles is predictive and can be understood by studying their physical properties. The process of “disentanglement” is carried out by limiting experiments to one of the two components of the system. After re-establishing one component by observation, the other one SPRING AND SUMMER 2021

can be inferred simultaneously (Schrödinger, 1935). For an entangled pair particle system with total spin zero, if one of the particles has clockwise spin, then the other particle will have counterclockwise spin (measured on the same axis). From this, it can be assumed that entanglement results in the partial knowledge of the quantum states of the components of a system. The opposite of an entangled system would be an independent system – a system in which the quantum states of particles are not inter-dependent. In such an independent system, knowledge of one state does not give information about another. On the other hand, in an entangled system, the constituents are not individual particles, but they exist together as a whole. The state of such a system is expressed as a superposition of the states of the local constituents. Entanglement between systems arises naturally – for example, if particles are generated together after high-energy collisions. This suggests that independent systems are rare since quantum particles are always interacting with each other, in one way or another. Their basic interaction renders them entangled. In 1935, Albert Einstein, Boris Podolsky, and Nathan Rosen argued that when two particles are correlated, they lose their individual states and share a unified quantum state together as a system. Through a thought experiment called the EPR paradox, the scientists claimed that there are “elements of reality” which are not well-defined in the then-standing quantum theory (Einstein et al., 1935). These elements of reality determine the measurement outcome of a specific experiment on these two particles. While the outcome of the measurement is known before the measurement takes place, this element of reality is something that exists in the “real” world and is “local”. Following from Einstein’s spacetime physics, local refers to a point on the light cone that happens in the past. Since the elements of reality are local, they can only be influenced by events that happen in their immediate surroundings (Van Raamsdonk, 2010). EPR called this the principle of locality, and it became the basic assumption of their 1935 paper.

"The property of spin is essential in characterizing the quantum states of particles and is at the foundation of quantum entanglement."

They demonstrated that in an entangled system of two particles, no action on one of the particles should instantly affect the second - which should not be possible, since it would suggest that information is travelling faster than light, which is forbidden by the theory of relativity. These hypotheses make up the principle of locality and together imply that the space between two points 101

Figure 1: Einstein’s light cone places the past, present, and the future on a three-dimensional graph in a spacetime plot. The positioning of the observer on the plot is used to make arguments about locality. Image Source: Wikimedia Commons

must be occupied by something (for example a field) if the points were to influence each other (Brunner et al., 2014). For particles A and B making up the entangled system, if the exact position of A is known, the exact position of B can be inferred. Alternatively, if the exact momentum of A is known, the exact momentum of B can be determined. Thus, EPR sought to establish the exact values of either the position or momentum of one of the particles when these values are known for the other particle. This is important because the values of B are determined through experiments on A and without the slightest physical disturbance on B (Kumar, 2011). The situation violates Heisenberg’s uncertainty principle as the paradox shows how particle B can have simultaneously exact values of position and momentum if these values were known for particle A. Although they will never be known simultaneously for A, the hypotheticality of the argument brings into question the validity of the uncertainty principle. The three scientists later realized that a measurement made on either of the particles in an entangled system apparently collapses the state of the entire entangled system. So, the uncertainty principle stands despite quantum entanglement. The collapse happens instantly, before any communication channel can be constructed between the particles (Anderson,

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2015). Assuming that the information cannot travel faster than light, the behavior or the observed properties of the second particle need to be pre-determined. Einstein hoped to explain this with his theory of hidden variables. The EPR paradox proved that quantum entanglement violates the local realism view of causality. The scientists believed that quantum mechanics is not a local theory and instead is a theory that follows “action at a distance” (Berkovitz, 2008). Einstein, Podolsky, and Rosen argued that particles like electrons and photons carry physical properties not yet included in quantum physics that lead to uncertainties called “hidden variables”. Quantum entanglement and the EPR paradox can be understood more readily with an example of the spins of fundamental particles. If two particles are formed spontaneously out of energy, it is reasonable to say that the particles will have opposite spins: one will be spin-up while the other will be spin-down, assuming that they are measured in the same direction. This is due to the law of conservation of angular momentum which requires the total angular momentum of a system (here the system being the entire universe) to remain constant. If the spins of these two particles are measured in the horizontal direction, there is a 50% chance that both measurements will have the same spin orientation, which will violate the conservation

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of angular momentum. According to quantum mechanics, such a probability means that the particles do not have a well-defined spin, or that their spins are entangled. By measuring the spin of one of the particles, the spin of the other one can be inferred instantly. Various cases of entanglement have been tested extensively. Irrespective of the direction of the original measurement and the distance between the particles themselves, the spins will always be opposite. The implications of this are quite groundbreaking. With two particles of undefined spin, the measurement of one of them immediately reveals the spin of the other. These two particles could be at two ends of a room or at two ends of the Milky Way, and the spin of one will still decide the spin of the other. The paradox aimed at addressing one particular issue: it appears that the measurement of the spin of the first particle has influenced that of the second particle instantly – faster than the speed of light. Einstein was irked by this seemingly apparent violation of his theory of relativity and proposed an alternate explanation. He believed that particles possess qualities (or properties) of hidden variables (Bohm & Aharonov, 1957). Einstein argued that particles possess qualities of these hidden variables in the form of information about what spin they should have if measured in any direction. That is, their spin is pre-determined and not affected by the measurements of the entangled companion particle (Einstein et al., 1935). The hidden variables are present inside the particles from the moment they are created, and we only learn of them when measurements are done. Since the information about spin states is already present inside them, no communication needs to happen between the entangled particles at a speed faster than that of light. Thus, Einstein believed that in this scenario the theory of relativity would not be violated. At the cornerstone of quantum entanglement lies the fact that if measurements are performed on one particle of an entangled system, the effects of these measurements are felt by the second particle instantly. However, this remains a controversial belief in modern physics. Some interpretations of the theory call the effect pseudo in nature, asserting that there is in fact no effect to be felt by the second particle. While this remains disputed, the following facts are universally agreed upon: •

Entanglement results in correlation between quantum states of particles in a system

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• •

•

The particles of the system do not need to be in physical proximity of each other An entangled system can be formed in a number of ways, the easiest one being when particles are generated simultaneously out of an energy bank The mutual dependence between the quantum states is inferred in the form of information about the states that can be deciphered This information can be used to probe the physical properties of the system and of its constituents

Bell’s Theorem In his 1964 paper, John Bell sought to further the discussion started by the EPR paradox by making a mathematical argument to “test” the theory of hidden variables by analyzing different scenarios nested within the EPR paradox. Bell’s theorem considers a quantum system of two entangled particles. Quantum mechanics allows predictions of correlations that would be observed if these two particles have their spin or polarization measured in different directions (Bell, 1964). Bell showed that if the local hidden variable theory holds, then these correlations would have to satisfy certain constraints, called Bell inequalities. The success of the theory lies in the fact that quantum mechanics predicts correlations that violate the inequalities. Thus, the only way hidden variables could be explained is if their nature is non-local (Werner, 1989). Quantum nonlocality is the phenomenon by which the measurement statistics of a quantum system do not admit an interpretation in terms of a local realistic theory. It is believed that for any pure entangled state there exists a choice of measurements that produce Bell nonlocal correlations.

"At the cornerstone of quantum entanglement lies the fact that if measurements are performed on one particle of an entangled system, the effects of these measurements are felt by the second particle instantly. However, this remains a controversial belief in modern physics."

By probing the EPR paradox further, Bell hoped to find an answer to a particularly tricky question: are the restrictions (like the uncertainty principle) on quantum mechanics in our theory or in reality? Einstein had argued that the restrictions were in theory and at the end of the day, the thenstanding theories were just not good enough to accurately describe quantum phenomena like entanglement. This point of view is called one of “blurred glasses”: a scenario in which the quantum theories are blurred glasses used to analyze the universe. Since they are blurred, they offer only a partial or an incomplete picture and only when we take them off, will we find more answers. The second point of view, the one Bell was aiming for, is one of “blurred reality”: a world

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where the quantum theories are complete, but the world is just messy in its own way. For example, when considering the uncertainty principle, the argument would be as: according to the blurred glasses picture, a particle in question has both definite position and momentum but because if the glasses we don’t know the values of both simultaneously. On the other hand, according to the blurred reality picture, a particle’s position and momentum cannot be measured simultaneously because the uncertainty is an intrinsic property, not an acquired one. The second case is what most scientists believe in since it’s the most logical (Bhatia, 2014).

"Bell showed that in a system of entangled particles, measurements about their spin orientations can be made."

Through a rigorous mathematical approach, Bell showed that in a system of entangled particles, measurements about their spin orientations can be made. The measurements are reflective of both the proposed hidden variables theory and the short straw of quantum mechanics. Since the spins of particles produced together should be opposite—in accordance with conservation laws—and, since the measurement of one of them is sufficient to infer the value of the other, Bell arranged the following experiment: Two particles make up an entangled system that is being probed for its properties. The spins of these particles are not well-defined since they are entangled; the spin of one is just the opposite of the other. There are two spin detectors set up, each capable of measuring spin in one of three directions which are chosen randomly and independent of each other. The particles are each sent to one of the detectors and their spins are measured simultaneously. After each measurement in a random direction, it is recorded whether the spins are both up, both down, or in opposite directions. The procedure is repeated numerous times to obtain a reasonable estimate the number of times the spins are in opposite directions. If the particles do contain hidden information, then they must have a pre-determined “plan” or a rulebook for what the spin should be when measured in a particular direction. For example, let Particle A have a plan of Up, Up, Up (UUU) for all directions and Particle B have a plan of Down, Down, Down (DDD) for every direction of measurement. The plan guarantees that the spins of the particles are different every time they are measured since they will always be opposite of each other. Now, if A has UDU for every direction and B has

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DDU, the spins will be different only 5/9 times, or 55.55% times. All the possible combinations of spins are listed below, and the different orientation pairs are marked with an asterisk.

UD* UU UD* DD DU* DD UD* UU UD*

From this plan of UDU and DDU, the probability that particles’ spins are opposite is 55.55% while it is 50% with the plan UUU and DDD. Bell’s inequality theorem argued that if the hidden variables theory was accurate then the spins should be different > 55.55% of the time. Through actual experimentation, it was soon discovered that the spins have to be different only and exactly 50% of the time. Bell ratified this using quantum mechanics as: if A is measured to have spin up, B will have spin down 1/3 of the times measured (accounting for the three directions of the detector). In the other two directions, B makes an angle of 60 with the detector’s direction leading to a spin up probability of 3/4. Simple math gives us: Pup= 23 × 34= 12 . So, B will have spin up only 1/2 of the times it is measured, leading to a predicted probability of 50%, in sharp contrast to the value predicted by the hidden variables theory. According to the hidden variables theory, the chances of both particles having the same spin orientation is at least 55.55%. But according to quantum mechanics, the answer is 50%. The data agrees with quantum mechanics, and thus, it rules out the hidden variables theory. This is again ground-breaking because the experiment proved that theories like the hidden variables idea are simply not true. As it stands, quantum mechanics is the most comprehensive description of most quantum phenomena. Bell’s theorem establishes a contradiction between hidden variables and the predictions of quantum mechanics, proving that the two are virtually incompatible.

Applications of Quantum Entanglement Quantum entanglement has a wide range of applications in modern physics. From quantum teleportation to quantum cryptography, entanglement forms the basis of many of DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

the world’s most widely used techniques of communication and computing.

to demonstrate entanglement and teleportation at a distance of 1600-2400 km (Jianwei et al., 2017).

Quantum teleportation

Quantum teleportation is a transfer of quantum states from one location to another for two identical particles. After this transfer, the state of the original particle is completely erased. Essentially, the state has been “transported” from one location to another without an explicit physical movement of the original particle (Ball, 2017). The teleportation is achieved through an entanglement of the two particles because entangled particles act like a system defined by a single wavefunction. In quantum teleportation, a pair of particles is entangled to set up a transmission channel between the sender “A” (Alice; a particle whose quantum state is known), the receiver “B” (Bob; the new particle), and the “C” (Charlie; an intermediate state particle between A and B). A and B are entangled in a system and thus any set of operations made on A are reflected on B instantly (Bennett, 1993). Through measurements on particles A and C, B placed in a state identical to C. This happens just as C’s state is erased. The original state is never copied; it is transferred completely. For all practical purposes, the original state is destroyed in the process to ensure that there is no duplicate. This obeys the law of no-cloning, a law that that states that it is impossible to clone a particle of unknown quantum state (Wootters & Zurek, 1982). This seems to violate Einstein’s theory of relativity because the transfer of states takes place instantly – faster than light. The resolution to this apparent paradox was the realization that Einstein’s theory prohibits faster-than-light influence. Fasterthan-light influence is what happens when an event in one location has a physical effect on another location in time less than it would take for light to travel the distance between these two locations. However, quantum teleportation does not transmit faster-than-light influence. After the teleportation, the state of A is copied onto that of B through the intermediary C. The novelty in teleportation lies in the fact that it can be achieved even if the state of A is unknown since the state does not matter. If A and B can be entangled, the state is irrelevant. Through their entanglement, teleportation is always possible. The physical distance between A and B also does not matter. In a 2017 experiment by scientist Pan Jianwei and his team, a quantum satellite was used

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Quantum cryptography

Entanglement also finds use in quantum cryptography. The main advantage of using quantum cryptography is its potential to encrypt data for longer periods of time, as opposed to classical cryptography (Bennett, 1992). In quantum cryptography, a secure communication method is established between parties sharing information. The method utilizes a protocol that allows parties to produce a shared random “key”. The process is also called quantum key distribution (QKD) and utilizes a series of photons that are used to transmit data from one location to another over a fiber optic cable. By comparing measurements of the properties of a fraction of these photons, the two endpoints can determine what the key is and if it is safe to use (Stebila et al, 2010). The key is only known to the participating parties and is used to encrypt and decrypt messages. Even if the encrypting and decrypting algorithms are publicly declared, the security of the cryptogram depends entirely on the secrecy of the key (Ekert, 1991). Entanglement is used to detect eavesdropping by establishing a threshold: if eavesdropping goes over this threshold the parties are notified through disturbances in the communication channel. If the photons in the cable are read or copied in any way by an eavesdropper, their state will change. The change will be detected by the endpoints. In other words, the photon cannot be read, copied, or forwarded without being detected. The principles of quantum entanglement stipulate that the process of observation of a quantum state causes perturbation due to any

Figure 2: A schematic diagram of quantum teleportation involving a photon that is transported between two points A and B. During the teleportation, photon at A is essentially deleted and an identical photon at B is produced by overwriting their respective quantum. Image Source: Wikimedia Commons

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measurements made during the observations. Various cryptography protocols are designed and put in place to ensure that any attempt by an eavesdropper to observe the transmitted photons will indeed perturb the transmission. The perturbation leads to transmission errors, which can be detected by the legitimate users. This is used to verify the security of the distributed keys (Kak, 2006).

"Qubits are used to store information on quantum computers in more compact and accessible ways, increasing their efficiency and making problem solving much easier."

There are many other applications of quantum cryptography that have entanglement at their core, such as quantum coin flipping and mistrustful cryptography. In both these protocols, participating parties do not trust each other with their information and there is no single key used for communication (Döscher & Keyl, 2002). Instead, both protocols require that parties communicate using qubits. A qubit is a two-state quantum-mechanical system and is the basic unit of quantum information and is primarily used to encode information. It is the quantum version of the classic binary bit physically realized with a two-state device (Schumacher, 1995). A qubit can have a value of both 0 and 1 whereas the classical bit has a value of either 0 or 1. Several different physical implementations of qubits are possible like the polarization of a photon, the energy levels of an ion, the nuclear spin states of an atom or the spin states of an electron. Like the particles considered earlier, when two qubits are entangled, the outcome of the measurements on the individual qubits could be 0 or 1. However, the outcome of the measurement on one qubit will always be correlated to the measurement on the other qubit. This is always the case, even if the qubits are separated from each other by a large distance. Moreover, unlike classical bits, qubits can be placed in a state of superposition. Qubits are used to store information on quantum computers in more compact and accessible ways, increasing their efficiency and making problem solving much easier. c

Superdense coding

Superdense coding is a quantum procedure that allows the communication of a definite number of bits between an entangled sender-receiver duo (Alice and Bob). The procedure allows Alice to send two bits to Bob – either 00, 01, 10, or 11 by only sending one at a time. Alice can choose a specific gate through which she wants to establish a communication channel and use to send the bits. The method works with a larger number of bits for the original sample – the key is that the actual number of bits sent is less than what 106

actually needs to be sent. The qubits sent are encoded with all the information required by Bob. The information can be subsequently retrieved by Bob due to the entanglement between them (Nielsen & Chuang, 2010). After receiving Alice's qubit, operating on the pair and measuring both, Bob obtains two classical bits of information. Superdense coding sounds similar to quantum teleportation, but they are the exact opposites of each other. The difference between them lies in the fact that teleportation transmits one qubit using two classical bits while superdense coding transmits two classical bits using one qubit. The teleportation protocol is the exact flipped version of the coding protocol. Superdense coding is a form of secure quantum communication and prevents eavesdroppers from gaining information. If an eavesdropper is present and intercepts Alice’s qubit, they cannot decrypt it since they do not have access to Bob’s entangled qubit. Without access to the entangled channel, the eavesdropper cannot obtain any information from the encrypted qubit. Moreover, an attempt to measure encrypted qubits in the channel is reported to both parties and the entire state of the qubit is collapsed (Nielsen & Chuang, 2010).

Entanglement of Macroscopic Systems The fragility of quantum states requires that they be isolated from their surroundings to accurately study them. This has hampered the pursuit of studying quantum phenomena on larger, macroscopic scales. Large systems are more likely to interact with their surroundings and it is much harder to isolate them. However, recent research has led to a better understanding of the mechanisms involving entanglement and its applications. In 2021, the entanglement between the motion of a mechanical operator and a cloud of atoms was reported by two independent research groups - Kotler et al. and Lépinay et al. The discovery was a breakthrough because it was the first of very few instances in which quantum effects were detected in macroscopic systems. While quantum mechanics was conceived in the context of subatomic particles, the ability to observe its properties on macroscopic systems holds great promise for fundamental research and technological applications. The first group deterministically generated and directly measured the correlations needed to verify entanglement between separate macroscale

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mechanical objects (Kotler et al., 2021). Using a superconducting electromechanical circuit and a pulsed microwave protocol, the scientists created a ground-state cool and entangled system of two mechanical drumheads with masses of 70 pg. The entanglement generated is followed by nearly quantum-limited measurements of the positions and the momenta of both mechanical oscillators. The team strongly entangled the massive oscillators and performed efficient tomography that is used to separately optimize the measurements of positions and momenta. The drums themselves are entangled by using a single microwave pulse that entangles photons in the cavity of Drum 1 with those in Drum 2. Due to this, the some of the correlations that originate from the interactions between them as a whole system get distributed in the form of correlations between the photons (Kotler et al., 2021). The second group succeeded in creating a “quantum mechanics free subspace” in which measurements of quantum states can be made even though they violate Heisenberg’s uncertainty principle. The violation means that measurements do not disturb the system even though the process of measurement is inherently supposed to do so (Lépinay et al., 2021). The biggest success of the second groups’ experiment and analysis comes from the fact that they demonstrated the monitoring of the entangled system without quantum backaction disturbance to the oscillator. It was long believed that it was not physically possible to observe such a disturbance-free system. This allows for a complete characterization of a weak classical force driving an oscillator. The procedure can similarly be used to increase the sensitivity in other quantum measurements at room temperatures. Due to the extremely low level of noise reported in their measurements, the group also believes that entanglement of the oscillators (or other macroscopic systems) is a key model in studying how to reduce errors in quantum protocols such as teleportation and entanglement-swapping of massive objects. The mechanical oscillators used are a part of hybrid systems that are well-isolated from their surroundings. Both experiments utilized pairs of micron-scale drumhead membranes that can oscillate together in near-perfect harmony and synchronization. The micron scale is very large when compared with the atomic scale that is generally the foundation for quantum phenomena. Photons are made to scatter off

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resonators in an elaborate set-up and are captured by detectors or made to interfere with each other match what would be expected if the vibrations were perfectly correlated (Berkowitz, 2021). The highly entangled and massive quantum systems studied by the two groups are uniquely poised to address fundamental tests of quantum mechanics, enable force sensing beyond standard quantum limits, and even serve as models for future research and exploration.

Conclusion Following the discovery of the quantum world and Schrödinger’s tell-all equation, many phenomena in 20th century physics suddenly became accessible to theorization and experimentation. Entanglement is one of these – a quantum phenomenon that links the quantum states of two particles produced together. Entanglement has a wide range of applications, from teleportation to cryptography and is being used to further the bounds of quantum computing and communication. Owing to its versatility and mathematical verification, entanglement promises a closer look into the very nature of fundamental particles. One of the many goals of understanding quantum entanglement further is to use it in solving the black hole information paradox. This is a part of an effort to understand scrambling which happens when entanglement takes place in a system made up of several particles. Such a large system can be considered to be analogous to information itself – the behavior of the system and of the individual particles is indeed information. As the entanglement among particles within the quantum system increases, the information spreads. For scientists, a black hole is the ultimate scrambler.

"In 2021, the entanglement between the motion of a mechanical operator and a cloud of atoms was reported by two independent research groups - Kotler et al. and Lépinay et al. The discovery was a breakthrough because it was the first of very few instances in which quantum effects were detected in macroscopic systems."

A hypothetical experiment calls for creating an entangled system comprising of a supercomputer and a black hole. Most of what we know about black holes comes from observations of their event horizons. An event horizon is the boundary within which the black hole's escape velocity is greater than the speed of light. In other words, beyond the event horizon a particle cannot escape the gravitational attraction of the black hole, including light. The event horizon is the last remaining “visible” part of a black hole. Once a particle is inside the horizon, moving into the hole is as inevitable as moving forward in time no matter what direction the particle is traveling, and can actually be thought of as equivalent to

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doing so, depending on the spacetime coordinate system used (Davies, 1992). By performing measurements on the so-called quantum states of the computer, the properties of the black hole can be measured. While it sounds far-fetched in practice, it should work in theory. Through a variational quantum algorithm that would exploit the leaking photons from the black hole’s event horizon, the computer would be able to run an optimization procedure to test various physical properties (Holmes & Sornborger, 2021). Probing this hypothetical experiment further is a test of the scalability and applicability of quantum machine learning. This is called the Hayden-Preskill thought experiment, which aims to do just that. While the entanglement thought experiment hasn’t been verified yet, the applications of applying quantum machine learning to black holes is very promising. It hopes to answer many other questions, such as those about Hawking Radiation and the encodingdecoding protocols in quantum information. References Anderson, R. (2015). “The Cosmic Compendium: Interstellar Travel” The Cosmic Compendium. p. 100. ISBN 9781329022027 Ball, P. (2017) “Quantum teleportation is even weirder than you think”. Nature doi.org/10.1038/nature.2017.22321 Bell, J. S. (1964). "On the Einstein Podolsky Rosen Paradox". Physics Physique Физика. 1 (3) pp. 195–200. doi:10.1103/ PhysicsPhysiqueFizika.1.195 Bennett, C. H.; et al. (1992). "Experimental quantum cryptography". Journal of Cryptology. 5 (1) pp. 3–28. doi:10.1007/bf00191318 Bennett, C. H.; Brassard, G.; Crépeau, C.; Jozsa, R.; Peres, A.; Wootters, William K. (1993). "Teleporting an unknown quantum state via dual classical and Einstein-Podolsky-Rosen channels". Physical Review Letters. 70 (13): 1895–1899. doi:10.1103/PhysRevLett.70.1895 Berkovitz, J. (2008). “Action at a Distance in Quantum Mechanics”. In Edward N. Zalta (ed.). The Stanford Encyclopedia of Philosophy (Winter ed.) Berkowitz, R. (2021). “Macroscopic systems can be controllably entangled and limitlessly measured”. Physics Today. (74), pp. 16-18. doi.org/10.1063/PT.3.4789 Bhatia, A. (2014). “The Experiment that Forever Changed How We Think About Reality”. Wired. Bohm, D.; Aharonov, Y. (1957). "Discussion of Experimental Proof for the Paradox of Einstein, Rosen, and Podolsky". Physical Review. 108 (4): 1070. doi:10.1103/PhysRev.108.1070 Brunner, N.; Cavalcanti, D.; Pironio, S.; Scarani, V.; Wehner, S. (2014). "Bell nonlocality". Rev. Mod. Phys. 86 (2): 419–478 doi:10.1103/RevModPhys.86.419

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Gut Microbiota: An Alternative Approach to Treating Depression BY SARAH LAMSON '24 Cover Image: The gut microbiome may be the key to finding alternative depression treatments. Image Source: Flickr

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Introduction In 2020, depression affected more than 264 million people in the world, but this number has grown due to the Covid-19 pandemic (WHO, 2020). During the pandemic, four in ten adults in the United States reported symptoms of anxiety or depression, while in June 2019, depression and anxiety was reported in only one in ten adults (Panchal et al., 2021). Following this surge in mental health issues, effective treatments are necessary. However, existing treatments such as behavioral activation, cognitive behavioral therapy (CBT), interpersonal psychotherapy, or antidepressant medication like selective serotonin reuptake inhibitors (SSRIs) and tricyclic antidepressants have their risks and are not always effective (WHO, 2020). For instance, antidepressants, one of the most common methods of treatment, are susceptible to heightened tolerance and withdrawal within patients and can have adverse side effects including anxiety, insomnia, and sexual dysfunction (Methiwala et al., 2021). Because of these risks, alternative methods are being investigated and developed

to help ameliorate today’s mental health crisis. Specifically, the role of the gut microbiome in mood disorders is an up-and-coming topic of interest.

Introduction to the Gut-Brain Axis The gut microbiome, a diverse ecosystem composed of 1013 to 1014 microbes, is comprised of different species of bacteria, viruses, fungi, and archaea (Kuwahara et al., 2020). The adult gut microbiota is constantly changing due to the influence of diet, disease, antibiotics, and other factors. When the gut’s homeostasis is disrupted, several different health problems can emerge, such as type 2 diabetes, inflammatory bowel disease, and obesity (Wen & Duffy, 2017). The gut microbiome also has a direct impact on mood disorders, including depression. The interaction between the gut and brain can be explained through the gut-brain-axis (GBA), or the bidirectional communication between the enteric and central nervous system. The GBA connects the brain and gut through many DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 1: The gut microbiome is connected to the brain through the GBA. Because of the relationship, the gut is linked to mood. Image Source: Pixabay

pathways such as the HPA axis, immune system, and nervous system (Liang et al., 2018). For example, the gut microbiota influences cytokine production, inflammation, and the immune system by interacting with the lymphatic system and immune cells. Another pathway involves the vagus nerve, which links the gut to the brain. Since sensory neurons are in contact with the gut microbiota, the latter influences the release of gut hormones and gastrointestinal motility. The gut’s microbiota and metabolites can also directly affect brain stress response, sleep, function, and hormone release (Smith et al., 2019). Finally, the neuroendocrine pathway connects the brain to the gut because the intestine is the body’s largest endocrine organ (Feng et al., 2018). Each of these pathways, while still not entirely understood by researchers, play a role in the gut’s connection to the brain.

Lachnospiraceae and Ruminococcaceae, the genera Faecalibacterium and Ruminococcus, and the species Lactobacillus and Bifidobacterium are all less abundant in patients with depression (Du et al., 2020). Additionally, a study by Jiang and colleagues found that Bacteroidetes, Proteobacteria and Actinobacteria were overrepresented in depressed patients while Firmicutes were underrepresented (Jiang et. al, 2020). But despite these patterns, there is no specific gut microbiome composition for patients with depression. Additionally, there is no single healthy gut microbiome profile either, a concept that further complicates these studies. To fully understand the gut microbiome of a depressed patient, further research will be necessary.

Recent studies show that the dysfunction of the GBA is linked to various mental illnesses and neurological disorders. This dysfunction can be caused by changes in the composition of the gut microbiota, known as gut dysbiosis. In this paper, methods of altering a patient’s gut microbiota are explored as potential therapeutic options for patients with depression.

Once the specific patterns of the gut microbiota in depressed patients are better understood, the gut could be manipulated to restore its balance and reduce depressive symptoms. Extensive research into gut microorganism profile patterns could also prevent microbiota-involved treatment options from interfering with the microbiota necessary for other aspects of a patient’s health. The treatment methods described below could be administered alone or concurrently with existing antidepressant medications. While further research is still necessary to make this option more effective, current studies indicate that the GBA could be an essential target for future treatment options.

Depression’s Connection with the Gut In patients with depression, the gut microbiome profile has patterns that differ from that of those without this mental illness. Scientific studies have demonstrated that patients with depression have gut microbiomes that are less diverse and less abundant than that of controls. Studies have discovered that, specifically, the bacterial families SPRING AND SUMMER 2021

GBA-Related Depression Treatment Options

"found that Bacteroidetes, Proteobacteria and Actinobacteria were overrepresented in depressed patients while Firmicutes were underrepresented"

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Figure 2: Probiotics modify the gut microbiome by adding microorganisms to the gut. Image Source: Wikimedia Commons

"Certain probiotics, such as L. plantarum, B. dentium, and L. brevis, can increase small-chain fatty acid (SCFA) levels in the gut, which subsequently stimulate enterochromaffin cells and cause the release of serotonin."

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Fecal Microbiota Transplantation (FMT), a procedure that transplants the feces of a healthy individual into a patient, can be used to alter the composition of the gut microbiome. FMT is administered by way of colonoscopy, oral capsule, nasogastric tube, nasoduodenal tube, esophagogastroduodenoscopy, or retention enema (Hsu et al., 2019). Currently, this procedure is used to treat C. difficile colitis, a species of bacteria that causes colon inflammation and severe diarrhea, but researchers are looking to expand this method into other avenues of care, including depression (Gupta et al., 2015). Various studies demonstrate FMT’s potential to treat depression. In one study done by Zheng and colleagues, the transplantation of feces from mice with depression-like behavior into germfree mice was compared to the transplantation of feces from mice without this behavior. When the mice were transplanted with the “depression microbiota,” depression-like behavior was subsequently observed (Zheng et al., 2016). Additional studies on alcoholism and anorexia, both of which are closely tied to mood and anxiety disorders, support the finding that FMTs from healthy donors can alleviate depressive symptoms (Meyyappan et al., 2020). While this technique has the potential to reduce depressive symptoms, there are risks and limitations. The effects of FMTs only appear to last for 3-6 months for mood disorders, so the procedure would likely need to be repeated to maintain the intended results (Meyyappan et al., 2020). Many adverse side effects are also associated with this procedure, including C.

difficile infections, peritonitis, IBS, and mild symptoms like diarrhea, nausea, constipation, and vomiting, each with varying levels of severity (Wang et al., 2016). Psychobiotics “Psychobiotics,” probiotics and prebiotics that can alter mood and cognitive function, are another up-and-coming approach to treating depression. Probiotics modify the gut microbiome by adding microorganisms to the gut, while prebiotics nourish specific microbial species with chemical compounds. Probiotics are currently used for gastrointestinal conditions such as antibioticassociated diarrhea, C. difficile infections, constipation, and IBS (U.S. Department of Health and Human Services, 2019). Prebiotics, on the other hand, can help with digestion, enhance the production of valuable vitamins, and help regulate the immune system (Markowiak & Śliżewska, 2017). Because of these supplements’ interactions with the gut-brain-axis, researchers are investigating their potential as a treatment for depression. In one study by Akkasheh and colleagues, the probiotics L. acidophilus, L. casei, and B. longum significantly reduced depressive scores (determined using the Beck Depression Inventory questionnaire) in comparison to the placebo group (2016). A study by Kazemi and colleagues also revealed that probiotics reduced the depression scores in patients (2019). Certain probiotics, such as L. plantarum, B. dentium, and L. brevis, can increase small-chain fatty acid (SCFA) levels in the gut, which subsequently stimulate enterochromaffin cells and cause the

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acids (PUFAs) and micronutrients also possibly play a role in influencing depression symptoms. Omega-3s act as prebiotics in the body because of their ability to regulate the gut microbiota composition and affect mood (Costantini et al., 2017). Micronutrients, such as iron and vitamin D, influence the gut’s microbiota, but an understanding of how these nutrients affect mood is currently lacking (Bear et al., 2020). Therefore, micronutrients can manipulate the gut’s composition, but it is unclear whether this manipulation could be used to treat depression. While the connection between mood and diet is not well understood today, diet could become a key method of decreasing the risks or monitoring the symptoms of depression and other mood disorders. release of serotonin. This release of serotonin plays an important role in monitoring the mood and cognitive functions of an individual, so this probiotic has a direct impact on the symptoms of depression (Cheng et al., 2019). The effectiveness of probiotics can be enhanced by combining them with prebiotics to create a mixture called a synbiotic. Synbiotics allow probiotic bacteria to populate the gut while the prebiotics trigger the growth of the gut microbiota (Methiwala et al., 2021). This technique of reducing depressive symptoms is less intrusive and risky compared to FMTs. Diet In addition to FMTs and psychobiotics, diet is another possible direction for gut microbiotabased treatments of depression. Various studies show that diet can partially or fully mediate the composition of the gut microbiome. However, the connection is not fully understood: the studies conducted on this topic contain conflicting results that do not provide a clear picture for how diet can affect the microbiome and the probability of depression. Despite this, since psychobiotics are components of many foods, diet directly intertwines with the use of probiotics and prebiotics. Because of this connection, specific diets can provide patients with the psychobiotics necessary to monitor their symptoms. Several human studies show that diets rich in whole grains, fruits, vegetables, fish, and olive oil are linked with a lower risk of depression (Lai et al., 2013). The fiber found in fruits and vegetables and whole grains reduces the risk of depression by acting as a prebiotic for microorganisms in the gut (Clutter, 2020). Omega-3 polyunsaturated fatty

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Figure 3: Omega-3s, a type of prebiotic, can alter the gut microbiome and thereby affect mood. This supplement can be administered through capsules or in foods like fish, nuts, and seeds (U.S. Department of Health and Human Services, 2021). Image Source: Wikimedia Commons

Conclusion Research into new depression treatments contributes not only to the fight against depression, but also to the greater understanding of the gut and its influence over the body. Other diseases and disorders like autism, epilepsy, Parkinson’s disease, Alzheimer’s disease, and autoimmune diseases appear to be connected to the activity of the GBA. Because the gut is connected to many different diseases and conditions, FMTs, psychobiotics, and specific diets could be adapted for use as alternative or complementary treatment options for more than just depression. Further research into the GBA is necessary to uncover the intricacies of how the gut interacts with each body system, as well as its role in various diseases and disorders. References Akkasheh, G., Kashani-Poor, Z., Tajabadi-Ebrahimi, M., Jafari, P., Akbari, H., Taghizadeh, M., Memarzadeh, M. R., Asemi, Z., & Esmaillzadeh, A. (2016). Clinical and metabolic response to probiotic administration in patients with major depressive disorder: A randomized, double-blind, placebo-controlled trial. Nutrition, 32(3), 315–320. https://doi.org/10.1016/j. nut.2015.09.003 Bear, T. L., Dalziel, J. E., Coad, J., Roy, N. C., Butts, C. A., & Gopal, P. K. (2020). The Role of the Gut Microbiota in Dietary Interventions for Depression and Anxiety. Advances in Nutrition, 11(4), 890–907. https://doi.org/10.1093/advances/ nmaa016 Cheng, L.-H., Liu, Y.-W., Wu, C.-C., Wang, S., & Tsai, Y.-C. (2019). Psychobiotics in mental health, neurodegenerative and neurodevelopmental disorders. Journal of Food and Drug Analysis, 27(3), 632–648. https://doi.org/10.1016/j. jfda.2019.01.002 Clutter, C. (2020, February 14). Of microbes and mental health: Eating for mental wellness. ASM.org. https://asm.org/ Articles/2020/February/Of-Microbes-and-Mental-HealthEating-for-Mental-We.

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Costantini, L., Molinari, R., Farinon, B., & Merendino, N. (2017). Impact of Omega-3 Fatty Acids on the Gut Microbiota. International Journal of Molecular Sciences, 18(12), 2645. https://doi.org/10.3390/ijms18122645 Du, Y., Gao, X.-R., Peng, L., & Ge, J.-F. (2020). Crosstalk between the microbiota-gut-brain axis and depression. Heliyon, 6(6). https://doi.org/10.1016/j.heliyon.2020.e04097

issue-brief/the-implications-of-covid-19-for-mental-healthand-substance-use/. Smith, K. S., Greene, M. W., Babu, J. R., & Frugé, A. D. (2019). Psychobiotics as treatment for anxiety, depression, and related symptoms: a systematic review. Nutritional Neuroscience, 1–15. https://doi.org/10.1080/1028415x.2019.1701220

Feng, Q., Chen, W.-D., & Wang, Y.-D. (2018). Gut Microbiota: An Integral Moderator in Health and Disease. Frontiers in Microbiology, 9. https://doi.org/10.3389/fmicb.2018.00151

U.S. Department of Health and Human Services. (2021, August). Office of dietary supplements - omega-3 fatty acids. NIH Office of Dietary Supplements. https://ods.od.nih.gov/ factsheets/Omega3FattyAcids-Consumer/.

Gupta, S., Allen-Vercoe, E., & Petrof, E. O. (2015). Fecal microbiota transplantation: In perspective. Therapeutic Advances in Gastroenterology, 9(2), 229–239. https://doi. org/10.1177/1756283x15607414

U.S. Department of Health and Human Services. (2019, August). Probiotics: What you need to know. National Center for Complementary and Integrative Health. https://www.nccih. nih.gov/health/probiotics-what-you-need-to-know.

Hsu, W. H., Wang, J. Y., & Kuo, C. H. (2019). Current applications of fecal microbiota transplantation in intestinal disorders. The Kaohsiung Journal of Medical Sciences. https:// doi.org/10.1002/kjm2.12069

Wang, S., Xu, M., Wang, W., Cao, X., Piao, M., Khan, S., Yan, F., Cao, H., & Wang, B. (2016). Systematic Review: Adverse Events of Fecal Microbiota Transplantation. PLOS ONE, 11(8). https:// doi.org/10.1371/journal.pone.0161174

Jiang, H., Ling, Z., Zhang, Y., Mao, H., Ma, Z., Yin, Y., Wang, W., Tang, W., Tan, Z., Shi, J., Li, L., & Ruan, B. (2015). Altered fecal microbiota composition in patients with major depressive disorder. Brain, Behavior, and Immunity, 48, 186–194. https:// doi.org/10.1016/j.bbi.2015.03.016

Wen, L., & Duffy, A. (2017). Factors influencing the gut microbiota, inflammation, and type 2 diabetes. The Journal of Nutrition, 147(7). https://doi.org/10.3945/jn.116.240754

Kazemi, A., Noorbala, A. A., Azam, K., Eskandari, M. H., & Djafarian, K. (2019). Effect of probiotic and prebiotic vs placebo on psychological outcomes in patients with major depressive disorder: A randomized clinical trial. Clinical Nutrition, 38(2), 522–528. https://doi.org/10.1016/j.clnu.2018.04.010 Kuwahara, A., Matsuda, K., Kuwahara, Y., Asano, S., Inui, T., & Marunaka, Y. (2020). Microbiota-gut-brain axis: Enteroendocrine cells and the enteric nervous system form an interface between the microbiota and the central nervous system. Biomedical Research, 41(5), 199–216. https://doi. org/10.2220/biomedres.41.199

World Health Organization. (2020, January 30). Depression. World Health Organization. https://www.who.int/news-room/ fact-sheets/detail/depression. Zheng, P., Zeng, B., Zhou, C., Liu, M., Fang, Z., Xu, X., Zeng, L., Chen, J., Fan, S., Du, X., Zhang, X., Yang, D., Yang, Y., Meng, H., Li, W., Melgiri, N. D., Licinio, J., Wei, H., & Xie, P. (2016). Gut microbiome remodeling induces depressive-like behaviors through a pathway mediated by the host’s metabolism. Molecular Psychiatry, 21(6), 786–796. https://doi.org/10.1038/ mp.2016.44

Lai, J. S., Hiles, S., Bisquera, A., Hure, A. J., McEvoy, M., & Attia, J. (2013). A systematic review and meta-analysis of dietary patterns and depression in community-dwelling adults. The American Journal of Clinical Nutrition, 99(1), 181–197. https:// doi.org/10.3945/ajcn.113.069880 Liang, S., Wu, X., Hu, X., Wang, T., & Jin, F. (2018). Recognizing Depression from the Microbiota–Gut–Brain Axis. International Journal of Molecular Sciences, 19(6), 1592. https://doi. org/10.3390/ijms19061592 Markowiak, P., & Śliżewska, K. (2017). Effects of Probiotics, Prebiotics, And Synbiotics on human health. Nutrients, 9(9), 1021. https://doi.org/10.3390/nu9091021 Methiwala, H. N., Vaidya, B., Addanki, V. K., Bishnoi, M., Sharma, S. S., & Kondepudi, K. K. (2021). Gut microbiota in mental health and depression: Role of pre/pro/synbiotics in their modulation. Food & Function, 12(10), 4284–4314. https:// doi.org/10.1039/d0fo02855j Meyyappan, A. C., Forth, E., Wallace, C., & Milev, R. (2020). Effect of fecal microbiota transplant on symptoms of psychiatric disorders: A systematic review. https://doi.org/10.21203/ rs.3.rs-16542/v1 Panchal, N., Kamal, R., Cox, C., & Garfield, R. (2021, February 10). The Implications of COVID-19 for Mental Health and Substance Use. KFF. https://www.kff.org/coronavirus-covid-19/

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Gene Therapy as a Treatment for Malignant Brain Tumors BY SOYEON (SOPHIE) CHO '24 Cover Image: A highly magnified image of glioblastoma cells, showing their histopathology. Characteristics include nuclear pleomorphism, shown by the variation in the sizes and shapes of cells in the micrograph. Below the pink section, a cell is undergoing multiple mitoses (MM), and a cell towards the top of the image has multiple nuclei (MN), suggesting growth of tumor cells. Image Source: Wikimedia Commons

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Introduction

Brain Tumors

Brain tumors are among the most difficult tumors to treat, mainly due the brain’s roles in forming the central nervous system and protecting the inner spaces from foreign material. Conventional treatments such as resection surgery, radiotherapy, and chemotherapy often does not stop recurrence or the decline of brain functions and health, shown by high recurrence rates of brain tumors and low probabilities of surviving for more than several years (Stupp et al., 2005; Oh et al., 2020; Weller et al., 2013). To address these difficulties, scientists have explored gene therapy to bypass the brain’s protective structures and selectively target tumor cells using vectors to transport transgenes, or genes of interest added to the vector genomes. Despite the development of various gene therapy strategies, they share the same challenge of killing tumor cells while fulfilling two goals: effective transgene expression in the tumor site and minimal damage to normal cells near the tumor cells (Lawler et al., 2005). This review will consider gene therapy as a treatment for malignant brain tumors, specifically for the most common type: malignant gliomas.

Around thirty percent of brain and central nervous system tumors, as well as 80% of malignant brain tumors are malignant gliomas, occurring in the glial cells (i.e., astrocytes, oligodendrocytes, and ependymal cells) of the brain, or non-neuronal cells in the nervous system responsible for neuron protection and homeostasis (Goodenberger & Jenkins, 2012; Fields et al., 2013). Out of malignant gliomas, glioblastomas, or glioblastoma multiforme (GBM), are the most aggressive type of cancer, as they have a median patient survival time of 12 to 15 months (Stupp et al., 2005). GBM begins in the astrocytes before invading other types of cells. In general, current treatments for gliomas include resection surgery, radiotherapy, and chemotherapy. GBM patients typically undergo radiotherapy and chemotherapy, and many are also prescribed temozolomide due to the fast development of the tumor (Stupp et al., 2005; Oh et al., 2020). However, six to nine months after these standard treatments, GBM recurrence rates are around 90%, and median overall survival DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 1: Two MRI scan of low grade, encapsulated glioma, from coronal (left) and axial (right) view. Both arrows point to the gliomas. Image Source: Wikimedia Commons

(OS) time is less than 2 years (Weller et al., 2013; CBTRUS, 2012). Median OS is the time taken for half of a group of patients to be alive since the start of a treatment (NIH, 2020).

kill (von Deimling et al., 1995). Scientists have explored alternative treatments such as gene therapy to limit tumor cell growth and treat brain tumors such as GBM.

The high recurrence rate and low median OS time among glioma patients are caused by migratory tumor cells that do not divide as they move from the primary tumor. As a result, glioma cells not only spread tumor cells to other parts of the brain, but also are less effectively targeted by drugs that usually target dividing cells, though, fortunately, gliomas do not metastasize extracranially (Armento et al, 2017). These intracranial metastases can harm surrounding brain tissue and prevent surgeons from completely resecting GBMs (Mozhei et al., 2020).

Gene Therapy

Another barrier to treating GBM is the bloodbrain barrier (BBB), a semipermeable layer consisting of endothelial cells, pericytes, and astrocytes, regulating transport of molecules between the cerebral blood vessels and the brain (Daneman & Prat, 2015). The BBB is impermeable to bacteria, large molecules with a molecular weight larger than 40 kilodaltons, hydrophilic molecules, and other toxic molecules, but receptors on the BBB selectively allow glucose as well as small, lipophilic ions and molecules through the layer (Dotiwala et al., 2020; Mehta et al., 2017). Many cancer drugs are too large to pass the BBB, and if they do enter the functional tissue, or parenchyma, of the brain, not enough molecules are allowed in, leading to lower bioactive concentrations of a drug (Zhou et al., 2017). Consequently, cancer drugs cannot effectively target tumor cells on the side of the BBB not originally exposed to the cancer therapy drug. As a result, these genetically diverse tumor cells in GBM cases are difficult to target and SPRING AND SUMMER 2021

Gene therapy is defined as the range of strategies that correct altered, or mutated, genes or make site-specific modifications that improve prognosis (Goncalves & Paiva, 2017). Due to the applicability of gene therapy in many different mechanisms within the body, researchers have studied gene therapy and its applications to treat a range of diseases, including cystic fibrosis (Davies et al., 2001) and cancer (Misra, 2013). Gene therapy systems consist of a transgene, a gene that is introduced into the genome of the vector, and a vector, which transports itself and the transgene of interest to the tumor site (Fulci & Chiocca, 2010; Lawler et al., 2005). These systems combine the transgene and the vector through recombinant DNA technology, a widely used technique that combines genetic material from multiple sources, including humans and viruses. Therefore, recombinant DNA technology allows for scientists to combine specific genes of interest with a vector.

"Many types of gene therapy use viral vectors due to their efficient gene delivery relative to non-viral vectors such as naked DNA and liposomes"

Many types of gene therapy use viral vectors due to their efficient gene delivery relative to nonviral vectors such as naked DNA and liposomes, where the vectors are injected into the patient and enter the cytoplasm through processes like endocytosis (Lam & Breakefield, 2001). This is because viral vectors are subsequently replicated or transcribed and translated to produce various molecules that inhibit tumor cell growth, unlike non-viral vectors that do not replicate or transcribe and translate the gene of interest and may require more administration of the material 117

(Pilaro & Serabian, 1999). The human immune system responds to these antigenic vectors and readily creates antibodies to the virus proteins, although this may decrease the efficiency of gene delivery.

"Around 70% of malignant primary brain tumors are malignant gliomas, showing that malignant gliomas comprising most of malignant brain tumors"

Gene therapy has been studied as a potential treatment for rapidly developing brain tumors because conventional treatments like chemotherapy are not effective against the semipermeable BBB, and malignant brain tumors are difficult to target due to the brain’s complexity (Gerstner & Fine, 2007). Around 70% of malignant primary brain tumors are malignant gliomas, showing that malignant gliomas comprising most of malignant brain tumors (Ostrom et al., 2013; Ahmed et al., 2014). Gene therapy vectors can directly inoculate tumor cells in gliomas because they are surrounded by nondividing cells and they do not metastasize, meaning they stay in one site (Lawler et al., 2005). Due to the localized nature of malignant glioma, many gene therapy studies are conducted on malignant glioma patients. Therefore, this review will be discussing gene therapy in relation to malignant brain tumors, with a focus on malignant gliomas. Among malignant gliomas, GBM makes up 60-70% of malignant gliomas and has a WHO tumor grade IV, the highest out of malignant gliomas (Kleihues et al., 2002). GBM is widely studied because it is highly vascularized and provide more opportunities for antiangiogenic treatments, explained later in the review (Indraccolo, 2004). Because other types such as anaplastic astrocytoma are less common, less studied, and less severe, research on GBM will be highlighted as adaptable treatments for less severe types of brain tumors.

Types of Gene Therapy for Brain Tumors Gene therapy delivers different combinations of transgenes and vectors, or vector-producing cells, which produce vectors on site, aiming to selectively kill tumor cells. For brain tumors, transgenes can perform many different functions. Some transgenes code for molecules such as interleukin (IL)-2, IL-4, and IL-12, which are cytokines that induce a host immune response against tumor cells (Fulci & Chiocca, 2010; Colombo et al., 2005). These genes are inserted to the genomes of vectors or vector-producing cells and transported to the tumor sites. The produced cytokines, or lymphokines, such as IL-2 induce lymphocytes – natural killer cells – to become lymphokine activated killer cells, showing that they use a targeting strategy to selectively kill

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tumor cells (Ge et al., 2011). However, toxicity from the direct administration of certain cytokines, such as IL-12, has been a recurring problem (Car et al., 1999). In response, Chiocca et al. found that administering GBM patients with human IL-12, a cytokine, followed by veledimex, a drug that activates the transcription of IL-12, produced antitumor immune responses with tolerable toxicity and side effects (Chiocca et al., 2019). Due to the activation drug, a smaller dose of vectors containing IL-12 could produce sufficient IL-12, which led to minimal toxicity in the tumor site and tolerable effects for the patients. Other transgenes produce tumor suppressors that are normally unexpressed by cancer cells (Fulci & Chiocca, 2010). Inserting tumor suppressor genes into the brain tumor site can improve the immune recognition of tumor cells, which causes apoptosis, or programmed cell death in the tumor cells (Lam & Breakefield, 2001). For example, the coxsackievirus and adenovirus receptors (CAR) act as a tumor suppressor in gliomas as well as other types of cancer, supporting that malignant glioma cells in the nervous system show a downregulation of CAR, which inhibits malignant tumor growth (Kim et al., 2003). Another major example is TP53, which produces the transcription factor and tumor suppressor p53. In around half of gliomas, the non-mutated, wild type p53 transcription factor is not present, and the mutated version accelerates tumor cell growth (Yahanda et al., 1995; Albertoni et al., 1998). Mutated p53 is sensitive to tumor related stress conditions like oxidative stress and limited nutrients, but more important, it responds through mechanisms that tumor cells rely on for survival (Mantovani et al., 2019; Senft & Ronai, 2016). For example, one of the responses is an increase in glucose import, which promotes the Warburg effect, or “aerobic glycolysis” (Zhang et al., 2013). The Warburg effect, a metabolism through which malignant tumor cells gain energy, describes that tumor cells gain adenosine triphosphate (ATP) through anaerobic glycolysis, regardless of oxygen availability (Warburg, 1956). Studies have demonstrated that transferring the wild type alleles of the p53 gene using adenoviral vectors limited the formation of human malignant glioma cells in mice (Cirielli et al., 1999). Other strategies related to tumor suppressors include transporting small interfering ribonucleic acid (siRNA) sequences that inhibit receptors like the epidermal growth factor receptor (EGFR), which are highly expressed in tumor

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cells (Fulci & Chiocca, 2010; Messaoudi et al., 2014). EGFRs support tumor cell development and help protect tumor cells from programmed cell death and autophagy, or the degradation of certain organelles due to starvation conditions. Messaoudi et al. showed that siRNA sequences targeting EGFR decreased EGFR expression and increased sensitivity to temozolomide, a drug used in chemotherapy, in GBM tumor cells. This study suggests that gene therapy could be combined with chemotherapy to produce better therapeutic effects. Furthermore, a Herpes Simplex Virus (HSV) 1 amplicon vector-mediated siRNA has inhibited GBM growth in mice, both in vitro and in vivo (Saydam et al., 2005). An HSV 1 amplicon vector is the same as an HSV 1 vector aside from the concatemeric deoxyribonucleic acid (DNA) plasmid, with multiple copies of DNA continuously forming the structure (Baez et al., 2018). To extend from recombinant vectors, other combinations of vectors, transgenes, and domains employ the same targeting strategy for tumor cells. Recombinant fusion proteins contain a toxin domain that induces cell death and a ligand binding domain that binds with receptors found on tumor cells such as IL-4 receptors (Lam & Breakefield, 2001; Puri, 1999). A toxin domain bound to a monoclonal antibody for the human transferrin (Tf) receptor also decreased tumor cell growth in mice, because the Tf receptor is highly expressed in glioma tumor cells, and when the toxin domain is bound to the Tf receptors, it is cytotoxic for the tumor cells (Laske et al., 1994). A variation of these targeting combinations binds capsids of viral vectors instead of proteins with ligands or antibodies for receptors that are highly expressed on tumor cells (Lawler et al., 2005). For example, a specific type of conditionally replicative adenoviruses (CRADs) contains antibodies for the epidermal growth factor receptor (EGFR), which is highly expressed in many tumor cells (van Beusechem et al., 2003). Another targeting combination modifies a part of the viral vector’s genome to change native structures on the viral capsid for binding to specific tumor cell receptors (Krasnykh et al., 2000). For example, glioma tumor cells do not express the aforementioned coxsackievirus and adenovirus receptors (CAR), which limits conditionally replicative adenoviruses (CRADs) like adenovirus serotype-5 (Ad5) from selectively targeting tumor cells (Kim et al., 2003; van Beusechem et al., 2003). To address this problem, scientists have inserted the Arg-Gly-Asp (RGD)

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sequence into the existing CAR binding domain, called the Ad5 knob, so that the knob interacts with integrin receptors on tumor cells, not the non-existent CARs on glioma cells, and more effectively infect the tumor cells through adenoviral internalization by CRADs (Wickham et al., 1993; Dmitriev et al., 1998; Lamfers et al., 2002). These examples utilize the recombinant DNA technology that allow for genes of interest to be added to the viral genomes. Some transgenes activate corresponding prodrugs to treat malignant brain tumors, and the addition of the prodrug makes the mechanisms more complex (Fulci & Chiocca, 2010). Prodrugs are non-toxic and require transformation for the desired pharmacological responses, unlike cancer drugs (Mishra et al., 2018; Zawilska et al., 2013). The traditional cancer drug treatments kill both normal and tumor cells through their cytotoxicity, while the targeted cancer treatments can be selectively toxic towards tumor cell. However, prodrugs can be converted into a toxic drug at the site of the brain tumor (Lam & Breakefield., 2001). This method addresses the main limitation of treating brain tumors with toxic cancer drugs because the BBB only allows small, non-foreign, non-toxic ions and molecules to cross and reduces the amount of cancer drug molecules that successfully cross the BBB and kill the tumor cells on site. Prodrugs are non-toxic as it crosses the BBB, and the prodrug activating transgene converts prodrug molecules to a toxic drug before dying from the toxicity, thus being a suicide gene (von Deimling et al, 1995; Mishra et al., 2018). For gene therapy, scientists categorize prodrugs as genetic prodrug activation therapy (GPAT), which use a recombinant vector with the gene for an enzyme that converts the prodrugs and the transcription sequence that transcribes the gene in tumor cells (Altaner, 2008). Once inside the tumor cell, the enzyme is produced by the transcription sequence, and it catalyzes a change in the structure of the prodrug so that it becomes cytotoxic and causes the death of the host cell. The first gene therapy clinically tested to treat GBM is a major example of prodrug therapy that recombines the HSV thymidine kinase (TK) gene from the herpes simplex virus (Lam & Breakefield et al., 2001; Mishra et al., 2018). The HSV TK gene produces the HSV TK enzyme, which is sensitive to an antiviral drug called ganciclovir (GCV). Heiss’ Phase 1 clinical trial by the National Institutes of Health used mouse retroviral vectors produced by the NIH 3T3 cell to carry the HSV TK gene to the site of the brain tumor, past the BBB (Heiss, 1999). The HSV

"Some transgenes activate corresponding prodrugs to treat malignant brain tumors, and the addition of the prodrug makes the mechanisms more complex"

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TK/GCV treatment has underwent Phase I, II, and III trials, showing its potential for clinical use, although the Phase III trial did not show significant differences between HSV TK/GCV and standard radiotherapy following surgical resection (Klatzmann et al., 1998; Rainov, 2004). The vectors incorporate the HSV TK gene into tumor cell genomes, bypassing non-proliferating, non-cancerous cells nearby and selectively targeting tumor cells, due to their rapid cell division and DNA synthesis (Colombo et al., 2005; Tseng et al., 2006). More specifically, when GCV is administered to the patient, the HSV TK gene in the tumor cells acts as a suicide gene. The resulting HSV TK enzyme phosphorylates GCV into GCV triphosphate, meaning it introduces phosphate groups into GCV. GCV triphosphate competes with deoxyguanosine triphosphate during DNA synthesis. This hinders DNA polymerase from properly synthesizing the tumor cell DNA , forms breaks in the DNA and hinders DNA synthesis (Moolten & Wells, 1990; Tomicic et al., 2002; Mar et al., 1985). Therefore, the HSV TK/GCV mechanisms operates when the host cell is replicating DNA, allowing for selective death of tumor cells. This gene therapy method reduces the concern of malignant cells persisting after treatment, since both the enzymatic process and the host immune response eliminate malignant cells. For the host immune response, HSV TK gene and GCV treatment for human GBM resulted in the secretion of interferon gamma, released by peripheral mononuclear cells, which include lymphocytes (Rainov et al., 2000; Tau & Rothman, 1999). This shows that the tumor infiltrating lymphocytes reacted more to malignant tumor cells following HSV TK/GCV treatment. Similarly, this response is reflected for tumor infiltrating lymphocytes in other types of cancer such as prostate cancer (Yanagisawa et al., 2020). However, subsequent studies have demonstrated that large injections of the retroviral vectors with the HSV TK gene can only treat relatively small brain tumors, due to limited gene distribution techniques, lipophobic traits of GCV, and limited activity of HSV TK enzymes (Ram et al., 1997; Stedt et al., 2015). Expanding from these challenges, using both the HSV TK gene and the IL-2 gene, which forms a cytokine inducing an anti-cancer immune response, in creating vectorproducing cells has shown promising results for GBM patients (Colombo et al., 2005). Other transgenes can be introduced to the genome of a patient’s brain tumor cells to inhibit angiogenesis, or the growth of blood vessels, and

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prevent angiogenesis from aiding brain tumor growth (Fulci & Chiocca, 2010). Like other types of cancer, brain tumors like GBM require the growth of blood vessels to deliver nutrients and oxygen in order to continue to grow, suggesting that inhibiting angiogenesis may help treat brain tumors (Feldman & Libutti, 2000). Many anti-angiogenetic agents inhibit the vascular endothelial growth factor (VEGF), a dominant growth factor and promoter of angiogenesis that binds to the VEGF receptor to promote malignant brain tumor growth (Reardon et al., 2008). For example, retrovirus vectors carrying truncated versions of the main VEGF receptor 2 (VEGFR-2) were transferred to the tumor site, causing two anti-tumor effects. First, the vectors co-express the mutated VEGFR-2, thus causing dominant negative inhibition, which means the expression of the vectors inhibited the wild type of the VEGF receptor. Second, since the mutated VEGFR-2 can still bind to VEGF, the introduction of the vectors depleted VEGF molecules and subsequently inhibited angiogenesis (Machein et al., 1999). In another study, injecting the antisense cDNA sequence for VEGF receptors inhibited tumor growth and reduced blood vessel growth that usually accompanies tumor growth in mice (Saleh et al., 1996). This study reflects antisense gene therapy, which depends on the fact that an antisense cDNA sequence, also called antisense oligonucleotide, is complementary to the template DNA of a gene of interest (Dias & Stein, 2002). This means it can bind to the template sequence for VEGF on pre mRNA or mature mRNA, which creates steric hindrance, or physical interference by the surrounding ligands in a reaction, for that sequence. More specifically, it prevents the translation of VEGF sequences into proteins (Chan et al., 2006). Alternatively, after binding to the template DNA, the antisense sequence may signal RNase-H to cleave the VEGF section and stop protein synthesis (Kole et al., 2012).

Vectors for Brain Tumors Gene therapy strategies utilize various vectors to express transgenes at the tumor site. Vectors can be divided into non-viral and viral vectors, the latter of which are subjects of clinical trials. Viral vectors are categorized into two main categories: non-replicating viruses (NRVs) and replicating, oncolytic viruses (OVs). NRVs include adenoviruses, adeno-associated viruses, retroviruses, lentiviruses, and HSV amplicons (Fulci & Chiocca, 2010; Saydam et al., 2005). OVs include replicating forms of the viruses in NRVs, but current clinical trials have tested adenoviruses, HSV, and vaccinia, or the cowpox virus (Fulci &

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Chiocca, 2010; Filley & Dey, 2017; Kirn et al., 2001; Thorne et al., 2006). In particular, CRADs have been applied in many of the gene therapy strategies involving the infection of tumor cells. For example, inserting the RGD sequence into the CRADs’ binding domain for CAR, a receptor absent in tumor cells, helped CRADs bind to integrin receptors instead and infect the tumor cells through adenoviral internalization and replication (Kim et al., 2003; Wickham et al., 1993). To compare the two categories, clinical trials have tested with more NRVs because their lack of replicability prevents adverse effects from OVs infecting tumor cells, making them a safer vector to test. However, OVs’ infection of tumor cells is more efficient, because OVs replicate unlike NRVs and these offspring kill tumor cells more quickly. This increase in the number of virus vectors in the tumor site is an advantage that OVs do to share with anticancer drugs or radiation, and it suggests a potential application of OVs in multimodal strategies where multiple vectors or domains could selectively target tumor cells (Fulci & Chiocca, 2003). Due to the ability to replicate, OVs are very cytotoxic even in their non-recombinant forms without transgenes, explaining clinical trials on both nonrecombinant and recombinant forms of OVs. Adenoviruses are non-enveloped viruses lacking lipid layers and contain double stranded DNA (Banerjee et al., 2021). Many types of gene therapy, including HSV TK/GCV treatment, utilize adenoviruses because they can be produced at high titers, or high concentrations, and they can transduce modified genetic material to cells regardless of whether they are dividing or not. Adeno-associated viruses (AAVs) are nonenveloped viruses with single stranded DNA (Asad et al., 2017). AAVs have smaller genomes (4.7 kilo-base pairs) than adenoviruses (up to 35 kilo-base pairs). AAVs also need helper viruses to replicate inside the human tumor cells, but their small sizes allow AAVs to quickly enter solid tumor cells like glioma cells (Enger et al., 2002). Retroviruses are RNA viruses that insert a copy of their genetic material into host cells for replication, and lentiviruses are types of retroviruses that infect host cells and produce a delayed onset of illnesses. Both retroviruses and lentiviruses contain single stranded positive sense RNA, but retroviruses only transduce tumor cells with their RNA during cell division, because this infection requires the absence of nuclear membranes in mitosis (Dufait et al., 2012; Lewis & Emerman, 1994). Nevertheless, retroviral vectors were used for the first clinical trials of HSV TK/GCV treatment in glioma patients (Heiss,

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1999). Lentiviruses infect both non-dividing and dividing cells, since they can transport their RNA even with the nuclear membrane, and they also are less likely to cause insertional mutagenesis, or the creation of mutations than retroviruses (Banerjee et al., 2021). Non-viral vectors include naked DNA, liposomes, and nanoparticles. They enter the tumor cell via endocytosis (Yoshida & Mizuno, 2003; Banerjee et al., 2021). Naked DNA refers to DNA sequences not bound to other proteins or molecules, but they are not often used due to the lack of protection around the sequence. Liposomes are small vesicles made up of lipids, and they have been tested with various transgenes such as the HSV TK gene (Fulci & Chiocca, 2010; Reszka et al., 2005). Reszka et al. conducted a clinical trial regarding liposomal vectors for the HSV TK gene/ GCV treatment, and the treatment decreased tumor volume by half and produced no serious side effects. Liposomes are more preservable than naked DNA and not highly cytotoxic, although this vector requires further research due to the current focus on viral vectors (Yoshida & Mizuno, 2003). Nanoparticles include a wide array of small, manufactured molecules that may more easily enter the brain parenchyma through the BBB. One example is the spherical nucleic acid gold nanoparticle transferring siRNAs to limit the production of Bcl-2-like protein 12 (Jensen et al., 2013). Systemic administration causes this particle to pass the BBB and kill tumor cells for GBM patients. Additionally, scientists have tested the HSV TK/GCV treatment on poly(beta-amino ester) (PBAE) nanoparticles (Choi et al., 2020). These are especially effective vectors for tumor drugs because the PBAE nanoparticles unpack their contents at low pHs below 6.5, and tumor sites are acidic (Shenoy et al., 2005). PBAE nanoparticles induce cytotoxicity at the site, not in normal tissue, helping target malignant tumor cells.

"Gene therapy strategies utilize various vectors to express transgenes at the tumor site. Vectors can be divided into non-viral and viral vectors, the latter of which are subjects of clinical trials"

Limitations in Gene Therapy for Brain Tumors However, limitations exist in gene therapy for brain tumors. Almost all types of gene therapy lack a maximum tolerated dose (MTD), which is the maximum weight of a drug or number of vector particles of viral vectors in gene therapy that can treat a particular condition without unacceptable adverse effects such as edema in the subsequent example, in humans (Stampfer et al., 2019). It should be noted that for preventive drugs and treatments, MTD is not as applicable as any adverse effects may be unacceptable. Currently, not enough trials have tested the 121

Figure 2: A computer graphic image of the adenovirus. Adenoviruses like adenovirus 5, a serotype introduced in the review, have protruding knobs used as receptors attaching to other molecules (van Beusechem et al., 2003; Baker et al., 2019). Image Source: Wikimedia Commons

toxicity of a specific dose of gene therapy, and without an MTD, it is difficult to determine if the current doses are the most effective in killing tumor cells when administered. The first gene therapy MTD was discovered when two trillion adenovirus-HSV-TK injected to two recurrent malignant glioma patients resulted in symptoms like edema, signifying that the MTD for recurrent patients is less than two trillion vector particles (Trask et al., 2000). Scientists have used these results to test the MTD for newly diagnosed patients, which is predicted to be larger than that for recurrent patients, but many gene therapy trials do not determine the MTD (Kaufmann & Chiocca, 2014). One obstacle to the discovery of a MTD is that it is difficult to grow high titers of the vectors (Fulci & Chiocca, 2010). This has prompted scientists to develop novel methods to grow high titers of the vectors, such as the immobilized metal affinity chromatography method, which selectively purifies the HSV-1 vectors by tagging them with a binding peptide attracted to immobilized transition metal ions, namely cobalt (Jiang et al., 2004). Another limitation in gene therapy is that viral vectors are commonly injected into the patient’s circulatory system in the brain following surgical resection of the brain tumor. Although this mechanical delivery technique is effective for a small tumor site, it does not work for larger sites due to interstitial pressure within the brain, or the net pressure on the capillaries from the surrounding interstitial fluids (Hall & Sherr,

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2006; Oh et al., 2009). The interstitial pressure can be around 25 times greater for tumor tissue than normal tissue. This stronger surrounding pressure on the capillaries may cause uneven distribution and lack of spreading across a larger site because mechanically injected substances travel from the capillaries to the tumor cells via transcapillary transport, or through the interstitial fluid convection flow (Heldin et al., 2004). Thus, the larger pressure inhibits substances in the capillaries from being efficiently distributed through the interstitial spaces. In a clinical trial testing adenovirus-HSV-TK therapy for malignant glioma patients using GCV, up to 70 injections have been used to distribute the vectors within the brain (Immonen et al., 2004). Targeting strategies are also limited in that, even though they are known to be selectively cytotoxic towards tumor cells, adverse effects from acute, recurrent, chronic, and delayed toxicities appear in imaging data (Liebler & Guengerich, 2005; Thomas et al., 2020). Drug toxicity can lead to two common mechanisms: hypersensitivity reactions, where an antigen-presenting cell transports the drug to the B and T cells, releasing cytokines and harming body tissue, and biological activation, in which oxidative stress in the liver causes organ toxicity. Imaging data has also shown frequent cases of on and off target toxicity, occurring after the drug binds to, respectively, a target receptor or an unintended receptor (Howard et al., 2012). Retrospective analysis supports that traditional chemotherapy, or cytotoxic agents, induces more

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intense, acute toxicity, while targeting agents lead to less intense, but possibly more delayed toxicities (Jordan et al., 2018). Thomas et al. note that the comparative gap in the research of delayed toxicities, showing that clinical trials should study the delayed effects of brain tumor treatments after months or years after administration.

Further applications Despite these limitations, scientists are exploring novel strategies to address the limitations of current gene therapy. One major example is BBB disruption through focused ultrasound (FUS). The relative impermeability of the BBB limits the delivery of the transgenes and vectors to the tumor site in the brain. For example, 98% of small molecule drugs do not pass the BBB into the brain parenchyma (Pardridge, 2005). FUS allows for endothelial transfection into the brain, without opening the BBB (Banerjee et al., 2021; Wu et al., 2021). The strategy injects microbubbles (MBs), or small bubbles filled with gas, into the bloodstream. Then it applies FUS, forming an acoustic field with ultrasound frequency (220,000 times/s) that expands and contracts the MBs in the cerebral capillaries. The expanding and contracting MBs, also called circulating MBs, stretch the walls of the capillaries and causes acoustic cavitation, or an increase in space occupied by MBs due to FUS. This cavitation increases BBB permeability without permanent tissue damage, since circulating MBs and FUS open new pathways for drugs, such as modified tight junctions on the capillary walls, cell membrane channels, endocytosis, or transcytosis (Burgess et al., 2015). Regarding the limitation of mechanical injection, there are various alternative strategies for delivering the vectors. One alternative to mechanical injection is creating a convection flow that spreads out the infused vectors as well as overcomes the relatively impermeable BBB (Stine & Munson, 2019; Mehta et al., 2017). This method is called convection-enhanced distribution (CED) and it uses an infusion catheter to infuse vectors or drugs into the interstitial spaces in the brain, creating a pressure gradient at the tip of the catheter in the process. The CED utilizes this pressure gradient to increase the bulk flow, or convection, within the interstitial spaces and evenly distributes the infusate. This method is applicable for both white matter, mostly made up of axons, and gray matter, mainly consisting of neural cell bodies (Lieberman et al., 1995). Some modifications to the CED include using a hollow fiber catheter, which has a larger surface area and is porous, to enhance and spread out

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bulk flow within the central nervous system (Oh et al., 2009). However, this technique depends on the infused vector’s physical and chemical properties, including tissue affinity (Saito et al., 2006). Furthermore, as the infusate is transported to the tumor site via catheters, the tumor site experiences more pressure and increases the interstitial fluid flow (IFF) from the tumor cells to the surrounding normal cells (Stine & Munson, 2019). Scientists have suggested that the bulk flow from the infusates may also move tumor cells through the existing or new pathways from the tumor site. Also, the increased bulk flow and movement within the interstitial spaces may also push the infusate back into the catheter, reducing the dose administered (Raghavan et al., 2006). The combination of these effects may negatively affect the extracellular matrix and the transport of molecules in the brain. Nevertheless, more research will likely reveal the various bulk flows in the brain caused by CED, allowing for novel modifications like the hollow fiber catheter to address them. Other alternatives to mechanical injection are intraventricular and intravascular injections, methods which are still being developed. Intraventricular injections have led to inflammation in animals in response to the toxicity of the vectors (Driesse et al., 2000). Intraarterial injections into the cerebral arteries have yielded better overall survival times for a Phase II HSV TK/GCV clinical trial than direct injections into the tumor or the brain (Ji et al., 2016; Chiocca et al., 2004; Papanastassiou et al., 2002). The increase in treatment area may have been a factor, although efficiency for transfection, or the transfer of nucleic acids into eukaryotic cells, should be monitored in subsequent trials (Huang et al., 2020). However, intravascular injections, both intravenous and intra-arterial, require vectors to move through the BBB, decreasing efficiency (Wakimoto et al., 2003). More research may be needed to improve these injections and test the effect of these injections on humans.

"Nevertheless, more research will likely reveal the various bulk flows in the brain caused by CED, allowing for novel modifications like the hollow fiber catheter to address them."

Some potential areas of research include osmotic agents to intravascular injections, which dilates capillaries through osmosis and widens tight junctions on the capillary walls (Rapoport, 2000). These changes increase BBB permeability and allow vectors, enzymes, and other larger substances to enter the brain parenchyma, or the functional brain tissue surrounding cerebral blood vessels. For example, a study injected an recombinant adeno-associated virus vector with the osmotic agent mannitol into rat brains (Doolittle et al., 2000). The study determined not

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Figure 3: A transmission electron microscope image of the tight junctions in the blood-brain barrier (BBB) in a mouse embryo. The curving pathway is the tight junction, formed by the plasma membrane’s inward folding. The brain tissue undergoes pinocytosis through the tight junction, since substances dissolved in the liquid can enter through the tight junction and be encapsulated in pinocytotic vesicles. Osmotic agents can widen the tight junction and increase transport of substances. Image Source: Wikimedia Commons

only that slow vector infusion rates of less than 33nl/min increased gene expression, but also that the mannitol increased the distribution of transduced cells by 200-300%. These cells were transduced by the marker genes (luciferase and enhanced green fluorescent protein), and the study suggests that mannitol-mediated injections can improve vector distribution beyond the injection site.

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Pharmacogenetic Testing: Using the Serotonin Transporter Gene to Predict Selective Serotonin Reuptake Inhibitor Response BY SUCHITRA SUDARSHAN, UNDERGRADUATE, UNIVERSITY OF CALIFORNIA, BERKELEY Cover Image: 3D representation of Deoxyribonucleic Acid (DNA) Image Source: Pixabay

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Abstract In the last decade, several genes involved in the onset of psychological disorders have been studied. Of these genes, the serotonin transporter gene, solute carrier family 6 member 4 (SLC6A4), has been implicated in the onset of depression, as it is more prone to reduced transcription after exposure to chronic stress or childhood maltreatment (Caspi et al., 2003; Hankin et al, 2015). While several studies demonstrate this gene by environment interaction, fewer studies have examined how SLC6A4 influences selective serotonin reuptake inhibition (SSRI). This is problematic, as pharmacogenomic assays are increasingly using SLC6A4 genotype information in order to identify genetically suitable SSRIs. Thus, this review details the discovery of SLC6A4 and evaluates several studies that examine SSRI response as a function of SLC6A4 genotypes. The mixed findings of these studies prompted

the use of population genetics. This revealed that SSRI response rates are influenced by SLC6A4 genotype frequencies in minority populations and are further complexed by other factors such as age and sex. Next, studies evaluating GeneSight Psychotropic, a pharmacogenomic assay utilizing SLC6A4, are examined. These studies also obtain several features that elicit favorable results: these relate to sample characteristics, methodology, and the inclusion of proteomics. Finally, suggestions for increasing clinical validity are discussed. This includes narrowing participant pools and evaluating the efficacy of GeneSight Psychotropic in individuals with other mental illnesses.

Introduction Depression serves as the second leading cause of death in 15- to 29-year-olds (James et al, 2018) and is estimated to increase in prevalence by 35% in the next 30 years (Heo et al, 2008). However, DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 1: SSRI blocks the uptake of 5-HT in order to increase activation of the 5-HT receptors. Image Source: Wikimedia Commons

despite this rise, existing pharmacological approaches in treating depression have remained stagnant. Serotonin Selective Reuptake Inhibitors (SSRIs), a class of antidepressant drugs, are a prime example of this phenomenon. SSRIs target the neurotransmitter serotonin (5-HT), which is thought to be a proprietor of depression due to its function as a mood regulator, or rather, “happy chemical.” Low levels of 5-HT are thought to contribute to symptoms of depression, such as feelings of worthlessness, anhedonia, and thoughts of suicide (American Psychiatric Association, 2013). For this reason, SSRIs aim to increase 5-HT levels by targeting the 5-HT transporter (SERT) and blocking its ability to reabsorb 5-HT into nerve cells—also referred to as “reuptake inhibition.” However, this process takes six to eight weeks to alleviate depressive symptoms, and only succeeds in doing so in 50% of patients (Frodl, 2017). While several studies have suggested that SSRIs are among the least effective class of antidepressants (Cipriani et al., 2018), they are still one of the most commonly prescribed antidepressants, in part because they cause fewer side effects than other antidepressants. So, while SSRIs vary in their effectiveness, their tolerability has led scientists to re-evaluate the mechanism by which SSRIs operate (reuptake inhibition) in order to optimize efficacy. In 2010, Baudry et al. suggested that SSRIs do not operate by targeting SERT directly, but instead, cause the genes involved in the production of SERT to become less active over time through a SPRING AND SUMMER 2021

process of suppression (Baudry et al., 2010). This causes the effects of the SSRI to be experienced several weeks later. In recent years, this finding has remained central to pharmacogenetic research that aims to use genomic information in order to predict genetically suitable antidepressants. In particular, the serotonin transporter gene, SLC6A4, has been of key interest in gauging SSRI response because of its role in regulating 5-HT reuptake However, it is important to note that several studies have demonstrated that SLC6A4 is not a viable predictor of SSRI efficacy due to external variables, such as race-by-genotype or gene-environment interactions influencing its function (Luddington etal., 2009). Even more so, a greater portion of the literature suggests that SLC6A4’s expression is strongly influenced by childhood maltreatment as well as exposure to chronic stress (Caspi et al., 2003; Hankin et al, 2015). Despite the uncertainty behind SLC6A4 and its relation to SSRI efficacy, pharmacogenetic tests, such as GeneSight Psychotropic, have adopted SLC6A4 as a primary gene for determining suitable antidepressants for patients. As such, this paper will review the existing literature regarding SLC6A4 and its merits and drawbacks in predicting SSRI response. Following this, several recommendations are made for future studies to clarify the relationship between SLC6A4 and SSRI response.

"So, while SSRIs vary in their effectiveness, their tolerability has led scientists to re-evaluate the mechanism by which SSRIs operate (reuptake inhibition) in order to optimize efficacy."

5-HTTLPR: Long and Short Alleles In recent years, genetic regulators of the SERT 131

have been of key interest in determining an individual’s vulnerability to depression. This is due to SERT’s function as a regulator of serotonergic neurotransmission: it directs the magnitude of 5-HT postsynaptic responses through reuptake. Thus, for individuals diagnosed with depression, low 5-HT levels are thought to be mediated by genes related to SERT. In 1996, Heils discovered that this mediation was related to a single nucleotide polymorphism (SNP) on SLC6A4. This variation in a single nucleotide (polymorphism) is also referred to as 5-HTTLPR: serotonin-transporter-linked polymorphic region. Promoter regions dictate how much of a gene is expressed in the form of a protein. With respect to SLC6A4, this expression is regulated via two allele variants, “long” (L) and “short” (S), that depend on the number of repeated nucleotides forming the allele. Scientists have studied the influence of these allele variants—SS, SL, LL, and LS—on SERT promoter activity (Lesch et al, 1996). In particular, this study found that LL genotypes synthesized an average of 1.55 times more SERT messenger RNA (mRNA) than S variants, demonstrating that the L allele leads to a greater expression of SLC6A4. This high level of expression increases mRNA synthesis of SERT, which then increases 5-HT levels. S variants, on the other hand, experience a lower level of SLC6A4 expression, which results in less transcriptional activity, and consequently, lower 5-HT levels. This suggests that classifying alleles as “long” or “short” may serve as a potential predictor of anxiety-related illnesses. Functional Variants of Long Alleles SLC6A4’s promoter region has also been identified as polymorphic, indicating that more than one allele occupies the region and subsequently affects its level of expression. In the L allele, the nitrogenous base adenine may be substituted for guanine, another nitrogenous base, in one locus. This results in two functional variants: LA and LG. The LG allele appears to reduce the expression of SLC6A4 to the S allele’s level of expression (Parsey et al., 2006). The codominance of the L and S allele suggests that intermediate transcriptional activity of 5-HT uptake may be the result of a variant formed by one low-expression allele (S or LG) and one high expression allele (LA) (Hu et al, 2006). The homozygous LA variant (LA LA) is therefore the optimal variant, as 5-HT uptake is greater than variants containing S or LG This, however, suggests that transcriptional activity of the LALG and SLG variants may not differ from

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the homozygous LGLG variant.

Literature Review The Relationship Between SLC6A4 and SSRI Efficacy The amygdala, a gray matter mass responsible for the regulation of emotions, has been a target for assessing the effects of SSRIs. Several studies have used neuroimaging methods to gauge amygdala activity as a function of SSRI and 5-HTTLPR variant type. An fMRI study, in which thirtysix Caucasian females received either one dose of escitalopram or a placebo (escitalopram/ placebo), investigated the relationship between SLC6A4 on SSRI blockades during emotion regulation (Outhred et al., 2016). It was found that participants possessing the L allele showcased an increase in amygdala connectivity relative to those with the S allele. Similarly, another study measured neural responses to negative emotions after administering citalopram (SSRI) or a placebo to fifty Chinese men (Ma et al., 2015). It was found that citalopram increased amygdala activity in the LL variant but not SS variants. Both Outhred (2016) and Ma’s (2015) studies restrict their participant pool based on gender and race and suggest that SSRIs are largely effective on LL genotypes. However, most of the literature suggests that the L allele is far less prominent in Asians, suggesting that genetic variability may restrict the effectiveness of genotypes in predicting SSRI response. In fact, Caucasian participants have displayed the SS genotype only 21.6% to 28.3% of the time, while Asian participants displayed the SS genotype 55.6% to 60.0% of the time. (Porcelli et al., 2012).However, a recent meta-analysis of 33 studies found that there was no statistically significant relationship between SLC6A4 variant type and SSRI efficacy in the Asian population, although this relationship exists for Caucasians (Porcelli et al., 2012). The overall response rate for the LL genotype in the Caucasian population was 61.6% as opposed to 48.8% in the SS genotype (Porcelli, et al., 2012). These results illustrate that SS genotypes may only experience a slightly less (12.8%) non-response rate to SSRIs. Overall, more studies should be conducted in order to determine whether there is a definite relationship between SLC6A4 variant type and SSRI efficacy—but specifically, within race in mind Because the relationship between 5-HTTLPR variant types and SSRI response is varied in different ethnic populations, it is possible that SSRI responses could be mediated by race-bygenotype interactions. Studies have found that

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African Americans possess an “extra-long” variant (XL), which may be implicated in a larger range of mRNA responses, and thus, influences SSRI responses differently (Vijayendran et al, 2012). Furthermore, Caucasians are less likely to be homozygous for the L allele while African Americans are 50% likely (Hu et al., 2006). Under the assumption that L genotypes deliver optimal SSRI efficacy, there is a possibility that SSRIs may be more effective for the African American population; however, the XL variant has not been thoroughly studied to conclude this. In addition, other factors have been identified as possible mediators of the genotype and SSRI interaction. Females with the S allele are less likely to respond to serotonin-based medications, while males with the S allele demonstrate no significant effect (Porcelli et al., 2012). SSRI response rates of LL and S genotypes (LL demonstrating a greater response) tend to become more distinct in older patients. One study also found that the onset of physical illnesses at a later age increased SSRI response in LL genotypes (Porcelli et al, 2012). These studies therefore indicate that a host of other factors may also be implicated in genotypeSSRI interactions. Although evidence suggests that SLC6A4 may not be the most promising indicator of SSRI response rates, SLC6A4 has been included in the assays of pharmacogenomic tests available for commercial use to optimize treatment plans for patients. Commercial Psychometric Tools for SSRI Modulation GeneSight Psychotropic and Genecept assay are the most prominent pharmacogenomic tests on the market. Both analyze DNA for a similar set of pharmacodynamic and pharmacokinetic genes that have been identified as role players in drug metabolism and the potency of drugreceptor interactions. In particular, GeneSight Psychotropic is able to generate a genetic profile of a patient while also analyzing the patient’s phenotypic and proteomic information using an algorithm. This algorithm then classifies a list of 38 psychiatric medications into “green,” “yellow,” and “red” bins, with “green” serving as the most optimal list (Zeier et al., 2018). Genecept operates differently: they test for a large range of genes, produce a “gene variation report,” and then provide therapeutic guidance on medication, exercise, or transcranial magnetic stimulation (Peterson et al., 2016). Both tests are conducted via a minimally invasive saliva swab, making them far more accessible than other diagnostic tools (e.g., blood draw).

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Genesight Psychotropic and Genecept assay test for SLC6A4, as well as HTR2A, another 5-HT linked gene, because of their role in indicating genetically suitable medications. However, as discussed, the existing literature has not specified the link between SLC6A4 and SSRI response, meaning that factors such as age, sex, and race lead to various interpretations on how strong of a relationship there is between those two variables. While Genecept Assay scans for both LA and LG, GeneSight Psychotropic identifies the general presence of the L allele. These differences highlight that psychometric tools may vary in their recommendations due to methodology, thus raising questions as to whether pharmacogenetic tests should offer advice based on algorithms generated from no widely established links. In fact, one study demonstrated that pharmacological knowledge of antidepressants, such as oxidative drug metabolism, allows physicians to make similar judgements to GeneSight Psychotropic’s algorithms (Macaluso & Preskorn, 2018). Despite these concerns, GeneSight Psychotropic has highlighted numerous studies reflecting their tool’s capability in improving patient experiences and treatment outcomes. A large portion of studies claim that GeneSight Psychotropic doubles the likelihood of response to SSRIs and that 30% of patients have been identified as having severe “gene-drug” interactions (Hall-Flavin et al., 2012). Like most studies that evaluate GeneSight Psychotropic, the Hamm Clinic study used an open-label study that consisted of guided and unguided groups. This study found that guided groups (those prescribed with GeneSight’s recommendations) displayed a greater percent improvement in depression scores in comparison to individuals in unguided groups (those that were prescribed medications without GeneSight’s recommendation) (Hall-Flavin et al., 2012). These results have been replicated in three other studies that illustrate the average improvement rate to be 53% greater that those in the unguided group (Altar et al., 2015). Another study referenced includes the Pine Rest Study, which implemented a randomized, doubleblind study and still suggested that GeneSight’s recommendations have the potential to improve depression scores significantly (Altar et al., 2015).

"A large portion of studies claim that GeneSight Psychotropic doubles the likelihood of response to SSRIs and that 30% of patients have been identified as having severe “genedrug” interactions"

Pharmacogenetic tests are not limited to improving depression scores. They can also decrease burden on the healthcare system. Genomind’s Genecept Assay, for instance, conducted a study in which Aetna insurance members with mood/anxiety disorders were

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classified as having “received Genecept testing” or having “not received Genecept testing.” Members of one classification were matched with members in the other based on commonalities including, but not limited to, diagnosis, gender, age, and socioeconomic status. It was found that the population that received Gencept’s test experienced a 40% reduction in emergency room visits and a 58% reduction in hospitalizations in comparison to non-Genecept users. Overall, this indicates that pharmacogenetic tests have positive implications that extend beyond the quality of healthcare (Perlis et al., 2018).

"Despite positive results, pharmacogenetic testing has not been implemented as a traditional pathway for treating depression because of a lack of evidence surrounding the tests."

Despite positive results, pharmacogenetic testing has not been implemented as a traditional pathway for treating depression because of a lack of evidence surrounding the tests. For each of the 38 psychiatric medications GeneSight sorts, there exists an ‘evidence’ profile. Ideally, this would offer insight as to why particular medications are more suitable than others; however, Macaluso & Preskorn (2018) suggest that these allocations reflect how newly marketed these medications are rather than how genetically suitable they are. Medications consistently in the green bin are often new on the market while medications presented in the other bins are older. In addition, scientists also question how drug-gene interactions are measured and used when determining suitable medications. This lack of transparency bolsters the need for more insight into how these tests gauge SSRI response. A Critical Evaluation of Pharmacogenetic Evidence

SLC6A4

and

This paper has discussed the influence of SLC6A4 variants on SSRI response, however, inconsistent methodologies spanning the studies mentioned have contributed to hesitancies amongst the scientific community . First, these studies have employed methodologies that produce favorable results, and second, these assays have included an array of genes that are not strongly linked to SSRI response. The Hamm Clinic study (Hall-Flavin et al., 2012) is representative of the first area. Although it produced statistically significant results, they were produced on the basis of an open-label methodology. Openlabel studies allow for both the researcher and the participant to know the treatment they are receiving. It is possible that patients selected to receive the GeneSight test were more optimistic about their course of treatment, which leads to a placebo effect. SSRIs themselves have only been shown to be slightly more effective in prescribed groups than placebo groups (Khan

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& Brown, 2015). As such, the likelihood of the placebo effect contributing to the success of the Hamm Clinic study is relatively high. Similarly, the Pine Rest study classifies their methodology as a randomized, double-blind study. However, prescribers were aware of whether a participant was assigned to the guided or unguided group, which could have influenced the comments that prescribers gave to their patients and still resulted in a placebo effect. Overall, the Pine Rest study does not provide sufficient evidence as the participant pool was not large enough (N=49) and did not produce statistically significant results (p =0.29) (Altar et al., 2015). Another instance of error may be the selection of participants for unguided and guided groups. In general, studies that have evaluated GeneSight do so on patients with major depressive disorder (MDD) rather than a host of psychological disorders that require antidepressants (e.g., bipolar disorder). However, this is not accounted for during the prescription process as GeneSight suggests that their algorithm can be used to prescribe SSRIs, regardless of diagnosis. Ultimately, this would lead physicians into applying an algorithm that has not been designed or tested for all psychological disorders that may need antidepressants, but instead, just one (MDD)Many of these studies also refine participant pools so that those who have already failed to respond to several courses of treatment are in the guided group; this makes the chances of a positive response rate more likely in the guided groups. Significantly, this selective undertaking demonstrates a critical flaw in the application of pharmacogenetic testing. These tests are built to work on individuals that showcase symptoms of depression, but many of these studies evaluate response on treatment resistant MDD patients. The diversification in genes tested for in pharmacogenomic assays are partially responsible for producing favorable results. In particular, GeneSight’s assay extends beyond the serotoninbased genes SLC6A4 and HTR2A and tests for differences in several cytochrome p450 enzymes to classify a patient's metabolism, which is critical for understanding how slow or fast medication is broken down by the body. GeneSight’s assay scan for differences in the CYP2C19 gene which gauges how tolerant an individual might be to a particular SSRI (Mrazek et al, 2011). These proteomic insights reveal why studies evaluating GeneSight claim that the assay is extremely effective, while studies that exclusively study SLC6A4 remain mixed. Studies have often aligned SLC6A4 genotypes with the combinatorial use of

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different proteomic and genomic information, increasing uncertainty between the strength of SLC6A4 genotypes and SSRI response. Using proteomic information to decipher dosage requirements provides substantial benefits, such as reducing errors in prescriptions. For instance, CYP450 enzymes have been used in the prescription of Warfarin, which is an anticoagulant that can often pose several risks due to dosage errors (Vinagradoca et al., 2018). Thus, metabolic information can help ensure that dosing conflicts are less likely to occur. However, medications like Warfarin aim to treat an objective dysfunction in the body, while SSRIs aim to elevate 5-HT levels in an attempt to disassemble symptoms of depression. It is not guaranteed that SSRIs will work, even if the correct metabolic rate is determined. The inability for metabolic information to inform SSRI treatment resurfaces a critical issue: race. Although thoroughly displayed in the evidence linking 5-HTTLPR to SSRI efficacy, most antidepressants are effective on non-Hispanic, white populations. Studies that evaluate antidepressant adherence suggest that minority populations are more likely to experience side effects, and thus, prematurely discontinue their medication (Rossom et al., 2017) Therefore, variations produced by race-bygenotype interactions suggest that GeneSight may only produce genetically suitable medications for non-Hispanic, white populations.

Conclusion Pharmacogenetic testing offers a set of radical advances both in the quality of healthcare, and in the healthcare industry. Even more so, it offers the opportunity to reverse the trend of prescribing treatments according to a one-size-fits-all approach and, instead, shift the focus towards personalized treatments. Yet, such advances have not been widely implemented in the field due to hesitancy in the psychiatry field. As reviewed, this stems from the lack of empirical evidence in favor of GeneSight Psychotropic. By implementing SLC6A4 and HRT2AC (two 5-HT related genes that have not been established as SSRI mediators), GeneSight Psychotropic has diversified their genetic assay but has not yet showcased that all of their genes effectively contribute to the identification of suitable antidepressants. Similarly, the evidence that does link SLC6A4 to SSRI efficacy is inconsistent across almost all races and is primarily derived from treatment-resistant patients. This suggests that GeneSight may only be effective for prescribing medications for Caucasians that have treatment

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resistant MDD. Thus, narrowing participant pools to a single race, such as African American, Latinx, Asian, etc., can help investigate how raceby-genotype interactions influence GeneSight’s ability to predict genetically suitable SSRIs. Furthermore, gathering response rates based on different clinical diagnoses, such as generalized anxiety and bipolar disorder, can help clarify whether GeneSight’s assay is appropriate for nontreatment resistant or non-MDD patients. While GeneSight and its supporting studies have been critically parsed through, it is important to note that these criticisms do not invalidate the merit of using proteomic information in predicting SSRI response. In fact, proteomics is an objective mediator of drug efficacy in the body, which has allowed for its widespread clinical use. GeneSight’s use of proteomic information can be helpful in determining suitable medication based on drug metabolism. However, for pharmacogenetic testing to be widely adopted, tests like GeneSight Psychotropic must provide sufficient reasoning and evidence linking all their genes as mediators of SSRI efficacy. This will increase certainty within the psychiatric community that such tests should be adopted as the new standard for prescribing antidepressants. References Altar CA, Carhart JM, Allen JD, Hall-Flavin DK, Dechairo BM, Winner JG. (2015) Clinical validity: Combinatorial pharmacogenomics predicts antidepressant responses and healthcare utilizations better than single gene phenotypes. The Pharmacogenomics Journal, 15(5):443-51. https://doi. org/10.1038/tpj.2014.85 American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). https://doi. org/10.1176/appi.books.9780890425596 Baudry A, Mouillet-Richard S, Schneider B, Launay JM, Kellermann O. (2010) miR-16 targets the serotonin transporter: a new facet for adaptive responses to antidepressants. Science. 329(5998):1537-41. doi: 10.1126/science.1193692. Caspi A, Sugden K, Moffitt TE, Taylor A, Craig IW, Harrington H, McClay J, Mill J, Martin J, Braithwaite A, Poulton R. (2003). Influence of life stress on depression: moderation by a polymorphism in the 5-HTT gene. Science, 301(5631):386-9. doi: 10.1126/science.1083968 Cipriani A, Furukawa TA, Salanti G, Chaimani A, Atkinson LZ, Ogawa Y, Leucht S, Ruhe HG, Turner EH, Higgins JPT, Egger M, Takeshima N, Hayasaka Y, Imai H, Shinohara K, Tajika A, Ioannidis JPA, Geddes JR. (2018). Comparative Efficacy and Acceptability of 21 Antidepressant Drugs for the Acute Treatment of Adults With Major Depressive Disorder: A Systematic Review and Network Meta-Analysis. Focus (Am Psychiatr Publ). 2018 Oct;16(4):420-429. doi: 10.1176/appi. focus.16407. Cipriani A, Furukawa TA, Salanti G, Chaimani A, Atkinson LZ, Ogawa Y, Leucht S, Ruhe HG, Turner EH, Higgins JPT, Egger

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M, Takeshima N, Hayasaka Y, Imai H, Shinohara K, Tajika A, Ioannidis JPA, Geddes JR. (2018) Comparative efficacy and acceptability of 21 antidepressant drugs for the acute treatment of adults with major depressive disorder: a systematic review and network meta-analysis. The Lancet. 391(10128):1357-1366. doi: 10.1016/S0140-6736(17)32802-7 Frodl T. (2017). Recent advances in predicting responses to antidepressant treatment. F1000Research, 6, F1000 Faculty Rev-619. https://doi. org/10.12688/f1000research.10300.1 Hall-Flavin, D. K., Winner, J. G., Allen, J. D., Jordan, J. J., Nesheim, R. S., Snyder, K. A., Drews, M. S., Eisterhold, L. L., Biernacka, J. M., & Mrazek, D. A. (2012). Using a pharmacogenomic algorithm to guide the treatment of depression. Translational psychiatry, 2(10), e172. https://doi. org/10.1038/tp.2012.99 Hankin BL, Young JF, Abela JR, Smolen A, Jenness JL, Gulley LD, Technow JR, Gottlieb AB, Cohen JR, Oppenheimer CW. (2015). Depression from childhood into late adolescence: Influence of gender, development, genetic susceptibility, and peer stress. Journal of Abnormal Psychology, 124(4), 803-816. https://doi.org/10.1037/abn0000089 Heils A, Teufel A, Petri S, Stöber G, Riederer P, Bengel D, Lesch KP. (1996). Allelic variation of human serotonin transporter gene expression. Journal of Neurochemistry. 2621-4. doi: 10.1046/j.1471-4159.1996.66062621 Heo, M., Murphy, C. F., Fontaine, K. R., Bruce, M. L., & Alexopoulos, G. S. (2008). Population projection of US adults with lifetime experience of depressive disorder by age and sex from year 2005 to 2050. International journal of geriatric psychiatry, 23(12), 1266–1270. https://doi.org/10.1002/gps.2061 Hu, X. Z., Lipsky, R. H., Zhu, G., Akhtar, L. A., Taubman, J., Greenberg, B. D., Xu, K., Arnold, P. D., Richter, M. A., Kennedy, J. L., Murphy, D. L., & Goldman, D. (2006). Serotonin transporter promoter gain-of-function genotypes are linked to obsessive-compulsive disorder. American journal of human genetics, 78(5), 815–826. https://doi.org/10.1086/503850 James SL & Abate D. (2018). Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the global burden of disease study 2017. The Lancet, 392(10159), 1789–858. https://doi. org/10.1016/S0140-6736(18)32279-7 Khan A, Brown WA. (2015). Antidepressants versus placebo in major depression: an overview. World Psychiatry. 14(3):294-300. doi: 10.1002/wps.20241 Lesch KP, Bengel D, Heils A, Sabol SZ, Greenberg BD, Petri S, Benjamin J, Müller CR, Hamer DH, Murphy DL. (1996). Association of anxiety-related traits with a polymorphism in the serotonin transporter gene regulatory region. Science. 274(5292):1527-31. doi: 10.1126/science.274.5292.1527. Luddington, N. S., Mandadapu, A., Husk, M., & El-Mallakh, R. S. (2009). Clinical implications of genetic variation in the serotonin transporter promoter region: a review. Primary care companion to the Journal of clinical psychiatry, 11(3), 93–102. https://doi.org/10.4088/pcc.08r00656 Ma Y, Li B, Wang C, Zhang W, Rao Y, Han S. (2015). Allelic variation in 5-HTTLPR and the effects of citalopram on the emotional neural network. British Journal of Psychiatry. 206(5):385-92. doi: 10.1192/bjp.bp.114.150128.

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Macaluso M, Preskorn SH. (2018) Knowledge of the Pharmacology of Antidepressants and Antipsychotics Yields Results Comparable With Pharmacogenetic Testing. Journal of Psychiatric Practice.24(6):416-419. doi: 10.1097/ PRA.0000000000000345 Mrazek DA, Biernacka JM, O'Kane DJ, Black JL, Cunningham JM, Drews MS, Snyder KA, Stevens SR, Rush AJ, Weinshilboum RM. (2011). CYP2C19 variation and citalopram response. Pharmacogenet Genomics. 21(1):1-9. doi: 10.1097/ fpc.0b013e328340bc5a. Outhred T, Das P, Dobson-Stone C, Felmingham KL, Bryant RA, Nathan PJ, Malhi GS, Kemp AH. (2016). Impact of 5-HTTLPR on SSRI serotonin transporter blockade during emotion regulation: A preliminary fMRI study. Journal of Affective Disorders. 196:11-9. doi: 10.1016/j.jad.2016.02.019 Parsey, R., Hastings, RS., Oquendo, MA., Hu X., Goldman D., Huang Y., Simpson N., Arcement, J., Huang, Y., Ogden, T., Van Heertum, R., Arango C., Mann, J. (2006) Effect of Triallelic Functional Polymorphism of the Serotonin-Transporter-Linked Transporter Region on Expression of Serotonin Transporter in the Human Brain American Journal of Psychiatry 163:1, 48-51, https://doi.org/10.1176/appi.ajp.163.1.48 Perlis, RH, Mehta, R, Edwards, AM, Tiwari, A, Imbens, GW. (2018). Pharmacogenetic testing among patients with mood and anxiety disorders is associated with decreased utilization and cost: A propensity‐score matched study. Depression and Anxiety. 35: 946– 952. https://doi.org/10.1002/da.22742 Peterson, K., Dieperink, E., Anderson, J. Boundy, E., Ferguson L., Helfand, M. (2017). Rapid evidence review of the comparative effectiveness, harms, and cost-effectiveness of pharmacogenomics-guided antidepressant treatment versus usual care for major depressive disorder. Psychopharmacology, 234, 1649–1661 https://doi.org/10.1007/s00213-017-4622Porcelli S, Fabbri C, Serretti A. Meta-analysis of serotonin transporter gene promoter polymorphism (5-HTTLPR) association with antidepressant efficacy. (2012). European Neuropsychopharmacology. 22(4): 239-58. doi: 10.1016/j. euroneuro.2011.10.003 Rossom RC, Shortreed S, Coleman KJ, Beck A, Waitzfelder BE, Stewart C, Ahmedani BK, Zeber JE, Simon GE. (2016). Antidepressant adherence across diverse populations and healthcare settings. Depression and Anxiety 33(8):765-74. doi: 10.1002/da.22532 Vijayendran M, Cutrona C, Beach SR, Brody GH, Russell D, Philibert RA. (2012). The relationship of the serotonin transporter (SLC6A4) extra long variant to gene expression in an African American sample. American Journal of Medical Genetics Part B Neuropsychiatric Genetics. 159B(5):611-2. doi: 10.1002/ajmg.b.32054 Vinogradoca, Y., Coupland C., Hill, T., Hippisley-Cox J. (2018). Risks and benefits of direct oral anticoagulants versus warfarin in a real-world setting: cohort study in primary care. British Medical Journal. 362 , doi: https://doi.org/10.1136/bmj.k2505 Wang, J., Wu, X., Lai, W., Long, E., Zhang, X., Li, W., Zhu, Y., Chen, C., Zhong, X., Liu, Z., Wang, D., & Lin, H. (2017). Prevalence of depression and depressive symptoms among outpatients: a systematic review and meta-analysis. British Medical Journal, 7(8). https://doi.org/10.1136/ bmjopen-2017-017173

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Zeier Z., Carpenter L, Kalin N,. Rodriguez, C. McDonald M., Widge A, Nemeroff C. (2018). Clinical Implementation of Pharmacogenetic Decision Support Tools for Antidepressant Drug Prescribing. The American Journal of Psychiatry. 175:9, 873-886 doi: 10.1176/appi.ajp.2018.17111282

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The Quantum Playing Field: Qubits and the Supremacy Question BY TIM STRANG '22 Cover Image: Russian researchers at FMN Labs assemble cryogenic housing for their quantum computer, responsible for cooling the delicate superconducting hardware down to a fraction of a Kelvin. Image Source: Wikimedia Commons

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Introduction First proposed by American physicist Paul Benioff in 1980, the “quantum computer” — a universal automaton that performs calculations using quantum, rather than classical, logical states — has for decades proven an enticing technical challenge for modern scientists. The allure of Benioff ’s theoretical machine lies in the fundamental differences between quantum and classical mechanics. Almost all classical computers today compute using units of digital information called bits, short for “binary digits”, so named because each individual bit has access to exactly two states. Traditionally, these are interpreted as the “one” or “on” state, and the “zero” or “off ” state. To represent larger numbers, bits are simply strung together in longer and longer sequences and interpreted using basetwo arithmetic. In fact, the use of bits is not in any way fundamental to computation. Ternary computers, though exceedingly rare, operate on strings consisting of three distinct values, and have even been shown to have advantages over their binary cousins under certain metrics, primarily due to the decreased number of digits

needed to represent a number in base three (Connelly, 2008). Quantum computers, on the other hand, implement an even more profound departure from traditional bits. By harnessing the uniquely quantum property of superposition, a delicately prepared physical system can be purposefully placed in a combination of two distinct states at the same time, which form a quantum representation of the “one” and “zero” states of the classical bit. Think Schrödinger’s cat on an atomic scale; while the box is closed, our quantum bit, or qubit, is both on and off. When we open the box, however, we find either a one or a zero, no matter what. We would never read out, say, a one-half valued qubit. The superposition is said to “collapse” upon observation. The key to quantum computation is precisely manipulating the probability of finding one state over the other for dozens of interacting qubits at the same time — all without looking in our metaphorical box until calculations are complete. In the nearly forty years since its conception, quantum computation has come a long way. Even for experts, the advantages offered by qubit mechanics may not be immediately DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

obvious. Luckily, early advances in quantum software theory, most notably Shor’s and Grover’s algorithms for factorization and data search, respectively, give experimentalists initial concrete incentives for production. Unfortunately, due to the incredibly small scale and the inherent instability of quantum systems, progress towards physical realization is an arduous global effort. The following paper surveys the state of quantum computation as it stands today, investigating both the various proposed models for quantum machines and the ground-breaking 2019 GoogleNASA quantum supremacy paper (Arute et al., 2019).

Qubit Models The process for manipulating and storing classical bits on a traditional computer is well-developed, relying largely on the mechanics of small, but nonetheless macroscopic, semiconducting transistors. To give a general picture, a semiconductor is any material that permits electric current under certain circumstances but prohibits it in others. Modern computers capitalize on this property by weaving intricate webs of semiconducting units that act on each other, permitting current (one) or restricting it (zero) depending on the states of their peers. These interdependencies are used to transform electromagnetically coded input data into output data for the use of humans and other machines. In a similar way, the oldest generation of computers represented bitstates via the presence or absence of a current flowing between electrodes on opposite ends of a vacuum tube. Since current could only flow across the nonconducting vacuum when supplied with a sufficient voltage, these tubes functioned logically equivalently to modern transistor technology, and could be connected in exactly the same patterns. This means that any program run on a modern-day transistor-based SPRING AND SUMMER 2021

laptop could theoretically be accomplished by an analogous array of vacuum tubes, albeit in an extremely inefficient manner. Much like these early computers, today’s quantum machines have yet to settle on the long-term preferred method for qubit encoding, and there are a wide variety of candidate systems under research. Theoretical requirements for a viable qubit are relatively limited; a quantum information bit may be stored by any system that can be placed into a quantum superposition of distinct states. To perform calculations on the stored information, nearestneighbor qubits must predictably interact in a quantum phenomenon called entanglement, so scalable entangleability is critical as well. To physically construct a qubit, however, other practical constraints must be considered (Divincenzo, 2005). Perhaps most limitingly, as quantum systems increase in complexity, they become increasingly susceptible to environmental interference, which may result in decoherence of the precisely chosen entanglement state. To understand the issue of decoherence, it may be helpful to imagine an altered Schrödinger’s cat experiment. Imagine that we have a Schrödinger’s cat and a regular mouse, each in its own box on opposite sides of a long room. The cat is of course, for the time being, both alive and dead, but assume that the mouse is known to be definitively alive and in no immediate danger in its box at the beginning of the experiment. Now, if we move the boxes together and remove their adjoining walls, the cat will kill the mouse if it is still alive. Of course, if the cat is dead, it can do no such thing. In this case the mouse will live on indefinitely. So, if the operation is a success, we have either a live cat and a dead mouse, or a dead cat and a live mouse. In no cases do the cat and the mouse occupy the same state upon observation, and yet individually both are in the exact same fifty-fifty superposition of alive and dead. Thus, we say the states of the mouse and the cat are entangled, since measurement of one instantly yields information about the other. In this way, one qubit’s superposition state can alter that of another, in a very generalized sense. Remember, however, that the power of quantum computation comes directly from superposition; if the state of a set of qubits is known before computations are complete, no improvement has been achieved over a regular computer. If the cat meows while we are moving its box across the room, we know with certainty what the end states of both cat and mouse will be. The superposition has collapsed, and our experiment is now classical. Likewise, if there is a chance for external factors to kill our mouse outside of the hungry cat, the desired entanglement is no longer

Figure 1: Bloch Sphere An arbitrary quantum state ψ represented as a point on the Bloch sphere of possible complexvalued superpositions between 0 and 1. Image Source: Wikimedia Commons

"Theoretical requirements for a viable qubit are relatively limited; a quantum information bit may be stored by any system that can be placed into a quantum superposition of distinct states."

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Figure 2: Magnetic Field and Electrical Current Current flowing through a wire (I) generates a curling magnetic field (B) whose orientation is dictated by the direction of the current. Flux qubits utilize the inverse process, creating a current using an applied magnetic field. Image Source: Wikimedia Commons

"A misalignment is physically discernible by miniscule voltage differences across the junction, which can be measured by extremely sensitive voltmeters at readout"

realized. Since no measurement has been made, the “quantum-ness” of mouse’s state is preserved, but it has become unwittingly entangled with uncontrolled confounding factors. Both of these examples represent decoherence of a quantum state, and render any subsequent quantum computations unreliable at best. To avoid this, it is crucial that average coherence time for practical qubit designs be sufficiently long to run calculations reliably. Additionally, the entanglement of the qubits must be precisely tuneable and permit a spectrum of superpositions for programming purposes. Finally, qubit readout must be reasonably easy in order to actually retrieve the output data (Divincenzo, 2005). These criteria, unfortunately, have proven extremely difficult to satisfy simultaneously. As we shall see in our examples, this is because most physical systems make a direct trade-off between coherence time and operability: the more noise-tolerant and isolated a system is, the harder it is to interact with. Nevertheless, there remain a handful of viable qubit designs being researched, each with its own particular strengths and weaknesses. Though these designs are widely variable, the most commonly studied can be grouped into a few broad categories: superconducting, spin-based, and topological.

Superconducting Many of the most successful qubit designs to date hinge on the quantum properties of superconductors. Such models leverage the interactions of Cooper pairs, or pairs of supercooled electrons bound together by uniquely quantum forces that form in superconducting materials. These pairs have an allowed energy state significantly beneath that

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which is obtained by summing their individual ground states. Importantly, this means that small excitations, such as the thermal scattering events responsible for resistance in normal metals, are categorically forbidden. The quantum state of Cooper pairs in a superconducting wire can thus be manipulated to a high degree of precision via the use of a Josephson junction, a uniquely quantum mechanical circuit element (Devoret and Martinis, 2004). Several styles of Josephson junctions exist, but all take the form of some break or barrier in a wire across which current can tunnel – a process in which quantum objects “jump” over obstacles that classical mechanics deem impassable. This rate at which current tunnels through a Josephson junction is wellunderstood and highly dependent on external electrical biases, meaning the state of such a qubit is relatively easy to control via classical controls. There are three popular variants of superconducting qubit that all utilize the Josephson junction tunnelling-rate equation to affect different quantum properties of the system: charge, flux, and phase. Superconducting charge qubits use an applied voltage to produce the desired bias across a Josephson junction between a superconducting reservoir and an ‘island’. Depending on the number of Cooper pairs present on the island at measurement, the qubit readout is either “1” or “0”. Flux qubits involve a loop of superconducting wire containing a Josephson junction, in which magnetic flux applied through the loop may induce a current with either clockwise or counterclockwise orientation, in accordance with Lenz’s law. For a carefully selected quantum superposition of microscopic fluxes, the two possible directions of current measured over the junction at readout form the basis of the bitstates, i.e., clockwise represents a zero, counterclockwise represents a one, or vice versa (Orlando et al., 1999). Phase qubits are harder to visualize, relying on the alignment or misalignment of electrons’ quantum wavefunctions on different sides of a Josephson junction. A misalignment is physically discernible by miniscule voltage differences across the junction, which can be measured by extremely sensitive voltmeters at readout (Devoret and Martinis, 2004). Each of these three variants offer intrinsic strengths and weaknesses over the other two. Most notably, flux and phase qubits are particularly resistant to small electromagnetic noise fluctuations relative to charge qubits, due to the latter’s reliance on high-precision capacitors (Devoret and Martinis, 2004). Certain

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adaptations to the charge qubit can be made to reduce this sensitivity, however. Perhaps the most popular such qubit, the transmon charge qubit, was developed by Yale researchers in 2007 (Koch et al.) and was subsequently utilized by Google’s Sycamore computer, discussed in detail later in this paper. Additionally, mainstream superconducting qubit models have a unique set of collective advantages and disadvantages. They in general provide for a much larger qubit than designs based on single-particle properties like spin, allowing for easier readout, construction, and entanglement. However, their size also means they are more vulnerable to decoherence due to environmental noise, from which they are not naturally isolated. Thus, most designs must be cooled to about 20 mK for useful operation (Devoret and Martinis, 2004). For context, the coldest natural temperatures ever recorded anywhere in the universe are on the scale of ~1 K, making this necessary cooling a severe limit on both long-term application and near-term design.

Spin A second methodology utilizes the spin orientations of quantum particles to encode information. Quantum spin is a property inherent to all particles and has very little to do with physical spinning in the classical sense. For most practical purposes, a particle’s spin represents the orientation and strength of its intrinsic magnetic field. Spin is naturally appealing for storing binary information since, due to extremely unintuitive quantum mechanical considerations, there are only two possible states in which a particle’s spin can ever be observed: perfectly aligned with the axis of measurement, or 180 degrees misaligned. This bypasses one important consideration in designing superconducting qubits: an effective qubit’s zero and one states should minimize the possibility of a qubit transitioning into some third state not defined with reference to the computation. The small physical size of individual spin qubits also offers increases in both coherence time and far-term scalability, at the cost of rendering manipulation and readout significantly more challenging (Struck, 2013). Since spin is intrinsic to all particles, there are a variety of methods for constructing qubits around it. One of the most successful techniques for early quantum computation involved manipulating nuclear spins in liquid-phase molecules via nuclear magnetic resonance, or NMR (Vandersypen et al., 2001). Liquid-state quantum computers, however, tend to be unscalable in the

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long term due to the chaotic tendencies of liquid environments. Current research into nuclearspin computation has shifted almost entirely to investigation of solid-state NMR techniques. As with all other methods, there are both pros and cons to using nuclei as a qubit basis. Due to their natural isolation from other nuclear spins, coherence times are unparalleled for single qubits, thus greatly reducing the technical challenges of noise reduction that plague most quantum computers today. However, by the same token, naturally isolated qubits mean inducing delicate entanglement interactions between them is exceedingly difficult. In 1998, Daniel Loss and David DiVincenzo proposed another promising method, focusing on the interactions of electrons confined to threedimensional voltage wells known as quantum dots. Using this method, external electric fields can modify the electron tunnelling rate between two target dots in proximity. Thus, spin-spin interactions can be effectively controlled with high precision (House, 2012). The individual spins themselves can be controlled via oscillating magnetic fields, similar to NMR techniques for nuclear spin. Strengths of this approach include ease of entanglement, as well as the strong correlation between quantum dot technologies and well-understood silicon nanotech. Various ideas have been proposed for a combined nuclear-electronic spin qubit, most notably by Australian physicist Bruce Kane in 1998. Kane proposed that single qubit operations are nuclear while multi-qubit operations utilize electronic exchange effects. Certain inherent complications limit the viability of all such proposals thus far, however, especially with regard to qubit readout. Thus, the bulk of the effort in this subfield is currently directed towards tweaking Kane’s proposal on paper into a more practical model.

"Spin is naturally appealing for storing binary information since, due to extremely unintuitive quantum mechanical considerations, there are only two possible states in which a particle’s spin can ever be observed: perfectly aligned with the axis of measurement, or 180 degrees misaligned."

Topological Although experimental results are currently infeasible, there is significant academic interest in constructing a quantum computer using the topology of anyon “world lines” — the threedimensional paths traced out by particles moving on a two-dimensional surface over time. Much of the practical difficulty in this regime arises from the creation of the two-dimensional anyons, a technical leap achieved in laboratory conditions only recently (Bartolomei et al., 2020). Unfortunately, the anyons reliably generated in all experiments to date have been abelian in nature. From a physical perspective, this means that swapping the positions of two anyons —

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quantum computers are developed based on superconducting models. Due to many longterm shortcomings of superconducting quantum computation, one of these unexplored avenues may even supplant it as the standard, just as Josephson junction technology has replaced liquid state NMR as the status quo today.

Figure 3: Example Braid An element of a braid group, represented by a unique combination of over-under twists on a set of strings with fixed starting points. Operations on a topological quantum computer can be visualized by spiralling anyons around one another in unique patterns, resulting in distinctly braided world lines.

Google-NASA Supremacy

Image Source: Wikimedia Commons

the unital operation used in braiding — has no effect on the state of the overall system, rendering them useless for computation. The non-abelian anyons required for computation — that is, anyons whose braid patterns lead to physically measurable effects — may have been created by a team working on the problem in 2013 (Willett et al.). Unfortunately, these results have yet to be independently confirmed, and the experiment is generally regarded as inconclusive by the scientific community at large. Given the theoretical acquisition of a non-abelian anyonic system, however, the world lines of these particles, with the passage of time represented as the vertical dimension, could be influenced to form braids with unique computational properties. Unlike many other types of qubits, anyon braids would be stable by their physical nature from most exterior perturbations (Kitaev, 2003). Actual computation would be carried out in terms of braid group algebra, a well-understood branch of abstract mathematics.

Other Many other promising propositions for qubit structure exist: quantum states of light (Zhong et al., 2020), charge differences in quantum dots (Gorman et al., 2005), and van der Waals effects between thin, near-planar semiconductors (Lucatto et al., 2019). Refinements to these proposals, experimental breakthroughs, and entirely new designs will most likely continue to be reported even as the first noisy, small-scale

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Quantum supremacy, or the ability of a quantum computer to perform calculations impossible in reasonable time scales for any classical computer, has been the primary goal of quantum computation since its conception. In October 2019, Google published a paper in Nature in partnership with NASA detailing the results of a program run on their 54-qubit universal quantum computer Sycamore, which they claimed to be the first recorded instance of quantum supremacy (Arute et al., 2019). The machine used noisetolerant superconducting transmon qubits, a variant of the charge qubit, connected in a rectangular lattice linking each qubit to its four nearest neighbors. One qubit did not function properly at runtime, so the effective qubit count for the computation was reduced to 53. The program in question was not a practically useful one, but rather an optimized benchmarking test in which pseudo-random quantum circuits were generated and run, then fidelity checked by classical estimation models. In order to increase accuracy, the two-qubit interactions were individually tailored to reduce qubit-specific errors identified in a previous set of isolated tests. While this means that the computer did not directly run any of the “textbook” operations used in quantum programming, collaborators claim that certain fundamental operations could still be achieved using a variant of the individualized two-qubit interaction scheme employed (Arute et al., 2019). The chosen program was run one million times, taking Sycamore 200 seconds in total to complete, the bulk of which was spent doing auxiliary classical computation. Quantum core activity lasted only around 30 seconds total. The output was a probability distribution of bitstrings resembling a laser scatter interference pattern, the reproduction of which was deemed intractable using classical methods and estimated to have a runtime of about 10,000 years on the world’s current fastest supercomputer, the IBM Summit 3. The next step identified by the authors involves an increased focus on error correction and the design of fault-tolerant logical qubits for researchers in pursuit of useful quantum applications (Arute et al., 2019). In wake of these claims, competitor IBM released their

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own statement regarding the Google-NASA paper, claiming that the 10,000-year estimate was based on a false assumption of memory limitations (Pednault et al., 2019). Google had noted that modern supercomputers do not have enough RAM to store the full state vector of the simulated quantum system outright, and thus a more memory efficient but exponentially more time-consuming method must be employed (Arute et al., 2019). IBM, however, theorized that algorithms making better use of hard drive storage in concert with their bulk RAM could provide the necessary memory to complete calculations using the former technique in under three days (Pednault et al., 2019), suggesting that the definitional requirements for quantum supremacy have not yet been met. In a press release soon after the IBM rebuttal, Google quickly pointed out that no such three-day simulation has yet to be run. Further complicating the matter, in the time since Google published their results, a Chinese team has staked their own claim in the race for quantum supremacy using a wildly different technique that involves the quantum interplay of photons, or the unital particles that make up light. The computation was estimated to take a modern supercomputer anywhere from 0.6 to 2.5 billion years, and, due to light’s lack of classical thermal conductivity, was able to be run in a controlled room temperature environment (Zhong et al., 2020). One must check their excitement, however, as the team’s machine was not a universal quantum computer. Indeed, it is not yet even programmable – it was custombuilt for exactly one measurement. Still, unlike Google’s computation, the technique is likely to have immediate practical applications calculating the permanents of large, complex matrices if the machine can be influenced to run some simple programs (Aaronson and Arkhipov, 2014). If this should be accomplished, the world may finally have its first practical quantum device – a great achievement in its own right, even if it lacks the universality of a full quantum computer.

Conclusions Precise definitions of quantum supremacy aside, these recent successes are a clear indication that we have entered what researchers refer to as the NISQ (noisy intermediate-scale quantum) era. Google itself now holds a 72-qubit processor in addition to Sycamore; Intel, a 49-qubit core; IBM, 53. As of 2019, specialized quantum computing start-up Rigetti has an unprecedented 128-universal-qubit processor, though no quantum supremacy claims have yet to emerge. It

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is important to note here that for NISQ machines, “larger” means “noisier” just as often as it means more power. And while current machines are no doubt impressive, the potential for mid- to near-term meaningful application is still under question, with some skeptical experimentalists like Mikhail Dyakonov predicting decades or centuries before generally applicable quantum machines become practical (2018). Indeed, some staunch third-party experts question the validity of the Google-NASA computation, adopting some of the same arguments and conclusions as Dyakonov. Notable among these is Professor Emeritus at the Hebrew University of Jerusalem, Gil Kalai, who voiced his doubts about the Sycamore test in a blog post from December of the same year (Kalai, 2019). In it, Kalai discusses questions about, among other things, the fidelity of the statistical methods used to verify the monster supremacy calculation, calling for rigorous peer review before acceptance from the general public. Whether the doubts of Dyakonov and Kalai prove founded, however, most agree that the next hurdles quantum researchers must face are those involved with reliability and error correction. What form this breakthrough will take, if any, is a question that must be answered by the next generation of quantum machines. Such a breakthrough could potentially revolutionize much of how we compute. The concept of quantum computation was, after all, first proposed as a solution to classical computers’ inefficiency at simulating quantum objects. This includes potential applications in protein binding, chemical engineering, pharmaceuticals, and materials sciences, among others. In addition, the aforementioned Shor’s and Grover’s algorithms promise to break most existing internet security protocols and greatly improve the efficiency of database management, along with whatever unforeseen applications are waiting for a clever programmer to root them out. At the same time, one must temper their expectations if they wish to avoid disappointment. Quantum computers will in no way constitute a substitution for regular computers in any conceivable scenario. Indeed, they are known to solve many classes of problems much slower than classical computers of comparable size (Moutafis, 2021). For a truly definitive picture, we must be resigned to watch and wait as the first practical quantum computers slowly come online around the world to see for certain just what new questions they may be able to answer – or what new obstacles might keep them just out of reach.

"The chosen program was run one million times, taking Sycamore 200 seconds in total to complete, the bulk of which was spent doing auxiliary classical computation."

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Aaronson, S., & Arkhipov, A. (2014). The computational complexity of Linear Optics. Research in Optical Sciences. https://doi.org/10.1364/qim.2014.qth1a.2 Arute, F, et al. (2019). Quantum Supremacy Using a Programmable Superconducting Processor. Nature, 574(7779), 505–510. doi: 10.1038/s41586-019-1666-5 Bartolomei, H., Kumar, M., Bisognin, R., Marguerite, A., Berroir, J.-M., Bocquillon, E., Plaçais, B., Cavanna, A., Dong, Q., Gennser, U., Jin, Y., & Fève, G. (2020). Fractional statistics in anyon collisions. Science, 368(6487), 173–177. https://doi. org/10.1126/science.aaz5601 Benioff, P. (1980). The computer as a physical system: A microscopic quantum mechanical Hamiltonian model of computers as represented by Turing machines. Journal of Statistical Physics, 22(5), 563–591. doi: 10.1007/bf01011339 Connelly, J. (2008). Ternary Computing Testbed 3-Trit Computer Architecture. Devoret, M. H., & Martinis, J. M. (2004). Implementing Qubits with Superconducting Integrated Circuits. Quantum Information Processing, 3(1-5), 163–203. doi: 10.1007/s11128004-3101-5 Divincenzo, D. P. (2005). The physical implementation of Quantum Computation. Scalable Quantum Computers, 1–13. https://doi.org/10.1002/3527603182.ch1 Dyakonov, M. (2018). The Case Against Quantum Computing. Retrieved April 12, 2020, from https://spectrum.ieee.org/ computing/hardware/the-case-against-quantum-computing Gorman, J., Hasko, D. G., & Williams, D. A. (2005). Charge-qubit operation of an isolated double quantum dot. Physical Review Letters, 95(9). https://doi.org/10.1103/ physrevlett.95.090502

Moutafis, R. (2021, February 1). Will Quantum computers replace their classical counterparts? Medium. Retrieved September 17, 2021, from https://towardsdatascience.com/ will-quantum-computers-replace-their-classical-counterparts847e20e32fc2. Orlando, T. P., Mooij, J. E., Tian, L., Wal, C. H. V. D., Levitov, L. S., Lloyd, S., & Mazo, J. J. (1999). Superconducting persistentcurrent qubit. Physical Review B, 60(22), 15398–15413. doi: 10.1103/physrevb.60.15398 Pednault, E., Gunnels, J., Maslov, D., & Gambetta, J. (2019). On "Quantum Supremacy". Retrieved April 12, 2020, from https://www.ibm.com/blogs/research/2019/10/on-quantumsupremacy/ Struck P., (2013). Spin coherence in carbon-based nanodevices. PhD thesis, University of Konstanz Vandersypen, L., Steffen, M., Breyta, G. et al. (2001). Experimental realization of Shor's quantum factoring algorithm using nuclear magnetic resonance. Nature 414(6866), 883–887. doi: /10.1038/414883a Willett, R. L., Nayak, C., Shtengel, K., Pfeiffer, L. N., & West, K. W. (2013). Magnetic-Field-Tuned Aharonov-Bohm Oscillations and Evidence for Non-Abelian Anyons atν=5/2. Physical Review Letters, 111(18), 186401. doi: 10.1103/ physrevlett.111.186401 Zhong, H.S., Wang, H., Deng, Y.H., Chen, M.C., Peng, L.C., Luo, Y.H., Qin, J., Wu, D., Ding, X., Hu, Y., Hu, P., Yang, X.Y., Zhang, W.J., Li, H., Li, Y., Jiang, X., Gan, L., Yang, G., You, L., Wang, Z., Li, L., Liu, N.L., Lu, C.Y., & Pan, J.W. (2020). Quantum computational advantage using photons. Science, 370(6523), 1460–1463.

House, M. G. (2012). Lateral Quantum Dots for Quantum Information Processing. UCLA. ProQuest ID: House_ ucla_0031D_10262. Merritt ID: ark:/13030/m5vm4d7z. Retrieved April 12, 2020, from https://escholarship.org/uc/ item/3fk0q280 Kalai, G. (2019, November 13). Gil’s Collegial Quantum Supremacy Skepticism FAQ. Combinatorics and More. https:// gilkalai.wordpress.com/2019/11/13/gils-collegial-quantumsupremacy-skepticism-faq/ Kane, B. (1998). A silicon-based nuclear spin quantum computer. Nature, 393(6681), 133–137. Kitaev, A. (2003). Fault-tolerant quantum computation by anyons. Annals of Physics, 303(1), 2–30. doi: 10.1016/s00034916(02)00018-0 Koch, J., Yu, T. M., Gambetta, J., Houck, A. A., Schuster, D. I., Majer, J., Blais, A., Devoret, M. H., Girvin, S. M., & Schoelkopf, R. J. (2007). Charge-insensitive qubit design derived from the Cooper pair box. Physical Review A, 76(4). https://doi. org/10.1103/physreva.76.042319 Loss, D., & Divincenzo, D. P. (1998). Quantum computation with quantum dots. Physical Review A, 57(1), 120–126. doi: 10.1103/physreva.57.120 Lucatto, B., Koda, D. S., Bechstedt, F., Marques, M., & Teles, L. K. (2019). Charge qubit in van der waals heterostructures. Physical Review B, 100(12). https://doi.org/10.1103/physrevb.100.121406

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Effects of Public Transportation Development BY TYLER CHEN '24 Cover Image: A closeup of the London Underground map – the rapid transit system that serves the greater London metropolitan area. This system originated from the Metropolitan Railway, which was the world’s first underground railway. Nowadays, underground passenger rail systems are commonplace and important components of transit systems worldwide. Image Source: Pixabay

Introduction As the world continues to expand, the transportation infrastructure fostering globalization becomes more and more important. To facilitate economic growth and societal wellbeing, goods and people must somehow make their way across the entire globe in a timely and cost-effective manner. During the 20th century, many countries across Europe and Asia responded to this growing need for expanded public transportation systems by launching large railway projects that efficiently connected communities to city centers. Most notably, from 2013 to 2017, the cumulative urban metro track length grew by 50% from 4815km of track to 7218km of track – a truly impressive feat for only 4 years (UITP, 2018). As such, global cities such as London and Tokyo now boast robust public transportation systems where subways and buses run frequently and network coverage is comprehensive. However, such a transition towards large public transportation systems has not occurred within the United States. The American train system

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pales in comparison to its European and Asian counterparts, with slow and infrequent service making it an unreliable form of transportation. In fact, when considering countries that saw more than 1 billion passenger-kilometers, the United States placed 36th out of 38 in terms of passenger-kilometers per capita, placing only in front of Mexico and Canada (OECD, 2021). But unlike the United States, Canada and Mexico still have relatively effective urban rapid transit systems. With insufficient railroad systems and urban rapid transit systems, it is no surprise that American citizens are very car-dependent – a quality that only fosters outward expansion of American cities to find space for all its residents’ personal vehicles. Known as urban sprawl, this phenomenon is characterized by low-density suburbanization outside the city center and has led to increases in traffic congestion and air pollution levels as a result of the pure abundance of cars on the road (Nechyba & Walsh, 2004). Public transportation projects have been slowly developing within the United States in the past few years. New plans to build high-speed railways and to revitalize urban transit networks paint a DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

promising picture of the near future. It has been long touted that public transportation systems are a very effective economic stimulant to the communities that they serve. However, public transportation funding has long been a contentious issue, as many of these systems consistently post a financial loss. Most prominently, Amtrak – the main intercity rail service provider in the United States – has long run a largely unprofitable service and relies on federal funding to stay afloat, drawing substantial criticism from citizens and policymakers alike. However, beyond the financial and economic implications of public transportation development, it is important to understand the various other effects that these services have.

Environmental Effects of Public Transportation The utilization of public transportation services can have large environmental impacts on the areas surrounding the transportation network. Every individual who decides to take a public bus or train for a particular trip means one less personal vehicle on the road. And with public transportation vehicles having much larger capacities than typical personal vehicles, the marginal increase in carbon emissions from a slightly heavier bus or train is far outweighed by the additional carbon emissions released by an extra motor vehicle on the road. But even though larger public transportation vehicles do release more greenhouse gas emissions overall, personal vehicles still emit more greenhouse gases on a per passenger basis. As per the Federal Transit Administration, the average U.S. singleoccupancy vehicle emits an estimated 0.964 pounds of Carbon Dioxide (CO2) per passenger mile, compared to an estimated 0.643 pounds of CO2 per passenger mile for urban bus systems across the United States (Hodges, 2010). This figure also accounts for bus occupancy rates, which average to be 28% across the top 50 bus transit systems in the United States. This means that at full capacity, these buses emit an estimated 0.177 pounds of CO2 per seat mile on average – 81.6% less than the CO2 emissions of a singleSPRING AND SUMMER 2021

occupancy vehicle. The same pattern can be seen for other forms of public transportation as well. Light rail systems – referring to streetcar/tram systems that run on tracks that are integrated with road traffic in urban areas – emit an estimated 0.365 pounds of CO2 per passenger mile on average. Heavy rail systems, or more traditional multi-car train systems that run on isolated track systems (e.g. subway systems and commuter rail), emit an estimated 0.224 pounds of CO2 per passenger mile. Both of these figures also come in at below the aforementioned 0.964 pounds of CO2 per passenger mile emitted for personal singleoccupancy vehicles (Hodges, 2010). However, these figures are undoubtedly biased towards larger, well-established systems in cities such as New York, Boston, and Chicago, where higher passenger volumes and occupancy rates lead to lower greenhouse gas emissions per passenger. Smaller systems such as the light rail system in Kenosha, Wisconsin, a town of 100,000, simply don’t see the same volume of passengers as large metropolitan areas, causing CO2 emission rates to be less favorable compared to singleoccupancy vehicles on a per passenger basis.

Figure 1: On the left, the inside of Munich’s central train station is depicted. On the right, the exterior of Houston’s only train station is seen. Although Munich is a smaller city than Houston (6,000,000 vs. 7,100,000 population by metropolitan area), its main train station can be seen handling 9 departures within a 25-minute time frame. Compare this to Houston’s only train station, which only sees 6 train departures per week and simply appears forgotten. This wide discrepancy in train activity and service frequency between the two cities exemplifies how small the American passenger rail system is compared to European and Asian systems – especially within some of the largest cities. Image Source: Wikimedia Commons

Additionally, the impact of public transit on other air pollutants can be seen in a case study on Madrid, Spain between 2005 and 2016. During this time, the city experienced 208 days of metro and urban transit strikes that led to stoppages in public transportation services, forcing public transit riders to use their personal vehicles. As a result, city-wide levels of Nitrogen Dioxide (NO2), Nitric Oxide (NO), Particulate Matter (PM10 specifically), and Black Carbon (BC) – air pollutants that abnormally increase acid rain, haze, and have heat-trapping properties – saw modest increases ranging from around 4% to 8% during those 208 days (Basagana et al., 2018). However, these recorded levels were dampened by the fact that a large number of the strikes that happened during this period were partial strikes that saw only a portion of services reduced, meaning that personal vehicle use would not have 147

Figure 2: An electric public bus charging at a bus stop in Helsinki, Finland. Many forms of public transportation are also moving towards electrification, which further reduces the amount of greenhouse gases emitted compared to non-electric forms of public transportation. More specifically, a 40-foot diesel passenger bus emits around 2,680 grams of CO2 per mile, while the electric-equivalent of a bus that is powered by the average American electric grid produces around 1,078 grams of CO2 emitted per mile in indirect emissions from electricity production (Houston, 2019). This reduction is even more pronounced in states with greener electric grids like New York, where the electric equivalent of the 40-foot passenger bus emits 347 grams of CO2 per mile in indirect emissions – an 87% reduction from the dieselpowered 40-foot passenger bus. Image Source: Pixabay

"Even though highspeed rail is a more energy-efficient mode of transportation than a personal vehicle, the energy generated to power these trains and the processes involved in installing the rail infrastructure to support these systems can still be environmentally taxing and should not be ignored."

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seen as significant of an uptick as if there was a full stoppage. Additionally, a further breakdown into the different kinds of strikes revealed that metro strikes specifically led to significant increases in BC, NO, and Carbon Monoxide (CO), with BC levels increasing by 30%, NO levels increasing by 60%, and CO levels increasing by up to 80% across Madrid – further emphasizing the drastic impact of public transit systems on air pollutant levels (Basagana et al., 2018). Despite the lower amount of greenhouse gas emissions that running public transportation services yields compared to single-occupancy vehicles, the construction of vital public transit infrastructure does take away from these benefits. Even though CO2 per passenger mile levels for commuter rail systems are roughly one-third that of single-occupancy vehicles, the process by which steel, concrete, and other equipment are manufactured, forged, and installed to build a track system also creates a substantial amount of greenhouse gases. O’Toole identifies this with the construction of Seattle’s North Link light rail system, which was projected to consume 17.4 trillion BTUs (British Thermal Units – a measure of energy) while saving around 350 billion BTUs annually by 2015 (O’Toole, 2008). Additionally, these annual savings were projected to decline year by year as more efficient single-occupancy vehicles hit the market, leading to annual savings of only around 200 billion BTUs by 2030. This means that it wouldn’t be until 2095 when the overall energy savings of this light rail system would offset the energy consumption required to construct the system. Similar concerns were brought forth with California’s high-speed rail project, which sought to connect the San

Francisco Bay Area with Los Angeles with a subthree-hour train link (Chester & Horvath, 2012). Even though high-speed rail is a more energyefficient mode of transportation than a personal vehicle, the energy generated to power these trains and the processes involved in installing the rail infrastructure to support these systems can still be environmentally taxing and should not be ignored.

Lifestyle Effects of Public Transportation Beyond the debate between the true cost/ benefit analysis of greenhouse gas emissions, the utilization of public transportation services is more tangibly linked to a change in overall lifestyle. The average American dedicates around 54 minutes per day to commuting, and close to 70 minutes per day in large cities like New York City and Los Angeles. This can often be a stressful experience, especially given that longer commute times are linked to a lower level of physical and mental well-being (Stutzer & Frey, 2008). Indeed, the medium of transportation can have a drastic effect on a commuter’s overall mood. Being stuck in traffic with many other commuters in their personal vehicles can be significantly less enjoyable than getting on a commuter train and having 45 minutes to oneself before reaching the destination. In fact, among New York residents, those who commuted by train were seen to have a more positive mood than those who commuted by car (Wener & Evans, 2010). Along with needed to sit through traffic, commuting by car adds additional stresses to commuters such as concerns over unpredictable car accidents,

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the additional burden of finding parking spots in crowded urban areas, and having to pay for said parking. Public transportation systems are typically on time and eliminate such concerns with parking. This reduction of stressors was particularly evident amongst Montreal residents, in which residents who commuted via public transportation experienced significantly less stress than those who commuted by car (Brutus et al., 2017). Additionally, using public transportation is linked to a more active lifestyle compared to using a personal vehicle. Those who use the bus or subway must climb stairs, walk, and engage in some fashion of physical activity (Brutus et al., 2017). This higher level of physical activity involved in public transportation use was documented in another study that saw the health impacts of replacing personal vehicles as the main mode of commuting. Individuals who commuted via public transportation had significantly higher levels of energy expenditure as a result of moderate aerobic activity that stemmed from walking to and from stations and climbing stairs to reach metro platforms, possibly leading to significant overall weight loss over six weeks (Morabia et al., 2010). In addition, higher public transportation access can be used as a social and economic stimulant to underserved and impoverished neighborhoods, lifting the standard of living and thus resulting in better dieting and health practices overall. All in all, it was also seen that a 1% reduction in personal automobile use results in a 0.4% decline in obesity rates, heavily indicating that public transportation development yields significant health benefits (Samimi et al., 2009).

Bike-sharing has also become a novel transportation development with significant health benefits all across the world. Similar to how taking the bus or metro can result in higher levels of physical activity, using bike-sharing services also involves high levels of aerobic activity. Additionally, 41% of Washington DC residents mentioned exercise as a reason to use the city’s bike-sharing service Capital Bikeshare, indicating that bike-sharing also encourages residents to exercise through a cost-effective and enjoyable outlet (Ricci, 2015). Utilizing a bikesharing service instead of a car has also been seen to prevent deaths as a whole. Considering a car-trip substitution rate of 4.7% by bike-sharing services – meaning that 4.7% of all bike-sharing trips are trips that specifically replace car trips – 2.53 deaths are prevented annually in Paris due to higher levels of physical activity (Otero et al., 2018). This 4.7% is also the minimum car-trip substitution rate across 12 European cities with the most comprehensive bike-sharing services. If the car-trip substitution rate was 12% – the maximum car-trip substitution rate from the same 12 European cities – the number of deaths prevented annually in Paris would jump to 3.80. The additional deaths prevented also have implications on the healthcare system overall, as the positive health effects of bike-sharing mean that less stress is placed on the healthcare system. Examining Paris once more, the health economic analysis of its bike-sharing systems, while considering a car-trip substitution rate of 4.7%, reveals that the city saves 10.2 million euros in healthcare expenditures annually as a result of its bike-sharing services (Otero et al., 2018). In addition to all the positive health effects that Figure 3: A picture of a Bluebikes stand in Boston, MA provides a glimpse into the new trend in public transportation of bikesharing. A cheap alternative to driving and other means of transportation, bike-sharing has emerged as a fun way to tour the city while also supporting healthy lifestyle practices by encouraging exercise in the process. Image Source: Wikimedia Commons

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Figure 4: A bus stop sign at Homerton Hospital in London, United Kingdom shows the different buses that service this stop. Public transportation links to hospitals and other healthcare providers are not uncommon across the world and are evidently an important part of London’s healthcare system.

transporting patrons from one point to another. This becomes especially important when considering individuals that don’t have consistent access to private vehicles for commuting to work or accessing life-sustaining healthcare services — an issue that is especially apparent in heavily rural areas. Although the United States is among the most developed nations in the world, its large size means that low-density areas in the center of the country make a far-reaching, comprehensive, and countrywide rail system difficult to achieve. On top of that, with rural areas typically being poorer, the necessity for effective public transportation systems across the Midwest is critical (Kyzyma, 2018).

Image Source: Wikimedia Commons

"Within urban areas, public transportation access can play a significant role in the socioeconomic development of a community. In areas where residents can’t afford to purchase a personal vehicle, the ability to obtain basic necessities such as food and healthcare is strained."

it brings, a more public-transportation-reliant society is objectively safer as well. With fewer personal vehicles on the road, the number of traffic accidents in less car-reliant areas is also lower, increasing average life expectancies. The United States has one of the highest traffic fatality rates in the entire world, largely due to its very high car dependency leading to more instances of risky driving behaviors such as driving when severely ill or following significant alcohol consumption (Lichtman-Sadot, 2019). In countries with far more developed public transport systems, traffic fatality rates are much lower, suggesting that higher access to public transit can result in a lower number of traffic-related deaths. This trend is highly prevalent in different areas within a nation as well. When examining the counties that make up the 101 largest metropolitan areas in the U.S., the traffic fatality rates of the 10 counties with the “smartest” urban growth – where residents are less car-dependent and have the most public transportation options – had a quarter of the traffic fatality rates per capita as the 10 counties with the most “sprawled” urban growth and high levels of car dependency (Litman, 2020).

Accessibility Effects of Public Transportation The goal of a public transportation system is to provide an accessible and inexpensive means of

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Within urban areas, public transportation access can play a significant role in the socioeconomic development of a community. In areas where residents can’t afford to purchase a personal vehicle, the ability to obtain basic necessities such as food and healthcare is strained. A study regarding food insecurity across the United States saw that increased public transportation access played a significant part in reducing food insecurity levels. Specifically, the addition of one bus-equivalent vehicle for every 10,000 residents was seen to decrease household food insecurity levels by 1.6 percentage points (Baek, 2016). This decrease in food insecurity levels was even more pronounced for those coming from a poor background, as there was almost twice as much of a drop in food insecurity levels among poor families. Similar trends in the involvement of transportation availability can be seen in healthcare access as well. In a study of 200 children that routinely missed clinical appointments, 51% of these children primarily attributed their missed appointments to transportation barriers (Syed et al., 2013). Those who did typically make their clinical appointments attributed their missed appointments to transportation barriers closer to 30% of the time, indicating that transportation access plays a major role in promoting healthcare access. This effect is even more pronounced in rural areas, where healthcare providers are fewer and farther in between. In rural North Carolina, those who had a driver’s license were seen to show up to chronic care visits 2.29 times as often and would also show up to regular care appointments 1.92 times as often (Arcury et al., 2005). Similar trends were seen among those who didn’t own a personal vehicle but knew somebody who did. Those who had family provide transportation to chronic care visits made 1.58 times as many appointments as those who didn’t.

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Conclusion In 2016, Amtrak recorded revenues of $3.2 billion, while recording expenses of $4.3 billion, leaving the net loss to be covered by federal grants (Peterman, 2017). Metra, Chicagoland’s primary commuter rail provider, reportedly can cover only a quarter of its expenses from its fare revenue. Needless to say, public transportation is not necessarily a profitable operation – at least at first glance. However, positive environmental effects, healthier lifestyles, and improved access to essential goods and services all contribute greatly to a sustainable economy by reducing costs from environmental degradation, strains on resources within healthcare systems, and economic stagnancy. So, while public transportation systems require heavy investment, it is imperative to the overall well-being of a nation.

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Peterman, D. R. (2017). Amtrak: Overview (No. R44973). Article R44973. https://trid.trb.org/view/1604434

Arcury, T. A., Preisser, J. S., Gesler, W. M., & Powers, J. M. (2005). Access to Transportation and Health Care Utilization in a Rural Region. The Journal of Rural Health, 21(1), 31–38. https://doi.org/10.1111/j.1748-0361.2005.tb00059.x

Ricci, M. (2015). Bike sharing: A review of evidence on impacts and processes of implementation and operation. Research in Transportation Business & Management, 15, 28–38. https://doi. org/10.1016/j.rtbm.2015.03.003

Baek, D. (2016). The Effect of Public Transportation Accessibility on Food Insecurity. Eastern Economic Journal, 42(1), 104–134. https://doi.org/10.1057/eej.2014.62

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Basagaña, X., Triguero-Mas, M., Agis, D., Pérez, N., Reche, C., Alastuey, A., & Querol, X. (2018). Effect of public transport strikes on air pollution levels in Barcelona (Spain). Science of The Total Environment, 610–611, 1076–1082. https://doi. org/10.1016/j.scitotenv.2017.07.263 Brutus, S., Javadian, R., & Panaccio, A. J. (2017). Cycling, car, or public transit: A study of stress and mood upon arrival at work. International Journal of Workplace Health Management, 10(1), 13–24. http://dx.doi.org/10.1108/IJWHM-10-2015-0059 Chester, M., & Horvath, A. (2012). High-speed rail with emerging automobiles and aircraft can reduce environmental impacts in California’s future. Environmental Research Letters, 7(3), 034012. https://doi.org/10.1088/1748-9326/7/3/034012 Hodges, T. (2010). Public Transportation’s Role in Responding to Climate Change. https://www.transit.dot.gov/sites/fta.dot. gov/files/docs/

Stutzer, A., & Frey, B. S. (2008). Stress that Doesn’t Pay: The Commuting Paradox*. The Scandinavian Journal of Economics, 110(2), 339–366. https://doi.org/10.1111/j.14679442.2008.00542.x Syed, S. T., Gerber, B. S., & Sharp, L. K. (2013). Traveling Towards Disease: Transportation Barriers to Health Care Access. Journal of Community Health, 38(5), 976–993. https:// doi.org/10.1007/s10900-013-9681-1 UITP (2018). WORLD METRO FIGURES. Wener, R. E., & Evans, G. W. (2011). Comparing stress of car and train commuters. Transportation Research Part F: Traffic Psychology and Behaviour, 14(2), 111–116. https://doi. org/10.1016/j.trf.2010.11.008

Houston, S. (2019). Electric Utility Investment in Truck and Bus Charging. Retrieved September 13, 2021, from https://www. ucsusa.org/resources/electric-utility-investment-truck-and-buscharging Kyzyma, I. (2018). Rural-urban disparity in poverty persistence. 34(3), 7. Lichtman-Sadot, S. (2019). Can public transportation reduce accidents? Evidence from the introduction of late-night buses in Israeli cities. Regional Science and Urban Economics, 74, 99–117. https://doi.org/10.1016/j.regsciurbeco.2018.11.009 Litman, T. (2020). Evaluating Public Transportation Health Benefits. 36. Morabia, A., Mirer, F. E., Amstislavski, T. M., Eisl, H. M.,

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mRNA VaccinologyPerspectives BY VARUN LINGADAL ’23 Cover Image: A vial of COVID-19 vaccine, a mRNA vaccine. Image Source: Wikimedia Commons

Introduction With the COVID-19 pandemic still devastating the global population, the desire to return to normal is greater than ever. The first COVID-19 vaccines, released in late 2020, provide a potential light at the end of the tunnel. These mRNA vaccines are a revolutionary approach to effectively protect individuals against both COVID-19 infection and severe COVID-19 symptoms. mRNA vaccine technology is ushering in a new era of vaccinology, where individuals can be immunized against a wide variety of diseases including those that, in the past, were not able to be countered with a vaccine. The human immune system is divided into two arms: the innate immune system and the adaptive immune system. The innate immune system provides protective barriers and a first line of defense against pathogens. It includes organs such as the skin, the cilia in the nose, lysozymes (hydrolytic enzymes within cells that are capable of cleaving the outer, peptidoglycan layer of bacterial cell walls), the inflammatory response, complement pathways, and countless other mechanisms (Clem, 2011). Complement

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pathways are a series of distinct plasma proteins that interact with one another to make pathogens more susceptible to phagocytes and induce inflammatory responses (Janeway et. al, 2001). There are three complement pathways that make up the complement system. The classical pathway involves the binding of C1q protein to the surface of a pathogen (Janeway et. al, 2001). This protein is unique in the fact that it can act as a key effector mechanism for either the innate or adaptive immune system (Janeway et. al, 2001). The MBlectin pathway is activated through the binding of mannan-binding lectin, to pathogens that are composed of mannose-containing carbohydrates (Janeway et. al, 2001). The alternative pathway can be activated when a complement component binds to the surface of a pathogen (Janeway et. al, 2001). The adaptive immune system, on the other hand, reacts specifically to particular pathogens that the body encounters – with a memory for pathogens encountered before (Clem, 2011). Though the adaptive immune response is slower, it allows the immune system to respond faster with successive exposure to a specific pathogen. Pathogens have a variety of proteins on their cell surfaces known as antigens, which bind to antibodies produced by the adaptive immune DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

system (Clem, 2011). The presence of antigens from pathogens leads to production of specific antibodies to that antigen, which then trigger the activation of immune cells that mount a response to the invading pathogens (Clem, 2011). Vaccines work by taking advantage of the adaptive immune response. By exposing the body to a pathogen (either a dead pathogen, an attenuated pathogen, or a product produced by a pathogen), a vaccine is capable of triggering an adaptive immune response in the body, giving the immune system memory to that specific pathogen. The history of vaccinology dates back to the fifteenth century, where there are examples of the Chinese and the Turks attempting to protect their people against smallpox by exposing them to small amounts of dried smallpox lesions (Clem, 2011). These early, rudimentary vaccination attempts were only partly effective at best. Another breakthrough in vaccinology occurred with Edward Jenner’s experimentation in the late 18th century (Plotkin, 2009). Edward Jenner realized that milkmaids were protected against smallpox as a result of their prior infection with cowpox. With this knowledge, Jenner ran scientific investigations that seemed to prove that inoculation with cowpox virus prevented virulent smallpox infection (History of Smallpox, 2021). Jenner took material from a cowpox

sore on a milkmaid and inoculated it into the arm of a 9-year-old boy (History of Smallpox, 2021). Months later, Jenner exposed the boy to the variola virus multiple times; however, the young boy never developed smallpox (History of Smallpox, 2021). With this, he had unlocked an early understanding of inoculation against one of the deadliest diseases to ravage humanity (History of Smallpox, 2021). Following Jenner, the field of vaccinology remained dormant for years until the end of the 19th century, when scientists like Louis Pasteur, Robert Koch, Emil von Behring, and Paul Ehrlich made groundbreaking discoveries that propelled the field of vaccinology forward. Pasteur discovered the concepts of induced resistance, methods to induce resistance to pathogens in organisms, leading to the development of useful vaccines against anthrax, cholera, and rabies. Koch gained a deeper understanding of how pathogens behaved, developing the four Koch postulates to describe a causative relationship between microbe and disease (Hilleman, 2000). These postulates state that 1) the microorganism must be found in diseased but not healthy individuals, 2) the microorganism must be cultured from the diseased individual, 3) inoculation of a healthy individual with the cultured microorganism must recapitulate the disease, and 4) the

"Following Jenner, the field of vaccinology remained dormant for years until the end of the 19th century, when scientists like Louis Pasteur, Robert Koch, Emil von Behring, and Paul Ehrlich made groundbreaking discoveries that propelled the field of vaccinology forward."

Figure 1: Koch’s Postulates with a diagram corresponding with each postulate. Image Source: Wikimedia Commons

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Figure 2: Preparation of the smallpox vaccine by injecting embryonated chicken eggs with viral particles. Image Source: Wikimedia Commons

"With the COVID-19 pandemic, the rise of mRNA vaccines and their near limitless potential presents a massive breakthrough in the field of vaccinology"

microorganism must be re-isolated from the inoculated, diseased individual and matched to the original microorganism (Segre 2013). Behring established the field of passive immunotherapy, in which soluble toxins from various bacteria are detoxified for the purpose of immunization. Last but not least, Ehrlich developed methods of specific quantification of antibodies (Hilleman, 2000).

use a killed version of a pathogen. Subunit, recombinant, polysaccharide, and conjugate vaccines use specific parts of a pathogen (such as proteins, antigens, sugars, capsids) to produce an immune response. The fourth group of vaccines, toxoid vaccines, utilize a toxin produced by a pathogen to create immunity to the parts of the pathogen that cause disease rather than create immunity to the pathogen itself (Vaccine.gov).

The next leap in vaccinology occurred from the 1930s to the 1950s. During WWII, methods of mass production were developed by Squibb Virus Laboratories to effectively mass produce the typhus vaccine by growing typhus Rickettsiae in the yolk sacs of hen eggs and to develop an influenza vaccine and the Japanese B encephalitis vaccines. Military initiatives and the rise of foundations dedicated to curing diseases led to the rapid development of several vaccines between 1950 to 1985, followed by a rapid decrease in pioneering achievements in the field of vaccinology after 1985. Today, modern era vaccines utilize vaccinology techniques and methods developed in the 20th century including whole and subunit bacterial vaccines, viral recombinant vaccines, and live and killed whole virus preparations. With the COVID-19 pandemic, the rise of mRNA vaccines and their near limitless potential presents a massive breakthrough in the field of vaccinology (Hilleman, 2000).

Live vaccines against viral diseases have proven to be one of the most cost-effective forms of vaccination, with previous successes against smallpox and poliomyelitis. (Minor, 2015). One of the most common methods of producing live vaccines involves passing a pathogen through a long series of cell cultures, typically chicken embryos, in order to attenuate and weaken the virus. With each culture the pathogen becomes more adapted to replicating in chicken cells and loses its ability to replicate as well in human cells. Eventually, the resulting pathogen may serve as a vaccine because it will not replicate in human cells well enough to cause illness but can still provoke an immune response (History of Vaccines, 2021).

Modern Vaccines Currently, there are four major types of vaccines. Live-attenuated vaccines use a weakened (attenuated) form of a pathogen to develop an immune response. Inactivated vaccines

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Live, attenuated pathogens present the same antigens as un-attenuated pathogens, inducing cell-mediated and antibody responses that can confer long-term immunity after only one or two doses. In addition, these vaccines can confer herd immunity through viral shedding, leading to indirect development of immunity in other individuals exposed to a vaccinated subject (Vetter et. al, 2018). Live attenuated vaccines typically provide immunity longer than killed or inactivated vaccines. However, there is the risk of the vaccine virus mutating back into a form that is capable of causing disease. Though unlikely, DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 3: A diagram of how mRNA vaccines elicit an immune response. The mRNA enters the cell and ribosomes translate into a viral antigen. This viral antigen is broken down by proteasomes and bind to MHC-1 and MHC-2. These MHCs induce responses Cytotoxic T Cells and T helper cells, specifically CD8+ and CD4+. Image Source: Wikimedia Commons

this has occurred in the past, particularly in the instance of the oral polio vaccine (OPV), which occasionally had mutations that resulted in rare cases of paralytic polio (History of Vaccines, 2021). Immunocompromised patients are also at risk of unregulated pathogen replication that can cause severe disease and even death (Vetter et. al, 2018). Inactivated or killed vaccines include the polio (IPV) vaccine, the rabies vaccine, and the hepatitis A vaccine. These vaccines are created by inactivating or killing a pathogen utilizing heat or chemicals. These methods kill the pathogen but keep its structure intact, allowing the immune system to recognize it and generate an immune response, thus retaining its immunogenicity, its ability to provoke an immune response. Inactivated vaccines do not carry the risk of mutating into a more virulent form; however, they provide a shorter length of immunity and typically require booster shots in order to provide long-term immunity (History of Vaccines, 2021). Subunit vaccines contain specific fragments of a pathogen known as antigens. These antigen fragments can include proteins, polysaccharides, and other parts of a pathogen or virus that may

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form virus-like particles (VLPs) (Vetter et. al, 2018). These antigen fragments can be isolated and used to produce the vaccine. Examples of these types of vaccines include the acellular pertussis vaccine and the influenza vaccine. Subunit vaccines can also be produced through genetic engineering. In this case, a gene coding for a specific viral protein or antigen is inserted into another virus or into cells in culture. When the carrier virus reproduces, or the cells are induced to produce the antigen, the target viral antigen can be isolated. The isolated antigen can then be introduced to a subject and be used to provoke an immune response. Though the viruslike particles come from the virus, it carries no genetic material and can’t cause illness (History of Vaccines, 2021). Finally, toxoid vaccines are vaccines that use inactivated versions of toxins that are produced by pathogenic bacteria to produce an immune response by inducing toxin-neutralizing antibodies (Vetter et. al, 2018). These include the tetanus vaccine, which protects tetanospasmin, a neurotoxin that is produced by the Clostridium tetani bacterium (History of Vaccines, 2021). Toxoids require multiple doses to maintain lifelong protection as they work by producing an

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"mRNA vaccines have several advantages compared to existing technologies. mRNA can be transfected into many types of cells including slowly dividing cells such as dendritic cells, allowing for more efficient presentation of its encoded antigens. mRNA vaccines can also trigger immunogenic responses without the need for adjuvants, additional substances added to vaccines to create a stronger immune response"

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immune response through the production of antibodies that must be present at the onset of disease to be effective. In addition, toxoids protect against disease pathogenesis in a vaccinated individual, but do not prevent transmission of the disease to other individuals. For toxoid vaccines to be effective, there must be high vaccination coverage through a population for initial doses as well as booster doses (Vetter et. al, 2018).

also provides a high degree of versatility in the antigens it can encode and it can also encode fulllength proteins. In one study by BioNTech AG, all vaccinated patients developed CD4+ and CD8+ T cell responses against the selected antigens from a mRNA vaccine. mRNA vaccines have been shown to elicit immune response for various infectious diseases including influenza, rabies, Zika, Ebola, and HIV (Verbeke et. al, 2019).

mRNA Vaccines

There are two major types of mRNA vaccines: conventional mRNA vaccines and self-amplifying vaccines. Conventional mRNA vaccines are based on the natural eukaryotic mRNA structure, with a 5’ cap structure, 5’ and 3’ untranslated regions, open reading frame (ORF), and a poly-A tail. The 5’ cap and the poly-A tail are required to protect the mRNA in a cellular environment and the 5’ and 3’ UTRs are important for mRNA stability. Self-amplifying vaccines enhance the potency of mRNA vaccines. SAM (self-amplifying mRNA vaccines) are based on replicons derived from RNA viruses allowing for abundant antigen expression inside cells infected with SAM (Lee et. al, 2018).

mRNA vaccines have several advantages compared to existing technologies. mRNA can be transfected into many types of cells including slowly dividing cells such as dendritic cells, allowing for more efficient presentation of its encoded antigens. mRNA vaccines can also trigger immunogenic responses without the need for adjuvants, additional substances added to vaccines to create a stronger immune response (Lee et. al, 2018). The concept of mRNA vaccines first took off in 1989. Vical Incorporated, a biotech company in San Diego, was able to show that mRNA packaged in liposomal nanoparticles could effectively be transfected into eukaryotic cells. The mRNA molecules were successfully integrated without the need for viral vectors and because they only need to reach the cytosol to be translated by ribosomes, there is no risk of integration into the host genome. In the early 1990s, mRNA was shown to be a useful method of delivering antigenic information to antigen-presenting cells (Verbeke et. al, 2019). Katalin Kiroko, a Hungarian biochemist who worked at UPENN in the 1990s, also produced groundbreaking discoveries in the field of mRNA technology. Kiroko was able to prove that mRNA could be used to direct a cell to make any protein (Kolata 2021). One of the groundbreaking discoveries she made that allowed mRNA to successfully be injected into live organisms and produce proteins was the discovery of pseudouridine, a molecule that organisms add to tRNA and mRNA molecules as they are produced (Kolata 2021). Adding this molecule to mRNA allowed Kiroko to inject the mRNA into an organism and avoid an immune response, allowing it to be successfully incorporated into the genome and produce specific proteins (Kolata 2021). Antigen-encoding mRNA is advantageous particularly because it provides an effective way to elicit presentation of MHC-1. MHC-1 is a major histocompatibility complex molecule that codes for cell surface proteins and induces responses from cytotoxic T lymphocytes (CTLs) that are essential in the adaptive immune system. mRNA

Early methods of mRNA vaccine delivery involved an ex vivo approach. In this method, monocyte-derived dendritic cells were transfected with antigen-encoding mRNA and then reinfused into patients. Subsequently, research shifted to in vivo methods and direct administration of mRNA to patients. This avoids the laborious and cost-extensive process of isolating and culturing patient-specific dendritic cells. In addition, these methods better mimic a natural viral infection. Despite these advantages, however, there are certain limitations that must be overcome in order to successfully infuse mRNA in vivo. This is partially attributed to the fact that there are several evolutionary barriers that prevent intrusion of foreign nucleic acids. mRNA has to resist degradation by RNases present in the bloodstream and in tissues. Within the cell, mRNA must resist being degraded by the endo-lysosomal compartment. Anti-viral host mechanisms in eukaryotic cells also increase enzymatic activity to degrade mRNA and reduce its cellular translation (Verbeke et. al, 2019). To attempt to avoid these issues, scientists consider the role the chosen injection site will play in what cell types may come in contact with and degrade the injected mRNA. Macropinocytosis, a form of nonselective bulk endocytosis, was found to be one of the most effective ways to introduce mRNA into host cells. In addition, nanoparticles and lipid nanoparticles may offer a new method for

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injecting mRNA into a host (Verbeke et. al, 2019). As a result of all these promising advancements, mRNA vaccines hold great potential as a new, burgeoning field of vaccinology.

Conclusion We have been attempting to combat diseases and pathogens since the beginning of humanity. Throughout history, we have adapted and developed new methods to combat these invisible organisms that have the potential to wreak havoc on human populations. Vaccines are one of many tools we use and are particularly effective as they work to prevent severe infection by a pathogen. With the advent of the COVID-19 pandemic, the first mRNA vaccines have been approved for human use with great success, opening the door to a new era of vaccinology. mRNA vaccinology can allow for the production of a wider array of vaccines that serve to protect against all kinds of pathogens, potentially allowing for better protection than ever seen before.

two centuries later? Microbial genomics and Propionibacteria acnes. The Journal of investigative dermatology, 133(9), 2141–2142. https://doi. org/10.1038/jid.2013.260 The College of Physicians of Philadelphia. (n.d.). Different types of vaccines. History of Vaccines. Retrieved September 14, 2021, from https://www.historyofvaccines.org/content/articles/ different-types-vaccines. Verbeke, R., Lentacker, I., De Smedt, S. C., & Dewitte, H. (2019). Three decades of messenger RNA vaccine development. Nano Today, 28, 100766–. https:// doi.org/10.1016/j.nantod.2019.100766 Vetter, V., Denizer, G., Friedland, L. R., Krishnan, J., & Shapiro, M. (2018). Understanding modern-day vaccines: what you need to know. Annals of Medicine (Helsinki), 50(2), 110–120. https://doi.org/10.1080/07 853890.2017.1407035

References Centers for Disease Control and Prevention. (2021, February 20). History of smallpox. Centers for Disease Control and Prevention. Retrieved September 14, 2021, from https://www.cdc.gov/smallpox/history/history.html. Clem A. S. (2011). Fundamentals of vaccine immunology. Journal of global infectious diseases, 3(1), 73–78. https://doi.org/10.4103/0974-777X.77299 Gina Kolata. (2021). Kati Kariko Helped Shield the World From the Coronavirus. The New York Times. Hilleman, M. R. (2000). Vaccines in historic evolution and perspective: a narrative of vaccine discoveries. Vaccine, 18(15), 1436–1447. https://doi. org/10.1016/S0264-410X(99)00434-X Janeway, C. (2001). Immunobiology 5 : the immune system in health and disease. Garland Pub. Lee, K., Kim, M., Seo, Y., & Lee, H. (2018). Development of mRNA vaccines and their prophylactic and therapeutic applications. Nano Research, 11(10), 5173–5192. https://doi.org/10.1007/s12274-018-2095-8 Minor, P. D. (2015). Live attenuated vaccines: Historical successes and current challenges. Virology (New York, N.Y.), 479, 379–392. https://doi. org/10.1016/j.virol.2015.03.032 Office of Infectious Disease and HIV/AIDS Policy (OIDP). (2021, May 4). Vaccine types. HHS.gov. Retrieved September 14, 2021, from https://www.hhs.gov/immunization/basics/ types/index.html. Plotkin S. A. (2009). Vaccines: the fourth century. Clinical and vaccine immunology : CVI, 16(12), 1709–1719. https://doi.org/10.1128/CVI.00290-09 Segre J. A. (2013). What does it take to satisfy Koch's postulates

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A (co-)End Approach to Day Convolution BY VARUN MALLADI ’23 Cover: Spheres are particularly well behaved under the smash product, the construction of which is a key application of Day Convolution. The smash product of two spheres is another sphere, and in particular the sphere spectrum emerges as the initial object in the symmetric monoidal category of spectra under the smash product of spectra. Image Source: Rocchini 2012, Wikimedia Commons

A technical nuisance of, say, the category of sequential spectra is that, unlike the stable homotopy category, it is not closed symmetric monoidal. It is sometimes useful to have this structure, and this motivates various other categories of spectra which all induce the same stable homotopy category, including symmetric and orthogonal spectra. While a smash product operation that exhibits this structure can be constructed explicitly, there is perhaps a more intuitive construction of the smash product as a Day convolution on pre-excisive functors. Presently, we develop the basic theory of Day convolution. We approach this by first discussing (co)ends, which afford an elegant expression of Day convolution.

(co)Limits and (co)Ends The most common definition of a (categorytheoretic) limit, and the most intuitive perspective in many use cases, is the universal cone over a particular diagram. We begin by unraveling this 158

definition into a definition via equalizers. From this perspective, it becomes clear that limits are a special case of a more general construction known as ends. These are powerful tools— in our case, their associated calculus, the “(co) end calculus,” will enable us to elegantly prove powerful statements. There is of course a dual notion of a coend, but for the sake of motivation we approach the (co)end calculus via limits. Corollary 1.1. The limit object of a presheaf F is the set of all cones with respect to F. We begin with the following approach in Mac Lane’s “Categories for the Working Mathematician” (p. 105). Consider a presheaf F over the category of ordinals N, whose morphisms are the standard ordering. Then, we have the following diagram:

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the morphisms are reversed because the source of F is the opposite category of N. But as it is, this diagram may not necessarily commute, i.e., not every triplet may constitute a cone (the above diagram only indicated the source and targets of maps). From this we are led to consider cones as specific “pieces” of the maps:

longer makes sense to index the products over the set morphisms; we need to somehow index over the space of morphisms. It makes sense to start by reworking the codomain. Notice that:

where: We want to express the limit in terms of this map, but first we will generalize. For a general presheaf Cop → Set, the codomain we are actually interested in is the product of all images of morphisms in Cop. For otherwise there couldn’t possibly be a cone. We adopt the convention that given a morphism f, write s(f) for the source object and t(f) for the target object. We can then express the above more generally as a map:

Recall that a cone is a collection of maps pj for each j ∈ Cop such that for all morphisms f : j → k the following diagram commutes:

(Here, A ∈ Set) This is the condition that F(f)∘pj = pk. By the definition of a product, every map pj factors uniquely through ∏j F(j) → A. We can consider the maps pj as maps out of the product, rather than out of A. (The maps out of the product are the canonical projections. At the risk of abusing notation for transparency, we will also call these maps pj.) We can thus consider the requirement that F(f)∘pj = pk as defining the equalizer of the parallel morphisms F(f)∘pj and pk. This is by definition the set of all cones, hence the limit of the presheaf F (cor. 1):

(By writing Mor(j) we mean the set of morphisms in the ambient category that j belongs to which have j as a source) This is the approach taken in the nLab limit article. In enriched category theory, the set of morphisms is an object (not just a set, for instance) in the category we are enriching over. So, we are motivated to rework the equalizer above— it no SPRING AND SUMMER 2021

Here we consider Cop(j,k) as a set, and so F(k)Cop(j,k) as a set has precisely as many elements as there are morphisms in Cop from j to k. The upshot of this phrasing is that it suggests a generalization to the case where Cop is V-enriched (hence our notation). For then Cop(j,k) ∈ V, and, if we view V as enriched over itself, F(k)Cop(j,k) ∈ V as well. Now we need to rework the maps we are equalizing. First let’s consider the map F(f)∘pj. There isn’t anything wrong with the projection map, even in our new codomain we still have a projection map, though it is of course defined slightly differently (in particular by postcomposing with the isomorphism above). At the risk of abusing notation for the sake of transparency, we will still call the projection pj. We do, however, need to redefine F(f) in light of our new codomain. Observe that F(f) is equivalently a map:

The adjunct of this map:

is of the form we desire and captures the same information. Hence the analog to the map ∏f∈Mor(j) F(f)∘pj is:

Now let’s consider the other map we are equalizing, pk. This map contains the information of the projection, as well as only being defined for k that were targets of morphisms in Cop. The set of k that are targets of morphisms are in bijection with maps of the form:

(Here, the second map is the adjunct of the identity on F(k), hence our factoring through * serves to indicate we are sending j → k to the 159

identity on F(k), which is necessary for our bijection). The adjunct of this map:

is of the form we want and contains the same information. Hence the analog to the map ∏f∈Mor(j) pt(f) is:

A limit is thus the equalizer:

But observe that given a pair (j,k), we defined λj,k to have source F(j) and pj,k to have source F(k). By having the domain of the parallel morphisms being indexed only over the product all F(j), we are only really considering the j which are both the source and target of at least one (perhaps seperate) morphism. We thus manifest ends as a generalization of limits that preserves this nuance, following the ends article from the nLab: Definition 2. For V a symmetric monoidal category, C a V-enriched category and F : Cop × C → V a V-enriched functor, the end of F is the equalizer:

with p given in components by:

and:

being the adjunct of:

Dually, we define: Definition 3. The coend of F is the coequalizer:

Example 5. In the above, F is a functor from Cop × C → V. Thus, if we define F such that F(c1,c2) = F'(c1) for some functor F' : Cop → V, we recover the notions of a limit and colimit:

In the spirit of consistency, limits and colimits are often written in this notation when (co)ends are involved. Example 6. What is almost immediate after unraveling definitions is the expression of natural transformations in terms of ends: given F , G : C → D,

Taking the end, this is the collection of F(c) → G(c) that are in the equalizer as above, i.e., satisfy that for each c1 → c2 there exists a commuting square of the form:

But this is equivalently a natural transformation. Since ends are universal with this property, each commuting square of the above form is in the equalizer and hence in the end. Example 7. Given a Hom functor that preserves limits in each variable separately, we have the following properties:

Notable examples of Hom functors that preserve limits are the standard Set-valued Hom and the pointed topological mapping space:

Example 8. The way of writing F hopefully makes transparent the idea of the end as the equalizer of the left and right actions encoded in F.

The (co)End Calculus with the parallel morphisms induced by the two actions of F. Remark 4. Typically, enriching over a “sufficiently nice” category V means requiring V to be symmetric monoidal. If we further assume V is closed monoidal, then V can be considered enriched over itself. Hence forth, we will assume V to by symmetric monoidal.

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We now collect several results that allow us to prove things using (co)ends. These and similarly motivated results constitute the co(end) calculus. We draw primarily from the nLab articles “ends” and “Introduction to Stable homotopy theory -- 1-2.” The particular form of Proposition 10 is due to Loregian’s “(co)End Calculus”, which is an excellent comprehensive reference for the general

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subject. Corollary 9. Any continuous functor K preserves ends, and any cocontinuous functor K' preserves coends. For instance, given a functor F : Cop × C → V and c ∈ C, v ∈ V,

Proposition 10 (Fubini’s theorem for (co)ends). Given V-enriched categories C and D, and a V-enriched functor:

if the (co)end of F exists, then:

Dually,

Proposition 11. Let F , G : C → D be functors. Write [C,D](F,G) for the set of natural transformations between them. Then:

Proposition 12. For functors S : Cop → D and T : C → D,

natural isomorphism:

Day Convolution We are motivated by the following example, a viewpoint illustrated by Campbell in their “Day Convolution Intuition” answer on Math Stack Exchange. Example 15. Given a ring R and a monoid M, we wish to extend the ring structure to R(M), the set of functions M → R of finite support. We require that R → R(M) is a ring homomorphism, and M → R(M) is a monoid homomorphism. In this way the resulting ring structure on R(M) becomes canonical. Let’s first consider a basis for R(M). We claim this is the set of em for m ∈ M, where em(x)=1 if x = m and is 0 otherwise (for instance, see Yu’s article “Vector Space of Functions from a Set to a Vector Space”). Addition is then well defined, and it remains to find a suitable multiplicative operation * that makes R(M) into a ring. But given that M → R(M) is a monoid homomorphism sending x ↦ ex, and since we can shuffle constants around the multiplication operation, we are led to define:

Lemma 13 (co-Yoneda lemma). Every V-valued presheaf F : Cop → V is a colimit of representable presheaves: In references, the standard way to define * is: Proof. But observe this is equivalent:

We call the operation * the convolution product. (The first isomorphism is by prop. 11, the second is prop. 12, the third is the tensor-hom adjunction, the fifth is the observation that y makes Cc,- redundant.) The result then follows by the enriched Yoneda lemma. ■ The following result is formally dual: Proposition 14 (Yoneda reduction) There is a

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The Day convolution we are after is the categorification of this concept. Example 16. Rather than the set of functions from a monoid M to a ring R, we are concerned with endowing a multiplicative operation to the functors from a category Cop to a category V (i.e. V-valued presheaves). By the co-Yoneda lemma (lemma 13), every V-valued presheaf F : Cop → V is a colimit of

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representable presheaves:

Thus, we can think of the set of such colimits as a “basis” for the presheaf category [Cop,V]. Since we require * to be canonically defined, we calculate

This is a very strong (and useful!) property to have. So even when we don’t have this property, we are still interested in approximating the functor F', even if it means fixing a single functor F. Kan extensions seek to do just that. There are many types of Kan extensions, which all coincide in the best-case scenario. For our purposes, we are interested in the following, taken from the Kan extension nLab article: Definition 18 (Local Kan extensions). Given a functor p : C → C', we have an induced functor p* : [C', D] → [C, D] given by precomposition by p. A left Kan extension of F along p is then a functor LanpF : [C', D] such that:

We now cover the assumptions needed to calculate as we did. First, we require C and V to be a monoidal category with respect to some tensor products ⊗C and ⊗V. We used Fubini’s theorem for coends (prop. 10) and so ⊗V needs to be continuous in each variable. Furthermore, that the coends exist at all is the assumption that V is cocomplete (the assumptions on V can be summarized by saying that V is monoidally cocomplete). The following definition is more standard, appearing for instance in the Day convolution article on the nLab. It utilizes C rather than Cop, thus switching the covariant hom for a contravariant one. The ordering is also switched, which is fine as long we stay consistent. Definition 17 (Day convolution). Let (C,⊗C,1) be a small V-enriched monoidal category. Then the Day convolution tensor product on [C, V] :

is a natural isomorphism. Perhaps more intuitively, LanpF corepresentation of Hom[C,D](F,p*(-)).

Remark 19. Def. 18 is a specific case of what are called global Kan extensions. Proposition 20. The left Kan extension is given by the coend:

Proof. It suffices to show [C', D](LanpF, G)≅[C, D] (F,p*(G)). We calculate:

is given by:

A Left Kan Extension Given a functor p : C → C', it is typically interesting to understand the extension problem, i.e., whether any functor F : C → D can be extended to a functor F' : C' → D: (The first step is ex. 6, the second step is our assumption, the third is ex. 7, the fourth is Fubini, thm. 10, along with the tensor-hom adjunction, the fifth is ex. 7 again, the sixth is Yoneda reduction, prop. 14, and the seventh is ex.

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6 again) ■

homotopy theory -- 1-2 article on the nLab.

Definition 21. For C a small V-monoidal category, its external tensor product:

References

given by:

D, A. (2016, October 22). Convolution product in monoidrings. Mathematics Stack Exchange. https://math.stackexchange. com/questions/1979827/convolution-product-in-monoid-rings.

The key result: Proposition 22. The Day convolution (def. 17) of two functors F and G is isomorphic to the left Kan extension of their external tensor product along ⊗C:

Campbell, A. (2016, February 11). Day convolution intuition. Mathematics Stack Exchange. https://math.stackexchange.com/ questions/1650786/day-convolution-intuition.

enriched Yoneda lemma. nLab. (n.d.). https://ncatlab.org/nlab/ show/enriched+Yoneda+lemma. Lane, M. S. (2010). Categories for the working mathematician. Springer. Loregian, F. (2021). (co)End Calculus. Cambridge University Press. cartesian product. nLab. (n.d.). https://ncatlab.org/nlab/show/ cartesian+product.

In other words, the Day convolution can be thought of as a left Kan extension. Proof. This is immediate by spelling out definitions:

Day convolution. nLab. (n.d.). https://ncatlab.org/nlab/show/ Day+convolution. end. nLab. (n.d.). https://ncatlab.org/nlab/show/end. Introduction to Stable homotopy theory -- 1-2. nLab. (n.d.). https://ncatlab.org/nlab/show/Introduction+to+Stable+homoto py+theory+--+1-2. Kan extension. nLab. (n.d.). https://ncatlab.org/nlab/show/ Kan+extension. limit. nLab. (n.d.). https://ncatlab.org/nlab/show/limit.

■

Set. nLab. (n.d.). https://ncatlab.org/nlab/show/Set.

Remark 23. Intuitively, we are approximating the external tensor product.

symmetric monoidal category. nLab. (n.d.). https://ncatlab.org/ nlab/show/symmetric+monoidal+category.

Corollary 24. There are natural isomorphisms:

Remark 25. The point is, the structure associated to Day convolution can be rather abstract. The external tensor product and tensor product with respect to C can oftentimes be more tractable. A particularly notable example of the usefulness of cor. 24 is in determining monoids with respect to the Day convolution. Certain functors (e.g., strong monoidal functors) arise as having the form on the right side of the natural isomorphism in cor. 24. Thus, these functors themselves can be monoids with respect to the Day convolution. A notable example is functors with smash product arising in the construction of a symmetric monoidal smash (tensor) product of spectra via full subcategory inclusions from the category of pre-excisive functors (e.g., orthogonal, symmetric spectra). For details, see the Introduction to Stable

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presheaf. nLab. (n.d.). https://ncatlab.org/nlab/show/presheaf. Rocchini. (2012, May 29). Sphere Inversion [Digital image]. Retrieved May 25, 2021, from https://commons.wikimedia.org/ wiki/File:Sphere_inversion.png Whacka. (2014, May 14). Is the convolution operation some kind of group operation? Mathematics Stack Exchange. https://math.stackexchange.com/questions/896704/ is-the convolution-operation-some-kind-of-groupoperation. Willerton, S., & Leinster, T. (2014, January 5). Ends. The n-Category Café. https://golem.ph.utexas.edu/ category/2014/01/ends.html.

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Holistic Overview and Discussion of Homosexuality and Genetics BY CHAE-GHANG JEONG, BUILDING THE MODERN MD WINNER, MEDICINE AND GENDER Cover Image Image Source: Wikimedia Commons

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In 2015, the U.S. Supreme Court ruled that same-sex marriages are protected by the 14th Amendment and promptly instigated the legalization in all fifty states. This was a triumph preceded by a long historical, scientific, and medical battle of defining and understanding homosexuality as a normal biological variation. With significant advancement in genetics research, scientists have now entered a new era to find the genetic radix of homosexual behaviour. Although we are still ways from identifying the biological and genetic underpinnings of homosexuality, there has been a striking leap of scientific advances in how different genetic factors work in a multifactorial way to affect human behaviors and features. Despite legalization and increased public awareness of homosexuality, social stigma still exists throughout the world. Consequently, several critical ethical and legal issues have been raised on the implication of handling highly private and potentially marginalizing information that revolves around genetically defining sexual orientation. Whether this genetic information should be recorded on one’s medical log is the primary subject of debate,

and several other issues may stem from it all. With a comprehensive analysis of historical, legal, and scientific backgrounds of homosexuality, this essay presents the ethical discussion of whether and how the genetic information should be shared with medical professionals in healthcare settings or even with the individuals who may require extensive and careful consultation to properly interpret and understand the genetics. The societal perception and the medical classification of homosexuality have continuously shifted over centuries of time. In the pre-historic era, there are evidences of homosexuality behavior in not only Israel where the Bible strictly forbids such activity but also Greece where it was more commonly described (Morris, 2009). Early on in history, same-sex attracted behaviours were distinguished as a mental illness from heterosexuality, which was then dubbed “a rational, or normal behaviour of humans.” Despite the lack of concrete evidence supporting the perspective, there were pervasive beliefs that such a condition was derived from a congenital defect or by external negative factors—either DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 1: Gender issues, debated in supreme court. Image Source: Wikimedia Commons

biological or social (Drescher, 2015). This view was further bolstered by not only religious but also secular affairs where the belief that homosexuality is an abnormal deviation from the normal standard was reinforced. Even up until the 19th century, homosexual behaviors were legally persecuted under the legislation, such as the sodomy law in Paragraph 175 of the German Criminal Code. Thenceforth, Sigmund Freud’s psychoanalytic theory pioneered a new explanation of homosexuality, where it should not be considered a mere medical ailment but a condition of hindered psychological development. This alternative theory allowed the overall view of the homosexual predisposition to shift from negative to neutral, albeit still considered as psychologically convertible to normality (Drescher, 2015). Previous scientific research has identified multiple biological correlates to homosexuality, including prenatal exposure to environmental immune insult and neural activation of the hypothalamic axis (Bogaert, 2020). These results generated many discussions of the contribution of environment and genetics on determining sexual orientation and how we, as a society, should view it as part of human nature. With the emergence of the modern view concerning homosexuality as a normal phenotypic variation, active debate and discussion involving medical scientists, psychologists, and lesbian, gay, bisexual, transgender, and queer or questioning (LGBTQ) advocates propelled the evolution of the medical classification of homosexuality. For example, the Diagnostic and Statistical Manual (DSM) which held homosexuality as a pathological condition for the first two editions now removed homosexuality from the manual raising the hand of the theory of normal variation (Drescher, 2015). This diversity in theories explaining the nature of homosexuality and continual modification of the interpretation is represented in the advancement of legislative changes, which will be discussed in SPRING AND SUMMER 2021

more detail in the following section. Evolving definition and classification of homosexuality concurrently influenced concerning legislation and its legal interpretations. The legislative impact of the change in the classification of homosexuality is most clearly seen in the following case of Bowers v. Hardwick. In 1982, Michael Hardwick was arrested and charged with violating Georgia’s anti-sodomy statute by engaging in oral sexual conduct with a male adult in his private bedroom (Bowers v. Hardwick, 1986). The accused man initiated legal proceedings against the Federal District Court, challenging the constitutionality of the statute as his act of homosexual sodomy had consent from both engagers. Hardwick’s protest was both fair and logical; his conduct would have been constitutionally protected in a marital setting according to Laurence Tribe, the opposing legal advocate who argued and presented the case for Attorney General Bowers. However, same-sex marriage in the United States was first legalized in 2004, which meant that before then, homosexuals had no legalized option to engage in sexual activities, as sodomy laws precluded one’s involvement in “unnatural sexual conduct” altogether. While the Supreme Court even considered the 14th Amendment and its impediment on the enforcement of the Georgia statute since the conduct took place in the privacy of the respondent’s home, the divided Court nevertheless concluded that there was no constitutional protection for acts of homosexual sodomy. The case was revisited after 17 years in Lawrence v. Texas where the Texas court overruled Bowers v. Hardwick. 14th amendment due process clause now claims that no person shall be “deprived of life, liberty, or property without due process of law,” and this would include the subject of homosexuality as freedom of one’s sexual orientation (Lawrence v. Texas, 2003). With the recognition that

" However, samesex marriage in the United States was first legalized in 2004, which meant that before then, homosexuals had no legalized option to engage in sexual activities, as sodomy laws precluded one’s involvement in 'unnatural sexual conduct' altogether."

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Figure 2: Genome-wide association study (GWAS) reveals genetic evidence, DNA. Image Source: Wikimedia Commons

"Well before the advent of such largescale genome analysis, a linkage study found that the Xq28 region of the X chromosome potentially influenced the development of male homosexuality"

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homosexuality falls rightfully under free human rights, the social stigma of homosexuality improved with the emergence of opinions that it is a normal variation. However, the significance of the legislative, social change in the view of homosexuality ultimately relates to science. The paradigm shift of homosexual behaviour as a variation, and not an ailment, redirected the doctors’ and scientists’ interest from finding a medication to what is considered a medical defect to investigating the biological source of variation. As the focus on human behavioral variation stimulates scientists to find the genetic, biological cause, numerous investigations about researching the genetic basis for homosexuality were propelled. We will look at the most recent and comprehensive study about the genetic basis of homosexuality that emerged from this paradigm shift. Recently, a large-scale genome-wide association study (GWAS) was conducted to elucidate the genetic underpinnings of sexual orientation and to explain homosexuality as a natural genetic variation. GWAS provides a bioinformatic investigative approach to associate phenotypic conditions with genetic markers in different individuals. Well before the advent of such largescale genome analysis, a linkage study found that the Xq28 region of the X chromosome potentially influenced the development of male homosexuality (Hu, 1995). However, this kind of linkage study based on genotyping requires multigenerational pedigrees and suffers from small sample sizes. GWAS effectively overcomes this limitation and provides compelling and comprehensive scientific evidence against specific phenotypes across the whole genome. The 2019 GWAS findings suggest that there are at least five genetic markers on the human genome that may statistically significantly influence sexual orientation (Ganna, 2019). The

study was based on 408,995 genomes from the UK Biobank research programme and 68,527 from the consumer-genetics private company, 23andMe. The study revealed that there are malespecific, female-specific, and combined genetic markers on the 4th, 7th, 11th, 12th, and 15th chromosomes. The researchers’ objective was to identify single-nucleotide polymorphism (SNP) in the genomes which can be associated with a difference in the group of homosexual people, which may suggest the biological factors behind the behaviour. However, the study provides more of a correlation than the actual biological link between the genetic markers and the behaviour. There are some hints that suggest that genes that are involved in sexual or hormonal regulations may further influence sexual behaviour and orientation. To exemplify, the gene linked with male baldness has been identified to affect sex hormones as well as sexual predilection. Yet the study is not readily applicable to the realworld scenario as that genetics may only explain 8-25% of the variation in homosexuality. 25% is a shred of liminal evidence on determining whether a person is born with homosexual behaviour. One of the major limitations of the study may be that those whose biological and self-identified sex do not match were not selected as the sample participants. Therefore, the analysis was incomplete with the exclusion of certain LGBTQ communities, which makes the study less widely applicable. Nonetheless, there is a great potential for the study as the future extensive examinations of the sample genomes could increase the likely impact of such genomes in the behaviour that would provide concrete evidence. For instance, scientists have now identified neural, hormonal, and environmental correlates that can affect homosexual behaviors on top of the genetic influences (Bogaert, 2020). With increasing knowledge of the biological basis of homosexuality, there will be paramount

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importance in properly dealing with such private and personal genetic data as explained at the beginning. With the increasing genetic and biological understanding of homosexuality, there must be a parallel discussion of how this private and profound information will be properly handled. There must be a collective agreement that sexual orientation is a normal variation and is a highly personal matter. As the social stigma about LGBTQ is unfortunately not yet fully eradicated from society throughout the world and is indiscreetly pervasive in the workplace, schools, and numerous daily social interactions, we may yet be in a preliminary stage to openly distribute and reveal this private information to the public. Furthermore, it must be ensured with proper regulations that these genetic records for sexual orientation will not prevent or interfere with any medical treatments. Homosexuality is a phenotypic variation of human behavior and not a potential cause of special medical conditions. If the establishment of medical records for homosexual genetic information may potentially create unnecessary bias, then we must re-envision how we think about curating and interpreting personal genetic data. Yet, scientific endeavors to further human genetics research to understand not only sexual orientation but also diseases and behaviors should be encouraged. There are numerous possibilities to utilize the results from these genetic studies to promote not only biological but anthropological appreciation of diversity

and variation in human behaviors. It would be an interesting application to track down the genetic variation of different sexual orientations similar to how ancestry and ethnicity genetic testing is currently achieving at a phenomenal rate. These kinds of genetic information will be conveyed as a form of scientific research and data where the individuals are informed by publicly available websites, such as Genetics of Sexual Behavior (geneticsexbehaviour.info), that provide the public with the concept that genetic studies provide possible correlative, not causal, relationships between genetics and human behavior. Further, it should be done cautiously so that this information does not magnify the marginalization of already marginalized groups of people. Our understanding of sexual orientation and other human behaviors is the culmination of centuries worth of active conversations, debates, and scientific and medical investigations. We have dramatically progressed from naively treating homosexuality as a pathological, illegal behaviour to embracing it as a normal human variation. Scientific research dedicated to elucidating the genetic factors that may explain homosexuality will further our understanding of how we, as humans, evolved and changed with time and may yield currently unexplored areas of human genetics. This may promote cognizant inclusion of the LGBTQ population in clinical trials for developing therapeutics as the sexual minority groups have traditionally been disproportionately misrepresented in Figure 3: LGBTQ movement. Image Source: Wikimedia Commons

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the drug development process. However, the interpretations of the scientific results should be carefully and thoroughly presented in collaboration with LGBTQ communities that may be directly affected by the findings to prevent any discrimination or segregation of those marginalized populations. This may involve the development and implementation of legislation along with venues for properly disseminating how to interpret and utilize the genetic information. The medical field must acknowledge how our understanding of sexual orientation has evolved and strive to promote a healthy conversation of science and medicine in order to better healthcare for all patients regardless of their sexual orientation or any other natural human variations. References Bogaert, A. F., & Skorska, M. N. (2020, January 8). A short review of biological research on the development of sexual orientation. Hormones and Behavior. https://www.sciencedirect.com/science/article/pii/ S0018506X19304660 Bowers v. Hardwick, 478 U.S. 186 (U.S. Supreme Court 1986). https://supreme.justia.com/cases/federal/us/478/186/ Drescher, J. (2015, December 4). Out of DSM: Depathologizing Homosexuality. Behavioral sciences (Basel, Switzerland). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4695779/ Ganna, A., Verweij, K., Nivard, M. G., Maier, R., Wedow, R., Busch, A. S., Abdellaoui, A., Guo, S., Sathirapongsasuti, J. F., 23andMe Research Team, Lichtenstein, P., Lundström, S., Långström, N., Auton, A., Harris, K. M., Beecham, G. W., Martin, E. R., Sanders, A. R., Perry, J., Neale, B. M., … Zietsch, B. P. (2019). Large-scale GWAS reveals insights into the genetic architecture of same-sex sexual behavior. Science (New York, N.Y.), 365(6456), eaat7693. https://doi.org/10.1126/science. aat7693 Hu, S., Pattatucci, A. M., Patterson, C., Li, L., Fulker, D. W., Cherny, S. S., Kruglyak, L., & Hamer, D. H. (1995). Linkage between sexual orientation and chromosome Xq28 in males but not in females. Nature genetics, 11(3), 248–256. https://doi.org/10.1038/ng1195-248 Lawrence v. Texas, 2003 (U.S. Supreme Court 2003). https://supreme.justia.com/cases/federal/us/539/558/ Morris, B. J. (2009). A brief history of lesbian, gay, bisexual and transgender social movements. https://www.apa.org/pi/lgbt/ resources/history

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COVID-19: Non-Equitable Healthcare and the Challenges of Achieving Equity BY DOYEOL KIM, BUILDING THE MODERN MD WINNER, MEDICINE AND GOVERNMENT Cover Image: The term corona was derived from the Latin word for crown, and the COVID-19 virus was first called the coronavirus for its crown-like shape. Image Source: Wikimedia Commons

Abstract One of the deadliest pandemics in history, COVID-19 is a devastating pandemic that began in late 2019. The pandemic has currently reached almost 222 million cases worldwide with 85 million of those cases in the United States, and it is also responsible for 4.5 million deaths (“WHO Coronavirus (COVID-19) Dashboard,” n.d.). Since the 1900s, achieving equitable healthcare has been an important part of medical treatment. However, with the rise of COVID-19, achieving equitable healthcare has become an even more prominent issue. The COVID-19 outbreak has shown that underpreparation for pandemics can be detrimental to society, resulting in public panic, economic decline, and especially inequitable healthcare. This study identifies and examines the challenges of achieving equitable healthcare during the COVID-19 pandemic within the U.S. The rapid spread of the pandemic led to difficulties in administering equitable healthcare due to

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inconsistent triage and lack of government control. Overall, the unpreparedness towards the pandemic was a major factor of its surge. Experts also predict that such pandemics are likely to continue occurring in periods of about every four years. As these pandemics continue to threaten humanity, it is crucial that governments and policy-makers in the U.S., as well as around the globe, consider exerting more effort into preparing for future outbreaks and developing more efficient procedures including triage to ensure that equitable healthcare is carried out effectively and consistently.

COVID-19: Non-Equitable Healthcare and the Challenges of Achieving Equity COVID-19 is an incredibly contagious virus discovered in Wuhan, China in December 2019. The World Health Organization (WHO) declared the virus a global pandemic on March 11 as the cases and deaths were increasing exponentially (“A Timeline of COVID-19 Developments in DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 1: The World Health Organization was established by the United Nations in 1948 as an international health organization. Image Source: Wikimedia Commons

2020,” n.d.). COVID-19 is an ongoing problem even today, especially since vaccines were approved for distribution only in early 2021 (“A Timeline of COVID-19 Vaccine Developments in 2021,” n.d.). The death count has climbed to almost four million globally, and many are eager to get the vaccine administered—though there are a few conflicting opinions on the efficacy of the vaccine. All in all, equitable access to healthcare, more specifically for COVID-19, is currently becoming an important issue to consider during the ongoing pandemic. By definition, health equity is the idea of giving each individual suitable treatment such that they all can at least reach a certain health standard (Oliver and Mossialos, 2004). The concept of health equity originated around the early 1800s, but only began to be implemented towards the mid to late 1900s (Yao et al., 2019). As of today, academics have defined health equity with a few fundamental principles: “equal access to healthcare, equal utilization of healthcare, and equal (or, rather, equitable) health outcomes” (Oliver and Mossialos, 2004, p. 655). However, health equity is difficult to accomplish because it has proven difficult to define equal access. Because there is no global agreement on the terms of equal access, there is an absence of a reference point for the government or policymakers in which to “judge the consistency of their healthcare” (Oliver and Mossialos, 2004, p. 655). This paper aims to identify the causes of inequitable healthcare during the COVID-19 pandemic by analyzing the failures in the U.S. pandemic plan including inconsistent triage with ventilator shortages, personal protective

equipment shortages, and government failure. This paper will conclude by suggesting improved government action in preparing for the pandemic such as increased funding for medical facilities as well as more effective policies for public control.

Results Inconsistent Triage Determining the terms of equal access requires consideration of the “health system structure (e.g. availability of financial and human resources), health care delivery (e.g. accessibility and quality of care), or health care outcomes (e.g. individual and population health) across populations'' (Yao et al. 2019, para. 6). For example, lack of available equipment can be a barrier to providing everyone with equitable care, as was in the case of insufficient ventilators for COVID-19 patients (Ranney, Griffeth, and Jha, 2021). The COVID-19 virus attacks the lungs, where it can potentially cause acute respiratory syndrome (ARDS); this is a condition where the alveoli is filled with fluid, and thus disabed from providing oxygen to the vital organs of the body (MacMillan, 2020). Ventilators, which are machines that help people with breathing difficulties by forcing air into the lungs, can help sustain COVID-19 patients that have or are developing difficulty breathing (MacMillan, 2020). However, the lack of available ventilators meant that some patients were not able to receive this care.

"This paper will conclude by suggesting improved government action in preparing for the pandemic such as increased funding for medical facilities as well as more effective policies for public control."

Because a sufficient number of ventilators were unavailable, it became necessary to prioritize some patients over others. The process in which this priority is decided based on the urgency of the patients’ condition is called triage (Chen, Shepherd, Taylor, and Marshall, 2021). With the outbreak of COVID-19, triage seemed

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to prioritize healthcare workers and other essential workers for access to ventilators when there was a ventilator shortage; this was a measure to preserve the medical professionals who could care for others. This is the multiplier effect, which states that saving healthcare workers is effectively saving more lives, as the surviving healthcare workers will go on to help a greater range of people (Chen et al., 2021). Moreover, many argued that priority access to healthcare was a reasonable reward to the healthcare workers who risked their lives to care for patients (Hull, 2020).

"Furthermore, being given priority violates the healthcare workers’ obligation to put patients first, an ethical norm inherently part of their profession."

Prioritizing healthcare workers is theoretically in line with the mentality of saving the most lives, but some studies highlight the unethical aspects of this strategy. Giving healthcare workers priority is essentially deciding someone’s worth through their instrumental value, which contradicts the social moral commitment that all lives matter equally. Furthermore, being given priority violates the healthcare workers’ obligation to put patients first, an ethical norm inherently part of their profession. As a result, this could induce public distrust towards clinicians and hospitals that adopt this policy (Chen et al., 2021). Besides just prioritizing healthcare workers, patients can be triaged through various criterias, such as by the likelihood of patient survival. Some guidelines even take into consideration non-clinical criteria such as pregnancy (Chen et al., 2021, para. 8). The criteria for triage was not very clear cut and caused an unprecedented dilemma for hospitals and healthcare workers throughout the US. PPE Shortage Aside from the shortage of ventilators, there was

also a shortage of personal protective equipment (PPE) such as face masks and medical gloves, which can be attributed to the ineffective U.S. governmental action (Cohen and Rogers, 2020). From a survey done by National Nurses United (NNU) over all 50 states of the United States, 87% of nurses reported that they had to reuse a single-use disposable mask or N95 respirator, and 27% nurses reported that they were exposed to confirmed COVID-19 patients without appropriate PPE (National Nurses United, 2020). PPE shortage is beyond just a workers’ rights issue: ill healthcare workers are not only unable to continue working, they also have the potential to spread the illness. Furthermore, ill healthcare workers combined with the increasing demand for care essentially reduces the quality and quantity of care available, therefore resulting in inequitable healthcare. This perpetuates a cycle of healthcare worker and PPE shortages and increased patient loads, further reducing quality or quantity (Cohen and Rogers, 2020). “PPE for healthcare workers is a key component of infection prevention and control; ensuring that healthcare workers are protected means more effective containment for all” (Cohen and Rogers, 2020, para. 3). There are a few reasons for the PPE shortage, and the most crucial are government failures. First of all, the PPE budgeting model used by hospitals is prone to failure (Cohen and Rogers, 2020). The Occupational Safety and Health Administration (OSHA) requires employers to provide healthcare workers with PPE for free (OSHA, 2007). This system is very counterintuitive in that from the perspective of employers, PPE becomes an expenditure or a cost rather

Figure 2: With the sharp incline in COVID-19 patients, the U.S. experienced critical shortage of key equipment including ventilators and protective equipment. Image Source: Wikimedia Commons

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Figure 3: Former President Trump signed a proclamation declaring a National Emergency Concerning the Novel Coronavirus Disease (COVID-19) Outbreak on Friday, March 13, 2020. Image Source: Wikimedia Commons

than a necessity. Employers running medical facilities are fundamentally running businesses and therefore pursue cost-minimization for profitability or revenue. As it is difficult to push the costs of unfunded mandates onto workers through lower wages or onto customers through higher prices, employers often resist these costly legal requirements. Prioritizing efficiency leads to hospitals relying on immediate production so that they do not need to maintain PPE inventories. These cost-saving measures inevitably become a problem when there is a sudden surge in the need for PPE, because immediate production might not be sufficient for the demand (Cohen and Rogers, 2020). Therefore, it is not surprising that there was a shortage of equipment once the pandemic struck. Government Failure Beyond merely inadequate budgets, the government also failed to keep the U.S. prepared. Since at least 2006, the National Institute for Occupational Safety and Health commissioned a report that there was a lack of equipment in preparation of a pandemic influenza. Furthermore, the PPE in the national stockpile was not maintained properly to prevent expiration, forcing the use of expired N95s during COVID-19 (Cohen and Rogers, 2020). Even so, the Trump administration forced policies that cut the public health budget, streamlined the pandemic response team, and started a trade war with a major supplier of PPE (Devi, 2020). Furthermore, the surge of cases with the COVID-19 virus can also be attributed to the governmental failure to actively manage the nation on the executive level. During the early months

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of the COVID-19 pandemic, then-President Donald Trump announced that the states would have primary responsibility for containing the virus, the federal government just maintaining a back-up role. Normally, with regards to public health, the federal government issues a national plan and allows for minor adjustments within states to accommodate for local circumstances. Therefore, the Trump administration’s new policy was unprecedented. The problem here is that the U.S. has 3,141 counties, and without a central authority, instructions became unclear. Some counties do not even have health departments. In some cases, authorities of counties and cities overlap. This fragmented authority resulted in varying responses to the pandemic throughout the states and even within the states. As of September 2020, 33 states had instituted that masks were mandatory, while the other states had not mandated masks as much or not even at all (Altman, 2020). In addition, the White House initially planned on imposing a gating criteria that had to be met before states could open up. However, this criteria had to be abandoned as the president pushed to open up as early as Easter, but it was just moved back once they faced the reality of the pandemic. This response troubled many Americans, and people split along partisan lines in their response to the pandemic. In a poll done in late August 2020, 90% of Democrats said that the number of COVID-19 deaths in the U.S. was unacceptable. On the other hand, a significant 57% of Republicans said it was acceptable, partly because they believed that the death count had been exaggerated (Altman, 2020).

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"In preparation for the next pandemic and onwards, the U.S. government should restore public trust in the government. With the failures of the Trump administration’s policies, public trust in the government eroded, and skepticism grew."

Due to this lack of or ineffective government control, a large portion of the public remained without protection from the virus, which then led to a surge of COVID-19 cases. The sudden, rapid increase in COVID-19 patients was also detrimental to medical facilities with insufficient equipment—both for the patients and for healthcare workers. Then the healthcare workers being exposed to COVID-19 patients without proper PPE due to shortage would then get infected themselves, and possibly spread the virus even more. The ever-increasing demand for care along with the lack of supplies then forced the U.S. to decrease some of their medical equipment exports; the US, being one of the top four global exporters, affected other countries in their shortage of equipment as well (Cohen and Rogers, 2020). Overall, it became difficult to provide equitable healthcare.

Conclusion and Limitations This study focused primarily on the reasons behind inequitable healthcare during the pandemic in the US, mainly due to underpreparedness. However, due to its focus on the US, it does not necessarily provide data on a global scale, nor does it account for other countries’ perspectives. Nonetheless, in the US, it is necessary to better prepare for future pandemics. This study has examined the destructive effects of underpreparation: inconsistent triage, underfunding of medical facilities, and lack of or ineffective government control can lead to a variety of public crises including unclear prioritization of treatment as well as resource allocation, equipment shortage, economic crisis, and most of all inequitable healthcare. Looking at pandemic history, the world has seen nine pandemics since 1700, the shortest gap between pandemics being three years and the longest being 56 years. Though not exactly cyclic, it is almost certain that pandemics will continue to occur in the future, whether that be just five years or 50 years. The question of a pandemic is not if, but when (Sandman, 2007). Even after COVID-19, pandemics are very likely to continue occurring, and so it is crucial to prepare countries for future pandemics to prevent unnecessary harm. In preparation for the next pandemic and onwards, the U.S. government should restore public trust in the government. With the failures of the Trump administration’s policies, public trust in the government eroded, and skepticism grew. In global health emergencies, public trust and faith

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in the government is necessary for maintaining public health, including “public adherence to health directives,” such as quarantine, social distancing, and wearing masks (Disparte, 2021). This also includes incorporating more effective policies regarding triage and public control. Lastly, public and private organizations should invest more in medical facilities. Not to mention the equipment shortages in hospitals, the World Health Organization (WHO) is also severely underfunded and therefore underprepared for pandemics. Greater support for research and development would also be beneficial in better preventing and battling the next pandemic (Wetter, 2021). In conclusion, the underpreparedness for the COVID-19 pandemic led to great losses from the United States, and in order to prevent the same tragedies happening again in the future with imminent pandemics, the U.S. government needs to make more effective preparations. References A Timeline of COVID-19 Developments in 2020. AJMC. (n.d.). http://www.ajmc.com/view/a-timeline-of-covid19developments-in-2020 A Timeline of COVID-19 Vaccine Developments in 2021. AJMC. (n.d.). http://www.ajmc.com/view/a-timeline-of-covid19-vaccine-developments-in-2021 Altman, D. (2020, September 14). Understanding the US failure on coronavirus-an essay by Drew Altman. The BMJ. https:// www.bmj.com/content/370/bmj.m3417 Chen, D. T., Shepherd, L., Taylor, J., & Marshall, M. F. (2021, June 24). Who will receive the last ventilator: why COVID-19 policies should not prioritise healthcare workers. Journal of Medical Ethics. https://jme.bmj.com/content/early/2021/06/25/ medethics-2021-107248 Cohen, J., & Rodgers, Y. van der M. (2020, December). Contributing factors to personal protective equipment shortages during the COVID-19 pandemic. Preventive medicine. https:// www.ncbi.nlm.nih.gov/pmc/articles/PMC7531934/ Devi, S. (2020, April). US public health budget cuts in the face of COVID-19. The Lancet Infectious Diseases. https://www. thelancet.com/journals/laninf/article/PIIS1473-3099(20)301821/fulltext Disparte, D. (2021, February 16). Preparing for the next pandemic: Early lessons from COVID-19. Brookings. https:// www.brookings.edu/research/preparing-for-the-nextpandemic-early-lessons-from-covid-19/ Department of Labor logo United States Department of Labor. Employer Payment for Personal Protective Equipment; Final Rule | Occupational Safety and Health Administration. (2007, November 15). https://www.osha.gov/laws-regs/ federalregister/2007-11-15-0 Hull, S. C. (2020, July 6). Op-Ed: Docs, Nurses Should Get

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Priority in COVID-19 Triage. Medical News. http://www. medpagetoday.com/publichealthpolicy/ethics/87418 MacMillan, C. (2020, June 2). Ventilators and COVID-19: What you Need to Know. Yale Medicine. http://www.yalemedicine. org/news/ventilators-covid-19 New survey of nurses provides frontline proof of widespread employer, government disregard for nurse and patient safety, mainly through lack of optimal PPE. National Nurses United. (2020, May 20). https://www.nationalnursesunited.org/press/ new-survey-results Oliver, A., & Mossialos, E. (2004). Equity of access to health care: outlining the foundations for action. Journal of Epidemiology & Community Health, 655–658. Ranney, M. L., Griffeth, V., & Jha, A. K. (2021, July 7). Critical Supply Shortages - The Need for Ventilators and Personal Protective Equipment During the COVID-19 Pandemic: NEJM. New England Journal of Medicine. http://www.nejm.org/doi/ full/10.1056/NEJMp2006141 Sandman, P. M. (2007, February 22). A severe pandemic is not overdue - it's not when but if. CIDRAP. https://www.cidrap. umn.edu/news-perspective/2007/02/severe-pandemic-notoverdue-its-not-when-if Wetter, S. (2021, January 13). Lessons From COVID-19 can Prepare us for the Next Pandemic. Forbes. https:// www.forbes.com/sites/coronavirusfrontlines/2021/01/13/ lessons-from-covid-19-can-prepare-us-for-the-nextpandemic/?sh=6a323e19728c WHO Coronavirus (COVID-19) Dashboard. World Health Organization. (n.d.). https://covid19.who.int/ Yao, Q., Li, X., Luo, F., Yang, L., Liu, C., & Sun, J. (2019, October 15). The historical roots and seminal research on health equity: a referenced publication year spectroscopy (RPYS) analysis. International Journal for Equity in Health. http://www.ncbi.nlm. nih.gov/pmc/articles/PMC6792226/

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Markov Chain Monte Carlo Utility in Systems Biology BY JIOH IN, BUILDING THE MODERN MD WINNER, MEDICINE AND PHILOSOPHY Cover Image: Person taking eye screening. Image Source: Flickr

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Abstract Diabetic retinopathy is a complication of diabetes that caused by damage to retinal tissue, which results in vision problems. Early diagnosis can prevent severe vision loss in diabetes patients. Diagnostic methods using artificial intelligence (AI) are being studied to supplement the accuracy of conventional human-based diagnosis, but AI-based diagnosis has sparked debates regarding medical ethics. Medical ethics of AI-based diagnosis is measured based on four pillars: justice, autonomy, beneficence, and nonmaleficence. Justice is a principle that patients should receive equal health care without economic inequalities and disparities based on social background. The AI-based diagnosis is cheaper than the conventional model (AI model: $62 per person per year vs. conventional model: $77 per person per year). Although AI-based diagnosis has disparities in accuracy (lighter-skin people: 73.0% vs darker-skin people: 60.5%), advanced algorithms could mitigate disparities (lighterskin people: 72.0% vs darker-skin people: 71.5%). Autonomy is a principle that clinicians should provide sufficient information for patients to

make decisions about their healthcare. Elaborate instructions to explain complex algorithms and data protection are necessary to ensure patient’s autonomy. Beneficence is a principle that medical services should provide benefits for patients. AIbased diagnosis (100% sensitivity and 88.4% specificity) provides benefits of higher sensitivity in accuracy than conventional methods (85.2% sensitivity and 92.0% specificity). Sensitivity is the ability to identify patients with diseases and specificity is the ability to identify people who do not have diseases. Nonmaleficence is a principle that medical service should not harm patients. To guarantee nonmaleficence, new policies and deidentification systems for data privacy should be developed. This paper aims to show that although AI technology still lacks policy and technology development to satisfy medical ethics completely, it is a promising technology to improve diabetic retinopathy diagnosis. Keywords: Diabetic retinopathy, Intelligence, medical ethics

artificial

Introduction DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Diabetic retinopathy (DR) is a complication of diabetes in the eyes. Insufficient blood supply to the light-sensitive tissue at the back of the eye, resulting from high blood pressure and high blood sugar, leads to bleeding of retina blood vessels and severe vision impairment. DR patients will be permanently blind if they are not properly treated within five years of contracting the disease (“Diabetic Retinopathy Treatment,” 2012). There are approximately 110 million people with DR and 28 million people with vision-threatening DR worldwide (Yau et al., 2012). Moreover, DR is a major cause of blindness in the United States, as 28.5% of adults with diabetes have visionthreatening DR (Zhang et al., 2013). In the later stage of DR progression, a patient is very likely to be blind. However, if DR is diagnosed at an early stage, a patient gets laser treatment called laser photocoagulation (“Diabetic Retinopathy Treatment,” 2012). Laser photocoagulation is used to seal or burn leaking blood vessels in the retina by using laser. Laser photocoagulation can prevent vision damage in approximately 50% of patients in the early stage of diabetic retinopathy (“Photocoagulation treatment of proliferative diabetic retinopathy,” 1978). If laser treatment is not available due to progressed retina impairment, a surgical method called vitreous resection can be performed. During vitreous resection, doctors use drills to clear leaking blood vessels in retina and to remove scar tissue. Unfortunately, neither laser treatment nor surgical treatment can fully prevent vision impairment because of technological limitation. Therefore, medical guidelines recommend regular DR screening to detect treatable lesions early to prevent sight loss. Despite this knowledge, only 55% of diabetic patients in the United States receive proper DR testing (Flaxman et al., 2017). Critically, systematic DR screening is not available in low-income and middleincome countries. The main reasons for the lack of screening are high testing expenses, a dearth of special ophthalmologists, and inadequate healthcare facilities (Nsiah-Kumi et al., 2009). SPRING AND SUMMER 2021

Figure 1: Eye with Diabetic Retinopathy Image Source: Flickr

In order to improve the cost-effectiveness of diabetic retinopathy screening, scientists are developing new detection methods using artificial intelligence healthcare to improve the conventional method, using ophthalmologists to analyze patient’s retina photographs. Artificial intelligence (AI) is a field of computer science that focuses primarily on solving cognitive problems associated with human intelligence (Bringsjord et al., 2018). Several AI technologies have already been adopted into various aspects of healthcare, such as diagnosis, treatment recommendation, and patient engagement (Davenport et al., 2019). Healthcare AI utilizes various algorithms such as natural language processing (NLP), AI robots, and machine learning (ML). NLP is a major AI field that mimics human linguistic structure to perform tasks such as text analysis, speech recognition, and language translation. NLP in healthcare includes classification of medical documentation and analysis of unstructured clinical patient notes. AI robots are robots with advanced learning algorithms and self-upgrading systems to perform tasks better than typical robots. AI robotics in healthcare includes surgery robots and auxiliary robots. Surgery robots can perform surgery without possible human error, and auxiliary robots can take care of restocking, bringing items, and cleaning so that nurses can focus more on patient care (Bocas et al., 2021). ML is a computational method that allows a program itself to learn from a large data set without human intervention or assistance. ML in healthcare is commonly used in medical diagnosis, mental healthcare, and new medicine development. AI in healthcare generally employs deep learning (DL) algorithms to train with large medical data sets. DL is a subfield of ML that implements neural networks to learn features in data (Yu et al., 2018). For diabetic retinopathy, deep learning algorithms can be trained with image data of the retina that is collected with a digital camera. Although AI technology has enormous potential to boost the accuracy and efficiency of DR detection, this powerful innovation creates a novel set of medical ethical issues.

"If laser treatment is not available due to progressed retina impairment, a surgical method called vitreous resection can be performed. During vitreous resection, doctors use drills to clear leaking blood vessels in retina and to remove scar tissue. Unfortunately, neither laser treatment nor surgical treatment can fully prevent vision impairment because of technological limitation."

Medical ethics is a branch of ethics in the medical field which analyzes medical practices and related research. Medical ethics consists of four 177

Figure 2: Relationship between machine learning and deep learning in Artificial Intelligence field. Image Source: Wikimedia Commons

"Justice in medical ethics is the principle that all groups in society should have equal access to the burdens and benefits of medical services and treatments."

basic principles: justice, autonomy, beneficence, and non-maleficence. The principle of justice is that medical services should equally distribute benefits, risks, and costs to patients. Autonomy is the right of patients to make medical decisions themselves. Autonomy also involves the obligations of doctors to protect patient’s privacy, disclose medical information, and guarantee transparency. The principle of beneficence obliges physicians to use medicine for good. Finally, non-maleficence is the opposite principle that medicine should not use on purpose to harm people (Jahn, 2011). This paper aims to measure medical ethics in AI technology for DR screening in terms of these four basic principles.

Justice of AI Screenings Justice in medical ethics is the principle that all groups in society should have equal access

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to the burdens and benefits of medical services and treatments. It is critical in health care it ensures that patients do not undergo unfair medical services due to their factors including socioeconomic status, race, gender, and religion. Justice in the use of AI in DR diagnosis is measured in terms of cost-effectiveness and disparities in accessibility and screening results among patient's race, gender, and socioeconomic status (Vujosevic et al. , 2020). The costeffectiveness of conventional DR diagnosis and AI-based DR diagnosis must be compared to identify the most “high cost-effective” method. High cost-effectiveness means that more effective and more accessible DR diagnosis is available at a low cost; as such, cost-effective screening is a more equitable diagnosis for both patients and hospitals (Russell et al., 1996). For

conventional

screening,

special

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ophthalmologists analyze digital fundus photographs of a patient's retinas for disease diagnosis. Several European researchers investigated the cost-effectiveness of this humanbased detection method by manipulating the screening interval (Scanlon, 2017). Researchers concluded that DR at first eye examination is not cost-effective in European countries; but they also suggested the potential error because they did not differentiate patients into low risk and high risk groups based on disease progression (Jones et al., 2012; Agardh et al., 2011; Looker et al., 2013). On the other hand, several researchers analyzed the cost-effectiveness of DL-based DR detection methods. One team performed research analyzing the cost-effectiveness of autonomous AI screening for children with type 1 diabetes (T1D) and type 2 diabetes (T2D). They compared the cost-effectiveness between AI and standard screening strategies for DR patients using medical data between 1994 to 2019. In terms of cost, they found that the mean patient payment for AI screening ($8.52 for T1D and $10.85 for T2D) was higher than conventional screening ($7.91 for T1D and $8.29 for T2D). However, when patient adherence to DR screening increased above 23%, the AI option showed a lower mean payment than the conventional option. In other words, though AI screening is more expensive upfront, it is cheaper in the long run. (Wolf et al., 2020). Other research conducted in Singapore evaluated the cost-effectiveness of AI detection methods. The researchers compared three DR screening models of human assessment, semiautomated deep learning model before human assessment for confirmatory diagnosis, and a fully-automated deep learning model. The least expensive model was the semi-automated deep learning model, with an annual cost of $62 per person per year. The most expensive model was the conventional model, with an annual cost of $77 per person per year. The authors estimated potential annual cost savings for Singapore at about $15 million when the semi-automated DL model is applied in ophthalmology (Xie et al., 2020). Both studies numerically demonstrate that DR diagnosis using AI reduces economic burden than a conventional diagnosis from children to older adults around the world. Furthermore, evaluating justice in the screening of DR patients through a social lens is vital because diabetic patients of different ethnicity, socioeconomic status, and gender have had different levels of accessibility to DR screenings and susceptibility to DR (Graham-Rowe et al., 2016). Conventional screening methods have

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considerable disparities depending on the patient's background. A study investigating the differences in rates of receiving DR screenings based on race and ethnic background showed that white people are more likely than African Americans, Latin Americans, Native Americans, Asian Americans, and Pacific Islanders to receive DR screenings (Fathy et al., 2016; "Diabetes & women's health across the life stages", 2001). A study on youths also indicated that racial minorities in the United States were less likely to have a DR examination but were more likely to have DR. Moreover, minority youths from families with low household income, medicaid, and low parental education levels were less likely to get DR examinations (Thomas et al., 2021). In regard to gender differences, interestingly, women are more likely to have DR screenings than men. However, despite the higher rate of screening among women, older women are more likely than older men to have a visual impairment (women 19.9% vs men 9.9%) (Fathy et al., 2016; "Diabetes & women's health across the life stages", 2001). In thinking about AI solutions, it is necessary to evaluate whether disparities in DR screenings can be addressed by AI technology. AI in DR screening commonly utilizes ML algorithms to perform accurate diagnosis. However, the performance of ML algorithms varies depending on the type, quality, and amount of data to be trained. An empirical study demonstrated that ML algorithms might provide unequal prediction of outcomes based on race, gender, and socioeconomic status (Chen et al., 2019). Several pieces of research provide evaluations of possible algorithmic disparities of AI-based DR screening and possible AI algorithms to mitigate disparities. Although AI technology in DR screening can have disparities based on ethnicity, it can be improved. One study compared the accuracy of DR diagnosis for fundus images of different skin colors. Researchers trained AI with the Kaggle EyePACS dataset, eye image dataset provided by an online community of data scientists and machine learning practitioners, with diverse ethnicity and manipulated a dataset to train DL algorithms with an imbalanced ethnicity. The results showed that AI screening with traditional DL algorithms had higher accuracy for lighterskin people than darker-skin people in AI performance across protected subpopulations. However, they also suggested that different DL algorithms called novel generative methods to reduce disparities. In this case, the accuracy for lighter skin was 72.0% and for darker skin was 71.5% (Burlina et al., 2021). This research

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demonstrates that advanced AI algorithms can mitigate racial discrimination in DR screening accuracy.

Autonomy of AI screenings

"Clinicians should educate the patient about which type of algorithm is used, what kind of data is used for input, and what are the possible biases and errors in the result. The incomplete explanation of AI algorithms in DR screening can lead to distrust of the diagnostic result"

In medical practice, autonomy is the right of all individuals to make informed decisions about their medical care based on sufficient information provided by a doctor. Doctors are responsible for protecting privacy, disclosing medical information, and providing high reliability (London, 2019). In AI healthcare, it is important to discuss autonomy because it is highly related to the transparency of AI algorithms and input data sets. Patients have a right to learn the complexities of AI algorithms used in DR diagnosis. Clinicians should educate the patient about which type of algorithm is used, what kind of data is used for input, and what are the possible biases and errors in the result. The incomplete explanation of AI algorithms in DR screening can lead to distrust of the diagnostic result, so people will refuse to use the AI screening. which results in slower results and causes late-stage treatment, which can result in vision loss. This lack of knowledge can also lead to confusion among clinicians, as it is difficult to determine that they need to disclose that they cannot fully understand the diagnosis results of AI. Therefore, it is challenging to determine the degree of transparency of complex AI such as what circumstances or to what extent the doctor should inform the patient that AI is in use (Gerke et al., 2020). In addition, doctors are obliged to disclose data used for diagnosis to the extent they are not infringing on a patient's privacy. The safety and reliability of data are required to guarantee autonomy in decision-making processes. It is critical to consider how the patient's medical records and retina photographs are being used in AI screenings. Since developers want to improve the accuracy of AI, medical data sharing is becoming more common between developers and healthcare services, who first need to gain consent from patients regarding the use of their data for commercial purposes (Maaloee, 2019). Cybersecurity problems such as the hacking of iris data on retina photographs can occur during data transfers. Hackers can use retina photographs to bypass multiple platforms such as private phones, safes, and houses. Moreover, doctors should inform the steps of data processing on how raw medical data is processed to be trained by AI to the patients (Gerke et al., 2020; Beil et al., 2019). Doctors are also responsible for disclosing which categories of data were used and what degree of data was used to train AI to the patients. Doctors

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also have to consider how the algorithm should be updated if the patients claim that they no longer want their eye photographs to be used for AI training (Maaloee, 2019). Therefore, DR screenings using AI currently have several potential challenges in clearly explaining medical information to patients and guaranteeing data safety thus, violating the autonomy of patients. However, when appropriate policies and regulations are made to resolve the potential problems discussed in the paragraph, doctors can use AI technology while also being able to provide sufficient transparency in DR screenings.

Beneficence & Non-maleficence of AI Screenings Beneficence and non-maleficence are related principles in medical ethics. Beneficence involves the benefits of medical treatments for patients, while non-maleficence is a principle of not using medicine to harm patients (Bosslet et al., 2015). Balancing the benefits and the risk of AI technology in DR screening is a critical issue in deciding if AI technologies should be implemented. DR screening benefits from AI because it improves the accuracy of diagnosis and reducing disparities by patients’ backgrounds. On the other hand, Non-maleficence of the use of AI in DR screening involves cybersecurity and privacy problems of data sets. AI technology in DR detection can provide benefits to patients through high accuracy. According to the research based on data from EyePACS, the largest United States screening program providing dataset of eye screening, in the United States and three eye hospitals in India, ML algorithms perform effectively for detecting DR ("Ethics - Definitions and approaches", 2009). Other research from India compared the sensitivity and specificity between DR detection using offline AI systems and DR detection performed by ophthalmologists. The AI system in diagnosis had 100% sensitivity and 88.4% specificity, while the human-based system in diagnosis had 85.2% sensitivity and 92.0% specificity (Voets et al., 2019). This research demonstrates that AI technology can provide reliable DR diagnosis with high sensitivity and specificity for patients. More developments in AI algorithms in the future benefit patients to get DR diagnosis results with high accuracy. On the other hand, AI technology in DR screening has potential risks in data privacy problems that can violate non-maleficence ("Ethics - Definitions and approaches", 2009). AI developers require large amounts of retina datasets to improve the accuracy of AI algorithms. More detailed data is also needed to address DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

algorithmic biases in screening results. Some patients may be concerned that this collection may violate their privacy (Natarajan et al., 2019). Survey data shows that 75 percent of healthcare insiders are concerned about AI violating the privacy of patient data. However, 86 percent of respondents said new policies for AI healthcare are taking steps to resolve privacy problems. For example, the Health Insurance Portability and Accountability Act (HIPPA) privacy rule defines the regulations to balance personal privacy and access to health information for scientific use. The rule explains the criteria when health information is protected by law and how much personal data will be used on AI training (Price et al., 2019). Moreover, scientists are developing modern clinical de-identification systems to prevent the potential of privacy violation in medical data. De-identification systems using DL algorithms removed 97-99% of personally identifying information (Hartman et al., 2020). Therefore, government, federal legislators, scientific communities, and healthcare workers need to collaborate closely to prevent privacy violations by implementing policies and deidentification systems.

Conclusion In summary, AI technology can improve the accuracy of DR detection and mitigate the disparities in screening accessibilities and susceptibility to DR. However, transparency and privacy issues of AI screenings need to be addressed with proper regulations and further technological improvements. This analysis shows that AI technology still lacks policy and technology development to satisfy medical ethics completely, but it is a promising technology to improve DR diagnosis. There limitations to the analysis presented in this paper. The disparity of DR screening results and accessibilities based on gender provide contradicting conclusions that women are more likely to access DR screenings but are more likely to get DR. Despite the limitation, this is valuable in light of addressing that sexual disparities in DR screenings are considerable and should be resolved by using AI. Moreover, the research utilized to analyze beneficence of AI technology in DR detection was only performed in advanced countries with high quality healthcare services. Since developing countries have different economic environments and lack awareness of DR in citizens, the accuracy of AI screenings can have different results in developing countries. Therefore, future research should be conducted in different economic settings to collect sufficient

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Cultural, Regional Diets and Understanding Cancer Distribution BY JULIANNA LIAN, BUILDING THE MODERN MD WINNER, MEDICINE AND ANTHROPOLOGY Cover Image: Map of the world. Image Source: Wikimedia Commons

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Abstract Cancer is a leading cause of death worldwide, and incidence rates are projected to increase (Sung et al., 2021). While normal cells display homeostatic renewal, regulated by growth factors and bodily cues, cancer cell growth is unregulated. Without repair mechanisms, cells accumulate dangerous genetic instability (Hanahan and Weinberg, 2011). Cancers vary greatly among individuals and even in an individual’s own cancerous cells. Thus, it can be difficult to identify causes, predict patterns, and treat. The future is hopeful with the discovery of promising chemical, genetic, and immunotherapeutic treatments, but preventing cancer remains at the forefront of battling the disease. Primary prevention is the reduction of cancer risk factors before precancerous or cancerous condition. Diet is one targetable factor. Though less restricted by geographical resources today, diet still differs between cultures and regions, and certain cancer statistics parallel this variety. This review examines correlations between cultural diets and cancer distribution.

Cancers occurring in the gastrointestinal tract and breast are of particular focus, with additional comparisons between populations and their emigrated counterparts. Cancer incidence rates and nutritional patterns observed in East Asia, South Asia, and North America and Europe constitute the bulk of this review as these populations’ dietary correlations to cancer risk are among the most well-studied. The implications of the expansion of Western diets on changing cancer statistics are discussed alongside obesity and increased cancer risk. Recognizing the role of nutrition in amplifying or diminishing risk can improve treatment and intervention techniques and help identify lifestyle changes that individuals can make.

Introduction Cancer is a disease characterized by the uncontrolled division of cells that progress by acquiring malignancy through random mutation and phenotypic changes. Lacking or overloading genetic repair mechanisms, cancer DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

cells are control-signal resistant, antiapoptotic, and resistant to senescence. In contrast to more localized benign character, a hallmark of malignancy is metastasis (Hanahan and Weinberg, 2011). Though there are similarities in all cancers, cancers vary greatly among individuals and even within the cells of individuals. Development of prevention methods and therapies are major areas of research as cancer incidence and prevalence rates increase worldwide (Sung et al., 2021). Alongside developments in advanced procedures, immunotherapy, and the discovery of new compounds, prevention and early detection of risk factors can avoid or maximize the treatability of cancer. In fact, a recent analysis of adults over 30 estimates that 42.0% of cancer incidences and 45.1% of deaths result from lifestyle, which includes nutrition, activity, and excessive, frequent exposure to certain carcinogens (Islami et al., 2017). Other studies have highlighted modifiable lifestyle risks, like exercise, alcohol consumption, and nutrition, correlated with the development of breast cancer (Cathcart-Rake et al., 2018; Harvie et al., 2015), pancreatic cancer (Midha et al., 2016), and colorectal cancer (Aleksandrova et al., 2021), among others. In particular, dietary patterns are one major emphasis of the growing interest in lifestyle and cancer risk. Though the relationship and its direct or indirect mechanisms are still unclear, a correlation exists between cancer and certain eating habits: correlations between cancer risk and refined sugars, low fiber, red meat, and cruciferous vegetables are of the most wellstudied dietary relationships (Donaldson, 2004). These nutritional patterns often vary by region and culture; certain cancer statistics parallel these geographical distributions. Often, this relationship has been explored in cancers of the gastrointestinal tract and associated metastatic sites, but the research has been broadened to other cancers including cancer of the lung (Fabricius and Lange, 2003) and prostate (Fabiani et al., 2016). Recognizing the implications of nutrition by examining the patterns of various cultural diets can identify lifestyle changes that reduce the risk for cancer.

Gastrointestinal Cancers Carcinogens can be organ-specific, concentrating in certain tissues: ingested aflatoxins, a family of mutagenic and carcinogenic fungal toxins, can concentrate in the liver for detoxification and filtration, and have been associated with increased incidences of liver cancer (Barrett, 2005). There is also an increased occurrence of lung cancer from aspirated N-nitroso compounds like nicotine

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from tobacco smoke (Brown et al., 2003), which when activated in the body, become potent, carcinogenic DNA-alkylating agents. Certain diets can have similar carcinogenic effects as foods travel through the gastrointestinal tract; thus, these tissues are of interest in studying the relationship between nutrition and cancer risk. Major global gastrointestinal cancers include esophageal, gastric, liver, pancreatic, and colorectal cancer (Arnold et al., 2020). Gastric Cancer and East Asian Diets Gastric cancer is one of the most widely occurring and deadly cancers in the world. In 2020, the Global Cancer Observatory (GLOBOCAN) reported that 5.6% of cancer incidences and 7.7% of deaths were due to stomach cancer, the majority of which occurred in East Asian populations (Sung et al., 2021). Salt intake in countries like China, Japan, and Korea rank among the highest in the world, with much of dietary sodium coming from home-cooked meals, processed and cured seafood, soy sauce, and pickled vegetables (Anderson et al., 2015). Gancz et al. (2008) report that high-salt diets have been linked to infection by Helicobacter pylori, a gram-negative gastric bacterium. H. pylori toxins can induce tumor necrosis factor alpha and cytokines IL-1, IL-6, and IL-8 (Tang et al., 2013). Such signaling molecules produce a gastric, inflammatory response that increases the risk for cancer, in some cases, by allowing proliferation of aberrant cells. Tang et al. (2013) report such elevated interleukin and TNF- α levels may be linked to a TNF inducing protein (Tip-α) present in strains of H. pylori. A mutant H. pylori strain was also reported to upregulate matrix metalloproteinase 1 (Wroblewski et al., 2015), which can degrade extracellular matrices of bodily tissues allowing tumor angiogenic substances to diffuse into the bloodstream. H. pylori’s inflammatory effect has been confirmed in a comparison between the incidence rate of gastric cancer in Japan and the UK by histologically studying gastritis occurrences. Naylor et al. (2006) suggest that the main cause of heightened levels of gastritis and more severe inflammation in Japan is H. pylori infection, where gastric cancer was, at the time of the study, four times as great in occurrence in Japan as it was in the UK.

"Though the relationship and its direct or indirect mechanisms are still unclear, a correlation exists between cancer and certain eating habits: correlations between cancer risk and refined sugars, low fiber, red meat, and cruciferous vegetables are of the most well-studied dietary relationships"

However, the mechanism by which sodium concentration affects H. pylori is still unclear. Gancz et al. (2008) suggests that the gene expression of various bacterial strains can be modulated by salt concentration. Cytotoxin

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"Japanese counterparts had an incidence rate one-third as high as Japanese living in Japan, with the primary observations related to H. pylori infection."

associated gene A (Cag-A), which is found in H. pylori, has been identified as the first bacterial oncoprotein that mediates the promotion of neoplastic epithelial to mesenchymal transition (Hatakeyama, 2017), which is the conversion of epithelial cells to an abnormal phenotype characterized by invasive qualities like disrupted cell adhesion and loss of polarity (Roche, 2018). Further salt concentration studies compare wild-type and Cag-A mutated H. pylori strains. Gaddy et al. (2013) determine that high-salt diets can potentiate wild-type H. pylori carcinogenic effects, suggesting Cag-A implications in cancer, and hypothesizing salt-upregulated expression of Cag-A. The elevated incidences of gastric cancer in East Asian populations have since been framed in the context of regional diets: Japan (Wang et al., 2009), China (Zhang and Zhang, 2009), Korea (Shin et al., 2015). The cultural diet’s correlation to cancer distribution is evident in cross-regional studies. In a review on gastric cancer incidences in Japanese ancestry living in Hawaii compared to Japan, Nomura et al. (1995) highlight how emigrated Japanese counterparts had an incidence rate onethird as high as Japanese living in Japan, with the primary observations related to H. pylori infection. Kolonel et al. (1981) also examined the dietary differences between the two regions, noting that the Hawaiian Japanese population had lower incidences of gastric cancer than did their counterparts in Japan. Other publications studying cancer incidence among the two populations have observed similar contrasts in stomach and other gastrointestinal cancer incidence, likely due to the adoption of new lifestyles (Galanis et al., 1998; Hirohata & Kono,

1997; Maskarinec & Noh, 2004). Additionally, Hawaiian Japanese populations observed a similar incidence of breast cancer in Caucasian populations in the United States, which was slightly higher relative to Japanese living in Japan; (Goodman, 1991; Maskarinec and Noh, 2004), possibly as a result of increased meat, fat, and dairy consumption (Nomura et al., 1978) as opposed to the high-sodium, leafy greens, fruits, and fish diet of Japan (Hirose et al., 2003). Alleged protective agents common to East Asian culture have also been studied, but such compounds and their mechanism of action warrant continued research: green tea has demonstrated potential in lowering risk for stomach cancer, but effects are still unclear (Hou et al., 2013; Huang et al., 2017); a variety of spices common in folk medicine have also shown protective promise, standalone and as adjuvants (Zheng et al., 2016). Colorectal Cancer and South Asian Diets Colorectal cancer affects the colon and rectum. GLOBOCAN reports that colorectal cancer accounts for 10.0% of cancer incidences and 9.4% of cancer deaths (Sung et al., 2021). Smoked or barbecued red meat, like beef, can contain polyaromatic hydrocarbons: carcinogenic compounds that can induce the secretion of inflammatory cytokines IL-1, IL-8, and IL-12, and subsequent activation of tumor-proliferating factors (Goulaouic et al., 2009). Additionally, it has been established that nitrites and nitrates added during the processing of red meat can be converted to carcinogenic N-nitroso compounds during digestion (Scanlan, 1983). Though varying greatly by subregions, South Asian diets

Figure 1: Micrograph of gastritis with H. pylori. Image Source: Wikimedia Commons

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have consistently reported some of the world’s lowest meat consumption rates (Vranken et al., 2014). In addition, many South Asian diets also consist of leafy vegetables and fruits rich in fiber, antioxidants, and other nutrients that have been associated with a reduced risk of colorectal cancer (Center et al., 2009; Giovannucci 1994). Studies examining South Asian populations living in the UK (Hebbar et al., 2012) and the United States (Goggins and Wong, 2009) find lower incidence rates of colorectal cancer, which may be related to the maintenance of a low-meat, leafy green diet. De Vogel et al. (2005) suggest that chlorophyll, which is structurally similar to the red meat pigment haem, from leafy vegetables can inhibit the formation of a cytotoxic metabolite, thus reducing the risk for colon cancer; other studies published in meat and non-meat contexts have studied the pigment’s protective potential, but continued research is necessary (Frugé et al., 2019; Wang et al., 2019). Such low-meat, leafy green, South Asian diets could reduce the risk for colorectal cancer, explaining the low incidence rate in contrast to populations with opposing dietary patterns (Wong et al., 2019). Similar low colorectal cancer distribution is present in Mediterranean populations with a diet of less processed meats than Western diets, and substantial consumption of antioxidative and anti-inflammatory nutrients (Farinetti et al., 2017; Maruca et al., 2019; Mentella et al., 2019). With Western diets, which consist of high meat consumption with few leafy vegetables, colorectal cancer risk is observed to increase with strong associations to different cancer subtypes (Mehta et al., 2017). Increasing meat consumption and global expansion of Western dietary patterns alongside

sedentary behaviors have been attributed to an increase in colorectal cancer incidence rates (Center et al., 2009). In Asia, particularly East Asian demographics, the colorectal cancer trend is increasing as compounding lifestyle risks are adopted by the population (Onyoh et al., 2019; Pourhoseingholi, 2012). Thus, the correlation between such factors and cancer risk lends greater importance to understanding the implications of nutrition. Esophageal Cancer Subtypes Esophageal cancer takes the form of two broad subtypes: (1) squamous cell carcinoma (SCC), and (2) adenocarcinoma. The former is more common in developing nations while the latter is more common in more developed nations (Napier et al., 2014). Though tobacco and alcohol consumption remain the greatest risk factors for SCC (Napier et al., 2014), diets lacking in vegetables and fresh fruit are also implicated in the cancer risk (Mao et al., 2011). South African populations with diets lacking in fresh, uncontaminated vegetables and fruit have high frequencies of SCC (Hendricks and Parker, 2002). Alongside low fresh fruit and vegetable intake, risk factors for esophageal adenocarcinoma also include consumption of processed foods and red meat as well as obesity (Kubo et al., 2010). Kubo et al. (2010) identify this second subtype of esophageal cancer as significantly more prevalent among whites and males of US and European populations. These comparisons may demonstrate a correlation between the nutrient availability of different regions and the risk for different subtypes of esophageal cancer. Further understanding of cultural dietary differences and their associated, regional cancer distributions may help identify dietary patterns that increase

"Increasing meat consumption and global expansion of Western dietary patterns alongside sedentary behaviors have been attributed to an increase in colorectal cancer incidence rates "

Figure 2: N-nitrosamine (R2NN=O), chemical structure of carcinogenic nicotine-derived nitrosamine ketone from tobacco smoke as mentioned in "Gastrointestinal Cancers." Image Source: Image modified from Radack

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or reduce modifiable cancer risk.

warrant further research.

Breast Cancer and Meat Consumption

Western Diet Expansion

Breast cancer is projected to increase into 2040 if current rates are maintained, with the greatest prevalence in European and North American countries. Worldwide, female breast cancer accounts for 11.7% of cancer incidence rates and 6.9% of deaths (Sung et al., 2021). Although unclear in mechanism, risk factors for breast cancer may include high fat intake (Dandamudi et al., 2018; Kotepui, 2016). One proposed mechanism involves heterocyclic amines (HCAs)—present in meat—and HCA metabolic activation, transportation, and modification to a reactive mutagenic metabolite in the breast tissue (Snyderwine et al., 2002). Studies, primarily in US and European populations, analyzing breast cancer incidence rates and dietary patterns have identified red meat, saturated fats, and some acids as consistently correlated to breast cancer, though some results are weak and limited in significance (Bendek and Zagożdżon, 2020; Dandamudi et al., 2018). A study on Swedish women reports that no correlation exists between breast cancer risk and total fat consumption, but the authors do acknowledge there may be differential effects on risk by age, and by the types of fat present at premenopausal age (Löf et al., 2007). However, Dai et al. (2002) emphasize how such studies on breast cancer risk and meat consumption, may prove inconclusive due to inconsistent methods of preparing and cooking meat. Dai et al. (2007) report findings in a study among Chinese women, where the degree of browning of cooked meats was noted; their results suggest that high consumption of red meat, particularly well-done, may have implications on breast cancer risk. Dietary fiber studies are also limited in significance (Kotepui, 2016), but Rohan et al. (2000), among others, identify alcohol consumption as a risk, possibly through the synthesis of carcinogenic ethanol metabolites and estrogen level modulation (McDonald et al., 2014). Alongside a lack of protective nutrients, these associations may explain the elevated breast cancer incidence rate in Western populations. Emigrated Hawaiian Japanese populations showed a higher incidence of breast cancer similar to US Caucasian rates, as compared to Japanese living in Japan (Goodman, 1991), which is discussed in Section 2.1 Gastric Cancer & East Asian Diets. A study by Silva et al. (2002) also attributes the lowered incidence rate of breast cancer in South Asian populations to a similar vegetable diet by studying cancer incidences of South Asian migrant women in England. The consistent associations between cultural dietary patterns and breast cancer

The “Western” diet is characterized by high consumption of processed meals, red meat, and fatty and sweet foods, and is often paired with sedentary behaviors (Varlamov, 2016). As this dietary trend spreads globally, particularly to economically transitioning countries (Center et al., 2009), valuable insights into the effect of nutrition on cancer risk factors have been observed through changing cancer incidence rates. Risks for colon cancer, including high consumption of red meat and lack of fruits and vegetables, were previously established in Section "Colorectal Cancer & South Asian Diets." O’Keefe et al. (2015) connect the Western diet of high-fat and low-fiber to higher concentrations of bile acids, colonic fatty acids, and mucosal biomarkers. By swapping this diet with a ruralAfrican diet of low-fat and high-fiber, O’Keefe et al. (2015) report that saccharolytic fermentation, or the break down of complex carbohydrates, and butyrate production, a byproduct associated with apoptosis, cell differentiation, and antiinflammatory (Hamer et al., 2011), are increased while potentially carcinogenic secondary bile acid synthesis from primary bile acid is suppressed. The nutritional transition and its effects suggest adopting certain aspects of a more prudent dietary practice may reduce the risk for certain gastrointestinal cancers; however, such studies also imply that the expansion of the Western diet, as nations develop, may increase the prevalence of certain associated cancers. Prostate cancer accounts for 7.3% of worldwide cancer incidences (Sung et al., 2021). Fabiani et al. (2016) observe a significant positive association between transition to more Western dietary patterns and a risk for prostate cancer; they identify characteristics of Mediterranean and Western diets. In a sample of Iranian men, food items categorized as Western were associated with an increased risk for prostate cancer (Bagheri et al., 2018). Bagheri et al. (2018) identify selenium, soy, vitamins, and other nutrients as effectors of risk for prostate cancer, but the mechanism of action is unclear. Other nutrients are also cited in protective or risk functions in prostate cancer, where Western dietary patterns, as opposed to more prudent diets, have been reported to affect specific gut bacteria implicated in tumorigenesis (Matsushita et al., 2020). Obesity and Cancer The global obesity epidemic lends its origin, in

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part, to the promotion of Western diets, where tissues get accustomed to storing more calories (Vastag, 2004). Obesity is a sustained, chronic inflammatory state, where high concentrations of cytokines and other signaling molecules are produced. Most notably in liver cancer, IL-6 is implicated in the activation of signal transducer and activator of transcription 3 (STAT3), a strong tumor-promoting transcription factor, increasing aberrant hepatic cells and the risk for liver cancer (Jenks, 2010). Giovannucci (2001) identify insulin and insulin-like growth factor (IGF) as proliferators of colon cancer risk. An increased incidence of colon cancer is also observed in parallel with increasing sedentary behavior and diets consisting of high saturated fatty acids and high glycemic index (Giovannucci, 2001). Kolb et al. (2017) cite various hypotheses with regard to increased breast cancer risk, ranging from estrogen derived from adipose tissue to elevated or decreased levels of tumor-proliferative hormones. Though the linking mechanism between obesity and cancer risk varies, and is not exclusive to inflammatory pathways, malignancy is clearly implicated, thus further research into the relationship and pathways between obesity and cancer may have significant impacts on cancer treatment and prevention.

Conclusion Diets vary greatly across cultures and regions, providing valuable studies to understanding cancer distribution. Current research suggests that certain statistics are correlated with these cultural and regional, nutritional patterns. Though the relationship between certain dietary aspects remains unclear, continued research may determine the direct or indirect mechanisms by which culturally-variable nutrition may affect cancer risk. More appropriate treatment or intervention techniques may be realized. By recognizing dietary patterns that mitigate or amplify risk, individuals can improve their own diets and lifestyles.

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From Beaked Masks to Bandanas: The Evolution of PPE in the Fight Against Infectious Disease BY NATALIA PAHLAVAN, BUILDING THE MODERN MD WINNER, MEDICINE AND HISTORY Cover Image: Personal protective equipment during COVID-19 for healthcare workers. Image Source: Wikimedia Commons

Introduction The COVID-19 pandemic began in December 2019 and has since killed more than four million people globally as of July 2021. The spread of COVID-19 has generated intense interest in personal protective equipment (PPE) among healthcare workers, health officials, and the general public. PPE shortages endangered the lives of many healthcare workers, while conflicting official statements about the transmissibility of COVID-19 in the early months of the pandemic caused confusion about the efficacy of PPE, contributing to public resistance to masking guidelines and mandates. While modern readers may view these developments as unprecedented, a historical overview of the history of infectious disease and PPE reveals that humanity has encountered similar events before. A historical study of the evolving understanding of infectious disease and the changes in the design and use of PPE—

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from the bubonic plague to the present day—can offer valuable insights into how to interpret the ongoing response to the COVID-19 crisis and how to effectively prepare for the next pandemic.

Miasma Theory, Humorism, and the First Epidemics The Greek physician Hippocrates and the Roman physician Galen both documented and witnessed epidemics. Hippocrates lived through the Plague of Athens (likely measles or smallpox) that killed at least 25 percent of the city’s population between 430 B.C.E. and 427 B.C.E. (Cunha, 2005). Galen treated soldiers infected during the Antonine Plague (likely smallpox), which first reached Rome in 166 C.E. and killed approximately 10 percent of the population of the Roman Empire (Hays, 2005). Both subscribed to miasma theory and humorism, believing that miasma—“bad” or corrupted air— DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

emanating from warm environments or decaying matter caused illness by disturbing the balance of the body’s humors, or fluids (Jouanna, 2012). Though both speculated on the cause and spread of infectious disease, their primary focus was on treating ill patients by learning the unique workings of each patient’s body and prescribing a regimen that would restore humoral balance (Mattern, 2011). Miasma theory and humorism dominated Westerners’ understanding of infectious disease for more than two millennia. Yet political, religious, and medical leaders often expressed frustration when their efforts to treat infectious disease based on these theories saw little success. For instance, during the Plague of Justinian that started in 541 C.E. and spread throughout Mediterranean societies, leaders struggled to make sense of what was the first instance of the bubonic plague (Harbeck et al., 2013). Hays (2005) notes that the Hippocratic and Galenic tradition prescribed “attention to diet, rest and bathing, and watchful waiting by the physician,” adding, however, that “cases of plague would be resolved (often fatally) before any such remedies could take effect” (p. 25).

The Return of the Plague and the Birth of PPE When the bubonic plague returned to Europe in 1346, initiating the eight-year wave known as the Black Death, leaders once again expressed frustration with the Hippocratic and Galenic prescriptions for responding to the disease. One physician, John of Burgundy, lamented that “the knowledge found from Hippocrates on had now become obsolete” (as cited in Cohn, 2010, p. 10). This frustration led many practitioners to experiment with treatments, such as surgery on the buboes (black boils) that appeared on patients’ bodies (Cohn, 2010). Physicians also recommended preventative measures to stave off the plague. For instance, some prescribed carrying and sniffing nosegays— small bouquets of sweet-scented flowers—to protect against noxious vapors (Porter, 2009). Others, in what might be one of the first medieval precursors to modern PPE, suggested “covering mouths and noses with bread or sponges soaked in vinegar and rose water when near the infected” (Cohn, 2010, p. 12). The first recorded case of PPE arose in 1619, when Charles de Lorme, a physician to French royals, invented the famous “plague doctor” outfit. Below is de Lorme’s own description of the SPRING AND SUMMER 2021

ensemble, as quoted by Christian Mussap (2019): The nose [is] half a foot long, shaped like a beak, filled with perfume with only two holes, one on each side near the nostrils, but that can suffice to breathe and carry along with the air one breathes the impression of the [herbs] enclosed further along in the beak. Under the [waxed] coat we wear boots made in Moroccan leather [goat leather] from the front of the breeches in smooth skin that are attached to said boots, and a short-sleeved blouse in smooth skin, the bottom of which is tucked into the breeches. The hat and gloves are also made of the same skin . . . with spectacles over the eyes. (pp. 672673) Additionally, the plague doctor carried a cane used to establish a safe distance from which to examine the patient and probe for signs of the plague (Earnest, 2020). This design inspired other outfits that physicians used during subsequent outbreaks of the plague in the following centuries. Plague doctors in Marseilles during the epidemic of 1720, for instance, wore a similar full-body outfit, though one without the herb-filled beak (Lynteris, 2019).

The Rise of Germ Theory and the Birth of Modern PPE

"In the 1540s, the Italian physician Girolamo Fracastoro expanded on this hypothesis, proposing that infectious diseases could be spread through direct contact, surfaces, and the air."

Germ theory, the theory that microorganisms are responsible for infectious disease, gradually started to replace miasma theory in the late 19th century. Intriguingly, this theory extends as far back as ancient Greece and pre-imperial Rome (Nutton, 1983). The Latin scholar Varro, for example, suggested in the 1st century B.C.E. that swamps and marshes produced small, invisible creatures that, when inhaled, caused disease (Nutton, 1983). Galen also wrote about “seeds of disease” that he suggested might be responsible for a patient’s relapse (Nutton, 1983). In the 1540s, the Italian physician Girolamo Fracastoro expanded on this hypothesis, proposing that infectious diseases could be spread through direct contact, surfaces, and the air. However, Fracastoro believed that inanimate “seedlets of contagion,” not living creatures, were the cause of contagion (Nutton, 1990). In the 1660s, Robert Hooke first identified cellular microorganisms using a microscope with 50× magnification, and in the next decade Antoni von Leeuwenhoek identified bacteria with microscopes capable of at least 250× magnification (Smith, 2012). John Snow’s 195

Figure 1: A plague doctor. Image Source: Wikimedia Commons

"Germ theory’s insights generated a focus on medical hygiene that sparked the creation of modern PPE."

Figure 1: St. Sebastian pleading for the life of an afflicted gravedigger during the 7th-century Plague of Justinian. Image Source: Wikimedia Commons

tracking of the spread of cholera in London in 1854 also challenged the validity of miasma theory. Snow demonstrated that cholera spread through the water supply rather than corrupted air and proposed that a cell might be responsible for the disease (Tulchinsky, 2018). The work of Louis Pasteur and others further advanced the germ theory of disease. After demonstrating that microorganisms catalyzed the processes of fermentation and food spoilage, Pasteur investigated the connection between bacteria and disease and showed that heating liquids or objects known to contain microbes could kill them (Smith, 2012). Pasteur’s work influenced Joseph Lister, a British surgeon, who in 1867 used carbolic acid to prevent the infection of wounds (Smith, 2012). Several years later, the Prussian physician Robert Koch was the first to definitively prove the link between a bacterium (Bacillus anthracis) and an illness (anthrax) (Blevins & Bronze, 2010). Germ theory’s insights generated a focus on medical hygiene that sparked the creation of modern PPE. In 1889, surgeon William Halsted commissioned the Goodyear Rubber Company to develop two pairs of gloves for the nurse Caroline Hampton, who complained about the pain caused by the harsh chemicals used in the pre-surgical scrubbing regimen (Lee, 2019). Some physicians had used gloves for medical purposes in the past, but practitioners had feared that gloves might reduce manual dexterity. Hampton and her fellow nurses at Johns Hopkins Hospital,

however, quickly adapted to the use of gloves and came to prefer them (Lee, 2019). The end of the 19th century also saw the development of medical face masks. In 1897, Carl Flügge showed that human respiratory droplets could carry infectious bacteria (Strasser & Schlich, 2020). This finding motivated his collaborator, the surgeon Jan Mikulicz-Radecki, to design a medical face mask to wear during procedures. In Mikulicz-Radecki’s words, the mask comprised “a piece of gauze tied by two strings to the cap, and sweeping across the face so as to cover the nose and mouth and beard” (as cited in Strasser & Schlich, 2020, p. 19). As with the introduction of surgical gloves, some physicians initially opposed the adoption of face masks and sterile medical attire. Many physicians took pride in the messiness of their work and were reluctant to give up their “‘blood and pus’ soaked coats” (as cited in O’Donnell et al., 2020). Nevertheless, mask-wearing among physicians became more commonplace through the early 20th century, especially as studies in the 1910s proved that gauze masks reduced the spread of infectious disease (Spooner, 1967).

The Use of Modern PPE Against Infectious Disease The adoption of masks in the West made an impression on Wu Lien-the, a Chinese-born physician trained at Cambridge. When the Manchurian Plague (caused by the pneumonic plague) erupted in 1910, the Chinese imperial court appointed Wu to help contain it (Lynteris, 2019). While many experts believed that fleas

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Figure 2: Bacteria as seen by Leeuwehoek. Image Source: Wikimedia Commons

transmitted the pneumonic plague (as with the bubonic plague), Wu suspected that the disease spread through airborne transmission and invented a multi-layered “anti-plague” mask made of cotton, gauze, and wool to combat it (Lynteris, 2019). The local population embraced Wu’s mask, which was produced in large numbers for wide distribution (Conti, 2020). Given that the pneumonic plague killed nearly everyone who contracted it, Wu’s anti-mask plague mask likely saved many lives, inspiring the use of masks during subsequent outbreaks of infectious disease. During the Spanish flu pandemic of 1918-1919, many localities in the United States—in addition to banning public gatherings, closing schools and businesses, imposing quarantines, and conducting contact tracing—urged or required residents to don face masks in public (Tognotti, 2003). In San Francisco, for example, residents could receive a fine of five dollars for not wearing a mask. While the mask mandate, among other measures, helped reduce the number of flurelated deaths in the city, it was also controversial,

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prompting the formation of an “Anti-Mask League” (Forbes, 2021). Statements by public authorities contributed to skepticism about the effectiveness of masks. For instance, a report from 1919 by the Surgeon General of the U.S. Navy stated that while it may be “good practice to require those who visit, examine, or wait upon the sick to wear masks,” a broad mask mandate was ill-advised: No evidence was presented which would justify compelling persons at large to wear masks during an epidemic. . . . Masks of improper design, made of wide-mesh gauze, which rest against the mouth and nose, become wet with saliva, soiled with the fingers, and are changed infrequently, may lead to infection rather than prevent it. (United States Department of Navy, 1920, p. 434) While mask ordinances and other public safety measures helped reduce mortality during the flu pandemic (Markel et al., 2007), scientists in the subsequent decades persisted in investigating the most effective ways to design and use PPE.

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Figure 3: Depiction of the gauzecotton mask. Image Source: Wikimedia Commons

"PPE also underwent a major change with the introduction of medical respirators, which provide a close fit around the nose and mouth and filter out particles much smaller than those filtered by surgical masks"

Researchers studied the factors that degrade a mask’s protectiveness, the importance of tightness of fit, the efficacy of deflection versus filtering mechanisms, and the porosity and comfort of various materials (Spooner, 1967). In the 1960s, disposable masks made of synthetic, non-woven materials began to replace reusable ones. Manufacturers argued that these disposable masks were more comfortable and convenient, while hospital administrators viewed them as cost-saving and better for maintaining a sterile environment (Strasser & Schlich, 2020). PPE also underwent a major change with the introduction of medical respirators, which provide a close fit around the nose and mouth and filter out particles much smaller than those filtered by surgical masks (Jagadeshvaran et al., 2021). The N95 mask, for example, is capable of filtering out 95 percent of particles larger than 0.3 micrometers. Healthcare workers deployed N95 respirators to protect themselves from drug-resistant tuberculosis in the 1990s (Pan et al., 2020) and again during the Ebola outbreak of 2013-2016 (MacIntyre et al., 2014). As with previous epidemics, a lack of immediate knowledge about the exact transmission of the Ebola virus caused uncertainty about how to most effectively use PPE (Hanoa & Moen, 2016). At the start of the COVID-19 outbreak, conflicting statements by public officials again sowed confusion regarding the efficacy of PPE. On February 29, 2020, the U.S. Surgeon General

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wrote on Twitter that the public should stop buying masks, adding, “They are NOT effective in preventing general public from catching #Coronavirus, but if healthcare providers can’t get them to care for sick patients, it puts them and our communities at risk! (as cited in Wong & Claypool, 2021). In the following weeks and months, however, new evidence demonstrated that asymptomatic individuals could transmit the virus through respiratory aerosols and droplets (Pan et al., 2020). In April 2020, the CDC updated its website, recommending that the public wear cloth coverings to limit the range of emitted respiratory particles (Wong & Claypool, 2021). In June 2020, Anthony Fauci, Director of the National Institute of Allergy and Infectious Diseases, explained that the public was advised not to wear face masks at the start of the pandemic in part to prevent a shortage of PPE for healthcare workers (Wong & Claypool, 2021). A limited national stockpile and surges in patients nevertheless caused severe PPE shortages around the world. Healthcare workers resorted to a few strategies to cope with these shortages. One was the sterilization and reuse of PPE. Though subjecting N95 respirators to heat, ultraviolet irradiation, and various disinfecting solutions has been shown to kill the coronavirus and enable reuse, each degrades the effectiveness of these respirators—to varying degrees—over time (Liao et al., 2020). Similarly, research has demonstrated

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that extended use of surgical masks reduces the strength of the electrostatic charge that deflects particles (Pan et al., 2020). 3D printing technology therefore has been an effective resource in the production of PPE during the COVID-19 pandemic. 3D printing has allowed for the rapid deployment of face shields, masks, and respirators. Nevertheless, 3D-printed PPE can encounter technical challenges. According to Tarfaoui et al. (2020), such PPE may be less effective than surgical masks and N95 respirators. Researchers thus continue to experiment with designs and materials that are scalable and can match or exceed the efficacy of mass-produced PPE (Aydin et al., 2021). The PPE challenges facing healthcare workers prompted the public to buy or create their own face coverings, including those made of cotton t-shirts or bandanas. Research has shown that such face coverings can help prevent those infected from infecting others and protect the wearer from inhaling airborne particles carrying the virus. According to Stewart et al. (2021), “There is laboratory-based evidence that household masks . . . help people keep their emissions to themselves” and that “cloth face coverings can provide good fit and filtration.” Despite these findings, approximately 10 to 15 percent of the public in several countries has expressed refusal to wear coverings, citing discomfort, doubts about their effectiveness, and civil liberties concerns (Taylor & Asmundson, 2021). In the United States, citizens have engaged

in displays of civil disobedience and protests against mask mandates in ways reminiscent of the Spanish flu pandemic. While PPE has undoubtedly saved the lives of countless individuals throughout the COVID-19 crisis, especially among healthcare workers, public confusion and mistrust regarding the effectiveness of PPE surely resulted in preventable deaths.

Conclusion A historical overview of infectious disease and the design and use of PPE—from the earliest plagues to COVID-19—can offer valuable insights into how to interpret the ongoing response to the current pandemic and how to prepare for the next one. First, it is important for physicians, researchers, and the general public to cultivate humility and recognize the persistent challenge of understanding the cause and spread of infectious disease. While modern readers may scoff at the beaked plague doctor outfit or the resistance to the adoption of modern PPE at the end of the 19th century, it can be humbling to recall that scientists needed months to learn that asymptomatic individuals could spread COVID-19 and that the survivability of the coronavirus on surfaces and the effectiveness of gloves are still uncertain (Goldman, 2020). This humility help can soften resistance to new, seemingly contradictory information and facilitate reception to new guidelines and policies.

"While PPE has undoubtedly saved the lives of countless individuals throughout the COVID-19 crisis, especially among healthcare workers, public confusion and mistrust regarding the effectiveness of PPE surely resulted in preventable deaths."

Figure 4: Doctor of San Salvatore Hospital in Pesaro, Italy at the end of a twelve-hour shift. Image Source: Wikimedia Commons

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Second, researchers can increase their efforts to preemptively understand the behavior of different pathogens and the effectiveness of PPE against them. While new evidence will undoubtedly arise over the course of a pandemic, researchers can continuously study which materials, designs, and sterilization methods will optimize the performance of PPE against infectious diseases. Such knowledge can be drawn upon in the future to help avoid the dissemination of untrue information and adoption of misinformed health guidelines. Third, governments, industries, researchers, and healthcare professionals can collaborate in advance to ensure that there is a sufficient supply of PPE for the next pandemic. One possibility is to refine and expand the use of 3D printing capabilities to enable hospitals and manufacturers to quickly produce PPE during a shortage. Another possibility is to better understand the reusability of PPE. While Strasser and Schlich (2020) acknowledge that “disposable masks and respirators will certainly remain an essential part of medical personal protective equipment in the future,” they also advise “look[ing] beyond the creation of large stockpiles of disposable face masks and consider[ing] the risks of the throwaway consumer culture applied to lifesaving devices” (p. 20). Finally, of special relevance to healthcare providers is the appearance of their PPE and its effect on patients. While contemporary PPE looks less unsettling than the beaked plague doctor outfit of the 17th century, healthcare providers during the COVID-19 pandemic have expressed concern about how their PPE might undermine their relationship with patients. Physician Mark Earnest (2020) has described the distancing he felt when visiting with his first patient suspected of having COVID-19: I was wearing two layers of gloves, a gown, an N95 mask, and goggles. While taking her history and examining her, I felt a wave of guilt and a sense that I was betraying something important. I was a walking hazmat suit, unrecognizable beneath heavy gear that was not for her protection but for my own. PPE can thus be a problem not only because it might interfere with clear spoken and nonverbal communication, but also because it can damage rapport with patients and reduce the quality of interviews and exams. Therefore, practitioners might consider ways they can make their patients

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comfortable and build rapport in light of the PPE they are wearing. Moreover, while personal safety cannot be sacrificed in the design of PPE, manufacturers might more strongly consider how PPE could appear less off-putting to patients. These are some of the lessons that arise from an overview of the history of infectious disease and the evolution of PPE. Despite the intellectual, scientific, and technological progress of humanity in its ability to understand and respond to contagion, the world is still vulnerable to the outbreak of the next lethal pathogen. The issue is not if there will be another pandemic, but when that next pandemic will be: understanding the history of infectious disease and PPE can be a valuable source of wisdom in meeting it effectively. References Aydin, A., Demirtas, Z., Ok, M., Erkus, H., Cebi, G., Uysal, E., Gunduz, O., & Ustundag, C. B. (2021, February 8). 3D printing in the battle against COVID-19. Emergent Materials, 4(1), 363-386. https://link.springer.com/article/10.1007/s42247-02100164-y Blevins, S. M., & Bronze, M. S. (2010, September). Robert Koch and the ‘golden age’ of bacteriology. International Journal of Infectious Diseases, 14(9), e744-e751. https://www.sciencedirect. com/science/article/pii/S1201971210023143 Cohn, S. K. (2010). Cultures of plague: Medical thinking at the end of the Renaissance. Oxford University Press. Conti, A. A. (2020, July 16). Protective face masks through centuries, from XVII century plague doctors to current health care professionals managing the COVID-19 pandemic. Acta Biomedica, 91(4). https://www.ncbi.nlm.nih.gov/pmc/articles/ PMC7927518/ Cunha, B. A. (2005, March 1). The cause of the plague of Athens: Plague, typhoid, typhus, smallpox, or measles? Infectious Disease Clinics of North America, 18(1), 29-43. https://www.ncbi.nlm.nih.gov/pmc/articles/ PMC7118959/#:~:text=Typhoid%20fever,-There%20is%20 no&text=Few%20features%20suggest%20that%20typhoid,a%20 diagnosis%20of%20enteric%20fever Earnest, M. (2020, May 20). On becoming a plague doctor. New England Journal of Medicine, 383(10). https://www.nejm.org/ doi/full/10.1056/NEJMp2011418 Forbes, A. W. (2021, January 30). COVID-19 in historical context: Creating a practical past. HealthCare Ethics Committee Forum, 33, 7-18. https://link.springer.com/article/10.1007/ s10730-021-09443-x Goldman, E. (2020, July 30). Exaggerated risk of transmission of COVID-19 by fomites. The Lancet, 20(8), 892-893. https://www.thelancet.com/ journals/laninf/article/PIIS1473-3099(20)30561-2/fulltext Hanoa, R. O., & Moen, B. E. (2016, February). Ebola care and lack of consensus on personal protective respiratory equipment. Workplace Health & Safety, 64(2), 48-50. https://doi. org/10.1177/2165079915608405

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Harbeck, M., Seifert, L., Hänsch, S., Wagner, D. M., Birdsell, D., Parise, K. L., Wiechmann, I., Grupe, G., Thomas, A., Keim, P., Zöller, L., Bramanti, B., Riehm, J. M., Scholz, H. C. (2013). Yersinia pestis DNA from skeletal remains from the 6th century AD reveals insights into Justinianic Plague. PloS Pathogens, 9(5). https://doi.org/10.1371/ journal.ppat.1003349

Porter, S. (2009). The Great Plague. Amberly. Smith, K. A. (2012, April 10). Louis Pasteur, the father of immunology? Frontiers in Immunology, 12(4), 347-350. https:// www.ncbi.nlm.nih.gov/pmc/articles/PMC3342039/

Hays, J. N. (2005). Epidemics and pandemics: Their impacts on human history. ABC-CLIO.

Stewart, C. L., Thornblade, L. W., Diamond, D. J., Fong, Y., & Melstrom, L. G. (2020, May 7). Personal protective equipment and COVID-19: A review for surgeons. Annals of Surgery, 272(2), e132-e138. https://www.ncbi.nlm.nih.gov/pmc/articles/ PMC7268841/

Jagadeshvaran, P. L., Menon, A. V., & Bose, S. (2021). Evolution of personal protective equipment from its inception to COVID-19. Current Science, 120(7), 1169–1183. https://www. currentscience.ac.in/Volumes/120/07/1169.pdf

Strasser, B. J., & Schlich, T. (2020, May 22). A history of the medical mask and the rise of throwaway culture. The Lancet, 396(10243), 19-20. https://www.thelancet.com/journals/lancet/ article/PIIS0140-6736(20)31207-1/fulltext

Jouanna, J. (2012). Chapter 7: Air, miasma, and contagion in the time of Hippocrates and the survival of miasmas in postHippocratic medicine (Rufus of Ephesus, Galen and Pallidius). In P. J. van der Eijk (Ed.), N. Allies (Trans.), Greek medicine from Hippocrates to Galen: Selected papers (pp. 119–136). Brill. https://www.jstor.org/stable/10.1163/j.ctt1w76vxr.12

Tarfaoui, M., Nachtane, M., Goda, I., Qureshi, Y., & Benyahia, H. (2020, July 27). 3D printing to support the shortage in personal protective equipment caused by COVID-19 pandemic. Materials, 13(15). https://doi.org/10.3390/ma13153339

Lee, K. P. P. (2019, November 19). Caroline Hampton Halsted and the origin of surgical gloves. SAGE Journals, 28(1), 63-66. https://journals.sagepub.com/doi/ full/10.1177/0967772019869167 Liao, L., Xiao, W., Zhao, M., Yu, X., Wang, H., Wang, Q., Chu, S., & Cui, Y. (2020, May 1). Can N95 respirators be reused after disinfection? How many times? ACS Nano, 14(5), 6364-6356. https://www.ncbi.nlm.nih. gov/pmc/articles/PMC7202248/pdf/nn0c03597.pdf Lynteris, C. (2018). Plague masks: The visual emergence of anti-epidemic personal protection equipment. Medical Anthropology, 37(6), 442–457. https://doi.org/10.1080/0145974 0.2017.1423072 MacIntyre, C. R., Chughtai, A. A., Seale, H., Richards, G. A., & Davidson, P. M. (2014). Respiratory protection for healthcare workers treating Ebola virus disease (EVD): Are facemasks sufficient to meet occupational health and safety obligations? International Journal of Nursing Studies, 51(11), 1421–1426. https://doi.org/10.1016/j.ijnurstu.2014.09.002

Taylor, S., & Asmundson, G. J. G. (2021, February 17). Negative attitudes about facemasks during the COVID-19 pandemic: The dual importance of perceived ineffectiveness and psychological reactance. PloS One, 16(2). https://www.ncbi.nlm.nih.gov/pmc/ articles/PMC7888611/ Tognotti, E. (2003, May). Scientific triumphalism and learning from facts: Bacteriology and the ‘Spanish flu’ challenge of 1918. Social History of Medicine, 16(1), 97-110. https://doi. org/10.1093/shm/16.1.97 Tulchinsky, T. H. (2018). John Snow, cholera, the Broad Street pump; Waterborne diseases then and now. Case Studies in Public Health, 77-99. https://doi.org/10.1016/B978-0-12-804571-8.00017-2 United States Department of Navy. (1920). Epidemiological and statistical data, U.S. Navy, 1918. Government Printing Office. Wong, J., & Claypool, E. (2021, March 4). Narratives, masks and COVID-19: A qualitative reflection. Qualitative Social Work, 20(1-2), 206-213. https://journals.sagepub.com/ doi/10.1177/1473325020973330

Mattern, S. (2011, August 6). Galen and his patients. The Lancet, 378(9790), 478-479. https://www.thelancet.com/journals/lancet/ article/PIIS0140-6736(11)61240-3/fulltext Mussap, C. J. (2019, May 13). The plague doctor of Venice. Internal Medicine Journal, 49(5), 671-676. https://doi. org/10.1111/imj.14285 Nutton, V. (1983). The seeds of disease: An explanation of contagion and infection from the Greeks to the Renaissance. Medical History, 27(1), 1–34. https://www.ncbi.nlm.nih.gov/ pmc/articles/PMC1139262/pdf/medhist00084-0005.pdf Nutton, V. (1990). The reception of Fracastoro's theory of contagion: The seed that fell among thorns? Renaissance Medical History: Evolution of a Tradition, 6(1), 196–234. https://pubmed.ncbi.nlm.nih.gov/11612689/ Pan, K., Akin, L. R., & Patel, S. R. (2020, December). Through plagues and pandemics: The evolution of medical face masks. Rhode Island Medical Journal, 103(10), 72-75. http://www. rimed.org/rimedicaljournal/2020/12/2020-12-72-spotlight-pan. pdf

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A Brief Review of the Evidence on the Health Benefits of Meditative Prayer and Active Gratitude BY SAJID HUQ, BUILDING THE MODERN MD WINNER, MEDICINE AND RELIGION Cover Image: A serene view of the water Image Source: Pixabay

Religion and spirituality refer to the collection of beliefs, rituals, and behaviors which individuals subscribe to due to their belief in a divine purpose. Religion and spirituality have long been shown to favorably affect certain physical health, including neurological health, and mental health outcomes (Bonelli & Koenig). Across all religious and spiritual groups, there are many types of practices, however. Researchers are studying the role of meditative prayer and active gratitude, in particular, on physical, neurological, and mental health outcomes in order to see if applications in medicine, where religion and spirituality are still underutilized resources, are possible. Thus, it is crucial to better understand and apply the evidence on the role of meditative prayer and active gratitude on health outcomes. Meditative prayer refers to a common practice across many religions that aims to attain mental tranquility. It includes Transcendental meditation (TM), Zazen meditation, and Chenrezig meditation, each of which have their own unique

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characteristics (Shear, 2006). Transcendental meditation, originated by the Hindu monk Swami Brahmananda Saraswati, is characterized by sitting on a chair with one’s feet and arms uncrossed and repeating mantras to bring mental peace (Melton, 2020; Trama & Cheema, 2016). Zazen meditation, embedded within Buddhist teachings, involves sitting in a lotus position and breathing in and out without any mantras (Shear, 2006; How to meditate: Zazen, 2021). Finally, Chenrezig meditation, another Buddgist technique, aims to increase one’s objective compassion and love for everything through maintaining a lotus position, eyes closed, and visualizing the Buddha of compassion, Chenrezig (Shear, 2006). The meditative prayer techniques across many religions such as Hinduism and Buddhism use various mediums of postures, mantras, and mindsets to accomplish the encompassing goal of bettering one's mental and physical states. Evidence shows that TM is positively associated DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

with improved physical health. In a randomized and controlled study authored by Schneider and colleagues (2012), African Americans diagnosed with coronary heart disease were divided into TM and Health Education (HE) groups. The intervention group, TM, and control group, HE, were both taught by professionals that engaged in the same duration and quality of education of their respective topics. The populations were checked intermittently on the status of their primary or secondary endpoints; the primary endpoint was triggered if a person in the study suffered a death, non-fatal heart attack, or a nonfatal stroke while the second endpoint consisted of death from cardiovascular deficiencies, nonfatal heart attack, non-fatal stroke, and coronary revascularization. After an average follow-up period of 5.4 years, the TM group demonstrated an adjusted hazard score for primary endpoints and secondary endpoints; the hazard scores for both endpoints were significantly less than 1, indicating the TM group faced a smaller percentage of the corresponding endpoint events when compared to the control group, HE, therefore reducing the risk of health complications resulting from coronary heart disease. The study was limited by a relatively modest sample size of 201 participants, however. It is possible the overall population and the effects of TM prayer were not properly represented due to the lack of variety within the sample, which typically is needed to reflect society as a whole (Schneider et al., 2012). Overall, the meditation method of TM when used as an interventional treatment has been seen to reduce the risk of coronary heart disease and related ailments(Gryczynski et al., 2018). Recent studies have also shown Zazen and Chenrezig meditation are associated with neurological health improvements (Luders et al., 2012). In an experimental study, Luders and colleagues (2016) assessed brain ages, relationship of natural loss of neural tissue to corresponding chronological age, using relevance vector regression (RVR), a machine-learning approach to draw patterns between collected MRI images and normal aging of the brain. A SPRING AND SUMMER 2021

pool of 50 meditators and 50 control individuals. All individuals were chronologically aged 50 and above to outline whether meditation would be able to reduce the effects of brain atrophy from that age. They found that among the 50 meditators, who had Zazen and Chenrezig meditation users the average brain age was approximately 7.5 years younger than the control group members. Additionally, it was found that for every year above 50, the meditative group’s brain age was 1 month and 22 days younger than their actual age. For example, a person who was 51 years old in the meditative group would exhibit a brain age of 50 years, 10 months and 8 days. While this study seems to suggest Zazen and Chenrezig meditative prayers are beneficial for neurological health, it was indeed limited by varying levels of education between the meditator and control groups. It is key to note that the difference in education levels may have had underlying effects on the resulting brain age calculations since education levels have been suggested to have a positive correlation with healthy brain aging (Steffener et al., 2016). In addition to being linked with improved neurological health, Zazen and Chenrezig meditative prayers have also been demonstrated to have mental health benefits. In an experimental study by Mohammed and colleagues (2018), 20 injured collegiate athletes were placed in an intense meditative practice program for 90 minutes through eight weeks. Control group members were in informal meditation practice and had 20-minute sessions. Both groups utilized meditative practices; however, the formal meditation group had a longer period with meditation techniques such as mindful breathing, something that is prevalent and fixed in Zazen meditation and sitting meditation, also seen in the lotus position in Chenrezig meditation. Mental health and acuity was recorded before and after each session and throughout all the sessions in the form of tests such as the Mindful Attention Awareness Scale (MAAS). MASS utilizes a questionnaire format with 15 mindfulness questions which can be answered from zero to 6, representing most of the time and almost never. For the formal meditation group, the pre and post session MAAS scores had an increase that was 3.4 MAAS units higher than the corresponding control group MAAS scores. Therefore, the enriched regime of formal meditation practice which includes active breathing found in Zazen and sitting meditation present in Chenrezig significantly increased the mental health of the group’s injured athletes; since the increased mindfulness from higher MAAS score improvements promotes better mental health (Shankland et al., 2020). However, the

Figure 1: The lotus meditative position, often used in Zazen meditation is seen in the Buddhist statue since Zazen meditation originated in Zen Buddhism. Image Source: https://pxhere.com/ en/photo/702954

"In addition to being linked with improved neurological health, Zazen and Chenrezig meditative prayers have also been demonstrated to have mental health benefits."

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Figure 2: Educating the primary care workforce on beneficial aspects of meditative prayer and active gratitude can promote a non-invasive multi-faceted method to treat certain patient conditions. Image Source: https://www. nursinginpractice.com/ professional/how-to-resolveconflict-as-a-nurse/

"The authors found that the experimental gratitude group had significantly greater improvement in mental and physical health relative to the control group."

very limited sample size of the study can prove to be a hindrance when applying the correlations on a larger scale. Despite the limitations, science has shown that Zazen and Chenrezig meditation techniques may improve neurological and mental health. Active gratitude is another religious and spiritual practice that health organizations and professionals should consider integrating more into medical practice. Active gratitude involves the conscious acknowledgment of the positive aspects of one’s life. Although this experience can be subjective and relative, resulting in being appreciative of different components of life, the action is collectively meant to make one more aware of their state and hopefully foster an optimistic mindset. This practice is seen across many religions such as the monotheistic Abrahamic religions, Judaism, Christianity, and Islam. One is often told to be actively grateful for the blessings that have been given by God through prayer or acknowledgment. Active gratitude can also be practiced through journaling positive facets of life, positive self-affimations, positive affirmations to other people, and reflection (Gallagher, 2019). Studies have utilized active gratitude as an experimental group to find connections with decreased physical and mental ailments. A review article by Boggiss and colleagues (2020) focused on 19 studies that were peer-reviewed and had relevant evidence pertaining to active gratitude. In one particular study, Jackowska and colleagues (2016) conducted a single-blind experiment that used random selection on a population of 119 women to assign them to 3 groups: an experimental group, and everyday events group,

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and a control group. While the experimental and everyday events groups were given a journal to write in daily for two weeks, the control group was given no immediate task. In specific, the experiment gratitude group was assigned to write three objects or persons they were grateful for daily; the everyday events group had to write three details, with no focus on gratitude. The authors found that the experimental gratitude group had significantly greater improvement in mental and physical health relative to the control group. At the end of the follow-up period, average ambulatory diastolic BP for the experiment gratitude group was 2 mmHg lower than the control group’s diastolic BP. As well, the positive emotional style variable increased more in the experimental group than in the control group, indicating the active gratitude component was responsible for lower blood pressure and more positive emotions(Boggiss et al., 2020). In an individual correlative diagnostic study, Wood and colleagues (2009) also examined 401 individuals’ active gratitude and sleep quality. To assess if there is a correlation between active gratitude and sleep quality, the authors used robust, tested scales. The GQ-6 (Gratitude Questionnaire) scale measured gratitude and the Pittsburgh Sleep Quality Index (PSQI) measured sleep issues. A lower PSQI represents a higher quality of sleep. The study found a negative correlation between the GQ-6 scale and all PSQI indices. Therefore, gratitude was found to be directly positively correlated with high-quality sleep. Although the negative correlation was weak the results were significant which ensured the presence of an actual correlation. Active gratitude also was indirectly associated with improved sleep quality through pre-sleep positive

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cognitions. In other words, the authors found that a covariant relationship existed between active gratitude and positive pre-sleep cognition, having positive thoughts before sleep. The positive presleep cognition then holds a negative correlation with PSQI scale, indicating higher quality sleep. Possible implications such as the scales in the study being formed from participants picking numbers on a small range could restrict more individual and specific scalings. A lack of personalized and descriptive data collection for each participant presents the possibility that certain parts of the test population are marginalized. This limitation can be solved by utilizing qualitative data collection which encapsulates much more of participant reaction and psyche about active gratitude. For example, psychologists Robert Emmons and Michael McCullough ran a series of three experiments asking different groups of people to list hassles, things they were grateful for, or nothing (Emmons & McCullough, 2003). The first experiment involved 192 eligible undergraduate participants that were split up into three groups. Each wrote in a weekly journal over a span of 10 weeks; the gratitude group wrote things they were grateful for, the hassles group listed nuisances in life, and the control group wrote about events without any restrictions. The second study had an eligible test population of 157 undergraduates who wrote 16 daily forms on the gratitude and hassle conditions outlined in study 1, but the control group was actively told to list comparisons between themselves and others. The third study followed the framework of the second study, but the test population was 67 people that had a neuromuscular disease who wrote in the forms for 21 days and the hassle experimental group was removed. All groups in these studies then selected words that equated to a composite score for each iteration of active gratitude (i.e weekly or daily journals). Across all the gratitude experimental groups the use of optimistic descriptive words, such as grateful, thankful, appreciative and other words in the positive spectrum was used often in the different writing tasks. In the second study, the gratitude group utilized more positive word markers relative to the hassle group. The word markers included: attentive, determined, energetic, enthusiastic accompanied with a p-value less than 0.05, confirming the statistics to be significant (Emmons & McCullough, 2003). All of the increased use of positive and gratuitous words indicate an improved and more positive mental state, a useful method to administer psychotherapy by directing patients to write gratuitously (Wong et al., 2016)

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Though there is a need for continued study, the current report found evidence that meditative prayers and active gratitude have physical, neurological, and mental health benefits. The physical, neurological, and mental health benefits from these religious and spiritual techniques can function as both prevention and treatment for many negative health conditions. Thus, based on the body of evidence presented, a case for further integrating meditative prayer and active gratitude into primary and specialty care medicine is growing. There is a need to ensure there are sufficient educational programs on meditative prayer and active gratitude for the general public and patients. The educational interventions should be customized for specific populations, including for multiple age demographics, those suffering from specific health conditions, and specific races. Additionally, there is a need for primary care physicians and other medical specialists to receive sufficient training on meditative prayer and active gratitude (Lindauer, 2021). Health professionals being informed of the most recent evidence on these strategies is important for ensuring both methods are appropriately integrated into the field of medicine. Organized religion or spirituality is a part of many peoples’ identities. Thus, the precedent of considering religion exclusive from medicine is limiting and should be challenged. There is a universal benefit for the general public in educating both patients and providers on the physical, neurological, and mental benefits of meditative prayers and active gratitude, and future research should continue in this area. References Boggiss, A. L., Consedine, N. S., Brenton-Peters, J. M., Hofman, P. L., & Serlachius, A. S. (2020). A systematic review of gratitude interventions: effects on physical health and health behaviors. Journal of Psychosomatic Research, 135, 110165. Bonelli, R. M., & Koenig, H. G. (2013). Mental disorders, religion and SPIRITUALITY 1990 to 2010: A Systematic Evidence-Based Review. Journal of Religion and Health, 52(2), 657–673. https://doi.org/10.1007/ s10943-013-9691-4 Emmons, R. A., & McCullough, M. E. (2003). Counting blessings versus burdens: an experimental investigation of gratitude and subjective well-being in daily life. Journal of personality and social psychology, 84(2), 377–389. https://doi. org/10.1037//0022-3514.84.2.377 Gallagher, M. W. (2019). Introduction to positive psychological assessment. Positive Psychological Assessment: A Handbook of Models and Measures (2nd Ed.)., 3–9. https://doi. org/10.1037/0000138-001 Gryczynski, J., Schwartz, R. P., Fishman, M. J., Nordeck, C. D., Grant, J., Nidich, S., Rothenberg, S., &amp; O'Grady, K. E.

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(2018). Integration of TRANSCENDENTAL Meditation® (TM) into alcohol use disorder (AUD) treatment. Journal of Substance Abuse Treatment, 87, 23–30. https://doi.org/10.1016/j. jsat.2018.01.009 Holden, C. (2003, March 21). BRIC news. Retrieved July 05, 2021, from https://www.ibric.org/myboard/skin/news1/print. php?Board=news&id=30832

influences sleep through the mechanism of pre-sleep cognitions. Journal of psychosomatic research, 66(1), 43–48. https://doi. org/10.1016/j.jpsychores.2008.09.002 Trama, S., & Cheema, N. (2016). Transcendental meditation: Nature and perspectives. Indian Journal of Health and Wellbeing, 7(9), 928.

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Medicine and the Modern Media BY STEPHANIE PARK, BUILDING THE MODERN MD WINNER, MEDICINE AND ART

Cover Image: The digital age of mass media is intertwined with medicine in unexpected ways. Image Source: Unsplash

Introduction Since the rise of modern search engines and the rapid dissemination of knowledge through the media, information has become more accessible now than ever before. This availability has inevitably led to increased public dependence on mass media for reliable information. Indeed, as of 2021, 93% of U.S. adults claim they use the internet, and 72% say they use at least one social media site—a staggering growth from the mere 5% of social media users in 2005 (Internet Use Over, n.d.; Social Media, n.d.). The “media” is defined as any medium of mass communication, including the radio, television, newspapers, magazines, and the internet (Konac & Barut, 2021). With the media becoming an increasingly influential source of information, both the content and manner in which information is conveyed now largely influence the public’s beliefs, attitudes, and behaviors. For instance, the media’s portrayal of certain illnesses or diseases may significantly sway the public perception of different health risks and promote certain health behaviors. Previous studies have indicated that medical conditions receiving greater media coverage have a significantly higher risk perception than

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those receiving less coverage, regardless of the actual risk associated with the event (Young et al., 2013). For example, motor vehicle deaths receive a considerably larger amount of media attention and hence higher risk perception than deaths due to toxic agents, despite the fact that toxic agents were responsible for almost seven times more deaths than motor vehicles in 2017 (Pilar et al., 2020). Additional studies have shown that the media drastically misrepresents the mortality rates of numerous diseases (Frost et al., 1997). Spreading misinformation, which is defined as false information that is inadvertently created or shared without the intention of causing harm (Wardle & Derakhshan, 2017), leads to alarmingly skewed public perceptions of health risks. Moreover, the choice of media coverage frames public discussions that ultimately drive major government policies and regulations (Johnson, 1998). Often, the government also uses funding mechanisms to control the media to advance the government agenda (Dragomir, 2017). In this regard, there is little doubt that the media and government are deeply intertwined; the media is a valuable outlet for the government to communicate information to the public, and, DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

in turn, the media also plays a critical role in government policymaking. Considering these effects, it is necessary to investigate the role of the government in employing the media to communicate health information. Government authorities must effectively communicate with the mass media to uphold their obligation in providing accurate health education to the public. For instance, government-sponsored programs and media campaigns can educate the general public with factual health information, playing a decisive role in promoting healthier outcomes. This beneficial influence is reflected by the substantial reduction in smoking prevalence after the implementation of several government-sponsored mass media interventions (England et al., 2017; Kuipers et al., 2017; Wakefield et al., 2014), emphasizing that the government can utilize media outlets to change the public’s awareness of health risks and, ultimately, their behavior. On the other hand, the media also impacts the health risk perceptions of government authorities, such as policymakers, who may then alter key public health policies. Media attention significantly impacts the policy process by shaping policymakers’ perceptions of an issue’s importance throughout the process of policy writing and implementation (Cook et al., 1983; Fawzi, 2017; Soroka et al., 2012; Walgrave, 2008). Health policies can ultimately determine the government spending on specific health issues; thus, it is crucial for policymakers to effectively communicate with the mass media to allocate government-funded resources to better align with actual health risks and not perceived risks from the media. The substantial impacts of the media’s coverage of medical issues deserve more attention, and the pivotal role of the government in providing accurate medical information should be recognized and further utilized. This is especially relevant in recent times due to the COVID-19 pandemic and the public’s growing dependence on the media for reliable health information. Numerous studies have found that the spread of COVID-19 misinformation in the media has masked healthy practices and ultimately led to detrimental physical and mental health outcomes among some individuals (Tasnim et al., 2020). This paper will explore the influence of the media on public perceptions of health risks and the implications of such consequences for the government.

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in the Media There has been much tension between the scientific community and the mass media due to their general disagreements in determining what is newsworthy content and what the role of the media is (Nelkin, 1996). Scientists have frequently criticized journalists and reporters for violating effective scientific communication principles by selectively reporting rare and attention-grabbing stories rather than more prevalent and urgent health issues (Young et al., 2013). Indeed, studies have found that the media overemphasizes novel health hazards compared to their actual risk, while more common threats receive less media coverage (Bomlitz & Brezis, 2008). For instance, there were over 100,000 media reports regarding severe acute respiratory syndrome (SARS) and bioterrorism, which killed fewer than a dozen people in the United States in 2003; however, there were less than 40,000 media reports altogether regarding smoking and physical inactivity, which killed nearly a million Americans in the same year (Bomlitz & Brezis, 2008). Consistent with criticisms highlighting that medical reporting is often driven by alternative motives, there is also strong statistical evidence indicating that financial interests may drive media coverage. For instance, magazines containing cigarette advertisements had diminished coverage of the health risks of smoking, suggesting that companies that financially depend on tobacco advertising may be more reluctant to report the genuine hazards of tobacco usage (Warner et al., 1992).

"studies have found that the media overemphasizes novel health hazards compared to their actual risk, while more common threats receive less media coverage"

The mass media is a leading source of health information for the general public (Brodie et al., 2003; James et al., 1999; Johnson, 1998), and hence, the media’s misrepresentation of medical hazards leads to largely distorted prioritizations and misguided health behaviors on a population level. More importantly, in the current social media era, such medical misinformation has been shown to spread faster, farther, and more broadly than accurate information, from Twitter bots amplifying controversies about vaccines to caregivers exchanging information about unproven cancer treatments on Facebook pages (Broniatowski et al., 2018; Gage-Bouchard et al., 2017; Sylvia Chou et al., 2020; Vosoughi et al., 2018). This dissemination of false information is further aggravated by the fact that there are true believers of misinformation who are armed with ignorance regardless of the genuine statistics (Wang et al., 2019). These circumstances illuminate the alarming extent of health misrepresentation in the media, accentuating the 209

Figure 1: Smoking causes cancer, heart disease, stroke, lung diseases, diabetes, and many more fatal diseases that are often underrepresented in the media. Image Source: Flickr

urgent need for greater regulation from health officials.

"Comprehensive studies on more specific health risks reveal that tobacco usage, physical inactivity, HIV/ AIDS, and now COVID-19 are among the most severely misrepresented by the media."

The Misrepresentation of Specific Health Risks Comprehensive studies on more specific health risks reveal that tobacco usage, physical inactivity, HIV/AIDS, and now COVID-19 are among the most severely misrepresented by the media. An extensive survey uncovered that many smokers largely underestimate their risk of lung cancer and demonstrate other misunderstandings regarding the health risks of smoking (Weinstein, 2005). The miscalculation of tobacco hazards may be ascribed to the media’s misrepresentation of health risks, as research shows that tobacco usage is the among most underrepresented causes of death by news media (Frost et al., 1997). Indeed, a recent exploratory study found that the dangers of tobacco usage continue to receive lower media attention than less dangerous risk factors, although tobacco usage was responsible for nearly 16% of all deaths in the United States in 2017 (Pilar et al., 2020). This may be owing to the strong political influence of the tobacco industry or the longstanding knowledge of tobacco's negative health effects that makes it difficult to generate new and more intriguing news reports regarding it (Pilar et al., 2020). Moreover, a large body of research literature

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illustrates that the media misleadingly associates smoking with favorable attributes, resulting in many adolescents perceiving smoking as acceptable and stress-relieving, despite being well aware of its harmful consequences (Watson, 2003). One comprehensive review found that exposure to e-cigarette marketing was correlated with lower harm perceptions of e-cigarettes, higher intentions to use e-cigarettes, and greater likelihood of e-cigarette trials (Collins et al., 2018), stressing the need for stricter government advertising regulations to reduce the distortion of tobacco’s health risks. Another example of the media’s misrepresentation of a critical health issue is physical inactivity and diet. In one audience reception study involving in-depth interviews, respondents expressed that the media had given inadequate attention towards physical activity, and media coverage was focused on stating the consequences of inactivity and obesity rather than providing practical advice (Smith & Bonfiglioli, 2015). Moreover, a study that examined how health behaviors were covered in over 80,000 stories across 1,354 newspaper issues found that stories addressing diet, physical activity, or tobacco usage were seldom prominently located in the newspaper, and a large majority had no call to action for the promotion of healthier behaviors (Caburnay et al., 2003).

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Figure 2: There has been a rapid spread of misleading rumors and conspiracy theories regarding COVID-19 through mass media platforms. Image Source: Unsplash

Additionally, HIV/AIDS used to be a popular news topic, especially when it first peaked as a U.S. health epidemic in the 1980s. However, there has been declining media coverage of HIV/AIDS and a consequent decline in the public’s perception of the issue’s gravity despite its enduring prevalence. A comprehensive analysis of the media coverage of HIV/AIDS from the first news reports in 1981 through December 2002 has indicated a media “fatigue” in covering the health issue; that is, there has been public desensitization to the perils of HIV/AIDS coupled with a considerable decline in the total number of HIV/AIDS media coverage over time (Brodie et al., 2004). This finding is particularly unsettling considering that stigmas surrounding HIV/AIDS are also hindering people from actively seeking information and treating the illnesses (Cullen & Callaghan, 2016), although this could be prevented with greater media coverage to break the social stigma. The drop in HIV/AIDS media coverage may be due to the increasing difficulty for journalists to generate entertaining stories that meet the editorial standards for “news.” Health officials face bigger challenges in highlighting the more compelling aspects of persisting diseases to meet the editorial standards, bringing to light a severe impediment to the accurate portrayal of health risks in the media. Yet, perhaps the most pressing issue of health misinformation in recent times is

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that of COVID-19. While social media platforms (e.g., Facebook, Instagram, Twitter) offer interconnectedness and effortless communication amidst the separation, they also allow for the rapid spread of misleading rumors and conspiracy theories that have devastating consequences. The misinformation accompanying the COVID-19 pandemic has created a sense of hysteria among the general public, scientists and healthcare workers who are battling the novel disease. Unproven and erroneous practices are being spread online, masking healthy and well-established prevention methods such as handwashing and wearing masks. For example, health officials in Nigeria found several cases of chloroquine overdose (a drug used to treat malaria) after false rumors of the supposed effectiveness of the drug for treating COVID-19 spread through the news media (Busari & Adebayo, 2020). In Iran, over 300 people died, more than 1000 required hospitalization, and many were expected to have permanent vision loss after drinking counterfeit alcohol containing toxic methanol upon hearing a false rumor that alcohol prevents the contraction of the coronavirus (Love et al., 2020). Furthermore, support for ivermectin (a common horse deworming drug) as a COVID-19 treatment has been circulating on social media, although national agencies such as the United States National Institutes of Health (NIH) and Food and Drug Administration (FDA) have

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strongly advised against its use (COVID-19 Treatment, 2021; Why You Should, n.d.). Such hoaxes create feelings of skepticism even towards reliable COVID-19 information found online, resulting in increased resistance against government-recommended prevention measures (Tasnim et al., 2020).

"If employed correctly, social media can become an integral vehicle for disseminating beneficial health information and campaigns"

Given the myriad of incidents and tragic fatalities caused by the rapid spread of health misinformation through the media, medical institutions and authorities should strategically partner with media platforms to broadcast reliable and proven public health reports regarding COVID-19. If employed correctly, social media can become an integral vehicle for disseminating beneficial health information and campaigns (Wong et al., 2020). Hence, medical institutions and government authorities should evolve to utilize the potential of media platforms in supplying valuable information regarding the COVID-19 pandemic and other highly prevalent yet overlooked health issues such as tobacco usage, physical inactivity, HIV/AIDS, and more.

The Media’s Impact on Health Policies and the Government Beyond shaping the public’s perception of different health risks, how does the media affect the government? More specifically, how is the media intertwined within the government agenda and policy process? During the past few years, such questions have emerged within the scientific community, leading to a steady stream of research literature. Media coverage directly affects the perceived importance of a health-related topic, ultimately influencing greater matters such as government spending for certain health issues and the establishment of different health policies. Considering this, it is necessary to analyze the extent to which the media is interrelated with the government. The policy process can be outlined by five main steps: defining the problem, agenda-setting, policy formulation, policy implementation, and policy evaluation (Pilar et al., 2020). While media attention is generally believed to only influence the earlier stages of the policy process, such as agenda-setting and policy formulation, a recent survey involving political figures and journalists has confirmed that all policy process stages are susceptible to media influence (Fawzi, 2017). Firstly, the omnipresent nature of the media makes it a powerful instrument for providing helpful information about a given issue and indicating which issue the public should direct their attention towards. The more media coverage an

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issue receives, the more likely it is to be perceived as being important by the public. Such public concerns do not go unnoticed by policymakers; in fact, it is one of the most significant factors affecting government officials’ prioritization of health issues (Pilar et al., 2020). Naturally, decision-makers allocate more resources to medical problems that are prioritized, meaning that media attention does indeed have a powerful effect on the government agenda. Considering this dynamic, policymakers should be more cautious as to not be swayed by the distorted representation of health risks on media platforms; yet, it is disquieting to note that the government prioritization of resources for certain health issues are not consistently aligned with the actual causes of death. Instead, the government’s priorities may be more correlated with media attention and perceived health risks. For instance, an in-depth study investigating the correlations between actual causes of death in the United States, media attention, policy attention, and government spending for ten leading health issues found that there were major misalignments between the nation’s priorities (as measured by media attention, policy attention, and funding) and the actual causes of death. The most severely misaligned was tobacco usage, which was ranked the second-highest real cause of death in the United States, but consistently received lower emphasis than other health issues regarding media attention, policy legislation, and allocated research funding (Pilar et al., 2020). These findings suggest that the disproportionate media coverage of health risks can have unintended consequences on the government agenda and, in turn, the public’s well-being. Government officials should better communicate with mass media platforms to best allocate public health resources to align with the actual causes of death. Additionally, public health authorities must attempt to utilize the powerful potential of the media in engendering behavioral and policy changes to promote healthier practices.

The Government’s Role in Utilizing the Media to Disseminate Health Information (Future Directions) If effectively used, the media serves as a critical source of reliable health information. Comprehensive research shows that when governments effectively utilize the media to sponsor health campaigns and interventions, they can promote healthier behaviors on a population level. For instance, increases in governmentsponsored tobacco control mass media

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interventions have led to decreased population smoking prevalence (Bala et al., 2017; England et al., 2017; Kuipers et al., 2017; Wakefield et al., 2014). In more recent studies regarding the COVID-19 pandemic, improved handwashing knowledge and behaviors followed governmentimplemented mass media campaigns (Islam et al., 2021). However, journalists inevitably seek to report stories that satisfy ‘news values’, a set of criteria for determining the importance or ‘newsworthiness’ of an event to meet the publication standard (Jorge, 2008). This makes it particularly challenging for ongoing health issues to receive media coverage, as public health advocates must consistently find new ways to highlight novel aspects of these issues. Moreover, media constraints of brevity, simplicity, and time often hamper the detailed and meticulous reporting necessary for accurate scientific communication (Institute of Medicine (US) Committee on Assuring the Health of the Public in the 21st Century, 2003). To ease these complications and tensions between the scientific and news communities, the Institute of Medicine (US) recommends that medical and public health officials continuously communicate with media platforms and journalists to best structure health-related publications to meet the needs of both sides. In addition, government health agencies should develop training programs to educate journalists on the specific public health issues they are reporting and provide public health officials with opportunities to learn about public and risk communication (Institute of Medicine (US) Committee on Assuring the Health of the Public in the 21st Century, 2003). These interdisciplinary and collaborative efforts will better prepare both journalists and public health officials to accurately report health issues and practices, ultimately benefiting the public’s health.

Conclusion The mass media plays a significant role in people’s everyday lives, particularly when it comes to health and well-being, as evidenced by the number of people who depend on the media for medical information. However, the current extent of health misrepresentation in the media is alarming, with distorted portrayals of mortality and health risks accompanied by the rapid spread of misleading rumors leading to devastating consequences. At present, the vast majority of media platforms and journalists do not consider themselves part of the public health system, even though they hold a crucial role in educating the public about critical medical

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pdf?x11129 Warner, K. E., Goldenhar, L. M., & McLaughlin, C. G. (1992). Cigarette Advertising and Magazine Coverage of the Hazards of Smoking a Statistical Analysis. New England Journal of Medicine, 326(5), 305-309. https://doi.org/10.1056/ NEJM199201303260505 Watson, N. A. (2003). Filthy or fashionable? Young people's perceptions of smoking in the media. Health Education Research, 18(5), 554-567. https://doi.org/10.1093/her/cyf039 Weinstein, N. D. (2005). Smokers' unrealistic optimism about their risk. Tobacco Control, 14(1), 55-59. https://doi. org/10.1136/tc.2004.008375 Why You Should Not Use Ivermectin to Treat or Prevent COVID-19. (n.d.). U.S. Food and Drug Administration. https:// www.fda.gov/consumers/consumer-updates/why-you-shouldnot-use-ivermectin-treat-or-prevent-covid-19 Wong, A., Ho, S., Olusanya, O., Antonini, M. V., & Lyness, D. (2020). The use of social media and online communications in times of pandemic covid-19. Journal of the Intensive Care Society, 22(3), 255-260. https://doi. org/10.1177/1751143720966280 Young, M. E., King, N., Harper, S., & Humphreys, K. R. (2013). The influence of popular media on perceptions of personal and population risk in possible disease outbreaks. Health, Risk & Society, 15(1), 103-114. https://doi.org/10.1080/13698575.201 2.748884

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Utilizing Interpersonal Psychotherapy as a Prominent Treatment Option for Lower Socioeconomic Ranking Pregnant Mothers Diagnosed with Postpartum Depression Disorder BY ZAINAB NEEMUCHWALA, BUILDING THE MODERN MD WINNER, MEDICINE AND ECOCover Image Image Source: Pixabay

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Abstract While pregnancy has been thought to be a time for emotional comfort, that is not the case for women of lower economic status. Postpartum Depression (PPD) is a medical disruptive depression condition suffered by mothers after childbirth, with long-lasting effects. This crisis, increasing over the past decade amongst families in low socioeconomic statuses, calls for a valuable treatment. Interpersonal Psychotherapy (IPT) is evaluated in this literature review paper because it targets long-term physical and mental health of the mother, offspring, and family, and because it is economically feasible. IPT is less common amongst the standard of care, antidepressants. However, IPT should be implemented more widely because it assesses the issues low-income

mothers face in the long term and day to day, improving their health and resolving problems as they progress through the treatment. In the future IPT needs to be more accessible to low-income families through increasing social support and maximizing opportunities.

Introduction Historically, pregnancy was thought to be a time of “emotional well-being,” conferring protection against depression. However, pregnancy does not always convey emotional comfort for women. Nearly 47% of pregnant women of low socioeconomic status experience postpartum depression (according to M. Spinelli and J. Endicott of Maternal Mental Health at Columbia University, 2003). PPD is a highly prevalent DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

medical disruptive depression condition suffered by mothers after childbirth which can last up to two years, depending on the severity and living situation of the mother. PPD rates have increased over the past decade, as one in every seven mothers is likely to experience it. This crisis calls for a valuable treatment helpful towards mothers and families without proper medical access, which raises the question, what is a proper treatment for mothers of low socioeconomic status who are likely to demonstrate postpartum depression symptoms? This literature review paper argues that given PPD is prevalent among low income standing expecting mothers, medical enforcers should implement interpersonal psychotherapy (IPT) because it addresses the long-term physical and mental health of the mother and offspring as well as the family, and because it is economically feasible. However, it is not a well-known option and needs recognition since the current, mostused treatment is not as worthwhile as previously thought.

Background First, PPD has harmful outcomes on the physical health of the mother, father, and infant. PPD tends to be underdiagnosed or not diagnosed early enough because of confusion with normal pregnancy effects. In most cases, when depression in pregnancy is underdiagnosed, there is a potential hazard for lower-than-normal pregnancy weight gain, which can cause preterm delivery. This risk is a major cause of infant mortality and morbidity in the US (Altshuler et al., 2008). This demonstrates the severe life effects of PPD. According to clinical health experts, J. Milgrom et al. (2005), subclinical depressive symptoms can last up to two years for a family. This calls attention to the fact PPD must be treated early to prevent depressive actions such as suicide or infanticide. As stated earlier, the effects of PPD may negatively impact the infant and father, too. Kiviruusu et al. (2019) found that 8% of fathers suffer from PPD up to one-year postpartum (after birth), adding additional strains to the family. This can cause the infant to be born with a “lower birth weight” SPRING AND SUMMER 2021

or an emergency cesarean section (use of surgery to give birth) calling for the infant to be treated at the neonatal intensive care unit (section of hospital for infants with health problems, either born early or a difficult birth) (Spinelli and Endicott, 2003). This is significant because it puts offspring’s life at risk and heightens the mother's depression symptoms as it adds additional strain to the anxiety already felt during childbirth. Because of this, pregnant women showing PPD symptoms (weight changes, anxiety/anger, infant neglect, irritability, etc.) need more attention. Health specialists at (insert university) Figueiredo et al. (2007), grouped PPD into three main causes: negative physical or emotional pregnancy experience (lack of resources/income), previous history of mood disorder, and lack of difficulties in close relationships. This shows the powerful roles life evaluation and emotional wellbeing have on the pregnancy experience, as they are factors for depressive signs. In sum, physical health problems are a serious factor in finding a final treatment for PPD. In addition, without a worthwhile and longlasting treatment, mothers experiencing PPD put their infant's and their own psychological mental state at a critical risk. S. Drury et al. (2016), of Tulane University’s Behavioral Sciences noted when mothers are irritative, hostile, and less engaged with their infants, offspring can exhibit signs of insecure attachment, reduced social engagement, increased negativity, and poor fear regulation. Overall, neuropsychology is critical in forming mother/father-child relationships and is important in finding a treatment as well. Adding on, the rate of PPD is significantly larger with women in poverty-like conditions, who lack necessary pregnancy resources, such as mental health services, which can reduce the pernicious effects of this condition. A. Augusto et al. (2000) from Instituto de Cincias Biomédicas note women from lower socioeconomic groups tend to be more at risk for experiencing PPD symptoms. This emphasizes the necessity for a treatment viable for lower wage-earning families, as the stress of money along with an expecting infant generates PPD. C. Zlotnick et al. (2001), psychiatry experts, state 10-16% of pregnant women experience PPD associate with social dysfunction and marital maladjustment due to their environmental situations. They add “poverty” equates “with twice the rate” of PPD making this group of people a specific target for this condition. When mothers experience poverty, isolation, chaos, or the absence of a husband/father of child, it is a trigger towards PPD. Moreover, Health and Wellbeing researchers Kahneman & Deaton of Health at

Figure 1: Postpartum depression Image Source: Max Pixel

"In sum, physical health problems are a serious factor in finding a final treatment for PPD."

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"Moreover, IPT trials show potential benefits for future mothers and offspring health as well."

Princeton University found that “low-income” people tend to have “low life-evaluation[s] and low emotional well-being[s]” (2010). This is important because mothers of the lower class and income rates under $75,000 experience much lower rates of life positivity experiences and positive emotional reinforcements, triggering PPD, and calling for an economical, affordable and cost-effective treatment. Presently, the most popular and most used option to treat PPD is a pharmacological drug issued medical action known as antidepressants. According to M. Ahmadpanah et al. (2017) of substance abuse establishments, antidepressants like SSRIs' (Selective serotonin reuptake inhibitors) and citalopram are commonly prescribed to women inhibiting PPD symptoms. Conversely, these drugs are only recommended in cases of severe depression. Moreover, these drugs provoke detrimental pregnancy health side effects, including “dry mouth, sweating, nausea, or vertigo.” These problems cause many to steer away from this form of treatment, leaving their health at a detrimental risk by avoiding antidepressants. Additionally, P. Cuijpers et al. (2008) of Clinical Psychology at Amsterdam University reiterate pharmacological interventions are better for unrelated childbirth depressions. Mothers continuously worry about the long list of safety issues and side effects regarding breastfeeding, a special motherhood aspect. This is important because it causes women to “discontinue their antidepressants'' without informing their doctors, according to

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Bérard et al. (2019) of pharmaceutical specialties. Conclusively, antidepressant pharmacological treatments are unreliable for expecting mothers exhibiting PPD symptoms.

The Case for IPT Alternatively, a plausible solution to this problem is IPT, an attachment-focused psychotherapy, centered on resolving interpersonal, or communal, problems and recovery support. It can last from twelve to sixteen weeks, dependent on the extent of the depression the future mothers are facing. This therapy is already widely used among people experiencing depression. However, IPT is unpopular among lower economic standing mothers due to lack of awareness, understanding, and access. This therapy can be quite helpful for them, however, as it targets poor social support, role transition (pregnancy to motherhood), and common life stressors (Zlotnick et al., 2001). Analyzing and resolving these problems is crucial in preventing PPD, as they can change how a future mother views pregnancy and infantry, benefiting the child, mother, and father’s health and physical well-being. Moreover, IPT trials show potential benefits for future mothers and offspring health as well. Through overcoming critical life events, maternal mood, “PND” (Paroxysmal nocturnal dyspneashortness of breath), and anxiety, mothers have improved emotional regulation during the harder stages of pregnancy (Milgrom et al., 2005). This is important because it can avert childbirth damage which tends to come with

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PPD, including caesarean section and premature birth which are harmful towards the mother and infant. Moreover, IPT discourages the mother from feeling overstressed and decomplicates her pregnancy, which can prevent preterm delivery and allow for the mother and infant to be healthy after labor (Spinelli et al., 2003). In addition, IPT is available during all stages of pregnancy and after birth for however long the mother needs support. Hence depression symptoms are not under-diagnosed and PPD traits do not last long after birth or disappear before then. In brief, this therapy encourages healthy pregnancy experiences for families dealing with PPD, allows for a safe childbirth experience, and proper wellbeing of the family members. As well as helping physical health, IPT is also usable and beneficial toward the future mother’s health and neuropsychology. IPT aids the growing offspring as it has “positive effects” on their essential “neurodevelopmental processes” in the long run (Drury et al., 2016). This is important because it can encourage a healthy upbringing for the offspring. IPT works through mood improvements that mothers gain from this insightful therapy, a unique effect that is vastly different from pharmacological usage (Zlotnick et al., 2001). By ensuring that future mothers develop healthy and attentive behaviors towards their offspring, the child avoids forming depressive symptoms and anxiety disorders. Families can grow closer, and feelings of protection and caring arises for the child. IPT allows for healthy mental growth and prevents obstructive thoughts to arise in the mother.

Also, IPT is an economical solution for lower income expecting women. As claimed by K. Maehder et al. (2020), medical psychology professionals at Habsburg University, this therapy is very cost-effective which will serve economic principles for low-income families expecting a child, as it can be very “cost saving” at the expense of treatment intensity and length a patient needs. Continuation of the treatment can improve emotional evaluation as it allows for mothers to understand they are being heard. This is important because many mothers whose families' total income is lower than $75,000 can hurt their outlook on the emotional quality of everyday life and how often they experience negative emotions (Kahneman and Deaton, 2010). Depression is usually built through life experiences, which is why early diagnosis and treatment is critical. As tensions arise during pregnancy due to low rates of mothers experiencing positive emotions, mothers start to build up depressive symptoms. In short, mothers of lower economic class do not need to stress about finances of IPT treatment using this therapy and can focus on overcoming their depression and doing what's best for the offspring.

"As well as helping physical health, IPT is also usable and beneficial toward the future mother’s health and neuropsychology."

Limitations Contrarily, families do not look to IPT as an accepted treatment despite its worthwhile investment. Mothers can feel overwhelmed to attend all therapy sessions and may end up falling back to antidepressant medication to manage symptoms. This limitation has led to slow Figure 1: Alois Alzheimer’s memorial located at his final home in Wroclaw, Poland. The inscription is in German on the left and Polish on the right. It reads: “in memory of the great psychiatric neuropathologist who lived in this building in the years 1912-1915. The Polish Society for Psychiatry, and the German Society for Psychiatry, Psychotherapy and Neurology.” Alzheimer is credited as the first to characterize the neurodegenerative disorder known today as Alzheimer’s disease Source: Wikimedia Commons

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development and adoption of IPT. Moreover, mothers find “organizing themselves and their babies to attend sessions is overwhelming” (Milgrom et al., 2005). This sense of treatment fatigue is significant because it may become an excuse to miss sessions. Hence, IPT should be more flexible to support mother’s schedules. Also, more research is required to study if this treatment improves the child’s long-lasting health (Drury et al., 2016). Also, because some low socioeconomic status families may not speak English, there is a high demand for “bilingual” therapy options (Spinelli and Endicott, 2003). For the therapy to be effective, mothers need to be able to communicate with their therapist, which is difficult in settings with cultural or language barriers, fatigue, or access.

Further Work In the future, IPT needs to be more accessible to these low-income families dealing with PPD. This includes increasing social support and maximizing opportunities (Milgrom et al., 2005). Increased accessibility promotes flexibility and removes stress for low-income families. Also, making the treatment feasible for fathers too is important (if they are experiencing depression symptoms) because IPT for PPD is more mother and child relationship oriented. Nevertheless, these reforms do not require large funds and effort, and within the next few years, large publicizing methods and popularity can help solve these limitations through creating a larger platform for the treatment and making it possible to treat fathers and be more accessible for couples experiencing PPD in general.

Conclusion In conclusion, PPD is a serious condition which can negatively impact the physical and mental wellbeing of the mother, offspring, and family unit. PPD is exacerbated among low-income mothers and their families with annual incomes lower than $75,000, due to financial stressors complicating depression when there is a child on the way. Current standard of care is to address PPD with antidepressants to withhold depressive symptoms, however lack of health and economic benefits as well as numerous safety issues call for alternative therapies. A feasible option which addresses the physical and mental health of the mother and can improve their relationship with their offspring is IPT. This recovery and communication-focused therapy targets the issues low-income mothers face in the long term and day to day, improving their health and resolving problems as they progress through the treatment. IPT is cost-effective and more reliable 220

than antidepressants. Research and development advances in IPT will overcome hurdles around flexibility and improve therapeutic efficacy. References Ahmadpanah, M., Nazaribadie, M., Aghaei, E., Ghaleiha, A., Bakhtiari, A., Haghighi, M., Brand, S. (2017). Influence of adjuvant detached mindfulness and stress management training compared to pharmacologic treatment in primiparae with postpartum depression. Archives of Women's Mental Health, 21(1), 65–73. doi: 10.1007/s00737-017-0753-6 Altshuler, L. L., Cohen, L. S., Vitonis, A. F., Faraone, S. V., Harlow, B. L., Suri, R., … Stowe, Z. N. (2008). The Pregnancy Depression Scale (PDS): a screening tool for depression in pregnancy. Archives of Women's Mental Health, 11(4), 277–285. doi: 10.1007/s00737-008-0020-y Augusto, A., Kumar, R., Calheiros, J. M., Matos, E., & Figueiredo, E. (2000). Post-natal depression in an urban area of Portugal: comparison of childbearing women and matched controls. Psychological Medicine, 26(1), 135–141. doi: 10.1017/ s0033291700033778 Bérard, A., Sheehy, O., Zhao, J.-P., Chambers, C., Roth, M., Bozzo, P., … Dieter, K. (2019). Impact of antidepressant use, discontinuation, and dosage modification on maternal depression during pregnancy. European Neuropsychopharmacology, 29(7), 803–812. doi: 10.1016/j. euroneuro.2019.06.007 Cuijpers, P., Brännmark, J. G., & Straten, A. V. (2007). Psychological treatment of postpartum depression: a metaanalysis. Journal of Clinical Psychology, 64(1), 103–118. doi: 10.1002/jclp.20432 Drury, S. S., Scaramella, L., & Zeanah, C. H. (2016). The Neurobiological Impact of Postpartum Maternal Depression. Child and Adolescent Psychiatric Clinics of North America, 25(2), 179–200. doi: 10.1016/j.chc.2015.11.001 Figueiredo, B., Pacheco, A., & Costa, R. (2007). Depression during pregnancy and the postpartum period in adolescent and adult Portuguese mothers. Archives of Women's Mental Health, 10(3), 103–109. doi: 10.1007/s00737-007-0178-8 Kahneman, D., and A. Deaton. “High Income Improves Evaluation of Life but Not Emotional Well-Being.” Proceedings of the National Academy of Sciences, vol. 107, no. 38, July 2010, pp. 16489–16493., doi:10.1073/pnas.1011492107. Kiviruusu, O., Pietikäinen, J. T., Kylliäinen, A., Pölkki, P., Saarenpää-Heikkilä, O., Marttunen, M., … Paavonen, E. J. (2020). Trajectories of mothers’ and fathers’ depressive symptoms from pregnancy to 24 months postpartum. Journal of Affective Disorders, 260, 629–637. doi: 10.1016/j. jad.2019.09.038 Maehder, K., Löwe, B., Härter, M., Heddaeus, D., Knesebeck, O. V. D., & Weigel, A. (2020). Psychotherapists’ perspectives on collaboration and stepped care in outpatient psychotherapy—A qualitative study. Plos One, 15(2). doi: 10.1371/journal. pone.0228748 Milgrom, J., Negri, L. M., Gemmill, A. W., Mcneil, M., & Martin, P. R. (2005). A randomized controlled trial of psychological interventions for postnatal depression. British Journal of Clinical Psychology, 44(4), 529–542. doi: 10.1348/014466505x34200

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O'hagan, A. (2015, July 17). The Happiness Project. Retrieved from https://www.nytimes.com/2015/07/17/t-magazine/ happiness-project-disneyland.html Spinelli, M. G., & Endicott, J. (2003). Controlled Clinical Trial of Interpersonal Psychotherapy Versus Parenting Education Program for Depressed Pregnant Women. American Journal of Psychiatry, 160(3), 555–562. doi: 10.1176/appi.ajp.160.3.555 Zlotnick, C., Johnson, S. L., Miller, I. W., Pearlstein, T., & Howard, M. (2001). Postpartum Depression in Women Receiving Public Assistance: Pilot Study of an InterpersonalTherapy-Oriented Group Intervention. American Journal of Psychiatry, 158(4), 638–640. doi: 10.1176/appi.ajp.158.4.638

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Overview of Inequities in Cancer Composition, Mortality, and Treatment STAFF WRITERS: ANGEL UGO-NWAUWA, VAISHNAVI KATRAGADDA, LAUREN FERRIDGE, MATTHEW LUTCHKO, SOYEON CHO, GEORGIA DAWAHARE, ABIGAIL FISCHER, JUSTIN FAJAR, MAEEN ARSLAN, SARAH LAMSON, ASHNA KUMAR, ANUSHKA BHATIA, ADVAITA CHAUDHARI EDITORIAL BOARD WRITER: ANAHITA KODALI

Cover Image: Cancer can occur in every bodily tissue. Pictured above is an osteosarcoma cell – the blue shows the cell’s DNA, the yellow shows the cell’s mitochondria, and the purple shows actin filaments of the surrounding muscle tissue. Source: Flickr

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Introduction Cancer was the second global leading cause of death in 2017, behind only cardiovascular disease (Ritchie and Roser, 2018). In 2020, it claimed the lives of 600,000 people in the US (National Cancer Institute, 2020). The onset of cancer follows a series of steps, beginning with a single cell’s accumulation of gain-of-function mutations in proto-oncogenes and loss-of-function mutations in tumor suppressor genes (Adjiri, 2016). Proto-oncogenes promote growth, proliferation, and survival of cells while tumor suppressor genes normally function to restrict cells from growing or dividing uncontrollably (Lee and Muller, 2010). Originally, as a result of mathematical work by Nordling in 1953, the general consensus had been that a sequence of at least six or seven of such mutations was required for oncogenesis. However, much more recent studies in a certain type of lung and colon cancer have revealed that

only three sequential mutations can be sufficient to induce cancer (Tomasetti et al., 2015). As whatever threshold amount of the specific mutations required in an individual is reached, a cell is transformed into a cancerous cell. Upon this transformation, the cell grows and proliferates rapidly; the two daughter cells it produces inherit the cancer-driving mutations and thus are also cancerous. This cycle continues and the mass of progenitor cells eventually builds up. All of the cells in the lineage have mutations that allow them to circumvent the mechanisms normally employed to keep them from growing too large or dividing too rapidly. Over time, the accumulation of the cancerous cells in this lineage develops into a tumor, followed by a manifestation of symptoms especially as the tumor may physically interfere with necessary bodily functions. According to the American Cancer Society, approximately 40% of males and 39% of females develop cancer at some point in their lifetime. Many studies have looked at the possibility that DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

specific dietary components or nutrients are associated with increases or decreases in cancer risk. For example, alcohol is a known cause of cancer. Heavy or regular alcohol consumption increases the risk of developing cancers of the oral cavity (excluding the lips), pharynx, larynx, esophagus, liver, breast, colon, and rectum. The risk of developing cancer increases with the amount of alcohol a person drinks (National Cancer Institute, n.d.). Other studies have found that consumption of fruits, vegetables, and whole grains decreases the risk of certain cancers. Secondary prevention trials and observational prospective epidemiologic studies have demonstrated the efficacy of a Mediterraneantype dietary pattern to decrease risk of both cancer and cardiovascular diseases (Williams & Hord, 2005). In addition to diet, a variety of environmental factors can cause cancer or increase risk. For example, exposure to ultraviolet light increases the risk of cancer (National Cancer Institute, 2020). Additionally, infectious agents, such as viruses, bacteria, and parasites can either directly cause cancer or increase risk through a variety of mechanisms. These mechanisms include disrupting cell signaling, weakening the immune system, and causing chronic inflammation (National Cancer Institute, 2019). One classic example of this is human papillomavirus (HPV), which causes nearly all cervical cancers and most anal cancers (National Cancer Institute, 2019). Exposure to carcinogens, cancer-causing substances, is also a risk factor for cancer. In the US, exposure to carcinogens in the workplace is regulated based on recommendations from the National Toxicology Program (NTP), a division of the US Department of Health and Human Services, and the International Agency for Research on Cancer (IARC), which is a World Health Organization (WHO) agency (National Cancer Institute, 2019). Some of the commonly known carcinogens currently on the list of known carcinogens include asbestos, coal tars, and tobacco (National Toxicology Program, 2021). As more studies have been conducted on the various risk factors for cancer, it has become increasingly evident that cancer is also driven by social and structural determinants of medicine. This paper aims to overview these determinants – it reviews the ways in which racial/ethnic identity, socioeconomic class, geographical region, and other factors can influence the incidence, mortality, and treatment for cancer.

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Figure 1: This figure depicts the life of a cancer cell. During replication, a piece of DNA gets mutated. This mutation occurs in a proto-oncogene and/ or a tumor suppressor gene, damaging the cell’s mechanism to control replication. After the cell replicates, both daughter cells will contain this mutation. As the cycle continues, more and more mutations accumulate until the cells begin to divide rapidly and form the cancerous tumors.

Incidence & Mortality – Racial/Ethnic Disparities Cancer Burden for the Black Community Cancer is the second leading cause of death among Black Americans, surpassed by only heart diseases. Among Black females, breast cancer is the most commonly diagnosed cancer. Lung cancer is the second largest group, followed by colorectal cancer and cancer of the uterine corpus. Together, these four cancer types make up more than half of the new cancer cases for Black females. Among Black males, prostate cancer is the leading site of cancer incidence, followed by lung cancer, colon/rectal cancer and cancer of the kidneys or renal pelvis. The deadliest cancer in both black males and females is lung cancer. For Black females, breast cancer is the second deadliest cancer, followed by colon/rectal cancer and pancreatic cancer. For Black males, prostate cancer is the second deadliest cancer, again followed by colon/rectal cancer and pancreatic cancer (American Cancer Society, 2019). The ranking of cancer incidence and mortality by cancer type generally mirrors those of the general population with breast cancer having the highest incidence rates, followed by prostate cancer, lung cancer, colon/rectal cancer and cancers of the uterus and corpus; however, it should be noted that breast cancer incidence for Black females is significantly higher than that of the general population (CDC, 2017). Upon examination of incidence rates of the most common cancer types by race, it’s evident that Black Americans are the most likely subgroup to develop colorectal cancer. Black men are also much more likely to develop prostate cancer than all other racial subgroups. While the highest rates of breast cancer and lung cancer incidence occurs among non-Hispanic White Americans, Black Americans come in at a close second for both cancer types (American Cancer Society, 2019; American Cancer Society, 2020). Additionally, Black Americans have the second highest rates of renal cancer in the country; they are surpassed only by Native Americans and Alaskan Natives.

Image Source: Wikimedia Commons

"Upon examination of incidence rates of the most common cancer types by race, it’s evident that Black Americans are the most likely subgroup to develop colorectal cancer."

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As of 2017, Black Americans had the second highest incidence rates of cancer overall in the US, surpassed by only non-Hispanic White Americans (American Cancer Society, 2020).

"Nevertheless, Black Americans are disproportionately more likely to die of their cancer than all other races and ethnicities."

Nevertheless, Black Americans are disproportionately more likely to die of their cancer than all other races and ethnicities. Black Americans are the most likely racial group to die of colorectal cancer, prostate cancer, breast cancer. Black Americans are also the third most likely racial group to die of kidney/renal cancer (American Cancer Society, 2020). Overall, for most cancers, at each stage of diagnosis, five-year relative survival is lower for Black Americans than for White Americans (DeSantis et al., 2020). Noteworthily, Black Americans do not appear to have significantly different lung cancer mortality rates from non-Hispanic White Americans (American Cancer Society, 2019; American Cancer Society, 2020). Further analysis reveals that one possible reason why Black Americans suffer higher mortality to most cancers may be because there’s a racially specific difference in the incidence rates of cancer subtypes (American Cancer Society, 2020; Kohler et al., 2015). Several studies have noticed this trend (Acheampong et al., 2020; Kong et al., 2020; Kohler et al., 2015). One such study looked at the incidence rates of breast cancer subtypes by race. They found that the most common type of breast cancer among all races is HR+/HER2breast cancer, a subtype of breast cancer known to have the best prognosis; white Americans experience the highest rates of this type of cancer. However, Black Americans had the highest rates of triple-negative breast cancer, the breast cancer subtype with the worst prognosis (Kohler et al., 2015). Kohler et al. (2015) suggest that differences in biological/genetic risk and

social risk, along with differences in screening rates, may drive this racially specific difference incidence rates of cancer subtypes. Differences in socioeconomic status, lifestyle, nutrition, practice of risk behaviors, rates of obesity and health access may also play major roles in explaining the high cancer mortality noticed among Black Americans (Akinyemiju et al., 2018; Hanson et al., 2019; Karanth et al., 2019; Kehm et al., 2018; Kish et al., 2014; Özdemir & Dotto, 2017; Schmitz et al., 2013). Cancer Burden for the Hispanic Community The Hispanic community makes up about 18% of the US population. They face unique challenges that present themselves in cancer-related health disparities. When compared to non-Hispanic White people, Hispanics have lower rates of cancer overall, However, Hispanics were found to have higher rates of infection-related (stomach, liver, cervical) and gallbladder cancer (American Cancer Society et al., 2018) When talking about cancer rates among the Hispanic community, it is important to note that country of origin plays a role in cancer outcomes. One reason is because of a process called “acculturation,” which is the balancing of two cultures. When applying this to Hispanic people, specifically Hispanic immigrants, both negative and positive effects are evident. There seems to be a negative effect of acculturation on diet. One study found that that more acculturated individuals consume more fast food, fatty snacks, and added fats than less acculturated individuals (Ayala et al., 2013). This would attribute to a higher rate of obesity, which has been linked to an increased risk of 13 types of cancer. This is especially concerning considering that Hispanic people experience the second highest prevalence of obesity among minority groups. Acculturation

Figure 2: Black Americans have the highest rates of triple negative breast cancer, which is the deadliest form of breast cancer. Pictured above is a stained sample of triple negative breast cancer. The darker stained regions may be cancerous. Image Source: Wikimedia Common

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also increases the likelihood of smoking for Hispanic women and drinking, though the effect of drinking varies between the different heritage groups under the term “Hispanic” (Bethel et al., 2005). Both smoking and drinking increase the risk of cancer. In general, American-born Hispanic people have a higher incidence rate of cancer and have poorer survival rates than their foreign-born counterparts (Stern et al., 2016). However, it is important to note that much of the current demographic research that has been done on American Hispanic communities lumps together all heritage groups. This muddles the data, and one reason for this is that the process of acculturation is different for each group (Pinheiro et al., 2017). Because of this, current research efforts have been unable to find a clear point of intervention to decrease cancer incidence and mortality in Hispanic populations. Further research that separates different heritage groups and studies the process of acculturation will be critical in curbing both. Cancer Burden for the Asian-American Community Surpassing Hispanics as the most rapidly growing racial/ethnic group in the US, there are currently 17.3 million Asian Americans (AAs), representing 5.6% of the US population. That number is expected to exceed 40 million by 2050 (Thompson et al., 2016). AAs generally have lower cancer rates than the non-Hispanic White population. However, disparities still exist in certain types of cancer. From 2012-2016, Asian/Pacific Islander (AAPI) men were 50% less likely to have prostate cancer, as compared to non-Hispanic White men but twice as likely to have stomach cancer. Similarly, although AAPI women are 30% less likely to have breast cancer than non-Hispanic White women, they are twice as likely to have stomach cancer (The Office of Minority Health, n.d.). Both AAPI men and women have almost twice the incidence of liver and inflammatory bowel disease (IBD) cancer, as compared to the non-Hispanic White population. Finally, AAPI men are twice as likely to die from stomach cancer as compared to non-Hispanic White men, and AAPI women are 2.8 times as likely to die from the same disease, as compared to non-Hispanic White women (The Office of Minority Health, n.d.). Stomach and liver cancer mortality combined accounts for 15-25% of cancer deaths, but less than 5% of cancer deaths in non-Hispanic White people (Thompson et al., 2016).

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AAs are the only racial/ethnic group in the US for whom cancer is the leading cause of death in men and women (for all other racial/ethnic groups, heart disease stands at number one). AAs face a confluence of cancer risks, with high rates of cancers endemic to their countries of origin due to infectious and cultural reasons, as well as increasing rates of “Western” cancers that are due in part to assimilation to the American diet and lifestyle. Despite the clear mortality risk, AAs are screened for cancers at lower rates than the majority of Americans. Solutions to eliminate the disparity in cancer care are complicated by language and cultural concerns of this very heterogeneous group. There is an urgent need to improve cancer screening for the AA population. To do so, health care providers will need to be aware of these facts, including the profile of cancer risks among different Asian subpopulations, and have the necessary tools to communicate cancer risks and benefits of screening. AAs will need to be educated and encouraged to be advocates for their health, which includes improving access to insurance and health care resources (Lee et al., 2021). Cancer Burden for Indigenous Communities Native American tribes are disproportionately affected by cancer and are more likely to be affected by certain cancers than non-Hispanic White people. From a review study between 2012 and 2016 it was observed that American Indian/ Alaska Native (AI/AN) were twice as likely to have liver cancer, 40% more likely to have stomach cancer and twice as likely to die from stomach cancer than non-Hispanic White men. Similarly, AI/AN women are 2.3 times more likely to have and twice as likely to die from liver cancer and are 20% more likely to have kidney/renal pelvis cancer than non-Hispanic White women (Cancer and American Indians/Alaska Natives The Office of Minority Health, n.d.). Trends for incidence and mortality are both increased in AI/ AN communities and the reasons for such trends are complex and include several factors.

"AAs are the only racial/ethnic group in the US for whom cancer is the leading cause of death in men and women"

Poverty and low socioeconomic status on reservations and within AI/AN communities is a big driver of increased cancer rates. There is a lack of resources to promote healthy habits and the medical resources available to them are severely underfunded. Without equal access to equal medical care, smoking rates are much higher in AI/AN populations, which is one contributor to the high incidence of lung cancer in these communities. Poverty perpetuates smoking addictions and without any help to fight addiction, lung cancer incidences will continue

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to increase. Poverty also influences eating habits. Poor diets that lack necessary nutrients and low accessibility to fresh food leads to high obesity rates and thus high incidences of kidney cancer. Additionally, there is a high prevalence of hepatitis C virus (HCV) in AI/AN communities, which is a known risk factor of liver cancer. Regulating and identifying HCV cases earlier, as attempted by the Cherokee Nation Health Services screening support tool, has influenced a 14% increase in individuals eligible for screening, thus hopefully influencing liver cancer trends (Melkonian et al., 2021).

"The combination of patient, physician, and healthcare factors in combination with systemically perpetuated low socioeconomic factors are what creates the complex source of increased cancer incidence and mortality in indigenous populations."

Lack of access to a proper health care system for AI/AN communities is the other major influencer of cancer incidence. Although there are treaties between governments and Native nations, they are often not upheld, which results in reservation health sites being underfunded. This forces those seeking screening or medical care to leave their reservations for proper appointments. Having to travel for care presents another barrier to receiving healthcare. If people have work, they may not get the time off to drive so far away for an appointment. Financially, paying for gas and then for the doctor’s appointment itself presents monetary issues which has a greater burden on lower socioeconomic communities (Lynch, 2019). Additional barriers to care manifests within AI/ AN medical mistrust and low satisfaction with health care. Patient related factors present as low health literacy concerning diseases, cultural differences and mistrust of physicians and hospitals. Physician related factors can include lack of cultural competence and appreciation when caring for a particular racial/ethnic group. Lastly, health-system related factors concern access to and funding for screening and care (Guadagnolo et al., 2009). The combination of patient, physician, and healthcare factors in combination with systemically perpetuated low socioeconomic factors are what creates the complex source of increased cancer incidence and mortality in indigenous populations.

Disproportionate Burden of Cancer Incidence & Mortality – Economic Disparities The National Institute of Health has described poverty as a carcinogen. A study conducted by the National Cancer Institute found that persistent poverty in US counties was linked to a higher probability of dying from cancer. Areas of persistent poverty were defined by at least 20%

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of its inhabitants living below the federal poverty line from 1980 to current times and comprised 12% of national counties. The southeastern US had a higher incidence of persistent poverty counties, many characterized by rural landscapes and higher percentages of minority groups in comparison to non-persistent poverty counties. Prior research has demonstrated rurality is positively associated with cancer mortality, as rural areas present a variety of barriers, including decreased access to quality healthcare. In counties without persistent poverty, 2007-11 data showed that 179.3 in 100,000 people died from cancer. A 12% increase was observed for persistent poverty counties which has a cancer mortality incidence of 201.3 per 100,000 people. Increased cancer mortality was true of a variety of disease types including lung, stomach, and liver cancers (National Cancer Institute). Several factors can be attributed to this correlation between socioeconomic status and disease mortality. Harmful behaviors like smoking and drinking take place at higher rates in poorer areas, and the use of substances like tobacco and alcohol increases cancer risk. Unregulated exposure to sunlight, ionizing radiation and infectious microorganisms are also environmental carcinogens that underprivileged people are more vulnerable to. Food consumption choices also impact one’s likelihood of developing cancer. Because poorer communities have restricted access to healthier foods like fresh fruits and vegetables, their diet could contribute to obesity which, in turn, predisposes individuals to cancer development. In less privileged populations, there is also an affordable healthcare deficit; decreased access in combination with no means to pay for insurance leads to increased suffering and mortality. (Heidary et al., 2013). Researchers emphasized understanding the historical context behind their findings and using that information to address the cancer inequities in these communities by helping foster an environment that promotes public health. Racism, crime, and violence ― all factors that feed into poverty ― also need to be evaluated and mitigated (National Cancer Institute).

Disproportionate Burden of Cancer Incidence & Mortality – Geographic and Environmental Disparities Cancer Burden for Rural Americans While cancer rates are lower in rural America compared to metropolitan centers, cancer mortality is higher in rural areas. The CDC

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conducted a study from 2004 to 2015 to determine whether people living in rural areas of the US were more likely to die from cancer than people living in metropolitan areas. The data used in the study was drawn from the CDC National Registries and the National Cancer institute, and the sample represented 97% of the US population. USDA ERS rural-urban continuum codes were used to classify counties as either nonmetropolitan or metropolitan. Nonmetropolitan counties were further classified based on density and proximity to metropolitan areas into nonmetropolitan rural and nonmetropolitan urban areas, though many differences between the two categories were not significant (Henley et al., 2017). After adjusting for age, the study found that cancer incidence was lower in rural areas compared to all other county classifications. Death rates were decreasing across the reporting period, but death rates decreased more quickly in metropolitan areas (-1.6%) compared to nonmetropolitan areas (-1.0%). Rural counties had higher death rates specifically for cancers related to smoking and HPV, as well as for cancers that can be prevented by screening, such as colorectal and cervical cancers. However, the authors note that some of the disparities observed in the study may be accounted for by modifiable risk factors, including smoking, obesity, insufficient physical activity, UV exposure, and exposure to cancercausing infectious agents. Disparities might also

be driven by differences in adherence to screening guidelines or differential availability of clinical preventive care (Henley et al., 2017). Zahnd et al. (2018) replicated the results, finding that cancer rates associated with modifiable behavioral risks (including tobacco, HPV, and some preventive screening measures) were higher in rural areas compared to urban areas between 2009 and 2013. Researchers note that rural residents may be at a socioeconomic disadvantage when it comes to obtaining health insurance and seeking care, as they are more likely to have lower educational attainment, lower income, and higher unemployment rates compared to people living in urban areas. Additionally, there is a shortage of healthcare providers in many rural areas, and oncologists, in particular, are underrepresented (Yabroff et al., 2020). Patients with cancer in rural areas can experience problems accessing treatment because they may have to travel long distances to seek care (Piana, 2018). Cancer Burden in American Cities Redlining was first introduced in the 1930s by the federal Home Owner’s Loan Corporation (HOLC) in attempt to normalize residential racial segregation (Krieger et al., 2020). These areas served as an institutional mechanism to ‘protect’ White people from interacting with Black people and became characterized by poor housing and living conditions. These neighborhoods had unequal access to municipal services and were Figure 3: This is a map of the regions in the US that are “entirely” rural. Rurality is measured based on statistical calculations of the population of people in an area and distance from urban metropolitan areas. Those living in completely rural counties may be at a higher risk for cancer as compared to those living in urban areas. Image Source: US Census

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more likely to have spending and services cut by the government. This meant that they lacked equal recreational facilities and medical care. As a result of these limitations reinforced by racial segregation, redlined areas were characterized by their low-income and low socioeconomic status (Williams & Collins, 2001).

"Although redlined districts are not technically enforced by law today, the effects of historical redlining remain apparent. To this day, these neighborhoods have high numbers of various racial/ethnic populations and are disproportionately underfunded and under-resourced."

Racial segregation placed redlined communities in underdeveloped areas and in poor housing meaning residents have a higher risk of being exposed to environmental toxins, increased access to tobacco, higher exposure to tobacco advertising, less physical activity, poor access to healthy food, and—most importantly—lack of access to equal and quality healthcare (Landrine et al., 2017). The environment created increased cancer risk factors in an area with no institutional aid or benefit to people living there, making it disproportionately harder to receive the same attention and quality of care. Although redlined districts are not technically enforced by law today, the effects of historical redlining remain apparent. To this day, these neighborhoods have high numbers of various racial/ethnic populations and are disproportionately underfunded and underresourced. This lack of resources has made socioeconomic mobility difficult, which prevents access to medical insurance. This, in turn, discourages people from frequent doctor’s visits, and therefore can influence the general health of people in low-income communities – a potential exacerbator for increased cancer incidence (Williams & Collins, 2001). Indeed, people living in previously redlined areas have an elevated risk for late-stage cancer diagnosis. Between 20012015, there has been an increased prevalence of breast and lung cancer in areas associated with historical redlining. Similar trends have been observed in areas that are historically redlined but are now wealthier, showing that even if these areas are able to economically develop, redlining has deeply rooted effects that may take generations to overcome (Krieger et al., 2020). Going forward there is hope that increased research into effects of redlining on contemporary health will inform debates and plans for policy and resource allocation to further efforts for fair housing and public and health resources. Increasing easy and affordable access to safe living environments to promote healthier living styles will be a first step towards decreasing cancer incidence in these communities (Krieger et al., 2020).

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Cancer Concerns in the Environment and Behavioral Factors While genetic factors and predisposition to disease do play a role in cancer incidence, extensive research has shown that environmental factors may perhaps pose a stronger and more imminent threat to disease development. As a matter of fact, 80-90% of malignant tumors are expected to be caused by various external factors. According to an analysis by the WHO, roughly 35% of all deaths due to cancer are caused by modifiable risk factors, such as access to a more nutritious diet or living in a more environmentally healthy neighborhood (Lewandowska et al., 2019). Physical factors include exposure to environments high in electromagnetic fields, with certain occupations putting people at higher risk of exposure to these fields. One study found that there was a 6.5-fold increased risk of breast cancer among telecommunication technicians, while another study showed that women living in a 300-meter radius from power lines had double the risk of breast cancer. Exposure to radiation can lead to increased risk as well. Even in cases of radiation exposure as a treatment for other cancer has led to risk for developing even more cancerous cells. Aside from ionizing radiation, ultraviolet radiation can lead to cancer as well. UV light excites electrons in the bonds between thymines, which results in thymine dimerization. These result in kinks in the DNA which results in more error-prone DNA replication, which can cause mutations in proto-oncogenes and tumor suppressor genes. Aside from ionizing radiation, ultraviolet radiation can lead to cancer as well, with damage to both the pathway that mediates apoptosis of already dead cells and an increase in the pathway that promotes the proliferation of premature cells. Chemical factors additionally lead to greater incidence of cancer. Chemicals in the environment include chemicals in the household or in car emissions, industrial pollutants, toxic industrial waste, pesticides, or other agricultural or industrial products. Additionally, an increased exposure to infections, as is characteristic of highly populated regions or in areas with high contact with animals, is associated with cancer. Certain diseases have been associated with later development of cancer, such as pneumonia leading to lung cancer or Epstein-Barr virus leading to nasopharyngeal cancer (Lewandowska et al., 2019). All of these factors cause a disproportionate incidence of cancer among those in lower socioeconomic groups. Due to the compounding effects of systematic discrimination against

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minority groups, many people in minority demographics are restricted to more hazardous occupations that pay less, meaning they experience exposure to carcinogens at work and at home. These poorer neighborhoods are often in environmentally hazardous areas, closer to factories or toxic waste sites. These results of disparity among race and socioeconomic status are translated globally as well, with a 20% higher overall cancer rate in the poorest 20 countries in comparison with the most affluent countries. Specifically, lung and liver cancer were found at rates that were 40% higher in these countries. This data aligns with the environmental factors highlighted above; exposure to carcinogens such as chemicals in the air in poorer neighborhoods or occupational hazards lead to lung cancer at higher rates (Siegel, Miller, and Jemal; 2019). As seen, dangerous environmental factors that disproportionately affect those that identify with certain racial or socioeconomic groups experience cancer at rates higher than average due primarily to the effects of systematic inequity and environment rather than genetic factors. Various studies reveal a connection between diet and cancer. Since 30 to 40 percent of all cancers are preventable by lifestyle and dietary changes, unequal access to healthy dietary options increases the risk for cancer (Donaldson, 2004). While the proportion of people with poor quality diets has decreased from 55.9% to 45.6% between 1992 and 2012, there are many disparities that are increasing based on race, ethnicity, education, and

income level. In the US, 11% of households have food insecurity, meaning that they have limited food options, often including low-cost unhealthy foods. Within this 11%, food insecurity is more common among Black, Hispanic, and Native American households (Belanger et al., 2020). However, it is important to note that the research on the link between diet and cancer is light. Many studies have conflicting findings, and some dietary options have inverse effects on different types of cancer. For each cancer type, different foods can affect the likelihood of that cancer in a person; however, these studies require more investigation. For example, studies have found that salt-preserved foods raise the chances for nasopharyngeal and stomach cancer while alcohol increases the risk for liver and stomach cancer. However, alcohol is associated with a decreased risk for kidney cancer. Researchers have been working to determine whether eating fruits and vegetables can decrease the risk for cancer; early studies found both this to be true, but a study by the World Cancer Research Fund found both not associated with a lower risk of cancer. The conflicting studies on the connection between diet and cancer make it difficult to determine what diets will best reduce risks for cancer. At the same time, a study from the UK found that alcohol increases cancer risk by 3.3%, dietary fiber increases cancer risk by 3.3%, and processed meats increase cancer risk by 1.5% (“Diet, nutrition, and cancer risk,” 2020). From country to country, these statistics vary, Figure 4: Excessive alcohol consumption can increase the risk of several types of cancer. Image Source: Flickr

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but these three diet options still have a significant effect on cancer risk. Since the information on diet’s link to cancer is still under investigation, understanding the exact dietary options to avoid is difficult. That being said, populations that have higher access to diverse dietary options will be better prepared to adjust their diets once more concrete research is conducted.

Cancer and Disease Comorbidities

"In fact, about 20% of all cancers are caused by excess weight; postmenopausal women are at an even higher risk for obesityrelated cancer."

Obesity Obesity is strongly related with cancer development. In fact, about 20% of all cancers are caused by excess weight; postmenopausal women are at an even higher risk for obesity-related cancer. There are many links between the two diseases, though the exact mechanism by which the two are related is still unknown. Currently, there are a few prevailing theories about what links the two. One focuses on the role of insulin. Excess body weight, as seen in obese patients, is directly correlated to insulin resistance and hyperinsulinemia (higher-than-normal levels of blood insulin). Hyperinsulinemia has been linked to faster growth and higher aggressiveness of several cancers, including colorectal, endometrial, liver, pancreatic, and postmenopausal breast cancers. This may be because insulin has anabolic and antiapoptotic effects, both of which promote the formation of tumors. Other researchers have looked at the dysregulation of estrogen in obesity; the obese condition can increase the level of circulating estrogen in the body, which can contribute to breast and endometrial cancer. Finally, some researchers have focused on the role of adipose tissue – obese patients have large amounts of adipose tissue, which has several metabolic and endocrine activities which have been related to the onset of cancer (Pergola & Silvestris, 2013). Likely, it is the interplay of each of these systems and more that leads to cancer in obese patients. There are several disparities in obesity distribution across the US. Some are driven by racial/ethnic factors. For example, significantly more Black and Hispanic Americans are obese than their Asian and White counterparts; these disparities exist for both adults and children. Within the categories of “Asian” and “Hispanic,” there are many variations within BMIs of different heritage groups. Though only 10.9% of Asian Americans are obese, Chinese Americans have an average BMI of 24.9 (which falls just under the cut-off for overweight BMI), Indian Americans have an average BMI of 25.8, and Filipinos Americans have an average BMI of 27.3. For Hispanics who were born in the US, Cubans have an average BMI of 29.5 (which

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falls just under the cut-off for obese BMI), Puerto Ricans have an average BMI of 30.6, and Mexicans have an average BMI of 31.1 (Krueger & Reither, 2016). There are also significant socioeconomic disparities – the proportion of obesity in lower socioeconomic classes is significantly higher than it is in higher socioeconomic classes, particularly for high income countries (like the US) (Hoebel et al., 2019). Geography builds on both of these disparities. There is a higher proportion of obese Black Americans in the South, while there is a lower proportion of obese Hispanic Americans in the Northeast. Additionally, unemployed adults in the West and Midwest are at higher risk for cancer than unemployed adults in other regions (Myers et al., 2015). Given the social and structural disparities that exist in obesity composition, there are also likely disparities that exist in obese cancer patients based on race, socioeconomic status, geography, and other factors, complicating the preexisting disparities for cancer patients alone. HIV/AIDS Human immunodeficiency virus (HIV) and acquired immunodeficiency syndrome (AIDS) are linked to higher incidence of several types of cancer. HIV can be transmitted several ways, including via blood and transplanted organs, as well as from mother to child during pregnancy and birth, or after birth as a result of transmission through breastfeeding. However, the majority of infections are transmitted sexually, via semen or vaginal fluid (German Advisory Committee Blood, 2017). Upon infection, the human immunodeficiency virus replicates in and destroys, thus depleting, CD4+ T helper cells that are vital to the functions of the immune response (Verma et al., 2019). Over time it progresses to AIDS, a serious disease associated with increased susceptibility to infection due to a weakened immune system (Janeway et al., 2001). Behind AIDS, cancer is the global leading cause of death among those with HIV (Smith et al., 2014). HIV infection may present a higher risk of cancer in those infected via multiple mechanisms; CD4+ T helper cell depletion weakens the immune system’s ability to detect and destroy cancer early on, and viral replication by HIV may promote signaling that induces proliferative and/or antiapoptotic characteristics in host cells, both hallmarks of cancer. HIV infection may contribute to increased risk of human papillomavirus (HPV)-driven cervical cancer in women, as immunodeficiency decreases their bodies’ ability to fight HPV infection. Non-Hodgkin’s lymphoma, a cancer starting in the white blood

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Figure 5: The HIV virus (which is depicted in yellow in the figure) can elevate the risk of several diseases, including cancer. HIV infection is highly driven by social and structural factors, including race and LGBT status. Image Source: Flickr

cells, is ten times more common in those infected with HIV than in others. Frighteningly, lung and anal cancer are also frequent comorbidities of HIV, with their incidence being three and thirty times higher, respectively, in HIV patients than in those without HIV (Casper et al., 2017). While HIV comes with elevated risk of cancer, it also sees dramatic racial disparities in incidence of infection. Black Americans account for only about 13% of the US population, but their HIV infections constituted 44% of the countrywide diagnoses in 2011. Notably, the disparity has been widening rather than narrowing; a decade prior to that, HIV infections in Black Americans constituted only 25% of diagnoses. As of 2011, Black men were six times more likely than White men to be newly diagnosed and for women the factor jumped to fifteen. These racial disparities could likely be attributed to disparities in prevention education between different communities (Williams et al., 2013). There are also disparities in HIV infection associated with sexuality. Most notably, young homosexual men are significantly more likely to face HIV infection; the risk is due to social conditions, sexual networks, and increased biological chance of transmission through anal sex (Everett et al., 2014). As there is no cure for HIV, the best way to avoid its effects is by prevention measures through education, especially on practicing safe sex. However, pivotal to those already infected has

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been antiretroviral therapy (ART), which has largely transformed AIDS from being completely fatal to an often-well-managed chronic disease (Bhattacharya, 2018). Although disparities between nations are significant and must be addressed moving forward, ART has allowed for an increase in life expectancy for twenty-year-old HIV-positive individuals from about 39 years to near the life expectancy of the general population (over 70 years) (Wandeler et al., 2016). Human Papillomavirus Human papillomavirus (HPV) is a sexually transmitted disease that can result in cervical cancer and/or genital warts. Most often, HPV is transmitted via anal or vaginal intercourse and direct skin-to-skin contact is often a requirement to the transmission although some self-reported cases state the lack of any such contact. HPV is a DNA tumor virus that results in epithelial proliferation. It exists as over 100 different types of the virus of which 30 to 40 infect the human genital tract. Of these, there are oncogenic types that are correlated with vulvar, vaginal, cervical, and anal cancers. Others are low risk and associated with genital warts. HPV 16 is the most oncogenic and HPV 16 and 18 account for about 70% of all cervical cancers. Oftentimes, infection is transient and those who were HPV positive are HPV negative in the span of 1 to 2 years post infection. However, some strains can be more persistent and bring with it risk of abnormalities within the cervical epithelium tissue (Braaten & Laufer, 2008). The HPV vaccine Cervarix protects against HPV 16 and 18 (de Sanjose et al., 2010). 231

The HPV vaccine Gardasil not only targets HPV 16 and 18, but also targets HPV 6 and 11, which cause around 90% of genital warts (Garland et al., 2009). Disparities in HPV and potential onset of cervical cancer include the gaps in vaccination coverage. HPV national programs cover around 30% of the global target population. Vaccination rates are higher in higher-income areas and only about 1% of adolescent females in low-income countries received a full course of HPV vaccines (Bruni et al., 2016). There is also a vaccination gap in urban and rural areas in low- and middle-income countries (Cheng et al., 2020). More than 80% of cervical cancer deaths are in low- and middleincome countries due to such gaps (de Martel et al., 2017). There are also disparities in screening for HPV and cervical cancer. In a study done, 64.7% had an annual household income <$30 000, 60.1% respondents had government-provided health insurance, and of women who had ever had a Pap test, 67.5% had an HPV test. Hispanic and non-Hispanic Black women were less likely than Hispanic and non-Hispanic White women to receive a Pap test. In this same study, women with government health insurance were more likely than women with private health insurance to have received a Pap test in the previous 5 years. Additionally, knowledge of HPV was a significant predictor of having received an HPV test in the previous 5 years (Johnson et al., 2020). A lack of testing could mean a higher mortality rate from undetected and untreated cervical or other genital cancers that arise because of HPV. Such preventative measures present obstacles in proper diagnosis and treatment of an HPV vaccine. Additionally, improving education surrounding HPV and its transmission could serve as a mechanism to reduce these gaps based on race and income. Hepatitis B & C Hepatitis B virus (HBV) infection is caused by the hepatitis B virus, which persists in 1-2% of patients with normal immune responses (Lavanchy, 2005). Patients with chronic HBV are more vulnerable to hepatocellular carcinoma (HCC), one of the most common types of liver cancer. This risk increases with age and is higher for males and people with existing liver damage, such as cirrhosis (Leung, 2005). This combined risk is supported by the Global Burden of Disease Study in 2010, where liver cancer and cirrhosis contributed to 83% of the deaths associated with

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HBV, the 15th leading cause of human deaths (Lozano et al. 2012). However, the risk of liver cancer also varies by the availability of free vaccines in a population, such as Taiwan (Chang et al. 2009). Hepatocellular carcinoma incidence was significantly higher for vaccinated cohorts than unvaccinated cohorts, meaning vaccines help reduce HPV infection from infectious mothers. This effect is large because it studied Taiwan (a high-prevalence region) after they started their vaccine program (Plymoth et al. 2009). Inequities exist in the distribution of HBV prevalence throughout the world. High-HBV prevalence regions, where the prevalence rate is 8% of the population or more, were disproportionately distributed in Asia-Pacific and sub-Saharan Africa (MacLacHLAn and Cowie, 2015). The high prevalence was also associated with a high proportion of endemic HBV, occurring at birth or during childhood. IntermediateHBV prevalence regions, with prevalence rates between 2% to 7%, were mainly in Eastern and Southern Europe, North Africa and the Middle East, South Asia, and Central and South America (Trépo et al., 2014). Intermediate prevalence rates signified that HBV occurred endemically and during adulthood in these regions. Low-HBV prevalence regions were focused in Northern and Western Europe, Australia, North America, Japan and other parts of Asia, as well as some parts of South America (MacLacHLAn and Cowie, 2015). These regions demonstrate that disparities exist in the prevalence of HBV, which has strong comorbidities with liver cancer. For example, the higher prevalence in Africa, the lower prevalence in North America and Australia, the variation within different parts of Europe, Asia, and Central and South America may suggest various factors in HBV prevalence. These factors may include access to healthcare, availability of free vaccines, infrastructure, etc. Hepatitis C virus (HCV) infection is often chronic for many patients, and it has strong comorbidities of hepatocellular carcinoma. It also relates to other types of cancer such as lymphoma (Yi and Yuan, 2017). HCV is one of the largest causes of cirrhosis and hepatocellular carcinoma (Lavanchy, 2009). Specifically, HCV patients had a higher “cancer burden,” or higher likelihood of all cancer sites, with the strongest comorbidity being liver cancer (Nyberg et al., 2020). After adjusting for risk factors like alcohol abuse, tobacco, diabetes, and BMI, the same study showed that comorbidities between HCV and cancers like liver cancer and non-Hodgkin's

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lymphoma were statistically significant (Nyberg et al., 2020). Furthermore, a study demonstrates that following chemotherapy, chronic HCV infection is reactivated and exacerbated for cancer patients. Since the progression of HCV infection damages liver functions, almost half of the patients were not able to receive vital chemotherapy (Mahale et al., 2012). Similar to HBV, HCV is associated with various disparities in prevalence. In general, HCV mortality rates have doubled from 1995 to 2004, and the mortality rates increased the most for African Americans, American Indians, and Alaska Natives (Wise et al., 2008). Referring to a review of studies on HCV-associated disparities (El-Serag et al., 2010), HCC incidence rates have increased by threefold from 1975 to 2005, due to HBV, HCV, and cirrhosis. Much of this increased mortality was attributed to middle aged African American, Hispanic, and White non-Hispanic males, although Asians and Pacific Islanders had higher incidence rates throughout the period (El-Serag, 2007). Asians and Pacific Islanders also took up 24% of HCC cases, even though they represent 5% of the US population. The same study examined a Medicare population and concluded that the dominant risk factor for HCC was different for racial groups. For example, HBV infection was associated with Asians, HCV infection with African Americans, and diabetes with non-Hispanic Whites (El-Serag et al., 2010). This supports the idea that racial disparities in hepatitis B and C appear for hepatocellular carcinoma. Regarding treatment, African Americans are more likely to be diagnosed at a more severe stage of HCC and less likely to obtain therapy than whites (Sloane et al., 2006). It is also noted that socioeconomic disparities affect the prevalence of HBV and HCV infections, shown by the relationship between lower income levels and higher probability of HBV or HCV infections (Flores et al., 2008).

Disproportionate Accessibility to Cancer Treatment Racial Variance in Accessibility of Cancer Treatment The chances that a patient survives their cancer diagnosis increases when their physician or provider follows the cancer treatment guidelines outlined by the National Comprehensive Cancer Network (NCCN) (Clair et al., 2020; Kaspers et al., 2020). However, currently, less than 50% of cancer patients received care and treatment in concordance with NCCN guidelines (Clair et al., 2020). Racial minorities and uninsured patients (including patients on Medicaid) are among

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the least likely to receive NCCN guidelineconcordant care (Clair et al., 2020). Kaspers and colleagues (2020) found evidence that Black Americans and Hispanic Americans are less likely to receive treatment in concordant with cancer treatment guidelines compared to White Americans (Kaspers et al., 2020). Similarly, Clair et al (2020) found that Black patients were less likely to receive guideline-concordant cancer medications and treatment for breast, prostate, colon, and ovarian cancers compared to White patients (Clair et al., 2020). Hispanic patients were less likely to receive NCCN guidelineconcordant care for breast, prostate, and liver cancers (Clair et al., 2020). This phenomenon has been noted in several studies examining the causes of racial disparities in cancer outcomes. One such study found that even though treatment guidelines for esophageal cancer recommend surgical resection for appropriate patients, physicians utilized surgery as treatment for esophageal cancer less for Black patients than White patients of similar diagnosis (Savitch et al., 2021). Therefore, Black cancer patients are at higher risk of mortality from esophageal cancer than White patients at all stages (Savitch et al., 2021). Another study noted that several patients suffering from lung cancer received no treatment or less chemotherapy and radiotherapy treatment than guidelines recommend (Blom et al., 2020). This was particularly noticed for non-Hispanic Black patients and elderly patients (Blom et al., 2020).

"Black patients were less likely to receive guideline-concordant cancer medications and treatment for breast, prostate, colon, and ovarian cancers compared to White patients"

Chen and colleagues (2021) alternatively examined patient adherence to NCCN guidelines and how it related to ovarian cancer survival as opposed to physician adherence. They found that Black patients were less likely to adhere to NCCN guidelines compared to White patients. Therefore, Black patients had a higher five-year mortality after their cancer diagnosis than White patients (Chen et al., 2021). Nonadherence to NCCN treatment guidelines was determined to be the most significant factor contributing to racial disparity in ovarian cancer, followed by access to care and comorbidity (Chen et al., 2021). Individuals with public insurance, low levels of education, comorbid conditions, and support from a community cancer program rather than a research/academic institution were similarly more likely to experience the non-adherence to treatment guidelines noted in Black Americans (Chen et al., 2021). Racial minorities may also experience general medical mistrust, including a mistrust of

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physicians, thereby contributing to subsequent underuse of cancer treatment in these populations (Bickell et al., 2009; Sheppard et al., 2016). They may also have misconceptions about cancer treatment and beliefs and preferences that reduce their likelihood of agreeing to undergo certain procedures like surgery (Esnaola & Ford, 2012).

"While some researchers have proposed that biological and genetic differences may also drive the racial health disparity, the general literature suggests that 'black-white differences in cancer outcomes are largely explained by failure to provide suitable cancer care, rather than racial differences in stage at presentation, tumor biology, or response to treatments'"

Often, due to differential access to care, patients may go undiagnosed for longer periods of time. Black women frequently present unknown or unstaged breast cancer (Yedjou et al., 2017). Additionally, Black patients were more likely to have metastatic or advanced cancer at diagnosis compared to Asian patients (Zhang et al., 2020). Also, compared to Asian Americans, Black and Hispanic patients were less likely to receive definitive treatment; and Black, White and Hispanic patients had worse survival prognoses overall and for each cancer type. This differential access to care can also mean that certain groups only have access to low quality care (Ensola & Ford, 2012). Black patients on Medicare were more likely to be treated by and cared for by less well-trained physicians, and in spaces with limited access to resources such as clinical specialists, imaging, and hospital admissions infrastructure (Ensola & Ford, 2012). A lack of regular health care access can influence rates of referrals and how early cancer diagnosis is made (Ensola & Ford, 2012). In general, racial and ethnic disparities in cancer outcomes can be attributed to a number of clinical and non-clinical factors including a lack of medical coverage, more advanced disease stage at diagnosis in minorities, barriers to early detection and screening, and unequal access to improved cancer treatment options (Yedjou et al., 2017). Financial difficulties, income and SES may also play a role in perpetuating this observed racial disparity in cancer mortality. Black Americans are more likely than White Americans to experience financial hardships and to limit care as a result (Hastert et al., 2019). While some researchers have proposed that biological and genetic differences may also drive the racial health disparity, the general literature suggests that “black-white differences in cancer outcomes are largely explained by failure to provide suitable cancer care, rather than racial differences in stage at presentation, tumor biology, or response to treatments” (Ensola & Ford, 2012).

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Socioeconomic Variance in Accessibility of Cancer Treatment The high cost of cancer treatment has often been mentioned as one of the most prominent barriers to receiving care for people of lower socioeconomic status. Cancer drugs incur these high costs due to the steep cost of drug development, with a need to perform extensive testing and regulatory studies and gain FDA approval. Since most cancers are incurable, a virtual monopoly is created as patients are treated with each approved agent and are willing to pay a higher price due to the serious nature of the disease (Siddiqui & Rajkumar, 2012). This cost has significant consequences for those who struggle to afford treatment. Increasing health care costs are associated with increased numbers of uninsured or underinsured citizens, since more businesses will be unable to provide these packages to their employees and individual workers may not be able to afford their own policies. If personal costs are high, patients that are uninsured or underinsured are less likely to seek care since they cannot afford it, and hospitals are hesitant to provide aid for treatment. Furthermore, insurance companies are less likely to cover expensive and long-term medication or treatment like that of cancer treatments. This means that they will increase barriers to prescriptions, and even with Medicare drug benefits patients must pay a specific percentage of the high total costs which they often cannot afford, leading many to be forced to decline treatment (Meropol & Schulman, 2007). If low-income patients are given greater access to cancer screening, some of these exorbitant costs can be prevented. As cancer moves from its early stages to late stages, the cost of treatment increases. Free clinics or government funded clinics could provide support for cancer screening. This would decrease the number of individuals that have not been screened that could find they have cancer later when it has already progressed and incur higher treatment costs (Subramanian et al., 2010). Geographical Variance in Accessibility of Cancer Treatment Yet another barrier to accessing high-quality cancer treatment is geography. Many studies have found an association between patients living in rural versus urban areas affecting patient prognosis because of the inaccessibility to specialized care. One study looking at both socioeconomic identities (such as profession, age, and education level) and their relation to

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geographic barriers showed how distance from specialized chemotherapy or radiotherapy centers leads to a greater delay between each stage of cancer treatment, leading to issues with local recurrence. If a patient lived more than 20 kilometers from their nearest radiotherapy center, the waiting time between surgery and the start of radiotherapy increased by 4-5 days. This is a 30% increase in waiting time between those two stages, while the waiting time between chemotherapy and radiotherapy increased by 12% (Bouche et al., 2010). While this study was conducted in the United Kingdom, the results have been reproduced in cities across the US as well. One study in Georgia analyzed regional differences in treatment specifically for ovarian cancer. By looking at urban versus rural differences as well as the travel time to the nearest treatment center, the study showed that geographic access greatly influences the receipt of surgery or chemotherapy. A generally higher accessibility to proper care was found in urban areas with concentrically less accessibility in surrounding suburban and rural areas. Many of these geographic factors were also found to be compounded on psychosocial and sociodemographic factors. Indicators such as poverty, the absence of a high school diploma, and a higher population to provider ratio resulted in weaker social networks that could potentially raise awareness of the existence of various cancers and their symptoms. Without these social networks, many patients fail to notice any developing symptoms and, without quality access to care, are unable to get quick treatment (Graham et al., 2019). The differences in sociomedical networks in rural areas are stark; while 20% of Americans live in rural areas, only 7% of oncologists bill from rural medical locations (Hung et al., 2019). Because of that, many rural patients are often diagnosed at much later stages, leading to worse prognosis. Rural patients in general have to travel much farther distances, with 50% of rural patients having to travel over 60 miles for access to specialized cancer care specialists while urban patients typically have to travel less than 30 miles. Up to 5% of patients in rural areas had to travel over 150 miles for the same level of specialization. With the extensive distances, patients often experience difficulty with treatment adherence in addition to increased waiting time between stages of treatment. Furthermore, patients that both live in poverty and are rural could have barriers with transportation, making it even more difficult to follow up on care. Many of these effects were found to be especially prominent for those that identify as Indigenous or as an Alaskan Native, as well as for those that live in the South or West

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(Hung et al., 2019). Many solutions have been proposed to these issues; however, most options still do not provide the same level of care as a specialized provider. Telehealth, home-based early-stage chemotherapy, and mobile cancer screening have all been suggested. While these will likely improve the present issues, they still do not provide the extensive, specialized care with reliable equipment that a specialty surgeon could provide (Hung et al., 2019).

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An Introduction to the Medicinal Uses of Marijuana STAFF WRITERS: VEDA SANE, ISABELLE WILSON, GRACE NGUYEN, ABENEZER SHEBERU, LOVE TSAI EDITORIAL BOARD WRITER: DEV KAPADIA

Cover image: Medicinal marijuana is one of the most controversial new areas in therapeutic innovation. While it has many documented health benefits, there is still a negative view of the drug derived from years of it being outlawed. Image Source: Public Domain Pictures

Introduction Marijuana is a drug that has been shunned by the American public for decades. Though cultures can trace the use of marijuana back centuries, the drug has been associated with laziness, irresponsibility, and–perhaps most jarring– criminality. However, the question arises as to how many of these perceptions are drawn from fact and how much is drawn from past politics? As time passes, it is becoming more and more apparent that the resounding amount of these misconceptions are drawn from politics. The reason for this is scientists’ ever-deepening understanding of the drug’s medicinal purposes. Medical marijuana incorporates the cannabis plant into therapeutic treatment. The scientific understanding of medical marijuana has opened the public to a consideration on marijuana’s benefits, as the marijuana treatments outshine industry standards and even provide relief for diseases with no known solution. Consequently,

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the majority of states have been quick to recognize the benefits, both medical and economic, of the proliferation of medical marijuana. Further, legalizing medical marijuana has encouraged some states to realize the overstated harm of the recreational use of the drug, leading some such as California and New York to take steps to decriminalize use of marijuana recreationally. It is therefore apparent that medical marijuana is sparking conversations around the country. However, few people understand the science behind its innerworkings and the impact that it can have on the ill. By presenting an introduction into the history, science, and economics behind one of the fastest growing industries in the United States, this paper seeks to provide the kindling for more intellectual debates regarding the future of this drug, as its fate impacts not only those directly involved in its production or use, but also the larger medical community.

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Figure 1:The above map depicts the legalization of Marijuana by state by the end of 2017. As shown, only four states had not and currently do not authorize use of medicinal marijuana (Idaho, South Dakota, Nebraska, and Kansas). Image Source: Flickr

History of Medical Marijuana Ancient cultures that grew marijuana likely did not cultivate it for its psychoactive properties; rather, it was grown for its herbal medicine and its hemp fiber to produce textiles and rope. Importantly, there is evidence that suggests that some ancient cultures cultivated plants similar to marijuana; these plants contained higher levels of tetrahydrocannabinol (THC), the chemical responsible for the medicinal properties of marijuana (DISA, 2021). These plants were likely utilized for religious ceremonies or healing practices; burned cannabis seeds have been found in the graves of shamans in China and Siberia from as early as 500 BC (Clark, 2000). Marijuana’s medicinal purposes as understood today, however, did not become known until the 19th century when an Irish doctor discovered that cannabis extracts could mitigate stomach pains and vomiting in cholera patients. By the late 1800s, cannabis extracts were being sold in pharmacies and doctors’ offices throughout Europe and the United States. Scientists then discovered that the THC component of marijuana responsible for the mind-altering effects of the plant also interacted with areas of the brain that promoted hunger and lessened nausea. As a result, the US Food and Drug Administration (FDA) has approved two pill-form drugs with THC–Marinole and Syndros–to treat nausea caused by cancer chemotherapy and loss of SPRING AND SUMMER 2021

appetite in AIDS patients (Badowski, 2017). Despite its prolonged existence, marijuana’s medical usage has only recently become increasingly popular–and controversial. In the United States, it was first introduced as a patent medicine during the 19th and 20th centuries after being described in the United States Pharmacopoeia in 1850. Use and sale of cannabis was later federally restricted, however, in 1937 with the Marihuana Tax Act, and legal penalties soon followed for possession of cannabis in 1951 and 1956 with the passing of the Boggs and Narcotic Control Acts. Consequently, the criminalization of cannabis restricted acquisition of the plant, limiting potential research on the plant for academic purposes (Badowski, 2017).

"the criminalization of cannabis restricted acquisition of the plant, limiting potential research on the plant for academic purposes"

California became the first state to legalize the usage of botanical cannabis for medicinal purposes under physician supervision in 1996 due to the Compassionate Use Act. After January 1, 2017, 28 states–alongside Washington D.C., Guam, and Puerto Rico–enacted legislation to govern medicinal cannabis sale and distribution. Also, during this time, 21 states and Washington D.C. decriminalized marijuana and the possession of it in small amounts. Even more, the District of Columbia and eight states–Alaska, California, Colorado, Maine, Massachusetts, Nevada, Oregon, and Washington–have legalized marijuana for recreational use (DISA, 2021). 243

Science of Medical Marijuana

"The THC binds to both CB1 and CB2 receptors and shows synergistic effects with pain-inhibiting systems by inhibiting particular pain pathways"

Figure 2: CBGA, one of the main intermediaries in the processing of marijuana is broken down by the body to produce THC and CBD. These products target the CB1 and CB2 receptors in the Endocannabinoid System to stimulate the effects of the drug. Image Source: Wikimedia Commons

The science behind marijuana and its effects on the body begins with the Endocannabinoid System (ECS), a neural network that reaches throughout the entire nervous system. The system consists of endogenous cannabinoids (neurotransmitters the human body produces) and two main cannabinoid receptors (CB1 & CB2) (Atakan, 2012). Both in vivo (performing the experiment in a living organism) and in vitro (performing the experiment outside a living organism) experiments using electrophysiological techniques have shown that endocannabinoids are synthesized and released by neurons “on demand” in order to stimulate cannabinoid receptors located in the brain, muscle and adipose tissues, the GI tract, and many more (Howlett et al., 2002). Within the body, CB1 receptors are primarily located at the terminals of neurons in the central nervous system, whereas CB2 receptors are found in the peripheral nervous system. However, their functions are the same: to mediate inhibitory action on the ongoing release of various excitatory and inhibitory neurotransmitter systems (i.e., dopaminergic, glutamatergic, serotonergic, and more) (Atakan, 2012). In essence, endocannabinoids travel from one neuron to another neuron in order to inhibit the second neuron's chemical releases. The presence of inhibitory neurotransmission in the ECS slows down rates of neural signaling, but doesn’t mean it slows down behavior (NIDA, 2020). For example, this diminished rate could be slowing down the rate of release for a neurotransmitter that inhibits the sense of smell, which would in turn amplify one’s smelling capabilities. Thus, the normal functioning of the nervous system relies

heavily on the neuromodulatory work of the ECS (NIDA, 2020). Using marijuana in any capacity introduces external molecular compounds (exogenous cannabinoids) into our bodies and disrupts the ECS (Howlett et al., 2002). The two main active exogenous cannabinoids in cannabis are delta9-tetrahydrocannabinol (THC) and cannabidiol (CBD). They are both similar in structure to the endogenous brain chemical, anandamide. Therefore, they can fit in the receptors as ligands and trigger different reactions that result in very high or low levels of various neurotransmitters (NIDA, 2021). THC is the primary psychoactive agent in cannabis. It primarily binds to CB1 receptors and affects brain areas that influence pleasure, memory, concentration, movement, coordination, and sensory and time perception. In medicine, the notion that THC’s activation of the ECS within the liver causes “the munchies” is used to help patients recovering from eating disorders (NASEM, 2017). CBD has the same chemical formula as THC but is shaped differently and therefore binds to cannabinoid receptors differently. The THC binds to both CB1 and CB2 receptors and shows synergistic effects with paininhibiting systems by inhibiting particular pain pathways (Manzanares et al., 2006). Different strains of cannabis produce different effects on the body. For example, the Indica strain is popularly known to be relaxing and sedative, whereas the Sativa strain is known to be stimulating (Encore Labs, 2019). Each strain’s notable effect is called the “entourage effect,” which is caused by different levels of each of the 113 regulatory compounds (cannabinoids and terpenes) present in the particular plant. Nonetheless, the characteristic of the plant holding the most influence in determining its effect is the THC to CBD ratio (Encore Labs, 2019). With the relatively recent discoveries of CBDA synthase and THCA synthase as enzymes that produce CBD and THC, professionals are able to breed plants with certain amounts of genes encoding for these two enzymes to obtain plants with certain ratios (de Meijer et al., 2003).

Comparison of Medical Marijuana Treatments to Current Standard As previously mentioned, when THC binds to CB1, it decreases incidence of nausea and vomiting, which can help treat chemotherapy-induced nausea and vomiting (CINV) (Badowski, 2017). CINV is one of the most common and unpleasant side effects of chemotherapy. Preventing this form of nausea is critically important for reducing 244

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morbidity and healthcare costs associated with cancer. Dronabinol is a new marijuana treatment being developed for CINV which acts as an agonist at the CB1 receptor. The CB1 receptor is correlated to the neuropeptide CCK, which is highly implicated in the causes of nausea. By targeting the CCK receptor, Dronabinol has been proven to effectively decrease nausea in cancer patients (Badowski, 2017). Before Dronabinol was developed, 5-HT3 receptor antagonists, such as ondansetron, were the only treatment available for CINV. However, a recent study injected musk shrews with LiCl to induce nausea and analyze the efficacy of 5-HT3 treatments compared to the CB1 treatment. Results show that while CB1 completely suppressed the nauseating reaction of the shrews, the 5-HT3 receptor antagonist did not, thus providing support that marijuana may suppress expression of anticipatory nausea better than 5-HT3 antagonists (Wilkie et al., 2016). Additionally, marijuana has been implicated in the treatment of severe childhood epilepsy. While THC binds to CB1 receptors, CBD shows a comparatively low affinity for endocannabinoid receptors, instead interacting with ion channel targets to increase calcium permeability to effectively modulate seizures in epilepsy (Silvestro et al., 2019). It is unclear exactly how CBD works, but some researchers hypothesize that the excitable interaction of CBD with ion channels causes a blockage which could be responsible for the antiepileptic action. The drug Epidiolex is currently in phase III clinical trials and has so far shown beneficial effects against treatmentresistant seizure disorders (such as LennoxGastaut Syndrome and Dravet syndromes) (Silvestro et al., 2019). Before the development of cannabidiol to treat epilepsy, common antiepileptic drugs (AED) were the only available epilepsy treatments. AEDs work by either inhibiting the glutamatergic system or enhancing the GABAergic system to mitigate neuronal hyperexcitability (Silvestro et al., 2019). While these drugs are effective in common forms of epilepsy, the cannabidiol approach is the only treatment that has shown efficacy in treatment-resistant seizure disorders and has therefore replaced many AEDs. Dronabinol and Epidiolex are just two examples of how medical marijuana is at the forefront of groundbreaking treatments for a variety of purposes, including chemotherapy-induced nausea and vomiting and treatment-resistant seizure disorders. Due to their high efficacy and

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reported safety, these treatments demonstrate the promising future of marijuana in the clinical sphere.

Economics of Medical Marijuana The widespread adaptation of any new therapy, however, must be both medically efficacious and economically viable from the perspective of the consumer, the providers, and the medical marijuana companies. Furthermore, because of the generally negative view of the drug in Washington, the likelihood of government subsidies being made available to support an economically unviable medical marijuana market is much lower compared to other treatments. Therefore, looking at the economics of this industry is critical to understand the viability of medical marijuana in mainstream markets. One good indication of the economic viability of the market is to actually analyze the size of the market, which is a measure of the total revenue generated from sales in the industry. The global medical marijuana market amassed $4.810 billion in 2018 and is anticipated to reach $33.212 billion by 2026 (Paliwal, 2021). This means that on average, the industry grows at a rate of 27.4% each year over this timespan (Paliwal, 2021). As a comparison, the mRNA vaccine market, believed to be one of the most innovative sectors of medicine following the COVID-19 vaccine rollout, is only expected to grow 11.9% each year (Global MRNA Vaccine Industry, 2021). This market is projected to have enough spend and interest to make it not just a viable market but a thriving market from the perspective of the private sector. Notably, the COVID-19 pandemic has had a negative impact on the medical marijuana market, decreasing the market value by $1.938 billion in 2020 (Paliwal, 2021). This was likely attributed to both lower consumer spending during the pandemic, closures of many companies producing and selling medical marijuana therapies, temporary lockdowns that negatively affected both research and production, and many companies diverting their research efforts and capital from medical marijuana development to vaccine development. Although these losses are large, especially for a nascent industry, the industry is expected to recuperate all losses by the end of 2022 and continue its upward trajectory.

"the industry grows at a rate of 27.4% each year over this timespan (Paliwal, 2021). As a comparison, the mRNA vaccine market, believed to be one of the most innovative sectors of medicine following the COVID-19 vaccine rollout, is only expected to grow 11.9% each year"

However, one cannot determine the economic viability of the industry just from looking at the private sector; these treatments need to be affordable for consumers to generate the volume that leads to these revenues. Medical marijuana

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is commonly used to treat chronic pain, anxiety, or depression. Prescription drugs like opioid painkillers or antidepressants can cost anywhere from $32 to $133 a month, depending on which drug has the greatest efficacy for the patient and whether the individual has insurance that covers a large cost of the drugs (John, 2020). At this point, it is difficult to compare this to the price of medical marijuana treatment because each state has varying laws for this industry. As a case study, imagine a patient is looking to purchase medical marijuana in Florida. In the Floridian system, there a few upfront costs that must be paid before an individual can purchase the treatment regularly. Before a patient may buy medical marijuana, they must pay a $75 medical marijuana cardholder application fee and spend $250 on an evaluation (Cannacare Docs, 2021).

"From the evidence researchers do have, however, it can be seen that the worst claims about marijuana are false: it is not a gateway drug to harder substances and will not illicit more drug use in patients"

Several factors then come into play when considering monthly costs such as the strain, the amount, the method of ingestion, and the dispensary of medical marijuana. It also greatly depends on the person ingesting the marijuana. The average person feels marijuana’s effects after 5mg of THC. This can cost around $20-$60 per 1000mg, which corresponds to 200 doses and leads to costs that can be far below opioid competitors on a monthly basis (John, 2020). Despite some medical and case studies showing the efficacy of medical marijuana, no insurance company reimburses for the use of medical marijuana. Marijuana is not an FDA-approved drug, which makes it virtually impossible for insurance companies to cover it and financially out of reach for some individuals (Neugent, 2019). Therefore, medical marijuana can be both economically viable from the perspective of the companies that produce it and the individuals that purchase it (Luthra, 2016). Combined with the efficacy that these treatments can bring that outperform the industry standards, if there even are any alternatives, this industry has proved itself to be one that deserves not just more favorable attention but also a disassociation from its unjustly negative past (Davis, 2020).

Ethics of Medical Marijuana Of course, the usage of marijuana in a medical context has had a fraught history, largely influenced by the criminalization of the drug in 1956 (Slaughter, 1988). As noted by Peter Clark in the Journal of Public Health Policy, the reasoning around medical marijuana was circular for many years: marijuana was made illegal and people should not use illegal drugs, so medical

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marijuana was deemed off-limits and considered unethical to use, despite its potential therapeutic benefits (Clark, 2000). Today, the conversation surrounding medical marijuana is more diverse. With the drug’s legalization in many states such as Colorado, Massachusetts, and California, one can no longer point to its criminalization as a reason for exclusion in treatment plans. In addition, most states today allow some form of medical marijuana (DISA, 2021). However, there is still a large difference between an individual’s recreational drug use and a patient’s drug use as recommended by a physician. In these cases, the focus now turns to the potential benefits that one could derive from using medical marijuana, and how they may be offset by other consequences. According to the Controlled Substances Act passed in 1970, marijuana is classified as a Schedule One drug. This means that it has “a high potential for abuse, no currently accepted medical use in treatment in the United States, and lacks acceptable safety for use under medical supervision” (Thomson, 2013). Because it is a Schedule One drug, marijuana research is restricted and not conducted at the levels it should be considering the early indications of benefits present in previously discussed therapies. Consequently, scientific knowledge about how the plant interacts with the human body and with other medicines is scarce, and doctors and policymakers may be currently operating without adequate evidence (National Academies of Sciences et al., 2017). From the evidence researchers do have, however, it can be seen that the worst claims about marijuana are false: it is not a gateway drug to harder substances and will not illicit more drug use in patients (Clark, 2000). Most patients are able to use the drug without many complications, although the smoked version of the treatment carries more side-effects such as an increased risk of cancer, lung damage, and pregnancy complications (Thomson, 2013).

Conclusion In conclusion, the medical marijuana industry is reaching a new inflection point as public opinion starts to diverge from its artificially muddied past. The industry could provide numerous innovative therapies that improve upon currently used solutions or develop answers to medical problems previously deemed unsolvable. The push has become so big that it has even turned the rusty and stiff wheels in the legislative branch

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that is notorious for being resistant to change, even in the face of undeniable proof. It is therefore of great importance that the public continues to understand rather than disregard this drug and the many benefits that it can bring. References Atakan, Z. (2012). Cannabis, a complex plant: Different compounds and different effects on individuals. Therapeutic Advances in Psychopharmacology, 2(6), 241–254. https://doi. org/10.1177/2045125312457586 Badowski, M. E. (2017). A review of oral cannabinoids and medical marijuana for the treatment of chemotherapyinduced nausea and vomiting: A focus on pharmacokinetic variability and pharmacodynamics. Cancer Chemotherapy and Pharmacology, 80(3), 441–449. https://doi.org/10.1007/s00280017-3387-5 Cannacare Docs. (2021, February 19). Costs of medical cannabis and obtaining a medical marijuana card. Medical Marijuana Clinics, Evaluations & Cards | Canna Care Docs. https://cannacaredocs.com/costs-of-medical-cannabis-andobtaining-a-medical-marijuana-card/ Clark, P. A. (2000). The Ethics of Medical Marijuana: Government Restrictions vs. Medical Necessity. Journal of Public Health Policy, 21(1), 40–60. https://doi. org/10.2307/3343473 Davis, E. (2020, November 29). Why Health Insurance Won’t Pay for Medical Marijuana. Verywell Health. https://www. verywellhealth.com/why-health-insurance-wont-pay-formedical-marijuana-1738421 de Meijer, E. P. M., Bagatta, M., Carboni, A., Crucitti, P., Moliterni, V. M. C., Ranalli, P., & Mandolino, G. (2003). The inheritance of chemical phenotype in Cannabis sativa L. Genetics, 163(1), 335–346. DISA, D. G. (2021). Map of Marijuana Legality by State (https:// disa.com/) [Text/html]. DISA Global Solutions; DISA Global Solutions. https://disa.com/map-of-marijuana-legality-by-state Encore Labs. (2019, December 18). What Determines the THC to CBD Ratio? http://www.encore-labs.com/what-determinesthe-thc-to-cbd-ratio Global mRNA Vaccines Industry. (2021). https://www. reportlinker.com/p06032278/Global-mRNA-Vaccines-Industry. html?utm_source=GNW

Manzanares, J., Julian, M., & Carrascosa, A. (2006). Role of the Cannabinoid System in Pain Control and Therapeutic Implications for the Management of Acute and Chronic Pain Episodes. Current Neuropharmacology, 4(3), 239–257. NASEM. (2017). The Health Effects of Cannabis and Cannabinoids: The Current State of Evidence and Recommendations for Research. The National Academies Press. https://doi.org/10.17226/24625 National Academies of Sciences, E., Division, H. and M., Practice, B. on P. H. and P. H., & Agenda, C. on the H. E. of M. A. E. R. and R. (2017). Cannabis. In The Health Effects of Cannabis and Cannabinoids: The Current State of Evidence and Recommendations for Research. National Academies Press (US). https://www.ncbi.nlm.nih.gov/books/NBK425762/ Neugent, B. (2019, October 21). Will Insurance Ever Pay for Medical Marijuana? | CannaMD. Https://Www.Cannamd. Com/. https://www.cannamd.com/will-insurance-ever-pay-formedical-marijuana/ NIDA. (2020, June 15). Marijuana. National Institute on Drug Abuse. https://www.drugabuse.gov/drug-topics/marijuana Paliwal, A. (2021, June 9). Global Medical Marijuana Market to Surpass $33,211.7 Million by 2026, with a CAGR of 27.4% Post-COVID-19 Crisis – Exclusive Report [150 Pages] By Research Dive. GlobeNewswire News Room. https://www. globenewswire.com/en/news-release/2021/06/09/2244395/0/ en/Global-Medical-Marijuana-Market-to-Surpass-33-2117-Million-by-2026-with-a-CAGR-of-27-4-Post-COVID-19Crisis-Exclusive-Report-150-Pages-By-Research-Dive.html Silvestro, S., Mammana, S., Cavalli, E., Bramanti, P., & Mazzon, E. (2019). Use of Cannabidiol in the Treatment of Epilepsy: Efficacy and Security in Clinical Trials. Molecules, 24(8), 1459. https://doi.org/10.3390/molecules24081459 Slaughter, J. B. (1988). Marijuana Prohibition in the United States: History and Analysis of a Failed Policy | Office of Justice Programs. https://www.ojp.gov/ncjrs/virtual-library/abstracts/ marijuana-prohibition-united-states-history-and-analysis-failed Thomson. (2013). The Ethics of Legalizing Medical Marijuana. https://www.brandeis.edu/ethics/publications/ethicalinquiry/2013/legalizing-marijuana.html Wilkie, G., Sakr, B., & Rizack, T. (2016). Medical Marijuana Use in Oncology: A Review. JAMA Oncology, 2(5), 670–675. https://doi.org/10.1001/jamaoncol.2016.0155

Howlett, A. C., Barth, F., Bonner, T. I., Cabral, G., Casellas, P., Devane, W. A., Felder, C. C., Herkenham, M., Mackie, K., Martin, B. R., Mechoulam, R., & Pertwee, R. G. (2002). International Union of Pharmacology. XXVII. Classification of cannabinoid receptors. Pharmacological Reviews, 54(2), 161–202. https://doi.org/10.1124/pr.54.2.161 John. (2020, August 4). Medical Marijuana Cost: How Much Will You Pay For Yours? https://themedmarijuanadr.com/ medical-marijuana-cost/ Luthra, S. (2016, July 6). After Medical Marijuana Legalized, Medicare Prescriptions Drop For Many Drugs. NPR. https:// www.npr.org/sections/health-shots/2016/07/06/484977159/ after-medical-marijuana-legalized-medicare-prescriptionsdrop-for-many-drugs

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U.S. Health Insurance Inefficiencies and Improvements STAFF WRITERS: ABIGAIL FISCHER, DANIEL KOTREBAI, ASHNA KUMAR EDITORIAL BOARD WRITER: DEV KAPADIA Cover image: President Barack Obama signs into law the Affordable Care Act, arguably one of the biggest changes in American Health Care and Health Insurance since the establishment of Medicare and Medicaid by Lyndon Johnson. Image Source: Wikimedia Commons

Introduction Health insurance seems to be one of the most controversial topics in global societies. Because it directly involves the welfare of an individual’s life, it must be correctly managed in order to ensure the optimal number of people receive adequate medical care. However, this issue is challenged by the fact that it not only affects people’s health, but also their wallets. Health insurance, particularly for low-income individuals that do not receive much assistance from the government, private companies, or other individuals, is often out of reach, forcing these people to hope and pray that their next life-threatening accident is far away. Therefore, finding the right balance between efficacious and cost-effective is critical and often belies the controversy. Addressing the aforementioned dilemma, however, often leads to further problems. Chiefly, if one is to receive support to pay their health insurance costs, who is to bear the cost? Should it be the government whose principal mission is to protect those from which it derives

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its power? Should it be private companies who already generate substantial revenue from their operations that can likely afford the civic duty of ensuring the health of those who do not have the resources? Or should it be other parties that are, much like private companies, in a position to provide relief to those less fortunate. Unsurprisingly, this question is just as contested as the one that led to it. There are those who think that the entire system should be privatized, those who think the system should be nationalized, and those who believe some mixture between the two. Because the system in any form requires effective management of the relationships and interests between patients, payers, governments, providers, and private corporations, it is regarded as one of the toughest problems to solve in today’s modern societies, particularly for a society as heterogeneous as America. For these reasons, a stance on the state of the health insurance market has become a fundamental platform opinion for many politicians since the introduction of Medicare by Lyndon Johnson. Because of the complexity, there have been multitude studies published on the efficiency DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

of health insurance. Consequently, forming a conclusion on the successes and failures of the American health insurance industry, digesting this wide body of research, is much easier said than done. Therefore, the goal of this paper is to begin the process of pulling together the perspectives of today’s scholars to create a more informed opinion on the state of the American health insurance industry. This will be put in context with recent events that have shaken the industry, including the COVID-19 pandemic, Affordable Care Act, Healthcare-for-All proposal, and more. Analyzing the industry from each of these perspectives should spark both further questions and answers to the question of how this system should adapt next.

How does US Health Insurance Work The US Health Insurance industry is one of the most complex health insurance industries in the world and one of the most complex industries in the United States. Health insurance markets factor in the interest of various parties, from patients to insurers to governments (both federal and state) to physicians and even to corporations producing products that are eligible for coverage by insurance. However, one of the primary reasons why the US health insurance market specifically has outshined others in terms of complexity is due to the markets incorporation of different healthcare system models. In fact, there are commonly believed to be four major national models for healthcare systems: the Beveridge model, the Bismarck model, the National Health Insurance model, and the Out-of-Pocket model. The Beveridge Model The Beveridge Model derives its name from the social reformer who implemented this system for Britain’s National Health Service. Just as the police force or firefighters are funded through tax payments, so is the health system. The plan relies on heavy nationalization, a version of the economy in which institutions are owned by the government instead of private corporations, in healthcare. The doctors can be either government employees or private networks and individuals, but they all collect payment through the government. Consequently, the government often limits what treatments and services doctors can offer and what they can charge for them, leading them to be more conservative than less which creates a lower cost health system. This system is still descriptive of what the UK, Spain, New Zealand, and Cuba all use as their health system model with Cuba’s model being the most pure form in which almost all aspects of the health system is nationalized (“Health Care Systems Four Basic Models,” n.d.). SPRING AND SUMMER 2021

There are, of course, large benefits to the implementation of this model. The obvious benefit is that all citizens under this model would be eligible to receive medical care. Further, having all health systems under one big system could simplify the health system and lead to lower costs due to economies of scale. The drawbacks, however, are very much comparable to the positives generated from this system. One of the main drawbacks being the increase in taxes that will inevitably be passed on to citizens as a result of all costs being paid by taxpayers. This will be especially harmful to lower-income citizens who don’t have a major reliance on healthcare. Further, with all costs being covered by the government, many individuals could be more likely to seek unnecessary treatment or be more likely to engage in activities that could require treatment, a phenomenon commonly referred to as “moral hazard.” This moral hazard dilemma will not only put a strain on costs for the health system but will also lead to longer waits for treatment given the limited supply of healthcare providers. With that, because the government is now determining the price of these procedures and consequently the pay of providers, it often opts for coverage of cheaper treatments that are comparable in efficacy to more expensive ones, leading to cheaper care for patients but also lower pay for healthcare providers, which could strain supply. Similarly, because the government is deciding which new treatments to approve, they would be expected to adapt to the adoption of new innovative treatments at a much slower rate than private insurers, given the complex bureaucracy and politics in the political sphere that must be ironed out before changes are made (“Health Care Systems - Four Basic Models,” n.d.).

"there are commonly believed to be four major national models for healthcare systems: the Beveridge model, the Bismarck model, the National Health Insurance model, and the Out-of-Pocket model.."

The Bismarck Model Like the previous model discussed, this model is named after its designer, Otto von Bismarck, for Minister President of Prussia that led the unification of Germany in the late 19th century. This system is much more decentralized than the Beveridge Model; it relies on both employers and employees contributing to insurers called “sickness funds” through payroll deductions. These sickness funds are then offered to private insurance plans to cover every employed persons, regardless of any pre-existing medical conditions (“Health Care Systems - Four Basic Models,” n.d.). Just as in the Beveridge Model, costs are controlled by the government so that insurers, regardless of whether they are public or private, are not guaranteed a profit on their services. 249

Figure 1: The above depicts how the out-of-pocket medical expense of a country varies around the world. As shown, countries in North America and Europe have some of the lowest out-of-pocket medical costs while developing countries have some of the highest due to the lack of financial resources that these countries have to build complex health insurance systems. Image Source: Wikimedia Commons

"The National Health Insurance Model seeks to take parts of both the Beveridge and Bismarck models, trying to incorporate the benefits of both to strike a balance between coverage, quality, and cost."

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Health providers, however, are generally private institutions, though they are still indirectly paid by the government since the government still controls costs and what is and is not covered under the sickness funds insurance plans. Governments that implement this model include Germany, Belgium, Japan, and Switzerland (“Health Care Systems - Four Basic Models,” n.d.). The benefits and drawbacks of this plan are similar to those of the Beveridge Model with a few notable exceptions. Firstly, for the benefits, the enrollment in coverage only for those employed ensures another labor incentive that can create a more productive workforce and economy. The principal downside is that this contribution from pay from the labor market essentially creates a “tax” on labor, disincentivizing individuals from working more or even staying in their country due to a “discount” on their work. Further, there are many groups of people that are susceptible to health problems that do not get coverage under this model, notably the elderly population because they are not employed. However, these drawbacks can be greatly exacerbated if this coverage is expanded to cover all individuals while still only drawing contributions from the working class. In order to be equally economically viable, there are only a fixed number of solutions: lower costs of treatments, which harms healthcare providers; cover less treatments, which harms patients; increase working contributions, which harms employers and employees; or expand contributions to all those receiving benefits,

which harms non-working-class individuals and essentially becomes a tax, mimicking the Beveridge Model. Therefore, there is no clear way to expand coverage under this method without harming any one party. The question then becomes: do the positives outweigh the drawbacks? This is the question that the National Health Insurance Model aims to address (“Health Care Systems - Four Basic Models,” n.d.). The National Health Insurance Model The National Health Insurance Model seeks to take parts of both the Beveridge and Bismarck models, trying to incorporate the benefits of both to strike a balance between coverage, quality, and cost. In this model, the government is acting as the single payer for procedures and treatments, taken from the Beveridge model. However, like the Bismarck model, the providers are private workers. The universal insurance that is provided to citizens does not make a profit and does not deny claims that are under coverage (“Health Care Systems - Four Basic Models,” n.d.). As stated previously, the benefits are drawn from both of the previous models. The private healthcare provider model allows them to maintain independence from the government while also simplifying payment infrastructure by only paying one party, the government. Further, this one insurance payer system can reduce costs as the government can realize economies of scale, which can in turn lead to slightly higher payments for treatments and procedures. The DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

main drawback, however, is that there is high utilization of healthcare under this system, which leads to high costs as well as long waitlists. For instance, Canada, which has implemented the National Health Insurance Model, has wait times for hip replacements in the range of 42 to 178 days (“Health Care Systems - Four Basic Models,” n.d.). The Out-of-Pocket Model This model is just what its name describes. In this system, all procedures are paid for by patients out of pocket. There is no government or private company that supports them financially in these costs. While this has the benefit of not troubling the government with setting up a health system and opens the market to competition that could lower costs and spur innovation, it also puts a significant burden on patients. Unfortunately, usually the only individuals who have the means to receive adequate medical care under this system are the rich, leaving a large portion of the population susceptible to medical disasters. This system is most used in developing countries as they often do not have extensive financial resources to create a complex medical system that many other countries have, which even further worsens outcomes as a majority of the population are low-income and cannot afford the exorbitant costs of healthcare treatment (“Health Care Systems - Four Basic Models,” n.d.). It might seem that these four systems are somewhat reminiscent to the structure of the American health system; in fact, they are all actually incorporated in different groups of individuals. The Beveridge Model can be seen as similar to the Veterans Health Administration, the Bismarck Model is similar to employer-based health care plans and Medicaid, the National Health Insurance Model is similar to Medicare, and the Out-of-Pocket Model is similar to the way that the United States cares for its uninsured or underinsured individuals. Obviously though, this does not give a detailed picture into the exact specifics of the health insurance industry, but more the impetus behind each facet as well as a clear view into the different compartments of the insurance industry. The US health market can be divided into two main areas: private and public. The majority of insurance is private, covering 70% of individuals, and is purchased by employers 61% of the time (Brown, 2003). Insurance firms prefer to cover groups of employees rather than sell individual plans because it takes less administrative costs to process a group together than each person

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individually, and firms prefer to give benefits in order to incentivize high-quality workers. Traditional insurance allows unrestricted choice of health care providers and reimburses on a fee-for-service with differing co-payments and deductibles for each plan. However, these plans only cover about 30% of individuals. Instead, about 70% of employees are enrolled in Managed Care Organizations (MCOs); MCOs have arrangements with selected providers that they trust and approve of and assist with the delivery of these services (Brown, 2003). There are two major types of public health insurance: Medicare and Medicaid. Medicare covers aged and disabled individuals, covering about 13% of the country, making it the largest insurer of the American population (Brown, 2003). Medicare consists of two parts: part A that provides compulsory coverage for inpatient hospital care and some home health and nursing home service; and part B that is voluntary and provides additional services such as outpatient, radiology, and more comprehensive home health services. Part A is funded entirely through a Medicare tax on citizens while Part B is mostly funded through Medicare tax but also funded partly by monthly premiums charged to recipients. Alongside with the premium, individuals enrolled in Part B must pay to providers a deductible and a co-payment for services. Medicaid, on the other hand, is for the economically disadvantaged, funded both by federal and state governments but actually run by states individually, with some providing more generous benefits than the other (Brown, 2003).

Recent Changes to the US Health Insurance Industry

"The Beveridge Model can be seen as similar to the Veterans Health Administration, the Bismarck Model is similar to employerbased health care plans and Medicaid, the National Health Insurance Model is similar to Medicare, and the Out-of-Pocket Model is similar to the way that the United States cares for its uninsured or underinsured individuals."

The general insurance industry is always in flux in order to adapt to public opinion, public need, and governmental regulation; the health insurance industry is no exception. Particularly in the past two decade, the American Health Insurance industry has weathered several events that have forced the industry to adapt in a major way. The two primary events being the introduction of the Affordable Care Act (ACA) and the onset of the COVID-19 pandemic. ACA The Patient Protection and Affordable Care Act, or its more common name the “Affordable Care Act” (ACA), was signed into law on March 23, 2010, by President Barack Obama. To date, it is considered the largest regulatory overhaul of the United States Health Insurance industry ever (McIntyre & Song, 2019). The goal of the program 251

"Expectedly, out of pocket expenses has drastically fallen for American families post-ACA, instead being spread out to more families via premiums charged for tiered plans from state marketplaces"

was to specifically increase coverage for low- and middle-income Americans that have traditionally not had access to health insurance coverage either through ineligibility or affordability and sought to achieve this through two major methods. The first method being an increase in Medicaid eligibility, which was achieved through a federal increase of Medicaid eligibility to those individuals and families at or below 138% of the Federal Poverty Level (FPL). Individuals and families from 139% to 400% of the FPL were eligible for subsidies in the form of payment tax credits. The second method was aiming to change to the individual insurance market altogether. This involved setting up state health insurance marketplaces where individual insurers offered four tiers of health insurance: bronze, silver, gold, and platinum. The bronze plans require 40%, on average, of all healthcare spending from individuals to come from out of pocket; silver requires 30% out of pocket; gold requires 20%; and platinum requires 10% (McIntyre & Song, 2019). Consequently, because more of spending is coming from out of pocket for the bronze plan, the premiums will be lower than those of all the other tiers with silver have the next-lowest, and so on. Beyond the tier system, the ACA also shook up the individual insurance industry through the cost-sharing reduction subsidies that were paid to insurance companies to reduce copayments and deductibles for individuals earning less than 250% of FPL and were enrolled in a state marketplace plan. Further, the ACA required that individual insurance companies could not turn down insurance to individuals due to pre-existing conditions. However, this forced insurance companies to take on policyholders that would submit many claims, more than the insurance company expects on average that could cause it a loss. To compensate, the ACA also mandated that all adults had to buy insurance (or pay a fine) so that healthy individuals who wouldn’t benefit from purchasing health insurance (their premiums outweighed their claims) would cover the losses derived from those submitting many claims (McIntyre & Song, 2019). With these positives, there have been several reported outcomes that have resulted from this program. Firstly, there is an estimated twentyfive million decrease in the number uninsured American adults. These coverage gains were achieved differently in every state based on their implementation of the ACA and its programs, with Kentucky being an example that, through aggressive Medicaid expansion, lowered the number of uninsured low-income individuals by 70% (McIntyre & Song, 2019). While studies on

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health outcomes have yet to reach a consensus, most studies do show a slight improvement in access to care for individuals as well as a reduction in the delay of care as compared to preACA (Kominski et al., 2017). Compared to preACA levels, studies have found a 6.6% increase in doctor visits as well as a statistically significant increase in the number of outpatient visits. Expectedly, out of pocket expenses has drastically fallen for American families post-ACA, instead being spread out to more families via premiums charged for tiered plans from state marketplaces (Kominski et al., 2017). For young adults (aged 19 to 25), the ACA has had an even more specific benefit. The ACA extended the age that children can stay under their parent’s health plan from under 19 to under 26, so long as their parents had private health insurance (Serakos & Wolfe, 2016). While this effect did have a greater effect on children of the higher-income families that could afford private insurance, the other tenants of the ACA still did a lot to help young adults in all socioeconomic backgrounds given that all individuals above 18 and below income requirements could receive benefits. This led to a six million decrease in the number of uninsured young adults since the signing of the ACA (Serakos & Wolfe, 2016). Similarly, nearly all preventative care metrics measured increased, including cholesterol screening, blood pressure measurements, and HPV vaccine initiation. Annual frequency of doctor office visits was estimated to increase by anywhere from 50 million to 149 million, and mental health treatment rates also increasing by 5.3 percentage points for young adults with mental health disorders (Serakos & Wolfe, 2016). And lastly, studies show that, after the ACA, young adults are less likely to have a full-time job, and more likely to work part-time, go to school, and start their own small businesses (Serakos & Wolfe, 2016). While the ACA has been documented to provide particularly low-income Americans with many improvements to their relationship with the health insurance industry, there is still much room for improvement with the laws (Sterbenz & Chung, 2017). The American College of Physicians in particular outline four major problems. The first being underfunding for the program that has led to premium spikes; this is resulting from insurers passing higher costs onto consumers after governments refuse to increase capital supplied to the program to cover the costs of more subsidies and cost-sharing coming from more enrollees. The second major problem is the tax credits fraud

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that has been documented after the introduction of the ACA, characteristic of any government program that has a tax benefit to it. According to the Government Accountability Office, about 1% of the 8 million enrollments for subsidized coverage might have been fraudulent (Crowley & Bornstein, 2019). The third major problem the American College of Physicians finds is the government continuing to narrow the eligibility of Medicaid expansion to ensure costs can still be supported. Specifically, there is worry that the government will keep passing laws that will eventually require enrollees to work or otherwise be engaged in the community, reminiscent of the Bismarck model and potentially leaving out the sick and those unable to find a job while creating new administrative burdens to agencies in screening these individuals. And the last problem found is the limits on premium tax credit and cost-sharing eligibility; considering that many individuals still find the premiums on some of the lower-tier plans (bronze and silver) to not be affordable, it is no surprise that the government limiting these benefits will negatively impact the care of Americans (Crowley & Bornstein, 2019). The American College of Physicians, however, does not leave these problems for the government to solve; it does provide several possible solutions to some of these problems. The first two specifically target the concern of affordability for Medicaid. The first suggestion is that requirements for premium tax credit and cost sharing should be restructured so that there is no more sub-400% FPL requirement but that benefits should be spread throughout income levels. They contend that this would help serve the almost 1 million Americans just above the 400% FPL that claim that the premiums are just out of reach for them to be able to afford and that even “minimal support” would open the door for them (Crowley & Bornstein, 2019). The second potential solution is to stabilize the market using reinsurance so that insurers are less concerned about possible losses from increasing health claims and consequently do not raise premiums. Reinsurance is essentially insurance for insurance companies. Without it, insurance companies act much like an individual without insurance, playing it very safe and ensuring that they have a buffer to sustain losses without failing. Therefore, if insurers have reinsurance on their health insurance portfolios, they are likely to pass much less of the costs onto the patients (Crowley & Bornstein, 2019). The next two solutions involve the expansion of coverage of the ACA and are much more straightforward than the previous two solutions. One solution is to increase marketing for the

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ACA and even auto-enroll citizens. The amount of paperwork that goes into filing for ACA can be daunting to individuals, and many do not even know what the requirements for ACA are and do not know where to go to ask; in fact, about ten million Americans are eligible for the ACA and would enroll, yet one of the two aforementioned barriers prevents them from doing so. Therefore, by both marketing the program much more as well as auto-enrolling individuals, the government can ensure that more of those that want and need Medicaid are receiving it (Crowley & Bornstein, 2019). The last solution for ACA is to require states to expand Medicaid and not engage in practices that dissuade citizens from enrolling (i.e. applying higher premiums, increasing paperwork requirements, etc.). While the ACA was a national policy, it was up to states to implement many aspects of the plan, which they could do to their own discretion, the statesponsored tiered-policy marketplace (bronze, silver, gold, platinum) being one instance of this. Some states, like California and New York, have been much more active in implementing the plan than others. By forcing states to maintain some level of expansion, the federal government can ensure people in every state are given a fair chance to take advantage of the ACA (Crowley & Bornstein, 2019). While the American College of Physicians certainly covered many of the problems that the ACA faces, there are still several others that don’t have very simple answers. One is that while the insurance plans offered by Medicaid and state marketplaces are in many cases affordable for those that enroll, the coverage is not very great. To make these plans economically feasible, the government can only cover certain low-cost treatments and allow treatment by few healthcare providers. The second problem should be expected given the structure of the marketplace: many individuals opt for bronze and silver coverages because they cannot afford the higher premiums of gold and platinum, but they find themselves in trouble when they submit claims and realize they must pay a significant portion themselves. Because the government mandates that individuals obtain health insurance, this dilemma occurs more often, leading to losses not only for insurance companies but also for the government. COVID-19 The COVID-19 pandemic has undoubtedly been a time of change. Beyond the medical exhaustion that it has exerted on hospitals and primary caregivers, it has also had a significant impact on

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"Health insurance payers, consequently, have had to rapidly adapt to the sudden shock to the fragmented American health care system that the COVID-19 pandemic evoked."

the health insurance markets. Currently, the most common way Americans obtain insurance is through employer-sponsored coverage (ESI). Job losses caused by the COVID-19 pandemic have severed millions of American citizens’ access to health insurance, where since the onset of the pandemic, approximately 6.2 million workers have lost access to healthcare coverage that they normally got through their employer (Bivens & Zipperer, 2020). Additionally, for every person covered under their employer’s ESI, about 2 people are also covered (spouses and dependents considered), making it nearly 13 million people who have lost healthcare insurance due to the job losses (Zipperer & Bivens, 2020). Fortunately, not every worker who loses ESI status loses health insurance. Medicaid has become the predominant alternative coverage source for those who have lost ESI due to the pandemic; Medicaid rolls have expanded by nearly 4 million since the pandemic began (Bivens & Zipperer, 2020). As a result, the idea of a “single-payer” healthcare plan has become increasingly popular as having the federal government being the primary insurer would eliminate the link between health insurance and specific jobs. Such a plan could potentially make healthcare coverage more accessible in tumultuous, uncertain times like the COVID-19 pandemic has induced. While COVID-19 is an evolving situation whose full impact on the markets cannot yet be fully determined, it is important to recognize the lasting impact that it will inevitably have. Currently, direct insurance claims associated with COVID-19 include testing, doctor/ emergency room visits, hospital admissions, stays in intensive care units, and end of life care (CDC COVID-19 Response Team et al., 2020). However, the growing use of telemedicine has become particularly indicative of this impact: the increasingly popular use of telemedicine is a new consideration that health insurance companies must now take into account regarding their coverage plans. Health insurance payers also had to keep pace with constantly revising federal and state mandates, as well as collaborate with other sectors (i.e. public health and communitybased organizations) (McClellan et al., 2021). Health insurance payers, consequently, have had to rapidly adapt to the sudden shock to the fragmented American health care system that the COVID-19 pandemic evoked.

Flaws in health insurance While the insurance system has certainly adapted to the changing times, leading to numerous positive effects of various magnitudes, there are

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still many flaws in the industry that still belie in the system from the perspective of patients. In general, these can be grouped generally into three main groups: accessibility, affordability, and coverage. To understand the future of health insurance and what would be best for society as a whole, one must first understand the causes and effects of these groups, which will be discussed presently. Accessibility Healthcare in the United States (US) is not meeting patient needs. More than in any other high-income country, people in the US report skipping necessary medical care; one third of US adults report skipping necessary care, a number which is as low as seven percent in Germany and the UK (Osborn et al., 2014). The Affordable Care Act has pushed the US forward in expanding healthcare coverage, but the US remains an outlier among high income countries in ensuring access to healthcare. Most other high-income countries provide universal insurance coverage, better cost protection, and a more extensive safety net (Osborn et al., 2014). Affordability Many other countries have both lower healthcare spending and higher rates of insurance coverage in comparison to US health systems. Papanicolas et al. (2018) published a study in the Journal of the American Medical Association in 2018 that compared US health care spending and outcomes with ten high-income countries. They concluded that the “main driving factors [in increasing healthcare spending in the US] were likely related to prices, including prices of physician and hospital services, pharmaceuticals, and diagnostic tests.” Compared to the other countries, the US spends nearly double the amount of money on pharmaceuticals. The United States also had the highest levels of administrative burden, spending nearly 8% of national healthcare spending on administration compared to the group mean of 3%. Contrary to popular belief, Papanicolas et al. (2018) found that social spending and healthcare utilization in the US were like that in other countries. However, the United States had the greatest inequity in access to physicians when adjusted for need and the lowest rate of insurance coverage. The US performed slightly worse than other countries on measures of access and quality for patients covered by Medicaid, and performance was uneven across private insurance groups. Despite this, the US still had some of the worst population health outcomes, including

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the lowest life expectancy, and highest maternal, neonatal, and maternal mortality rates. However, addressing these issues in health outcomes is not simple. A number of studies have produced strong evidence to indicate that expanded insurance coverage increases access to preventive services in particular, among other benefits (Sommers et al., 2017). Expanded coverage leads to an increase in most types of treatment utilization, meaning that simply expanding coverage without reducing spending will actually increase costs in the foreseeable future (Sommers et al., 2017). Coverage By far, one of the biggest complaints of the US health insurance market is the lack of coverage. There are still over 30 million Americans, for one reason or another, that lack health insurance, creating not just health problems, but also restricting the ability to purchase basic necessities if a member of the family falls ill and exorbitant health payments must be made to keep them alive. While 30 million is much less than the almost 50 million uninsured Americans a year ago, there is still work to be done to overcome this gap (Finegold et al., 2021). What makes these coverage gaps particularly difficult to address in the United States is that these uninsured individuals cannot easily be organized into one cohesive group that a national redesign could address. Reforms discussed previously like that of the ACA have provided steps in the right direction by expanding the public insurance sector, but there is obviously a limit to how specific these mandates can be to target the numerous pockets of uninsured individuals left (Ridic et al., 2012). One point important to bring up during this discussion is not cost to policyholders but the cost of coverage to the government. One would think that with less coverage, the US spends much less on insurance than other countries with less of a gap (Manchikanti et al., 2017). In the 34 members of the Organisation for Economic Co-operation and Development (OECD), the United States ranked 33rd in insured rates. However, despite these coverage gaps, the US continues to remain the country that spends the highest on insurance, spending almost $4,200 per capita annually according to OECD Health Data (Papanicolas et al., 2018). Because a sizable portion of insurance is public insurance, and the government providing many subsidies to private institutions to fund insurance coverage, this large insurance spend means the government is paying more and that these costs will likely be passed

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down to citizens through taxes. While the growth of private insurance and MCOs have pushed costs down from what they were decades ago, the problem still remains. Therefore, while it is true that the US should try to increase coverage to provide benefits to all individuals, there might be a better, more economically efficient, method of structuring the industry so that it can be both efficacious and cost-effective (Wray et al., 2021).

Future of Health Insurance Now with an understanding of the problems that are still inherent in the American health insurance system, one can now be much more prepared to begin a discussion on the methods that have been proposed to fix many of these broken parts. There are many proposals currently in the public discussion on changes to the insurance industry, and likely more so discussed privately amongst regulators and politicians, but three next-steps have gained significant support…and consequently significant opposition: Value Based Care, Social Determinants of Health (SDoH), and Medicare-for-All. While the full details of the plans are neither fully outlined later in this paper nor fully defined by any group, understanding the beginnings of these ideas is paramount to furthering the discussion on how American society should adapt its insurance system next to reach the next level of improvement. Value Based Care Under the value-based healthcare model, patient health outcomes determine the pay physicians and hospitals receive. The “value” lies in improved health outcomes instead of the cost of the treatments used to deliver those outcomes (NEJM Catalyst, 2017a). Instead of paying for the treatments they receive, as is currently the standard practice in the US, patients pay for the improvements they see in their health. Value Based Care rewards providers for helping their patients improve and incentivizes efficacious treatment.

"while it is true that the US should try to increase coverage to provide benefits to all individuals, there might be a better, more economically efficient, method of structuring the industry so that it can be both efficacious and cost-effective"

Value Based Care has the power to reduce costs. First, Value Based Care increases preventative care – making healthcare “proactive rather than reactive” – which involves holistically looking at patients to improve their healthcare outcomes (Cleveland Clinic, 2020). Preventative care creates a healthier society with a decreased need for medical tests, treatments, medications, and procedures, which reduces individual patient expenses. The risk spread for insurance is smaller, translating to “less drain on payers premium pool and investments” (NEJM Catalyst, 2017b). Implementing Value Based Healthcare in the US

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could be a big relief to the 18% of America’s GDP that health expenditures currently account for (NEJM Catalyst, 2017b). However, there is more to Value Based Care than simple economic efficiency. An ideological shift accompanies the transition from a fee-forservice model to a Value Based Care model. Value Based Care “connects clinicians to their purpose as healers” and can “counter clinical burnout” (Teisberg et al., 2019). Value-based core aligns providers with their intrinsic motivation, improving the lives of their patients. A 2017 article in the BMC Health Services Research Journal provides a longitudinal analysis of the implementation of Value Based Care in four representative pilot programs in Sweden. The study concludes that patients appreciated the transition to Value Based Care for its “focus on value for the patients and [measurement of] health outcomes” (Nilsson et al., 2017) Though the implementation process went through stages of progression and regression, providers did markedly improve at asking patients what they considered valuable and important and then weighing patients’ answers, which improved patient outcomes and satisfaction. According to Elizabeth Teisberg, the director of the Value Institute for Healthcare at Dell Medical School, implementing Value Based Care in the US, changes start on the educational level. Since Value Based Care requires a transition to interdisciplinary medicine where patients are viewed in groups with related needs, encouraging physicians develop teamwork abilities by working with their teams to ensure optimal care both inside and outside of the hospital (Teisberg et al., 2020). Through education, the mindset of physicians practicing Value Based Care can be cultivated to understand how to measure what healthcare outcomes matter most to patients, which the Dell Medical School has successfully been doing. DMS has been a leader in this paradigm shift in healthcare by exposing medical students to the principles of Value Based Care both during class and through clinical rotations with interdisciplinary teams of physicians who are “organized around patients with shared needs” (Teisberg et al., 2020). Social Determinants of Health The US Department of Health and Human Services defines social determinants of health (SDOHs) as the “conditions in the environments where people are born, live, work, play, worship, and age that affect a wide range of health, functioning, and quality-of-life outcomes and

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risks” (Social Determinants of Health - Healthy People 2030 | Health.Gov, n.d.). The federal government has launched an initiative entitled “Health People 2030” to improve health and reduce health disparities by addressing SDOHs. Healthy People 2030 places determinants into five categories: healthcare access and quality, education access and quality, social and community context, economic stability, and neighborhood or built environment (Healthy People 2030, n.d.). Researchers found that SDOHs have a greater impact on population health than healthcare (NEJM Catalyst, 2017a). At the state level, those states that allocate more resources to social services than to medical costs have better outcomes. Rather than focusing on treating individual patients, hospitals can invest in populationlevel approaches that address SDOHs. One recent example of this is the accountable care organization (ACO), which uses existing infrastructure to address health-related needs and aligns community resources towards the goal of improving population health (Sullivan, 2019). The National Academies of Sciences, Engineering, and Medicine has also put forth a framework for healthcare providers that defines approaches providers can take to address SDOHs. These include increasing awareness of social risks and strengths, adjusting clinical care to address these risks, and connecting patients, if needed, with available government and community resources (Cheney, 2019). Medical education and the medical professions at large are also starting to emphasize the importance of recognizing the various forces that impact health. Metzl and Hansen (2014) first coined the term “structural competency,” which consists of five main competencies: acknowledging how clinical interactions are built, structuring language outside of the clinic to be recognized, incorporating and detailing the cultural influences into the clinical structure, implementing interventions that are beneficial to the effects of the structure, practicing humility in the face of change. Medicare for All Medicare for All, in its most revisionist iteration, is a single-payer national health insurance program that seeks to provide affordable healthcare to a broader population. Medicare currently serves as the health insurance program for people who are sixty-five and older, with the exception of younger people who have certain disabilities and diseases, while everyone living in the United

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States is eligible for Medicare for All. Medicare still presents a financial burden for patients, but Medicare for All seems far more generous in its coverage. Medicare for All promises to pay for all necessary medical services, whether that be primary care, prescription drugs, mental health services, or emergency care, with the government responsible for reimbursing doctors and hospitals (Fisher, 2020). Medicare for All does not have one true form; different candidates push variations on policies, some emphasizing universal coverage and some calling for a much lower reliance on private insurance providers (Freeman, 2020). The Kaiser Family Foundation identifies two main forms of Medicare for All: single health program and nationalized health program. The former calls for everyone to utilize the same insurance, potentially resulting in higher taxes and lower healthcare costs. A nationalized health program presents Medicare for All as an option, rather than the default. Residents would get to choose to mainly rely on their private insurance provider or the national system, possibly making healthcare

more affordable due to increased competition in the marketplace (Nall, 2021). A national healthcare system ensures more equal service to patients regardless of socioeconomic status, as the appeal of profiting off of wealthy clients through expensive procedures is no longer a large factor. Universal healthcare also boosts public health with increased access to affordable care with fewer people relying on emergency room services (Fisher, 2020). However, a single-payer healthcare system means a tremendous shift in the current state of affairs. The country would need to turn away from private insurance companies, which has the potential to cause two million people to lose their jobs (Johnson, 2019). There are also several unknowns and variabilities that come with this system, including whether patients would remain with their current doctors or if the cost of prescription drugs would decrease. In addition, in order to meet the standards of such extensive coverage and the possible advantage of no copays or deductibles, the government would need to increase taxation. Some experts argue that the Figure 2: The image above depicts many of the Social Determinants of Health that are either currently being used or have been proposed to better represent a patient’s health. As shown, analyzing genetics and medical care is only one element of analysis as this method incorporates other determinants, like social environment and individual behavior to best represent and care for patients. Image Source: Wikimedia Commons

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switch to such a system would cost thirty-two trillion dollars on top of the three and a half trillion that is currently expended on healthcare. Health policy researcher Kenneth Thorpe spoke on Vermont’s attempt to move toward a single-payer system, saying a nearly twenty percent increase in payroll and income taxes were necessary to facilitate expanded coverage, inevitably presenting the threat of small business closure and unemployment (Johnson, 2019). Some argue that Medicare for All takes away the incentive to look after oneself and remain healthy because of alleviated financial pressure. In addition, if healthcare providers are paid less, they may not be motivated to provide quality care in order to limit costs. The extent of healthcare coverage is also unclear, since the government may not cover the cost drugs for rare conditions or very risky procedures (Fisher, 2020). Currently, seventeen countries worldwide have an established single-payer healthcare system of which Japan, Canada, Spain, and Sweden are a few. However, these systems don’t cover the entire population, as Medicare for All promises. The Canadian system lacks a wide range of benefits, with a lack of coverage for services like mental health, vision and dental care, and outpatient prescriptions, leading to some reliance on private insurance. Some of the countries with systems closest to that of Medicare for All are Denmark, Britain, and Germany because they have low

copay costs and provide comprehensive benefits for services like mental health (Wahner-Roedler et al., 1997). The German universal multi-payer healthcare system constitutes both private and statutory insurance and provides much more equitable standards of service than the American system. Germany also boasts a much higher satisfaction with healthcare services, with forty percent of Germans liking the existing system as opposed to around ten percent of Americans, who also struggle with the highest healthcare expenditure. Physicians in Germany were also much more satisfied with the state of their country’s healthcare system than physicians in the United States, as fewer Germans thought healthcare inequity presented a serious issue to patients (Wahner-Roedler et al., 1997). Evidently, transforming from our current system to a completely single-payer system is not necessary for more affordable and satisfactory healthcare, where the two systems are reconciled as seen in the German model which has the potential to benefit the population tremendously.

Conclusion While the American Health Insurance industry is certainly one that has adapted well in the past, particularly in the past decade, there is still improvements to be made. It is likely that the next major improvement will be one of the three discussed in the last section, but, as seen from the effects of COVID-19, one unexpected world

Figure 3: Regular doctor visits and checkups are an essential part to cancer prevention. Early detection of cancer directly leads to a higher success rate of cancer survival. Image Source: Wikimedia Commons

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event can realign the industry to new priorities, and subsequently lead to the implementation of new legislation and policies. With the United States being both one of the most populous and richest countries in the world, this industry will demand a large amount of attention, and consequently a large amount of controversy, until a replacement is introduced. Therefore, no matter where this industry decides to innovate next, it will certainly be thrilling to observe. References

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Catalyst, N. (2017a). What Is Value-Based Healthcare? NEJM Catalyst. https://catalyst.nejm.org/doi/full/10.1056/CAT.17.0558 Catalyst, N. (2017b). Social Determinants of Health (SDOH). NEJM Catalyst. https://catalyst.nejm.org/doi/full/10.1056/ CAT.17.0312 Cheney. (2019). 5 Ways Healthcare Organizations Can Address Social Determinants of Health. https://www. healthleadersmedia.com/clinical-care/5-ways-healthcareorganizations-can-address-social-determinants-health

Nall, R. (2021, January 14). Medicare for all: Proposals, and working with Medicare. https://www.medicalnewstoday.com/ articles/medicare-for-all Nilsson, K., Bååthe, F., Andersson, A. E., Wikström, E., & Sandoff, M. (2017). Experiences from implementing value-based healthcare at a Swedish University Hospital – a longitudinal interview study. BMC Health Services Research, 17(1), 169. https://doi.org/10.1186/s12913-017-2104-8

Cleveland Clinic. (2020, October 19). Value-Based Care & Lower Costs. Cleveland Clinic. https://my.clevelandclinic.org/ health/articles/15938-value-based-care

Osborn, R., Moulds, D., Squires, D., Doty, M. M., & Anderson, C. (2014). International survey of older adults finds shortcomings in access, coordination, and patient-centered care. Health Affairs (Project Hope), 33(12), 2247–2255. https://doi. org/10.1377/hlthaff.2014.0947

Crowley, R. A., & Bornstein, S. S. (2019). Improving the Patient Protection and Affordable Care Act’s Insurance Coverage Provisions: A Position Paper From the American College of Physicians. Annals of Internal Medicine, 170(9), 651–653. https://doi.org/10.7326/M18-3401

Papanicolas, I., Woskie, L. R., & Jha, A. K. (2018). Health Care Spending in the United States and Other High-Income Countries. JAMA, 319(10), 1024–1039. https://doi.org/10.1001/ jama.2018.1150

Finegold, K., Conmy, A., Chu, R. C., Bosworth, A., & Sommers, B. D. (2021). Trends in the U.S. Uninsured Population, 20102020.

Ridic, G., Gleason, S., & Ridic, O. (2012). Comparisons of Health Care Systems in the United States, Germany and Canada. Materia Socio-Medica, 24(2), 112–120. https://doi. org/10.5455/msm.2012.24.112-120

Fisher, S. (2020, October 6). Medicare for All: Definition and Pros & Cons. SmartAsset. https://smartasset.com/insurance/ medicare-for-all-definition-and-pros-and-cons Freeman, J. (2020). Health Reform, Medicare for All, and Family Physicians. Family Medicine, 52(3), 165–167. https://doi. org/10.22454/FamMed.2020.970445 Health Care Systems—Four Basic Models. (n.d.). PNHP. Retrieved August 9, 2021, from https://pnhp.org/resource/ health-care-systems-four-basic-models/ Johnson, A. (2019, September 6). Medicare-for-All Is Not Medicare, and Not Really for All. So What Does It Actually Mean? ProPublica. https://www.propublica.org/article/ medicare-for-all-is-not-medicare-and-not-really-for-all-sowhat-does-it-actually-mean?token=YxUntiDH12MOMHz5OD 1yLBRth4wTzdEG

Serakos, M., & Wolfe, B. (2016). The ACA: Impacts on Health, Access, and Employment. Forum for Health Economics & Policy, 19(2), 201–259. https://doi.org/10.1515/fhep-2015-0027 Sommers, B. D., Maylone, B., Blendon, R. J., Orav, E. J., & Epstein, A. M. (2017). Three-Year Impacts Of The Affordable Care Act: Improved Medical Care And Health Among Low-Income Adults. Health Affairs (Project Hope), 36(6), 1119–1128. https://doi.org/10.1377/hlthaff.2017.0293 Sterbenz, J. M., & Chung, K. C. (2017). The Affordable Care Act and Its Effects on Physician Leadership: A Qualitative Systematic Review. Quality Management in Health Care, 26(4), 177–183. https://doi.org/10.1097/QMH.0000000000000146 Sullivan, H. R. (2019). Hospitals’ Obligations to Address Social Determinants of Health. AMA Journal of Ethics, 21(3), 248–258. https://doi.org/10.1001/amajethics.2019.248

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Teisberg, E., Wallace, S., & O’Hara, S. (2020). Defining and Implementing Value-Based Health Care: A Strategic Framework. Academic Medicine, 95(5), 682–685. https://doi. org/10.1097/ACM.0000000000003122 Wahner-Roedler, D. L., Knuth, D. P., & Juchems, P. D. R.-H. (1997). The German Health-Care System. Mayo Clinic Proceedings, 72(11), 1061–1068. https://doi. org/10.4065/72.11.1061 Wray, C. M., Khare, M., & Keyhani, S. (2021). Access to Care, Cost of Care, and Satisfaction With Care Among Adults With Private and Public Health Insurance in the US. JAMA Network Open, 4(6), e2110275–e2110275. https://doi.org/10.1001/ jamanetworkopen.2021.10275 Zipperer, B., & Bivens, J. (2020, April 16). 9.2 million workers likely lost their employer-provided health insurance in the past four weeks. Economic Policy Institute. https://www.epi.org/ blog/9-2-million-workers-likely-lost-their-employer-providedhealth-insurance-in-the-past-four-weeks/

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An Overview of Duchenne’s Muscular Dystrophy: Molecular Mechanisms, Clinical Manifestation, and Treatments STAFF WRITERS: AYUSHYA AJMANI, ANNA GUNDLACH, ABIGAIL FISCHER, ABENEZER SHEBERU, VICTORIA FAUSTIN, JOHN ZAVRAS LEAD WRITER: VALENTINA FERNANDEZ Cover Image Image Source: Wikimedia Commons

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Introduction 1. Background: Muscular Dystrophy There is no clear unanimity in who discovered Muscular Dystrophy (MD), but the severity of the disease is overwhelmingly agreed upon. Still, most accredit Sir Charles Bell for the first historical account of MD in 1830, in which he describes an illness in boys resulting in progressive weakness (NINDS, n.d.). A different account, written by Conte and Gioja in 1836, characterizes a similar case: two brothers with generalized weakness, muscle damage, and the replacement of muscle tissue with fat and connective tissue (Huml, 2015). MD increasingly gained attention at this historical junction, making its way into the most prominent of medical journals during the 1850’s. Neurologist Guillaume Duchenne was a particularly crucial contributor to this discussion (NINDS, 2021.). In 1868, Duchenne wrote a comprehensive account of 13 patients suffering from MD, and one of the

most severe and recognized forms of this disease now bears his name: Duchenne’s Muscular Dystrophy (DMD). Alongside DMD, there are 8 other major forms of muscular dystrophy to note: Becker, congenital, distal, Emery-Dreifuss, facioscapulohumeral (FSHD), limb-girdle, myotonic dystrophy, and oculopharyngeal. Each of these forms affects individuals differently and is not exclusive to a particular race, sex, or age (though some forms are more prevalent in certain demographical populations) (NINDS, 2021). In a systematic review detailing the prevalence of muscular dystrophies within the general population, Duchenne’s muscular dystrophy specifically was found to have a prevalence range from 1.0-4.2 per 100,000 (Theadom et al., 2021). However, it must be noted that the prevalence of Duchenne’s may not properly represent the implications of this condition, since Duchenne’s has early mortality, often before the age of twenty (Theadom et al., 2021). MD is an inherited disease where the afflicted DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 1: Cross section image of the gastrocnemius muscle from a patient who died of Duchenne’s muscular dystrophy. There is severe degeneration of muscle tissue and extensive replacement of muscle fibers by adipose cells (fatty tissue). Image Source: Wikimedia Commons

can inherit via X-linked recessive inheritance, autosomal inheritance, or autosomal recessive inheritance (Huml, 2015). While many cases of MD result from spontaneous mutations not present in parental genes, all mutations can still pass to future progeny. Such defects can interfere with the protein production required to form healthy muscle, thereby resulting in the very observations first noted by Bell: gradual loss of muscle mass and progressive weakness. There is currently no cure for MD, despite the disease being widely considered as the third most common genetic disease of skeletal muscle (Huml, 2015). It is therefore imperative to continue all manners of associated research and awareness. 2. Molecular and clinical aspects of MD As previously stated, MD is a disease characterized by weakness and deterioration of skeletal muscle mass (Mayo, 2020). Skeletal muscle serves many functions for the human body, the most important of which include locomotion and energy metabolism (Rahimov & Kunkel, 2013). Most forms of MD begin in childhood, where patients become progressively weaker until they eventually require a wheelchair (Mayo, 2020). Trouble breathing and swallowing are also common, and many cases are associated with a shortened lifespan (Mayo, 2020). Since MD is a genetic disease, mutations in different genes target different muscle groups. This partially explains why there are so many SPRING AND SUMMER 2021

subtypes of the disease (Rahimov & Kunkel, 2013). Mutations may occur in a wide range of structural proteins and enzymes, resulting in different disease phenotypes based on which proteins are affected. The basic functional unit of skeletal muscle is the myofiber, which is a long, multinuclear conglomeration of many mononuclear muscle cells called myoblasts (Rahimov & Kunkel, 2013). Satellite cells are stem cells that give rise to myoblasts and are located between the sarcolemma (skeletal muscle cell membrane) and the basal lamina, which is a basement membrane lying above the sarcolemma. Within each myoblast are many sarcomeres, which provide the contractile power of skeletal muscle. One sarcomere includes both myosin-containing thick filaments and actin-containing thin filaments that intricately slide over each other to form a crossbridge (Rahimov & Kunkel, 2013). This is how the muscle contracts, and it is a delicate process requiring the thin actin filaments and thick myosin filaments to be structurally compatible much like two puzzle pieces (Rahimov & Kunkel, 2013).

"Within each myoblast are many sarcomeres, which provide the contractile power of skeletal muscle."

Myofibrils are then attached to the sarcolemma via the Z-disks of the myofibrils, and this attachment is facilitated by subsarcolemmal protein complexes called costameres (Rahimov & Kunkel, 2013). Costameres contain an abundance of dystrophin-glycoprotein complexes that helps synchronize the contractile operations of many 263

"These molecular mechanisms surrounding skeletal muscle loss have largely been established by genetic research on animal models, in addition to gene mapping efforts on affected families"

sarcomeres within the same myofibril and combat the mechanical stress of myofibrils to prevent rupture of the delicate sarcolemma (Rahimov & Kunkel, 2013). This leads to sarcolemmal disruption, where the sarcolemma fails to attach to the basal lamina, and it is the underlying cause of most MDs (Rahimov & Kunkel, 2013). The sarcolemma is closely attached to the basal lamina via extracellular membrane proteins, and structural damage via mutation of these proteins can also cause sarcolemmal disruption (Rahimov & Kunkel, 2013). Mutation usually is localized within the laminin-ɑ2 chain, which is the part of the protein that interacts with the dystrophin-glycoprotein complexes (Rahimov & Kunkel, 2013). These protein complexes interact with entactin to help bind them to the collagen fibers which are critical to forming functional extracellular matrix (ECM) proteins (Rahimov & Kunkel, 2013). In cases of MD, the mutation is also common in collagen VI, an ECM collagen critical to ECM protein formation (Rahimov & Kunkel, 2013). Whereas healthy muscle includes myofibrils of equal size and the nuclei on the periphery of the cell, dystrophic muscle cells include myofibrils of varying diameter and nuclei aligning towards the center of the cell (Rahimov & Kunkel, 2013). This condition is the result of alternating rounds of degeneration and regeneration of myofibrils, as sarcolemmal disruption causes satellite cells to promote regeneration of myofibrils (Rahimov & Kunkel, 2013). The cyclical regeneration and degeneration of myofibrils end up exhausting the satellite cells that are tasked to repair the muscle so much so that the satellite cell count is depleted (Rahimov & Kunkel, 2013). Thus, the muscle cell loses its regenerative ability and leads to muscular deterioration and atrophy (Rahimov & Kunkel, 2013). Healthy muscle is slowly weakened and replaced with fibrous and adipose tissue, which happens in nearly all cases of MD (Rahimov & Kunkel, 2013). Furthermore, sarcolemmal disruption causes leakage of muscle proteins into the blood, further weakening the muscle and providing an important biomarker for detecting MD via blood sampling (Rahimov & Kunkel, 2013). These molecular mechanisms surrounding skeletal muscle loss have largely been established by genetic research on animal models, in addition to gene mapping efforts on affected families (Rahimov & Kunkel, 2013). 3. MD prevalence and costs to society MD encompasses a range of about thirty diseases, with s ome being more severe than others, and each with varying symptoms, inheritance patterns,

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ages of onset, and global prevalence (National Institute of Neurological Disorders and Stroke, 2021). The most common form, Duchenne’s MD, affects one in every 3,500 to 6,000 males per year (National Institute of Neurological Disorders and Stroke, 2021). Even though it is a largely genetic disease, MD can often occur in the absence of a family history of MD, which may be because the affected genes are large (2,200 kb)and are vulnerable to non-familial mutations (National Institute of Neurological Disorders and Stroke, 2021). MD affects families and healthcare institutions across the world, not only physically and emotionally, but also financially (The Lewin Group, 2012). It is estimated that the annual cost per patient for Duchenne’s MD is $50,953 (The Lewin Group, 2012). This total is attributed towards medical costs, non-medical costs, and also lost income for caregiving, where about $22,000 of the $50,000 are devoted to medical costs alone (The Lewin Group, 2012). On a larger scale, the disease costs the United States a total of about $362 to 488 million dollars a year (The Lewin Group, 2012). To put this in perspective, the cost of living with Duchenne’s MD is very similar to that of Parkinson’s, a disease that receives much more federal attention (The Lewin Group, 2012). In an international cross-sectional study, Landfelt and colleagues examined the total cost and economic burden of DMD, drawing data from over 770 muscular dystrophy patients in Germany, Italy, the United Kingdom, and the United States to estimate cost both at a societal and individual level. They found that DMD is associated with a “substantial economic burden,” which corresponded to a mean per-patient annual direct cost between $23,920 and $54,270. The total societal burden was estimated between $80,120 and $120,910 per person each year. Notably, the study also demonstrated certain economic disparities between the US and the other countries included in the analysis. For example, compared to the other countries studied (Germany, UK, and Italy), test subjects in the US had a much higher economic burden due to hospital admissions, which accounted for 24% of the total annual costs the disease produced (Landfelt et al., 2014). The authors of the paper suggested that the economic context of the disease be used to further inform health policy, financial support programs for families, and further research into the cost of MD (Landfelt et al., 2014).

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Figure 2: Diagram of the Xp21.2 locus on chromosome X containing the human dystrophin gene, represented by the yellow arrow. Image Source: Wikimedia Commons

Paper Overview and Sections This review article will provide a comprehensive overview of MDs, specifically focusing on Duchenne’s Muscular Dystrophy (DMD), which is the most widely studied type of MD. The paper will first examine the molecular mechanisms at play in DMD, focusing on the heritability of DMD and the genes responsible for encoding the proteins of the dystrophin-glycoprotein complex (DGC). Next, the paper will explore the specific components of the DGC and each of their functions in maintaining the integrity of the muscle cell’s sarcolemma. After reviewing the key molecular mechanisms associated with DMD, the paper will summarize the clinical manifestation of the disease including the various other forms of MDs and the signs and symptoms that characterize each, with particular focus on DMD. Then the paper will discuss the methods used to diagnose DMD and the current therapeutic treatments for the disease. The paper will conclude with a discussion of the psychological impacts of the disease and big picture ideas. Finally, the paper will recommend future directions for research and topics around the DMD that remain unknown and require further investigation.

Molecular Mechanisms 1. Genetics of MD Due to the heritable nature of MD, people often look to family history when determining a cause. MD largely depends on an individual’s genes when determining the probability of affliction. However, the various forms of MD complicate the genetic explanation for how the disease is passed down (LaPelusa & Kentris, 2021). Each form of

MD displays its own unique inheritance patterns. While some types of MD can follow autosomal recessive and dominant linkage patterns, others revolve around more complicated sex-linkage inheritance (Lovering et al., 2005). Genome Wide Association Studies (GWAS), which involve scanning the genomes of thousands of affected individuals to identify disease-causing genetic abnormalities, find that DMD causes progressive muscle degeneration in approximately 1 out of 5,000 boys (Mendell et al., 2012). These inheritance patterns are further complicated by non-genomic influences. Along with the molecular and genomic variations in the different forms of MD, environmental factors can create striking variations between the onset and manifestation of the disease (Barakat-Haddad et al., 2017). As a result, even when identical genetic mutations are present in two individuals, MD rarely presents itself in the same manner (Heydemanna et al, 2007). The significant variation in how MD affected individuals limits most knowledge of the disease. Studies mapping out MD genetics only took a significant turn in the 1980s with a breakthrough in DMD research. In the late 80s, a series of young girls with a DMD‐like clinical picture were identified and gathered. These individuals shared X-autosome chromosomal translocations, with the X chromosome breakpoint always being near the end of the short arm of the X- chromosome at the Xp21 region (Jacobs et al., 1981). The localization of the DMD genomic locus at Xp21 was confirmed through DNA markers, and the disease was shown to be allelic and pertained to the genes. Not only did the localization of the Figure 3: Diagram of the Dystrophin gene in normal, Becker, and Duchenne MD. The Becker variation frequently presents with a large deletion but leaves the reading frame intact. Meanwhile, small variations in the Dystrophin gene in Duchenne MD often alter the reading frame. Image Source: Wikimedia Commons

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DMD genomic locus at Xp21 confirm previous suspicions about the X-linkage of the disease, but also formed the foundation for further DMD research.

"These various subcomplexes work in tandem to link the DGC to both the ECM and the intracellular cytoskeletal network"

Using GWAS techniques, the DMD gene was identified in X-linked phenotypes, making it one of the largest genes identified in humans yet. The DMD’s ∼2.5 Mb of genomic sequence is composed of 79 exons and can be found mainly in skeletal and cardiac muscle (Blake et al., 2002). The protein associated with the DMD gene was later named dystrophin and is responsible for strengthening muscle fibers. Expression of the dystrophin gene is controlled by the brain, muscle, and Purkinje promoters, which are the first exons that get spliced to a common set of 78 exons (Blake et al., 2002). These different promoters control the regions of dystrophin protein production. While the brain promoters drive expression in neurons, muscle and Purkinje promoters drive protein synthesis in the skeletal and cardiac muscles (Goercki et al., 1992). In the common forms of MD including Becker (BMD) and DMD, different mutations take place in the Xp21 region of the X chromosome. The complexity of the dystrophin gene increases the likelihood of spontaneous mutations, which occur in nearly ⅓ of DMD cases, explaining the possibility of expressing DMD without inheritance (Lovering et al., 2005). Normal expression of the dystrophin sequence allows for the protein to assist with the transfer of muscle contraction from the inside of the muscle cell outward into the cell membrane. Alterations in the genomic sequence can inhibit this activity and prevent dystrophin from being produced in the muscles of DMD patients (Nowak & Davies, 2004). While BMD patients still have most dystrophin intact, the dystrophin is left only partially functional (Hoffman, 2020). Muscle cells without enough of this protein become damaged as muscles repeatedly contract and relax with use. 2. The Dystrophin-Glycoprotein Complex The dystrophin-glycoprotein complex (DGC) exemplifies the correlation between structure and function. As a cytoskeletal integrator, the DGC plays an essential role in stabilizing the plasma membrane of striated muscle cells, as well as in signal transduction and mechano protection (Gao & McNally, 2015). With the dystrophin gene being the largest known human gene, the DGC is critical for the maintenance of plasma membrane integrity. In fact, animal models of DGC mutants have shown the adverse effects of a mutation in any of the components of the DGC, all of which

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result in membrane fragility. This in turn leads to degeneration of skeletal muscle (Lapidos et al., 2004). During contraction of a striated muscle fiber, the myofiber temporarily shortens as the actin and myosin filaments work in tandem to allow for movement (Sweeney & Hammers, 2018). Muscle contraction requires that the machinery involved in this process remain intimately connected with the membrane and ECM (Sweeney & Hammers, 2018). If the muscle fiber were to somehow detach from its ECM, the muscle would be unable to properly contract. In this sense, the DGC provides the necessary structural support that intricately links the intracellular cytoskeleton to the ECM (Sweeney & Hammers, 2018). The DGC is divided into various subcomplexes that are classified by the location of their domains— either extracellular, intracellular or transmembrane. As implied by the complex’s name, the main protein in the DGC is dystrophin (Gao & McNally, 2015). In addition to dystrophin, however, there are three main components to the DGC: the sarcoglycan & sarcospan complexes, the dystroglycan, and the cytoplasmic proteins. These various subcomplexes work in tandem to link the DGC to both the ECM and the intracellular cytoskeletal network (Gao & McNally, 2015). 3. Components of the DGC A. Dystrophin Dystrophin is a cytoskeletal protein that localizes to the cytoplasmic face of the sarcolemma (Gao & McNally, 2015). By interacting with beta dystroglycan, which will be discussed in depth later, dystrophin is able to maintain its position near the sarcolemma. Dystrophin acts as a “mediator,” binding to actin in order to link the cytoskeletal network of muscle cells to the other components of the DGC (Gao & McNally, 2015). The dystrophin protein itself is made up of 427 kDa, making it one of the largest proteins in the human body. It is subdivided into four functional domains: the actin-binding amino-terminal domain (ABD1), the central rod domain, the cysteine-rich domain, and the carboxyl-terminus. Within the ABD1, there are two calponin homology domains (CH1 and CH2), each about 100 amino acids in length, which facilitate the direct binding to F actin through their 4-alpha helice configuration (Gao & McNally, 2015). Dystrophin’s second domain, the central rod domain, is also critical for mediating the interaction between dystrophin and F actin. This is because the domain has the second actin-

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binding motif (ABD2). The central rod domain is composed of 24 spectrin repeats (bundles of three helices), where the second actin-binding domain (ABD2) spans spectrin-like repeats #1117 (Gao & McNally, 2015). ABD1 and ABD2 work together to ensure proper association with actin filaments. The cysteine-rich domain, in turn, is found between the central rod and C-terminus of the dystrophin protein (Gao & McNally, 2015). Through its binding activity with ankyrin-B, an adaptor protein, the cysteine-rich domain is required for maintaining dystrophin’s position at the sarcolemma (Gao & McNally, 2015). Finally, the carboxy-terminal (CT) domain is essential for protein-protein interactions and contains two polypeptides that fold into alpha-helical coiled coils, structurally resembling the spectrin repeats in the rod domain (Gao & McNally, 2015). This domain has multiple binding sites that are important for the sarcolemma localization of dystrobrevin and syntrophins (Gao & McNally, 2015). Since dystrophin is one of the largest human proteins and by far the largest one in the DGC, most mutations associated with DMD directly affect the dystrophin gene and protein (Lapidos et al., 2004). Most DMD mutations occur around two mutational hotspots in the DMD gene, resulting in either extremely low expression of the original protein or a smaller but functional version of dystrophin (Lapidos et al., 2004). Therefore, to determine the phenotype, it is necessary to consider both the level of dystrophin

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and the content of dystrophin protein expression. B. Sarcoglycans The sarcoglycan and sarcospan complexes are the transmembrane components of the DGC. In a striated muscle, the major sarcoglycan complex contains α (50kDa), β (43kDa), and δ (35kDa) sarcoglycan (Gao & McNally, 2015). In vascular smooth muscle, the major sarcoglycan complex is composed of ε (50kDa), ζ (40kDa), and β (43kDa). Notably, in a dystrophic phenotype where the α subunit of the sarcoglycan complex is absent, overexpression of the ε (50kDa) subunit fully rescues the phenotype, indicating that both the α and ε subunit perform parallel functions in their respective muscle fibers (Imamura, 2005).

"Therefore, to determine the phenotype, it is necessary to consider both the level of dystrophin and the content of dystrophin protein expression."

Many studies have reported on the assembly of the sarcoglycan complex, specifically on its post-translational modifications and how it localizes to the plasma membrane. In order for the sarcoglycan complex to properly localize to the plasma membrane, all of the subunits are necessary (Shi et al., 2004). In other words, each individual subunit is unable to localize to the plasma membrane by itself. The only exceptions to this rule are the β and δ sarcoglycans, which when co-expressed can localize to the plasma membrane, indicating their collective role as the core of the sarcoglycan complex. After each subunit of the sarcoglycan complex is made in the endoplasmic reticulum, it passes by the Golgi apparatus and associates with β-dystroglycan and sarcospan while en route to its final destination, 267

"Specifically, the dystrobrevin protein heterodimerizes with dystrophin through coiled-coil motifs acting to further hold the complex together"

the plasma membrane. Once the sarcoglycan complex reaches the plasma membrane, its membrane localization is reinforced by the dystrophin protein (Shi et al., 2004). Proper sarcoglycan complex assembly and localization is crucial for muscular function. A few studies have elucidated the adverse effects of recessive mutations in the sarcoglycan genes, pointing to the wide range of MD phenotypes. For example, a study using the uptake of Evans blue dye as a readout for proper muscle contraction found that sarcoglycan-deficient mice have a weakened sarcolemma and are unable to undergo proper muscle contraction, a phenotype that parallels the one in dystrophin-deficient mice (Araishi et al., 1999; Hack et al., 1998; Hack et al., 2000). In patients with DMD (modeled by mdx mice) the sarcoglycans are absent from the sarcolemma (Hack et al., 2000). In muscles lacking dystrophin or δ-sarcoglycan, there was contraction-induced damage reported, evidenced by eccentric contraction with increased dye uptake. Notably, in the absence of sarcoglycans, dystrophin was found to still be intact. This indicated that while the sarcoglycans fully depend on dystrophin to function, the presence or absence of sarcoglycans does not directly determine whether dystrophin will function properly (Hack et al., 2000). When considering the DGC as a whole, sarcoglycans play more than a “mediator role,” as they are also important in stabilizing the DGC’s structure in two main ways. First, the sarcoglycans strengthen the connection between alpha and beta dystroglycan (Gao & McNally, 2015). In a hamster model where the sarcoglycan complex was made absent, the dystroglycan detached from the other components of the DGC, indicating that dystroglycan is unable to anchor

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to the cell membrane without the support from the sarcoglycan complex (Straub et al., 1998). The second main function of sarcoglycans is to interact directly with dystrobrevin. Dystrobrevin is one of the cytoplasmic proteins that make up the DGC. Sarcoglycans (being the transmembrane components) associate with dystrobrevin and dystrophin to maintain the integrity of the complex and therefore of the membrane. In other words, a group of proteins— either cytoplasmic, transmembrane or extracellular— associate with each other to strengthen the sarcolemma, ensuring that it is able to sustain proper contraction. Specifically, the dystrobrevin protein heterodimerizes with dystrophin through coiledcoil motifs acting to further hold the complex together (Sadoulet-Puccio et al., 1997). In addition to its mechanical roles in stabilizing the DGC, sarcoglycans are also believed to participate in signal transduction and cell-cell adhesion. In a 2005 study conducted by the University of Pennsylvania, sarcoglycan-null muscle cells were plated on a collagen-coated surface. Collagen, acting as an anchor for the cells, allowed the null muscle cells to adhere to the surface. However, the null muscle cells showed a significantly higher amount of apoptosis and hypercontractility despite their proper cell adhesion (Griffin et al., 2005). In addition, the activity level of ERK-1 (extracellular signal-regulated protein kinase), which plays numerous roles in the downstream components of distinct signaling pathways, was greatly increased in the Sgcg (sarcoglycan) null muscle cells compared to WT (Griffin et al., 2005). When an eccentric contraction was induced, WT muscle cells responded with an increased phosphorylation in ERK-1 (which activates the kinase), while the null muscle cells

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failed to increase ERK-1 phosphorylation. All in all, the abnormal response of ERK-1 in Scgc null muscle cells indicates the potential role sarcoglycans may play in mediating specific signal transduction pathways related to muscle contraction and apoptosis kinase cascades. In terms of their role in cell-cell adhesion, the sarcoglycans are believed to interact with the integrin complex, which is the primary protein involved in binding animal cells to the ECM (Takada et al., 2007). When myocytes (muscle cells) were cultured, sarcoglycans co-precipitated with integrin and other focal adhesion proteins, pointing to the cell-matrix adhesion properties of this system (T. Yoshida et al., 1998). In addition, when α- and γ-sarcoglycan were removed by antisense treatment, the number of adhesion proteins decreased as well (T. Yoshida et al., 1998). Antisense treatment utilizes short DNAlike molecules called antisense oligonucleotides to inhibit gene expression (Sharad, 2019). In the context of the myocyte cell culture, the antisense oligonucleotides bind to mRNA and downregulate the expression of α- and γ-sarcoglycan (T. Yoshida et al., 1998). The fact that this treatment resulted in a total removal of adhesion proteins, suggests a possible signaling mechanism between the two categories of proteins (T. Yoshida et al., 1998). With regards to Duchenne’s Muscular Dystrophy, this result is significant because it shows how disruption of this component of the DGC may impact the viability of a muscle cell by affecting cell-adhesion properties. C. Sarcospans The sarcospan (SSPN) is a 25 kDa highly hydrophobic, transmembrane protein that, like sarcoglycans, mechanically supports the DGC (Crosbie, 2000). SSPN contains four transmembrane domains (TMs), with both the N-terminal (NT) & C-terminal (CT) regions located inside the cell, and a large extracellular loop (LEL) between TM3 and TM4 (Crosbie, 2000). SSPN requires sarcoglycan for its proper expression at the sarcolemma. In sarcoglycandeficient human patients (and animal models), sarcospan was either fully absent from the sarcolemma or greatly reduced (Crosbie, 2000). However, mutations in the SSPN gene have not been found to cause human diseases, unlike the sarcoglycan genes (Marshall & Crosbie-Watson, 2013). SSPN functions to regulate the survival of muscle cells and work in regeneration. SSPN controls the abundance of laminin-binding complexes like the DGC, as well as the integrin complex and

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the utrophin glycoprotein complex (UGC). The UGC localizes specifically to the neuromuscular junction, where it replaces dystrophin and acts as a functionally analogous complex (Peter et al., 2008). In aged SSPN-null mice, DGC and UGC levels are lower than in younger mice, and there is also a reduced laminin-binding affinity (Marshall et al., 2012). Furthermore, SSPN-null mice also showed a delayed regeneration ability due to the loss of utrophin and Akt in the regenerating fibers, two proteins that when activated increase the survival chances of damaged muscle cells through their roles in protein synthesis (Kim et al., 2011). When Akt was delivered to the SSPN null muscle cells, the cells’ regeneration ability was restored (Kim et al., 2011). D. Dystroglycan Dystroglycan is an integral transmembrane protein present in the sarcolemma (as well as other tissues) that connects cytoskeletal proteins of the DGC to the ECM (IbraghimovBeskrovnaya et al., 1992). Proper glycosylation of dystroglycan is necessary for its function. Therefore, unlike SSPN, mutations in the genes that contribute to the dystroglycan glycosylation pathway cause muscular dystrophy-related phenotypes referred to as dystroglycanopathies (Ibraghimov-Beskrovnaya et al., 1992). The dystroglycan protein itself is encoded by one gene Dag1 and cleaved into two subunits, α and β, during post-translational modifications (Ibraghimov-Beskrovnaya et al., 1992). α-dystroglycan is crucial for ECM-ligand binding, serving as a receptor for laminins, perlecan, and agrin (all ECM proteins) (Gee et al., 1994; Ibraghimov-Beskrovnaya et al., 1992; Talts et al., 1999). As mentioned above, glycosylation is essential for proper function of α-dystroglycan; when α-dystroglycan is fully deglycosylated, it loses its ligand-binding ability. Notably, when α-dystroglycan is partially deglycosylated, meaning that only the N-linked sugars are eliminated, α-dystroglycan retains its activity as an ECM receptor. This indicates that while the ECM ligand-binding ability of α-dystroglycan is dependent on glycosylation, only the O-linked sugars rather than N-linked sugars are needed for proper function (Gao & McNally, 2015). The β subunit of dystroglycan binds to α-dystroglycan to anchor it in place at the sarcolemma; it also binds to a variety of other proteins to sustain the physical integrity of the DGC. E. Cytoplasmic Components of the DGC Cytoplasmic components of the DGC associate on the periphery of the sarcolemma and include

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dystrobrevin, syntrophin, and nitric oxide synthase (Lapidos et al., 2004). α-dystrobrevin interacts with dystrophin through their respective C-terminal coiled-coil regions and dystrophin is needed in order for α-dystrobrevin to localize to the sarcolemma (Lapidos et al., 2004). α-dystrobrevin also binds to sarcoglycans and syntrophins, the latter of which will be discussed in detail later (M. Yoshida, 2000).

"In the end, the transmembrane, extracellular, and cytoplasmic components of the DGC work together to anchor each other to the sarcolemma, regulate signal transduction pathways, cell-cell interactions, and ensure proper muscle contraction."

Because of its interactions with many components of the DGC, it is no surprise that a deficiency or lack of α-dystrobrevin results in a dystrophic phenotype in both cardiac and skeletal muscle (Grady et al., 1999). Specifically, α-dystrobrevin deficient mice lack the ability to properly mature their neuromuscular junctions and have abnormal myotendinous junctions at the interface between muscle and tendon (Grady et al., 2000). Syntrophins associate with α-dystrobrevin and dystrophin, and like α-dystrobrevin, syntrophindeficient mice showed disrupted formation of neuromuscular junctions with reduced acetylcholine receptor (Grady et al., 1999). However, unlike α-dystrobrevin-deficient mice, syntrophin-deficient mice do not develop the DMD phenotype (Adams et al., 2000). Finally, neuronal nitric oxide synthase (nNOS), the third cytoplasmic component of the DGC, is responsible for producing nitric oxide (Thomas et al., 1998). nNOS localizes to the sarcolemma and produces nitric oxide from L-arginine to control blood flow through regulation of vasoconstriction (Thomas et al., 1998). There is a remarkable understanding of the complexities of the DGC, which have helped understand the mechanical and nonmechanical roles the complex plays in muscle cells. In summary, at the sarcolemma, dystrophin binds to dystroglycan, which acts as a receptor for ECM ligands. The sarcoglycans create a complex that associates with dystrophin and dystroglycan. The intracellular molecules— dystrobrevin, syntrophins, and nNOS— are localized to the periphery of the sarcolemma through their interactions with the other components of the DGC. In the end, the transmembrane, extracellular, and cytoplasmic components of the DGC work together to anchor each other to the sarcolemma, regulate signal transduction pathways, cell-cell interactions, and ensure proper muscle contraction.

Clinical Manifestations 1. Key features of MD subtypes

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Broadly, MD is characterized by muscle weakness and impaired body movement. Common symptoms include difficulty walking, impaired function of the heart and lungs, and poor posture. With nine different types of MD, symptoms vary by condition (Hannah, 2016). DMD is the most common type of MD among children and primarily affects males (Harrison & Goldsmith, 2021). It is the first of three sex-linked MD subtypes. Diagnosis typically occurs in patients when they are around 4 years old. Patients experience progressive muscle degeneration such that by the time they are 10, they usually require a wheelchair (Guiraud et al., 2015). Symptoms of DMD include muscle pain, learning difficulty, improper gait, frequent falls, enlarged calves, and difficulty running and jumping. Ultimately, DMD patients develop severe respiratory and heart problems, often leading to premature death (Hannah, 2016). The muscle fibers of DMD patients show inflammation, disorganization, and unusual amounts of fat and connective tissues (Guiraud et al., 2015). Becker muscular dystrophy (BMD) is similar to DMD but less severe. It also mainly affects males (Hannah, 2016). While DMD results from an absence of dystrophin, BMD arises from merely defective or reduced dystrophin. Onset occurs around the ages of 5 to 15, with most patients still being able to walk after age 15 (Harrison & Goldsmith, 2021). BMD can also cause heart problems (Hannah, 2016). Emery-Dreifuss muscular dystrophy is the final type of MD that mainly affects males. It usually begins during childhood or early adolescence. (Hannah, 2016). Symptoms include weakness around the tibia and fibula, early contractures, and heart problems (Harrison & Goldsmith, 2021). Myotonic muscular dystrophy (MDD) is the most common type of MD among adults. Age of onset varies, as does the severity of symptoms. (Harrison & Goldsmith, 2021) MDD is named for its symptom of myotonia, in which the muscles spasm or harden after activity. (Hannah, 2016). MDD is also characterized by weakness of distal musculature including the hands, feet, and lower arms and legs. Patients also experience long face, wasting, excessive sleepiness, drooping of the upper eyelid, cognitive impairment, and cardiac conduction defects (Harrison & Goldsmith, 2021). MDD may affect certain other parts of the body including the eyes, gastrointestinal tract, glands, and heart (Hannah, 2016).

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Congenital muscular dystrophy occurs at birth. It includes 2 types: congenital MD with myosin deficiency and Fukuyama congenital MD. Congenital MD with myosin deficiency is characterized by muscle weakness, muscle shrinkage and joint problems. Fukuyama congenital MD is characterized by brain defects (Hannah, 2016). Limb-girdle muscular dystrophy (LGMD) usually presents in teenagers and young adults (Hannah, 2016). Patients suffer from weakness in the hips and shoulder girdles. However, the extraocular muscles, facial muscles, and intellect are unaffected. As LGMD progresses, patients lose the ability to walk. This usually happens after the age of 30. However, some more severe cases of LGMD exist in which the onset is at 3 to 5 years old and the disorder progresses more rapidly (Harrison & Goldsmith, 2021). Facioscapulohumeral muscular dystrophy begins in late childhood to adolescence (Harrison & Goldsmith, 2021). It is named for the muscles of the shoulder blade, face, and upper arm, which are predominantly affected. Patients have difficulty speaking, chewing, swallowing, and walking. However, they usually retain their ability to walk. The progression of the disorder is slow, and patients live an average lifespan (Hannah, 2016). Oculopharyngeal muscular dystrophy appears between the ages of 50 and 60 (Belliveau & ten Hove, 2014). It progresses slowly, leading to muscle weakness in the eyes and face and difficulty swallowing. Common complications include choking and pneumonia (Hannah, 2016). Distal muscular dystrophy begins between the ages of 1 and 25. The progression of the disorder is slow, with muscle weakness first appearing in the lower leg anterior compartment and spreading to the neck, fingers, shoulders, trunk, face, and tongue (Udd, 2007). Distal MD is one of the less severe forms of MD because fewer muscles are affected (Hannah, 2016). 2. Signs and Symptoms of MDs The first signs and early symptoms of MD also vary by type. DMD and BMD usually start with dilated cardiomyopathy, while Emery-Dreifuss MD begins with conduction disturbances (Mercuri & Muntoni, 2013). Myotonic dystrophy starts with cardiac abnormalities, and congenital MD starts with ventricular dysfunction or dilated cardiomyopathy. LGMD begins with

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cardiomyopathies and arrhythmias followed by muscle weakness (Mercuri & Muntoni, 2013). Facioscapulohumeral MD initially presents with muscle weakness in the face followed by the scapular fixator, upper arm, trunk, and lower extremities (Tawil & Van Der Maarel, 2006). Oculopharyngeal MD begins with ptosis, dysphagia, and limb weakness (Belliveau & ten Hove, 2014). Finally, Distal MD starts with distal leg weakness (Udd, 2007). These initial symptoms are the first indicators of MD and can lead doctors to a diagnosis. Depending on the type of MD, such symptoms can appear in a broad range of ages. The earliest type, congenital MD, often presents at birth and the latest type, oculopharyngeal MD, has been observed in middle age. 3. Diagnostic Tests The many types of MDs, which are caused by mutations in over 40 different genes, are common primary diseases of muscle tissue. Considering that most of the genes for these conditions have been identified, early and accurate diagnoses are now possible (Mercuri et al., 2019). In addition to the identification of specific genes, various diagnostic tests and physical characteristics often associated with MD have been discovered to help diagnose patients with these conditions. Nevertheless, diagnosing MD begins with a visit with a healthcare provider for a physical exam. A series of questions asked by the physician will allow the patient to share their family history with MD and their own medical history. Based on these answers, the physician can recommend any of the following tests in order to determine if MD is present and diagnose it if possible.

"These initial symptoms are the first indicators of MD and can lead doctors to a diagnosis. Depending on the type of MD, such symptoms can appear in a broad range of ages."

Blood and urine tests can be used to measure specific substances and enzymes that may typically be high in people with MD. One of these enzymes includes creatine kinase, which is released by damaged muscle tissue. If the person hasn’t had any traumatic injuries recently, this may signal the presence of MD (Mayo Clinic, 2020). Another enzyme that might signal MD is serum aldolase, which helps break down sugars into energy. Exercise assessments may be given in order to measure muscle strength (NICHD, n.d.). Certain chemicals and chemical rates are elevated following exercise in people with MD, so these assessments (which can be done bedside) help give an idea of the nature of the MD (NINDS, 2013). Additionally, heart and lung-monitoring tests like echocardiograms and pulmonary

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function tests can be used to check function of the muscles involved with the heart and lungs (Mayo, 2020 Clinic, n.d.). Genetic testing is employed to look for genes known to either cause or be associated with MD. Oftentimes, this DNA analysis can confirm the diagnosis of MD. Additionally, further research in genetic linkage studies strive towards determining if specific chromosomal genetic markers and certain diseases are inherited together (NINDS, 2013).

"Many different imaging methods can help determine if an individual has MD and the nature of their condition."

Many different imaging methods can help determine if an individual has MD and the nature of their condition. One such method is the utilization of magnetic resonance imaging, which can examine the condition the muscle is in (i.e. if there is any atrophy or size abnormalities), and is often used to monitor the progression of the disease. Another method is called phosphorus magnetic resonance spectroscopy, which uses functional imaging techniques to measure how the muscle cells respond to activity (NINDS, 2013). Biopsies are procedures where a small piece of internal body tissue can be removed either surgically, through a small skin incision, or via needle biopsy, where a hollow needle is used (Mayo, 2020 Clinic, n.d.). The specimen is then stained and may be determined to be MD, nerve disease, or other conditions. With the development of molecular diagnostic techniques, muscle biopsies have become less common and are oftentimes the last resort (NINDS, 2013). 4. Personality and Behavioral Changes Accompanying MDs Over the past couple of decades, many studies have come out detailing the accompanying behavioral traits of MD. These neuromuscular disorders caused by varying levels of dystrophin deficiencies in muscle and nervous tissues are believed to not only affect the physical wellbeing but also the neurobehavioral development of individuals with these medical conditions. The overarching consensus of the literature currently available gives reason to believe that individuals with these conditions often have distinct personality phenotypes (Polakoff et al., 1998). In 1998, The Department of Neuromuscular Diseases in Paris, France, released a study by Delaporte that aimed to investigate the possibility of a personality pattern that is consistent between patients with myotonic dystrophy (DM), a type of muscular dystrophy. This study included 15 DM

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patients and 14 healthy adults within the age of 20 to 53 year who were given the International Personality Disorder Examination. The patients with DM exhibited a homogenous personality profile, with statistically significant differences (with a p-value of less than 5%) for avoidantcompulsive, passive-aggressive, and schizotypal traits. In contrast, the personality of the control group was extremely heterogeneous, which suggests that the personality traits common in patients with MD are related to their condition (Delaporte, 1998). Similarly, a study by Young et al. (2007) aimed to define a cognitive and psychological profile of males with BMD. Enrolled in this study were 24 males (17 children and 7 adults), with a median age of 14.2 years and a range of 6 to 43.2 years. Several different psychological tests were used to assess various intellectual attributes and behavioral qualities of the patients. The results of this study concluded that patients with BMD have a homogenous cognitive phenotype. Additionally, these patients were found to have a higher probability of experiencing learning difficulties (despite findings of normal intelligence levels) and behavioral problems than the general population (Young et al., 2007). Both studies compare the personality and behavioral test results of patients possessing MDs with that of the general population. The results in both cases were statistically significant and distinct patterns were seen in the personalities of the patients with MDs. Furthermore, a more comprehensive study done in 2015 by Ricotti and colleagues was able to include more participants and come to more comprehensive results on the incidence of specific personality traits within patients with DMD. The study included 130 males with DMD (mean age 9y 10mo, range 5-17yr). The methods of this study were similar to Young and colleagues’ study in that each of the participants completed IQ assessments and neurodevelopmental screening questionnaires. However, in addition to these assessments, 87 of them were evaluated further through structured diagnostic interviews and parent-reported questionnaires. The results showed that the difference between the overall mean score on the questionnaires of children in the study and the general population was highly statistically significant, with a p-value measuring less than 0.1%. The average intelligence was below the population mean. Statistics for the incidences of intellectual disabilities, autistic spectrum disorders, hyperactivity, and

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inattention in children with DMD were far above those of the general population. This, along with the conclusions of the two studies previously mentioned, strongly suggests that there is a “neuropsychiatric syndrome” that often accompanies MD (Ricotti et al., 2015).

with disease progression, with FF and MRI T2 levels demonstrating a nonlinear, sigmoidal trajectory over time. The strongest predictors of future loss of function were the vastus lateralis FF, soleus FF, vastus lateralis MRI T2, and the biceps femoris long head MRI T2 (Barnard et al., 2011).

Some believe that— in addition to phenotypic manifestations of genetic mutations in those with MD— the stress of handicapping conditions (such as MD) makes it difficult to master the routine tasks in our society by which emotional and behavioral development occurs (Polakoff et al., 1998). However, further research must be done to determine if these distinct neuropsychiatric traits can also be attributed to the social and environmental factors one experiences during pediatric development or solely to the gene mutations that cause MD.

MD Treatment

5. Early identification of MDs with Clinical Biomarkers Research on clinical biomarkers of DMD has traditionally focused on identifying pharmacodynamic biomarkers in order to evaluate the effectiveness of therapies. These biomarkers have not yet been fully identified, but researchers have demonstrated the promise of circulating microRNAs (miRNAs) as markers of disease progression (Roberts et al., 2013, Mizuno et al., 2011). Roberts and colleagues used the mdx mouse model— a model that introduces a point mutation in exon 23— to demonstrate a relationship between dystrophin rescued levels and restored microRNA levels (2013). They also found a positive correlation between the expression of myogenic miRNA, miR-206, and the myogenic transcription factor in the anterior tibialis muscle and serum dystrophy-associated miRNA levels (Roberts et al., 2013). A second group, Mizuno and colleagues, quantified serum miRNA levels in two mouse models (dystrophindeficient and mdx) and in a canine X-linked MD dog model (CXMD(J)). They observed elevated levels of muscle-specific miRNAs (miR1, miR-133a, and miR-205) in both the mdx and CXMD(J) models (Mizuno et al., 2011). In addition to serum biomarkers, imaging techniques have also been used to identify clinical biomarkers. Barnard and colleagues identified several clinical biomarkers of disease progression using magnetic resonance imaging (MRI) to measure muscle fat fraction (FF) and MRI T2 markers in the lower extremities of patients with MD (2020). In the 48-month longitudinal study, Barnard and colleagues found that these lower extremity biomarkers were strongly associated

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Currently, there are multiple modes of treatment available for the various forms of MD, but as mentioned, a cure has yet to be discovered. Gene replacement therapy, for example, has great potential in addressing the primary cause of MD (defected protein production), but there are many associated challenges including therapy timing, the development of precise gene-therapy vectors, and the avoidance of potential immune responses to the replacement gene (National Institute of Neurological Disorders and Stroke, 2021). Similarly, one could also consider genetic modification therapy as a means to bypass inherited mutations. As described earlier, afflicted persons with DMD often have mutations in the dystrophin gene which inhibits their dystrophin protein production. If this treatment plan were in action, one can theoretically manipulate protein synthesis and produce a gene that “skips” the mutation, allowing for a functional or semifunctional dystrophin gene. As of now, the research explores this approach in terms of drug application and antisense therapy, which targets mRNA to inhibit gene expression (National Institute of Neurological Disorders and Stroke, 2021). Cell-based therapy is another developing treatment option. As muscle cells of MD-afflicted individuals often lack a critical protein, scientists are investigating missing protein replacement via the introduction of muscle stem cells (National Institute of Neurological Disorders and Stroke, 2021). Doing so would theoretically allow for the production of the missing protein, as well as potentially restore muscle function. From just these few approaches, much progress has been made in the treatment of MD, but further research is still necessary to allow for the continued improvement of MD-patient quality of life (National Institute of Neurological Disorders and Stroke, 2021). 1. Therapeutic Approaches: Medications & Developments Drugs to treat muscular dystrophy are continuously under development and experimental trials. In addition, it’s important to

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frequently monitor the progression of the disease to determine what drug treatments will target affected areas of the body and adjust that as the disease progresses. Typically, people with MD are treated by a team of medical specialists who can recommend treatment options such as medical, physical and occupational, and possibly surgical interventions (Birnkrant et al., 2018).

"Despite its initial promises, genomic therapy is limited by the abilities of the current CRISPR system."

Currently, the most common medications prescribed to muscular dystrophy patients are corticosteroids, such as prednisone and deflazacort (commercial name Emflaza), which work to delay the progression of MD by improving muscle cell membrane repair (Birnkrant et al., 2018, Torgan 2018). In addition to corticosteroids, heart medications such as angiotensionconverting enzyme (ACE) inhibitors or betablockers are often prescribed as well (Birnkrant et al., 2018). Eteplirsen, the first FDA-approved drug for the treatment of DMD, and golodirsen are also commonly prescribed (Birnkrant et al., 2018). Other therapeutic approaches, such as range-of-motion and stretching exercises, braces, mobility aids (canes, walker, wheelchairs, etc.) and breathing assistance can help improve the quality of life for people with MD (Birnkrant et al., 2018). 2. The Future of MD Treatment Despite the present use of therapeutic techniques and medications for MD patients, these solutions are often inadequate. In the testing of different MD medications on different age groups, most treatments were only able to slow down the degradation of patient mobility (Kupatt et al., 2021). In fact, despite the initial promise for patients, phase 2b trials of common MD medications involving 174 patients aged 5–20 years did not reach significant improvement in the endpoint of treating the disease (Kupatt et al., 2021). The lack of a proper cure for MD has been a major concern for researchers, who now study genome editing as a viable alternative (National Institute of Neurological Disorders and Stroke, 2021). Since the development of the Cas-9 mouse model, which allows scientists to alter pinpoint genes, it has become clear that gene editing technology offers promise for the course of inherited diseases such as MD. Studies corroborate that although certain limitations exist such as the preference of non-homologous end-joining (NHEJ) over homology-directed repair (HDR) upon enzymatic cleavage of the double-stranded DNA by Cas9, MDs seem an ideal target for genome editing (Kupatt et al., 2021). Particularly, for

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DMD, which is caused by an X-linked mutation in the Xp21 region, genomic editing can alter the internal truncations of the dystrophin gene to restore normal levels of protein or even restore DMD patients with a milder form of MD such as BMD (Chemello et al, 2020). In contrast to current pharmacological approaches, most genomic editing techniques aim to restore the expression of the protein that MD patients lack. Despite its initial promises, genomic therapy is limited by the abilities of the current CRISPR system. The genome-editing tool requires protospacer adjacent motif (PAM) sequences to pinpoint the target site for DNA repair (Hotta, 2015). The PAM sequence plays a critical role in the initial step of sequence recognition and helps distinguish bacterial self from non-self DNA. The necessity for certain sequences for the CRISPR system to function during initiation reduces its ability to target any sequence within the dystrophin gene (Hotta, 2015). Thus, when considering the efficacy of MD treatment, exon snipping may offer a path to the future development of an applicable therapeutic option, but it may also require advancements in CRISPR technology before being clinically viable (Hotta, 2015).

Conclusion In the United States alone, the different MDs impact nearly 250,000 individuals (NORD, 2021). Despite the decades of ongoing research into the disease, much of MD has still yet to be explored and mapped out. Especially for the rarer forms of MD, almost nothing is known yet about the different inheritance patterns and their impacts on different age groups (Mercuri & Muntoni, 2013). While researchers have attempted to extrapolate existing knowledge of DMD and BMD towards these other forms, the complexity and nuances of how the disease manifests have halted significant progress. However, despite the hurdles, bringing attention to the forefront of MD research is crucial for hundreds of thousands of individuals (Theadom et al, 2014). Due to the progressive nature of DMD, the consequences of this detrimental disease reach far beyond the physical symptoms of the patient (Venugopal & Pavlakis, 2021). In a study conducted to assess the psychological impact of DMD on 26 male patients, all subjects reported feelings of isolation, self-depreciation, depression, anxiety, and a general sense of insecurity (Filippo et al., 2012). In addition to the psychological impact of the disease, DMD has also been found to cause impairments of intelligence

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of variable degrees, particularly problems with long-term memory (Filippo et al., 2012). About 30-40% of patients with DMD have some sort of mental retardation, although whether the cause of the intellectual deficits is due to biological, emotional familiarity, or social factors remains unknown (Nardes et al., 2012). It is important to remember that the psychological impact of DMD extends beyond the patient and affects families, which are typically overprotective and consumed by anxious and depressive thoughts and reactions (Filippo et al., 2012).

Molecular Genetics, 8(9), 1589–1598. https://doi.org/10.1093/ hmg/8.9.1589

Fortunately, there has been an increased focus on research aimed at improving the psychological repercussions for patients with DMD and their families. In 2010, the Center for Disease Control and Prevention sponsored new management guidance for DMD, updating it in 2018. Addressing the issue has become a stronger priority for the entities involved in DMD research and awareness, which is a step in the positive direction for DMD patients and their families. The main recommendations include increased screening for mental health issues to maximize optimal medical care and identify early-on issues that may interfere with appropriate medical treatments (Colvin et al., 2018). Screening scores should be recorded to allow for tracking of symptoms over time, which will help determine whether consultation with specific mental health specialists is required or not. In addition, families are encouraged to have productive conversations around DMD to expose their children to all factors of the disease. Beginning these conversations early will normalize discussion of DMD for the child and will facilitate their mature decision-making and eventual independence as they grow older (Colvin et al., 2018). Evidently, stronger research efforts to find a cure for DMD are essential. For now, more potent psychological monitoring will also remain a key player in improving the quality of life for DMD patients as well as their families.

Belliveau, M. J., & ten Hove, M. W. (2014). Neglected conditions: Oculopharyngeal muscular dystrophy. Canadian Medical Association Journal, 186(6), 453.1-453. https://doi. org/10.1503/cmaj.114-0025

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DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

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DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE Hinman Box 6225 Dartmouth College Hanover, NH 03755 USA http://dujs.dartmouth.edu dujs@dartmouth.edu

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Dartmouth Undergraduate Journal of Science - Spring and Summer, 2021

Articles inside

Challenges in the Clinical Treatment of Obese Cancer Patients Anahita Kodali '23

Mutant p53 and its Isoforms in the Onset & Treatment of Breast Cancer Brooklyn Schroeder '22

Healthcare Inequality for Unauthorized Immigrants Anushka Bhatia '24

When Hands Are Tied Instead of Tubes: The Barriers Women Face in Accessing Tubal Ligations Caroline Conway '24

Health and Heat Waves: Harbingers of What's to Come with Anthropogenic Climate Change Cady Rancourt '24

Effects of Exercise on Mental Health Aarun Devgan '23

Bibbidi Bobbidy Bone: Exploring the Magic Behind Bone Tissue Engineering Amritha Anup '23

Addressing the Plastic Waste Problem with Chemical Upcycling Anna Kölln '22