Dartmouth Undergraduate Journal of Science - Winter/Spring 2022 by dartmouthjournalofscience

DUJS

Dartmouth Undergraduate Journal of Science

WINTER & SP R I N G 2 0 2 2

VO L . X X I V

N O. 1

RENEWAL

SCIENCE AS A CYCLE OF QUESTIONS C OV E R A RT B Y G A IA Y U N ' 2 5

A Bioinformatic Analysis of mecA Prevalence in Bacterial Species

Pg. 25 1

Overcoming Mortality: A Denial of Death & Dying

Pg. 71

An Excavation of the American Healthcare System

Pg. 125 DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Letter from the President Dear Reader, Our understanding and view of the world of science is constantly evolving as researchers continue to find new pieces of the puzzle. In just the past decade, researchers and doctors around the world have published breakthrough articles on mental health, cancer treatment, black holes, and engineering instruments. These findings have both shed light on previously unanswered questions in scientific communities and provided new opportunities and questions for a future generation of scientists to explore. It is with this in mind that we decided the theme of this article should be Renewal. Each writer in this edition of DUJS embarked on a cycle of curiosity, exploration, answering, and resparked curiosity as they researched and published papers on a topic they are deeply passionate about. The list of topics represented in this edition of the Journal was incredibly broad. In the engineering sciences, Katherine Lasonde, ’23, presented novel work on the use of nitrogen-vacancy quantum defects, which have the potential to change the way scientists do NMR experiments. Rujuta Purohit, ’24, focused on the astrological sciences and described supermassive pockets in space and astronomers' search for active galactic nuclei within the stars. Vania Zhao, ’25, explored our conceptions of death and mortality utilizing an interdisciplinary framework. These three articles touch on just a fraction of the topics studied in this edition of the Journal. Though the list of topics was broad, each paper drew on an incredibly rich and specific base of previous knowledge. Each paper answers a fundamental question within its field – whether it be health, astronomy, engineering, or something else entirely – and each provides a ground base for readers to ask even more questions. It is my hope that as you read through the papers in this edition of DUJS, you push yourself to think deeply about the topics that you are presented with and find new interesting questions to explore yourself. Sincerely, Anahita Kodali

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: Aditi Gupta '23 Chief Copy Editors: Alex Gavitt '23, Andrew Sasser '23, Audrey Herrald '23, Daniel Cho '22, Dina Rabadi '22, Eric Youth '23, Kristal Wong '22, Maddie Brown '22 EDITORIAL BOARD Managing Editors: Callie Moody '24, Carolina Guererro '24, Caroline Conway '24, Geogia Dawahare '23, Jennifer Chen '23, Matthew Lutchko '23, Miranda Yu '24 Assistant Editors: Grace Nguyen '24, Juliette Courtine '24, Owen Seiner '24, Rujuta Purohit '24, Sicong (George) Shan '23, Soyeon (Sophie) Cho '24, Valentina Fernandez '24 STAFF WRITERS Abenezer Sheberu ‘24

Julien Grimaud

Abigail Fisher ‘23

Juliette Courtine ‘24

Aditi Gupta '23

Katherine Lasonde '23

Aksheta Kanuganti ‘24

Kevin Staunton ‘24

Allison Pittman ‘25

Kristal Wong ‘22

Anahita Kodali ‘23

Lauren Ferridge ‘23

Andrew Barry ‘24

Madeleine Brown ’22

Anjali Dhar '24

Madeleine Carr '24

Arshdeep Dhanoa ‘24

Maryanne Barasa ‘25

Ash Chinta ‘24

May Jin '25

Ashna Kumar ‘24

Md Mubtaseem Ahnaf

Ayushya Ajmani ‘24

Aronno ‘24

Bridget McNally ‘24

Nathan Thompson ‘25

Caroline Conway '24

Patrick Herrin ‘25

Cecelia Plass ‘25

Rohan Menezes '23

Daniel Cho ‘22

Rujuta Purohit '24

Dina Rabadi ’22

Sarah Berman ‘25

Elizabeth (Shuxuan) Li '25

Sarah Chacko '23

Emily Johns

Soyeon (Sophie) Cho ‘24

Erica Simon ‘25

Sreekar Kasturi ’24,

Francisca Fadairo '25

Stephen Adjei '25

Frankie Carr ‘22

Summer Hargrave '25

Hayden Barry ‘25

Tyler Chen ‘24

Huong Le

Ujvala Jupalli '25

Hyunjin Rheem '25

Vaishnavi Katragadda ‘24

Isabelle Kocher '22

Valentina Fernandez ’24

Ishaan Goswami

Vania Zhao '25

Jean Yuan '25

Varun Lingadal ‘23

Jennifer Do-Dai ‘25

Victoria Faustin ‘23

Jenny Oh ‘25

Yihan (Elaine) Pu ‘25

Julian Franco Jr. '24

Zara Kiger ‘25

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

Table of Contents

Individual Articles Our Consciousness During and After Meditation: A Study of the Neural Basis of Meditation and How the Practice Alters Our Consciousness Anjali Dhar '24, Pg. 5

Face Blindness: Case Studies on Developmental Prosopagnosia Elizabeth (Shuxuan) Li '25, Pg. 14

Breast Reconstruction and the Risks of a Mastectomy Hyunjin Rheem '25 & Jean Yuan '25, Pg. 20

A Bioinformatic Analysis of mecA Prevalence in Bacterial Species Ishaan Goswami, Pg. 25

“I can't stop eating”- Binge Eating Disorder and the Leptin Signaling Pathway Huong Le, Emily Johns, Julien Grimaud Pg. 36

The utilization of Nitrogen-vacancy quantum defects for NMR experiments Katherine Lasonde '23, Pg. 41

Supermassive Pockets in the Cosmic Neighborhood: Searching for Active Galactic Nuclei Rujuta Purohit '24, Pg. 54

Passive Sensing to Prevent Mental Health Issues during the COVID-19 Pandemic Stephen Adjei '25, Pg. 61

An Introduction to Blood Pressure Ujvala Jupalli '25, Pg. 67

Overcoming Mortality: A Denial of Death & Dying Vania Zhao '25, Pg. 71

Team Articles

Investigating the Annual Influenza Vaccine Pg. 81

Innovations in Cancer Treatment Pg. 91

Food Justice and the Impacts of Food Insecurity on Health Pg. 106

136

An Excavation of the American Healthcare System Pg. 125

Assisted Reproductive Technology: An Overview Pg. 136

Physician Burnout During the COVID-19 Pandemic Pg. 144 4

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Our Consciousness During and After Meditation: A Study of the Neural Basis of Meditation and How the Practice Alters Our Consciousness BY ANJALI DHAR '24 Cover Image Source: Wikimedia commons

Image 1: An ancient statue of the meditating Buddha from Pakistan Image Source: Wikimedia Commons

Meditation was also a common practice in Buddhism, an early religion that emerged around the 6th century BCE. In canonical Buddhist literature, Sidhartha Gotama, or the Buddha, attained nirvana (enlightenment) under a Bodhi tree after profuse meditation (Encyclopedia of Global Religion, 2011). Today, there are three main branches of Buddhism: Theravada, Mahayana, and Vajrayana. Theravada, when compared to Hindu tantric practice, has a more passive discipline. In the former’s practice of bhavana (meditation), one strives to attain awareness of samatha (calm) and vipassana (insight or enlightenment). Together, these two create a practice that brings the body to a state of sunyata (emptiness), after which it is ready for the “adsorption” of true, objective knowledge (Encyclopedia of Global Religion, 2011). The goal of consistent meditation is to relieve one of their sufferings. In Buddhist literature, this suffering originates from the false belief that one’s perceptions and thoughts are real. By meditating, the consciousness becomes aware that its thoughts and perceived reality are false, revealing the impermanence of its suffering. From this point, the mind is liberated from its anguish, as its perceived reality no longer predicts its destiny. The discipline of meditation traveled West in

the late 19th century when Eastern philosophies began to be transcribed into English. It wasn’t until the counterculture movement in the United States that meditation centers were established with increasing frequency (Encyclopedia of Global Religion, 2011). In the modern day, a novel form of meditation has appeared; many

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Western, contemporary meditators use mobile meditation apps that provide a wide array of guided meditations (Bostock et al., 2019). These apps provide a new way to tackle modern day stressors, such as work stress, which is often correlated with depression, anxiety, cardiovascular disease, and type II diabetes (Ganster & Rosen, 2013). Although their efficiency is currently under review, meditative mobile applications make the practice more accessible, perhaps providing ample fuel for a modern-day revolution of consciousness. Defining meditation A famous Buddhist analogy describes the brain as a wild monkey that never sits still (Carr, 1993). The monkey is always engaged in some activity, jumping from one thought to the next. One might try to restrain the monkey to gain some peace and quiet. However, this is a short-term solution, as the monkey will be angered by the restraint and made more restless. Instead, one must teach the monkey to sit still using the discipline of meditation. After years of practice, the monkey will eventually learn to sit on its own (Carr, 1993).

of Global Religion, 2011). Whenever one loses focus of the breath, the user is advised to return their focus to the breath with gentle, nonjudgmental awareness. This practice increases one’s saliency of their own bodily states, decreases reactivity to external stimuli, and induces an acceptance of the fleeting nature of our thoughts and feelings. As a note, these studies cannot be generalized to all types of meditation. Many meditative practices focus on the cultivation of attention and awareness, suggesting a common underlying neural circuit for all types of meditation. However, this generalization cannot be made without further research into each individual practice.

As it is such a dynamic and wide-ranging practice, meditation has been defined in many ways. For this paper, the practice of meditation will be defined as cultivated, volitional attention on a specific object or repetitious activity with the goal to eventually alter one’s consciousness. The latter is important, as meditation is most successful when complete mastery of the mind is desired. It is important to note here that the purpose of mediation is not solely to attain enlightenment, but rather learn a new way of life that is superior to one’s current day-to-day habits.

The volitional practice of meditation

There are many different types of meditation, as the practice is ancient and has evolved in many different cultures. Generally speaking, there are two main types of meditation: passive and active. The typical Western belief is that meditation evokes bodily states of calm and tranquility. However, as a practice, meditation aims to master the mind completely. Thus, the discipline must cultivate control over both the active and passive habits of the brain (Tse, 2019). There are many practices that focus on the cultivation of active control, such as yoga and the martial arts (Encyclopedia of Global Religion, 2011). This paper, then, will discuss the more passive form of meditation.

The volitional practice of mindfulness meditation can be described as a cycle between concentration and awareness, as shown in Figure 2. Concentration is the cultivation of volitional attention on a specific object of the meditation (like the breath). Prolonged concentration is preferred – however, distraction is often inevitable. After consistent practice, the ability to concentrate is enhanced, as pertinent brain regions are repeatedly used and conditioned, discussed further later in the paper.

When considering passive meditation techniques, there are still many different types. This paper will focus on mindfulness meditation. Mindfulness meditation involves the cultivation of volitional attention on a specific desired object, such as the breath, to obtain mental tranquility (Encyclopedia WINTER/SPRING 2022

Although many different feelings arise during meditation, it is important to understand the volitional practice behind it; in other words, it is important to understand the conscious, intentional processes implemented to control the body and mind during meditation.

Image 2: The volitional practice of meditation: a cycle between concentration and awareness. Image Source: Made by Dhar in Google Slides

"... The volitional practice of mindfulness meditation can be described as a cycle between concentration and awareness..."

The human mind is prone to distraction. This distraction manifests itself during meditation as a loss of concentration on the breath (or an object of the meditation). During this loss of focus, the brain becomes engaged in undesirable thought. It is here that awareness comes into play, as once the user becomes aware of their distraction, they can gently and non-judgmentally note the 6

mind-wandering behavior and return to the breath (the concentration stage). Although many novice meditators chastise themselves over being constantly distracted, the purpose of mindfulness meditation is to enhance one’s awareness of mindwandering through consistent re-correction. In summary, mindfulness meditation flows between the volitional practices of prolonged concentration and later awareness of mindwandering that may arise during the exercise.

"...increased awareness of the present moment also allows the user to review their physical body."

What we consciously experience during meditation

Figure 3: Hasenkamp et al.’s model of the volitional practice of meditation: an amplified cycle.

There are physical and emotional feelings that arise during the meditative experience as well. Of these sensations, one that is most easily recognized is the feeling of calm or tranquility. The user is unable to consider past or future events due to an active focus on the breath. This fosters an awareness of the present moment, allowing the mind to be still. The body follows suit, creating a physical and mental calm. This has been described as a “relaxation response,” where the body feels sleep-like yet the mind aroused (Lazar et al., 2000).

Image Source: Made by Dhar in Google Slides

This increased awareness of the present moment also allows the user to review their physical body. It is difficult to observe one’s bodily sensations throughout the day, as one is constantly flooded with new sensory information and plagued with a myriad of thoughts. These thoughts, however, fade with meditation, allowing the user to note their bodily sensations. This cultivates an acceptance for bodily sensations by realizing our feelings’ impermanence, building on the idea that meditation alleviates suffering. One prominent example of these bodily sensations is the feeling of pain, a discomfort often associated with suffering. Recent studies have shown how meditation could help those who experience chronic pain (Bawa et al., 2021). As one learns to accept pain rather than to fear it, they feel alleviated from their pain, as it is this fear that generates most of their discomfort. Although it is still in the early stages of research, the use of mindfulness techniques to treat physical and psychological disorders appears to have promising results. The neural circuitry of the meditative practice When considering the neural circuitry that underlies meditation, both the neural basis of the practice and the long-term neuronal changes

To first consider the neural basis of the literal practice, one can look one can look no further than Hasenkamp et. al’s model of the meditative cycle, as shown in Figure 2. This cycle is very similar to that in Figure 1, accompanied by two more phases. To briefly explain this model, the sustained concentration stage is followed by “mind-wandering (MW)” in which the user becomes distracted. An “awareness of MW” occurs when the meditator realizes they have become distracted. Finally, there is a “shifting of attention” as the user disengages from the act of MW and returns to their original focus. This model represents the meditation cycle studied by Hasenkamp et. al in a 2012 fMRI study. Experienced meditators were asked to meditate for twenty minutes in the fMRI scanner, pressing a button each time they became aware of MW. This action gave researchers a timestamp which allowed them to match meditators’ brain activity to the various proposed stages of meditation (Figure 3). The brain regions employed during the “sustained focus” stage were involved in cultivating volitional focus during the meditation. This concentration required both the dorsal and ventral attentional networks, whose associated brain areas are the anterior cingulate cortex (ACC), the lateral ventral prefrontal cortex (lvPFC), and the basal ganglia (Raz, 2004). This concentration was also characterized by activity in the dorsolateral prefrontal regions. These areas have been previously implicated with the executive control network, a subdivision of the attentional networks (Hasenkamp et al., 2012). The executive control network assigns attention to a desired object. In the case of meditation, the executive control network must direct attention to the object of the practice’s focus. The observed, sustained activity of these regions suggests that this concentration

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requires the constant reassignment of attention in a top-down manner. Top-down control is defined as a process in which upper-level brain areas (such as the prefrontal cortex) give directions and control lower-level brain regions (Raz, 2004). The dorsolateral prefrontal cortex then must constantly re-assign attention to the breath (in the case of mindfulness meditation) as a form of active rehearsal. This active rehearsal enhances attention, providing prolonged concentration necessary for this meditative technique. During the “mind-wandering” phase, activity was observed in the posterior parietal cortex (PCC) and the medial prefrontal cortex (mPFC). These areas, along with the precuneus, are the primary brain regions associated with the default mode network (DMN) (Mason et al., 2007). The DMN is the resting state of the brain, active when one is not engaged in a goal-oriented task. It is the network responsible for our internal virtual reality, self-referential thought, and simulation of future possibilities, functioning as a planning mechanism (Mason et al., 2007). It is then understandable that this network is active during the “mind-wandering” phase of meditation, as the meditator becomes distracted from the task at hand. This also supports the default mode network interference hypothesis, which states that activation in the DMN can emerge during goal-oriented tasks to disrupt one’s focus (Brewer et al., 2011). Considered on a neuronal level, active circuitry in the DMN can compete with task-positive neural circuitry. This neuronal competition may lead to the success of DMN-positive circuitry, causing distraction in the user. Furthermore, this neuronal competition makes sustained concentration difficult, reaffirming how the DMN is associated with

deficits in task performance. Brain activity in the premotor areas of the brain was also observed just before the meditator pressed the button and became aware of MW. Therefore, there is a possibility that activity in the default mode network, be it self-referential thoughts or future plans, began to realize motor planning. Since this motor planning was founded in the false reality of one’s brain, an error detection network can suddenly realize the act of mind-wandering. This is manifested in the act of pressing the button, as the meditator is awoken from their stupor. This error detection network, otherwise known as the salience network, acts to keep the brain on task. It primarily consists of the anterior cingulate cortex (ACC) and the cingulo-opercular control network (Raz, 2004). During this sudden saliency, activity in the bilateral anterior insula and the dorsal anterior cingulate cortex was observed as well. Both areas are associated with the error detection network as well, with the bilateral anterior insula primarily responsible for present moment consciousness (Hasenkamp et al., 2012). This is shown in its activity during the “awareness of MW” phase; as the brain suddenly realizes it has been distracted, the bilateral anterior insula becomes active, increasing current moment awareness. The primary role of this salience network is to detect the error that the brain is off-task and no longer concentrating on the breath. After this detection, the salience network must identify the distractor so that the executive control network can then disengage attention from this distractor. Amihai, I. & Kozhevnikov, M. (2014). Arousal vs. relaxation: a comparison of the neurophysiological and cognitive correlates of Vajrayana and Theravada meditative practices. PLoS ONE, 9(7). Image 4: The common brain

activation of the default mode network, with notable prefrontal and precuneus activation. Image Source: Wikimedia Commons

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part of the executive control network, responsible for much of the top-down control of the brain (Raz, 2004). They are active during visual tasks, suggesting their necessity in goal-oriented activities. In particular, the parietal regions are associated with the disengagement of attention, allowing the brain to reorient itself and return focus to the breath (Hasenkamp et al., 2012). The activity of these parietal regions decreased during the later phase of “sustained attention,” indicating that they are not necessary for prolonged concentration. Instead, their primary function is to disengage task-negative attention and reestablish task-positive attention, characteristic of the “shifting attention” stage of meditation.

"... meditation causes increased acceptance of bodily sensations."

How meditation alters functional connectivity in the brain There have been a handful of studies that observe the long-term effects of meditation on the brain. One prominent project was conducted by Brewer et al. in 2011, which compared fMRI scans of both experienced and novice meditators. It was found that experienced meditators had a downregulated default mode network when compared to those novice meditators both during and after the exercise (Brewer et al., 2011). This supports the aforementioned default mode network interference hypothesis, as activity in the DMN leads to deficit in task performance. Experienced meditators had lower activity in their DMN because they frequently practice the act of staying on task (in the form of mindfulness meditation). This repetitious volitional practice rewired their brains, allowing them to decrease DMN activity and increase the executive network’s control of the brain. This supports the theory of neural plasticity, a concept in which the neurobiology of the brain changes during an individual’s life in response to an environmental stimulus. This reveals how volitional practices can change one’s pattern of thought. In addition to this comparative study, Brewer et al. (2011) also ran a functional connectivity analysis between areas of the default mode network and the executive control network in both novice and experienced meditator groups. It was hypothesized that in the experienced meditator, there would be increased functional connectivity between the default mode network and executive control network. The executive control network would become more active whenever mind-wandering was employed as a form of “monitoring for conflict” (Brewer et al., 2011). After placing a seed in the PCC, a primary node of the DMN, Brewer et al. observed increased connectivity between the PCC and the medial prefrontal cortex (mPFC) in experienced

meditators, as well as increased PCC connectivity with the dorsolateral prefrontal cortex (dlPFC). Both the mPFC and the dlPFC are associated with cognitive control processes in the brain. This increased functional connectivity can be explained as a “coactivation,” in which activity in the default mode network predicts activity in these cognitive control regions (Brewer et al., 2011). As experienced meditators repeatedly practice shifting their attention from MW to complete concentration on the breath, the act of MW immediately elicits activity in the executive control network as a form of error detection. This practice causes these areas to become intricately intertwined. Experienced meditators can consistently detect the error of MW, therefore enhancing their attentional capabilities. This again supports the notion of neural plasticity, showing how the volitional practice of meditation can alter connectivity among various brain regions. How the autonomic nervous system develops with consistent meditation As mentioned before, meditation causes increased acceptance of bodily sensations. In fact, numerous observational studies of experienced meditators have shown drastic changes in parasympathetic body control (Benson et al., 1974; Lazar et al., 2000). To begin this analysis, consider the following physical example of autonomic nervous system transformation. Emotional states of high stress, such as fear or anxiety, are often accompanied by an increased rate of breath. Specific breathing techniques (like mindfulness meditation) require the user to volitionally control their pattern of breath. In doing so, one can elicit the emotional states associated with those controlled breathing patterns. Later, in situations of high stress, an experienced meditator can implement these techniques, slowing their breathing rate. This new breath pattern will trigger the more relaxed emotional state associated with it. The autonomic nervous system contains neurons from both the central and peripheral nervous systems. This system is made of two opposing networks known as the parasympathetic and sympathetic nervous systems. The sympathetic nervous system is active during situations of high stress that require a “fight or flight” response. Physical responses of the sympathetic nervous system include increased heart rate, blood pressure, and breath rate. The sympathetic response is associated with a state of phasic alertness, in which the body can respond to stressful and demanding stimuli. Conversely, the parasympathetic nervous system is active during situations of low stress, in which the body elicits

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a “rest and digest” response meant to heal and restore the body (Low, 2013). Parasympathetic responses are usually characterized by lowered blood pressure, heart rate, and breath rate. The parasympathetic response has no need for phasic alertness, as there are no demanding stimuli to be addressed. Rather, a different kind of awareness, known as tonic alertness, is employed during parasympathetic response. As activation of the sympathetic and parasympathetic nervous systems are mutually exclusive, tonic alertness describes one’s ability to respond to stimuli when the sympathetic nervous system is deactivated (Amihai and Kozhevnikov, 2015). During passive meditation, the parasympathetic nervous system is upregulated. A “relaxation response” is then generated, as studied extensively by Lazar et al. in their 2000 paper. They define it as such: "Meditation is one technique that induces a set of integrated physiological changes termed the relaxation response and is effective as a complementary treatment for many diseases… The practice of meditation induces a hypometabolic state characterized by decreases in many physiological measures as well as by changes in EEG patterns. These EEG changes are different from those associated with sleep, and suggest that while subjects are deeply relaxed and have decreased peripheral activity, they are engaged in an active mental state requiring intense neural activity (1581). " This relaxation response explains the aforementioned sleep-like yet energized conscious experience of meditation. Lazar et al. describe this state to be “hypometabolic,” suggesting that usual sympathetic activity is decreased in this meditative state. Although this decrease is typically associated with periods of rest and sleep, Lazar et al. note that this relaxation response differs from sleep states as the mind is engaged in “intense neural activity.” This implies that meditation creates a mental state unlike any other cognitive exercise known to humans. At a physiological level, this relaxation response has been characterized by a decrease in cardiorespiratory activity. This relaxation response also elicits activity in brain regions associated with arousal and autonomic control, such as the pregenual anterior cingulate, the amygdala, the midbrain, and the hypothalamus (Lazer et al., 2000). These elevated parasympathetic physical responses yet increased arousal suggests a form of tonic alertness is at play during meditation, in line with the relaxation response proposed by Lazar et al. (2000).

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In a later 2014 study conducted by Britton et al., it was found that passive meditation triggers activity in the dorsal anterior cingulate cortex (dACC), the thalamus, the dorsolateral prefrontal cortex (dlPFC), the inferior parietal lobe, the anterior insula, and the brainstem. These areas have been previously associated with tonic alertness (Britton et al., 2014). As a result of increased neural activity in regions of tonic alertness, neuronal synapses must have adapted, making these neural circuits more sensitive to stimuli than before, perhaps through long term potentiation. This adaptation would reveal how experienced meditators’ minds may change to allow one to enhance their ability to volitionally induce the relaxation response. This would also allow meditators to have more control over their own autonomic nervous system when compared to the neurotypical person, as their neural circuitry is more accustomed to frequent activity in these autonomic associated regions. It is important to note that this parasympathetic is specific to passive forms of meditation that cultivate the relaxation response. Those more active meditative techniques trigger sympathetic dominance rather than parasympathetic dominance (Amihai and Kozhevnikov, 2015).

"Today, consciousness is still a subjective experience; therefore, modern science has struggled to define it or find the neural circuitry in which it is realized."

This has been observed in Buddhist and Hindu tantric traditions, which involve phasic alertness rather than tonic alertness. Vajrayana meditation in particular is associated with a general increase in arousal (Amihai and Kozhevnikov, 2015). Those who practice Vajrayana meditation also were observed to have improved visual task performance when compared to a control group, suggesting that their attentional focus or phasic alertness had been enhanced, supporting this theory of increased sympathetic dominance (Amihai and Kozhevnikov, 2014). Heightened sympathetic activity has been observed in other studies as well, noted in physical responses such as increased metabolic activity and oxygen consumption (Benson et al., 1990). Although beyond the scope of this paper, these studies suggest that varied techniques of meditation that do not generate the relaxation response can trigger sympathetic dominance. This response allows the user to further master their autonomic control. A brief divergence on consciousness Today, consciousness is still a subjective experience; therefore, modern science has struggled to define it or find the neural circuitry in which it is realized. When considering its purpose, author Kristoff Koch (2004) emphasizes the importance of future and selfconceptualization. 10

Consciousness elevates us from our ancestors by allowing us to create impressive simulations of ourselves in our reality and hypothetical future realities. We can attempt an act many times in our head and then choose the most beneficial action as a form of future planning. As Karl Popper, the Australian-British philosopher, once said, while the “uncritical animal” may be held up in “its dogmatically held hypotheses”, we humans possess the ability to “formulate our own hypotheses”, letting our misconstrued ideas “die in our stead” (1977). In this way, we differ from the “uncritical animal” as we possess the ability to create our own simulations of the future and let them “die in our stead” if they fail within our own minds (Popper, 1977). This ability reveals the true benefit to consciousness and how it elevates us from the beings from which we came. Image 5: The common physiological responses of both the parasympathetic and sympathetic nervous systems, as depicted in most introductory neuroscience textbooks. Image Source: Wikimedia Commons

Regarding consciousness: how meditation transforms our consciousness when considering the autonomic nervous system First, note that consciousness is not realized in the neural circuitry of the autonomic nervous system (Koch, 2004). However, a being’s parasympathetic and sympathetic nervous systems can greatly influence their state of consciousness, as these systems’ underlying processes bring about physiological states integral to survival and daily life. Although these autonomic responses are typically non-volitional,

practicing passive mindfulness meditation allows the user to consciously exercise their parasympathetic nervous system. These exercises volitionally induce the relaxation response. With consistent practice, triggering activity in these neural circuits can turn into a routine exercise, allowing the meditator to control their own parasympathetic response. In this way, if one were to suffer from an undesirable sympathetic response, the user could employ familiar neural circuits to trigger a relaxation response instead. This control over one’s autonomic system reveals the plasticity of the brain, and how through sustained practice one can bring subconscious processes under volitional control. Again, it is important to note that this autonomic control can also arise from a cultivation of sympathetic dominance as well. These forms of meditation can allow an experienced meditator to enhance the neural circuitry involved in sympathetic response and later volitionally call on those responses. Regarding consciousness: how meditation transforms our consciousness when considering the default mode network Consciousness is not solely realized in the neural circuitry of the default mode network (Koch, 2004). However, the DMN is responsible for our internal virtual reality, allowing us to DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

simulate hypothetical future realities. This ability is critical to the purpose of consciousness. The DMN is also responsible for many other mental faculties that make us human, such as creativity and imagination (Mason et al., 2007). In short, the DMN plays an important role in influencing consciousness, perhaps supporting the neuronal correlates of consciousness in which conscious percepts are realized. So then, why is the default mode network down regulated in experienced meditators? When considering the purpose of meditation, it was noted that the practice brought one closer to enlightenment, or a better way of life. Experienced meditators can accept the false nature of their perceived reality and live without suffering. It appears this nirvana manifests itself on a neurological basis through the down regulation of the default mode network (Brewer et al., 2011). The default mode network is integral to our consciousness yet is downregulated in individuals with a higher quality of life. From this discrepancy, the only logical conclusion that can be drawn is that there are certain disadvantages to the DMN. Many studies have revealed that serial mind-wandering is associated with lower levels of happiness (Bostock et al., 2019). A constant obsession with past or future events can pull one out of the present moment, creating a general feeling of dissatisfaction. Although capable of producing wonderful images and clever planning, the default mode network’s power is far too great. If one is not accustomed to it, they may fall victim to the DMN, in a sense tortured by their own mind. This torture manifests itself through the canonical Buddhist definition of suffering and can manifest itself as modern day affective disorders or negative patterns of thought. The DMN allows us to escape from reality, living in false realities in our heads. This disengagement from reality is especially prevalent in contemporary society, as the invention of modern-day technology has created a new influx of digital information. Constantly bombarded with sensory stimuli, modern minds are seldom asked to focus on one particular object at a time.

unable to grow fully accustomed to the power of our minds, or the DMN in particular. Our own intelligence turned against us, manifesting itself in the mental sufferings we see today. Although these may not be cured by the practice of mindfulness, these meditative practices hold much potential for clinical treatment in the future. Meditation can alter the functional connectivity of one’s brain, overwriting past potentially negative habits (of serial mind-wandering, for example). This discipline transforms the way in which we perceive reality. If widely implemented, meditative practice taken seriously could jump start a revolution of consciousness. This revolution would be characterized by a new prioritization of thought, perhaps centered around a religion of practice rather than belief. If we as a population placed emphasis on being aware of the present moment, we could perhaps see the dissolution of modern-day stressors and their resulting disorders. Our own consciousness creates problems yet does not possess the power to realize its own error. Through meditation, we can realize the insignificance of our own thoughts, relieving us of our self-implemented torture.

The ancient practice of meditation appears to be worlds apart from our own. This form of intense mental contemplation is rarely seen today, a longforgotten way of thought. However, considering the practice once again could turn the entire world on its head. One theory from prominent yogi Sadhguru is that our brains simply evolved quicker than we could manage. In a recent talk, the yogi considered that perhaps we simply lack a stable platform for our intelligence (Sadhguru, 2020). As we evolved too quickly, humans were WINTER/SPRING 2022

References: Amihai, I. & Kozhevnikov, M. (2015). The Influence of Buddhist Meditation Traditions on the Autonomic System and Attention. BioMed Research International, 2015, 1-13.

Koch, C. (2004). The Quest for Consciousness: A Neurobiological Approach. Roberts & Co. Publishers.

Benson, H., Rosner, B. A., Marzetta, B. R., & Klemchuk, H. P. (1974). Decreased blood pressure in borderline hypertensive subjects who practiced meditation. J Chron Dis, 27, 163-169.

Lazar, S. W., Bush, G., Gollub, R. L., Fricchione, G. L., Khalsa, G., & Benson, H. (2000) Functional brain mapping of the relaxation response and meditation. NeuroReport, 11(7) 1581-1585.

Benson, H., Malhotra, M. S., Goldman, R. F., Jacobs, G. D., & Hopkins, P. J. (1990) Three case reports of the metabolic and electroencephalographic changes during advanced buddhist meditation techniques. Behavioral Medicine, 16( 2), 90-95. doi: 10.1080/08964289.1990.9934596.

Low, P. (2013). Autonomic nervous system. Edited by Porter, R. S. & Kaplan J. L.. The Merck Manual, Whitehouse Station.

Bostock, S. Crosswell, A. D., Prather, A. A., & Steptoe, A. (2019). Mindfulness On-The-Go: Effects of a mindfulness meditation app on work stress and well-being. Journal of Occupational Health Psychology, 24(1), 127-138. doi: 10.1037/ ocp0000118.

Marikar Bawa, F. L., Sutton, J. W., Mercer, S. W., & Bond, C. M. (2021) “I’m empowered to look after myself ”— Mindfulness as a way to manage chronic pain: An interpretative phenomenological analysis of participant experiences in Scotland. Social Science and Medicine, 201(114073). doi: 10.1016/j.socscimed.2021.114073.

Brewer, J.A., Worhunsky, P. D., Gray, J. R., Tang, Y., & Kober, H. (2011). Meditation experience is associated with differences in default mode network activity and connectivity. PNAS, 108(50), 20254-20259. https://doi.org/10.1073/ pnas.1112029108. Britton, W. B., Lindahl, J. R., Rael Cahn, B., David, J. H., & Goldman, R. E. (2014). Awakening is not a metaphor: the effects of Buddhist meditation practices on basic wakefulness. Annals of the New York Academy of Sciences, 1307(1), 64-81. doi: 10.1111/nyas.12279. Carr, Michael. (1993). “Mind-Monkey” Metaphors in Chinese and Japanese Dictionaries. International Journal of Lexicography, 6(3), 149180. Clarke, T. C., Barnes, P. M., Black, L. I., Stussman, B. J., & Nahin, R. L. (2018). Use of yoga, mediation, and chiropractors among U.S. adults aged 18 and over. NCHS Data Brief, 325. Ganster, D. C. & Rosen, C. C. (2013). Work stress and employee health. Journal of Management, 39, 1085-1122. Hasenkamp, W., Wilson-Mendenhall, C. D., Duncan, E., & Barsalou, L. W. (2012). Mind wandering attention during focused meditation: fine-grained temporal analysis of fluctuating

cognitive states. NeuroImage, 59, 750-760. doi: 10.1016/j.neuroimage.2011.07.008.

Manocha, R. (2000). Why meditation? Australian Family Physician, 29(12).

Mason, M. F., Norton, M. I., Van Horn, J. D., Wegner, D. M., Grafton, S. T., & Neil Macrae, C. (2007). Wandering Minds: the Default Mode Network and Stimulus-Independent Thought. SCIENCE, 315, 393-395. (2011). Meditation. Encyclopedia of Global Religions, 2, 768-771. Mirams, L., Poliakoff, E., Brown, R. J., & Lloyd, D. M. (2013). Brief body-scan meditation practice improves somatosensory perceptual decision making. Consciousness and Cognition, 22, 348-359. https://doi.org/10.1016/j. concog.2012.07.009 Patanjali., Patanjali., translated by James Robert Ballantyne. (1952). Yoga Sutras of Patanjali, [2nd ed.]. Calcutta: Susil Gupta. Popper, K. (1977). Natural Selection and the Emergence of Mind. Darwin Lecture, Darwin College, Cambridge. Raz, A. (2004). Anatomy of Attentional Networks. The Anatomical Record (Part B, New Anat.), 281, 21-36. Sadhguru. [Motivation Madness] (2020, Mar. 9). What 7000 HOURS of MEDITATION Looks Like | Sadhguru [Video]. YouTube. https://youtu. be/NujzbIulVik. DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Face Blindness: Case Studies on Developmental Prosopagnosia BY ELIZABETH (SHUXUAN) LI '25 Cover Image:: Prosopagnosia, otherwise known as face blindness, is characterized by the inability to distinguish faces. If looking at the image, a prosopagnosic would realize that there are faces on the walls but would have extreme difficulty in telling them apart Image Source: Uppertal, 2014

History and overview For humans, the most prominent form of sensory detection has been vision. When interacting with others, humans rely heavily on the visual pathway to obtain information about the content and emotions of the speaker. Under circumstances where communication lacks a visual component, such as phone calls or texting, the brain can easily miss clues about the moods and feelings of those on the other side. Hence, the detection of facial features in others is essential to everyday interaction. In the past century, psychologists’ attention has been drawn to a small but steady stream of cases where an individual’s facial recognition has been impaired since birth in a condition named “developmental prosopagnosia.” One of the first scientists to study prosopagnosia was German neurologist Joachim Bodamer, who coined the name of the condition as “ProsopAgnosie” in German (Bodamer, 1947). In general terms, developmental prosopagnosia (DP) is “the selective degradation of face perception and face memory” since birth in the absence of previous brain trauma (Duchaine & Nakayama, 2006). Distinct from acquired prosopagnosia,

where a major head injury deprives patients of their ability to distinguish faces, developmental prosopagnosics have never been able to recognize faces as successfully as the average individual. In addition to lowered sensitivity to differences in facial features, some developmental prosopagnosics observe one half of someone's face as morphing (hemi-prosopometamorphopsia) or even displace one person’s face as someone else’s (Almeida et al., 2020; Jonas et al, 2018). Systematically, the criteria for a DP diagnosis require (1) impediments in facial recognition abilities to the extent of impacting one’s daily life in significantly negative ways and (2) lab testing using methods such as the CFMT (Psychology Experiments: Cambridge Face Memory Test, n.d.). This paper first contextualizes developmental prosopagnosia in real life by discussing its consequences on daily functioning; then, it will explore two aspects of face processing that are relevant in understanding the disorder, followed by three notable case studies on DP that each represents different cognitive and neural aspects of the condition.

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being prosopagnosic, his configural processing is still intact (Duchaine, 2000). Various electrophysiological and behavioral evidence also demonstrates the importance of holistic processing. EEG data has shown that a sample of DP subjects perceived a face as merely the sum of its parts while normal recognizers exhibited activity that superseded a strictly additive approach (Towler et al., 2018). In addition, DeGutis and colleagues have found that holistic face training helps DPs in recognizing the front view of faces (2014). However, this is not an absolute principle, as psychologists like Susilo et al. (2010) have studied DPs with normal holistic processing. Thus, holistic processing and configural processing both play a part in facial recognition, but the holistic mechanism is more favored.

Prosopagnosia’s Impacts on Quality of life Notable figures such as English primatologist Jane Goodall (fig. 1) and American actor Brad Pitt have admitted to having prosopagnosia (Sacks, 2010; Staff, 2013). The most common form of prosopagnosia is DP, which occurs in about 2% of the general population (Duchaine & Nakayama, 2006). It has significant impacts on quality of life since the visual info available for prosopagnosics to recognize others is greatly reduced. Given that the inability to recognize faces persists for close family members and even oneself, DP patients may find themselves dumbfounded in a variety of social situations. To identify friends, family, and coworkers, they often report using hair, accessories, and elements of clothing, but these items change day-to-day and are thus unreliable (Dingfelder, 2019). Children with DP suffer at school, leading to reduced social interactions and quality of learning from a young age, which can impede their emotional development and life achievement. In fact, many DPs do not realize that they have the condition at all or doubt if their facial recognition abilities are unreliable enough for a medical diagnosis (Wilson et al., 2010). This can be quite frustrating and further detracts from their everyday experience. Two General mechanisms of face processing First, faces are processed more holistically (as one) than configurally (in parts), although both are important to processing a face as a whole. One case study on patient Bill Choisser mentioned below demonstrates the dependence of face recognition on holistic processing because despite WINTER/SPRING 2022

Second, face processing is “special” in visual recognition in that it occupies certain pathways distinct from the rest of the visual system. In other words, the brain delegates specialized mechanisms to faces but not to other objects. A notable study by Farah et al. (1998) found that individuals performed much worse when recognizing parts of faces than the whole, unscrambled faces. Their performance in identifying parts of non-face stimuli, such as the door to a house, was comparable to recognizing the entire house. The specialization of facial recognition mechanisms is also logical given that they rely more on holistic faces, which require neurons operating at a level larger than simple part recognition. Furthermore, the receptive fields of high-level face cells are much bigger, indicating that the brain tends to perceive a face in its entirety at once (Rolls et al., 2003). In fact, there is a double dissociation between face recognition and object recognition, meaning that these two processes operate from different mechanisms that overlap to a minimal extent, if at all. For example, Bill Choisser had prosopagnosia without object agnosia, an extreme difficulty in recognizing objects. Conversely, there have also been individuals with impaired object recognition and intact face processing, such as patient C.K. (Moscovitch et al., 1997) and Mr. W (Rumiati et al., 1994). Since both disorders can exist without the other, the processes when recognizing a face versus an object are likely distinct.

Image 1: Jane Goodall, who is known for her extensive study on chimpanzees, reported that she has had difficulty recognizing and distinguishing faces since childhood (Sacks, 2010). She identifies her close friends by features such as hair and glasses. Image Source: Step, 2010

"In other words, the brain delegates specialized mechanisms to faces but not to other objects."

Case studies The causes and presentations of DP have led to several complicated models, partly because the literature on DP is mostly based on case studies rather than general population research. It is 15

important to note that, like many other mental disorders, those diagnosed with DP are simply on the extreme end of a range of face-recognizing abilities; the other end of the spectrum is known as “super-recognizers.” Psychologist Tardif and her colleagues at the University of Montreal found that the performance of DPs and superrecognizers can be extrapolated from the data of normal individuals (2019). In other words, DPs are quantitatively rather than qualitatively different from the typical population (Tardif et al., 2019). This is informative in researching and diagnosing DP since it affects how psychologists and neuroscientists categorize and analyze relevant case studies. It also informs their investigation of face processing abilities in the normal population. DP is a heterogeneous disorder, meaning that there is a myriad of neural etiologies and behavioral symptoms depending on the individual. To provide a better illustration of how this condition plays out, below are three documented case studies on DP. Case Study One: Patient B.C. Bill Choisser (B.C.) was an ambidextrous man who had been around fifty years old when he was tested for DP. He had never been able to recognize faces, and he reported using hair and jeans to identify people. As an MIT graduate, a lawyer, and an engineer, B.C. had an IQ of 131, possessed above-average abilities on low-level tasks such as copying and orientation matching, and had

Image 2: An inferior view of the brain shows the fusiform face area (FFA) in red. Located within the fusiform gyrus, the FFA responds most preferentially to face stimuli, and prosopagnosics often (but not always) suffer from an impairment or a lesion in this area Image Source: Science, 2015

no troubles with spatial navigation. He suffered from minor neurological problems unrelated to DP, and had no visual difficulties other than DP. In numerous face identification tests, he scored below average for most of the tasks. For the one task in which he scored within the normal range, he spent an abnormally long time (>1 min.) assessing the faces and used unusual techniques to tell them apart. B.C.’s test results present multiple points of interest: first, he did not lack the ability to recognize people’s identities per se, as he scored normally or above average when not using faces as identifiers. Second, B.C. could recognize identical photos of faces but not across novel views. Third, his configural processing was intact while the problem lay somewhere along the facespecific processing system (Duchaine, 2000). Together, these three factors exemplify one of many possible thresholds in the chain of facial processing that may go wrong in DP, as it is a heterogeneous disorder. Case Study Two: Patient C.M. Another case study concerns C.M., a patient with congenital prosopagnosia who was studied by neurologists Schultz and Bertolucci at the University of Santo Amaro and the Federal University of São Paulo respectively (2011). Congenital prosopagnosia will be subsequently abbreviated as CP, and it is a type of DP. Specifically, while DP does not specify any cause for the dysfunction of face processing from birth, CP is “a deficit in face processing apparent from early childhood in the absence of any underlying neurological basis" (Schultz & Bertolucci, 2011). C.M., who was 46 years old at the time of the study, was bilingual in Portuguese and Greek and worked as an executive. Since childhood, she has relied on voice and other non-face physical characteristics to recognize friends and strangers. Her verbal abilities were significantly above average, while her other non-verbal abilities such as detecting facial emotions were below average. C.M. had a normal memory with no mental pathologies according to SPECT and MRI scans. The case report described her as being able to identify if she was looking at a face versus some other stimuli, but she was not able to ascribe the face to any particular person (Schultz & Bertolucci, 2011). This evidence demonstrates that C.M.’s face perception system was intact, but her facial recognition systems were disrupted. C.M’s case of congenital prosopagnosia exemplifies that DP patients do not always have degradation in “perception” as suggested earlier by Duchaine and Nakayama; instead,

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the malfunction can occur further down the line of face processing in the recognition stage (Duchaine & Nakayama, 2006). Although Schultz and Bertolucci did not report C.M.'s underlying neural activity, they describe that CP individuals in general have significantly smaller anterior fusiform gyrus (Schultz & Bertolucci, 2011), which is located close to the fusiform face area (fig. 2). The anatomical anomalies of congenital prosopagnosics suggest that the fusiform gyrus plays an active role in both the perception and recognition of faces.

For most DPs, the most troublesome aspect of the condition is difficulties in social interactions. In lieu of facial recognition, DPs often use hair, articles of clothing, or accessories to recognize close ones. The neurological underpinnings of DP are usually specific to regions and pathways involving face processing, which rely more on a holistic mechanism than configural and use highly specialized pathways of the brain. This specialization of mechanism demonstrates how humans have evolved to pay special attention to face identity and face information.

Case Study Three: A Family of Prosopagnosics

Since DP presents differently across individuals, case studies are quite useful in parsing out specific causes one factor at a time. For patient B.C., his deficit took place more upstream in the face processing path, although there can be various points where face perception and recognition fail. In a separate case study, patient C.M. demonstrated the importance of the fusiform gyrus and the fusiform face area in face processing. Lastly, the genetic history of a family with prosopagnosia showed an autosomal dominant inheritance pattern in the disorder. This case reveals that DP does not occur in isolation and can often be passed down.

The third case is a family study on ten direct and indirect relatives with prosopagnosia and/ or object agnosia (Duchaine et al., 2007). The sample consisted of seven females and three males (plus two additional males believed to have DP but were not tested). Ages ranged from twentythree to sixty-six, and the family members held a variety of occupations, including a geologist, a truck driver, and a physician. No one in the sample had any history of head trauma, and most of them scored within or above the normal range on cognitive tests measuring vocabulary size, auditory memory, nonverbal intelligence, and many other abilities. In contrast, during the facial recognition test, the family members scored statistically significantly below control groups. Whether looking at friends, family, or celebrities, the members in the sample identified very few faces correctly. In addition, the validated CPFT (Cambridge Face Perception Test) measured the family as lacking in facial perception capacities. However, their abilities to recognize emotions from close-up pictures of the eye region are intact. Most but not all family members had normal object recognition (Duchaine et al., 2007). These presentations suggest that different mechanisms underlie face identity processing and emotion processing, and that prosopagnosia and object agnosia at least partially operate on distinct systems. This case study is also significant because it was one of the first investigations on the inheritance of prosopagnosia, showing that DP has a solid basis in genetics (Duchaine et al., 2007). One investigation on non-syndromic hereditary prosopagnosia suggested that the disorder follows autosomal dominant inheritance (Kennerknecht et al., 2006). Thus, although prosopagnosia does not implicate reduced cognitive ability, its genetic inheritance may reduce the quality of life for relatives. Conclusion DP is a heterogeneous disorder with a variety of symptoms at the neural and behavioral levels. WINTER/SPRING 2022

Implications Although limited in scope, case studies are important for identifying potential DPs and predicting the onset of the disorder. However, much of the condition is still being studied, including ways to prevent or improve face blindness. It is possible to better face recognition with training, but improvements are usually modest and cannot be generalized to all prosopagnosics (DeGutis et al., 2014). Psychologists are also searching for non-training treatments such as deep brain stimulation or drug-assisted therapy. Many psychologists and patients with prosopagnosia have helped expand the knowledge of the disorder, and various tests exist for measuring one's acuity with faces. Bill Choisser, one of the aforementioned patients, constructed an extensive archive detailing his experiences with prosopagnosia (Face Blind! Bill’s Face Blindness (Prosopagnosia) Pages - Introduction, n.d.). Furthermore, behavior measurements are readily accessible online on websites such as the Cambridge Face Memory test (Psychology Experiments: Cambridge Face Memory Test, n.d.). Those who believe they have some form of prosopagnosia can contact researchers at faceblind.org (Prosopagnosia Research Center - Faceblind, n.d.). The field of DP welcomes new research from both the patient and research sides.

"Since DP presents differently across individuals, case studies are quite useful in parsing out specific causes one factor at a time."

References Almeida, J., Freixo, A., Tábuas-Pereira, M., Herald, S. B., Valério, D., Schu, G., Duro, D., Cunha, G., Bukhari, Q., Duchaine, B., & Santana, I. (2020). Face-Specific Perceptual Distortions Reveal A View- and Orientation-Independent Face Template. Current Biology, 30(20), 4071-4077.e4. https://doi.org/10.1016/j.cub.2020.07.067 Bodamer, J. (1947). Die Prosop-Agnosie: Die Agnosie des Physiognomieerkennens. Archiv für Psychiatrie und Nervenkrankheiten Vereinigt mit Zeitschrift für die Gesamte Neurologie und Psychiatrie, 179(1–2), 6–53. https://doi. org/10.1007/BF00352849 DeGutis, J., Cohan, S., & Nakayama, K. (2014). Holistic face training enhances face processing in developmental prosopagnosia. Brain, 137(6), 1781–1798. https://doi.org/10.1093/brain/ awu062 Dingfelder, S. (2019, August 21). My life with face blindness: I spent decades unable to recognize people. Then I learned why. Washington Post. https://w w w.washingtonp ost.com/ne ws/ magazine/wp/2019/08/21/feature/my-life-withface-blindness/ Duchaine, B. (2000). Developmental prosopagnosia with normal configural processing. NeuroReport, 11(1). https://lab. faceblind.org/papers/duchaine00neuroreport. pdf Duchaine, B. C., & Nakayama, K. (2006). Developmental prosopagnosia: a window to content-specific face processing. Current Opinion in Neurobiology, 16(2), 166–173. https://doi.org/10.1016/j.conb.2006.03.003

Moscovitch, M., Winocur, G., & Behrmann, M. (1997). What Is Special about Face Recognition? Nineteen Experiments on a Person with Visual Object Agnosia and Dyslexia but Normal Face Recognition. Journal of Cognitive Neuroscience, 9(5), 555–604. https://doi.org/10.1162/ jocn.1997.9.5.555 Psychology Experiments: Cambridge Face Memory Test. (n.d.). Birkbeck, University of London. Retrieved February 7, 2022, from https://www.bbk.ac.uk/psychology/ psycholog yexperiments/experiments/ facememorytest/startup.php?r=8&p=0&d=1& dn=0&g=0&m=68f7d848edeaebd6cc29371b80 6b3017 Rolls, E. T., Aggelopoulos, N. C., & Zheng, F. (2003). The Receptive Fields of Inferior Temporal Cortex Neurons in Natural Scenes. The Journal of Neuroscience, 23(1), 339–348. https://doi. org/10.1523/JNEUROSCI.23-01-00339.2003 Rumiati, R. I., Humphreys, G. W., Riddoch, M. J., & Bateman, A. (1994). Visual object agnosia without prosopagnosia or alexia: Evidence for hierarchical theories of visual recognition. Visual Cognition, 1(2–3), 181–225. https://doi. org/10.1080/13506289408402300 Sacks, O. (2010, August 23). Face-Blind. The New Yorker. http://www.newyorker.com/ magazine/2010/08/30/face-blind

Duchaine, B., Germine, L., & Nakayama, K. (2007). Family resemblance: Ten family members with prosopagnosia and within-class object agnosia. Cognitive Neuropsychology, 24(4), 419– 430. https://doi.org/10.1080/02643290701380491

Schultz, R. R., & Bertolucci, P. H. F. (2011). Congenital prosopagnosia: A case report. Dementia & Neuropsychologia, 5(1), 54–57. https://doi.org/10.1590/S198057642011DN05010010

Farah, M. J., Wilson, K. D., Drain, M., & Tanaka, J. N. (1998). What is “special” about face perception? Psychological Review, 105(3), 482–498. https:// doi.org/10.1037/0033-295X.105.3.482

Staff, C. N. N. (2013, May 23). Does Brad Pitt suffer from face blindness? CNN. https://www. cnn.com/2013/05/23/showbiz/celebrity-newsgossip/brad-pitt-esquire-face-blindness/index. html

Jonas, J., Brissart, H., Hossu, G., Colnat-Coulbois, S., Vignal, J.-P., Rossion, B., & Maillard, L. (2018). A face identity hallucination (palinopsia) generated by intracerebral stimulation of the face-selective right lateral fusiform cortex. Cortex, 99, 296–310. https://doi.org/10.1016/j. cortex.2017.11.022 Kennerknecht, I., Grueter, T., Welling, B., 18

Wentzek, S., Horst, J., Edwards, S., & Grueter, M. (2006). First report of prevalence of nonsyndromic hereditary prosopagnosia (HPA). American Journal of Medical Genetics Part A, 140A(15), 1617–1622. https://doi.org/10.1002/ ajmg.a.31343

Susilo, T., McKone, E., Dennett, H., Darke, H., Palermo, R., Hall, A., Pidcock, M., Dawel, A., Jeffery, L., Wilson, C. E., & Rhodes, G. (2010). Face recognition impairments despite normal holistic processing and face space coding: Evidence from a case of developmental prosopagnosia. Cognitive Neuropsychology, 27(8), 636–664. https://doi.org /10.1080/02643294.2011.613372 DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Tardif, J., Morin Duchesne, X., Cohan, S., Royer, J., Blais, C., Fiset, D., Duchaine, B., & Gosselin, F. (2019). Use of Face Information Varies Systematically From Developmental Prosopagnosics to Super-Recognizers. Psychological Science, 30(2), 300–308. https:// doi.org/10.1177/0956797618811338 Towler, J., Fisher, K., & Eimer, M. (2018). Holistic face perception is impaired in developmental prosopagnosia. Cortex, 108, 112–126. https://doi. org/10.1016/j.cortex.2018.07.019 Wilson, C. E., Palermo, R., Schmalzl, L., & Brock, J. (2010). Specificity of impaired facial identity recognition in children with suspected developmental prosopagnosia. Cognitive Neuropsychology, 27(1), 30–45. https://doi.org/1 0.1080/02643294.2010.490207

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Breast Reconstruction and the Risks of a Mastectomy BY HYUNJIN RHEEM '25 & JEAN YUAN '25 Cover Image: This specific breast implant is a saline implant. They last about 10-20 years and are usually removed due to complications or cosmetic concerns. This type of breast implant is usually safer in the case of a rupture since the saline solution can be safely absorbed by the body. (Mayo Foundation for Medical Education and Research) Image Source: Flickr - Breast Reconstruction Market by Durgesh Kumar

Process of getting a mastectomy to the process of breast reconstruction Breast cancer is the most fatal cancer for women in the United States. It is usually caused by hereditary mutations in genes such as BRCA 1 or BRCA 2 and other external factors. Breast cancer that is not inherited through genetics has not been able to be identified (American Cancer Society of Breast Cancer). External factors such as radiation and the breathing in of certain chemicals through air pollution, such as lead, mercury, and cadmium, can also lead to abnormally rapid cell growth in the breast. There are two types of breast cancers: carcinomas and sarcomas, divided based on the cell of the breast in which the cancer originated. Carcinomas occur when the epithelial components, such as the cells that line the lobules and milk ducts (Feng, 2018) of the breast are affected. This occurs when the DNA of a cell is damaged, the cell then grows into a malignant tumor (National Cancer Institute). Sarcomas occur when the stromal components, such as myofibroblasts and blood vessel cells, are affected (Feng, 2018). The most common type of breast cancer is Invasive Ductal Carcinoma (IDC), comprising about 80% of all breast cancer cases. A type of adenocarcinoma,

IDC starts in the cells in the lining of epithelial organs, such as the lining of milk ducts. These cells secrete digestive juices that grow out of control, allowing malignant tumors to form, which are the adenocarcinomas (Cleveland Clinic). The cells then invade breast tissue and can spread further to other organs or areas through lymph nodes or the bloodstream, resulting in metastatic breast cancer. Although the 5-year relative survival rate is high for localized and regional stage cancers, 99% and 86% respectively (American Cancer Society of Breast Cancer), part of breast cancer treatment involves surgery, specifically breast conserving surgery (BCS) and mastectomy. Breast conserving surgery removes only the part of the breast containing the cancerous tissue, allowing a patient to keep most of her breast. However, there is a high chance that patients will need radiation therapy after surgery in order to reduce the risk of a secondary cancer or of the original cancer coming back. When women cannot receive breast-conserving surgery, a mastectomy is needed in order to remove the cancer, and sometimes a double mastectomy, which is the removal of both breasts, DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

in order to lower the risk of getting cancer in the second breast. A mastectomy removes the entire breast regardless of tumor size, but patients are less likely to need radiation after surgery. Both surgeries allow for the option of breast reconstruction. There are different types of mastectomies depending on the condition of the cancer and how much tissue is needed to be removed: simple mastectomy and modified radical mastectomy. A simple mastectomy involves a surgeon removing the entire breast, including the nipple, areola, fascia, and skin. Even some of the underarm lymph nodes could possibly be removed, called a sentinel lymph node biopsy, depending on the type of procedure and the severity of the cancer. In a modified radical mastectomy, the surgeon removes the lymph nodes under the arm, which is called an axillary lymph node dissection. Sentinel lymph node biopsies are usually for “patients without axillary lymph node involvement, thereby making more extensive surgery unnecessary” (Petrelli, F. et al., 2012). Presently, sentinel lymph node biopsies are the accepted approach for women in the early stages of breast cancer, and the axillary lymph node dissection is not necessary for clinically “node-negative patients,” or patients without the axillary lymph node involvement. Other types of mastectomies include radical, skin-sparing, nipple sparing, and as previously mentioned, a double mastectomy. Radical mastectomies are very rare in present times since it requires the surgeon to remove the entire breast, axillary lymph nodes, and the pectoral muscles under the breast and has many side effects. These side effects include swelling at the surgery site, numbness in upper chest, a hematoma (buildup of blood in the wound), WINTER/SPRING 2022

seroma (buildup of clear fluid in the wound), and limited arm movement (American Cancer Society). It is only done if there is cancer in the pectoral muscles. Skin-sparing mastectomies involve removing the breast tissue, nipple, and areola and leaving the skin over the breast. Nipple-sparing mastectomies follow a similar procedure to other types of mastectomies, but the nipple and areola are kept. The removal of the nipple and areola in this procedure also depends on if there is cancer found in the tissue under the nipple and areola. This procedure is usually done on women who are in the beginning stages of cancer (American Cancer Society of Breast Cancer). Lastly, a double mastectomy is when both breasts are removed in order to reduce the amount of risk of a secondary cancer; those with the BRCA gene mutation are more likely to receive a double mastectomy in order to reduce the risk of relapse. Women have options to choose from based on aesthetics for breast reconstruction Depending on the aesthetic that the patient desires, they primarily have two options for reconstructive breast surgery: implant reconstruction and tissue reconstruction, the latter also referred to as flap reconstruction. This article will focus on implant reconstructions. Implant reconstruction options include saline and silicone breast implants, both made of a silicone outer layer and a saline or silicone gel on the inside. The surgical procedure for implant reconstruction is much quicker than that for tissue reconstruction and leads to fewer postoperative complications. There are multiple types of implants, the major types being round or shaped. Round implants come in textured and smooth options, whereas shaped implants are always textured. Although smooth implants are preferred by patients, studies on these two implant types have presented conflicting information, some studies showing the potential for capsular contracture with smooth implants. Capsular contracture, one of the major risks of breast implants, is an immune system response to the presence of a foreign object, in this case, the implant. The immune system separates the implant from the rest of the body by creating a layer of scar tissue around the implant. Capsular capture leads to a hardening of the area of the tissue surrounding the implant, leading to possible pain in the breast area and aesthetic irregularity. Studies published in 1993 and 1996 demonstrated that patients with textured breast implants had fewer occurrences of capsular contractures compared to those with smooth implants (Asplund, 1996). However, a study in 1997 showed no significant difference in rate

Image 1: This is a tumor shown on a diagnostic mammogram. In this case, a sentinel lymph node biopsy was needed Image Source: Flickr-Diagnostic Mammogram by Elissa Malcohn

"Depending on the aesthetic that the patient desires, they primarily have two options for reconstructive breast surgery: implant reconstruction and tissue reconstruction...."

"Freeway development has historically displaced minorities and underrepresented groups, tearing through parts of cities that once housed marginalized communities."

Image 2: This is a T cell/ histiocyte rich diffuse large B cell lymphoma. Breast implantassociated anaplastic large cell lymphoma, a rare form of T-cell lymphoma, can develop following breast implantation. Source: Flickr-Pathology Outlines contributed by Drs. Asmaa Gaber Abdou and Nancy Youssef Assad

of capsular contracture between patients who received textured or smooth implants (Tarpila, 1997). Even so, textured and shaped implants are still popular, as they adhere to the surrounding tissue better than smooth implants, are firmer to the touch, and hold the teardrop shape better. Risks with Breast Implants The primary risks associated with breast implants include rupture of the implant, capsular contracture, and certain kinds of implants can cause breast implant-associated anaplastic large cell lymphoma (BIA-ALCL). Breast implantassociated anaplastic large cell lymphoma is a form of T-cell lymphoma in the scar tissue around the implant. A T-cell lymphoma (or Cutaneous T-cell lymphoma) is a “rare type of cancer that begins in white blood cells called T cells,” and these T cells develop abnormalities causing them to attack the skin. Usually these cells aid the “germ-fighting immune system,” but a cutaneous T-cell lymphoma can cause rashes on the skin and, sometimes, skin tumors (Mayo Foundation for Medical Education and Research). Although very rare – the risk of developing BIA-ALCL estimated at 0.35 to 1 case per million people per year – BIA-ALCL occurs more frequently in people who have had textured implants than in those with smooth implants (Kricheldorff, 2018). The most common indicators of BIA-ALCL include fluid collection or an unusual mass near the implant, associated with 70% and 30% of recorded cases, respectively (Mitry, 2020). Although a clear cause behind BIA-ALCL is unknown, there are several theories. Some previous studies suggest that chronic inflammation surrounding the breast can cause BIA-ALCL. Tissue inflammation around the implant occurs when rougher surfaced implants stimulate higher macrophage activity, scar tissue

formation, and T-cell responses by rubbing against the tissue surrounding the implant (Doloff, 2021). It is theorized that the textured surface on the implant would be rubbed off, with the rubbed off surfaces (silicone) ending up trapped in the surrounding tissue. This would stimulate chronic inflammation that could eventually lead to lymphomas (Doloff, 2021). Chronic inflammation can lead to leukocytes such as neutrophils, monocytes, macrophages, and eosinophils contributing to development of cancer. Additionally, inflammatory mediators, which promote inflammatory response, such as cytokines, chemokines, and free radicals, lead to increased cell growth and a development of mutations within the cell. One T-cell associated cytokine that promotes the inflammatory response, IL-6, is identified as a tumor growth stimulating cytokine (Sansone, 2012), which would lead to growth of breast carcinomas (Lajevardi, 2021), contributing to BIA-ALCL. Another theory is that biofilm growth might play a role. Biofilm is comprised of structures of cells that stick to each other and adhere to the surface of objects – in this case, the surface of the breast implant. Textured implants have increased surface area and therefore greater ability for biofilm growth and bacterial buildup. Biofilm tends to buildup in the implant surface texture as well as the spaces where the tissue and implant meet. Previous studies have shown a positive correlation between implant surface area and bacterial growth as well as increased T-cell response to biofilm infection (Hu, 2015). A high amount of bacteria can lead to immunostimulation, more specifically, the stimulation of lymphocytes, leading to lymphoma growth (Loch-Wilkinson, 2017). Additionally, the greater bacterial growth eventually leads to transformation of cell genes and the development

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of CD30-positive ALK-negative T cells (Kao, 2021). These are cells lacking the expression of a protein, anaplastic lymphoma kinase, which plays a role in brain development. However, the mutated form of this gene can lead to the genesis of ALK-negative anaplastic large cell lymphomas. Conclusion: Breast reconstruction after a mastectomy is a common procedure for many breast cancer patients, with options that allow for comfort and aesthetic satisfaction. However, there are risks to certain options, such as textured implants, which can lead to the genesis of a new cancer, breast implant-associated large cell lymphomas (BIA-ALCL). Despite the presence of this risk, the FDA has found that the quantified risk rate of this lymphoma, depending on the specific manufacturing of a textured versus a non-textured implant, has gone from 1 in 3,000 patients down to 1 to 30,000 patients. The development of biocompatible prosthetics works to decrease the risk of breast implant associated problems while still creating an implant that addresses both the structural and aesthetic needs of the patient. References: Adenocarcinoma cancers: Symptoms, causes, diagnosis & treatment. Cleveland Clinic. (n.d.). Retrieved February 25, 2022, from https:// my.clevelandclinic.org/health/diseases/21652adenocarcinoma-cancers Anne Trafton | MIT News Office. (n.d.). How the surfaces of silicone breast implants affect the immune system. MIT News | Massachusetts Institute of

Technology. Retrieved February 25, 2022, from https://news.mit.edu/2021/silicone-breastimplants-surfaces-health-0621 Asplund, O., Gylbert, L., Jurell, G., & Ward, C. (1996). Textured or smooth implants for submuscular breast augmentation: a controlled study. Plastic and reconstructive surgery, 97(6), 1200–1206. https://doi.org/10.1097/00006534-19960500000015 Clemens, M. W., & Jacobsen , E. (2020, October 26). Breast implant-associated anaplastic large cell lymphoma. UpToDate. Retrieved February 25, 2022, from https://www.uptodate.com/contents/ breast-implant-associated-anaplastic-large-celllymphoma#H457380827 Doloff, J. C., Veiseh, O., de Mezerville, R., Sforza, M., Perry, T. A., Haupt, J., Jamiel, M., Chambers, C., Nash, A., Aghlara-Fotovat, S., Stelzel, J. L., Bauer, S. J., Neshat, S. Y., Hancock, J., Romero, N. A., Hidalgo, Y. E., Leiva, I. M., Munhoz, A. M., Bayat, A., … & Langer, R. (2021). The surface topography of silicone breast implants mediates the foreign body response in mice, rabbits, and humans. Nature Biomedical Engineering, 5(10), 1115–1130. https://doi. org/10.1038/s41551-021-00739-4 Feng, Y., Spezia, M., Huang, S., Yuan, C., Zeng, Z., Zhang, L., Ji, X., Liu, W., Huang, B., Luo, W., Liu, B., Lei, Y., Du, S., Vuppalapati, A., Luu, H. H., Haydon, R. C., He, T. C., & Ren, G. (2018). Breast cancer development and progression: Risk factors,

Image 3: Pictured on the right: a smooth breast implant; Pictured on the left: a textured breast implant. Recently, there has been findings that textured breast implants have been connected to a rare cancer known as anaplastic large-cell lymphoma (Sauerwein, 2019). Image Source: Flickr-UHMed

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cancer stem cells, signaling pathways, genomics, and molecular pathogenesis. Genes & diseases, 5(2), 77–106. https://doi.org/10.1016/j. gendis.2018.05.001 Lajevardi, S., Rastogi, P., Isacson, D., & Deva, A. (2021). What are the likely causes of breast implant associated anaplastic large cell lymphoma (BIAALCL)? JPRAS Open, 32, 34-42. https://doi.org/10.1016/j.jpra.2021.11.006 Loch-Wilkinson, A., Beath, K., Knight, R., Wessels, W., Magnusson, M., Papadopoulos, T., Connell, T., Lofts, J., Locke, M., Hopper, I., Cooter, R., Vickery, K., Joshi, P., Prince, H., & Deva, A. (2017). Breast Implant–Associated Anaplastic Large Cell Lymphoma in Australia and New Zealand: HighSurface-Area Textured Implants Are Associated with Increased Risk. Plastic and Reconstructive Surgery, 140(4), 645-654. https://doi.org/10.1097/ PRS.0000000000003654 Kao, E. Y., Mukkamalla, S., & Lynch, D. T. (2021). ALK Negative Anaplastic Large Cell Lymphoma. In StatPearls. Kricheldorff, J., Fallenberg, E. M., Solbach, C., Gerber-Schäfer, C., Rancsó, C., & von Fritschen, U. (2018). Breast implant-associated lymphoma. Deutsches Ärzteblatt International. https://doi.org/10.3238/arztebl.2018.0628 Mayo Foundation for Medical Education and Research. (2021, February 2). Cutaneous T-cell lymphoma. Mayo Clinic. Retrieved March 16, 2022, from https://www.mayoclinic. org/diseases-conditions/cutaneous-tcell-lymphoma/symptoms-causes/syc20351056#:~:text=Cutaneous%20T%2Dcell%20 lymphoma%20(CTCL,make%20them%20 attack%20the%20skin. Mitry, M., Sogani, J., Sutton, E., Kumar, P., Horwitz, S., Elmi, A., Patel, S., Gallagher, K., Dashevsky, B., & Mango, V. (2020, June 26). Rare Cancer on the Rise: An Educational Review of Breast Implant-associated Anaplastic Large Cell Lymphoma. Journal of Breast Imaging. 2(4), 398–407. https://doi.org/10.1093/jbi/wbaa041

the treatment of pathologically node-negative breast cancer: a meta-analysis of four randomized trials with long-term follow up. Oncology reviews, 6(2), e20. https://doi.org/10.4081/oncol.2012.e20 Sansone, P., & Bromberg, J. (2012). Targeting the interleukin-6/Jak/stat pathway in human malignancies. Journal of clinical oncology : official journal of the American Society of Clinical Oncology, 30(9), 1005–1014. https://doi. org/10.1200/JCO.2010.31.8907 Tarpila, E., Ghassemifar, R., Fagrell, D., & Berggren, A. (1997). Capsular contracture with textured versus smooth saline-filled implants for breast augmentation: a prospective clinical study. Plastic and reconstructive surgery, 99(7), 1934–1939. https://doi.org/10.1097/00006534-19970600000019 Tevis, S. E., Hunt, K. K., Miranda, R. N., Lange, C., Butler, C. E., & Clemens, M. W. (2019). Differences in human leukocyte antigen expression between breast implant–associated anaplastic large cell lymphoma patients and the general population. Aesthetic Surgery Journal, 39(10), 1065–1070. https://doi.org/10.1093/asj/sjz021 Wang, Y., Zhang, Q., Tan, Y., Lv, W., Zhao, C., Xiong, M., Hou, K., Wu, M., Ren, Y., Zeng, N., & Wu, Y. (2022). Current progress in breast implantassociated anaplastic large cell lymphoma. Frontiers in Oncology, 11. https://doi. org/10.3389/fonc.2021.785887 What is a mastectomy? American Cancer Society. (n.d.). Retrieved February 25, 2022, from https://www.cancer.org/cancer/breast-cancer/ treatment/surgery-for-breast-cancer/ mastectomy.html What is cancer? National Cancer Institute. (n.d.). Retrieved February 25, 2022, from h t t p s : / / w w w. c a n c e r. g o v / a b o u t - c a n c e r / understanding/what-is-cancer Sauerwein, K., (October 23, 2019). Surgeon weighs in on textured breast implants. Washington University School of Medicine in St. Louis. https://medicine.wustl.edu/news/surgeonweighs-in-on-textured-breast-implants/

Petrelli, F., Lonati, V., & Barni, S. (2012). Axillary dissection compared to sentinel node biopsy for

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A Bioinformatic Analysis of mecA Prevalence in Bacterial Species BY ISHAAN GOSWAMI (BAYVIEW GLEN INDEPENDENT SCHOOL) Cover Image: View of double stranded DNA Image Source: Pixabay

Abstract: Antibiotic resistance is a serious issue in healthcare. mecA is the gene in MRSA and many other bacterial species responsible for the development of resistance to commonly used β-lactam antibiotics. MRSA and other β-lactam resistant bacteria pose risks to health by increasing healthcare related mortality and morbidity rates. This paper aims to display the promising usage of bioinformatic tools in tackling antibiotic resistance by investigating the prevalence of mecA across bacterial species. It is imperative that further research be done to investigate the prevalence of other antibiotic resistant genes using similar bioinformatic approaches. Introduction Antibiotic resistance is a problem of great concern for the medical community. “Superbugs” are pathogens that undergo mutations which causes resistance to treatments, and can cause increasingly harmful infections. One such superbug is Methicillin-resistant Staphylococcus aureus (MRSA). Staphylococcus aureus is a gram-positive, coccal bacteria which causes staph infections and has the potential to cause serious complications, such as pulmonary, coronary, and urinary tract infections (Taylor & Unakal, 2018). Due to mutations, a strain of S. aureus has

developed into MRSA and has become resistant to commonly used β-lactam antibiotics, which include penicillin and its derivatives such as methicillin (Green et al., 2012). mecA is a gene in MRSA conferring resistance to β-lactam antibiotics. (Ubukata et al., 1989). In susceptible strains of S. aureus, β-lactam antibiotics specifically inhibit a transpeptidase that catalyzes cell-wall crosslinking between polysaccharide chains and peptides, which creates a strong polymer called peptidoglycan that maintains the rigidity and shape of bacterial cell walls. However, in mutated forms of S. aureus that contain mecA, the gene encodes for a protein called PBP2A (penicillin-binding protein 2A), which has a low affinity for β-lactam antibiotics. This means that it does not bind to β-lactam antibiotics. This means that cell wall synthesis is not inhibited, and bacterial reproduction is unhampered (Fishovitz et al., 2014). MRSA is not benign and has been observed in clinical settings to be hazardous to health. Typically, MRSA infections occur in hospitals, nursing homes, dialysis centers, and other primary care locations. These cases of MRSA are called healthcare associated MRSA, or DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

HA-MRSA. MRSA can be contracted during surgeries, or by touching unclean surfaces (Mayo Clinic, 2018). Community-associated MRSA, or CA-MRSA can spread by skin-to-skin contact between seemingly healthy populations. Thus, people who are constantly in physical contact with other people such as wrestlers, or people living in crowded conditions are considered at risk populations (Mayo Clinic, 2018). The main unsolved issue surrounding MRSA is the lack of effective remedies to infections. Since methicillin is a narrow range antibiotic, meaning it can only inhibit a limited number of bacterial species, it has become increasingly difficult to treat such infections. Since methicillin targets specific bacteria, antibiotics that would have targeted these infections become unresponsive. Thus, broad range antibiotics must be employed, which is discouraged as they can develop antibiotic resistance in more bacterial species. MRSA is responsible for approximately 80,461 infections, and 11,285 deaths annually in the United States (Melander et al., 2017). It is evident that MRSA poses a serious threat to public health. Two bioinformatic analyses related to the mecA gene from MRSA were conducted in this paper; these included the investigation of the spread of mecA to other bacterial strains via homologybased searches and exploration available information about the structure and function of mecA protein via secondary databases. This work will hopefully improve the understanding of the characteristics and spread of mecA and will thus contribute to the efforts of combating MRSA.

Methods Investigating the prevalence of mecA across bacterial species To investigate the prevalence of mecA, and analogous proteins across bacterial species, BLAST was utilized (using the accession number “MW682923”), which was accessed at the National Centre for Biotechnology Information (NCBI) website. BLAST stands for basic local alignment search, and is an algorithm used to compare primary biological sequence information. BLAST compares a subject sequence called a query against a database of sequences to find analogous matches. BLASTn was used for the nucleotide search, while BLASTp was used for the protein search. For hits to be considered biologically significant, the following cut-offs, based on current literature (Lee et al., 2010; Kaur et al., 2019), have been introduced to the BLAST searches: >50% Percentage Identity, >80% coverage, and E-value <1e-5.

"The main unsolved issue surrounding MRSA is the lack of effective remedies to infections."

Investigating the function of mecA To investigate the function of mecA, public secondary databases were employed. uniProt, a secondary database which contains protein annotations; Pfam, a secondary database which analyzes protein sequences and determines conserved protein domains; and Phobius, a secondary database that analyzes protein signatures to figure out where in the cell they are located. Image 1: Bioinformatic tools can effectively be used to track antibiotic resistance Image Source: Flickr

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Results Investigating the prevalence of mecA across bacterial species

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Image 2: Phobius Posterior Proabilities for mecA Source: Produced by Goswami via Phobius

Discussion Investigating the prevalence of mecA across bacterial species Table 1 shows that only bacteria of the genus Staphylococcus met the required cut-offs to be considered significant. This means that all the species that were hits in the BLASTn search have mecA, and these findings are biologically significant. This is in line with previous labbased experimentation, which finds that mecA exists in multiple other Staphylococcal species found in humans and animals called coagulasenegative staphylococci (CoNS) (Becker et al., 2014). BLASTn only accounts for hits with regards to the genetic sequence of the query and other organisms, not the function or expression of this sequence. However, even though some of the species do not meet the cut off, they should be considered and investigated, as on the nucleotide level, they may be different, while they create proteins with similar structures and functions. The hits obtained that did not meet the cut-offs had annotations of peptidoglycan glycosyltransferase, mecA, penicillin-binding protein 2, and penicillin binding transpeptidase, all of which are either mecA or use the similar mechanisms to obtain β-lactam resistance. An analysis of the results of the BLASTn hits shows multiple bacterial species that have β-lactam resistance. Enterococci have been shown to have β-lactam resistance by altering penicillinbinding proteins (mecA) and the production of a β-lactamase in E. faecalis (Fontana et al., 1990). Genus Clostridium has been shown to have developed β-lactam resistance by producing β-lactamase like E. faecalis (Sandhu et al., 2019). Genus Listeria has been observed to have an innate resistance to β-lactam antibiotics (Krawczyk-Balska et al., 2012). The two hits both employ Penicillin-binding transpeptidase, which

is thus an intrinsic part of its genome, and not a mutation. P. vulgaris has been shown to exhibit β-lactam resistance. There are certain novel findings that must be examined in further detail. M. litoralis has not been experimentally confirmed to possess β-lactam resistance, but these findings show that it should be investigated further via experimentation. W. coagulans has been shown to be a probiotic agent in dairy, but there is no literature on this species’ β-lactam antibiotic resistance (Tóth et al., 2021). Dairy is a consumer product, thus, W. coagulans has the potential to be a public health concern. It is implored that this finding is observed in more detail. Table 2 shows organisms that have a similar protein sequence to the query. Staphylococcus, Mammaliicoccus, Escherichia, Listeria, Macrococcus, Mycobacteroides, and Salmonella are the represented genera in this BLASTp. However, it should be noted that most of these are not annotated as mecA. Instead, they are typically a penicillin binding protein, beta-lactam resistant peptidoglycan transpeptidase, mecB, or mecC. This shows that these are analogous proteins, but not identical to mecA. Their amino acid sequence is similar, and thus, in these cases, have similar functions. It has been shown that non-staphylococcal bacteria, such as E. coli have gained β-lactam antibiotic resistance, which corroborates the results found in this analysis. (Kassem et al., 2008) E. coli has been experimentally observed to have gained antibiotic resistance to β-lactam antibiotics and has shown the potential to develop further antibiotic resistance via laboratory cloning (Jacoby & Sutton, 1985). Listeria, as stated previously, has been discovered to have

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innate β-lactam resistance (Krawczyk-Balska et al., 2012). Salmonella has also been associated with β-lactamase production, which provides β-lactam resistance (Souza et al., 2020). There were also several findings of note. Genus Mammaliicoccus has been shown computationally to have β-lactam resistance. However, the only information available on this genus are primary database entries, and a study on wide-range antibiotic resistance in various Mammaliicoccus species in cattle (Schauer et al., 2021). This result must be investigated further. M. caseolyticus have been shown to carry mecB, as these results show, and mecD, which is a novel gene that shares a 66% nucleotide identity with mecB (Schwendener et al., 2017). This novel gene is a potential area of further inquiry into the evolution of antibiotic resistance. M. abscessus has innate antibiotic resistance. However, it has been determined that a combination of β-lactam antibiotics have a 100% efficacy rate against M. abscessus (Story-Roller et al., 2021). This is encouraging, as M. abscessus is associated with Penicillin-binding protein PBpA, a β-lactam resistance conferring protein. These results show that members of the genus Staphylococcus other than MRSA are genetically homologous for mecA, while other bacterial genera exhibit β-lactam antibiotic resistance, which are analogous in terms of protein sequence to mecA. Investigating the function of mecA Table 3 shows the protein annotations of mecA. Penicillin binding is in line with the function of mecA and PBP2A. D-Ala-D-Ala carboxypeptidase activity entails the activity of an enzyme that is involved in cell wall integrity and strength (Spidlova et al., 2018). Β-lactam antibiotics work by inhibiting cell wall growth, and thus reproduction. The D-Ala-D-Ala carboxypeptidase activity thus counteracts this. Peptidoglycan glycosyltransferase activity involved in biosynthesis of bacterial cell wall, involves enzyme reactions that take place within the cytoplasm, and outside the cytoplasmic membrane. (Barreteau et al., 2008). This is in line with the methodologies of PBP2A to counteract Β-lactam antibiotics. The transmembrane nature of Peptidoglycan glycosyltransferase activity is in line with results from the Phobius analysis.

rest of the protein and have their own functions. These domains can be used to infer function, and proteins which probably have similar functions, but this must be tested via experimentation. There are three conserved domains: Penicillin binding transpeptidase domain; Penicillin binding Protein dimerization domain; and NTF2-like N-terminal transpeptidase domain. Transpeptidase is responsible for catalyzing cell wall cross-linking, which ensures bacterial cell wall integrity (Fishovitz et al., 2014). Thus, the Penicillin binding transpeptidase domain is related to maintaining cell wall structure and integrity. Dimerization is a process wherein two chemically similar molecules form a dimer, which is a single polymer. Dimerization is important role in maintaining transmembrane proteins. Dimerization is important for polymerizing peptidoglycan, which is related to the function of PBP2A. Its transmembrane nature is also in line with the Phobius findings, which explains the Penicillin binding Protein dimerization domain. The NTF2-like N-terminal transpeptidase domain’s length suggests a possible structural role of the domain, and thus gives the transpeptidase domain a longer reach from the cell membrane (Lim & Strynadka, 2002). This means that it is involved in bacterial cell wall cross-linking and is thus a part of the function of mecA. Figure 2 shows the probabilities of the location of mecA in a cell by analyzing protein signatures. The Phobius Posterior Probabilities for mecA clearly shows a transmembrane region (purple, score ≈ 1) and a non-cytoplasmic region (light blue, score = 0.8). These results show that it resides on the outside of the cell with a transmembrane region across the bacterial membrane, which is fully in line with the mechanism of PBP2A against β-lactam antibiotics, and with the findings from UniProt and Pfam. An analysis of secondary databases may shine light on the structure, location, and function of mecA, and all these results are in line with the mechanisms of antibiotic resistance employed by PBP2A. A firm understanding of these functions and structures can be used to determine effective counters to these new antibiotic resistant species.

Table 4 shows the conserved domains of mecA. Domains are more conserved evolutionarily than other regions of a protein and evolve as units. Domains are also structurally distinct from the WINTER/SPRING 2022

Conclusion This bioinformatical analysis highlighted the use of bioinformatic tools to track antibiotic resistance in bacterial populations, and thus formulate adequate responses to this urgent issue. The novel findings of β-lactam antibiotic resistance in the species M. litoralis, W. coagulans and genus Mammaliicoccus must be investigated further. They represent a potential concern in healthcare, as new species of antibiotic resistant bacteria. More research into the analysis of analogous protein structures to ¬mecA in various bacterial species will be an important step to combatting antibiotic resistance from a bioinformatics perspective. Acknowledgements I would like to acknowledge Dr. Ashraf Zarkan of the University of Cambridge for his guidance and mentorship in this project. I would like to thank the Cambridge Centre for International Research for their sustained support throughout the research process. I would also like to thank Ms. Kristin Carpenter of the Bayview Glen Independent School for supporting my passion for, and exploration in the biological sciences. References Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990). Basic local alignment search tool. Journal of molecular biology, 215(3), 403–410. https://doi.org/10.1016/S00222836(05)80360-2 Barreteau, H., Kovač, A., Boniface, A., Sova, M., Gobec, S., & Blanot, D. (2008). Cytoplasmic steps of peptidoglycan biosynthesis. FEMS Microbiology Reviews, 32(2), 168–207. https:// doi.org/10.1111/j.1574-6976.2008.00104.x Becker, K., Heilmann, C., & Peters, G. (2014). Coagulase-Negative Staphylococci. Clinical Microbiology Reviews, 27(4), 870–926. https:// doi.org/10.1128/cmr.00109-13 EBI. (n.d.) Sequence: MW682923.1. Www.ebi. ac.uk. https://www.ebi.ac.uk/ena/browser/view/ MW682923 Fishovitz, J., Hermoso, J. A., Chang, M., & Mobashery, S. (2014). Penicillin-binding protein 2a of methicillin-resistantStaphylococcus aureus. IUBMB Life, 66(8), 572–577. https://doi. org/10.1002/iub.1289 Fontana, R., Canepari, P., Lleò, M. M., & Satta, G. (1990). Mechanisms of resistance of enterococci to beta-lactam antibiotics. European Journal of Clinical Microbiology & Infectious Diseases: Official Publication of the European Society of Clinical Microbiology, 9(2), 103–105. https://doi. org/10.1007/BF01963633 Green, B. N., Johnson, C. D., Egan, J. T., Rosenthal, M., Griffith, E. A., & Evans, M. W. (2012). Methicillin-resistant Staphylococcus aureus: an overview for manual therapists. 34

Journal of Chiropractic Medicine, 11(1), 64–76. https://doi.org/10.1016/j.jcm.2011.12.001 Jacoby, G. A., & Sutton, L. (1985). Beta-Lactamases and beta-lactam resistance in Escherichia coli. Antimicrobial Agents and Chemotherapy, 28(5), 703–705. https://www.ncbi.nlm.nih.gov/pmc/ articles/PMC176364/#:~:text=Escherichia%20 coli%20strains%20determining%2017 Käll, L., Krogh, A., & Sonnhammer, E. L. L. (2004). A Combined Transmembrane Topology and Signal Peptide Prediction Method. Journal of Molecular Biology, 338(5), 1027–1036. https:// doi.org/10.1016/j.jmb.2004.03.016 Kassem, I. I., Esseili, M. A., & Sigler, V. (2008). Occurrence of mecA in Nonstaphylococcal Pathogens in Surface Waters. Journal of Clinical Microbiology, 46(11), 3868–3869. https://doi. org/10.1128/jcm.01035-08 Kaur, H., Bose, C., & Mande, S. S. (2019). Tryptophan Metabolism by Gut Microbiome and Gut-Brain-Axis: An in silico Analysis. Frontiers in Neuroscience, 13. https://doi.org/10.3389/ fnins.2019.01365 Krawczyk-Balska, A., Marchlewicz, J., Dudek, D., Wasiak, K., & Samluk, A. (2012). Identification of a ferritin-like protein of Listeria monocytogenes as a mediator of β-lactam tolerance and innate resistance to cephalosporins. BMC Microbiology, 12, 278. https://doi.org/10.1186/1471-2180-12278 Lee, J.-H., & Lee, J. (2010). Indole as an intercellular signal in microbial communities. FEMS Microbiology Reviews, 34(4), 426–444. https:// doi.org/10.1111/j.1574-6976.2009.00204.x Lim, D., & Strynadka, N. C. J. (2002). Structural basis for the β lactam resistance of PBP2a from methicillin-resistant Staphylococcus aureus. Nature Structural Biology, 9(11). https://doi. org/10.1038/nsb858 Mayo Clinic. (2018). MRSA infection - Symptoms and causes. Mayo Clinic; https://www.mayoclinic. org/diseases-conditions/mrsa/symptoms-causes/ syc-20375336 Melander, R. J., Zurawski, D. V., & Melander, C. (2017). Narrow-spectrum antibacterial agents. MedChemComm, 9(1), 12–21. https://doi. org/10.1039/c7md00528h Mistry, J., Chuguransky, S., Williams, L., Qureshi, M., Salazar, G., Sonnhammer, E. L. L., Tosatto, S. C. E., Paladin, L., Raj, S., Richardson, L. J., Finn, R. D., & Bateman, A. (2020). Pfam: The protein families database in 2021. Nucleic Acids Research, 49(D1), D412–D419. https://doi. org/10.1093/nar/gkaa913 MW682923. (n.d.). Getentry.ddbj.nig.ac.jp. http://getentry.ddbj.nig.ac.jp/getentry/na/ MW682923?filetype=html Sandhu, B. K., Edwards, A. N., Anderson, S. E., Woods, E. C., & McBride, S. M. (2019). Regulation and Anaerobic Function of the Clostridioides difficile β-Lactamase. Antimicrobial Agents and DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Chemotherapy, 64(1). https://doi.org/10.1128/ AAC.01496-19 Schauer, B., Szostak, M. P., Ehricht, R., Monecke, S., Feßler, A. T., Schwarz, S., Spergser, J., Krametter-Frötscher, R., & Loncaric, I. (2021). Diversity of methicillin-resistant coagulasenegative Staphylococcus spp. and methicillinresistant Mammaliicoccus spp. isolated from ruminants and New World camelids. Veterinary Microbiology, 254(109005). https://doi. org/10.1016/j.vetmic.2021.109005 Schwendener, S., Cotting, K., & Perreten, V. (2017). Novel methicillin resistance gene mecD in clinical Macrococcus caseolyticus strains from bovine and canine sources. Scientific Reports, 7(1). https://doi.org/10.1038/srep43797 Souza, A. I. S., Saraiva, M. M. S., Casas, M. R. T., Oliveira, G. M., Cardozo, M. V., Benevides, V. P., Barbosa, F. O., Freitas Neto, O. C., Almeida, A. M., & Berchieri, A. (2020). High occurrence of β-lactamase-producing Salmonella Heidelberg from poultry origin. PLOS ONE, 15(3). https:// doi.org/10.1371/journal.pone.0230676 Spidlova, P., Stojkova, P., Dankova, V., Senitkova, I., Santic, M., Pinkas, D., Philimonenko, V., & Stulik, J. (2018). Francisella tularensis D-Ala D-Ala Carboxypeptidase DacD Is Involved in Intracellular Replication and It Is Necessary for Bacterial Cell Wall Integrity. Frontiers in cellular and infection microbiology, 8(111). https://doi. org/10.3389/fcimb.2018.00111 Staphylococcus aureus strain MRSA-12 penicillinbinding protein 2 (mecA) gene, complete cds. (2021). NCBI Nucleotide. https://www.ncbi.nlm. nih.gov/nuccore/MW682923.1?report=fasta Story-Roller, E., Galanis, C., & Lamichhane, G. (2021). β-Lactam Combinations That Exhibit Synergy against Mycobacteroides abscessus Clinical Isolates. Antimicrobial Agents and Chemotherapy, 65(4). https://doi.org/10.1128/ AAC.02545-20 Staphylococcus aureus strain MRSA-12 penicillinbinding protein 2 (mecA) gene, complete cds. (2021). NCBI Nucleotide. https://www.ncbi.nlm. nih.gov/nuccore/MW682923.1?report=fasta Taylor, T. A., & Unakal, C. G. (2018). Staphylococcus Aureus. Nih.gov. https://www. ncbi.nlm.nih.gov/books/NBK441868/ Tóth, A. G., Csabai, I., Judge, M. F., Maróti, G., Becsei, Á., Spisák, S., & Solymosi, N. (2021). Mobile antimicrobial resistance genes in probiotics. BioRxiv. https://doi. org/10.1101/2021.05.04.442546 Ubukata, K., Nonoguchi, R., Matsuhashi, M., & Konno, M. (1989). Expression and inducibility in Staphylococcus aureus of the mecA gene, which encodes a methicillin-resistant S. aureusspecific penicillin-binding protein. Journal of Bacteriology, 171(5), 2882–2885. https://www. ncbi.nlm.nih.gov/pmc/articles/PMC209980/ UniProt. (n.d.). mecA - Beta-lactam-inducible WINTER/SPRING 2022

penicillin-binding protein - Staphylococcus aureus - mecA gene & protein. (n.d.). Www. uniprot.org. https://www.uniprot.org/uniprot/ A0A0P0D5K6 UniProt. (n.d.). mecA - MecA - Staphylococcus aureus - mecA gene & protein. (n.d.). Www. uniprot.org. https://www.uniprot.org/uniprot/ Q7DHH4

“I can't stop eating”- Binge Eating Disorder and the Leptin Signaling Pathway BY HUONG LE (HARVARD UNIVERSITY), EMILY JOHNS (STANFORD UNIVERSITY SCHOOL OF MEDICINE), & JULIEN GRIMAUD (SUP'BIOTECH RESEARCH DEPARTMENT) Cover Image: Burger, Soda, and Fries. Image Source: Pexel

Abstract Binge Eating Disorder (BED) is a very common mental illness that significantly reduces the quality of life and health. BED is characterized by consuming an abnormally large amount of food in a short period of time and feeling a lack of control over what and how much you are eating, often resulting in guilt or emotional distress. Despite its prevalence and severity, the neuroscience of BED is not well understood in medical and research communities alike. Recent research on the hormone leptin sheds light on a possible neural map of BED. Understanding the role of leptin signaling in BED may illuminate avenues of future research and treatment.

of self-conscious peers. She became hyper-aware of her meal portions, eating “good” food and avoiding “bad" food. After failing to live up to her impossible standards, Amanda was overcome with an intense sense of guilt and would spend 2+ hours in the gym every day attempting to burn off the excess calories.

Introduction At first, Amanda L. didn't recognize she had an eating disorder. Until age 15, she never cared much about her eating habits. Like most other teenagers, she enjoyed her food in large quantities and did not give too much thought afterward, even when she felt full.

However, in the spring of 2020, she was evicted from her college campus and found herself back in her parent's home primarily confined to her childhood bedroom. As the COVID-19 pandemic sent huge waves of panic across the nation most schools and businesses also closed. The combined increase in stress and inactivity from lockdowns prompted Amanda to continually reduce her portions and exercise excessively. Soon, one, three, and six months passed. Prompted by a combination of the stress and anxiety caused by the pandemic and her disordered eating and exercise habits she developed a cycle of restricting caloric intake, binging food, feeling guilty about it, over-exercising, restricting, and so on.

Her mindset and eating habits changed when Amanda entered college and was immersed in a highly pressured environment and community

Amanda was not alone. Across the country, the COVID-19 pandemic has wreaked havoc on peoples’ mental and physical health (Von DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Table 1: DSM-V Diagnostic Criteria for BED. A patient must meet all five criteria to be diagnosed with BED. A binge refers to the rapid consumption of an unusually large amount of food in the absence of hunger, causing an individual to feel guilty, embarrassed, depressed, or out of control. Information adapted from the DSM-V (American Psychological Association [APA], 2013).

Keyserlingk et al., 2021). People who struggled with body image and healthy eating behaviors before the onset of the pandemic were some of the most vulnerable to its added stressors (Christensen et al., 2021). A recent study published in the International Journal of Eating Disorders associated the pandemic and its social consequences with increased food consumption, eating as a coping mechanism, as well as caloric restriction (Termorshuizen et al., 2020). For many people, eating is used as a coping mechanism during stressful times. Eating as a stress reliever, combined with food scarcity, prolonged quarantined periods, and increased access to misleading social media (on which uncensored, misleading content about daily caloric intake and diet tips run rampant) have led many individuals like Amanda to develop binge eating behaviors. Over the past few years, various studies have highlighted how the COVID-19 pandemic has exacerbated food insecurity throughout the world, further contributing to disordered eating behaviors (Parekh et al., 2021). What is binge eating disorder? The Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-V) characterizes eating and feeding disorders as the presence of continuous alterations of eating or eatingrelated behavior causing alterations in food consumption leading to impairments in physical and/or psychosocial functioning (American Psychological Association [APA], 2013). Among many devastating eating disorders is binge eating disorder (BED). The five-part diagnostic criteria for the disorder emphasize the frequent and often ritualistic eating of atypically large quantities of

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food in short periods of time (maximum twohour binges occurring at least once a week for three months) and the distressing nature of such activity in patients (Westerberg et al. 2013) (Table 1). About 3.5 percent of adult women and 2 percent of adult men suffer from BED, making it the most common eating disorder in the United States. Most people with BED also suffer from obesity, childhood trauma or psychological problems that lead them to overeat as a form of coping (Westerberg et al. 2013). In addition, BED is often associated with mood, anxiety, substance use disorders, and an increased risk of suicide attempts (Udo et al. 2019; Udo and Grilo, 2019).

"About 3.5 percent of adult women and 2 percent of adult men suffer from BED, making it the most common eating disorder in the United States."

Coleman’s Experiments and the Satiety Hormone To this day, despite the high prevalence and negative impacts of BED, its underlying neurological mechanisms remain poorly understood (Steward et al. 2018). However, over the past few decades, various experiments have shed some light on the possible neurobiological basis of disordered eating behaviors. In 1960’s, Douglas L. Coleman was working at the Jackson Laboratory, a research institute in Maine specializing in mammalian genetics, when he got interested in two of their mouse strains: the ob/ob (obese) and db/db (diabetic) mutants. Both strains showed hyperphagia (lack of satiety) and were obese. The ob and db mutations were located on distinct chromosomes. When Coleman began his investigations, it was known that the db mutation caused issues in insulin

signaling. However, the mechanisms that led to hyperphagia in ob/ob and db/db mice was still unclear. Coleman hypothesized that a hormone may be responsible for the control of satiety. To test his hypothesis, he conducted a set of seminal parabiosis experiments, in which he joined two mice at the hip with surgical suture shortly after birth so that they shared each other’s circulating blood (Coleman, 1973; Coleman, 2014) (Figure 1).

"The hormone leptin is secreted by adipocytes in proportion to fat mass, providing feedback on the status of lipid amount in the bloodstream."

When two wild-type mice were surgically joined together at the hip, they were healthy for the duration of the experiment. When an ob/ob was joined with a wild-type mouse, however, the ob/ob mouse lost weight. This experiment suggested that the wild-type mouse produced a satiety hormone that was either absent or nonfunctional in the ob/ob mouse before their two blood systems were connected. More surprisingly, when joining a wild-type mouse with a db/db animal, the db/db mouse kept gaining weight as normal, while wild-type mouse let itself starve to death. Coleman therefore concluded that the db/ db mouse produced much greater quantities of this satiety hormone – enough to stop any food intake in the wild-type mouse – and was not responsive to it. Finally, when Coleman joined an ob/ob and a db/db mouse together, he observed that the ob/ob mouse lost weight, while the db/ db mouse kept exhibiting the expected behavior (hyperphagia and obesity). This confirmed that the satiety hormone identified in both mutants were the same molecule (Coleman, 1973) (Figure 1). Subsequent genetic studies identified the hormone leptin as Coleman’s satiety factor (Halaas et al., 1995; Barone et al., 1995)

Since Coleman’s seminal work, several lines of inquiry on leptin’s role in appetite, obesity, and eating disorders have been pursued. Remarkably, BED is characterized by high levels of circulating leptin, suggesting that it plays an important role in the development and maintenance of the disorder (Monteleone et al., 2000b). Recent studies indicate that the neural pathway that regulates eating behavior might potentially be the site of leptin's actions on mediating feeding behaviors, suggesting that there might be a neurochemical circuit that explains the neurobiological underpinnings of behaviors associated with BED (Branson et al., 2003; Monteleone et al., 2000b; Shah et al., 2014). The Role of Leptin in Regulation of Eating Behaviors The hormone leptin is secreted by adipocytes in proportion to fat mass, providing feedback on the status of lipid amount in the bloodstream. The target tissue of leptin is a subdivision of the hypothalamus called the arcuate nucleus (ARC), where the blood-brain barrier allows for the passage of nutrients and hormones. When it binds to its receptor, leptin acts as a reporter of the amount of fat in the body, promoting both satiety and lipid metabolism. In the ARC, leptin activates two distincts neuronal populations: the pro-opiomelanocortin (POMC) and agouti generelated protein (AgRP) neurons (Andermann & Bradford, 2017; Pan & Myers, 2018; Varela & Horvath, 2012) (Figure 2). Once activated by leptin, POMC neurons secrete a neuropeptide called α-MSH into the paraventricular nucleus of the hypothalamus (PVH). This, in turn, activates various receptors at the surface of PVH neurons, including

Image 1: Douglas L. Coleman’s parabiosis experiments. Two wildtype (WT) joined together remain healthy. When a WT mouse is joined to an ob/ob mouse, the WT animal remains healthy while the ob/ob mutant loses weight. When a WT mouse is joined with a db/ db mutant, the mutant remains obese while the WT mouse lets itself starve to death. Finally, when mutants ob/ob and db/db are joined together, the ob/ob mouse loses weight while the db/ db mutant remains obese. From this set of experiments, Coleman hypothesized the existence of a satiety hormone, now known as leptin.

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Image 2: Leptine signaling pathway. Leptin activates POMC and AgRP neurons in the ARC. When activated, POMC neurons release α-MSH at the synapses they form with PVH neurons, which in turn activates them through the interaction of α-MSH with its receptor MC4R. On the contrary, AgRP neurons inhibit PVH neurons by releasing three peptides: AgRP (which antagonizes MC4R), NPY (which interacts with its receptor YR), and GABA (which interacts

melanocortin-4 receptors (MC4R). Among the PVH neurons, MC4R are known to play a central role in appetite and energy regulation in the brain. Once activated, the PVH ultimately triggers a reduction of food intake, which is why PVH neurons are often called “satiety neurons” (Andermann & Bradford, 2017; Pan & Myers, 2018; Varela & Horvath, 2012) (Figure 2). In contrast to POMC neurons, AgRP neurons inhibit the PVH through the release of three neuropeptides: AgRP, GABA, and neuropeptide Y (NPY). Peptides AgRP and GABA directly inhibit PVH neurons, while NPY antagonizes MC4R. As a consequence, AgRP neurons trigger an increase in food intake. Overall, the activation of POMC and AgRP neurons have opposite effects on satiety. They are part of a strongly regulated satiety balance (Andermann & Bradford, 2017; Pan & Myers, 2018; Varela & Horvath, 2012) (Figure 2). Discussion BED is a condition characterized by frequent and often ritualistic episodes of binge eating, often resulting in guilt or emotional distress (Westerberg et al. 2013). Despite its prevalence, the physiological mechanisms leading to BED are not well understood (Steward et al. 2018; Westerberg et al. 2013). Since Coleman’s discovery of leptin as the satiety hormone (Coleman, 1973), various studies have investigated the link between the leptin signaling pathway and eating disorders (Branson et al., 2003; Monteleone et al., 2000b; Shah et al., 2014). For example, it has been found that mutations in the MC4R gene are often associated with binge eating behavior in patients suffering from obesity (Branson et al., 2003). This discovery suggests that MC4R mutation may alter POMC and AgRP communication to the PVH neurons, inhibiting the feeling of satiety and leading to binge eating. It is important to recognize that the neurochemical environment and genetic basis of binge eating disorder are complex and MC4R mutation is only one piece of our biological understanding of this disorder, albeit an important piece (Branson et al., 2003; Monteleone et al., 2000b; Shah et al., 2014). The precise role of MC4R and the leptin pathway in BED is still open to testing (Steward et al. 2018; Westerberg et al. 2013). For example, it would be interesting to quantify MC4R mutations in BED patients. Future research could aim to find other mutations associated with MC4R mutations in BED, as only analyzing one gene is far too simplistic and unreliable an approach for such a WINTER/SPRING 2022

complex system. After identifying other genes of interest, one potential avenue of study would be to knock out the genes of interest in mice and see how eating behaviors change accordingly. Such experiments will help advance our understanding of the genetics of BED in a systematic manner. Competing interests The authors have no competing interests to declare. Authors’ contributions HL and EJ designed and drafted the manuscript with support from JG. All authors contributed to the final manuscript. The first draft of this manuscript was written as part of HL and EJ's final submission for the year-long course NEURO101J "Maps of the Brain", taught at Harvard University in 2020-2021 by JG. References American Psychological Association [APA]. (2013). Feeding and Eating Disorders. In Diagnostic and Statistical Manual of Mental Disorders. American Psychiatric Association. Andermann, M. L., & Lowell, B. B. (2017). Toward a Wiring Diagram Understanding of Appetite Control. Neuron, 95(4):757-778. Branson, R., Potoczna, N., Kral, J. G., Lentes, K.U., Hoehe, M. R., & Horber, F. F. (2003). Binge Eating as a Major Phenotype of Melanocortin 4 Receptor Gene Mutations. New England Journal of Medicine, 348(12): 1096–1103.

Christensen, K. A., Forbush, K. T., Richson, B. N., Thomeczek, M. L., Perko, V. L., Bjorlie, K., Christian, K., Ayres, J., Wildes, J. E., & Mildrum Chana, S. (2021). Food insecurity associated with elevated eating disorder symptoms, impairment, and eating disorder diagnoses in an American University student sample before and during the beginning of the COVID‐19 pandemic. The International Journal of Eating Disorders, 54(7): 1213–1223.

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Coleman, D. L. (1973). Effects of parabiosis of obese with diabetes and normal mice. Diabetologia, 9(4) : 294–298.

Udo, T., & Grilo, C. M. (2018). Prevalence and Correlates of DSM-5 Eating Disorders in Nationally Representative Sample of United States Adults. Biological Psychiatry, 84(5): 345–354.

Coleman, T.R. (2014). Douglas L. Coleman, 1931–2014. Diabetologia, 57(12) : 2429–2430. Halaas, J. L., Gajiwala, K. S., Maffei, M., Cohen, S. L., Chait, B. T., Rabinowitz, D., Lallone, R. L., Burley, S. K., & Friedman, J. M. (1995). Weightreducing effects of the plasma protein encoded by the obese gene. Science, 269(5223) : 543–546. Monteleone, P., Di Lieto, A., Tortorella, A., Longobardi, N., & Maj, M. (2000). Circulating leptin in patients with anorexia nervosa, bulimia nervosa or binge-eating disorder: Relationship to body weight, eating patterns, psychopathology and endocrine changes. Psychiatry Research, 94(2): 121–129.

Termorshuizen, J. D., Watson, H. J., Thornton, L. M., Borg, S., Flatt, R. E., MacDermod, C. M., Harper, L. E., van Furth, E. F., Peat, C. M., & Bulik, C. M. (2020). Early impact of COVID-19 on individuals with self-reported eating disorders: A survey of 1,000 individuals in the United States and the Netherlands. International Journal of Eating Disorders, 53(11): 1780–1790.

Varela, L., & Horvath, T. L. (2012). Leptin and insulin pathways in POMC and AgRP neurons that modulate energy balance and glucose homeostasis. EMBO Reports, 13(12):1079-1086. Von Keyserlingk, L., Yamaguchi-Pedroza, K., Arum, R., & Eccles, J. S. (2021). Stress of university students before and after campus closure in response to COVID-19. Journal of Community Psychology. Mar 31: 10.1002/jcop.22561. Online ahead of print. Westerberg, D. P., & Waitz, M. (2013). Bingeeating disorder. Osteopathic Family Physician, 5(6): 230–233.

Pan, W. W., & Myers, M. G. (2018). Leptin and the maintenance of elevated body weight. Nature Reviews Neuroscience, 19(2): 95–105. Parekh, N., Ali S. H., O’Connor, J., Tozan, Y., Jones, A. M., Capasso, A., Foreman, J., & DiClemente, R. J. (2021). Food insecurity among households with children during the COVID-19 pandemic: results from a study among social media users across the United States. Nutrition Journal, 20(1): 73–73. Shah, B. P., Vong, L., Olson, D. P., Koda, S., Krashes, M. J., Ye, C., Yang, Z., Fuller, P. M., Elmquist, J. K., & Lowell, B. B. (2014). MC4Rexpressing glutamatergic neurons in the paraventricular hypothalamus regulate feeding and are synaptically connected to the parabrachial nucleus. Proceedings of the National Academy of Sciences of the United States of America, 111(36): 13193–13198. Steward, T., Menchón, J. M., Jiménez-Murcia, S., Soriano-Mas, C., & Fernández-Aranda, F. (2018). Neural Network Alterations Across Eating Disorders: A Narrative Review of fMRI Studies.

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The utilization of Nitrogen-vacancy quantum defects for NMR experiments BY KATHERINE LASONE '23 Cover Image: The utilization of Nitrogen-vacancy quantum defects for NMR experiments Image Source: Unsplash

Abstract

Motivation

This paper demonstrates the feasibility of room temperature nuclear magnetic resonance (NMR) experiments through an inexpensive, tabletop Nitrogen-vacancy (NV) center spectrometer. The spectrometer operates in a low magnetic and microwave field, ambient temperatures and requires only commercially available components. The state of an NV center can be read out using optically detected resonance measurements (ODMR). While other NMR experiments use electromagnets, this experimental setup utilizes a permanent magnet source to decrease the cost and portability of the set up. Additionally, the Quanta Image Sensor (QIS) is used to count individual photons from singular NV centers. NV center readout is best observed in experiments with low light and high contrast conditions, which is perfect for the QIS but difficult with many complementary metaloxide semiconductor (CMOS) and charge couple device (CCD) image sensors. Applications of NV center spectrometer sensing includes detection of single-neuron action potentials, single protein detection, and investigations of meteorites.

Transistors are small semiconductor devices used to amplify and control electrical signals. Typically, transistors are composed of adjacent electron-doped (N) and hole-doped (P) regions. By allowing current to flow from an N to a P region or a P to an N region, the output power can be controlled. Based on the applied voltage to the transistor, the signal can be completely stopped or greatly amplified. Transistors are the fundamental building blocks of all computer electronics. For the past several decades, classical computers have continuously improved in speed and size per the projection of Moore's law – the hypothesis that the number of transistors in an integrated circuit doubles approximately every two years. However, the transistors within the computers are beginning to become so small that they are approaching the size of an atom. Classical computing architecture improvements are beginning to slow as issues such as current leakage and electron tunneling become increasingly impactful as transistor size decreases (Britannica, 2019). Thus, a new architecture regime is being explored: quantum DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Image 1: Pictorial representation of transistors within all electronics. Image Source: Unsplash

computers. Quantum computers follow laws of quantum physics — rather than classical physics — to perform computations. While classical bits are physical entities represented by a zero or one, quantum bits, also known as “qubits,” are physical entities that can be in a superposition of the zero and one states until they collapse. (That is, fall out of a quantum state and lose all of the associated information). The ability to be in superposition means that the qubit is neither a zero nor a one, but a combination of probabilities that are either zero or one. Further, qubits are represented by vectors and matrices in a vector space, unlike classical bits, which exist in a list of numbers. Thus, programmers can apply matrix multiplication and other linear algebra operations to qubits without them losing their quantum mechanical properties.

Due to the tendency of qubits to superimpose and entangle, quantum computers can quickly simulate complex atomic and molecular phenomena (Nielsen 2011). Thus, quantum computers have the potential to significantly improve ‘molecularly-based’ issues such as global warming by simulating atomic structures which could lead to carbon neutral and negative technologies. However, according Langione (2020), the most promising technologies are the ones which adapt existing infrastructures rather than completely overwrite them. Making extreme nation-wide changes overnight is difficult, but adapting current techniques is much more feasible. Thus, the following quantum technologies increase the efficiency of current industry standards rather than replace them are prioritized.

Further, the state of qubits can be entangled. This means that the probability of a qubit being a zero or one is tied to the fates of other qubits in the system. By entangling the states of qubits within vector space, quantum computers can speed up the output of many algorithms, as computations are being increasingly run in parallel.

The first quantum computing application in global warming is the reduction of carbon emissions due to the production of fertilizer. The leading method to produce fertilizer is through the Haber-Boch process, which fuses together nitrogen and hydrogen to make Ammonia. this process is extremely inefficient economically and environmentally — 3-5% of the world's natural gas is expended on fertilizer synthesis every single year (Langione 2020). Scientists know how to improve the efficiency of fertilizer production: simulate every molecular interaction in the electrostatic field of the catalyst nitrogenase. This simulation could be started today, but it wouldn't finish for 800,000 years. On a quantum computer, the simulation time would take a day (Langione 2021).

To exemplify the difference between classical and quantum computers, imagine a computer trying to solve a maze. A classical computer would go through every path of the maze sequentially to see if it was successful. However, a quantum computer would test every single pathway in a single step. In other words, the quantum computer can solve the maze in one try. Many of the challenging problems of today are characterized by a “mazelike” quality, especially simulation and optimization issues (Langione, 2020).

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"Thus, quantum computers have the potenial to significantly improve 'molecularly-based' issues such as global warming by simulating atomic structures which could lead to carbon neutral and negative technologies."

Additionally, quantum computers will catalyze the hydrogen production industry. Currently, hydrogen conversion processes to fuels are 42

costly. Photovoltaic cells in solar cells may also increase 30-50% in efficiency with the help of quantum computing software (Langione 2020). There are currently several competing climate change models that predict vastly different results. To create a climate model, many assumptions about the different interactions of regions throughout the globe are made. Characterizing those assumptions by leaving them as probabilities and creating one climate model could be an important driver for reducing global warming (Langione 2020).

"To build such a powerful quantum computer, researchers need to design qubits with lower error rates, longer coherence times, lower costs and noncryogenic operating temperatures."

Another key area that quantum computers will have an immense impact on is the infectious disease pharmaceutical industry. The design and analysis of molecules for drug development is a challenging problem today. From identifying the drivers of the disease, to screening millions of candidate activators and inhibitors, and developing a drug that can go to clinical trial testing is a process that takes typically ten or more years per drug (Langione 2020). In addition, 90% of those drugs fail to pass the clinical trials, costing companies billions of dollars. Scientists already know how to design a drug based on searching through a massive chemical space to find the best fitting compound. However, building, tracing, and exactly describing and calculating all the quantum properties of all the atoms in a molecule is an extremely difficult computational task (Ghose 2018). Then, converting this information into chemical a database for searchable drug design would take 5 trillion, trillion, trillion, trillion years. This clearly not feasible. But, on a quantum computer, this process would only take 30 minutes. Since a quantum computer operates using the same quantum properties as the molecule it’s trying to simulate, future large-scale quantum simulations for drug development could treat everything from Ebola to HIV to Alzheimer’s (Ghose 2018). Both hardware and software developments are required to turn these applications into reality. Challenges in quantum computing lay mainly in designing and controlling quantum hardware systems. Current quantum computing hardware is currently small-scale, because as the number of qubits in computation increases, there is a higher likelihood for error. Due to the atomic nature of qubits, their states are very fragile and susceptible to small effects. As the number of qubits in a system increases, the more likely

one of the many qubits will ‘collapse’ (lose all its data). Qubits may collapse for a variety of reasons, such as random electron movement. The understanding of how to correct qubit errors, a field known as quantum — is still a largely emerging field. Furthermore, quantum algorithms do not provide many, if any, advantages in reading or printing data compared to classical algorithms. Scientists have not yet figured out how to capitalize on quantum properties for reading and writing data (Biamonte 2017). Thus, the time it takes for a quantum algorithm to read or print data may prevent it from having a faster run time than its classical counterpart. Additionally, very little is known about the number of logic gates used in various quantum machine learning algorithms, so it can be hard to estimate their runtime. There has also not been extensive testing of the runtime of many quantum machine learning algorithms, so it is impossible to assert that they are superior to their classical counterparts. Quantum states are incredibly fragile and are easily destroyed by temperature & pressure fluctuations, stray electromagnetic fields, and collisions from nearby particularly. Currently, qubits are still far from being 99.99% error proof & only a few qubits can be controlled together at a time. There must be large strides forward in the fabrication of high-quality qubits on a hardware level and self-imposed error correction on the software level (Ghose 2018). Many times, quantum computers also do not improve the run time or memory usage of a classical computer. To build such a powerful quantum computer, researchers need to design qubits with lower error rates, longer coherence times, lower costs and non-cryogenic operating temperatures. Unlike many qubit designs, diamond lattice qubits operate under ambient conditions (Liu 2018). This alleviates the need for quantum computers to rely on complex cryogenic storage facilities, making building NV-center qubits more manageable. Additionally, NV-centers can be easily entangled using electromagnetic driving fields (Benjamin 2011). Since NV centers are also located within a tough diamond, they are less susceptible to noise than other designs. Nitrogen vacancy center theory Replacing two neighboring Carbon atoms in a diamond lattice with a nitrogen atom and a vacancy (or “hole”) creates a nitrogen-vacancy

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Experimental background The combination of a magnetic field, microwave pulses, and 532 nm laser light are the main components required to create an NV center spectrometer in diamonds. Each component has a very specific and unique purpose, which will be detailed in the following paragraphs.

(NV) center in the lattice. Nitrogen atoms have five electrons. In the NV, three of the electrons form covalent bonds with surrounding Carbons. The other two electrons near the vacancy will form a lone pair (Eichhorn 2019). The carbons around the vacancy each have a single electron where the covalent bond used to be. The center carbon oscillates between covalently bonding to the left and right carbon as shown in the diagram below (Haque 2017). This nitrogenvacancy pairing in a diamond is known as a ‘quantum defect,’ which is a physical entity that models a quantum-mechanical system. The quantum defect has special electronic states within the band gap of diamond, allowing transitions between energy levels of the NV to be forced. NV center defects in diamond exist in three charge states: NV-, NV0 and NV+ (Eichhorn, 2019). In the NV0 state, the resonating Carbon bonding and lone pair on the nitrogen creates an ‘NV-axis’ line of symmetry, which induces three energy states in the defect. Inserting another electron (creating the NVstate), creates two pairs of unpaired electrons in the defect (Eichhorn, 2019). The NV0 state is paramagnetic (not magneto-optically active), while NV- state is not. Thus, the NV- charge state yields better results in high-resolution magnetic field sensing and imaging via optically detected magnetic resonance (ODMR) (Eichhorn, 2019). The NV- electronic states are thus used as opposed to NV0. An NV- (NV) center in diamond has three main electronic levels: an excited triplet state, a metastable singlet state, and a ground triplet state. A singlet state (ms = 0 only) occurs when electron spins are paired in opposite (one up, one down) states and the energy levels of the electrons do not split when exposed to a magnetic field. A triplet state (ms = -1, 0, or 1) has three spin combinations – both up, both down, or one up and one down. The ms = 1 and ms = -1 states are degenerate, which means that the states have the same energy level (Haque, 2017).

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Image 2: A nitrogen and vacancy pairing within a diamond lattice Image Source: Produced by Lasonde (author)

NV centers have an electronic spin property which can be manipulated by microwaves. Each electron in the NV center can either spin counterclockwise or clockwise, which corresponds to the +1/2 (spin up) and -1/2 (spin down) spin states (ms) respectively. A resonant magnetic field and microwave pulses across a frequency band of ~3.64 GHz. control the specific state that an NV center can be excited into from the ground energy state. The microwave pulses trigger polarization from the electron to surrounding carbon lattice, allowing manipulation of the electronic state. Once NV centers are polarized, a green laser light (532 nm) can be shone into the NV center (Levine et al. 2019). This stimulates the unpaired electrons from the ground state (spin triplet) to the excited state (spin triplet) a higher energy state. The difference between the ground triplet state and the excited triplet state is referred to as the zero-phonon line. After a few milliseconds, the electrons will return to the ground state and release energy as series of 1.8 eV photons. (The color perceived as red by human eyes.) The variation in photoluminescent intensity is correlated to the resonance and spin to charge conversion (SCC) of the NV centers as manipulated by the green laser (Levine et al. 2019). Depending on the speed of the emitted photons and the microwave pulse sequence, an image sensor can determine the direction of the magnetic moment of the NV center. Experimental goals and setup The general goal of the magnetic and microwave field setup of the experiment is to implement a sequence of pulses to induce excitation states in the NV centers through an antenna, DAQ, and a SPFT RF switch. There is also the creation of inhouse fabrication of a diamond sample holder & an NMR probe. Any commercial materials like the ones below may be swapped out. The overall schematic of this portion of the experiment is as follows:

Image 3: Full experiment schematic Image Source: Produced by Author

Image 4: Magnetic & microwave schematic. Note: To record ODMR spectra, a microwave field and magnetic field must be present. Image Source: Produced by Author

The general goal of this magnetic field is to create a 40 mT magnetic field needed for DNP experiments. This is implemented through a combination of a cylindrical Halbach permanent magnet array and a fringe field (about 1.2 cm from the Halbach magnet array). Placing a Halbach array of strength 170 mT approximately 12 mm away (on the coaxial z axis) from the sample will yield a proper magnetic field of approximately 40 mT.

Microwave Field For this experiment, a microwave field will be generated at an approximate frequency of 2.87 GHz (±0.2). By broadcasting the microwaves from thin copper wires near the sample, ODMR spectra can then be determined by recording the change in fluorescence intensity as the microwave frequency changes. The microwaves excited a process of Landau-Zalner transistions that help to polarize the nuclei for the NMR.

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Image 5 (left): Halbach array within the experiment (3) Image 6 (right): Magnetic field strength vs. distance from the Halbach Array (mm) Image 6 source: Produced by author

Microwave Field: Description and Justification of the static setup The base of the experiment was an optical table (board) which had mountable pieces to ensure accuracy of the setup. Custom linear actuator and Halbach magnetic mounts were designed and created. For our chosen actuator, an 8 cm by 8 cm by 1 cm aluminum rectangle was designed and manufactured to interface the optical mounting table and the manufacturer’s mounting bracket. Similarly, for our chosen Halbach ring, a 7 cm by 0.7 cm by 1 cm aluminum mount was designed and manufactured to mount the magnet to the optical table. The top portion of the mount has a half-cylinder groove cut such that only half of the Halbach ring sits inside the holder. After the mounting and layout of the pieces was implemented, the design of the diamond sample holder must be considered. Design constraints considered include the size of the NMR probe and attachment to the linear actuator. The final design was determined to be a 5 mm wide by 30 mm long piece of ABS plastic. The diamond crystal is directly glued onto the holder. ABS plastic is transparent to microwaves and radio waves in the DNP and NMR experiments, and it will not interfere with the Halbach magnet. Then, we pivot our attention to the programming of the linear actuator. The goal of the actuator in the experiment is to transfer the diamond sample approximately 14mm from the DNP setup (which includes microwaves) into the high magnetic field for readout such that the state of the NV center does not decohere, which means to fall out of a superposition or quantum state. (The collapsing of a qubit mentioned in WINTER/SPRING 2022

the introduction). If the traverse speed of the actuator is 110 mm/s, it will take approximately take 0.13 seconds to move the sample 14 mm. Once in the magnetic field, the sample is coherent on the order of a few minutes. The accompanying board to the L12-XXPT-3 Linear actuator required control parameters of min/max stroke length speed. To program these variables, the board interfaced with a TTL/PWM line connected to the computer through USB. The max stroke length was set to 30 mm and the minimum stroke length was set to 0.5mm. Furthermore, the goal of the actuator is to cover 14 mm in 0.13 seconds. Thus, the traverse speed of the actuator was determined to be 110 mm/s. Finally, the voltage of the actuator was set to 10V. However, the greater the voltage placed on the linear actuator, the faster the actuator will operate. Microwave Field: Communications setup of the device To program the sequential steps required of the experiment to occur at the proper times, a communications system must be built. The main two parts of the communication system include transmitting and receiving data. The flow of data through the system is as follows: 1.The microwave sweep band is set to 3.54e4 GHz & the repetition rate is set to 147 Hz (manual) 2.The data acquisition device is turned on 3.NMR_setup.m is run

Image 7: T/R communications schematic Image Source: Produced by Author

3a. Sets the RF signal and TTL signal HIGH 3b. Laser is turned on 4.Actuator is turned on moves the sample into the proper position

The schematic of the receiver communication system is shown in the diagram above. A signal from the AWG is passed into the limiter, which then is passed into three amplifiers and read out by a picoscope channel.

5.Data is then collected from the AWG and passed into the power amplifier to transmit the signal generated to the RF coil 6.The output of the probe is then passed to the receiver portion of the circuit, which consists of a limiter and a series of amplifiers Image 7 (left middle): Timing diagram of the mw/rf/magnetics Image Source: Produced by Author

Image 8 (right middle): Picture of the limiter and the amplifier (with capacitors and cross diodes) Image Source: Produced by Author

7.The output signal is then passed into the second channel of the picoscope The diagram below summarizes the timing of events based on clock cycles:

The purpose of the limiter in this design is to stabilize generator outputs, reduce amplitude variations, and protect low noise amplifiers and other devices power damage. Additionally, the purpose of each amplifier is to increase the size of the input signal. In experiments, input signals ranging from -70 dBm to -10 dBm will be passed into the system to be analyzed by the oscilloscope. Each amplifier has a pair of capacitors (470 uF and 220 nF ) to prevent noise from entering the system by bypassing it to the ground. Before the chain of amplifiers, there is a pair of cross diodes to ground that prevent power surges from ruining the circuit.

Image 9 (bottom): Transmitter schematic Image Source: Produced by Author

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Image 10 (left): Antenna for the MW source Image 11 (right): Optical subsystem schematic of the DNP/ NMR systems Image 10 & 11 sources: Produced by author

a. Laser Light propagates through the system from a G150-1803 532 Nm Laser is a class IIIB laser system capable of a continuous power output ranging from 50 mW – 150 mw. This laser fires a continuous beam of green light to excite the spin +/- ½ electrons for the DNP experiment. NVs only need to be polarized once every T1e cycle, so a laser power in the order of mW is sufficient. However, the laser power must be better than 1% stable since ODMR is dependent on detecting relatively small (<10%) changes in the fluorescence intensity (Zhang et al. 2018). There are no requirements on the excitation wavelength, linewidth, or mode quality of the laser. Moreover, the laser is cw-mode and requires no synchronization or pulsing infrastructure for this experiment. The laser is controlled by a TTL line that will be hooked up to the Data Acquisition Device (DAQ). The main difference between the pulsed vs. CW laser to consider is the sensitivity of fluctuations required for the experiment. With a pulsed laser, gated high-speed probing is possible, and the setup is less susceptible to certain types of noise. A CW laser is more limited in suppressing noise, and it requires a much more stable power supply (~10%).

First, green photons from a 532 nm laser (I) are emitted into a fiber acousto-optic modulator (II). Then, a 100 MHz sound signal is used to attenuate the electrical signal in a manner such that the AOM will either permit light to pass through or be blocked. The light passed through the free space AOM propagates into a collimator, which is a “device for producing a parallel beam of rays or radiation” (OED). The collimator expands the beam width to allow for parallel optical and magnetic NV center detection. For now, the magnetic portion of the experiment will be ignored. After the collimator has widened the beam, the laser light is passed through a neutral density (ND) filter to attenuate the power level to be a proper level for the CCD and QIS detection. The specified ND filter is composed of a UV fused silica glass substrate and a metallic Inconel coating through a full 270°. The data sheet guarantees a flat spectral response from UV to the mid-IR wavelengths. b. ND Filter + Mirrors The optical density is a linear function of the angle of the ND filter:

Image 12 (left): Optical subsystem schematic of the DNP/NMR systems Image source: Produced by author

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Where OD is the optical density and theta is the angle in degrees. The value of m depends on the OD range of the filter, which in this case is 0-2.0. Thus, m = 0.00741. Furthermore, this formula assumes 0 degrees at the beginning of the coating & 270 degrees at the end of the coating.

The CCD is generally only used when a new diamond sample is mounted or when the sample-lens distance is much larger than the focal length. In this experiment, a commercial photodetector was used to detect the surface of NVs.

The light is then manipulated using a series of filters and mirrors to allow the CCD and QIS to properly detect the surface and emissions properly. The first filter in the filter/mirror component subsection is a dichroic filter “used to selectively pass light of a small range of colors while reflecting other colors.” In this experiment, the laser emits green photons, but the NV center detection picks up on the red photon emission of the diamond. Thus, a dichroic filter which reflects green light but passes red light is required. Once light is passed through the dichroic filter, a mirror is used to alter the direction of light propagation from a position z direction to a positive x direction as specified to the axes above.

d.QIS

The beam is both reflected and passed through another mirror/filter into order to allow parallel detection of the surface and emissions via a CCD and QIS respectively. Finally, both the CCD and QIS has a specific filter & objective lens to prepare the light for proper detection. c.CCD The role of the CCD in the optical setup is to find the diamond’s surface. The CCD can detect white light coming off the diamond surface (and not necessarily emissions from NV centers). The light comes through the objective lens, such that the image of the surface can only be seen at the focal point. Thus, as the sample stage is manually moved toward the NV center, the image remains blurred until the lens reaches the target surface.

The QIS is a single-photon image sensor that measures light packets and generates binary measurements (Fossum, 2016). This allows the QIS to take pictures, or optically read-out, tiny cavities such as NV-centers without much noise. By decreasing the noise in the system, the QIS would immensely improve the scalability of NVcenter qubits. In the 2020 paper described by Misonou, a Basler based CCD camera was utilized due to the group’s previous experience with the device. The Basler ace camera, known as a 'workhorse camera,' is relatively cheap, flexible, high definition, and can run at 100 Hz or up to 3 kHz with a reduced ROI. This image sensor works well with a decent amount of light and is often paired with the QDM for readout. Any image sensors with reasonable specs can be swapped out for the Basler. A table of comparison of the QIS and the Basler ace is detailed in the table below: In the experiment, signal red photons are imaged onto the single-mode fiber and collected by an SPCM, which in this case is the quanta image sensor. The key criteria of an effective SPCM for NV-center readout are high photon detection efficiency, low dark count, and high timing resolution.

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Table 2: : Table comparing the QIS vs other image sensors Image Source: Produced by Lasonde (author)

Both the QIS and SPCM are photon detectors, and thus the two technologies can be interchanged. Typically, a CCD has a large field of view for imaging (or allows for wide spectral range when it's combined with monochromator), while an SPCM is more focused on high quantum efficiency and low dark counts. The QIS model used in this experiment, nicknamed ‘Cupertino’, has a 16.7 Mpixel, 3D-stacked backside illumination with 1.1 μm-pitch pixels. The sensor can achieve 0.19 e- rms array read noise and 0.12 e- rms best single-pixel read noise under room temperature operation. The accurate photon-counting capability enables superior imaging performance under ultra-low-light conditions. The sensor supports programmable analog-to-digital convertor (ADC) resolution from 1-14 bits and video frame rates up to 40 fps with 4096×4096 resolution and 600 mW power consumption The most important parameter to consider when swapping the QIS for the Excelitas SPCMAQRH-16-FC are the quantum efficiency in the 650-800 nm range. The SPCM used in the original experiment has the Q.E of 70% at 650 nm to 800 nm. The lower the QE of an SPCM, the longer it will take to collect photon counts and will compromise the sensitivity of the NV magnetometer. The dark count of the image sensor should also be below < 100 counts/s. The confocal capability of an image sensor is also crucial for single-NV detection.

NV ensemble regimes, which require low light conditions, pair well with CMOS image sensors. SPAD or scanning instruments are particularly effective with ensemble read-out due to their low photon count per pixel. However, most researchers currently have found a need for reading out one to an ensemble of ten defects at a time. Reading out ten individual NVs (one per pixel) is currently more complex than reading out an average of an ensemble of ten NV centers because of the high quantum efficiency and dark count required. In this regard, the QIS sensor is looking much better than the current SPAD technology (Turner). Since the QIS has particularly low read-out noise, single-photon light sensing applications, such as quantum interconnects, may benefit greatly.

"...the QIS will be particularly impactful in experiements... where the exact photon count is critical"

In addition to NV centers, the QIS would help read out trapped ions, trapped cold atoms, and quantum dots as qubits (Turner). The QIS would also be great for scaling the number of photons or qubits read at once compared to SPADs. Since photon counting has historically not been available data, it is unclear exactly how this knowledge could benefit scientists; however, that doesn't mean the applications and benefits do not exist. In particular, the QIS will be particularly impactful in experiments with low-density samples, low light systems, noise-sensitive systems, and systems where the exact photon count is critical. The QIS is worth researching compared to current industry technology, particularly for the specific applications in which the QIS would excel.

The use of the QIS image sensor was determined to be the most beneficial for the experiment after a length analysis. As shown in the table above, the QIS has the smallest pixel size and lowest read noise and power consumption. The QIS can determine the number of photons more precisely than any other sensor, ensuring that a single photon is detected and not a whole stream of photons. WINTER/SPRING 2022

Table 4: Comparison of different performance metrics across image sensors Source: Produced by Author

e.Fiber optics

"To build such a powerful quantum computer, researchers need to design qubits with lower error rates, longer coherence times, lower costs and noncryogenic operating temperatures."

Finally, fiber optics were chosen to be used throughout the system. There are two main advantages of fiber optic cables. First, fiber optics make the laser alignment less susceptible to drift. Additionally, a fiber also acts as a spatial filter, such that putting a laser beam through a fiber cleans it up. The downside of using fiber optics is how long it takes to become accustomed to using them. Beginners typically take a few days to set up their first optical cable, but more advanced students may only take 20 minutes. Using a fiber instead of free space results in in higher strength, increased component reliability, and better production yields. Additionally, in free space, the beam diameter would have to be expanded from a couple millimeters to larger to meet the requirements of the image sensors through a beam expander. Applications of a quantum sensing NMR/DNP From this point forward, the entirety of the device built in this paper will be called a quantum diamond spectrometer (QDS). There are many advantages of using a NV center QDS than comparable technology on the market. First, the QDS has does not require narrowline width lasers for initialization and readout, meaning that a commercial green laser will work perfectly. Additionally, NV centers in diamond compute in ambient conditions (temperature & pressure), and thus do not require a cryogenic component as many other types of qubits do. Diamonds can be ethically grown, and the NV centers within them can also be ethically crated. They are naturally chemically inert, and thus are also biocompatible (Schloss, 2018). There are many applications of the QDS in a range of fields for both ensemble and single NV center read outs. Ensemble readout is best observed in experiments with high photons levels and low contrast levels are best used in where ensembles are utilized. For example, quantum sensing of a field requires an ensemble

of NVs to ensure a reasonable readout time (Hopper et al., 2018). On the other hand, single NV center readout is best observed in experiments with low light and high contrast conditions (which is excellent for the QIS either way) (Hopper et al., 2018). Diamonds with NV defects can be embedded within a living cell for magnetometry; electrometry; and thermometry conditions, potentially allowing for magnetometry in a single cell as well as electrometry and thermometry” (Abe, 2018). Recent biological examples of NV center sensing include ODMR detection of single-neuron action potentials, single protein detection, and NMR investigations of meteorite composition and paleomagnetism (Scholss, 2018). Conclusion Nuclear magnetic resonance (NMR) spectroscopy techniques are relatively insensitive compared other popular microscopy methods. H0wever, a spectrometer based on the fluorescent quantum defects in diamond, such as the colored NV centers in this paper, permit probing of sizes down to singular proteins and protons (Suter et al., 2017). The low sensitivity of magnetic resonance is an insurmountable barrier for technologies with biological application, and a quantum diamond spectrometer combined with NMR techniques may provide unprecedented information about molecular structure and dynamics. However, the present performance of quantum NV sensors remains far from their theoretical limits, and more work in the field is required (Schloss, 2018). Reading out the state of a single NV center requires low light and high contrast conditions (Hopper et al., 2018) is, for the first time, analyzed with the QIS. Fields dealing with microscopic organisms, such as biology, have low light conditions and need high contrast imaging.

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References: Abe, E., & Sasaki, K. (2018). Tutorial: Magnetic resonance with nitrogen-vacancy centers in diamond—microwave engineering, materials science, and magnetometry. Journal of Applied Physics, 123(16), 161101. https://doi. org/10.1063/1.5011231 Biamonte, Jacob et al. 2017. “Quantum Machine Learning.” Nature 549(7671): 195–202. Britannica, T. Editors of Encyclopaedia (2019, December 26). Moore’s law. Encyclopedia Britannica. https://www.britannica.com/ technology/Moores-law Bucher, D. B., Aude Craik, D. P. L., Backlund, M. P., Turner, M. J., Ben Dor, O., Glenn, D. R., & Walsworth, R. L. (2019). Quantum diamond spectrometer for nanoscale NMR and ESR spectroscopy. Nature Protocols, 14(9), 2707– 2747. https://doi.org/10.1038/s41596-019-0201-3 Deng, W. (n.d.). Deep Sub-Electron Read Noise in Image Sensors Using a Multi-Gate SourceFollower (invited). 6. Eichhorn, T. R., McLellan, C. A., & Bleszynski Jayich, A. C. (2019). Optimizing the formation of depthconfined nitrogen vacancy center spin ensembles in diamond for quantum sensing. Phys. Rev. Materials, 3(11), 113802. https://doi. org/10.1103/PhysRevMaterials.3.113802 Fossum, E.R.; Ma, J.; Masoodian, S.; Anzagira, L.; Zizza, R. The Quanta Image Sensor: Every Photon Counts. Sensors 2016, 16, 1260. https://doi. org/10.3390/s16081260 Ghose, S. (2018, Nov). A beginner's guide to quantum computing [Video]. TED Conferences. https://www.ted.com/talks/shohini_ ghose_a_beginner_s_guide_to_quantum_ computing?language=en Haque, Ariful & Sumaiya, Sharaf. (2017). An Overview on the Formation and Processing of NitrogenVacancy Photonic Centers in Diamond by Ion Implantation. Journal of Manufacturing and

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Materials Processing. 1. 6. 10.3390/ jmmp1010006. Hopper, D., Shulevitz, H., & Bassett, L. (2018). Spin Readout Techniques of the NitrogenVacancy Center in Diamond. Micromachines, 9(9), 437. https://doi. org/10.3390/mi9090437 Langione, M. (2020, Nov). The promise of quantum computers [Video]. TED Conferences. https://www.ted.com/talks/matt_langione_the_ promise_of_quantum_computers?language=en Levine, E., Turner, M., Kehayias, P., Hart, C., Langellier, N., Trubko, R., Glenn, D., Fu, R. & Walsworth, R. (2019). Principles and techniques of the quantum diamond microscope. Nanophotonics, 8(11), 1945-1973. https://doi. org/10.1515/nanoph-2019-0209 Liu Gang-Qin, Pan Xin-Yu. Quantum information processing with nitrogen–vacancy centers in diamond. Chinese Physics B, 2018, 27(2): 020304 Ma, J., & Chan, S. (n.d.). Review of Quanta Image Sensors for Ultra-Low-Light Imaging. 16. Ma, J., Zhang, D., Elgendy, O. A., & Masoodian, S. (2021). A 0.19e- rms Read Noise 16.7Mpixel Stacked Quanta Image Sensor With 1.1 μmPitch Backside Illuminated Pixels. IEEE Electron Device Letters, 42(6), 891–894. https://doi. org/10.1109/LED.2021.3072842 Misonou, D., Sasaki, K., Ishizu, S., Monnai, Y., Itoh, K. M., & Abe, E. (2020). Construction and operation of a tabletop system for nanoscale magnetometry with single nitrogen-vacancy centers in diamond. AIP Advances, 10(2), 025206. https://doi.org/10.1063/1.5128716 Nielsen, M.A. & Chuang, I.L., 2011. Quantum Computation and Quantum Information: 10th Anniversary Edition, Cambridge University Press. Schloss, J. M. (2018). Optimizing NitrogenVacancy Diamond Magnetic Sensors and Imagers for Broadband Sensitivity. Physics Department, Massachusetts Institute of Technology. https://www.hertzfoundation.org/ wp-content/uploads/2020/10/Jenny-SchlossThesis-2019.pdf 52

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Supermassive Pockets in the Cosmic Neighborhood: Searching for Active Galactic Nuclei BY RUJUTA PUROHIT '24

Cover Image: The spiral galaxy NGC 3393 hosts an obscured active galactic nucleus at its center. In the sky, NGC 3393 is located in the constellation of Hydra and is about 56 mega parsecs away from us. The galaxy is characterized as a Seyfert galaxy and actually has two supermassive black holes at its core. Image Source: Wikimedia Commons

Introduction An active galactic nucleus (AGN) is the physical manifestation of gas accreting onto a supermassive black hole (SMBH). SMBHs lie at the centers of most, if not all, large spiral and elliptical galaxies and are believed to be responsible for powering the galaxy. Sagittarius A* (Sgr A*) is the SMBH at the center of the Milky Way Galaxy. Although not producing large amounts of radiation (thus, often called dormant) today, the SMBH is truly giant, with a mass of 4.3 million times that of the Sun (Abuter, 2019). In 2020, Andrea Ghez of the University of California, Los Angeles, and Reinhard Genzel of the Max Planck Institute received the Nobel Prize in Physics for proving that Sgr A* indeed hosts a supermassive black hole at its center.

galaxies. However, a small fraction is known to emit significant amounts of light and energy. This is due to an interesting combination of many factors, including the masses of the black holes and their host galaxy, the rate of star formation in the galaxy, and the amount of dust and gas present in the vicinity of the SMBH. These black holes then outshine the entire host galaxy across the electromagnetic spectrum, resulting in an active galactic nucleus (AGN). AGN are powered by the release of gravitational energy from all of the matter that is accreted onto the SMBHs. The large energy released by an AGN can effectively influence its surrounding environment, eventually impacting the whole nuclear region, as well as the star formation and the evolution of the galaxy as a whole (Masini et al., 2020).

SMBHs have masses on the order of millions of times that of the Sun and are very strong sources of radiation. Their strong gravitational force means that no physical matter can escape their event horizons, including light. Event horizons are the last optically visible regions of the black holes themselves; they are large, compact discs of gas and dust surrounding the center of a black hole. The event horizon is what could theoretically be “seen” when looking at a black hole.

Physical Characteristics of AGN

At any given time, the majority of SMBHs are mostly dormant at the centers of their host 54

The Eddington luminosity (also called the Eddington limit) is the maximum luminosity an object can ever have such that the inward gravitational force is balanced by the outward radiation force. If the luminosity exceeds the Eddington limit, the radiation pressure drives jets, which are high-energy beams of matter travelling out of the center of the black hole at relativistic speeds (speeds very close to that of light) (Bassani & Sembay, 1983). They are extremely energetic and thus very bright. The jets DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Image 1: An artist’s illustration of relativistic jets being ejected from the core of a supermassive black hole of an active galaxy. The jets are often thousands of parsecs long and are very energetic. Image Source: Wikimedia Commons

have lengths that range from anywhere between a few thousand parsecs to millions of parsecs (Kundt, 2015). It is unknown what exactly causes the jets, but it is believed that they result from electron-positron interactions at high velocities (Georganopoulos et al., 2005). Figure 1 shows an artist’s illustration of a spiral galaxy with jets from a supermassive black hole. The accretion of gas around the SMBH produces an optically thick disk of material, called the accretion disk. The accretion disk emits thermally because of the viscosity within the disk. The gas within the accretion disk has a wide range of temperatures, and the emission is consequently produced over a broad wavelength range (Gurzadyan, 1979). AGN are interesting astronomical phenomena since they are regions and not objects themselves. The physical model of an AGN thus hopes to describe the many features of the black hole and the galaxy. There are a number of theories that seek to model the physical structure of AGN. The currently accepted model is called the Unified Model of the AGN and explains the structure by dividing the AGN region into 6 main regions: the black hole, the accretion disk, the torus, the narrow-line region, the broad-line region, and the outflow (jets) (Hickox & Alexander, 2018). Jets and accretion disks are described above but will be discussed again in context of the model. The accretion disk is surrounded by a geometrically and optically thick dusty and molecular torus, often referred to as the dusty WINTER/SPRING 2022

torus. It is thought to be within the gravitational influence of the SMBH. The torus is composed of the cooler, outer regions of the accretion disk where molecules and dust grains can form (Hickox & Alexander, 2018). The torus is broadly symmetric around the accretion flow axis. The narrow-line region (NLR) and the broadline region (BLR) are defined on the basis of the velocity width of the emission lines obtained for the radiation of the AGN. The BLR has gases with a broader distribution of emission line velocities than the NLR. The typical range of velocity widths for the gas in the BLR is about 1,000 – 10,000 km/s while that for the NLR it is about 100 – 500 km/s (Padovani et al., 2017). The different velocity widths of the BLR and NLR result from the relative location of the gas with respect to the SMBH. The gas in the BLR lies within the gravitational influence of the SMBH and thus resides close to the accretion disk. By comparison, the gas in the NLR lies under the gravitational influence of the host galaxy and is produced on larger scales. The bulk of NLR emission generally originates within the central kiloparsecs, but for some systems the emission from the gas ionized by the AGN is observed on the scale of the entire galaxy, out to ≈ 10 kilo parsecs (Hainline et al., 2014). The radiation from the AGN impinges on the interstellar medium in space, exciting the gas by ionization and transferring mechanical energy to the gas through radiation pressure and disk winds. 55

Image 2: A sketch of the main AGN structures under the Unified Model of the AGN. The sketch shows the SMBH, the accretion disk, the torus, the BLR, the NLR, and the outflow. Image Source: (Hickox & Alexander, 2018)

This appears in the form of cones extending from the nucleus (Durre & Mould, 2018). Figure 2 shows a sketch of the main AGN structures seen along the equatorial and polar directions. The regions are colored according to their contributions to the SED in Figure 3 that follows. Searching for AGN A term useful when searching for AGN is the “bolometric luminosity.” The bolometric luminosity of an AGN corresponds to the total luminosity produced by the accretion disk. It is a measure of the luminosity produced across the entire electromagnetic spectrum. Temperatures are also useful in determining what physical properties are needed to search for AGN and what regions of the EM spectrum they can be assigned to. For the accretion disk of a typical AGN, the range of gas temperatures is likely to be T about 104 K, and therefore the majority of the emission from the accretion disk will be at detected between 30 and 300 nm (i.e., at UV–optical wavelengths) (Shields, 1999).

A plot of the emission fluxes against the different wavelengths is called the spectral energy distribution (SED). SEDs are relatively unique for different astronomical objects as fluxes are representative of an object’s mass and size. The SED of an AGN accretion disk is distinct from the SEDs of other astrophysical sources and is comparatively easy to identify. A SED is thus one of the first ways to identify an AGN. Figure 3 is the SED of an AGN with different wavelength ranges indicated for different wavelengths. Different methods are employed in different bands to identify the AGN sources. The various wavelength regimes provide different windows on AGN physics. Namely, the infrared (IR) band is mostly sensitive to dust, the optical/ ultraviolet (UV) band is related to emission from the accretion disk, and the X-ray band traces the emission of a corona 𝛾-ray. High flux density radio samples, on the other hand, preferentially select AGN emitting strong non-thermal jetrelated radiation (Padovani, 2017).

Image 3: : The spectral energy distribution of an AGN. The horizontal axes show the wavelength in two different scales and the vertical axis shows the luminosity of the AGN over those wavelengths. Image Source: (Hickox & Alexander, 2018)

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Figure 4: A schematic breakdown of the physical regions of an AGN and their classifications. Image Source: NASA Open Source

There are two broad categories into which AGN are classified: radio-quiet AGN and radio-loud AGN. Like the name suggests, radio loud AGN have emissions from jets and the jets’ lobes. The emissions of radio quiet AGN can be neglected since they are not strong enough to always be detected. Within these two categories, there are lots of types of AGN (Komberg, 1992). Radio-quiet AGN include low-ionization nuclear emission-line regions (LINERs), Seyfert galaxies, and radio-quiet quasars. LINERs have weak emissions and are thought of as “maybe AGN”. They are hard to detect and classify with certainty, since the weak nuclear emission isn’t supported by other emission lines (Belfiore, 2016). Radio galaxies are AGN that are very luminous at radio wavelengths. The observed structure in radio emission is determined by the interaction between the jets from the galaxies and the gas/ dust. Most radio loud AGN are ellipticals (Kraft, 2003). Seyfert galaxies are detected using their optical range nuclear continuum emission. These AGN have very high surface brightness and reveal high-ionization emission lines. As a result, their ionization cones are very large and distinct. The host galaxies are easily detectable using the emission lines. These galaxies have bolometric luminosities on the order of 1042 – 1045 ergs/s (Hickox & Alexander, 2018). Seyfert galaxies show an excess of radiation in the far infrared region of the EM spectrum. At some wavelengths, this excess radiation is variable, and it is thus theorized that the excess variable radiation actually comes from the compact AGN inside the galaxy.

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Quasars— “quasi-stellar radio-source objects”— are more luminous Seyfert galaxies. Quasars produce large amounts of radiation and are thought to be one of the most luminous objects in the entire Universe; a quasar alone could potentially emit energy that is a thousand times more than that of the entire Milky Way Galaxy (Wu, 2015). Quasars have bolometric luminosities greater than 1045 ergs/s (Hickox & Alexander, 2018). Since they are extremely luminous and powerful, it is believed that they were more common in the early Universe. Energy production would slow down and come to a halt later in the lifetime of an active galaxy. This is used to support the thesis that most large galaxies go through an active phase (Tiziana et al., 2005). For example, the Milky Way is no longer an active galaxy, but the black hole in its center might have once been an AGN.

"Understanding the nature of AGN better is intricately linked to our understanding of the conditions of the early universe..."

Understanding the nature of AGN better is intricately linked to our understanding of the conditions of the early universe, black-hole accretion models, and the theories surrounding the Big Bang. Furthermore, since these were more common in the early Universe, measuring quasar redshift could help create better models for the expansion of the Universe. A large redshift would mean that the quasar is far away from the Earth – if a measured redshift is due to the expansion, then such objects’ high luminosity could only be explained by high initial masses. Such conditions would only be possible if they were formed in the early Universe. Following this cyclic reasoning, quasars can only be as luminous and powerful as they are now if there were formed at the center of and right at the beginning of the Universe where they could accrete more mass and then move father away due to the expansion (Grupen, 2005). In contrast, Seyfert galaxies are closer to the Earth as compared to quasars and are believed to have formed later in the evolution of the Universe. 57

Image 5: NGC 1448, a galaxy with an obscured AGN, is seen in this image combining data from the Carnegie-Irvine Galaxy Survey in the optical range and NuSTAR in the X-ray range. Image Source: NASA Open Source

sources of high-energy gamma ray photons. The jets extend up to 100 kiloparsecs from the central black hole (Kellermann, 1992). The observed emission from a blazar is greatly enhanced by relativistic effects in the jet, a process called relativistic beaming. The relativistic jets characteristic of blazars are such that they are oriented close to the line of sight of the observer from the Earth. The accretion of gas onto a SMBH is an exceptionally efficient process. About 5% to 42% of the mass is ultimately converted into emission, depending on the spin of the SMBH (Shapiro & Teukolsky 1983), and therefore large luminosities can be produced for a modest amount of accretion, allowing for luminous AGN to be detected out to high redshifts. Most AGN are detected by searching for such redshifts over different luminosity values. Figure 4 shows a schematic of the physical regions of an AGN and how they get classified between the different types depending on the physical characteristics that are detected. Obscured Active Galactic Nuclei Although they are enormous and have great gravitational influences, active galactic nuclei cannot always be easily detected. The huge radiative power of most AGN cannot be seen directly, since the accretion is hidden behind gas and dust that absorb many of the characteristic observational signatures (Hickox & Alexander, 2018). Obscuration is defined as anything that absorbs emission and/or scatters a large fraction of it away from the line of sight of the observer. In astrophysical sources, the obscuring medium is typically composed of dust and/or gas. Broadly, 58

dust particles are solid state structures which are typically carbonaceous grains and amorphous silicate grains, in UV-IR wavelengths. Gas molecules are just gaseous states particles, ranging from fully ionized gas including electrons and protons, to neutral gas and molecular compounds. For many of, and probably the majority of, obscured AGN, the obscuration occurs in the close vicinity of the accretion disk and lies within the gravitational influence of the SMBH (Hickox & Alexander, 2018). The impact of the obscuring material on the detection of the accretion disk emission is directly dependent on the wavelength used for observation. This is called the optical depth. It is a measure of absorptivity up to a specific depth (or length of distance) across space. A small optical depth means that a small fraction of the emission will be absorbed, whereas a large optical depth means that a large fraction of the emission will be absorbed (Hickox & Alexander, 2018). The optical depth is one of the most important factors in determining whether an AGN is obscured or not. In an AGN, the observed X-ray emission is absorbed by material in the surrounding torus. Any obscuration also always occurs in close vicinity of the e accretion disk and lies within the gravitational influence of the SMBH (Hickox & Alexander, 2018). The radiation is then re-emitted at mid-infrared wavelengths by the torus. Thus, the X-ray and mid-infrared luminosities of AGN are related through a defined and predictable relationship. If an AGN has a mid-IR luminosity that is greater than the X-ray luminosity, then the AGN is said to be obscured (Lambrides et al., 2020). These AGN are often found in the faintest group of observations which makes them even harder to detect. Galaxy NGC 1448, shown in Figure 5, hosts an obscured AGN at its center. DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

The classical definition of an obscured AGN is the absence of emission from the BLR in the optical waveband (Antonucci, 1993). This corresponds to a typical obscuring screen or extinction from dust. For typical dust-to-gas ratios, this corresponds to an equivalent absorbing column density from gas measured in the X-ray band of NH > 1022 cm−2. The NLR can be detected in both obscured and unobscured AGN, whereas the BLR is expected to be detected only in unobscured AGN. Because of its extent and its positioning, the emission from the NLR is generally not obscured (Hickox & Alexander, 2018). Certain obscured AGN are called “Comptonthick” AGN. Compton-thick active galactic nuclei (CTAGN) are defined as AGN that are obscured along the line-of-sight by absorbing gas with a column density of NH ≳ 1024. The study of Compton-thick AGN is crucial and will enlarge our current database for obscured AGN. Observational evidence suggests that a large fraction of AGN in the local universe are obscured by Compton thick gas (Matt et al., 2000). The absorbed luminosity eventually will be reemitted in the far-infrared (far-IR) by the accretion disk makes. This makes Comptonthick sources potential contributors to the long wavelength radiation emitted by some AGN. Finally, accretion in the Compton-thick AGN may contribute to the local black hole mass density and help create better models for the formation of black holes. The search for Compton-thick AGN has been limited to the relatively bright fluxes accessible to the high energy detectors. Careful analysis of X-ray observations can help find such sources, with Mrk 462 being one of the very few Comptonthick obscured AGN to be detected in a dwarf galaxy. Recent research has focused on identifying and studying obscured AGN, especially those in low mass galaxies since their numbers are poorly defined. It is believed that this will place time and mass constraints on the evolution of galaxies and the formation of black holes in these galaxies (Parker & Hickox, 2021). Conclusion Supermassive black holes are found at the centers of most massive galaxies and are thought to be their sources of power. The accretion of gas onto such a black hole is called an active galactic nucleus (AGN) that emits radiation over many different wavelengths.

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The Unified Model of the AGN describes various regions of the AGN like the accretion disk, the torus, the outflow (jets), the narrow-line region, and the broad-line region. These physical regions and how they are detected are used to classify AGN. There are two main types of AGN: radio-quiet and radio-loud. These have further subtypes with unique characteristics and offer information about the formation and evolution of the Universe. The majority of the AGN population is obscured by the dust and gas surrounding it. Therefore, the construction of a complete census of AGN activity requires the identification of both obscured and unobscured sources. A complete census of AGN activity is required to reliably measure the cosmological buildup of SMBHs and to place fundamental constraints on the efficiency of SMBH growth (Hickox & Alexander, 2018). Such a census would also prove helpful in analyzing the influence SMBHs have on powering the host galaxy. The occupational fraction of lower mass black holes in dwarf galaxies is poorly constrained; searching for such black holes requires greater spatial resolution than is afforded by most intermediate mass black holes. It is believed that detecting more obscured AGN in general and more obscured dwarf AGN will greatly add to current theories on galaxy evolution and black hole formation.

"...studying obscured AGN...will place time and mass constraints on the evolution of galaxies and the formation of black holes in these galaxies..."

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Durré, M., & Mould, J. (2018). “The AGN Ionization Cones of NGC 5728. I. Excitation and Nuclear Structure”. The Astrophysical Journal, 867(2), 149. Georganopoulos, M.; Kazanas, D.; Perlman, E.; Stecker, F. W. (2005). "Bulk Comptonization of the Cosmic Microwave Background by Extragalactic Jets as a Probe of Their Matter Content". The Astrophysical Journal. 625 (2): 656–666. doi:10.1086/429558 Grupen, Claus; Cowan, Glen (2005). “Astroparticle Physics”. Springer. pp. 11–12. ISBN 978-3-540-25312-9. Gurzadyan, V. G.; Ozernoy, L. M. (1979). "Accretion on massive black holes in galactic nuclei". Nature. 280 (5719): 214–215. doi. org10.1038/280214a0 Hainline, K. N., Hickox, R. C., Carroll, C. M., Myers, A. D., DiPompeo, M. A., & Trouille, L. (2014). “A spectroscopic survey of WISE-selected obscured quasars with the Southern African Large Telescope”. The Astrophysical Journal, 795(2), 124. Hickox, R. C., & Alexander, D. M. (2018). “Obscured active galactic nuclei”. Annual Review of Astronomy and Astrophysics, 56, 625-671. Kellermann, Kenneth (1992). "Variability of Blazars". Science. 258 (5079): 145–146. doi:10.1126/science.258.5079.145-a Komberg, B. V. (1992). "Quasars and Active Galactic Nuclei". In Kardashev, N. S. (ed.). Astrophysics on the Threshold of the 21st Century. Taylor & Francis. p. 253 Kundt, W. (2014). “A Uniform Description of All the Astrophysical Jets”. Proceedings of Frontier Research in Astrophysics (FRAWS 2014), 25, 1-9.

Alexander, D. M., Assef, R. J., ... & Murray, S. S. (2020). “The Chandra Deep Wide-field Survey: a new Chandra legacy survey in the Boötes field. I. X-ray point source catalog, number counts, and multiwavelength counterparts.” The Astrophysical Journal Supplement Series, 251(1), 2. Matt, G., Fabian, A. C., Guainazzi, M., Iwasawa, K., Bassani, L., & Malaguti, G. (2000). “The X-ray spectra of Compton-thick Seyfert 2 galaxies as seen by BeppoSAX”. Monthly Notices of the Royal Astronomical Society, 318(1), 173-179. Padovani, P., Alexander, D. M., Assef, R. J., De Marco, B., Giommi, P., Hickox, R. C., ... & Salvato, M. (2017). “Active galactic nuclei: what’s in a name?” The Astronomy and Astrophysics Review, 25(1), 1-91. Parker, J., and Hickox, Ryan C. (2021) “X-ray observations of candidate active black holes in dwarf galaxies with the Chandra X-ray Observatory”. The Astrophysical Journal Shapiro, S. L., & Teukolsky, S. A. (1983). “BookReview-Black-Holes White Dwarfs and Neutron Stars”. Journal of the British Astronomical Association, 93, 276. Shields, G. A. (1999). "A Brief History of Active Galactic Nuclei". Publications of the Astronomical Society of the Pacific. 111 (760): 661. doi:10.1086/316378 Tiziana Di Matteo; et al. (2005). "Energy input from quasars regulates the growth and activity of black holes and their host galaxies". Nature. 433 (7026): 604–607. doi:10.1038/nature03335. Wu, Xue-Bing; et al. (2015). "An ultraluminous quasar with a twelve-billion-solar-mass black hole at redshift 6.30". Nature. 518 (7540): 512– 515. doi:10.1038/nature14241.

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Passive Sensing to Prevent Mental Health Issues during the COVID-19 Pandemic BY STEPHEN ADJEI '25 Cover Image: Passive data sensing tools can measure behavior in individuals through the real-time collection of personal data Image Source: Pixabay

Introduction Smart devices are now helping our healthcare system address one of the most significant challenges currently plaguing psychiatry: the difficulty of accurately labeling disease phenotypes (Torous et al., 2016). Recent developments in smart devices and wearable technologies such as smartphones allow for realtime data collection, effectively transforming smart devices into health records. Today, the healthcare system can utilize data collected from these devices to provide personalized diagnostics and proper preventive treatment. (Torous et al., 2016). Critically, this technology can enable health professionals to aid children and adolescents struggling with mental health issues during the pandemic by identifying early indicators of worsening mental health (de Figueredo et al., 2021). This report will address both the benefits and issues associated with passive data sensing and defend an argument for its implementation. This article will outline how this technology has helped youth during the pandemic and discuss studies that demonstrate its effectiveness. Lastly, this article will address ethical issues and discuss

measures the government and the healthcare industry can take to address concerns. Passive Data Sensing Passive Data Sensing (PDS) is the indirect acquisition of data about a person's or group's activity at a specific location in real-time. Passive data sensing tools can measure behavior in individuals through the real-time collection of personal data, which is referred to as digital phenotyping (Martinez-Martin et al., 2021). Digital phenotyping is essential to healthcare. The analysis of sleep patterns, movement, social media activity, and more can predict relapses in schizophrenia, depression, and mania, among many other mental illnesses. The concept originated from research in the computer science field regarding 'contextaware' computing. Context-aware devices monitor changes within the environment, such as location changes, lighting, network connectivity, and noise level (Schilit et al., 1994). These devices interact with their primary users and other context-aware computers within a specified range and vicinity (Schilit et al., 1994). DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Image 1: Smartphones, the optimum context-aware device for PDS, contain many sensors and software services that help researchers collect data about users' activity, location, and behavioral patterns.. Image Source: Pixabay

Context-aware devices are beneficial because they collect, analyze, correlate, and disaggregate data for third parties. Before using passive data sensing, researchers and psychologists typically assessed depressive symptom severity by administering questionnaires to patients. These questionnaires are distributed daily to individuals suffering from depression to allow them to self-assess their depressive symptoms. One of the most common self-assessments is the Patient Health Questionnaire (PHQ). There are two major PHQ assessments used in research: PHQ-8 and PHQ-9. PHQ-8 helps assess the depression level of a large group of people by determining how often specific depressive symptoms are scored highly among members of that group (Dhingra et al., 2011). The PHQ-9 is similarly used to assess depression but includes one question to ascertain suicidal tendencies. Questionnaires like PHQs, however, can become tedious to administer daily. Moreover, those administering the surveys cannot be sure that patients will complete the survey with objectivity. On the other hand, PDS allows for data collection without any effort or input from patients (Cornet et al., 2018). In short, PDS reduces the burden of data collection in medical research and provides more accurate and relevant input (Cornet et al., 2018). In the 2010s, medical researchers utilized smartphones to conduct studies on the clinical applications of passive data collection (Torous et al., 2016). A 2015 report from the International Business Times states that, at the time, there were more smartphones in use than there were people on earth, with 64% of US adults and 85% of US adolescents, ages 18-25, owning smartphones (Torous et al., 2016). Smartphones, WINTER/SPRING 2022

the optimum context-aware device for PDS, contain many sensors and software services that help researchers collect data about users' activity, location, and behavioral patterns. Today, researchers use a wide variety of sources to collect data in this field. A user's calling, texting, and social media activity, for example, can be utilized to capture specific characteristics of the user's social and mental health. This information can also be used to establish correlations between mental status and expressed needs (Cornet et al., 2018). Machine Learning Paired with Passive Data Sensing The use of machine learning models, unique algorithms designed to analyze large data sets, in PDS studies has improved the ability to create prognoses for users (Jacobson et al., 2021). In 2014, Dartmouth's Rui Wang and a team of researchers assessed the effects of daily and weekly workload on the consequential stress levels and behaviors of 48 Dartmouth undergraduates through a smartphone app and machine learning models. To assess changes in sleep, activity, mood, and sociability, the team developed an app called StudentLife (Rui et al., 2014). StudentLife collects data from sensors contained in Android smartphones, including light sensors and the phone's accelerometer. Researchers also used mobile software like the Google location service and usage data services like Samsung Digital Wellbeing. Machine learning was instrumental in the StudentLife team’s ability to determine sleep patterns. The team implemented a method developed in 2013 called the Best Effort Sleep Model. This algorithm predicted sleep duration using smartphone usage patterns such as the length of smartphone usage, light sensors to detect prolonged instances of darkness, and 62

Image 2: The use of Machine learning models, unique algorithms designed to analyze large data sets, in PDS studies has improved the ability to create prognoses for users (Jacobson et al., 2021) Image Source: Pixabay

"Several studies suggest that social isolation increases the risk of developing depression and age-related health problems in adulthood..."

the microphone to detect long periods of conversation. They then aggregated data from these sources to determine students' need for counseling and support. Although machine learning algorithms expedite the data collection process, its accuracy has been disputed. A team of psychologists and computer scientists from Dartmouth led by Professor Nick Jacobson utilized passive sensing data collected over 18 years to predict Generalized Anxiety Disorder and Personality disorder and their model yielded predictions with 68.7% accuracy (Jacobson et al., 2021). A team of researchers from Singapore experienced similar problems. They used a system called StressMon to collect activity data from 108 students via Wi-Fi. This system was created as a possible "detection solution" that utilized non-intrusive methods to identify highly stressed and depressed individuals in work settings (Camellia et al., 2019). In a two-year-long study, the team conducted three longitudinal studies with different groups of students, in which stress and depression questionnaires (PSS-4 and PHQ-4) were administered to participants every three days. The results, however, were lackluster; their machine learning models could not surpass an Area Under the Curve (AUC) value of 0.67, meaning that the model successfully predicted students as stressed only around 67% of the time (Camellia et al., 2019). Researchers are now reflecting on how the data collection process may have influenced their findings. Dartmouth researcher Jacobson and his team captured data in three phases over a 17 to 18-year interval and now find that gaps between their collection phases may have led to more subtle changes in depressive symptoms (Jacobson et al., 2021). Perhaps improving

continuous data collection processes, rather than altering currently used machine learning models will help fine-tune the results. The COVID-19 Pandemic and Mental Health Disruptions in social activities and increasingly stress-inducing conditions contribute to psychopathology development in young children (de Figueredo et al., 2021). Several studies suggest that social isolation increases the risk of developing depression and age-related health problems in adulthood and negatively affects dieting patterns (de Figueredo et al., 2021). There are many well-established correlations between social isolation and mental health problems. In 2009, a team of UK researchers studied the correlation between adverse childhood psychosocial experiences, such as social isolation and age-related diseases. The team found that socially isolated children were more likely to become depressed. Similar correlations were also discovered in maltreated and socioeconomically disadvantaged children: the UK researchers found that 32 year old individuals with more severe adverse childhood experiences may struggle with 59-73% more agerelated disease risks than individuals with less severe experiences (Danese et al., 2009). The team also found that predicting age-related health complications using childhood experience was more accurate than using smoking history, physical inactivity, and poor dieting at 32 years old (Danese et al., 2009). Children who have experienced socioeconomic disadvantages and maltreatment may be more at risk of developing depression or other mental health problems in adulthood (Danese et al., 2009). DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Image 3: Several studies suggest that social isolation increases the risk of developing depression and age-related health problems in adulthood and negatively affects dieting patterns (de Figueredo et al., 2021). Image Source: Pixabay

The pandemic offers opportunities to expand passive data sensing, alongside machine learning and statistical learning models, to help detect early signs of mental health issues in children and adolescents. These data collection and analysis methods have already been used in studies conducted shortly before the pandemic and have proven benefits (Huckins et al., 2020). The StudentLife study, for example, was conducted during Dartmouth’s first academic term impacted by the pandemic – the 2020 Winter Term (January 4th to March 13th). Beginning February, students' daily lives were disrupted by many unexpected changes, including requests to social distance, vaccinate, mask up, and leave their campus dorms (Huckins et al., 2020). On February 4th, students returning to Dartmouth from China were required to isolate for 14 days. On March 11th, college-sponsored athletic competitions were canceled after the World Health Organization declared COVID-19 a pandemic. Moreover, on March 17th Dartmouth terminated all inperson, on-campus options to attend classes from March 28th to June 3rd (Huckins et al., 2020). To assess the impact these changes had on undergraduate students" mental the team conducted a 10-week long-term study. The app uploaded anonymized data from smartphone sensors such as the GPS, lock/unlock status, and the accelerometer to a server and monitored behavior, sleep, and social activity changes in daily and weekly intervals (Huckins et al., 2020). The scientists found noticeable differences in behavior and mental health towards the end of the Dartmouth 2020 winter term - February 15th to March 25th (Huckins et al., 2020). Measurements of student inactivity increased, WINTER/SPRING 2022

and self-reported anxiety/depression symptoms spiked during the last week of the term - March 8th to March 13th . The team also discovered that sedentary time, anxiety, and depression symptoms increased from February to March (Huckins et al., 2020). As a result, the team informed: "public health officials and individual citizens to raise public awareness about the benefits of aerobic exercise and unplugging from technology (moderating phone usage)." These activities have been "shown to have positive effects on alleviating anxiety and depression" (Huckins et al., 2020). Ethics of Passive Sensing

"While passive data collection requies consensual agreement, considerable measures must be taken to address patient privacy, third-party data acquisition, and usage"

While passive data collection requires consensual agreement, considerable measures must be taken to address patient privacy, thirdparty data acquisition, and usage. The healthcare sector requires more clearly stated regulations before utilizing such data to inform decisionmaking and patient services (Martinez-Martin et al., 2021). When data collection takes place outside the healthcare sector and instead on consumer devices, digital phenotyping could capture health information outside the Health Information Portability and Accountability Act (HIPAA) (Martinez-Martin et al., 2021). HIPAA specifies that data containing personal "identifiers" should only be shared with third parties when used for health-related operations like treatment. However, this enables deidentified data, where data such as names and ages are removed, to be shared with third parties without restriction. With many nonhealthcare companies aggregating patient data, companies or outside parties could use data to link information to individuals (Martinez64

Image 4: HIPAA specifies that data containing personal "identifiers" should only be shared with third parties when used for health-related operations like treatment. Image Source: Pixabay

"...clear communication to patients and users about the risks and benefits of passive data collection was deemed essential (MartinezMartin et al., 2021)."

Martin et al., 2021). For instance, a user's IP address could be an identifier to third parties. Moreover, current regulations in other countries, such as the European Union's General Data Protection Regulation Act, do not address or protect individuals from companies aggregating health-related information, enabling companies to "draw health inferences from personal data" (Martinez-Martin et al., 2021). A 2021 Stanford University study attempted to identify the most significant concerns surrounding digital phenotyping. The team implemented a modified version of the Delphi method: a technique in which field experts in mental health law, ethics, and data science respond to questionnaires and analyze them to reach a reliable consensus (Dalkey et al., 1963). The study showed strong favor among all 24 participants to develop new security and privacy guidelines for HIPAA that address personal health data collection occurring outside its current authority. Additionally, clear communication to patients and users about the risks and benefits of passive data collection was deemed essential (Martinez-Martin et al., 2021). Many other issues were also addressed in this study. On data re-identification, the Delphi participants suggested existing frameworks should never consider data as "non-identifying." With the advent of massive public databases, personal data is always at risk of being traced to a specific person or group (Martinez-Martin et al., 2021). Conclusion Passive data sensing (PDS) removes complexities in data collection by enabling real-time data collection. By analyzing data collected by context-aware devices, researchers can find correlations between trends in the data and mental health deterioration. Today, the ongoing pandemic introduces significant changes and

stress-inducing situations in people's lives that may negatively affect their physical and mental health. PDS, therefore, could be an effective way to detect worsening mental health in individuals earlier by analyzing changes in behavior patterns via sensors and phone services. Researchers must ensure that their machine learning models can use the data collected to predict depression with high accuracy to implement this technology. Additionally, implementing passive data sensing and machine learning to predict changes in mental health during the COVID pandemic will be particularly challenging if privacy and transparency. Nevertheless, a collective and concerted effort among healthcare service providers, researchers, and data collectors to establish regulations and protocols for HIPPA compliance is required for a more efficacious implementation of passive data sensing. References: B. Schilit, N. Adams, and R. Want. 1994. Context-Aware Computing Applications. In Proceedings of the 1994 First Workshop on Mobile Computing Systems and Applications (WMCSA' 94). IEEE Computer Society, USA, 85–90. DOI:https://doi.org/10.1109/ WMCSA.1994.16 Camellia Zakaria, Rajesh Balan, and Youngki Lee. 2019. StressMon: Scalable Detection of Perceived Stress and Depression Using Passive Sensing of Changes in Work Routines and Group Interactions. Proc. ACM Hum.-Comput. Interact. 3, CSCW, Article 37 (November 2019), 29 pages. https://doi.org/10.1145/3359139 Cornet, V. P., & Holden, R. J. (2018). Systematic review of smartphone-based passive sensing for health and wellbeing. Journal of biomedical informatics, 77, 120–132. https://doi. org/10.1016/j.jbi.2017.12.008 DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Danese, A., Moffitt, T. E., Harrington, H., Milne, B. J., Polanczyk, G., Pariante, C. M., Poulton, R., & Caspi, A. (2009). Adverse childhood experiences and adult risk factors for agerelated disease: depression, inflammation, and clustering of metabolic risk markers. Archives of pediatrics & adolescent medicine, 163(12), 1135–1143. https://doi.org/10.1001/ archpediatrics.2009.214 de Figueiredo, C. S., Sandre, P. C., Portugal, L., Mázala-de-Oliveira, T., da Silva Chagas, L., Raony, Í., Ferreira, E. S., Giestal-deAraujo, E., Dos Santos, A. A., & Bomfim, P. O. (2021). COVID-19 pandemic impact on children and adolescents' mental health: Biological, environmental, and social factors. Progress in neuro-psychopharmacology & biological psychiatry, 106, 110171. https://doi. org/10.1016/j.pnpbp.2020.110171 Dhingra, S. S., Kroenke, K., Zack, M. M., Strine, T. W., & Balluz, L. S. (2011). PHQ8 Days: a measurement option for DSM-5 Major Depressive Disorder (MDD) severity. Population health metrics, 9, 11. https://doi. org/10.1186/1478-7954-9-11 Huckins, J. F., daSilva, A. W., Wang, W., Hedlund, E., Rogers, C., Nepal, S. K., Wu, J., Obuchi, M., Murphy, E. I., Meyer, M. L., Wagner, D. D., Holtzheimer, P. E., & Campbell, A. T. (2020). Mental Health and Behavior of College Students During the Early Phases of the COVID-19 Pandemic: Longitudinal Smartphone and Ecological Momentary Assessment Study. Journal of medical Internet research, 22(6), e20185. https://doi.org/10.2196/20185

Torous J, Kiang MV, Lorme J, Onnela J New Tools for New Research in Psychiatry: A Scalable and Customizable Platform to Empower DataDriven Smartphone Research JMIR Ment Health 2016;3(2):e16 doi: 10.2196/ mental.5165 PMID: 27150677 PMCID: 4873624 Rui Wang, Fanglin Chen, Zhenyu Chen, Tianxing Li, Gabriella Harari, Stefanie Tignor, Xia Zhou, Dror Ben-Zeev, and Andrew T. Campbell. 2014. StudentLife: assessing mental health, academic performance and behavioral trends of college students using smartphones. In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp '14). Association for Computing Machinery, New York, NY, USA, 3–14. https://doi.org/10.1145/2632048.2632054 Zhenyu Chen, Mu Lin, Fanglin Chen, Nicholas D. Lane, Giuseppe Cardone, Rui Wang, Tianxing Li, Yiqiang Chen, Tanzeem Choudhury, and Andrew T. Campbell. 2013. Unobtrusive sleep monitoring using smartphones. In Proceedings of the 7th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth' 13). ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), Brussels, BEL, 145–152. https://doi.org/10.4108/icst. pervasivehealth.2013.252148

Jacobson, N. C., Lekkas, D., Huang, R., & Thomas, N. (2021). Deep learning paired with wearable passive sensing data predicts deterioration in anxiety disorder symptoms across 17-18 years. Journal of affective disorders, 282, 104–111. https://doi.org/10.1016/j. jad.2020.12.086 Martinez-Martin, N., Greely, H. T., & Cho, M. K. (2021). Ethical Development of Digital Phenotyping Tools for Mental Health Applications: Delphi Study. JMIR mHealth and uHealth, 9(7), e27343. https://doi. org/10.2196/27343 Norman Dalkey, Olaf Helmer, (1963) An Experimental Application of the DELPHI Method to the Use of Experts. Management Science 9(3):458-467. https://doi.org/10.1287/ mnsc.9.3.458 WINTER/SPRING 2022

An Introduction to Blood Pressure BY UJVALA JUPALLI '25 Cover Image: Blood pressure should be checked more regularly as the one gets older. It is crucial to maintain a blood pressure of 120/80 mmHg by eating a wellbalanced diet and exercising daily. Image Source: Wikimedia Commons

Overview and Trends of Blood Pressure Blood pressure is the force of one’s circulating blood against the walls of arteries and veins. Most of this pressure comes from the heart pumping blood through the circulatory system to the rest of the body. Blood pressure, also known as arterial pressure, is determined by the volume of blood ejected by the heart into the arteries, the elasticity of artery walls, and the rate of blood flow out of those arteries (Magder, 2018). There are two different types of blood pressure: systolic pressure and diastolic pressure. Systolic pressure is generated by cardiac contraction and is critical for pumping blood against gravity, up to the brain, and out to the rest of the body through arteries and capillaries. Diastolic pressure is the pressure in the arteries during cardiac relaxation that ensures continuous blood flow while the heart receives oxygen. According to the Center for Disease Control, a healthy and active adult should have a systolic blood pressure of less than 120 mmHg and a diastolic pressure of less than 80 mmHg. High blood pressure is a leading cause of cardiovascular disease, chronic kidney disease, dementia, and more. In 2015, high systolic blood pressure was associated with the death of over 8.5 million people (Zhou et al., 2021). However, problems with blood pressure are not spread

out evenly across low and high income regions. High blood pressure is more prevalent in lowerand middle- class countries rather than in highincome regions. This is evidenced by the decline of the mean systolic and diastolic blood pressures among high income regions and the increased mean blood pressure among women and men in East Asia, South Asia, and sub-Saharan Africa (Zhou et al., 2021). Determinants of Blood Pressure There are two main determinants of blood pressure. The strength of cardiac contraction determines systolic pressure since the pumping of the heart determines how much blood is in the arteries. Vessel resistance determines diastolic pressure as diastolic pressure depends on the speed of the blood flow back to the heart. This is also why blood pressure increases during physical exertion: the heart pumps stronger and faster to get more oxygen to the organs and muscles that are working. The volume of blood in the vascular space also plays a major role in determining blood pressure since more blood increases pressure (Magder, 2018). Environmental factors such as ambient temperature and altitude have also been shown to DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

actions would lower the overall blood pressure.

have an impact on blood pressure. Temperature tends to have an inverse relationship with blood pressure. This means that when temperature decreases, many individuals tend to have a higher blood pressure. The reason for this could be further explained by changes in diet, lower vitamin D levels, and reduced physical activity (Brook et al., 2011). On the other hand, there is a direct relationship between altitude and blood pressure. Increases in blood pressure due to higher altitudes are most likely explained by the lower temperatures and fewer oxygen molecules in the air. With less oxygen available, individuals will have to exert more physical effort to get the same amount of oxygen as in lower altitudes. It is important to note that the amount of time spent in these higher altitudes also plays a role- many individuals will acclimate to higher altitudes over time, and their blood pressures will neutralize to how they were in lower altitudes in a couple weeks (Brook et al., 2011). How is Blood Pressure Maintained? Blood pressure is maintained in the human body with the help of the endocrine system, a messenger system composed of glands and hormones. If one’s blood pressure drops due to blood loss or dehydration, their kidneys can sense it in their juxtaglomerular apparatus (JG apparatus). The JG apparatus will then release an enzyme known as renin, which in turn creates a hormone called angiotensin II (Li et al., 2018). This hormone will then cause the arterioles to constrict, therefore narrowing the vascular space and increasing the pressure of blood against the walls of those arteries and veins. Angiotensin II will also cause the adrenal glands to secrete aldosterone, which instructs the kidneys to retain sodium. When this happens, the kidneys will produce less urine, and as a result blood volume will increase and cause blood pressure to go back up (Li et al., 2018). Alternatively, when blood pressure rises, the human body reacts in the opposite way, causing the arterioles to expand and the kidneys to produce more urine. These WINTER/SPRING 2022

Another way the human body controls blood pressure is through blood pressure sensors called arterial baroreceptors which are located in the carotid sinus near the carotid artery and the aortic arch (Hirschl & Kundi, 2014). These baroreceptors inform the autonomic nervous system of any changes in the blood pressure by detecting the tension of arterial walls. For instance, if blood pressure suddenly fell after a person stood up, the baroreceptors would sense it and decrease their firing rate. This leads to an increase in sympathetic outflow including hormones like epinephrine (also known as adrenaline) and norepinephrine which accelerate the heart rate, thereby increasing blood pressure. On the other hand, when blood pressure rises, the baroreceptors would increase their firing rate which leads to an increase in parasympathetic activity (Hirschl & Kundi, 2014). This includes the hormone acetylcholine which slows down the heart rate and dilates blood vessels, thereby decreasing blood pressure. A combination of these processes keeps blood pressure stable on a daily basis. Hypotension Hypotension, or low blood pressure, occurs when there is an inadequate amount of pressure in the bloodstream for the blood to make it to the brain, organs, and tissues. The blood is not able to maintain the supply of nutrients and oxygen. When low blood pressure prevails, shock can occur causing organ failure and other major problems later on (Biaggioni 2016). There are three major causes of hypotension: loss of blood volume (due to a major hemorrhage or severe dehydration), low cardiac output, and loss of peripheral vessel resistance (commonly due to a bacterial infection called sepsis). A major hemorrhage occurs when there is a rupture in a blood vessel that causes blood to be released inside or outside the body. Similarly, dehydration leads to a decreased amount of fluid circulating in one’s blood vessels. Low cardiac output results when the heart cannot pump enough blood to other organs in the body. This leads not only to low blood pressure, but also to other issues including lightheadedness, low urine output, and fatigue since the heart isn’t pumping enough oxygen to the brain and other organs. Lastly, when peripheral resistance is lost, arteries dilate and blood flows at a faster rate. This leads to organ malfunction and even shock.

Image 1: Systolic pressure is determined by the heart’s ability to pump out blood to other organs and diastolic pressure makes sure that there is still blood flow while the heart is refilled with oxygen. Image Source: Wikimedia Commons

"There are three major causes of hypotension: los of blood volume...,low cardiac output, and loss of peripheral vessel resistance..."

relax (Hariri and Patel, 2022). A combination of some of these drugs along with a change in a diet can allow an individual to control their blood pressure.

Image 2: Foods like fries and hamburgers contain high levels of sodium and fat. Consistently eating high sodium foods can increase blood pressure and lead to heart complications. Source: Wikimedia Commons

"High blood pressure... puts the indiviudal at a higher risk for a heart attack, stroke, or heart disease."

Hypertension Hypertension occurs when blood pressure exceeds the 140/90 systolic to diastolic range and is classified as extreme when it exceeds 180/120. When an individual has high blood pressure, their heart must work harder to pump blood to organs and muscles. This has a negative effect on the heart and can cause the left ventricle to thicken, which puts the individual at a higher risk for a heart attack, stroke, or heart disease. Hypertension can also damage arteries by decreasing their elasticity which affects the flow of oxygen and blood to the heart as well as the other organs. Hypertension can be caused by various reasons. A diet that contains high levels of fat, sodium, or cholesterol and a lack of physical activity can lead to obesity and cause blood pressure to increase. Genes and family history also have a role in one’s blood pressure, but genes alone do not cause hypertension. Furthermore, high stress levels are known to play a role in increasing blood pressure (Ayada et al., 2015). Lastly, underlying health conditions such as diabetes, kidney diseases, and other long-term kidney infections can cause hypertension. Treatments for Controlling Blood Pressure Blood pressure can be controlled using medications or through a balanced and healthy lifestyle. A low-calorie diet with low levels of sodium as well as daily exercise can allow individuals to maintain a healthy blood pressure. It is crucial to control body weight and to make sure one is within the recommended BMI range. There are also medications that are taken daily that help control blood pressure. One type of medication called Losartan inhibits the formation of angiotensin II by blocking the interaction between angiotensin II and its receptor (Siegl et al., 1995). Another type of medication called beta blockers blocks the actions of epinephrine. Thus, the individual will not have arterial constriction and/or lower cardiac output. Diuretics cause the kidney to get rid of sodium through urine, lowering the blood volume. Lastly, another drug category, called vasodilators, forces arterioles to

Conclusion All in all, blood pressure is an important factor in life that must be controlled through a healthy diet and exercise. High blood pressure is when one has a systolic pressure above 140 and a diastolic pressure above 90. Chronic high blood pressure or hypertension can lead to damaged arteries and increased risk of a heart attack or stroke. Low blood pressure or hypotension can also occur due to dehydration or blood loss. This can result in dizziness or cause one to faint since the brain isn’t able to get enough blood. There are, however, a variety of medications that can be used to keep one’s blood pressure stable along with a change in diet. References Ayada, C., Toru, Ü., & Korkut, Y. (2015). The relationship of stress and blood pressure effectors. Hippokratia, 19(2), 99–108. Biaggioni, I. (2016). The Pharmacology of Autonomic Failure: From Hypotension to Hypertension. In S. W. Watts (Ed.), Pharmacological Reviews (Vol. 69, Issue 1, pp. 53–62). American Society for Pharmacology & Experimental Therapeutics (ASPET). https://doi. org/10.1124/pr.115.012161 Brook, R. D., Weder, A. B., & Rajagopalan, S. (2011). “Environmental Hypertensionology” The Effects of Environmental Factors on Blood Pressure in Clinical Practice and Research. In The Journal of Clinical Hypertension (Vol. 13, Issue 11, pp. 836–842). Wiley. https://doi.org/10.1111/ j.1751-7176.2011.00543.x Hariri L, Patel JB. Vasodilators. [Updated 2022 Feb 6]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2022 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/ NBK554423/ Hirschl, M., Kundi, M. Carotid interventions and blood pressure. Wien Med Wochenschr 164, 503–507 (2014). https://doi.org/10.1007/s10354014-0327-4 Li, X. C., Zhu, D., Zheng, X., Zhang, J., & Zhuo, J. L. (2018). Intratubular and intracellular reninangiotensin system in the kidney: a unifying perspective in blood pressure control. Clinical

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science (London, England : 1979), 132(13), 1383– 1401. https://doi.org/10.1042/CS20180121 Magder, S. The meaning of blood pressure. Crit Care 22, 257 (2018). https://doi.org/10.1186/ s13054-018-2171-1 Melville, S., Byrd, J.B. Personalized Medicine and the Treatment of Hypertension. Curr Hypertens Rep 21, 13 (2019). https://doi.org/10.1007/ s11906-019-0921-3 Raven, P.B., Chapleau, M.W. Blood pressure regulation XI: overview and future research directions. Eur J Appl Physiol 114, 579–586 (2014). https://doi.org/10.1007/s00421-0142823-z Schwarz, C. E., & Dempsey, E. M. (2020). Management of neonatal hypotension and shock. Seminars in Fetal & Neonatal Medicine, 25(5), 101121. https://doi.org/10.1016/j. siny.2020.101121 Siegl, P. K., Kivlighn, S. D., & Broten, T. P. (1995). Pharmacology of losartan, an angiotensin II receptor antagonist, in animal models of hypertension. Journal of hypertension. Supplement : official journal of the International Society of Hypertension, 13(1), S15–S21. https:// doi.org/10.1097/00004872-199507001-00002 Zhou, B., Perel, P., Mensah, G.A. et al. Global epidemiology, health burden and effective interventions for elevated blood pressure and hypertension. Nat Rev Cardiol 18, 785–802 (2021). https://doi.org/10.1038/s41569-02100559-8

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Overcoming Mortality: A Denial of Death & Dying BY VANIA ZHAO '25 Cover Image: On the left is the general immune response that leads to wheal formation – the characteristic symptom of chronic urticaria. With cholinergic urticaria, increases in body temperature lead to this immune response through multiple mechanisms. On the right is the ribbon for chronic urticaria awareness. Image Source: Wikimedia Commons

Introduction From the moment of birth, the dying process begins. Through religion, science, philosophy, spirituality, and other means, humans have long attempted to understand, rationalize, and confront the inevitability of death. In our pursuit to find meaning in life despite the certainty of death, our inquisitive nature demands a way to transcend death. As we grow and deal with aging and the loss of those around us, the promise of eternal life beckons us to ask the forbidden question: what if death is not inevitable? What if we could escape the grasps of death entirely and live forever? This essay will be a comprehensive exploration of immortality in the modern world through four pillars. The first part of this article will define and explain literal and symbolic immortality through various anthropological lenses, including models proposed by Robert Jay Lifton, Arnold van Gennep, and Robert Hertz, as well as through a spiritual and higher-existential lens. The second part will examine the possibility and feasibility of immortality by examining forms of immortality that exist with nature and the human body. The third part will outline hypothetical methods and models for immortality through

modern medicine and technology and examine those methods through the anthropological, philosophical, ontological, and theological lens introduced in the second pillar. The fourth part will explore the implications of immortality for society, examining whether immortality is something that is desired in the modern day; it will also tackle questions in a future where immortality is possible, such as: Will the wealth gap widen? Would only a few social elites be able to afford immortality? How would the demographic look? How will education, religion etc. shift with this development? These questions are explored through the anthropological work of Antonio Sandu, who examines the posthuman/ transhuman world, as well as through hypothetical worlds through fiction. What Is Immortality? While there are many forms of immortality, at its core, it is a continuation of life beyond the claws of death. Immortality can essentially be boiled down to two categories: literal immortality and symbolic immortality. Literal immortality is simple to define. It is achieved when an individual transgresses the limits of natural life and lives forever, retaining their consciousness beyond death accompanied by their physical bodies. DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Many modern technologies aim to accomplish this. Meanwhile, symbolic immortality, according to Harvard psychiatrist Robert J. Lifton, MD, is to find a connection beyond the scope of individual life, often through concepts, imagery, or symbols to create meaning and significance to experience (Lifton, 1991). Lifton further splits symbolic immortality into five modes: biological, creative, theological, natural, and experimental (Lifton, 1991). The Five Modes of Symbolic Immortality Lifton’s modes of symbolic immortality provide a framework to compartmentalize the various forms of immortality created as a socio-cultural, psychological construct to cope with the inevitability of death, as well as the great unknown that lies beyond death. Biological immortality is the idea that one continues to live through their offspring– a generational continuation as well as the passing down of reproductive cells and DNA. Creative immortality consists of human influences that persist throughout the centuries, such as pieces of literature, art, and knowledge that extends to the greater human “flow” beyond the self. Theological immortality often constitutes a central immortal figure that has attained eternal life and perpetuates the idea of an immortal soul, offering immortality through spiritual belief under specific conditions. One can also find immortality through nature. As nature is cyclical and continuous, returning to nature upon death signifies an eventual renewal through the Earth. Finally, experimental immortality, or transcendence, is a psychological state of an ecstatic sense of timelessness, which can be found through stimulating activities or induced through substances. Symbolic immortality allows humans to form an explanation for the afterlife, as well as face the reality of death by believing that life doesn’t just end. The reassurance of a legacy, of some part of the self-persisting for eternity, offers a sense of solace in life (Lifton, 1991).

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While Lifton’s framework provides a helpful categorization of symbolic immortality, to further understand immortality (specifically literal immortality), it is necessary to examine the concept through additional anthropological frameworks and ethnographic methodology. Since it is impossible to conduct an ethnographic study on immortals because, to public knowledge, none exist. Immortality can be viewed as a complete deconstruction of death and mourning by eliminating the factor of death completely, combatting death anxiety. We can cross-examine literal immortality with rites of death to identify points of deviance and its significance. The first model, introduced by Arnold van Gennep (1991), a Belgian ethnographer, analyzes death and mourning rites through a tripartite structure of separation, liminality (a transitional state), and incorporation. Robert Hertz, a French sociologist, builds upon van Gennep’s works and examines rites through the soul, the body, and the mourners (1991). For starters, literal immortality completely rejects separation as the soul is bound eternally to the body, and neither experiences death (Lifton, 1991; Hertz, 1991). In contrast, for symbolic immortality, the soul is the only actor that does not experience death, while the body is corrigible and the corpse impure (Lifton, 1991; Hertz, 1991). By this logic, immortality denies all impurities of the earthly vessel, and becomes a form of perfection and purity. In contrast, if complete separation allows for purity, then since immortals never experience this separation, they can be seen as permanently impure. The inability to die also creates a complicated relationship with the mourner: one is never mourned and always the mourner.

Image 1: Time and Antiquity. Image Source: Pixabay

"...immortality rejects liminality... Immortality imposes, instead, a state of permanence"

Moreover, immortality rejects liminality. Van Gannep (1991) describes liminality as existing in a state of neither-nor. Immortality imposes, instead, a state of permanence. Immortals are never dead and always alive. It is black and white; they do not enter the gray area between life and death. Immortality signifies a stagnation of the natural cycle of life; there is no destruction, so there is no transition. Finally, as the immortal is never changing, there is no need for incorporation into anything at all, as one has never departed from their initial state. From these lenses, the search, and obsession, of immortality is driven by the denial of death completely and allows one to exist in a state of permanence, which is only seen in divinity. However, analysis of immortality through these models are in relation to death, and under the assumption that one has achieved immortality. The process of becoming immortal, or “transhuman” (a term used by anthropologists and futurists alike to describe the posthuman condition after life-prolonging procedures 72

or immortality), sees different relationships between these rites and actors, which will be explored further in the introduction of methods of immortality later in the essay (Sandu, 2015). Immortality and Spirituality

"...symbolic and literal immortality serve as mental touchstones for humans to cope with the imminence and finality of death..."

Notions of both symbolic and literal immortality serve as mental touchstones for humans to cope with the imminence and finality of death. Thus, it is unsurprising that immortality is deeply ingrained within religion, philosophy, ontology and theology. While within each religion, there are nuances on the exact belief of immortality, there are overarching themes and similarities that can be derived. For instance, in symbolic theological immortality, the immortal soul is a key concept. This can be represented as eternal existence after death in a spiritual location such as heaven or hell, central to Christian ideas, or as reincarnation in Eastern religions such as Hinduism, Jainism, and Buddhism (Nagaraj, 2013), which take a more philosophical approach in comprehending the soul. Where in Western religions, the separation of the body of the soul is an irreversible process, in Eastern religions the soul can take on the form of flesh again, or as animals, plants, or spirits. There is no finality in the separation of the soul from the earthly body. In fact, one’s deeds can carry over to future lives in the forms of Karma, the results of your deeds, or yuan fen, a Chinese belief of relationships and connections formed in past lives that must be realized in the present. Aspects of one’s consciousness can also be transferred. Though not identical to the current life, consciousness throughout lives is part of a continuum or “stream” (Nagaraj, 2013), which calls into question whether the differences are enough to consider it the same self or being, on whether the human condition changes its ontological status (Sandu, 2015). However, humans are not satisfied with attaining immortality through death. Thus, many seek immortality to prolong their current identity of self and transcend the human condition. Sandu attributes the “the Kantian category of synthesis, and also from the religious experience of humanity” (2015) as philosophical and theological separators of humanity and divinity. In many religions, deities possess immortality, omnipotence, and omniscience. Immortality is a staple in divinity, and a current impossibility for humans, thus it is no surprise that it is something that humanity is fascinated with. By defining the limitations of human beings, the distinctions of humanity and divinity through “anthropological characteristics” (Sandu, 2015), there is context for the efforts that humanity takes to overcome

these limitations. However, connecting back the purity and impurity of the body and the quest for immortality, it can be seen as a gift just as a punishment, as is the case with the Gilgamesh Odyssey, the myth of the wandering Jew, the story of Ivan Turbinca (Sandu, 2015). Immortality is first portrayed as a desirable goal worthy to be sought after, but upon obtaining it becomes an eternal curse as an exile from the essence of being human. There are many nuances and complexities of immortality, but first, we must explore the question: is immortality possible? Is Immortality Possible? While it has been established that humans can feasibly become immortality symbolically, the question of whether a human can live forever literally has yet to be answered. Without factoring accidental death or death due to such as murders, the primary agent of death is aging and disease. There are many theories on why humans age: the shortening of telomeres (repetitive protective DNA sequence at the end of chromosomes, without which cells can no longer divide successfully), and genetic instability is often pinpointed as one of the leading causes of aging. Another is the deterioration of cellular functions (Max Planck Institute, n.d). Throughout history, humans have continuously pursued immortality despite their race, religion, or ethnicity. Immortality is an anthropological constant uniting all of humanity (Sandu, 2015). Clearly, it is an important mission for humanity. Thus, seeing that it is possible inspires humans for further discovery, and there are many instances of immortality in nature, and even within the human body that is driving research to further technologies. While immortality is not yet possible, research in these areas have already improved the quality of life through advances in medicine, curing diseases that were otherwise deadly or debilitating. Immortality in Nature It is important to examine the available forms of immortality as they offer us a clue on what is possible and how we can apply these insights to humans. Science looks to these instances for clues to significantly extend our lifespan, slow down the effects of aging, or to stop aging completely. The following three cases of immortality in nature offer us a glimpse of the secret to eternal life. According to the Australian Academy of Science, Turritopsis dohrnii, a type of jellyfish, has been dubbed the only biologically immortal species on earth. These jellyfish have the unique ability to switch back and forth between life stages depending on the situation. In events of

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Image 2: Jellyfish, some of which are biologically immortal Image Source: Pixabay

injury, starvation, or imminent death, a mature Turritopsis dohrnii reverts into a blob of tissue, which then changes back into the sexually immature polyp phase of life (Berthold, 2021). The Hydra viridissima is a tubular shaped species with a tentacle-ringed mouth and adhesive feet that resembles the jellyfish in the polyp stage. Unlike the jellyfish, Hydra is immortal on a cellular level. Hydras have infinitely self-renewing stem cells, which is due to FoxO genes. These genes regulate the longevity of cells. When researchers suppressed FoxO genes, Hydra showed decreased ability to regenerate as well as signs of aging. Thus, it can be concluded that these genes are clearly paramount to their immortality (Berthold, 2021). The jellyfish and the Hydra have achieved biological and cellular immortality, but there is another form of immortality that can be found in nature– genetic immortality. Lobsters have an endless supply of telomerase, which continuously generate telomeres and maintain their healthy DNA. However, Lobsters can still die, and they do so frequently. They are still susceptible to disease, predation (especially by humans), and exhaustion of growing new shells (Berthold, 2021). Immortality in Humans While immortality can be found throughout nature, it can also be found closer to us. Immortality exists within our own bodies in many forms. One of the most perplexing and prominent forms is the case of cancer cells. While scientists are unsure of how regular somatic cells can grow into immortal cancer cells, a leading theory is that cells stabilize their telomeres through the actions of telomerase continuously proliferate and achieve immortality (Weinberg, 2014). The infinite capability of cancer cells to divide and proliferate poses a great threat to humanity, and it is, according to the CDC, the second leading cause of death after heart disease. However, in an ironic sense, one of the primary causes of death

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for humans could be the breakthrough to help humans achieve immortal life. As seen by the aforementioned instances of immortality, it can be concluded that immortality is indeed possible on a biological, cellular, and genetic basis, and can exist within humans. Based on these discoveries, humans are aiming to develop several methods of immortality on these different levels. Methods of Artificial Immortality Immortality for humans currently exists in the realm of science-fiction. However, there are several fields of research that are dedicated to prolonging of human life. Currently, there are five main methods of artificial immortality under development which include cryonics, genetic editing, cellular repair, intelligence digitization, and cyborgism. These methods can be understood through both a scientific and anthropological lens for a more holistic approach. Cryonics Unlike the other methods of immortality, it is important to note that cryonics does not directly allow for infinite life. Instead, cryonics aims to freeze someone just before or immediately after they pass away to preserve their body and mind until science is advanced enough to bring the person back, cure their disease or further extend their life. Cryonics is currently the only viable option of all the methods, and thus it is necessary to examine the practice, as well as its implications. The process of begins with the death of the patient. The technician must cool the body immediately in an ice bath to prevent degeneration. Blood is drained and replaced with cryoprotectant agents, as blood can freeze and form ice crystals. Finally, the body is placed in liquid nitrogen to preserve tissues and organs until its eventual revival. Currently, 165 patients have undergone the process, with over 2000 living people signed up for services that the

Image 3: Cryonics Chamber Rendering Image Source: Pixabay

Cryonics Institute offers (Lawrie, 2018), who believe in the Institute’s mission to give current humans with a chance of either a second chance to live or immortal life for when the technology is available. As it is uncertain if cryonics will be successful, it can essentially be viewed as a new form of burial, suspending an individual in an indefinite liminal state of being neither fully alive nor dead. The body, specifically the brain, is seen as an important vehicle in the definition of personhood and houses one’s consciousness. Consciousness, through the ontological lens, is stored on a molecular level. However, cryonics is currently a more symbolic form of immortality, as it eases the patient’s death anxiety through the belief that one day technology will advance to the point that a. they can successfully be unfrozen and b. a cure exists for their disease or that immortality is available. In line with van Gennep’s ideas, since the stage of liminality due to being frozen could last for decades or centuries, in the process of incorporation, one would need to be accustomed to potentially an entirely different world, where everyone they knew, and love are already dead, and they are no aspect of the culture, technology, or society have any resemblance at all with the time they were from.

Genetic Editing Evident from the lobsters’ longevity or cancer cells, the key to immortality may lie within our genetics. Scientists have long attempted to map out the human genome and advance technologies in genetic editing in hopes of eliminating diseases and eventually prolong life indefinitely. The most promising technology for genetic editing currently is the CRISPR/ CAD9 technique. In 2017, American researchers successfully edited the genome of an embryo using this technique, and thus the proposition of modifying the genome to produce more telomerase has become more of a possibility. However, simply increasing telomerase in humans is risky as it is associated with several types of cancers (Djojosubroto, 2003). Furthermore, genetic editing is extremely controversial as it brings into questions of ethics and morality, which will be further explored later in the essay. The question of whether a modified individual is still the same person is also called into question, opening philosophical debates about personhood and self.

Image 4: Genes viewed under a microscope with rendering Image Source: Pixabay

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Image 5: Cells under microscope with rendering Image Source: Pixabay

Cellular Repair Self-renewing stem cells, like those of the Hydra, is another promising area of research regarding artificial immortality for humans. Stem cell research has long dominated the medical field for various purposes as these cells can perform an array of tasks. For starters, the human embryonic stem cells are immortal. These cells do not age, they can proliferate indefinitely, and create any tissue of the organism (Mummery, 2014). Thus, not only do stem cells offer the promise of eternal life, but they also have the potential to heal disease and injury. Cellular repair transforms the body into a state of permanence, and its regenerative capabilities brings humanity closer to divinity through the sense of omnipotence. Cellular repairs further immortality by allowing invulnerability, which may be key to retaining quality of life for immortals. Both genetic editing and cellular repair places an emphasis on the body over the mind, and do not consider whether the human mind is capable of functioning beyond the lifespan in terms of memory or emotions. Thus, in both cases, the body is suspended in permanence, and one’s soul is eternally tied to the body. Again, this is an instance that rejects the separation of body and soul, and after incorporation into the state of immortality after undergoing the procedures, the notion of liminality will be rejected in favor of permanence. Intelligence Digitization Intelligence digitization is fundamentally different from immortality. Instead of creating an immortal body, the transfer of consciousness sustains an immortal mind. It is bringing symbolic immortality into the digital world. It celebrates and implements the separation of the body and the mind, in the lens of van Gennep and Hertz. Intelligence digitization is contingent upon notions of consciousness, and whether it is something that can exist without the body and be transferred into a computer. It raises philosophical questions on whether a digitized

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duplicate of a consciousness could be considered the same as the original consciousness. Questions about self are also raised in response to this method. In Buddhism, the transfer of consciousness is mentioned in the Tibetan philosophy under the Dhrong Jug technique (Sandu, 2015). It assumes that consciousness is a form of energy instead of a physical form, in the ontological sense, and perpetuates the idea of an immortal consciousness. Virtual immortality also allows the transcendence of omniscience and spatial limitation. As one exists in a digital space, they are no longer constricted by the physical realm, another staple of the divine. Intelligence digitization may be the technology to truly push humanity into an altered form of ontology, as previously mentioned forms do not allow omniscience and spatial limitations, and only overcomes biological limitations of humanity. Already, we have seen shifts of people to mourn in the digital space, finding more meaning and a more lasting legacy compared to traditional forms. Creative symbolic immortality is exercised without the limits of physical objects, which are subjected to destruction and deterioration (Bennet, 2015).

"Intelligence digitization is fundamentally different from immortality."

Cyborgs A cyborg is a human/machine hybrid. Proposed theories for cyborg immortality include replacing faulty human parts with machines or placing the human consciousness into an artificial body. In her article for the Society of Cultural Anthropology, Cassandra Hartblay (2022) notes cyborg implementation as the ultimate destruction the notion that “natural and the technological are distinct spheres” by blurring boundaries between human/tool, human/animal, animal/ machine, body/mind, and physical/nonphysica. In terms of anthropological lenses that have been mentioned in this essay, it blurs the boundary between literal and symbolic immortality, as well as the body, mind, and soul. She mentions ethnographic consciousness, and how much our

"...the final question remains: do people want to be immortal?"

tools and objects become a part of us. A modernday analogy would be prosthetics. Cyborgism, in essence, is turning our entire body into an extension. It is the most complete overcoming of human limitation by destroying the body and replacing it with machines, including the brain by potentially implementing the consciousness as a chip or data in the machine body. Humans will be able to live in both a physical and digital world through cyborgism, a feature no other method will be able to accomplish (Hartblay, 2022). The Implications of Immortality Some of the world’s brightest minds are working fervently for breakthroughs in technologies revolving around immortality. Upon examining the roots of immortality, examples of immortality in nature, as well as developing methods for immortality, the final question remains: do people want to be immortal? The Pew Research Center had the same inquiry and published their finding through their article “Living to 120 and Beyond: Americans’ Views on Aging, Medical Advances and Radical Life Extension”. According to their data on whether Americans are willing to undergo life-prolonging treatment, such as the five methods of artificial immortality, most U.S. adults (56%) say no, but roughly two-thirds (68%) think that most other people would (Pew Research Center, 2022). From the data, it is evident that while most people currently will not undergo these procedures, they assume that others around them would. This assumption roots from the historical and cultural yearning for immortality, as mentioned earlier in the essay, that the average person would want to live beyond the human lifespan. However, as seen by the data, on the individual level, it is not a choice that most people would make currently. Perhaps it is because these technologies are immature. Additionally, there is always a reluctance, and skepticism, to accept new forms of developments until they are popularized and normalized for implementation into society. An example of this would be the internet,

computers, or even vaccines. In fact, many people do not follow updates of new developments in the life prolonging field, and thus do not even know about available options. Another reluctance is the thought of losing loved ones if they do not opt for immortality, strained natural resources and wealth due to overpopulation, or the thought of artificial immortality as fundamentally unnatural. It could also be due to the eternal punishments that have been illustrated by lore throughout history. Immortality and Transhumanism in a Knowledge-Based Society for Elites While immortality is neither a currently viable nor widely sought after by the public, it is still worth thinking about what immortality would imply for our society when it becomes a possibility. There are two instances: the first is that immortality is exclusive, and the second is that immortality is accessible to all. In his article, “The Anthropology of Immortality and the Crisis of Posthuman Conscious,” Antonio Sandu examines the transhuman and posthuman condition in the pursuit of divinity, as well as its implications for society. For starters, Sandu posits that, in the anthropological lens, immortality does not transition humans from the current condition to a superhuman condition, instead, it is “similar to the supposed biological evolution of anthropoid primates towards the human state” (Sandu, 2015). It is important to note that the future, a “knowledge-based society (KBS)” of “intelligent evolution”, is not one chosen by natural selection, but instead artificial selection, driving humanity into a “existential singularity of a demiurgic nature” (Sandu, 2015). The methods introduced by this essay will be some of those driving factors for artificial selection, and those who can afford or have access to those services will be favored by that selection. In a knowledge-based society, Sandu (2015) notes that due to transparency in knowledge, traditional social structures would be replaced

Image 6: Human-AI interaction Image Source: Pixabay

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by network convergence, in which there will be both a social and anthropological paradigm. The idea is that when we can attain immortality, we would be in a post-singularity era. Not only would the human condition improve, but technology also targets the economy, society, and cultural developments through institutional design (Sandu, 2015). But what would this mean to people on an individual level? In the event of a virtual non-biological immortality, instead of susceptibility to biological threats, humans will instead be vulnerable to informational viruses. Issues of storage and data corruption also exist. Furthermore, immortality could result in the loss of personal identity, life motivation and even the will to survive (Sandu, 2015), whereas longevity is a tangible and desirable good. He insinuates that indefinite lifespan will diminish the purpose of life, as we will have infinite time and therefore no sense of urgency or innovation. Like any new technology, initially, it will only be available to selected elites. From the price point to scarcity, immortality will not be a procedure just anybody can afford. In the thought-experiment of a post-immortality world, we will see a more defined pyramid structure of lifespan, with the elite on top as the demographic. Although this pyramid exists today, with the introduction of immortality, it will only widen the gap between the wealthy and the poor. Inequality would increase in all aspects of society. Due to longer lifespans, or indefinite lifespans, the wealthy will be able to amass more wealth, solidifying generational wealth, while the poor will be trapped in a more restrictive cycle of poverty, with less time and opportunities to create their wealth. In other words, those with power will only get more powerful, and those without will only fall further behind. In fact, humans and transhumans would become distinct species (Sandu, 2015). Politically, in the declaration of independence, there is a line that quotes, “all men are created equal”. However, with advanced life-prolonging procedures that fundamentally either alter our biology, genetics, and consciousness, that statement no longer holds true, or will be highly questioned and obsolete. The new transhuman population will have “biological superiority”. Influence, and soft power of control systems developed by Joseph Nye in the international relations theory, will alter the structure of capital, leading to strict class systems with low social and economic mobility (Sandu, 2015), as the analysis in the previous paragraph illustrates. Sandu goes further and proposes the potential for “techno-slavery” or even classical

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forms of slavery despite the initial illusion of maintained democracy. Sandu then identifies two outcomes: the rebellion of the oppressed or space colonization, which will physically separate the two types of humans (Sandu, 2015). In the second case, humanity would have diverged into two different species completely irrelevant from one another and separated by physical space. The transhumans would appear like gods to the regular humans and would either abolish religion completely or become gods of a new religion. Ethics can be called into question to further analyze the state of society in a transhuman world. As technology for improving lifespan and genetics exist, the same could be done to decrease lifespan or remove genetic information for the normal humans, which are created to serve the transhumans (Sandu, 2015). This builds upon the risks introduced in the genetic engineering section of the paper. For instance, removing the human tendency for aggression or self-actualization, or other traits that prompt rebellion or disobedience, Sandu (2015) uses Nietzsche’s idea of slave mortality as herd mortality, showcasing that humans would be reduced to subhuman states engineered to serve the elite few with technologies that allow for those elite few to have an immortal rule, and that is truly a terrifying thought.

"...humanity trades biological symbolic immortality for biological literal immortality."

Equal Access Immortality In the event that immortality is accessible to all, Sandu (2015) refers to John Harris’s idea that human reproduction would completely end. Thus, humanity trades biological symbolic immortality for biological literal immortality. The world would be composed entirely of the same people, without any new additions to society due to overpopulation if allowed. It would likely be ingrained into law, and anyone who attempts to reproduce would likely be eliminated. The world, in a sense, would become static. There will be little movement between social classes. There will be no incentive for change or innovation. If only immortality is guaranteed, then the quality of life will not be able to be guaranteed for all. Those who do not lead privileged lives will continue to suffer for all of eternity. If neither aging nor disease is an issue, that could potentially allow a maintenance of a decent quality of life. However, if solving these issues require additional technologies that do not come included with immortality, the poor will suffer additionally– life will be no better than death. Although hypotheticals of the future seek bleak, that is only in the event of abuse of power, corruption, and greed. Sandu and other experts maintain

Image 7: Human connection and biology Image Source: Pixabay

an air of optimism and hopes that global ethics centered on social responsibility with respect for human rights and ethical principle in science will create sustainable, human-centered technology that improve the quality of life for everyone will prolonging lifespans before reaching technologies that allow for some form of immortality (Sandu, 2015). This allows responsibility in ensuring that dystopian-like futures do not come into actuality with the development and eventual implementation of immortality and other lifeprolonging technologies and maintaining the basis that all humans are equal and deserve equal rights and quality of life. Netflix’s show Love, Death + Robots, volume 2, episode 3, presents a fictional world in which there is equal-access immortality and the ban of reproduction. The episode follows Detective Briggs, someone in charge of eliminating “unregistered offspring”. The detective has PTSD from killing children for his job, and the episode features the hunt of an unregistered offspring. In this world, immortality has diminished the meaning of life, which has also been explored in this essay, and there is no sense of wonder. However, when Detective Briggs discovers the newborn and her mother, he observes the two and marvels at the child’s curiosity opposed to his own numbness. As he previously imagined having children with his lover, he decides to spare the two, but as he is leaving another officer arrives and hears the cries of the baby. The two have no choice but to confront one another and shoot each other. In his final moments, Detective Briggs seems to have recovered the essence of being human again and dies feeling truly alive. Although fictional, the episode illustrates the human aspect of a future stripped of generational continuance in a manner that spurs a reevaluation of what it means to be human for the viewer, and the value of our legacy. It is ironic that in

the moment of his death, Detective Briggs truly feels alive since he has lived for centuries and has already seen and experienced everything that could be experienced, except death and parenthood. While humans will always want more, and the promise of eternal life will always beckon us, the episode of Love, Death + Robots reminds us to appreciate our loved ones, as well as the ability to experience and wonder due to our mortality. Conclusion After examining symbolic and literal immortality through the lens of Hertz, van Gennep, and Lifton, as well as through other lenses such as philosophical, religious, theological, or ontological, exploring existing forms of immortality within nature and the human body, presenting technologies for immortality under development and analyzing them through various lenses, and finally diving into the implication of immortality for society through Sandu and hypothetical worlds through fiction, we now have a more holistic understanding of immortality dissected through different perspectives and lenses. As death, disease and aging is inevitable for everyone, it is important to examine the possibility of overcoming those limitations. Ian Pearson, a futurist who tracks and predicts development across of technology, society, and business, estimates that immortality will be attainable as soon as 2050, which means that we are at the dawn of what many call the “transhumanist” movement, and many of us will see immortality become an option in our lifetimes. Already, we are seeing a shift in that more people are accepting cryonics, which is a transition into other forms of immortality. In a self-perpetuating cycle, confidence in breakthroughs in related technologies, such as the various methods of artificial immortality, also increases those who would choose cryonics.

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All in all, we must ask ourselves the big question, framed through bioanthropology: Are we indeed headed for the next stage of human evolution (Sandu, 2015)? In a rapidly changing world of technological innovation, how will we, as individuals, as a community, shape our present to secure a peaceful future for all? How will we adhere to our ethics and values in an increasingly complex world, in which traditional society and culture shifts to center around knowledge and data? From examining symbolic and literal immortality, to existing forms of immortality of various animals and cancer cells, proposed methods of immortality through different technologies, and the implications of immortality for our society, this article merely presents the tip of the iceberg in discussing a knowledge-based society, in which immortality is merely one aspect of a nuanced, unimaginable world. Although the possibilities are endless, it is, nonetheless, important to plant a seed of higher existential thinking in these matters as slowly, but surely, the future comes into actuality.

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Works Cited Bennett, J., & Huberman, J. (2015). From monuments to megapixels: Death, memory, and symbolic immortality in the contemporary United States. Anthropological Theory, 15(3), 338–357. https://doi.org/10.1177/1463499615575943

Netflix. (2019). Love, Death + Robots. Retrieved from https://www.netflix.com/title/80174608.

Berthold, E. (2021, May 24). The animals that can live forever. Curious. Retrieved April 27, 2022, from https://www.science.org.au/curious/earthenvironment/animals-can-live-forever

Living to 120 and beyond: Americans' views on aging, medical advances and Radical Life Extension. Pew Research Center's Religion & Public Life Project. (2022, April 15). Retrieved April 27, 2022, from https://www.pewforum. org/2013/08/06/living-to-120-and-beyondamericans-views-on-aging-medical-advancesand-radical-life-extension/. Mummery C. (2004). Stem cell research: immortality or a healthy old age?. European journal of endocrinology, 151 Suppl 3, U7–U12. https://doi.org/10.1530/eje.0.151u007 Nagaraj, A. K., Nanjegowda, R. B., & Purushothama, S. M. (2013). The mystery of reincarnation. Indian journal of psychiatry, 55(Suppl 2), S171–S176. https://doi.org/10.4103/0019-5545.105519 (Retraction published Indian J Psychiatry. 2015 Oct-Dec;57(4):439)

Sandu, A. (2015). The anthropology of immortality and the crisis of posthuman conscience. Journal for the Study of Religions and Ideologies, 14(40), 3-26. Weinberg, R. A. (2014). The Biology of Cancer. Garland Science.

Djojosubroto, M. W., Choi, Y. S., Lee, H. W., & Rudolph, K. L. (2003). Telomeres and telomerase in aging, regeneration and cancer. Molecules and cells, 15(2), 164–175. Hartblay, C. (n.d.). Cyborg. Society for Cultural Anthropology. Retrieved April 27, 2022, from https://culanth.org/fieldsights/cyborg Hertz, R. Lifton R. J. Robben, A. C. G. M. (Ed.). van Gennep A . (1991). Death, mourning, and burial : A cross-cultural reader. John Wiley & Sons, Incorporated. How and why do we age. MPI - Biology of ageing. (n.d.). Retrieved April 27, 2022, from https:// www.age.mpg.de/healthy-ageing/how-and-whydo-we-age Lawrie, E. (2018, March 20). Are 'cryonic technicians' the key to immortality? BBC News. Retrieved April 28, 2022, from https://www.bbc.

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Investigating the Annual Influenza Vaccine STAFF WRITERS: FRANKIE CARR ‘22, LAUREN FERRIDGE ‘23, JULIETTE COURTINE ‘24, HAYDEN BARRY ‘25, VARUN LINGADAL ‘23, ABIGAIL FISHER ‘23 TEAM LEADS: MADELEINE BROWN ’22, KRISTAL WONG ‘22 Cover Image: Physicians recommend yearly vaccine for influenza. Patients should consult with their healthcare provider before inoculation. Source: CDC

Introduction Influenza is a highly contagious respiratory illness that may cause serious complications in individuals with weakened or compromised immune systems such as children and the elderly, and for people with certain health conditions (CDC, 2021c). Luckily, modern medicine has developed a way to curb the serious complications of the flu: vaccination. However, the fact that there are multiple strains of the flu that can each give rise to infection in humans, coupled with high within-strain mutation rate, contribute to the need for yearly “booster” inoculations to protect humans from a year’s predicted most prominent and most dangerous strands. Powerful antivirals such as Tamiflu can alleviate symptoms and speed up recovery. It is also important to note that an influenza virus was responsible for the previous global pandemic, given the moniker “the 1918 Spanish Flu,” and much can be compared between the latter pandemic and the current COVID-19 pandemic. According to the US CDC, there were an estimated 35 million cases of flu-related instances and 20,000 flu-related deaths in the 2019-2020

flu season (CDC, 2021f). This paper will discuss the influenza virus and its pathology. It will also outline outlining the history of influenza, highlighting notable strains, epidemics, and pandemics. A large component of the piece will be dedicated to understanding current vaccine technology and dissecting the need for an annual vaccine. Biology and Pathology of the Virus The flu is caused by a family of viruses known as the influenza viruses. There are four kinds of influenza viruses: Alphainfluenzavirus (influenza A virus or IAV), Betainfluenzavirus (influenza B virus or IBV), Gammainfluenzavirus (influenza C virus or ICV), and Deltainfluenzavirus (influenza D virus or IDV), defined by their unique host specificities, the symptoms they trigger, and mutation rates (Asha & Kumar, 2019; Krammer et al., 2018; Sautto et al., 2018). All four types of viruses can infect humans. IAV is the cause of many of the past pandemics, including the aforementioned 1918 Spanish Flu (Asha & Kumar, 2019; Sederdahl & Williams, 2020). Meanwhile, IBV and ICV infections are rarer, with both disproportionately infecting children DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Image 1: Tamiflu Image Source: Wikimedia Commons

(IBV has contributed to some of the seasonal epidemics of the past). IDV was not discovered until 2011 and thus there is ongoing research into its effects, although it is known that it can infect humans and can spread to them from cattle and swine populations (Asha & Kumar, 2019). All of these viruses have a negative sense, singlestranded RNA genome. This means that once the virus has docked to a target cell and injected its genetic material into the host, its genome must be copied by an RNA polymerase, producing the positive strand which can then be transcribed into mRNA (and eventually translated into the viral proteins). These genomes are also segmented into eight smaller fragments, which can be thought as mini chromosomes of sort, with each segment coding for different protein(s). This segmentation allows for the rearrangement and combination of the genomes of different influenza viruses (of the same A, B, C, or D type) that are infecting the same host cell. Additionally, pieces of homologous fragments from different viruses can recombine into one new fragment, with sections from both parents. These processes of rearrangement and recombination are the origin of many zoonotic strains of influenza, and they are often referred to collectively as the “antigenic shift” (Asha & Kumar, 2019; Sederdahl & Williams, 2020). Antigenic shift is also responsible for another well-known feature of influenza: the large number of variable strains. IAV strains are often labelled in the format of “H1N1” (the “swine flu” responsible for the 2009 pandemic) (Krammer et al., 2018). But what does this format stand for? There are two main proteins that vary between different flu strains: haemagglutinin (HA) and neuraminidase (NA). HA proteins coat the outside of the viral capsules (~500 molecules per virion) and are responsible for viral docking and entry into the target cell via binding to sialic acid in the cell’s membrane. For this reason, HA is a popular target for most WINTER/SPRING 2022

vaccines. There are two groups of HA proteins with a total of 18 known varieties (labelled as H1, H2, etc) (Madsen & Cox, 2020). NA proteins are also present on the external face of the viral capsule (about ¼ to 1/5 as common as HA) and serve to cleave those same sialic acid molecules to release virions into the body once HA has allowed the virus entry to the cell and it has co-opted the cell’s machinery to build new virions. More research is being done to mobilize vaccination technologies against NA. There are 11 varieties of NA, labelled in the same way as HA varieties (N1, N2, etc). Rearrangement of these various HA and NA genes (for example, an H1N1 virus intermixing with an H18N11 virus to produce H1N1, H1N11, H18N1, and H18N11 virions) leads to the different IAV strains that are known to cause massive pandemics. Since these proteins are on the surface of the viruses, they make the perfect targets for the immune response and, thus, vaccines. The rearrangement mentioned above along with the fact that the different HA and NA proteins are different enough means that we require different vaccines for each strain. Additionally, differences in these proteins lead to variable transmissibility (the rate of spread of the virus from individual to individual) and virulence (the danger a virus poses to an individual; a measure of the symptoms caused by the virus) (Sautto et al., 2018; Webby & Sandbulte, 2008).

"...influenza viruses also have two evolution mechanisms driving antigenic diversity that further increase complexity and chance of a new strain emergence."

In addition to the specificity of HA, influenza viruses also have two evolution mechanisms driving antigenic diversity that further increase complexity and chance of new strain emergence. These two mechanisms are antigenic drift and antigenic shift (Webby & Sandbulte, 2008). Antigenic drift is the main reason for needing frequent updates of flu vaccines. It is the mechanism where amino acid changes occur that change binding sites of the HA, thus escaping recognition by antibodies and creating a new antigenic variant (Ziegler et al., 2018). This erases any immunity or memory developed from 82

previous vaccination. The second phenomenon, antigenic shift, is the virus’s ability to exchange or recombine gene segments between two different influenza strains within one host: simultaneously infecting and replicating within that host. This genetic reassortment generally occurs in a nonhuman host, but recombination of two strains enables the new virus to ‘hop’ from the animal reservoir to humans—where it unleashes a new flu strain on naïve human immune systems (Ziegler et al., 2018). Examples of animal reservoirs are birds or pigs, which have become namesakes for certain epidemics or pandemics such as the “swine flu” and the “avian flu”. In the United States, flu season—the time period when flu cases begin to rise—occurs roughly between October and May (CDC, 2021). The timing of flu season is thought to be the result of a multitude of factors including an influx of people indoors, lack of vitamin D, as well as changes in humidity as temperatures begin to drop (Lowen, 2007). As the flu is estimated to be responsible for as many as 52,000 deaths and millions of hospitalizations in the United States alone per year, proper treatment is a necessity. Most cases of the flu resolve without medical intervention, but antiviral drugs are available to relieve severe symptoms and prevent spread of infection. Currently, there are four FDA approved antiviral drugs for the flu: Rapivab, Relenza, Tamiflu, and Xofluza (FDA, 2021). Rapivab, Relenza, and Tamiflu are neuraminidase inhibitors. Neuraminidase is an enzyme that cleaves sialic acid—a carbohydrate on the surface of cells. In the context of the flu virus, this cleavage promotes the release of new viral particles. Neuraminidase inhibitors mimic sialic acid but cannot be cleaved by Neuraminidase, suppressing the virus (Palese, 1976). On the other hand, Xofluza prevents the flu virus from replicating by blocking viral transcription (Eisfeld, 2019). Although effective, antiviral drugs are reactive measures and are not considered the first line of defense against the flu virus. The most effective method at preventing the transmission of the flu is the flu vaccine. History of Influenza - Present Day The most severe pandemic prior to the current COVID-19 pandemic was the 1918 influenza pandemic, which was caused by an H1N1 virus (History of 1918 Flu Pandemic, 2019). The pandemic occurred during World War I, and the first cases in the United States were detected at an army encampment in March of 1918. A second wave of the flu emerged at a naval facility outside of Boston in September. The second wave 83

was highly fatal, accounting for the majority of pandemic deaths and killing an estimated 195,000 Americans during the month of October alone (1918 Pandemic Influenza Historic Timeline, 2019). A third wave of flu emerged in the winter and spring of 1919 before the pandemic subsided. In total, the 1918 pandemic caused at least 50 million deaths worldwide (~675,000 in the United States) and infected 500 million people, representing nearly a ⅓ of the world’s population at the time (1918 Pandemic Influenza Historic Timeline, 2019). A new influenza, caused by influenza A (H2N2), emerged in East Asia in February of 1957 and originated in China (1957-1958 Pandemic (H2N2 Virus), 2019). This provided the first opportunity to investigate the spread of influenza in a laboratory setting, though resources for surveillance were more limited compared to today (Kilbourne, 2006). The pandemic caused an estimated 1.1 million deaths worldwide, though it was generally considered to be less severe both than the Spanish Flu and the Russian Flu, which came after (Rogers, 2019). The 1968 pandemic, first discovered in Hong Kong, was also caused by an influenza A virus, H3N2. It caused approximately 100 million deaths worldwide and 100,000 deaths in the United States (1968 Pandemic (H3N2 Virus), 2019). This pandemic was later followed by the “Russian Flu” in 1977, which marked the return of an H1N1 virus. More recently, around 2009, a novel influenza A virus, (H1N1)pdm09, emerged in the United States and quickly spread to the rest of the world. Between April 2009 and April 2010, the CDC estimated that this virus infected over 60 million people in the United States, killing between 151,700 and 575,400 people worldwide in that same time period. The pandemic primarily impacted children and young and middle-aged adults, but the impact was still less than that of previous pandemics (CDC, 2019). Influenza Vaccine Vaccines Overview The term vaccine is derived from the Latin word vaccinae, meaning cow. This is because the first vaccine was created by Edward Jenner, a British scientist and surgeon during the late 1700s, when he began trying to prevent patients from getting infected with the smallpox by giving them a case of the less-deadly cowpox. Until that time, doctors had been deliberately infecting patients with smallpox (by injecting it under the skin) to allow them to build up immunity to the disease to prevent severe infection; Jenner’s attempt was the first to create a safer way to build up natural DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Image 2: CDC Ad for 2021 National Influenza Vaccination Week (NIVW) December 5th – 11th, 2021. Image Source: CDC

immunity (Baxby, 1999). The goal of any vaccine is to allow the body to safely learn what a certain pathogen “looks like” and build an adaptive immune response to it. The role of B cells is to produce antibodies to bind to the target pathogen and memory B cells to mobilize a quicker response upon a subsequent infection. In addition, T cells work to destroy cells infected with it the virus or signal other immune cells to mount an effective response. By artificially stimulating adaptive immunity, rather than stimulation via infection by a pathogen, is referred to as vaccination. This word alludes to Jenner and his work with cowpox; Jenner has been hailed one of the fathers of germ theory (Pasteur, 1881). Vaccines can be prophylactic (or preventive, meaning that they prepare the body to fight off an infection that might occur later) or therapeutic (meaning that they teach the immune system what to fight when the body might already be infected, as is the case with the rabies vaccine (CDC, 2021) or the cancer vaccines that are being developed (Guo et al., 2013). There are many kinds of vaccines, and they come in many different forms: some use attenuated/ weakened versions of a pathogen, dead/ inactivated versions of a pathogen, pieces of a pathogen, or some sort of carrier for genetic material to cause the host’s cells to produce the pieces of the pathogen that the immune system should target. Additionally, some vaccination protocols require different numbers of treatments/injections (CDC, 2018). Nonetheless, vaccines have truly revolutionized modern medicine, saved countless lives, and have helped nearly eradicate many diseases that plagued us for so long, including Polio (WHO, 2021). History of Influenza Vaccination The history of influenza vaccination has a rather

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recent start; it wasn't until 1933 that the virus was first isolated. English scientists Wilson Smith, Sir Christopher Andrews, and Sir Patrick Laidlaw isolated influenza A virus from nasal secretions of infected patients and successfully infected ferrets (Hannoun, 2013; Barberis et. al, 2016). In 1936, American virologist and epidemiologist Thomas Francis Junior successfully isolated influenza B virus (Hall, CDC). In the same year, Macfarlane Burnet successfully grew influenza virus on the chorio-allantoid membrane of embryonated hen eggs (Barberic et. al, 2016). Following this, in 1936, the first neutralized antibodies generated by human influenza virus infection were isolated (Barberis et. al, 2016). During the 1930s, there were several further developments, including the inactivation of the virus by formalin and virus purification through high-speed centrifugation (Barberis et. al, 2016). These led to the creation of early forms of influenza vaccine, and the first clinical trials were conducted in the mid-1930s. In 1938, Jonas Salk and Thomas Francis Junior managed to protect US military forces with influenza vaccines, research that would culminate in Salk’s development of the polio vaccine in 1952 (Barberis et. al, 2016).

"Climate change is particularly devastating for the 100 million people, or 2% of the world’s population, who are homeless."

The 1940s saw the first widespread vaccine with the objectives of protecting against disease and achieving high vaccination rates to ensure protection in unvaccinated people. The first vaccine was an inactivated, monovalent vaccine. Studies between 1942 and 1945 led to the discovery of influenza mismatch, a phenomenon that arises when the vaccine does not provide protection against the influenza strain that is widely circulating and causing the current seasonal epidemic (Barberis et. al, 2016). Thus, in 1944 and 1945, a bivalent vaccine was manufactured and widely distributed that contained influenza A and B strains inactivated with a formalin (aqueous formaldehyde)

treatment (Hannoun, 2013). Wendell Meredith Stanley, an American biochemist, developed a detailed preparation and purification of influenza virus vaccine that was produced using embryonated hen eggs (Hannoun, 2013). These improvements in production, strain selection, and safety led to improved performance of the influenza vaccine.

"The production of fluc vaccines is essentially a yearround process and involves a variety of global and domestic parties."

In the 1950s, following pandemics and the discovery of new influenza strains, the World Health Organization (WHO) created a system to conduct surveillance to observe, predict, and monitor flu strains to prevent virus mismatch (Barberis et. al, 2016). The discovery of new subtypes required vaccines to cover new and different strains depending on the relative prevalence of influenza subtypes. In 1968, trivalent inactivated vaccines were first developed to provide increased coverage, and split/subunit vaccines helped decrease the risk of adverse reactions, particularly in children (Barberis et. al, 2016). Split/subunit vaccinations consist of viruses that are degraded into viral particles using detergents (O’Gorman et. al, 2015). These split vaccines can elicit a potent immune response in previously exposed individuals with increased safety and lower rates of adverse reaction (O’Gorman et. al, 2015). The major downside of split vaccines was that they were seen to be less immunogenic than whole virus vaccines - that is, they do not prompt as large of an immune response. Thus, in the 1970s, genetic reassortment of influenza vaccines enabled vaccine strains to grow faster in embryonated hen eggs (Barberis et. al, 2016). Subunit vaccines soon followed, containing only the surface antigens of the influenza virus, hemagglutinin (HA) and neuraminidase (NA). Surveillance systems such as that created by WHO monitor circulating strains and their respective HA NA variants to ensure adequate vaccine coverage (Barberis et. al, 2016). Today, research has shifted to better predicting strains of influenza that could be circulating, developing a universal influenza vaccine that could protect against all influenza virus strains regardless of antigenic drift, and identifying sustainable ways to rapidly meet the global demand for influenza vaccines particularly when facing a global pandemic (Barberis et. al, 2016). Production and Manufacturing of Different Vaccines The production of flu vaccines is essentially a yearround process and involves a variety of global and domestic parties. The World Health Organization

(WHO) hosts two annual meetings with relevant advisory groups – such as the FDA and vaccine manufacturers – to review important influenza data. This includes the results of flu samples collected by the CDC year-round and other laboratory data which is used to determine what strains of flu may be circulating or most serious (CDC, 2021). WHO makes a recommendation about what viral strains to include in the flu vaccine, but ultimately, the governing medical body of each country – which is the FDA in the United States – will make the final decision about what strains to protect against (WHO, 2022). In 2022, the first of these annual meetings was held in late February, although vaccine manufactures may have begun growing strains for vaccines as early as January. It may seem shocking that this year’s flu vaccine is already being produced, but the CDC estimates that it takes nearly six months to produce enough flu vaccine for the general population. All flu vaccine production is handled by private manufacturers in the United States (CDC, 2021). There are four main types of flu vaccines, and they are manufactured in two different ways. The Quadrivalent flu vaccine is the primary formulation which uses inactivated viruses and protects against two type A strain flu viruses and two type B strain flu viruses. Different administration methods and formulations of the Quadrivalent vaccine can be administered to anyone six months or older. The Jet Injector is a method of administering the Quadrivalent flu vaccine which uses a high-pressured stream of liquid powered by compressed gas or springs. The Jet Injector can be administered on people between the ages of 18 and 64. The High-Dose Quadrivalent vaccine is for those 65 years or older. It contains four times more of the antigen than the regular Quadrivalent vaccine, which is what builds protection against the virus. The Adjuvanted vaccine is also for those 65 years or older and includes an adjuvant, which increases the immune response to the vaccine. Therefore, less vaccine is needed per dose for the same effect and more vaccines can be made using less resources (CDC, 2021). These vaccines can be produced either through a cell-based process or a recombinant process. In the cell-based process, candidate vaccine viruses are injected into mammalian cells, allowed to incubate so the candidate vaccine viruses multiply. Then, the candidate vaccine viruses are extracted and refined, and used in the vaccine. Because these vaccines are produced using mammalian cells, they have shown greater protection against

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Image 3: Figure 3: The flu vaccine Image Source: Wikimedia Commons

the virus. The cells used to create the vaccine can also be frozen and stockpiled so, in case of a pandemic, vaccine production can be jump started. Recombinant vaccines involve genetically modifying a virus to deliver the “instructions” for producing the flu antigen into a cell where it is then grown, collected, and purified. For all vaccines, anyone outside of the FDA-approved age range or who has had severe reactions to the vaccine or any of its ingredients should not get the vaccine. The CDC does not recommend any one vaccine over another (CDC, 2021). The nasal spray vaccine is also known as the Live Attenuated influenza vaccine (LAIV). It is an egg-based flu vaccine, which means it is produced first by candidate vaccine viruses (CVVs). The CVVS are injected into fertilized eggs and allowed to incubate for several days so the CVVs can replicate. The fluid containing the CVVs is then extracted from the eggs and the viruses are weakened, allowing for use in the nasal spray vaccine. The LAIV is administered from a health provider via mist. Half the dose is sprayed into one nostril, and the other half into the other (Immunization Action Coalition, 2021). The nasal spray vaccine is effective for most nonpregnant people between the ages of 2 and 50 (CDC, 2021). Those with weakened immune systems, who have had a severe allergic reaction to a past flu vaccine, children receiving aspirin- or salicylate-containing medications, people with cochlear implants, those with an active cerebrospinal fluid leak, and those without a spleen should not receive LAIV. One should also take precaution when receiving the LAIV if they are ill. The nasal spray flu vaccine is as effective as inactivated flu vaccines for most strains; however it is slightly less effective against the H1N1 strain (CDC, 2021). While the nasal spray vaccine increases vaccination costs, it is very effective in reducing the amount of healthcare necessary for flu-related illnesses (Tarride et al., 2012).

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Tracking and Surveillance To know which vaccine to produce, vaccine strain patterns of emergence, virulence, and severity must all be tracked. Many actors contribute to this effort. On a global scale, the Global Influenza Surveillance and Response System (GISRS) is coordinated by the World Health Organization (WHO) and endorsed by many national governments. GISRS fosters global confidence and trust and is an example of success of commitment to a global public health model. Its mission is to function as a “global mechanism of surveillance, preparedness and response for seasonal, pandemic, and zoonotic influenza; global platform for monitoring influenza epidemiology and disease; and a global alert for novel influenza viruses and other respiratory pathogens” (Global Influenza Surveillance and Response System (GISRS), n.d.). The GISRS was founded in 1952 and was adopted by the Pandemic Influenza Preparedness Framework (PIP Framework) in 2011. These actions acknowledge the importance of surveillance in preparing for influenza strain emergences. The GISRS is a complex network that tests clinical samples, reports the positive results to the WHO, and provides influenza viruses to WHO Collaboration Centers (Ziegler et al., 2018). Today, it is comprised of 150 established laboratories, 142 National Influenza Centers, 6 WHO Collaborating Centers, 4 Essential Regulatory Laboratories, and 13 H5 Reference Laboratories (Ziegler et al., 2018) in 114 countries representing 91% of the world’s population (Broor et al., 2020). The GISRS network is a platform for systematic testing for RSV (respiratory virus) associated with respiratory illnesses and disciplined global reporting (Broor et al., 2020). On a domestic level, the Center for Disease Control (CDC), the Food and Drug Administration (FDA) and the Surgeon General are all important actors in the United States’

effort to prepare for and adapt to each flu season. The broad CDC goals are to “monitor and assess influenza virus and illness, .. support surveillance and response capacity, improve vaccine … interventions, and … enhance prevention and control policies” (CDC, 2020). Additionally, the CDC is the leading body that informs healthcare providers and public about influenza updates, and prevention and control measures. They connect with businesses, schools, and communities to help plan for flu threats (CDC, 2020). The FDA is responsible for ensuring that the supply of flu vaccines and flu antiviral drugs is safe and effective (Commissioner, 2020b). They are also crucially involved in ensuring supply and distribution of the flu vaccine. They work to certify and approve new vaccines and treatments are safe for the public and conduct roll out and distribution efforts. Since engaging in flu vaccine efforts is a year-round effort, the FDA collaborates with the CDC and WHO to first identify and select the focused most likely strain for the upcoming season, produce materials for new vaccines in labs, and ensure new vaccines meet appropriate safety and efficacy standards (Commissioner, 2020a). Lastly, the surgeon general is the “chief medical doctor and health educator” for the (Definition of Surgeon General - NCI Dictionary of Cancer Terms - National Cancer Institute, 2011). They are tasked with communicating scientific information to the American public on how to improve health and lower risk of infection. The Surgeon General can issue health warnings on consumer products, vaccines, or current health risks such as the flu and flu vaccine (“Surgeon General of the United States,” 2021). As demonstrated, there are many actors, on the global, national, and community levels, that mobilize ahead of each flu season. Prediction of upcoming strains, accurate vaccines, and effective communication with the public will ensure public health safety and minimize incidence of flu infection, mortality, and morbidity. Barriers to Vaccination Vaccinations are sometimes classified as one of the greatest achievements of public health (Larson 2014), yet in recent decades the phrase “vaccine hesitancy” has also become more commonplace. More than ever before, globalization plays a key role in allowing people all over the world to share their concerns regarding vaccine safety, and the conversation is made additionally complex by an expansion in vaccination options (Larson 2014). Previously the delineation was between 87

“pro-” and “anti-” vaccination; yet, this language was deemed polarizing and unproductive and therefore shifted to describing the newer term of vaccine hesitancy. The World Health Organization Strategic Advisory Group of Experts on Immunization (WHO SAGE) defines vaccine hesitancy as “the acceptance of vaccines on a continuum between demand and no demand ranging from accepting all vaccines to accepting no vaccine” (Schmid 2017). Due to the rising numbers of people who identify within this broad category, research on the topic has also expanded. Studies including data from countries across the world have shown that there are multiple influences which carry varying importance to certain communities, depending on the values of the culture and the vaccine being discussed. For example, in Greece, the education of one’s siblings and father was found to be an important marker for determining one’s hesitancy, whereas in Nigeria, the approval or disapproval of parental guardians was a deciding factor (Larson 2014). It is worth noting that across risk groups, barriers for seasonal and pandemic influenza vaccination were similar in content and reported frequency (Schmid 2017). WHO SAGE has developed a model for categorizing these different factors. Specifically, the individual/social and contextual levels contain valuable information that will be discussed in this paper. It should be noted that the following research is based on countries in WHO regions, primarily Western samples. On the micro-level, there have been individual/social psychological and physical barriers identified. The main psychological barriers include utility, subjective norm, and attitude, among others. The utility barrier is a comparison of the vaccine’s proposed benefits (including protection from disease and herd immunity) versus the possible risks (including vaccine-adverse events, contracting the disease, and even anticipated regret of not receiving the vaccine) (Schmid 2017). The subjective norm barrier identified that when social pressure to receive the vaccine is high, so is the uptake of vaccination, and attitude research showed that every risk group had lower vaccination uptake if the vaccine was not believed to be trusted or effective, therefore making it a major psychological barrier (Schmid 2017). The main contextual physical barriers to influenza vaccination were cues to action and previous healthcare system interaction. A lack of cues to action (i.e., medical professionals or relatives recommending vaccination) and previous interactions with one’s healthcare system such as through yearly check-ups were strongly correlated with less vaccine uptake. Interestingly, DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Image 4: Inoculation with an annual flu vaccination may proves beneficial to a spectra of age groups. It is most beneficial amongst high-risk groups such as children, students, and the elderly. Image Source: CDC

access barriers such as political, geographical, or economic issues, or reliability of vaccination supply were not identified as a physical barrier to vaccination in this research (Schmid 2017). Furthermore, socioeconomic status (SES) and level of knowledge were identified as major contextual barriers (Larson 2014). For the SES barrier, low SES was identified in multiple countries as being a barrier, yet the factors for why it was an obstacle varied. For example, in the United States, low SES was linked to trust issues with healthcare providers, whereas in Nigeria, it was primarily linked to low education (Larson 2014). Level of knowledge was also an important barrier because it was identified that in all risk groups as well as in the public, vaccination uptake decreased if knowledge concerning influenza and the vaccine was low (Schmid 2017). One can determine from this research that there are a variety of barriers leading to influenza vaccine hesitancy, but they are connected to different factors across countries and there is no “universal algorithm” with which to assess them all (Larson 2014). Further research should examine countries outside WHO regions with greater diversity in barriers, thereby creating a more comprehensive understanding of influenza vaccine hesitancy. Why do we need a new flu vaccine each year? Seasonal influenza causes 290,000 to 650,000 respiratory deaths each year (Madsen & Cox, 2020). This number increases when a novel influenza virus strain emerges and which the humans are immunologically naïve to. However, vaccination plays an important role in reducing this number. Seasonal flu vaccines are produced every year. Annual vaccines are based on predictions on which strain will be most prevalent that year. As mentioned earlier, influenza vaccines in the United States are “quadrivalent” and provide protection against two influenza A strains H1N1 and H3N2 and two influenza B strains (CDC, 2021). But despite the quadrivalent coverage, a new vaccine is still required every year. There are two main reasons

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for this; first, a person’s immune protection from vaccination declines over time so annual vaccines will promote protection, and second, flu viruses are constantly changing, and a different strain is dominant each year, so a different vaccine is necessary each flu cycle (CDC, 2021). The rapid evolution of influenza and the ease with which it increases its antigenic diversity are the barriers that necessitate annual flu vaccines. While it would be ideal to have a universal and one-time flu vaccine, scientist must first identify other drawbacks of the current flu vaccine campaign. The main issues are that vaccines target variable proteins and time is needed to update vaccines. Consequently, it takes about 6-7 months to produce each seasonal flu vaccine (Webby & Sandbulte, 2008), which means predictions must occur months out of vaccine implementation. Predictions so far in advance can be inaccurate, risking the development of a vaccine that does not defend against the dominant strain.

"...flu viruses are constantly changing, and a different strain is dominant each year, so a different vaccine is necessary each flu cycle."

Conclusion The benefits of the flu vaccine are impressive, and its development has saved countless lives— particularly among those in high-risk groups such as children or the elderly. While flu season still poses serious health risks, widespread vaccine use as well as antiviral treatments have significantly reduced the number of deaths and prevented serious flu pandemics from sweeping the globe again. As the world continues to grapple with the COVID-19 pandemic, it is easy to draw parallels between the path of influenza and COVID. Notably, COVID-19 variants have increased the need for multiple vaccines and booster shots much like the annual flu vaccine. Most importantly, however, flu and COVID vaccines remain at the forefront of the world’s battle against these pandemics.

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& Denker, M.-L. (2017). Barriers of Influenza Vaccination Intention and Behavior – A Systematic Review of Influenza Vaccine Hesitancy, 2005 – 2016. PLOS ONE, 12(1), e0170550. https://doi. org/10.1371/journal.pone.0170550 Sederdahl, B. K., & Williams, J. V. (2020). Epidemiology and Clinical Characteristics of Influenza C Virus. Viruses, 12(1), 89. https://doi. org/10.3390/v12010089 Webby, R. J., & Sandbulte, M. R. (2008). Influenza vaccines. Frontiers in Bioscience: A Journal and Virtual Library, 13, 4912–4924. https://doi. org/10.2741/3050 WHO. (2021, April 22). Counting the impact of vaccines. https://www.who.int/news-room/ feature-stories/detail/counting-the-impact-ofvaccines WHO. (2022, February 21). WHO Consultation on the Composition of Influenza Virus Vaccines for Use in the 2022-23 Northern Hemisphere Influenza Season. https://www. who.int/news-room/events/detail/2022/02/21/ default-calendar/who-consultation-on-thecomposition-of-influenza-virus-vaccines-foruse-in-the-2022-23-northern-hemisphereinfluenza-season World Health Organization. (n.d.). Global Influenza Surveillance and Response System (GISRS). Retrieved October 14, 2021, from http s : / / w w w. w h o. i nt / i n it i at ive s / g l ob a l influenza-surveillance-and-response-system Ziegler, T., Mamahit, A., & Cox, N. J. (2018). 65 years of influenza surveillance by a World Health Organization‐coordinated global network. Influenza and Other Respiratory Viruses, 12(5), 558–565. https://doi.org/10.1111/irv.12570

Paules, C. I., Marston, H. D., Eisinger, R. W., Baltimore, D., & Fauci, A. S. (2017). The Pathway to a Universal Influenza Vaccine. Immunity, 47(4), 599–603. https://doi.org/10.1016/j. immuni.2017.09.007 Rogers, K. (n.d.). 1957 Flu Pandemic. Britannica. Retrieved December 4, 2021, from https://www. britannica.com/event/1957-flu-pandemic Sautto, G. A., Kirchenbaum, G. A., & Ross, T. M. (2018). Towards a universal influenza vaccine: Different approaches for one goal. Virology Journal, 15(1), 17. https://doi.org/10.1186/ s12985-017-0918-y Schmid, P., Rauber, D., Betsch, C., Lidolt, G.,

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Innovations in Cancer Treatment STAFF WRITERS: TYLER CHEN ‘24, VICTORIA FAUSTIN ‘23, VAISHNAVI KATRAGADDA ‘24, ASHNA KUMAR ‘24, ARSHDEEP DHANOA ‘24, SARAH BERMAN ‘25, STEPHEN ADJEI ‘25, CAROLINE CONWAY ’24, SOYEON (SOPHIE) CHO ‘24, JENNIFER DO-DAI ‘25, SHOAIB JAMIL ‘25, CALLIE MOODY ‘24 TEAM LEADS: AYUSHYA AJMANI ’24, SREEKAR KASTURI ’24, ANAHITA KODALI ‘23

Cover Image: Histological slide of cancerous breast tissue that has been stained with H&E and magnified to 200x. The pink “riverways” are normal connective tissue, and the blue is cancer cells. Image Source: Wikipedia Commons

Sociocultural Overview of Cancer Racial and Ethnic Disparities in Cancer Treatments Racial and ethnic disparities persist within the United States. Unfortunately, these disparities have the potential to detrimentally influence healthcare accessibility and the quality of medical care. Cancer treatment is no exception. According to a 2002 study published in the Journal of the National Cancer Institute, there are two dimensions of treatment that can contribute to racial disparities in cancer treatment outcomes: racial differences in treatment efficacy and the failure to provide suitable care (Shavers & Brown, 2002). Although the authors found limited evidence surrounding racial/ethnic differences in treatment efficacy amongst patients with similar disease stage, grade, and comorbidities, it was overwhelmingly reported that racial disparities significantly prevailed in cancer treatment itself (i.e. the receipt of definitive primary therapy,

adjuvant therapy, conservative surgery, followups etc.). Uppal et al. (2017) evaluated similar racial/ ethnic disparities in guideline-based care in regards to locally advanced cervical cancer and their relationship to hospital case volume. After the completion of their retrospective cohort study, it was determined that racial and ethnic disparities in the delivery of guideline-based care are the highest in high-volume hospitals (Uppal et al., 2017). Graboyes et al. reported a similar phenomenon in their 2018 study, in which they investigated racial and ethnic disparities in travel for head and neck cancer treatment and the impact of travel distance on survival. Long distance travel for healthcare was not only often associated with treatment at academic and highvolume hospitals, but also improved primary patient outcomes on multivariable analysis (as compared to short distance travel). Black and Hispanic patients with Medicaid insurance who had nonsurgical treatment were determined to be DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

less likely to travel long distances for treatment, thereby negatively influencing their potential quality of care and overall likelihood of improved primary outcome (Graboyes et al, 2018). Data collected by Yedjou et al. (2017) mirrors this finding, as they found that cancer mortality was higher for both Black men and women compared to White men and women, with Black individuals having a disproportionate 33% higher risk of dying of cancer than White individuals. While it is imperative to note that this outcome is likely influenced by innumerable multi-faceted factors (including lifestyle, environment, age, genetics, family history, personal health history, and diet) it is also necessary to consider the negative consequences of racial/ethnic disparities in medicine. These racially and ethnically-driven inequalities can be attributed to a large number of clinical and non-clinical risk factors, ranging from lack of medical coverage and barriers to early detection and screening to more advanced stages of disease at diagnosis amongst minorities and unequal access to improvements in cancer treatment. Understanding these risk factors may offer a potential explanation for the widely observed differences in cancer treatment and survival between people of color and white individuals. Over time, it has become increasingly apparent that equality in cancer treatment can yield significantly better cancer outcomes, and it is crucial that we, as a society, develop new strategies to address this ubiquitous issue, promoting cancer prevention, improving survival rate, and ultimately improving the health outcomes for racial and ethnic minorities. Socioeconomic Disparities While some disparities in cancer treatment have been decreasing in the past few decades, socioeconomic inequities are unfortunately widening. This effect is clear on both large and small scales, with the world’s poorest countries experiencing mortality rates two times higher than their richer counterparts for some cancer types. Even on an individual or countylevel, health disadvantages and access to less effective treatments result in a disproportionate burden of cancer deaths upon those of a lower socioeconomic status (SES). Reducing these disparities and healthcare disadvantages by improving access to treatments could actually result in a decrease of up to one third of cancer deaths in Americans aged 25 to 74 (Siegel et al., 2019). The skewed distribution of cancer deaths along socioeconomic lines is directly attributable WINTER/SPRING 2022

to disparities in treatment, as studies have continuously shown that those of lower SES are often treated with less aggressive or less advanced treatment options. Many of the disparities based on SES have actually been increasing for preventable cancers, as treatments vary greatly between patients of varied SES (Siegel et al., 2019). Men who live in areas of lower SES, for example, were less likely to have been treated with prostatectomy or radiation than men from higher SES areas, despite these being the most effective treatments. Instead, those of lower SES were given hormone therapy. These less effective treatments often mean higher mortality among individuals of lower SES (Byers et al., 2008). An interesting case study exemplifying these disparities can be found in studying breast cancer. Women from areas of lower SES with localized breast cancer were more likely to undergo mastectomy than those from higher SES areas. Patients of lower SES who received lumpectomies, surgical operations to remove lumps from the breast, were often less likely to have initial radiotherapy following these procedures. For breast cancers that were estrogen/ progesterone receptor-positive, patients from lower SES areas were also less likely to receive antiestrogen therapy (Byers et al., 2008). After breast-conserving surgery, women who were poor or near poor were also less likely to receive sentinel lymph node biopsies and radiation and were less likely to receive any sort of axillary surgery. Interestingly, with treatments like aromatase inhibitors, there were no significant differences in usage based on SES; however, the more effective aromatase inhibitors were often reserved for patients of higher SES (Dreyer et al., 2017). As these more effective and aggressive therapies are often used solely for patients of higher SES, patients of lower SES suffer greater mortality rates. Necessary proper access to treatment is regardless of SES (Siegel et al., 2019).

"Women from areas of lower SES... were more likely to undergo mastectomy than those from higher SES areas."

Gender- and Sexuality-Based Disparities in Cancer Treatment Some disparities in cancer treatment lie along lines of sex, gender, or sexual orientation. The sex an individual is assigned at birth can play a biological role in one’s susceptibility to cancer. For instance, one study on genetic components of lung cancer determined that about 1160 genes in smoking patients with lung cancer had expression patterns that consistently varied according to the patients’ sexes. This is particularly interesting given that female smokers tend to exhibit higher immune responses than males and that among individuals who have never smoked, females are more likely than males to develop lung cancer (Davuluri et al., 2021). 92

There is troubling evidence that women tend to be treated suboptimally. For example, women with head and neck squamous cell carcinoma (HNSCC) are less likely to receive chemoradiotherapy than men with the same condition, and women with HNSCC tend to be underrepresented in chemotherapy clinical trials (Benchetrit et al., 2019). In cases of renal cancer (cancer in the lining of kidney tubules), women are more likely to undergo procedures removing a small, localized renal mass and a large portion of normal tissue around it (a procedure called radical excision), while men are more likely to undergo partial excision, or the removal of only part of a renal mass. This is concerning because women are actually more likely to have benign growths and are also more likely to have multiple diseases simultaneously, meaning minimizing surgical complications is more of a concern (O’Malley et al., 2013).

"LGBTQ+ status can influence their cancer treatment, largely due to social stigmas acting as barriers to adequate care."

This is not to say that gender bias in cancer treatment always favors men. In fact, in the case of breast cancer, men are at a disadvantage and are consistently diagnosed with more advanced stages, resulting in a need for more aggressive and expensive treatments from the moment of diagnosis. Furthermore, women tend to outlive men when comparing lifespan from the time of breast cancer diagnosis, although breast cancer mortality rates are generally comparable across genders (Nemchek, 2018). Nemchek (2018) proposes that the late diagnosis of breast cancer in men might result from less robust educational programs and might therefore be partially addressed by using breast cancer awareness resources targeted toward women to educate men about their risk. LGBTQ+ status can influence their cancer treatment, largely due to social stigmas acting as barriers to adequate care. For instance, queer, lesbian, and bisexual women are less likely than heterosexual women to regularly see a physician and get screened for breast and gynecologic cancer due to social stigmas within the .doctors office Furthermore, women from communities of marginalized sexual orientations are more likely to be dissatisfied with health care professionals during cancer treatment. More than half of trans individuals report negative health care experiences, and they are consequently substantially less likely to seek emergency care. Additionally, gender-affirming hormones and/ or surgery can increase a patient’s cancer risk, making it all the more alarming that many patients receiving such treatments do not get screened for cancer as regularly as cisgender patients

(Bryson et al., 2020). Overall, while there are biological effects of sex on cancer risk that require further investigation, evidence suggests that social structures related to gender and sexuality contribute to disparities in cancer treatment, so these social norms must be addressed in order to ensure equitability in cancer treatment and, by extension, in quality of life. Immunology Overview To begin to understand the theory behind different cancer treatments, it’s important to recognize the human body’s defense mechanisms against cancerous cells and tumors. Cancer immunoediting is the primary process in which the immune system deals with tumors. It consists of three overarching stages: elimination, equilibrium, and evasion. Each corresponds to the relative level of immunogenicity, or the ability to provoke an immune response, of the tumor cells in question (Dunn et al., 2004). Elimination, also known as cancer immunosurveillance, occurs at the beginning of tumor formation, and is the stage in which the body’s immune system has the strongest response in attacking tumor cells. This elaborate immune response can be characterized into four separate phases as well. The first phase in the elimination aspect of cancer immunoediting involves initiating anti-tumor immune response. At this point, the individual’s immune system becomes alerted of the growing tumor. This occurs partly because the growing tumor disrupts the surrounding normal tissue because of the cancer cells’ stromal remodeling – a series of changes in the basic physiology of the tumor cells induced by angiogenesis, or the formation of new blood vessels, and surrounding tissue invasion that occur to ensure consistent tumor development (Hanahan & Weinberg, 2000). From here, proinflammatory molecules produced from the stromal remodeling process and chemokines released from the tumor cells attract the attention of cells in the innate immune system, leading to the immediate immune response (Dunn et al., 2004). Cells such as natural killer cells, killer T cells, dendritic cells, macrophages, γδ-cells, and others converge on the site and begin recognizing some of the tumor cells. There are many different proposed mechanisms of recognition of the tumor cells for each of these immune system cells, but regardless, what follows recognition is the production of Interferon-γ, which promotes the second stage of elimination. The production of Interferon-γ by infiltrative lymphocytes in the first phase of elimination

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has several downstream effects that define the second stage of elimination. The first effect is the increased production of the chemokines CXCL9, CXCL-10, and CXCL-10 within the tumor cells in response to higher levels of Interferon-γ, leading to more cells in the innate immune system to converge on the tumor site (Dunn et al., 2004). This in turn leads to a higher production of Interferon-γ, and the positive feedback loop ensues. A similar positive feedback loop is also seen through the increased production of Interleukin-12 from the higher production of Interferon-γ, which thus stimulates tumorinvasive natural killer cells to produce more Interferon-γ, and so on and so forth (HodgeDufour et al., 1997). Additionally, higher levels of Interferon- γ lead to higher levels of anti-tumor processes as well. Several Interferon-γ dependent processes have antiproliferative, proapoptotic, and/or angiostatic effects – all of which promote tumor death (Coughlin et al., 1998). In addition to these direct tumoricidal Interferon-γ dependent processes, Interferon-γ-activated macrophages and natural killer cells can also kill tumor cells through TRAIL (TNF-Related Apoptosis Inducing Ligand) related processes and perforindependent processes, respectively (Dunn et al., 2004). The resulting dead tumor cells serve as a plentiful source of tumor antigen for the immune system, leading to the next phase of elimination. In the third stage, the tumor antigen supply leads the way for tumor-specific adaptive immune responses. Immature dendritic cells that first arrive at the tumor site via the initial immune response then become activated either by interacting with cytokines produced in the ongoing innate immune response, or by interacting with tumorinfiltrating natural killer cells (Gerosa et al., 2002). From here, the activated dendritic cells consume the tumor antigen, and then migrate to the draining lymph node, leading to the activation of naïve tumor-specific Th1 CD4+ T cells, which then leads to the development of tumor-specific CD8+ cytotoxic T cells due to the cross-presentations of tumor antigen peptides on the MHC class I molecules on the dendritic cells (Dunn et al., 2002). This development of adaptive immunity gives way to the fourth step of elimination, which should theoretically lead to the elimination of the tumor. In the fourth stage, the tumor-specific CD4+ and CD8+ T cells move towards the tumor site, helping kill the tumor cells. Theoretically speaking, the host should have the capacity to eliminate all tumor cells at this point, but less immunogenic tumor cells may evade this final adaptive immune response, progressing into the equilibrium stage.

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During the equilibrium stage, the back-andforth between increasing selective pressure of the adaptive response and the Interferon-γdependent processes and the tumor cells that withstood the initial immune response continues (Dunn et al., 2002). During this time, the remaining tumor cells are unstable and undergo many genetic mutations in hopes of withstanding the continuously improving immune response. As within the elimination phase, the equilibrium phase is characterized by Darwinian selection, in which the most “fit” tumor cells withstanding the immune response will continue to replicate (Kim et al., 2007). This period of dynamic equilibrium is the longest phase (lasting for years), as tumor cells continue to improve while the immune system adapts. However, those tumor cells that do manage to improve and withstand the immune attack will emerge out of the equilibrium phase and into the last phase: escape. In the escape phase, tumor cells that have been selected for throughout the elimination and equilibrium phases can now exist and grow within a normal immune system and can thus grow in an uncontrollable manner. There likely were a series of different genetic and epigenetic changes within these selected tumor cells that allow them to circumvent the innate and/or the adaptive immune response to grow progressively. Several of the immunoevasive strategies resulting from mutations during the equilibrium phase have likely accumulated to produce a tumor cell capable of malignancy against a powerful immune environment (Dunn et al., 2002). One of these strategies is the development of immunosuppressive cytokines or the use of immunosuppressive mechanisms involving T cells – directly impeding the development of anti-tumor immune responses (Khong & Restifo, 2002). Additionally, other methods of escape include changes that occur directly on the tumor level. Some of these changes reduce the level of tumor recognition by effector T cells. These changes include loss of antigen expression, loss of MHC components, shedding of NKG2D ligands, and increased insensitivity to Interferon-γ (Dunn et al., 2002). Other methods include ways for tumor cells to evade immune destruction mechanisms, such as having defects in the traditional death-receptor signaling pathways or being able to express anti apoptotic signals. Either way, at this point, the tumor cells have developed a resistance to the immune system and can proliferate and grow uncontrollably without intervention. At this point, cancer can be clinically diagnosed.

"...the tumor cells have developed a resistance to the immune system and can proliferate and grow uncontrollably without intervention. At this point, cancer can be clinically diagnosed."

Figure 1: MRI scans of breast cancer before and after treatment. Using modern imaging techniques, the initial lesions highlighted with the yellow arrows were able to lapse upon the 14 month treatment of breast cancer. Image Source: Wikimedia Commons

Different Stages of Cancer Upon diagnosing a patient with cancer, doctors use a staging system to classify the extent to which the cancer has grown and how far it has spread from its original cells. This system consists of Stages 0-4, which will be described throughout this section. There are different methods to classify what stage a tumor is in, including imaging techniques (MRI, CT, x-ray), surgery, and biopsy. Using this standardized staging system helps doctors determine a patient’s prognosis at diagnosis as well as determine a treatment plan, including possible clinical trials the patient may be eligible for. Both the American Cancer Society (ACS) and the National Cancer Institute (NCI) state that the stage determined at diagnosis is retained throughout treatment, even if the cancer progresses and spreads further, allowing researchers to track statistics such as the prevalence of specific stages of cancer at diagnosis and patient outcomes as well as compare the effectiveness of treatments in a research study. However, many oncologists will often describe cancers based on its current state of progression. During Stage 0, the cancer has yet to develop or spread. A small group of abnormal cells, or dysplasia, are localized at their initial location, not yet forming a tumor. This state where the cells display abnormal growth but are not yet invasive into other tissues or organs is also known as carcinoma in situ (CIS). The NIH does not classify this non-invasive stage as cancer because while these cells have the potential to develop into cancer, not all cases of CIS will progress into cancer. At this early stage, it is often difficult to detect these abnormal cells as CIS will usually not be visible on internal organ scans due to its small size. Cancers with more visible presentation such as skin cancer or that are screened for more often like breast or cervical cancer may be detected during Stage 0. An early diagnosis generally implies a good prognosis, as doctors can eliminate the threat of cancer before the abnormal cells progress and metastasize. Generally, the higher the stage number, the

larger the tumor is and the more the cancer has metastasized across adjacent regions of the body or the body as a whole. This classification of the anatomical extent of cancer spread is dependent upon the TNM system of staging (Cancer Staging, n.d.). The “T” category describes the extent of the tumor’s size, depth of invasion, or invasion of different structures. The “N” category indicates the absence or extent of metastasis of regional lymph nodes. Finally, the “M” category explains if there is a presence of distant metastasis (Brierley et al., 2016). The combination of TNM categories at the time of diagnosis constitutes the clinical TNM (cTNM) and analysis of the tumor biopsy comprises a pathological TNM (pTNM). The cTNM determines the overall approach to treatment, while the pTNM guides the possibility of different adjuvant therapies (Brierley et al., 2016). Stage 1 of cancer manifests differently depending on the type of cancer in question. For example, in stomach cancer, Stage I is split in subset stages. Stage 1A entails that the cancer has not yet grown past the submucosa of the gastric wall; Stage IB means the cancer has not yet grown past the muscle layer of the stomach, and it may have spread into 1 or 2 neighboring lymph nodes (Stomach Cancer: Stage 1, n.d.). As such, the most effective treatment would be surgery, possibly followed by adjuvant therapy with chemotherapy. Compared to stomach cancer, breast cancer manifests differently. Stage 1A of breast cancer means that the cancerous tumor is <2cm in diameter and has not spread outside the breast; Stage IB entails a tumor that is still <2cm in diameter, and few cancerous cells are found in nearby lymph nodes (Breast Cancer: Stage 1, n.d.). Though manifested differently in their respective bodily regions, Stage 1 of cancer entails localized tumor formation with minimal possibility of spreading malignant cells to adjacent regions. Stage 2 cancer signifies that the cancer is growing, but the cancer cells are contained within the initial site and have not fully spread to other sites (National Health Service, 2018). Within each type of cancer, the symptoms for this stage are more specific and can be divided into substages. For example, in Stage 2 breast cancer, the cancer is growing and contained in the breast or only within the nearby lymph nodes (National Breast Cancer, 2020). Stage 2A for breast cancer is determined by the cancer having spread to the lymph nodes paired with no tumor or a tumor less than 2cm wide, or the cancer not having spread to the lymph nodes paired with a tumor 2-5cm wide. Stage 2B is more advanced and diagnosed

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by the cancer having spread to the lymph nodes and a tumor 2-5cm wide, or the cancer not having spread to the lymph nodes and a tumor 5cm wide. Similarly, for colon cancer, stage 2A occurs when the cancer is contained within the muscle layer of the colon and the serosa, or the outer lining of organs in the chest, and stage 2B occurs when the cancer has spread to the visceral peritoneum, which covers the surface of the abdominal organs (National Cancer Institute “Stage II Colorectal Cancer”, 2020; Merkel et al., 2001). Finally, stage 2C occurs when the cancer is starting to spread to different organs. These examples demonstrate that the sub-stages within stage 2 are determined by specific indicators of the degree to which the cancer has spread to other regions or developed larger tumors. Stage 3 cancer is often defined as having spread around the local area and/or distant lymph nodes, but not yet metastasizing in distant tissues. Many patients are diagnosed at this state. Generally, 3 substates are defined slightly differently based on the cancer type. In lung cancer, state 3A means the cancer is on one side of body only. This state has approximately a 36% chance of 5-year survival (Willow). State 3B indicates that the cancer has spread to both sides of the body and has a 26% chance of 5-year survival. State 3C describes that the cancer has spread throughout the chest, often accompanied by a persistent or changed cough, trouble breathing, and chest pain. This state has approximately a 1% chance of 5-year survival (Willow). Stage 4 cancer is referred to as metastatic cancer, because it means that the cancer has spread from the origin to various distant parts in the body. When a cancer metastasizes to a different part of the body, it is defined by the original location. For example, if breast cancer were to metastasize to the brain, it is still considered breast cancer instead of brain cancer. Many Stage 4 cancers have subcategories, such as Stage 4A or Stage 4B, which indicate the degree to which the cancer has spread throughout the body. The 5-year survival rate for people with breast cancer, for example, that has spread to distant areas of the body is 28%. On the other hand, the 5-year survival rate for mesothelioma that has spread to distant areas is 7%. Current Treatments Current treatments for cancer fall into two major categories: chemotherapy and surgery. Chemotherapy began as monotherapy drugs that targeted single types of cancer and only lasted

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for a limited amount of time (Pearson et al., 1949). However, starting with choriocarcinoma in 1958, the combination of multiple drugs increased the effectiveness of chemotherapy as a standard treatment for cancer, since different drugs can target different phases of the cancer cell’s cycles (Li et al., 1958; Einhorn & Donohue, 1977). Currently, chemotherapy is used to treat patients with advanced types of cancer such as choriocarcinoma, lymphoma, acute leukemia, and more. Surgery, which aims to remove the tumer, emerged in the 20th century for solid tumors such as sarcomas, carcinomas, and lymphomas (Arruebo et al., 2011; National Cancer Institute “Solid Tumor”, 2020). Heading into the 21st century, non-invasive techniques in addition to the more invasive Halstedian techniques were invented, allowing for more conservative surgery techniques to remove tumors and minimizing functional damage on organs (Arruebo et al., 2011; Phillips et al., 1992). Radiation therapy, or radiotherapy, began from Marie Curie’s discoveries and developed techniques such as linac radiotherapy, which specifically concentrates X-rays to the site, and computed tomography (CT) guided radiotherapy, which reduce toxic effects on the body by concentrating radiation on the CT-generated 3-dimensional reconstructions of tumors (Arruebo et al., 2011; Hall, 2006). Furthermore, image-guided radiation therapy (IGRT) and image-guided adaptive radiation therapy (IGART) use 4-dimensional video reconstructions of tumor movements as patients breathe or move around (Timmerman & Xing, 2009).

"...chemotherapy can be traced back to the ancient Egyptians..."

Chemotherapy Utilizing chemical agents to interact with cancer cells, chemotherapy is a distinct approach to cancer treatment. The practice itself has existed for thousands of years: chemotherapy can be traced back to the ancient Egyptians who combined barley, pigs’ ears, and other chemical agents to treat gastric and uterine cancers (“Introduction to Chemotherapy”, n.d.). Nonetheless, the application of chemical agents as robust forms of cancer treatment emerged following the research conducted by German chemist Paul Ehrlich in the early 20th century (DeVita & Chu, 2008). Burgeoning forms of chemotherapy subsequently began to rival the dominant forms of cancer treatment at that time—namely surgery and radiation therapy.

Figure 2: Diagram of chemotherapy treatment on cancerous cells. After the cancerous cells are surrounded by the chemotherapy drug, electrical impulses open the cell surface so that the drug can center. Upon the cell closing, the drug is trapped inside the cell. The drug damages the DNA inside of the nucleus of these cells and prevents them from dividing and growing. Image Source: Wikimedia Commons

"Studies specific to COVID-19 in patients have found that the median age of infected patients is around 56 years..."

In the early decades following Ehrlich’s research, chemotherapy was generally restricted to model development. Chemical drug discovery faced immense limitations in this stage: the vast repertoire of known chemicals had to be gleaned for suitable drug candidates, and the accessibility to clinical facilities to handle these chemicals had to be addressed (DeVita & Chu, 2008). Trials and tribulations to find substantive modeling systems lasted until the early 1940s when the first discoveries were made. A study of vesicant war gases employed by armies during World War II, such as sulfur mustard and nitrogen mustard, revealed that exposed soldiers demonstrated markedly less bone marrow and lymph nodes. Scientists in the U.S. experimented with nitrogen mustard gas on mice bearing transplanted lymphoid tumors, and signs of remission convinced them to experiment on humans. Unfortunately, the investigation resulted in temporary and incomplete cancer remission on human patients (DeVita & Chu, 2008). Various institutions and academic physicians thereafter became harsh critics of chemotherapy ever functioning as a viable cancer treatment beyond palliative care. Breakthroughs in the 1960s brought chemotherapy to the forefront of cancer treatment discussions. Combination therapy, the idea of simultaneously administering a variety of drugs, tremendously improved patient outcomes from chemotherapy (Shewach & Kuchta, 2009). Cancer cells are themselves composed of mutated DNA that contribute to their aberrations from the normal cell cycle; thus, each chemical drug used for chemotherapy is only one or few genetic mutations away from becoming obsolete. Employing a combination of different chemicals at once requires that cancer cells must undergo several different mutations to prove resistant—overall decreasing the likelihood of resistance and increasing the efficacy of the chemotherapy (Shewach & Kuchta, 2009). Moreover, chemotherapy is a viable option for adjuvant therapy. Primary treatment, usually

surgery, is followed by a secondary form of therapy to mitigate chances of cancer cell survival (Definition of Adjuvant Therapy, 2011). A thematic setback to chemotherapy is the rather low specificity with which drugs can differentiate between cancerous and normal cells. Despite being comprised of mutated DNA, the genetic and metabolic framework of cancerous cells are identical to those of their non-cancerous counterparts. Novel chemotherapeutics such as angiogenesis inhibitors could address this critical challenge (DeVita & Chu, 2008). Chemotherapy as a form of cancer treatment has only burgeoned in the last half a century. The treatment demonstrates great promise in effectively reducing the lives claimed by all forms of cancer. Surgery Surgical resection of tumors is the oldest oncological treatment and is regarded as one of the most successful (Wyld et al., 2014; Singhal, 2016). However, while surgery is effective and can often completely eliminate a cancer as well as alleviate patient symptoms, there are many studies suggesting that surgery is perhaps not as effective as it needs to be (Chen et al., 2019). Some data has shown that surgery may lead to greater metastatic seeding of tumor cells. Surgical stress may also lead to inflammation, immunosuppression, and risk of ischemia or reperfusion injury, all of which may lead to increased tumor metastasis risk. Animal studies have demonstrated that surgery-induced stress results in malignant cancer growth. The body's response to surgery may also lead to an environment favorable for tumor metastasis, as the body releases increased cytokines and experiences a shift in immune cell populations. Specifically, regulatory T cells increase post-operatively and helper T cells and cytotoxic T cells decrease, allowing neoplastic cells to survive in varying degrees. Clinical trials have also shown that circulating and disseminated tumor cells increased after surgery in a variety of cancer types, including gastric, colorectal, and breast. Furthermore, anesthesia itself may lead

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to be found in five out of forty patients. These procedures using fluorescence are safe, as they do not expose patients to dangerously high levels of ionizing light. However, more research still needs to be done prior to the clinical approval of this method (Singhal, 2016). Eventually, using multimodal treatments without surgery might result in the best outcome for the patient; in the meantime, medical professionals rely on improvements in surgical techniques (Wyld et al., 2014).

to greater cancer incidence. Some inhalational anesthetics, like isoflurane, have been shown to accelerate tumor progression. Renal cell carcinoma tumor cells, for example, migrate more rapidly after being exposed to 2% isoflurane. Intravenous anesthetics also pose problems, with compounds like ketamine reducing the activity of natural killer cells and doubling the survival and metastasis rate of cancers like lung cancers (Chen et al., 2019). Another problem with surgical treatment is the risk of cancer recurrence. Depending on the tumor type, recurrence rates range between 8 and 50% across the US, especially since some tumors are difficult to cleanly resect. However, technological advancements in fluorescence are decreasing this issue. Previously, surgeons had to rely solely on visual inspection and finger palpation to decide which cells needed to be resected, leading to many cases where tumors became recurrent. By fluorescently labeling cells, the decisions made intraoperatively are made easier, allowing surgeons to find all tumor cells, including those that metastasized. Several possible fluorescent contrast agents are being studied in trials now, such as EC17 and aminolevulinic acid, both of which are agents that are delivered systemically and accumulate in tumor cells. Other agents that target tumors specifically, whether through having an increased permeability in the tumor environment or targeting tumor cells through receptor-mediated binding, would work as well. Improved detection technology is also required, of course, to find the fluorescently labeled cells during a procedure. Some studies done with aminolevulinic acid fluorescence during malignant glioma resections have proven successful, with control surgeries having higher residual tumor volumes when performed solely under white light. Another study looking at the effectiveness of fluorescence during hepatic resection found that using NIR fluorescence allowed superficially located lesions

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Figure 3: Illustration of the removal of cancerous tissue from the breast during the 1900’s. Since many modern techniques for fluorescently labeling the malignant cells weren’t present in the 20th century, surgeries performed were often invasive and scarring. Image Source: Wikimedia Commons

Effect of Advancements in Imaging techniques to identify Cancer Imaging techniques are extremely important for cancer detection. Not only can medically imaging aid physicians and radiologists in determining early treatment options for patients with cancer by exam, but it can also help radiologists detect other anomalies within the body. With the digitalization of medical scans through technologies such as the Picture Archiving and Communication System (PACS), medical imaging became much more convenient. Storing medical images and scans as digital representation helps prevent theft and ensures scans are organized and viewable by multiple physicians at once. However, digitalization and storage of medical scans have seen great improvement with the adoption of big data analytics. The increased availability of large data sets to hospitals has increased the predictive power of hospitals. By representing characteristics of the population using large data sets including medical scans and electronic health records, hospitals can recommend treatments that are tailored to the individual needs of the patient. Analyzing and assessing large datasets can also provide other information and answers to questions such as the effectiveness of a program. These advancements have helped optimize workflows and have potential to reduce false positive rates in cancer detection. Big Data acquisition has many important benefits to both medical imaging and the medical field in general. By collecting larger volumes of data, physicians and radiologists can develop and use programs that predict characteristics of their patient population more accurately by analyzing pre-existing datasets. For example, machine learning models can detect cancers in MRI Images through Stochastic Object Models (SOM). Specifically, a SOM can detect object variability or noise in an MRI scan if given a training data set of experimental data. According to a 2020 research project led by Professor Hua Li of the University of Illinois,

another machine learning model, the Generative Adversarial Network (GAN) can synthesize fake but extremely realistic MRI images and other medical images. Professor Li and her team have developed a new type of generative adversarial network (GAN) architecture called ProAmGAN with the sole purpose of creating realistic MRI images by comparing its images to real training data that does not contain noise. This enables hospitals to use ProAmGAN’s experimental data to be used to train SOMs to detect levels of noisy and randomized measurement data in real MRI objects, which will help doctors and radiologists distinguish cancers easier and reduce false positives. Additionally, big data analysis can also help radiologists access information quickly and reliably. According to a 2019 study, despite the adoption of filmless radiology methods, access to information from imaging workflows must still be improved. In rare cases, radiology scans can be misplaced or remain received by physicians and medical practitioners for long periods of time. This can delay diagnoses and care for patients who need it most. As big data analytic methods make it easier to manage large volumes of data, hospitals gain the ability to provide large volumes of information to specific stakeholders in real time, resulting in immense benefits. Knowing exactly when important information will be available can not only optimize radiology workflows, but also allow documentation and reporting to be managed instantly. The previously mentioned study introduces a realtime web dashboard for radiologists. Named Pipeline, the dashboard relies on multi-sourced message streams to display imaging exam results in real time. Advancements such as these allow radiologists to improve radiology exams, where data can commonly be misplaced and remain unreported for long periods of time. New Treatments The passage of time brings novel research and innovation to various fields of study, and the effects of this phenomenon are equally apparent in the treatment of cancer. From adopting new techniques and oncological approaches to revisiting former medical methodologies with a fresh perspective, the current modality of cancer treatment is constantly evolving. In fact, Khan et al. (2021) investigated flavonoids and their potential use and benefit in cancer treatment and clinical prospects. Flavonoids are a class of polyphenolic secondary metabolites

found in plants, and in vitro and vivo studies show the potential of flavonoid nanoformulations, especially quercetin, naringenin, apigenin, catechins and fisetin, in the prevention and treatment of several types of cancer (Khan et al., 2021). While the use of flavonoids may offer new insights in the field of drug discovery, more research is still required, particularly investigating flavonoid safety and tumor site-specific action. Many scientists now turn to a different practice: repurposing various pharmaceuticals and treatment alternatives to treat cancer. A primary example of this can be seen in La-Beck et al.’s 2021 study that explored the repurpose of amino-bisphosphonate by liposome formulation for a new role in cancer treatment. Aminobisphosphonates have been commercially available for over four decades and are generally used for the treatment of osteoporosis, Paget’s disease, hypercalcemia of malignancy, and bone metastases derived from various cancer types (La-Beck et al., 2021). While there is hesitancy to repurpose these pharmaceuticals due to their lack of patentability and low product cost, the team demonstrated the promise of this treatment option. Pegylated liposomal alendronate may be an attractive and promising immunotherapeutic agent, passively targeting and accumulating in tumors, having proven biocompatibility of the liposome carrier, and exhibiting preclinical anticancer efficacy (La Beck et al., 2021). Similar repurposing with other drugs has been investigated by Aggarwal et. Al (2021), who examined this practice in the context of breast cancer treatment. Drugs such as alkylating agents, anthracyclines, antimetabolite, CDK4/6 inhibitor, aromatase inhibitor, mTOR inhibitor and mitotic inhibitors have been repositioned and successfully used in breast cancer treatment during the last decade. In their review, Aggarwal et al. (2021) suggest that a comprehensive approach of selecting the most appropriate geneprotein-pathway-target-drug modeling (via system biology and bioinformatics) has high potential in providing efficient, safer, and costeffective chemotherapeutics for breast cancer treatment of varying stages. Frandsen et al. (2020) considered a different novel treatment approach known as calcium electroporation. This is a practice by which high calcium concentrations are introduced into cells by electroporation. Electroporation is a method that uses an electrical pulse to create temporary pores in cell membranes through which substances can pass into cells. Not only has

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calcium electroporation has been shown to be a safe and efficient anti-cancer treatment in clinical studies with cutaneous metastases and recurrent head and neck cancer, but the treatment itself is also inexpensive and efficient, generally lacking side effects (Frandsen et al., 2020). It has been suggested that calcium electroporation could potentially be used on a wide-scale-basis for tumors of all types. Cancer treatment research is an ongoing area of investigation with no clear solution in sight. Yet, as society inches closer in research and discovery, unique and specialized treatment for cancer patients is no longer unfathomable. Immunotherapy Two prominent immunotherapy approaches have emerged during the past few decades: checkpoint blockades and direct tumor targeting (Waldman). Checkpoint blockades offer a promising avenue for mediating immune responses. Checkpoint blockades function by regulating downstream immune responses to block cytotoxic T lymphocyte activity. The most established checkpoints are programmed cell death protein 1 (PD1) and Cytotoxic T lymphocyte antigen (CTLA 4) that operate within the tumor microenvironment (Waldman, 20). PD1 mediates apoptosis and CTLA4 regulates T-cells as immunosuppressives (Waldman, 20). To target this pathway, researchers have identified monoclonal antibodies (mAb) to block this pathway (Topalian, 16). It is important to note that checkpoint blockades have varying efficacy based on cancer line and cancer type. In addition, research has found that tumors can still upregulate PD1 ligands and cause autoimmune loss (Topalian, 16). Another field within immuno-oncology includes targeting tumor-associated macrophages (TAMs) within the tumor microenvironment (TME) (Ngambenjawong, 17). TAMs regulate transcription factors including interferons and cytokines to induce a pro-inflammatory response and function as the first line of defense for the immune system (Ngambenjawong, 17). TAMs have varying effects that are contingent on the macrophage; some increase definition of tumors, whereas others may stimulate tumors (Ngambenjawong, 17). Some promising macrophage therapeutic candidates have the ability to penetrate tumors, switching them from a cold, static state to a hot state. Antibody conjugates are another method to target cancer cells expressing TAMs (Huang,

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20). Antibodies can be used to physically block ligand-receptor interactions and stop signaling cascades (Huang, 20). Antibodies are classified by their heavy, constant region. There are five groups of antibodies: IgG, IgM, IgA, IgD, and IgE (Huang, 20). Antibodies also have a light, variable chain that binds to antigens, called the antigenbinding fragments (Fab) and the fragment crystallizable (Fc) region. The Fc receptor can be modified to prolong the half-life of the antibody, keeping it viable within the body for longer. Wild type antibodies are generally monospecific and symmetric with two identical sides, but can be engineered to be bispecific to bind to two different antigens (Huang, 20). An emerging candidate for tumor targeting includes using bispecific antibodies (BsAbs) (Shim, 20). BsAbs engage two different targets within a signaling cascade, creating a more powerful upstream regulatory response. There are over 100+ BsAb conjugated formats. They generally consist of two or more antibody fragments held with a peptide linker, disulfide bonds, and non-covalent interactions.

"...as society inches closer in research and discovery, unique and specialized treatment for cancer patients is no longer unfathomable."

Gene Therapy Due to the toxicity of chemotherapy, new cancer treatment approaches have emerged in recent decades, including gene therapy. Gene therapy consists of a variety of treatment possibilities including immunotherapy, oncolytic virotherapy and gene transfer. Immunotherapy aids the immune system in fighting tumor cells through relying on the administration of genetically modified T cells, drugs that block immune checkpoints and therefore strengthen immune response, treatment vaccines, monoclonal antibodies that target tumor cells, or immune system modulators which also contribute to a more robust immune response. However, issues can arise in this form of treatment when immune cells mistakenly target healthy cells and cause further damage. While immunotherapy can treat several types of cancers, it is not as widely used as radiation therapy or chemotherapy. This treatment option still needs to be further studied to predict what patients’ responses to immunotherapy might be and combat possible resistance to treatment. Oncolytic virotherapy utilizes viruses which are known to invade host cells and replicate its own DNA using the host cell’s machinery. In this case, the virus would be targeting and invading cancer cells to induce apoptosis, which is particularly useful for metastatic cancers that have started to spread throughout the body. The viruses used in oncolytic virotherapy are

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intended to remain harmless to the healthy cells of the body. The strains of viruses chosen to infect tumors typically possess an inherent ability to target cancer cells like adenovirus and reovirus. Unfortunately, immune response complicates the successful administration of this form of therapy as the immune system could target and destroy these foreign particles before it has the chance to induce death in cancer cells. Moreover, the method of gene transfer introduces novel genes into tumor cells through vectors like viruses and plasmids, to either induce apoptosis or slow tumor progression. The treatment combinations are incredibly diverse as scientists have tried using a number of genes and vectors to administer this form of therapy. The foreign genes introduced into the cancer cells could have apoptotic, antiangiogenesis (preventing the formation of blood vessels innervating tumor cells), or cellular stasis functionalities, all of which contribute to working against tumor growth.

"Risk factors for cancer can be 1) modifiable which are lifestyle-dependent or 2) unmodifiable which are genetic."

Drug-Free Treatments Recent studies have scientifically validated the use of herbs from traditional Chinese medicine to ameliorate cancer side-effects and treat tumors, including beta-elemene, a compound found in traditional Chinese cancer drugs (Zhai, 19). Scientists concluded that beta-elemene decreases abdominal pain, amenorrhea, congestive cardiac failure, constipation, and stomach pain (Zhai, 19). It was also discovered to upregulate p53 in ovarian cancer cells (and other signaling pathways that are non-functional in tumor cells) (Zhai, 19). beta-elemene also inhibited cell proliferation, halted the cell cycle, and induced cell apoptosis, indicating therapeutic potential beyond usage as a holistic therapy to reduce cancer symptoms (Zhai, 19). Acupuncture is another form of traditional Chinese medicine validated to reduce side effects. Researchers treated mice models engrafted with osteosarcoma tumors with acupuncture to determine the effects on tumor growth and overall health (Xu, 20). Data indicated decreased body weight loss and stunted tumor growth and size (Xu, 20). Assays also detected an increase in NK cells in treated groups of mice, indicating that acupuncture stimulated an immune response to the engrafted tumors as NK cells are recruited to fight tumors (Xu, 20). Other non-Western forms of medicine were also found to inhibit tumor growth. Researchers focusing on Ayurveda found a consistent way to recreate Indian holistic cancer treatments by

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combining traditional techniques with cuttingedge science. Researchers created a standardized version of an herb and gold tincture called “Swarna Bhasma” by using nanotech to produce gold nanoparticles and phytochemicals from herbs (Koobchandani, 20). Their mixture was validated to decrease tumor size in vivo. In mice models, the tumor volume of treated sample five weeks post-treatment was roughly 0.04 cm3, versus untreated with tumors averaging 0.08 cm3. Lifestyle and Cancer Risk Risk factors for cancer can be 1) modifiable which are lifestyle-dependent or 2) unmodifiable, which are genetic. Some of these modifiable factors include behavior, physical activity, use of drugs, sexual habits, and reproductive health. Smoking is a behavior that increases one’s risk of developing lung, bladder, kidney, pancreas, cervix, mouth, esophagus, and throat cancer. With physical activity, such as exercise, one can decrease the risk of developing cancer because it would help ensure that they are maintaining a healthy weight. Concerning skin cancer, one could decrease their risk by protecting their skin perhaps by staying out of the sun too much, especially during 11 AM and 3 PM, which are common peak hours of ultraviolet exposure. One could also avoid sunbeds, tanning lamps, wear sunscreen with an SPF of 30 or higher, and wear protective clothing such as long sleeve tops and long pants. In terms of reproductive cancers, the practice of safer sex (use of condoms and knowing partner sex history) could help prevent men and women from getting the Human Papilloma Virus (HPV), which increases women’s likelihoods of getting vaginal cancer and cervical cancer and increases the risk of anal and oral cancers for both men and women. One way a woman can reduce the risk of getting cervical cancer is by scheduling yearly pap smears; both men and women can also receive the HPV vaccine, which protect against the most common HPV types. The National Advisory Committee on Immunization (NACI) recommends the vaccine for females and males ages 9 to 26; however, the vaccine may also be given to women ages 27 to 45 who didn't get the vaccine when they were younger. Alcohol abuse has been shown to increase the chances of one developing liver cancer; however, drinking abnormal amounts of alcohol (more than a glass a day) could increase the chance of developing breast cancer since it leads to extra estrogen levels in the body. In contrast to modifiable risks, breast cancer and ovarian cancer present an example of

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unmodifiable risk. This is since one cannot control whether they inherit a mutated gene. Specifically, the BRCA-1 gene that is found on chromosome 17, this gene provides instructions for making a protein that acts as a tumor suppressor. Women that have one copy of a mutated BRCA-1 gene are more likely to get breast cancer & ovarian cancer if their 2nd BRCA-1 gene on their other 17th chromosome becomes mutated. Also, men can get breast cancer if they inherit a mutated copy of the BRCA-1 gene and then experience a mutation over the course of their lifetime on their 2nd 17th chromosome. Mastectomies and ovariectomies are lifestyle changes that could be implemented to decrease the risk of cancer cells developing in the breast or in the ovaries. Cancer development in such tissues could be quite hazardous since they pose the potential of metastasizing to other tissues in the body. In terms of decreasing the risk of colon cancer, one could get yearly colonoscopy screenings to detect the presence of abnormal lesions. Magnitude of Cancer (Statistics) Cancer is the second most common cause of death in the United States of America, surpassed only by heart disease. This is true even though cancer rates have been steadily declining after reaching a peak in 1991. A lot of this decline—31% total to be precise—has been attributed to preventative measures. Campaigns to reduce cigarette usage have played an especially important role in reducing the rates of lung cancer, which is the second-most prevalent cancer in America. In 2022, the American Cancer Society estimates that around 1.9 million more cancer cases will be diagnosed and an estimated 600,000 people will die from cancer this year. This estimate reflects a leveling-off of cancer estimates, as in 2020, it was estimated that 1.8 million more cancer cases will be diagnosed and there will be 606,520 more cancer deaths. Additionally, it is not known whether the COVID-19 pandemic will have a significant impact on the number of cancer cases diagnosed, though it is known that, in 2020, COVID-19 hampered cancer diagnosis rates. It is also not known whether COVID-19 will cause misattributions in cancer deaths, though it is known in the United Kingdom, at least, that COVID-19 has exacerbated deaths in cancer patients, which may lead to higher reports of cancer deaths in the United States, due to comorbidity. This effect is likely to be overrepresented in Black and Hispanic Americans. These groups hold a disproportionate amount of cancer cases and cancer deaths in specific areas. This is seen in the example of breast cancer—the most diagnosed form of cancer—

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in which cancer rates for White women are 100 times more common than in White men; these rates are only 70 times more common in Black women than Black men. While breast cancer diagnosis is more common in White women than Black women, Black women have a 40% higher death rate due to breast cancer than White women. Thus, during the COVID-19 pandemic, in which Black Americans are 2 times more likely to die of COVID-19 than White Americans, it is expected that cancer rates and deaths in 2021 will have a disproportionate impact on Hispanic/ Latino groups and African Americans. References Acosta AM, Garg S, Pham H, et al. Racial and Ethnic Disparities in Rates of COVID-19– Associated Hospitalization, Intensive Care Unit Admission, and In-Hospital Death in the United States From March 2020 to February 2021. JAMA Netw Open Aggarwal, S., Verma, S. S., Aggarwal, S., & Gupta, S. C. (2021, January). Drug repurposing for breast cancer therapy: Old weapon for new battle. In Seminars in cancer biology (Vol. 68, pp. 8-20). Academic Press. American Cancer Society. Cancer Facts & Figures 2020. Atlanta: American Cancer Society; 2020. American Cancer Society. Facts & Figures 2021. American Cancer Society. Atlanta, Ga. 2021. Arruebo, Manuel, et al. “Assessment of the Evolution of Cancer Treatment Therapies.” Cancers, vol. 3, no. 3, 2011, pp. 3279–3330., https://doi.org/10.3390/cancers3033279. Benchetrit, Liliya, et al. “Gender Disparities in Head and Neck Cancer Chemotherapy Clinical Trials Participation and Treatment.” Oral Oncology, vol. 94, 2019, pp. 32–40., https://doi. org/10.1016/j.oraloncology.2019.05.009. Breast Cancer: Stage 1. (n.d.). Cancer Research UK. Retrieved October 23, 2021, from https:// www.cancerresearchuk.org/about-cancer/breastcancer/stages-types-grades/number-stages/ stage-1 Brierley, J., Gospodarowicz, M., & O'Sullivan, B. (2016). The principles of cancer staging. Ecancermedicalscience, 10, ed61. https://doi. org/10.3332/ecancer.2016.ed61 Bryson, Mary K., et al. “Awkward Choreographies from Cancer's Margins: Incommensurabilities of Biographical and Biomedical Knowledge in Sexual and/or Gender Minority Cancer Patients’ Treatment.” Journal of Medical Humanities, vol. 41, no. 3, 2018, pp. 341–361., https://doi. org/10.1007/s10912-018-9542-0. Burns, J. L., Hasting, D., Gichoya, J. W., McKibben, B., Shea, L., & Frank, M. (2020). Just in Time Radiology Decision Support Using

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More Likely to Undergo Radical Excision of a Localized Renal Mass.” Urology, vol. 82, no. 5, 2013, pp. 1065–1070., https://doi.org/10.1016/j. urology.2013.06.060. Pearson, O. H., et al. “ACTH- and CortisoneInduced Regression of Lymphoid Tumors in Man.A Preliminary Report.” Cancer, vol. 2, no. 6, 1949, pp. 943–945., https://doi. org/10.1002/1097-0142(194911)2:6<943::aidcncr2820020602>3.0.co;2-p. Phillips, E H. “Laparoscopic Colectomy.” SpringerReference, Dec. 1992, https://doi. org/10.1007/springerreference_108991. “Radiation Therapy for Cancer.” National Cancer Institute, https://www.cancer.gov/ about-cancer/treatment/types/radiationtherapy#:~:text=Radiation%20therapy%20 (also%20called%20radiotherapy,your%20 teeth%20or%20broken%20bones. Shavers, V. L., & Brown, M. L. (2002). Racial and ethnic disparities in the receipt of cancer treatment. Journal of the National Cancer Institute, 94(5), 334-357. Shewach, D. S., & Kuchta, R. D. (2009). Introduction to cancer chemotherapeutics. Chemical reviews, 109(7), 2859–2861. https:// doi.org/10.1021/cr900208x Shim, Hyunbo. “Bispecific Antibodies and Antibody–Drug Conjugates for Cancer Therapy: Technological Considerations.” Biomolecules 10, no. 3 (February 26, 2020): 360. https://doi. org/10.3390/biom10030360. “Side Effects of Radiation Therapy.” Cancer. Net, 23 Sept. 2020, https://www.cancer.net/ navigating-cancer-care/how-cancer-treated/ radiation-therapy/side-effects-radiation-therapy. Siegel, RL, Miller, KD, Fuchs, H, Jemal, A. Cancer Statistics, 2021. CA Cancer J Clin. 2021: 71: 7- 33. Stage 0 Treatment Options. breastcancer.org. (2021, July 29). Retrieved October 22, 2021, from https://www.breastcancer.org/treatment/ planning/cancer_stage/stage_0. Stages of Cancer. Cancer Research UK. (2021, May 7). Retrieved October 22, 2021, from https:// www.cancerresearchuk.org/about-cancer/whatis-cancer/stages-of-cancer. Stomach Cancer: Stage 1. (n.d.). Cancer Research UK. Retrieved October 23, 2021, from https:// www.cancerresearchuk.org/about-cancer/ stomach-cancer/stages/stage-1 Strickland, N. H. (2000). Current topic: PACS (picture archiving and communication systems): filmless radiology. Archives of Disease in Childhood, 83(1), 82–86. https://doi. org/10.1136/adc.83.1.82 Sun HF, et al. Clinicopathological characteristics and survival outcomes of male breast cancer according to race: A SEER population-based

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Food Justice and the Impacts of Food Insecurity on Health

STAFF WRITERS: MD MUBTASEEM AHNAF ARONNO ‘24, ALLISON PITTMAN ‘25, SUMMER HARGRAVE ‘25, FRANCISCA FADAIRO '25, STEPHEN ADJEI '25, SOYEON (SOPHIE) CHO ‘24, MAY JIN '25, YIHAN (ELAINE) PU ‘25, ANDREW BARRY ‘24, ROHAN MENEZES '23, SHUXUAN (ELIZABETH) LI ‘25, JENNY OH ‘25, SARAH CHACKO ‘23, ERICA SIMON ‘25 TEAM LED BY: AKSHETA KANUGANTI ‘24, ANAHITA KODALI ‘23

Cover Image: Food is at the core of our health. Image Source: Wikimedia Commons

Introduction: What is food justice? How is the food that we eat related to our health? Food justice is the act of making good quality, healthy, and fresh foods available to people of all socio-economic backgrounds, race, and genders. Food justice is a response to the food insecurities that plague largely low-income households. Food insecurity refers to uncertainty or total lack of supply of quality healthy foods needed for an active and healthy lifestyle (FAO, 2003). The concept of food justice involves changing the damaged and damaging system that directly results in under-availability of healthy food in minority societies. Much of this underavailability is due to lack of affordability, and cultural preferences that have been shaped by a low economic status. Food as a result has taken up different meanings for different groups including African-American, Hispanic, and other people of color. Although food is usually considered to be a substance that can counter hunger, food is meant to be any edible substance that provides the essential nutrients for the body to function and carry out metabolic activities properly. The food we eat has a direct impact on our functionality and overall health. Americans,

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especially racial minorities and low socioeconomic groups, suffer from many foodrelated diseases such as obesity, type 2 diabetes, cardiovascular, liver, and kidney disease, cancer and Alzheimer’s disease. All of these diseases are within the top 12 leading causes of death as of 2020, increasing the importance of food justice (NVSS, 2022). Furthermore, half of all American adults (117 million people) are living with at least one preventable disease, such as dental disease, experienced as a direct result of food insecurity (“Food Related Diseases,” n.d.). Black and Hispanic communities are further targeted by fast food chains as they encourage consumption of mainly unhealthy foods in advertisements on Spanish-language or African-American targeted TV channels (Malkan, 2021). Hispanic and Black children see on average more fast-food ads than their white peers. This excess advertisement of fast-food restaurants is likely due to the higher proportion of fast-food restaurants in Black and Hispanic neighborhoods, further highlighting the food justice problem: Hispanic and Black racial communities do not have as much access to healthier food options (Malkan, 2021). Food justice is necessary for these communities to dismantle the systemic racism in the United States. Healthier food options do not only improve DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

residents’ health, but new research shows that it can provide new occupations, increase wages, and stimulate overall local economic activity, thereby empowering people of color. This article aims to bring to light the inequalities of access to healthy food based on characteristics such as race, economic status, geographical location, and gender that shouldn’t hinder quality food availability in this current global economy. This article will also highlight the physical and mental health issues related to food insecurity and show the importance for food justice in America. In this paper, “healthy food” is considered to be minimally processed food, including fruits, vegetables, whole grains, healthy fats, and healthy sources of protein. On the other hand, “low quality food” is highly processed foods such as sugarsweetened beverages, foods with high saturated and trans fats, refined sugars, and highly processed snack foods (“The Best Diet”). Additionally, “empty calories” are food and drinks that provide high energy but low nutritional value. There are generally two categories of empty calories: added sugars and solid fats (Reedy & Krebs-Smith, 2010). Added sugars are simple carbohydrates: monosaccharides and disaccharides (Kent, 2016). Examples of foods rich in added sugars include soft drinks, cookies, and candy bars high in glycemic index and where sugar is added during processing or preparation; the glycemic index is a way that doctors and researchers can quantify how much eating a certain food increases blood sugar. Solid fats are also called saturated fats. They are solid at room temperature and found in meat and dairy products such as bacon and butter. COVID-19’s effects on food insecurity in the US COVID-19 has drastically exacerbated existing food insecurity in the United States. Before the pandemic, “1 in 9 households in the United States were food insecure” (Leddy et al., 2020). However, according to Feeding America's Map the Meal Gap’s (MMG) annual projection of local and national-level food insecurity, the number of food-insecure Americans increased from 17 million in 2018 to 54 million in 2020. The number of food-secure children increased from 7 to 18 million (Gundersen et al., 2020). Rising unemployment, economic shutdowns, and the implementation of social-distancing policies prompted by COVID-19’s arrival in early 2020 have all contributed to rising household stress, healthcare interruptions, and inflation on food prices, perpetuating food insecurity rates and short and long-term poor health outcomes

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Food insecurity has adverse health effects by increasing family stressors, provoking highrisk behaviors such as unprotected sex and low medication adherence, and triggering severe inflammation. COVID-19 further worsens these issues, increasing anxiety about job security and family wellbeing, the prevalence of the aforementioned high-risk behaviors, and mechanisms that boost inflammation levels, including fat uptake and chronic-disease causing inflammatory markers such as C-reactive protein (11, 91), IL-6, and TNF receptor 1 (90). Furthermore, overburdened healthcare facilities often do not have the resources to attend to patients negatively impacted by these health implications due to large influxes of COVID-19 cases, which disproportionately impacts those who are food insecure during the pandemic (Leddy et al., 2020). COVID-19 also exacerbates food insecurity “in the context of pre-existing economic disparities” by revealing flaws in the existing US food system (Leddy et al., 2020). The shutdown of grocery stores, farmers’ markets, food banks, and restaurants has elevated demand for at-home food preparation and created a stress on grocery stores and charitable feeding organizations. Much of the food grown for restaurant consumption has gone to waste and the quantity of food available in grocery stores has plummeted, as millions of Americans compete for available foods. Households relying on food banks also experience heightened food insecurity, as stayat-home orders strain the system by increasing food demands, disrupting the food supply chain, and producing a shortage in volunteer workers. In addition, unemployment and subsequent income loss have left many without the financial means to purchase enough food or compensate for the drastic increase in food prices because of the pandemic, and school shutdowns negatively impacted 30 million children who depend on the National School Lunch program to access low-cost or free meals (“COVID-19”). Those more vulnerable to COVID-19, such as those with pre-existing conditions or those that are immunocompromised, “may be unwilling or unable to access food due to fear of viral exposure, further driving food insecurity” (Leddy et al., 2020).

"COVID-19 also exacerbates food insecurty 'in the context of pre-existing economic disparities' by revealing flaws in the existing US food system (Leddy et al., 2020)"

The widening of food insecurity caused by the COVID-19 pandemic and its subsequent economic and health crises has garnered little attention. The increased stress placed on the US food system and households “poses a serious threat to the nutritional health of millions [of Americans]” (Fitzpatrick et al., 2021). Therefore, 107

Image 1: This image displays several facts and statistics about food insecurity in the United States. Though a high percentage of individuals in the US are consistently food secure, 14.6 of the US population (or 49.1 million people) live in households that are food insecure. Image Source: Wikimedia Commons

it is essential that solutions are found to remedy current social disparities to mitigate effects on food insecurity from similar future dilemmas to the COVID-19 pandemic. Inequities in food access: Race The relationship between race and food inequity is complex and is influenced by social and economic disadvantages against people of color. Structural racism limits people of colors’ access to equal education, employment and social representation, resulting in consequences that may contribute to food insecurity. Statistical analysis modeled by Trends in food insecurity by race and ethnicity (see fig. 1) reveals that, in comparison to White and non-Hispanic households, a greater percent of Black and Hispanic households experience food insecurity.

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Particularly, the percent of Black and Hispanic households who experienced food insecurity during the Great Recession was approximately double the percent of white households. With the COVID-19 crisis, “rates of food insecurity among Black households with children are [reported to be] nearly twice as high [as compared to their white counterparts]” (Schanzenbach & Pitts, 2020). Institutional racism, interknit with political, social, economic, and legal elements of the United States, is one underlying cause of food insecurity. Racial discrimination in education and employment opportunities have been identified as significant factors that engender social and economic consequences which ultimately could result in food insecurity. Systemic racism infiltrates the current education system, negatively

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impacting students’ learning experience and beyond. Although marks of racism are more subtle in contemporary high education systems as compared to the past, modern education policies are nevertheless influenced by the history of racism. Given the inextricable link between education and socioeconomic status, students from families with higher income are more likely to have access to greater educational resources, allowing for students to perform better on standardized tests that factor into institutions’ admission of applicants into higher-education programs. Specifically, standardized tests have been argued to “perpetuate false notions of meritocracy and mask existing systemic inequities in educational opportunity [as] a proxy for socioeconomic status, rather than a measure of academic ability” (Museus & Parker, 2015). Coupled with stereotypes that some students of color are not capable of performing as well as their peers, standardized tests and other educational measures may serve as factors that limit such populations’ access to quality education. Education is closely linked to employment opportunities, as higher-paying occupations often require higher educational backgrounds. Students of color with limited access to higher ranking institutions are less likely to be employed to high-paying jobs, contributing to restraints and inequities in food access. This perpetuating feedback loop negatively impacts a significant share of families of color and their ability to obtain sustained access to food. Solutions have been identified in efforts to address the impact of structural racism on food insecurity. The federal government can expand and increase access to federal income support benefits for families; systems such as the Earned Income Tax Credit (EITC) and the Child Tax Credit provide financial credit for low- and moderate-income working people, adding to the incomes of families of color who are more likely to work in low-paid occupations (Odoms-Young, 2018). According to the 2018 Current Population Survey data conducted by CBPP, while 9% of white women have received credit from the EITC system, 21% of Latina and Black women – greater than twice the share of white women – have benefitted from the program (Marr & Huang, 2019). Programs that offer broader access to employment opportunities for people of color can also serve as solutions to combat the economic consequences of structural racism on food insecurity. By race, whites constituted the majority of the labor force at 78 percent (in 2018) while Blacks and

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Asians constituted, respectively, 13 percent and 6 percent (“Labor force characteristics,” 2019). To tackle the persistent issue of food inequity across race, the fundamental root of structural racism must be addressed with a human rights approach: once again, we make clear that all forms of discrimination, based on racial or socioeconomic factors, must be eliminated. Relevant efforts will require political measures and programmatic strategies to be carefully devised to promote effective equity in food access. Economic status The scarcity of healthy food in low-income communities is overshadowed by the more affordable unhealthy food option. It is not unheard of that “people experiencing food insecurity often consume a nutrient-poor diet, which may contribute to the development of obesity, heart disease, hypertension, diabetes, and other chronic diseases” (Murthy, 2016). In low-income areas, the most frequently eaten foods are cheap fast foods or monotropic meals - meals consisting of just eating one food, such as potatoes- that do not meet the body’s nutritional requirements. The paradox of food insecurity and obesity is perpetuated by socioeconomic disparities as “diets with greater nutrient density are more expensive than less-healthy calorically dense diets”(Levy et al, 2012). Since the 1950s, the fast-food trend has flourished with food production companies producing and distributing unhealthy foods at lower cost, thereby capitalizing on communities that can only afford such goods. In this way, unhealthy foods have become more common and accessible, leading to unhealthy lifestyles and health consequences. Moreover, in low-income areas, Yale researchers have recently found that there are not only significantly less healthy food options, but the produce tends to be lower in quality (it is less fresh and dirtier) (YaleNews). Those who cannot afford to live in higher income areas have fewer options to eat healthier, exacerbating the food justice problem. Therefore, the economic status of low- income earners directly impacts the quality of food they consume.

"The scarcity of healthy food in lowincome communities is overshadowed by the more affordable unhealthy food option"

A culture around unhealthy eating—that has been built in a subtle systemic manner unknown to affected minority populations— is an additional point to consider in the food choices. The subtle systemic manner refers to purposeful focus on the minority population in marketing unhealthy food in America (Vlasits, 2016). A 9-month longitudinal study of food choices among minority and low-income individuals found that two interventions–

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"A household's geographic location is a significant predictor of healthy food access..."

“point-of-purchase color-coded food labeling and choice architecture” –improved healthy choices equally among employees from all racial/ ethnic and socioeconomic backgrounds” (Levy et al, 2012). The significance of this study is that interventions are effective ways of curtailing unhealthy food consumption and increasing healthy food choices. The point-of-purchase color-coded food labeling refers to a system of using colors (red, yellow, green) to differentiate healthy and unhealthy food: green being the healthiest and red the unhealthiest. The effect of this intervention was a psychological response to the colors, where customers avoided red which commonly signifies danger and yielding to green labeled foods. This intervention demonstrates that simpler consumer communication is needed to facilitate healthier food choices in low-income communities. Choice architecture is also a psychological play that involves arranging the store (where the observation occurred) in such a way that “green” foods are more accessible than the red foods. It also showed a significant change in food choices across all people. This shows that if healthy food is available, people are willing to buy it; however, shaping certain areas so a higher portion of food sources are unhealthy takes away the access to food, creating food injustice. This can be perceived as a systemic injustice like redlining but in the form of targeting by fast food chains. Instead of stereotyping certain areas based on income and predicting that unhealthy, but affordable, food would sell better, food justice aims to create equity in food access, regardless of income. Geographical barriers to healthy food access A household’s geographical location is a significant predictor of healthy food access, particularly in concert with a locale’s average socioeconomic status. One major issue indicated by prior research is that low-income neighborhoods, which are primarily urban, have less than half as many supermarkets as highincome neighborhoods on average (Moore and Diez-Roux, 2006). This disparity presents an issue for food justice as supermarkets are often able to provide a much larger selection of food products, including healthier options, and at a lower price than smaller alternatives, such as groceries and convenience stores (Powell et al., 2007; Walker et al., 2010). The difference may be partly due to the shift of wealthy households with higher purchasing power to suburbs, widening the physical distance between richer and poorer neighborhoods, and creating an incentive for larger stores to migrate with the former group (Morland et al., 2002; Treuhaft and Karpyn, 2010).

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The average nutritional quality of food products is lower, and prices higher, in neighborhoods with a lower median income (Hendrickson et al., 2006). This geographical issue is particularly impactful given that lower median income is correlated with higher time requirements for child-rearing and employment, and lower rates of private vehicle ownership (Cotterill and Franklin, 1995; Morland et al., 2002). In combination with a lack of supermarkets, this leads to the increased exposure to high-calorie unhealthy food options in relatively prevalent convenience stores and fast-food restaurants, causing unhealthy eating habits (Morland et al., 2002; Walker et al., 2010). Therefore, income, time and mobility constraints limit neighborhood residents to purchasing less nutritious food available in their own area, turning these locales into food deserts (Morland et al., 2002; Walker et al., 2010). While food deserts have often been defined as primarily urban, rural areas have similarly low healthy food access due to income, time, and mobility issues, especially compared to suburban communities (Treuhaft and Karpyn, 2010). The racial composition of neighborhoods has also been found to be a significant geographic indicator of healthy food access, even when controlling for economic status (Powell et al., 2007). This inequality is especially severe for Black Americans. In Detroit, Michigan, for example, the most impoverished white neighborhoods are on average over a mile closer to the nearest supermarket than the most impoverished Black neighborhoods (Zenk et al., 2005). An analysis of neighborhoods across multiple states found that majority nonwhite and racially mixed neighborhoods had less than half as many supermarkets (on average) as majority White neighborhoods (Moore and Diez Roux, 2011). For majority-Black neighborhoods, that proportion drops to a fourth (Morland et al., 2022). These healthy food access issues may be associated with disproportionate rates of morbidities and obesity in minority communities (Deaton and Lubotsky, 2003; Paeratakul et al., 2002). One potential reason for racial disparities in heathy food access is the modern impacts of historical racial segregation in residential areas, concentrating minority populations in lowresource areas, with limited economic activity and opportunities, and therefore limited healthy food access (Gee and Payne-Sturges, 2004; Bower et al., 2014). Geographical location

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Image 2: This is a map of food desert locations in Chicago. Food deserts are regions in which inhabitants do not have easy access to healthy food (like from a supermarket). The white pentagons with carts in them represent grocery stores, and areas that are shaded with blue lines are food deserts. The darker red an area is, the more impoverished it is. From the graph, many grocery stores fall in low poverty areas, and in line with this, the darkest red areas – which have the highest rates of poverty – are also food deserts.

The tropics, situated around the equator, boast a perpetual exposure to the sun and a season of heavy rainfall. It is precisely these climate conditions that make the area ripe as an agricultural playground. Inhabitants of tropical regions are much more dependent on the agrarian industry (in comparison to the manufacturing industry), specifically on crops for both local consumption, export, and their economic livelihoods. While local family farms produce around 80% of food globally, these same farmers suffer the most from malnutrition and food insecurity. Furthermore, the need to meet the global demand of crop production has resulted in wide-scale unsustainable agricultural practices, which in turn further endangers food security by land degradation (Rashid, 2018).

Image Source: Wikimedia Commons

The country of Madagascar serves as a prime example for the exacerbating effect of unsustainable farming practices on food security in tropical, low-income countries. Herrera et al. investigated the challenges of food security in northeast Madagascar and the impact of agricultural practices that heighten food stress. In this evaluation, the authors linked increasing land size with the decreased agricultural productivity, highlighting the “inefficiencies of input use on larger fields, especially when they are in fragmented parcels” (Herrera et al., 2021). These inefficient farming techniques often degrade the soil and water of the field, consequently reducing future crop yield and the nutritional value of the obtained harvest. Also, the use of fertilizers introduces contaminants to local water streams, inflaming the water scarcity crisis plaguing the area. These agricultural practices are incompatible with the ever-growing global demand for food, considering the 70% global increase in agricultural productivity needed by 2050 as estimated by the Food and Agriculture Organization of the United Nations (“Making agriculture more sustainable and productive,” n.d.). The introduction of sustainable farming practices in these areas are a necessity in the interest of local and global food security.

gap. According to an analysis done by the Pew Research Center, women earned 84% of their male counterparts’ salaries in 2020 (Barroso & Brown, 2021). This lower income correlates to less spending money available for meals, forcing women to either purchase less food or choose the less expensive- and often unhealthier- option. Further, pregnant women face even more stress due to greater physical and nutritional needs along with a potential lack of pay during maternity leave (Ivers & Cullen, 2011). For impoverished families, this temporary lack of income limits access to food for the entire family. Another worrisome consequence is the health of the baby, as approximately 17 million children are born underweight annually as a result of inadequate nutrition of their mothers before and during pregnancy (Sachs & Patel-Campillo, 2014). Thus, food insecurity’s disproportionate effect on women extends beyond gender to intersect with economic concerns and the wellbeing of the entire family.

Gender Access to food is also divided by gender; globally, women are more likely than men to be food insecure, this difference becoming more intense in certain populations (Broussard, 2019). In the United States in 2020, the rate of food insecurity for single-mother households was 27.7%, compared to 16.3% for single-father households, and the national average food insecurity is 10.5% (Coleman-Jensen et al., 2021). This inequality can be attributed in part to the gender wage

Food Culture Food culture is defined as the attitudes, beliefs and practices that surround the production and consumption of food; it is shaped by upbringing and incorporates elements of a person’s ethnicity, cultural heritage, and religion. Cultural components of behavior have significant impacts on patterns of eating, drinking, and social interactions–all of which contribute to health. One’s food habits and subsequent diet is a combination of sociodemographic

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"...globally, women are more likely than men to be food insecure..."

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characteristics, health and lifestyle, food beliefs and attitudes, food preferences, dietary environment, and food availability. These food habits have large influences on the health disparities observed between societies. Studying the food behaviors that lead to such disparities can help explain why some groups seem to have a predisposition to certain health issues.

"To ensure successful health education programs...it is important to identify local cultural practices and beliefs, as well as the local food culture."

Diet is a cultural and social construct. It can impact one’s predisposition to certain health issues. Particularly, cultural-religious beliefs have shown how religion can have both a positive and negative impact on health. Religions often have health and dietary “rules;” for example, Judaism does not permit the consumption of pork. These “food taboos”—or prohibited foods—have both good and bad health implications. For example, a population of Seventh-Day Adventists in the United States in the 1980s was found to have low mortality, cancer, and diabetes (Phillips et al., 1980). This was a result of their low animal intake—Seventh-Day Adventists are lacto-ovovegetarians, which means that they are vegetarians that avoid alcohol. Another example comes from Ohio, where a group of Old Order Amish were found to have lower rates of hypertension, smoking, alcohol consumption, and stress in comparison to the non-Amish rural Ohio residents (Fuchs et al., 1990). However, obesity was extremely prevalent for this population, as the Amish see food and eating as very important. This, coupled with decreased physical activity and other factors contribute to the high incidence of obesity and related issues seen within the population. These examples demonstrate the unbreakable link between religion and health. Food is an important part of many religious cultures; because of this, it is important that health professionals seek to understand how various religious and cultural practices influence health outcomes, especially those that result from diet. Similar to religion, ethnicity and socioeconomic status shape food culture, which in turn shapes the health of individuals within a population. Diet-related diseases are more prevalent among lower-income and minority groups, which is why it is important to study these groups to reduce these health disparities. In a study conducted in north central Florida, researchers aimed to explore how culture and community impact the nutritional attitudes, food choices, and dietary intake in a select group of African Americans. Among the individuals studied, there was a perception that “eating healthfully” meant giving up part of their cultural heritage

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and trying to conform to the dominant culture (James, 2010). The results highlighted how the social and cultural symbolism to eating healthy foods was a barrier to this specific population, which subsequently impacted the dietary habits of the individuals studied. Similar work is being done in Nebraska by Georgia Jones, an Associate Professor and Extension Food Specialist at the University of Nebraska-Lincoln. Jones specializes in food literacy and is working with multiple populations of Native Americans to determine how they can establish native food traditions in healthy ways. Historically, Native American populations have suffered from a high incidence of diabetes as they have over time, due to genetic mutations from ancestors, have more sugar in their blood. This could be due to Native Americans historically not having as much access to sources of glucose. Therefore, their bodies have evolved to hold onto glucose in their blood. In fact, as Jones said in an interview, “it's almost a rite of passage to have diabetes if you're Native American…It's kind of presumed that you're sooner or later going to get it” (Tan, 2012). This mindset indicates a mindset shared by many minority groups––that there is nothing that can be done about their predisposition to certain health conditions. However, a healthier diet with diabetes in mind could help Native Americans mediate their pre-diabetes more effectively. Increasing the amount of access to unhealthy food could only exacerbate the risk of diabetes for Native Americans. Hence, the need to connect cultural traditions with healthy eating cannot be ignored. Through increased and more thorough research, we can diminish the risk that food behavior poses to individuals in developing disease. To ensure successful health education programs, especially in relation to diet and a group’s culture surrounding food, it is important to identify local cultural practices and beliefs, as well as the local food culture. Physical Disease and Food Insecurity: Obesity According to the CDC, in 2021, 42.5% of U.S. adults aged 20 and over are obese, including 9.0% with severe obesity, and 31.1% who are classified as overweight. These percentages have seen a stark increase in the past fifty years; in 1960, an estimated 31.5% of U.S. adults aged 20 and over were overweight (Sprankle, 2021). This can be attributed, in part, to the increase in fast food availability across the nation. Today, it is more common for both parents in a household to work, which means that there is less time to prepare food at home. Therefore, fast food has become a tempting option.

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Image 3: Obesity is typical defined via BMI. This chart shows the various categories of BMI one can fall into. Image Source: Wikimedia Commons

Fast food is a growing part of the American diet. The convenience it poses to busy Americans makes it more attractive than a home cooked meal. However, fast food is full of calories without any nutritional benefit (empty calories), which puts its consumers at risk for weight gain and obesity. Due to environmental injustices, the increasing trend of fast food disproportionately affects low-income and minority groups. Environmental justice is defined as “fair treatment and meaningful involvement of all people regardless of race, ethnicity, income, national origin, or educational level in the development, implementation, and enforcement of environmental laws, regulations, and policies” (Hilmers et al., 2012). The concept of environmental injustice can be applied to food access across socioeconomic and ethnic groups. Higher obesity rates among low-income and minority populations are linked to a higher density of fast-food outlets in traditionally lowincome and minority neighborhoods––this promotes unhealthy eating habits. The data researchers have collected on this issue presents concerning patterns. For example, Hispanic, African American, and low-income populations lived in regions with higher densities of convenience stores and fast-food restaurants (Hilmers et al., 2012). These findings correspond with the statistics, as the percentage of calories consumed from fast food in non-Hispanic Black adults was 21.1%, compared to 14.6% and 14.5% in non-Hispanic white and Hispanic adults, respectively. Similarly, in the youngest age group studied in a census (aged 20-39), there was a statistically significant decrease in the percentage of calories consumed from fast food with increasing income level (Fryar and Ervin, 2013). As demonstrated, accessibility is a key determinant of fast-food consumption; in order to reduce the prevalence of obesity in low-income and minority communities, there needs to be a reduction of fast food availability WINTER/SPRING 2022

in certain neighborhoods. Ideally, this will result in a reduction in the obesity prevalence in such groups. Diabetes Diabetes is a health condition associated with disordered glucose metabolism. Research consistently demonstrates the relationship between food quality and diabetes; the association of empty calories and type 2 diabetes is particularly robust. Based on current understanding, type 2 diabetes usually develops over time due to a high concentration of blood sugar in the body, which damages the pancreas and impacts its ability to maintain glucose levels (Willett et al., 2002). It is a common condition that affects 17 million individuals in the U.S and has been increasing in prevalence over the past decades alongside the obesity epidemic (Schulze et al., 2004). As the consumption of added sugars grew in both adults and children across the U.S, research on the link between simple carbohydrates and type 2 diabetes gained focus. A study by Schulze et al. (2004) found that high consumption of sugary beverages such as sugar-sweetened soft drinks and fruit punches is associated with weight gain and greater risk for type 2 diabetes. In another study by Willett et al. (2002), researchers calculated the glycemic load by multiplying the amount of carbohydrate with its glycemic index; this allows researchers to measure the rise in blood sugar due to the number of carbohydrates in a meal. They found that women in the highest 20 percent for glycemic load had almost double the risk for developing diabetes than did women in the lowest 20 percent for glycemic load. This study also identified that, in patients with diabetes, consuming foods with low glycemic index improved control of their glucose levels (Willett et al., 2002). There are several pathways by which simple carbohydrates might increase the risk for type 2 diabetes. Schulze et al. (2004) proposed that 113

sugary drinks are high in fructose, which raises blood sugar levels. Similarly, Willett et al. (2002) suggested that carbohydrates high in the glycemic index increase blood glucose and insulin demand. As a result of high blood sugar, beta cells in the pancreas, which control the synthesis and secretion of insulin, have to work harder and are more susceptible to damage; exhaustion of beta cells could lead to glucose intolerance and diabetes (Willett et al., 2002). In addition, sugary snacks and drinks may contribute to obesity, a risk factor for type 2 diabetes due to its link with insulin resistance (Willett et al., 2002), by preventing people from feeling full despite consuming high energy, which leads to subsequent energy intake (Schulze et al., 2004). While many studies confirm the connection between simple carbohydrates and type 2 diabetes, the link between saturated fat and diabetes remains uncertain. One study found that increased proportions of saturated fatty acid in plasma correlate with an increased risk for developing this chronic condition (ARIC Study Investigators, 2003). However, dietary studies presented mixed results. Micha and Mozaffarian (2010) found that there is an independent relationship between the consumption of saturated fatty acids and diabetes – however, the risk for diabetes decreased with the consumption of monounsaturated fatty acids (healthy fat from plant foods) (Micha & Mozaffarian, 2010). A study by van Dam et al. (2002) also showed that saturated fat consumption was only associated with a higher risk of type 2 diabetes without adjustment for body mass index. Therefore, evidence suggests that, of the two

categories of empty calories, added sugars have a stronger association with the development of type 2 diabetes which may be attributed to their direct effect on blood sugar levels and their link to obesity. At the same time, more research is needed to determine the association between solid fat and diabetes. Vascular disease The term vascular disease is used as an umbrella term to describe many diseases involving the narrowing and stiffening of blood vessels, such as peripheral vascular disease, stroke, and aortic aneurysm. Vascular diseases and disorders are not restricted to just the blood vessels. Blood disorders such as sickle cell disorder, where deformed blood cells become adhesive and stick to the inner lining of blood vessels and platelets, disrupt blood flow by causing blockage within the vessels (Ofori-Acquah, 2020). Vascular diseases are burdensome to the US population and the healthcare industry; As of 2015, vascular diseases affect over 30 million people and generate healthcare costs of up to $100 billion annually (Clavijo, 2015). Several studies have also suggested that food insecurity may be directly correlated with vascular disease and poor cardiovascular health. For example, a study by the USDA concluded that the prevalence of cardiovascular diseases was six times higher for individuals with low food security. At the same time, those individuals were 2.36 times more at risk of having 10-year cardiovascular disease risk and were more likely to die due to CVD. Low income is an essential factor in this correlation. According to the study, low-income individuals may suffer from limited

Image 4: Vascular disease is strongly linked to issues with food accessibility. Image Source: Wikimedia Commons

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transportation access and food insecurity and find CVD treatments financially burdensome, increasing their likelihood of remaining food insecure. The same study claims that food insecurity is associated with the intake of sugar, processed foods, and other unhealthy meals. These dieting patterns contribute to early vascular changes in children, such as higher BMIs and accumulation of body fat, contributing to cardiovascular mortality (Chang et al., 2022). Chang et. al's study demonstrates that the behavioral changes, stress levels, and nutritional quality associated with food insecurity contribute to CVD development and the increased risk of death from CVD (Chang et al., 2022). This relationship locks those affected in a vicious cycle of unfortunate circumstances: As CVD treatment becomes financially burdensome for low-income individuals, the individuals may turn to unhealthy dieting options due to their affordability, which directly contribute to cardiovascular disease and mortality (Chang et al., 2022). Building on this analysis, Chang et. al's study lists sociodemographic factors used to determine which demographics struggling with food insecurity are more likely to develop cardiovascular complications. One such factor is race and ethnicity. The study cites "socioeconomic inequality, educational disparities, and bias… in healthcare" as factors that leave under-represented racial groups more at risk of cardiovascular complications. For example, according to a 2020 study by K. Cooksey, Hispanic and Black individuals are more likely to live in places with more unhealthy food options. Food insecurity was also linked to obesity among food-insecure Black and Hispanic individuals, which represented 46.1% and 35.7% of the sample population, respectively (Chang et al., 2022). Furthermore, a 2017 study headed by Seth Berkowitz sought to identify a correlation between food insecurity and Atherosclerotic Cardiovascular Diseases (ASCVD). Like Chang, Berkowitz suggests that food insecurity is most associated with health behaviors and factors contributing to expensive medical treatment and poor health. The Berkowitz study used the National Health Interview Survey data to measure food insecurity with 10 question surveys over 30 days. Certain individuals with ASCVD identified their prior coronary artery diseases or recent strokes. The association between food insecurity among those with ASCVD and a composite score of sociodemographic characteristics was measured

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using Stata SE v 16.0. Berkowitz's results showed that 14.6% of individuals with ASCVD reported food insecurity, whereas only 9.1% of individuals without reported food insecurity (Berkowitz et al., 2017). Furthermore, Berkowitz et al. report the highest risk sociodemographic factors as follows: 65 years or older; Black or Hispanic; lowincome; female; separate marital status; and no health insurance. Among those displaying only 1 of these characteristics, only 2.2% were food-insecure, whereas those showing anywhere from 2-6 of these characteristics reported 6.4 – 53.7% food insecurity (Berkowitz et al., 2017). Indeed, like Chang et al.’s study, Berkowitz et al. infer that food insecurity shows a solid correlation to cardiovascular disease and mortality. Those suffering from food insecurity may not display optimum dieting practices or have enough income to change their lifestyles. This leads to a critical conclusion: High healthcare expenses for treatment for vascular diseases contribute to prolonged food insecurity for specific groups. These studies display how important it is to tackle barriers preventing specific demographics from obtaining proper nutrition and paying for medical treatment. Cancer Food insecurity and one’s diet can be further correlated to increased likelihood of cancer, particularly breast, prostate, pancreatic and colorectal cancer. These forms of cancer can be influenced by dietary habits such as consuming processed and red meats. Red meats include beef, pork, veal, and lamb, while processed meats are but not limited to ham, hotdogs, bacon, and beef jerky (CTCA, 2021). There are growing sings of a correlation between increased consumption of red meat and processed meat and colorectal cancer. Attention has in the past thirty years been continuously called upon the rise of cancer in younger, less fit groups. The New England Journal of Medicine advised for the age of screening for colorectal cancer (CRC) to be lowered to 45 based on studies done from 1974 to 2013. They’ve noticed a 1.0-2.4% rise per year in colon cancer cases in the 20-39 age group over this time period. As for rectal cancer cases, an even steeper margin of growth of 3.2% a year has been recorded for the 20-29 age group (Dyer, 2018). This significant increase in cases is why the American Cancer Society is urging younger screening, as this trend will most likely follow this generation into their older years.

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"Given the link between nutrition and oral health, it is not surprising tha tfood insecurity plays a major role in the development of dental caries."

Several studies have attempted to answer the question of what is causing this rise in CRC cases and have begun researching the relationship between CRC and processed and red meat. Processed meat has already been labeled as a Group 1 carcinogen, placing it on the same level as alcohol and smoking as a probable risk for inducing cancer. Meanwhile, red meat has been placed in Group 2A, which should still be advisable for caution (Dyer, 2018). A 2017 on-going study in Germany took two groups of people (upwards of two thousand in each) with family history of CRC, one with CRC and one control, and conducted research on the diets of both. They examined the various mutations in the CRC group, looking for trends in the mutations that could reveal a correlation. They found insufficient data to determine if processed and red meats caused a specific mutation, though they claimed that they found an association of meat intake and CRC with a confidence interval of 95% (Carr et al., 2017). The report does note that due to the small sample size, the data is more helpful as a stepping stone for larger work. The next year, another study in France by NutriNet-Santé included a baseline of 104,980 participants who did not have cancer. Their diets, as well as physical shape and activity, were monitored over a five-year span. In that span, 2228 were diagnosed with cancer, 153 cases being CRC. The other two significant cancers noted in the study were breast (739) and prostate (281). The study found that ultra-processed fats had a correlation to increased risk in all cancers. The study concluded that a 10% increase in processed food consumption was associated with a 12% increase in risk of all cancers (Fiolet et al., 2018). Such data further proves why meat consumption continues to be a high-level carcinogenic risk. Dental disease To maintain oral health, the human body requires daily nourishment in the form of a balanced diet containing appropriate amounts of all nutrients. Malnutrition (over and undernutrition) can severely compromise oral health and cause dental diseases such as dental caries, periodontal diseases, diseases of the oral mucosa, oral cancer, and infectious diseases. Among them, dental caries, or tooth decay, is the most prevalent disease worldwide and the most common pediatric disease in the United States (Chi, 2014). According to a recent survey by the global oral health data bank, the prevalence of dental caries varies in the range of 49% to 83% (Rathee, 2021). According to the CDC, from 2015 to 2018, the

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prevalence of untreated tooth decay in the United States was 13.2% for children aged 5 to 19 years and 25.9% for adults aged 20 to 44 years (FastStats, 2022). A chronic infectious, transmissible disease, dental caries results from cariogenic bacteria, primarily Streptococcus mutans, in the dental plaque (Rathee, 2021). These bacteria anaerobically metabolize dietary sugars to produce lactic and other acids (Gondivkar et al., 2019). The formation of acid in the mouth reduces the oxygen coefficient, making conditions more anaerobic and favorable for cariogenic bacteria (Rathee, 2021). This increases the rate and progression of dental caries. Over time, the acid dissolves the calcified tissue – enamel and dentin – in the tooth, forming cavities. According to studies, this irreversible demineralization of teeth occurs at a pH of 5.5 and below (Rathee, 2021). Dental caries is a multifactorial disease: it depends on the interaction between various factors, including the presence of fermentable sugar, host factors, and the presence of cariogenic microbial flora (Rathee, 2021). Plaque and dietary factors are interdependent upon each other in the causation of dental caries (Rathee, 2021). A diet rich in processed sugar provides the substrate for cariogenic bacteria in the mouth to flourish and generate enamel-demineralizing acids. Previous studies have found that frequent consumption of carbohydrates in the form of simple sugars such as sucrose increases the risk of dental caries (Gondivkar et al. 2019; Moynihan, 2004). Furthermore, Rugg-Gunn et al. and Burt et al. have found significant association between caries progression and dietary sugar intake in their longitudinal studies (Rugg-Gunn et al., 1984; Burt et al., 1998). The host acts simply as a platform for the interaction of plaque and diet (Usha, 2009). Given the link between nutrition and oral health, it is not surprising that food insecurity plays a major role in the development of dental caries. According to a cross-sectional analysis of US National Health and Nutrition Examination Survey (NHANES) data from 2007 and 2008 conducted by Chi et al., children from low or very low food security households had significantly higher untreated caries prevalence than children with full food security (2014). Food-insecurity often forces parents or caregivers from low socioeconomic status (SES)-households to make food-purchasing decisions optimized for quantity rather than quality (Chi et al., 2014). For example, they may have no choice but to buy sugar-

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Image 5: Several forms of dental disease are linked to poor nutritional habits. Image Source: Pixabay

sweetened beverages such as Coca-Cola or Pepsi which are cheap and easily accessible. However, these drinks have a high sugar content which significantly increases the risk of dental caries. Additionally, food-insecure households usually live in rural areas or poor neighborhoods where there is a lack of quality food stores (Tungare, 2021; Chi et al., 2014). Purchasing options in these so-called “food deserts” are often limited to convenience stores and fast-food restaurants. Therefore, these households only have access to processed foods, snacks, and sugar-sweetened beverages which are high-energy, nutrient-poor, fatty, and sugary. This deprives children of fresh, nutritiously dense food such as vegetables and fruits, complex carbohydrates, non-processed proteins, and dairy products. In addition to dental caries prevalence in children, food insecurity is also linked with prevalence of dental diseases in adults. Last year, Bahanan et al. performed a cross-sectional analysis of the NHANES 2011-2012 and 2013-2014 data. The study, which included 10,723 adults, aged 18 and above, found that food-insecure adults had 1.2 times higher odds of having untreated dental caries than fully food-secure adults (Bahanan et al., 2021). This finding agrees with previous studies which investigated the harmful effects of food insecurity on self-reported oral health. For example, an analysis of NHANES 2011-2012 data by Wiener et al. found that adults with low food security were 58% more likely to report unmet dental care need as compared to adults with full food security (2018). This may be because foodinsecure individuals are more likely to consume a poor-quality diet deficient in fruits, vegetables, dairy products, vitamins, and minerals. Furthermore, food-insecure individuals tend to consume large amounts of energy dense food (e.g., burgers, hot dogs, etc.) and to adopt bad

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eating habits to cope with food deficiencies. As explained before, a diet rich in fermentable carbohydrates such as sucrose significantly increases the risk of developing dental caries. Dental diseases such as dental caries negatively impact self-confidence and overall quality of life (Govindkar, 2019). Furthermore, compromised oral health can alter food choices and negatively impact food intake leading to suboptimal nutritional status. According to an analysis of the NHANES 2005-2008 data by Zhu and Hollis, teeth loss in adults is associated with lower diet quality and reduced energy intake (2014). This may partly explain the significant association between tooth loss and risk of chronic systemic diseases shown by previous studies (Zhu, 2019). Therefore, recognizing and managing oral health conditions is crucial in order to improve the health as well as the quality of life of affected individuals. However, this can only be done when food inequality is reduced by making healthy, nutritious food affordable and accessible to poor neighborhoods. Mental Health and Food Insecurity: Diet and mental health are linked in complex ways with physical health as a prominent mediator. It is commonly known that a healthy diet, positive mental health, and physical wellbeing are often correlated, but the underlying factors are often difficult to parse out. A "good quality diet" usually consists of healthy fats, fruits and vegetables, and high-fiber foods, and a healthy diet increases physical health via numerous biological pathways (Firth et al.). The most prominent factors of good physical health are typical levels of insulin sensitivity, lowered risk of heart diseases, and having a weight that corresponds to one's activity demands. These biological factors can drive individuals to have a

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"high intake of fruit, vegetables, whole grain, fish, olive oil, low-fat dairy and antioxidants and low intakes of animal foods" (Li et al). Healthy dietary patterns are associated with a reduced risk of depression by several meta-analyses (Li et al., Molendijk et al.). In addition, mentally healthy individuals often experience fewer cravings and put themselves in situations with healthier foods, such as home-cooked meals rather than fast foods. These findings demonstrate the various ways that positive diet and mental health are mediated by physical health. The reverse trend is true in that an unhealthy diet covaries with the onset of depression symptoms. Multiple factors contribute to this correlation, including glycemic load, immune response activation, and the gut microbiome. First, having an excess of processed carbohydrates ultimately results in counter-regulatory secretions of cortisol and adrenaline. An overload of these hormones is one of the causes of depression in the long term (Firth et al.). Secondly, the immune system has been proposed as a possible pathway in which an unhealthy diet results in mood disorders via the inflammatory response. People with a Western diet (regular fast food consumption) and people with mood disorders both report heightened inflammatory symptoms, although causality has yet to be established (Yuan et al.). Lastly, the gut microbiome is tightly linked with the nervous system. The gut contains microbial metabolites, which often travel into various regions of the brain via the bloodstream. Abnormal regulation of the microbiota-gut-brain axis is one of the major predictors of major depressive disorder (Ortega et al.). These aforementioned factors exemplify pathways in which mental health disorders and unhealthy eating behavior are associated with each other. Along with depression, research also links food insecurity to generalized anxiety and other anxiety disorders. According to a study conducted by the Journal of Hunger & Environmental Nutrition, those experiencing greater fear and generalized anxiety symptoms, such as families with children who must worry about having to keep more than themselves fed, experience elevated levels of food insecurity (Fitzpatrick et al., 2021). This correlation is further exacerbated by fears surrounding COVID-19. Anxiety over food shortages during times of stay-at-home orders and shutdowns has further increased uncertainties about access to food, perpetuating household food insecurity.

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The association between food insecurity and anxiety is particularly prevalent among women, which is evident in research carried out by the United States Department of Agriculture that measured food security in households in 2018. Respondents were asked about “anxiety related to the household food supply, running out of food, providing inadequately nutritious food, and substitutions or restrictions in food consumption by adults and/or children in the household due to lack of financial resources” (Maynard et al., 2018). Results indicated that food insecurity and self-reported anxiety/poor mental health were positively correlated in US women. The “experience of food insecurity itself is characterized by worry and anxiety about the household food supply” (Maynard et al., 2018). The worry over access to food in low-income or struggling households represents a stressor that leads to periods of generalized anxiety or chronic stress. This development in turn generates a negative household or individual relationship with food due to constant uncertainty about food availability or affordability. According to responses collected through a survey by Health Equity, adults with high food security experience anxiety surrounding food insecurity due to “fear of the unknown,” and “are [living] week by week … [avoiding] asking for help … falling through the cracks, invisible to a system suddenly flooded by the needs of people it already recognizes as needing help” (Woflson et al., 2021). Not only is the prevalence of food insecurity linked to anxiety disorders harmful to adults, but it can also be detrimental to children living in these households. Child health and behavioral development are susceptible to the household risk for food insecurity, and parental anxiety over food accessibility can pose a negative influence on children (Lauren et al., 2021). Food insecurity and eating disorders intersect at many levels. Higher levels of eating disorders, especially binge eating disorder (BED) and bulimia nervosa, are associated with food insecurity in adults. Studies have found that irregular food access results in an irregular trend of food intake: this trend is emphasized in part due to some food aid programs, such as the U.S. Supplemental Nutrition Assistance Program (SNAP). SNAP benefits are provided once a month, which are often used soon after reception and “exhausted before the end of the month.” Such fluctuations in food availability result in food restriction, in turn creating a tendency to binge-eat in the absence of food restriction (Hazzard et al., 2020).

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Additionally, a survey conducted in 2018 found that altered eating patterns associated with food insecurity were consistent with the diagnostic criteria (as outlined in the DSM5) for binge eating disorder, including loss of control, recurrent episodes, and psychopathology (Rasmusson et al., 2018). Such eating patterns, in line with characteristics of BED or bulimia nervosa, often result in obesity or changes in body weight. Higher levels of food insecurity are associated with higher levels of weight self-stigma and dietary restraint along with binge eating and other eating disorder pathology (Becker et al., 2017). These trends of negative body image echo trends of high-calorie food consumption and obesity that also accompany food insecurity. Eating disorders are a concern not only because of their ties to mental health, but because of their additional physical health implications. Both bulimia and binge eating disorder increase a person’s risk for type II diabetes as well as obesity (Raevuori et al., 2014). Bulimia nervosa, in particular, can lead to diverse medical complications because of purging behavior (Mehler & Rylander, 2015). Thus, food insecurity has diverse and adverse effects on both mental and physical health, characterized by its relation to eating behavior. Conclusion: The food that we eat is at the core of our health, both physical and mental. Eating foods that are rich in nutrients promotes good health and better quality of life; conversely, consistently eating foods that are high in saturated fats and that have low nutritional value can result in diabetes, obesity, dental disease, and various cancers. Despite this clear link, disparities persist in access to good food, with people of color, women, those in lower socioeconomic classes, and those in certain geographic regions having lower access to good food. This results in a disproportionate burden of food-related disease in these regions and for these people. Additionally, lack of access to food can promote mental health issues, which further can result in poor diets. Centering food justice in public health efforts will be key in addressing these issues in the coming years.

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References: Alkerwi, A., Vernier, C., Sauvageot, N., Crichton, G. E., & Elias, M. F. (2015). Demographic and socioeconomic disparity in nutrition: Application of a novel Correlated Component Regression approach. BMJ Open, 5(5), e006814–e006814. https://doi.org/10.1136/bmjopen-2014-006814 Am, Barroso, a, & Brown, A. (n.d.). Gender pay gap in U.S. held steady in 2020. Pew Research Center. Retrieved February 6, 2022, from https:// www.pewresearch.org/fact-tank/2021/05/25/ gender-pay-gap-facts/ ARIC Study Investigators, Wang, L., Folsom, A. R., Zheng, Z.-J., Pankow, J. S., & Eckfeldt, J. H. (2003). Plasma fatty acid composition and incidence of diabetes in middle-aged adults: The Atherosclerosis Risk in Communities (ARIC) Study. The American Journal of Clinical Nutrition, 78(1), 91–98. https://doi.org/10.1093/ ajcn/78.1.91 Asfaw, A. (2011). Does consumption of processed foods explain disparities in the body weight of individuals? The case of Guatemala. Health Economics, 20(2), 184–195. https://doi. org/10.1002/hec.1579 Bahanan, L., Singhal, A., Zhao, Y., Scott, T., & Kaye, E. (2021). The association between food insecurity and dental caries among U.S. adults: Data from the National Health and Nutrition Examination survey. Community Dentistry and Oral Epidemiology, 49(5), 464–470. https://doi. org/10.1111/cdoe.12622 Barroso, A., & Brown, A. (n.d.). Gender pay gap in U.S. held steady in 2020. Pew Research Center. Retrieved February 7, 2022, from https://www. pewresearch.org/fact-tank/2021/05/25/genderpay-gap-facts/ Becker, C. B., Middlemass, K., Taylor, B., Johnson, C., & Gomez, F. (2017). Food insecurity and eating disorder pathology. International Journal of Eating Disorders, 50(9), 1031–1040. https:// doi.org/10.1002/eat.22735 Berkowitz, S. A., Berkowitz, T. S. Z., Meigs, J. B., & Wexler, D. J. (2017). Trends in food insecurity for adults with cardiometabolic disease in the United States: 2005-2012. PLOS ONE, 12(6), e0179172. https://doi.org/10.1371/journal.pone.0179172 Black and Hispanic youth unfairly targeted by fast food TV ads. (2021, July 2). https://www. medicalnewstoday.com/articles/fast-foodsequity-problem-Black-and-Hispanic-youthunfairly-targeted-by-ads Boston, 677 Huntington Avenue, & Ma 02115 +1495‑1000. (2013, November 20). The Best Diet: Quality Counts. The Nutrition Source. https:// www.hsph.harvard.edu/nutritionsource/healthyweight/best-diet-quality-counts/ Bower, K. M., Thorpe, R. J., Rohde, C., & Gaskin,

"The food that we eat is at the core of our health, both physical and mental."

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An Excavation of the American Healthcare STAFF WRITERS: PATRICK HERRIN ‘25, BRIDGET MCNALLY ‘24, ABENEZER SHEBERU ‘24, MARYANNE BARASA ‘25, ALLISON PITTMAN ‘25, JULIETTE COURTINE ‘24, JULIAN FRANCO JR. ’24, ANDREW BARRY ‘24, ELIZABETH LI ’25, NATHAN THOMPSON ‘25 TEAM LEAD: ANAHITA KODALI ‘23

Cover Image Source: Pixabay

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Introduction: Healthcare costs - What does the American government spend so much money on? In 2020, the United States government spent $4.1 trillion dollars on healthcare, a sharp 9.7 percent increase from 2019 spending and a 14.3 percent increase from 2018 (Centers for Medicare & Medicaid Services, 2021). While this marked increase is due in part to the federal allocation of funds to alleviate the fallout of the COVID-19 pandemic, there was also a sustained upsurge in healthcare spending as a percent of American Gross Domestic Product (GDP) from 13.3 percent in 2000 to 19.7 percent in 2020 (“U.S. National Health Expenditure as percent of GDP,” 2022); GDP measures the monetary value of the final version of various goods and services produced by a country in a specific time. When compared to other OECD (Organization for Economic Cooperation and Development) countries, the nature of U.S. healthcare spending renders the nation an outlier. In 2016, U.S. per capita healthcare spending ($9,892 that year) exceeded that of second place Switzerland by 25 percent, Canada by 108 percent, and the OECD median by a whopping 145 percent (“U.S. Health Care Spending Highest Among Developed Countries,” 2019). So, where does all the money go? The National

Health Expenditure Accounts (NHEA) breaks down health expenditures in the U.S. into the following ten categories, listed in descending order of percent of total expenditures: Hospital Care; Physician and Clinical Services; Retail Prescription Drugs; Health, Residential, and Personal Care Services; Nursing Care Facilities and Continuing Care Retirement Communities; Dental Services; Home Health Care; Other Professional Services (including services provided by occupational therapists, speech therapists, chiropractors, and private-duty nurses); Other Non-durable Medical Products (which covers retail sales of non-prescription drugs); and Durable Medical Equipment (which covers retail sales of ophthalmic products like glasses and contacts as well as hearing aids, wheelchairs, and rental of medical equipment) (“Historical”, 2021). While U.S. healthcare funds are distributed widely over the various types of services or products that are necessary for a fully functioning healthcare system, one question remains to be answered: does this increased spending translate to increased efficacy? Unfortunately, this does not seem to be the case. Research shows that there were only 7.9 nurses and 2.6 active physicians per 1,000 U.S. population in 2015, while the OECD medians were 9.9 and 3.2, respectively. That same year, OECD countries boasted a median of 3.4 DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

hospital beds per 1,000 population, whereas the U.S. had a mere 2.5 (“U.S. Health Care Spending Highest Among Developed Countries,” 2019). These disparities reflect a difference in medical resource pricing. The services and products which constitute the infrastructure of the healthcare system, as listed above, on average cost more in the United States than they do in other OECD countries. The most salient example is the sheer price of inpatient and outpatient care, entailing payments to hospitals and physicians, which currently accounts for roughly 51 percent of total U.S. healthcare spending (Cox & Kurani, 2020). Hospital procedures and physician salaries are more expensive in the U.S., driving up the price of the largest proportion of the American healthcare economy (“U.S. National Health Expenditure as percent of GDP,” 2022). All told, the discrepancy of spending in this sector alone accounts for 76.4 percent of the difference in U.S. healthcare spending compared to other OECD countries in 2018. Similarly, prescription drug prices are highly inflated in the U.S., contributing roughly 10 percent to the difference in healthcare spending that same year (Cox & Kurani, 2020). Where does the money come from? Given that healthcare spending is a large portion of The United States’ budget, it is important to discern where these funds come from and who supports this spending. There is a dual-pronged approach to funding health spending. The first and increasingly primary source is the portion of federal taxes that are collected through income taxes (“United State Tax Revenues”, 2019). These sources are variable, depending on which administration is in office – throughout the years, taxation rates have varied depending on the wealth and productivity of Americans. Thus, federal income tax is largely dependent on the state of the overall economy. A second source of funding is through private means and large insurance companies that reimburse or facilitate health expenditures (WHO Health Financing, 2017). While this is not a direct source of government funds, it can reimburse government spending on medical resources. Together, federal taxes and private capital contribute to hundreds of billions, approaching trillions, of dollars that fund the government and its health spending needs.

History: Historical reforms in American healthcare in WINTER/SPRING 2022

the 1980s Leading up to 1980, the U.S had been on par with other nations in healthcare spending per capita with respect to life expectancy. Although it is assumed that higher spending should coincide with a larger life expectancy, the U.S did not have a strong positive correlation compared to other countries. Since then, there has been a notable change in the U.S trajectory as we have spent significantly more than other nations with a minimal change in life expectancy (Frakt, 2018). A closer look into laws, acts, and amendments passed throughout the decade attributed to this increase in spending. During the onset of the 1980s, Medicaid expanded and raised the nation’s budget on healthcare expenses. The Boren Amendment of 1980 made it essential for nursing homes to be paid at “reasonable and adequate” rates by the states. This amendment was eventually repealed in 1997 due to state Medicaid officials’ concerns over its high cost (Wiener and Stevenson, 1998). In 1981, Omnibus Budget Reconciliation Act (OBRA 81) was passed and required states to provide additional Medicaid payments to hospitals with high rates of low-income patients who are old, blind, disabled, or a family member with dependent children. Furthermore, it repealed the requirement that state Medicaid programs pay hospital rates equivalent to those paid by the federal Medicare program (Library of Congress, 1981).

"Given that healthcare spending is a large portion of the United States' budget, it is important to discern where these funds come from and who supports this funding."

The Consolidated Omnibus Budget Reconciliation Act of 1985 (COBRA) is a law passed by Congress and signed by President Ronald Reagan. It dealt primarily with providing some workers and their family members, who lose health benefits upon the loss of a job, the right to choose to continue group health benefits provided by their health plan for limited periods of time under certain instances. These circumstances involve a voluntary or involuntary job loss, reduction in the hours worked, transition between jobs, death, divorce, and other life events (U.S. Department of Labor). The following year, OBRA 86 provided state Medicaid with options to cover infants, young children, and pregnant women up to 100% of the poverty level regardless of whether they receive public assistance (The Henry J. Kaiser Family Foundation). The 1988 Medicare Catastrophic Coverage Act (MCCA) expanded Medicare coverage to widend benefits for the elderly and disabled. After a strong negative reaction, the MCCA was repealed the following year, retracting these major provisions (Kagan, 2021).

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Figure 1: Percent share of GDP spent on healthcare in 2009. America spends significantly more money on healthcare than other OECD countries around the world. Image Source: Flickr Content Source: OECD Health Data 2009

With these reforms, life expectancy still did not increase as rapidly as the rate of U.S expenses on healthcare. Some outlying factors could include the lack of competition within the American health system and possible inflation (Frakt, 2018). Historical reforms in American healthcare in 1990s By the time President Clinton took office in 1993, National Health Expenditures (NHE) had been increasing by 10-14 percent annually for decades. NHE is a measure of the total amount the U.S. spends on “health care goods and services, public health activities, government administration, the net cost of health insurance, and investment related to health care” (Centers for Medicare and Medicaid Services [CMS], 2021). In 1990, NHE accounted for 12.1 percent of the U.S. GDP, a 7.1 percent increase over the last 30 years. This increase was largely associated with the development of expensive medical technologies and restrictions on Health Maintenance Organizations, which provide healthcare through provider networks for a fee (Moseley, 2008). Clinton and others were concerned about the effects this increase was having on American citizens and the economy. During his first week in office, President Clinton created the White House Task Force on Health Reform, the first major organized attempt to mend the American Healthcare System since Lyndon Johnson’s administration in 1965 (Kaiser Family Foundation [KFF], 2011). After the appointment of First Lady Hillary Clinton to Chair of the Task Force, it set to work to create a proposal for comprehensive reform of the American Healthcare System (Clinton Digital Library, n.d.). Ten months after his inauguration, 127

Clinton’s administration introduced the Health Security Bill. If passed, it would have modified the public-private system that we know today. Every citizen would be required to enroll in the health plan, through which all employers would be obligated to pay 80 percent of their employees’ health coverage (Clinton Digital Library, n.d.). It would be required to have a “Health Security Card” ensuring access to care. Despite increased government oversight, Americans would still have been able to choose between private insurance plans, fostering competition between private insurers. This “managed competition” model combined with universal coverage was thought to appease both liberals and conservatives in Congress (Oberlander, 2007). Small businesses and individuals without a separate employer would be subsidized by the government. The plan was also appealing because it avoided major new taxes and left Medicare intact. Despite the bipartisan allure the plan offered and the predicted benefits it promised, the bill ultimately failed to pass. Critics cited its length, complexity, and increase of government control over healthcare as bases for opposition (Oberlander, 2007). While the bill failed in 1994, many of its central ideas were repurposed in the successful Affordable Care Act. This failure did not mean that the 1990s did not see successful healthcare reform. In 1997, the State Children's Health Insurance Program (S-CHIP) was enacted as part of the Balanced Budget Act (KFF, 2011). To qualify for Medicaid, families needed to have extremely low income. S-CHIP provided grants to states for low-income children who did not quite qualify for Medicaid DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

to be covered. The eligibility requirements for disabled Americans were also changed to increase coverage. Finally, arguably the most important reform of the 1990s was the passage of the Health Insurance Portability and Accountability Act (HIPAA) in 1996. HIPAA had been a part of the Health Security Act, and it prevents insurance companies from using pre-existing conditions in determining coverage (Manchikanti et al., 2017). HIPAA is also the authority on medical privacy and encourages longer-term coverage through tax benefits (KFF, 2011). While the 1990s did not see the level of reform that many Americans had hoped, policymakers created established a framework for future healthcare legislation was created, and the passage of S-CHIP and HIPAA provided muchneeded protection for millions of Americans. Stakeholders of American Healthcare: The patients Patients are critical stakeholders of the American healthcare system, yet the system supposedly designed to serve them has many flaws that have contributed to the health inequities that we see in the United States today. To illustrate the issue, consider a state in the United States with more than 21 hospitals available for open heart surgery, three of which can perform transplants; the state also has more MRI machines than in all of Canada and a large population of specialists. At first glance, these numbers may seem to suggest a thriving, well-funded healthcare system. Yet the reality is bleak— at the same time these numbers were recorded for the state of Colorado, more than 50 percent of those hospital beds were empty, 21 percent of women were giving birth without sufficient prenatal care, and roughly 450,000 citizens were uninsured (with another 400,000 uninsured residents on top of that) (Lamm, 1994). The fundamental goal of any healthcare system is to preserve and promote the continued health of a target population, but this objective is compromised if the system maintains inequality at an institutional level. The scenario described above is not an isolated occurrence. At its most basic level, the American healthcare system is not structured to serve its patient stakeholders equitably. Primary contributors to this inequality are the ideologies and legislation of the United States’ political system. Since 1965 when Medicaid and Medicare were enacted, the American healthcare system has seen no substantial Congressional legislation promoting universal healthcare or expansion in coverage with the important exception of the Affordable Care Act in 2010.

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On the contrary, a large portion of legislation in the United States in the past 30 years has been looking to reduce and even terminate healthcare programs, especially those that support the health of migrants, dependent children, and the working poor (Putsch & Pololi, 2004). Furthermore, an individualized (and usually racialized) ideology has permeated the healthcare system through political channels, leading to general population perceptions that those patients who cannot afford insurance are responsible for their situations and should not be supported by the insured population. This thinking is reflected in healthcare financing for patients. Health insurance in the United States is balanced so that the public sector addresses mutual aid needs and private health insurance aims for actuarial fairness (meaning that they strive for adequate and fair premiums for business), leading to higher-risk populations being neglected (Putsch & Pololi, 2004). Furthermore, this ideology has permeated institutional practices and clinical decisions. Under the guise of business and marketing concerns, institutions can choose to locate facilities in suburban areas distant from low-income populations, and clinicians have been documented to describe low income, low intelligence, or otherwise less favorable patients in negative terminology (George & Dundes, 1978). The individual and institutionalized inequality of patients in the American healthcare system is exacerbated by a tradition of research that, remarkably, lacked patient input. Today, patient stakeholder input has begun to be prioritized (with one notable advancement being the founding of the Patient-Centered Outcomes Research Institute [PCORI] in 2010), allowing the healthcare system to gain important insights into primary stakeholder values and expectations (Fleurence et al., 2013). This is a positive indicator that the healthcare system is beginning to prioritize patients, although due to discriminatory biases, it is clear there are larger structural changes that must take place for the United States to achieve equitable patient care.

"Patients are critical stakeholders of the American healthcare system, yet the system supposedly designed to serve them has many flaws that have contributed to the health inequities we see..."

The physicians When considering how the American healthcare system works and where it needs to be reformed, it can be easy to forget one of the most vital features: physicians. Physicians are the cornerstone of healthcare. After completing an odyssey of education, observation, and training, they strive to both keep people healthy and treat people’s illnesses. Physicians must maintain a vast and intricate understanding of the human body and the injuries and diseases that afflict it, often while specializing in a specific subfield. At

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"One of the best ways to help physicians maximize the quality of care they give is by directly involving them in workplace culture shifts."

the same time, they must be skilled in interacting with administration, colleagues, and, most importantly, patients. Not only is the road to practicing medicine long and laborious, practicing medicine can be stressful and exhausting. Even before the added dangers and workload resulting from the COVID-19 pandemic, physicians were facing significant levels of stress and burnout (Yates, 2020). Part of this issue involves a lack of help; a severe shortage of doctors is developing, and it is projected that there will be a shortage of between 37,800 and 124,000 physicians by 2034 (Association of American Medical Colleges [AAMC], 2021). Without physicians, let alone those who are not stressed our burnt out, the American healthcare system is in deep trouble. However, there are changes we can make to the system that will make life easier for physicians and in turn improve the quality of their care. Immediately after medical school, physicians-intraining are faced with some of the most difficult years of their career: residency. Residency is a crucial part of training to become a doctor, as students get hundreds of hours of direct clinical experience. Before becoming a doctor, it is important to be immersed in the complex world of medicine without taking on undue responsibility. However, residency is a grueling period that subjects students to long hours, sleep deprivation, and a lack of time off. Because residency lasts three to seven years, it is not something that students can merely “stick out”; they must adjust to the stressful and exhausting routine. Sleep deprivation and chronic overworking decreases productivity and the quality of care that residents can provide. By reducing residents’ shift lengths, increasing their supervision by physicians, and limiting their caseload based on experience, residents would not feel the burden of an unhealthy work-life balances much and would improve the quality of their care. This would save billions of dollars in preventable medical errors by residents (Institute of Medicine, 2009). One of the best ways to help physicians maximize the quality of care they give is by directly involving them in workplace culture shifts. Participatory organization allows physicians to collaboratively identify workload overloads, unnecessary time sinks, areas that need more independent control, and communication issues (Weigl, 2013). Even if the physician shortage continues, the current system can be modified to maximize the number of patients physicians can see. For example, Telehealth visits, popularized during the COVID-19 pandemic, decrease wait times for patients and are often sufficient for

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the physician to make an informed decision and communicate it to the patient (Mangiofico, 2018). Telehealth also improves access to care, by allowing doctors to reach underserved rural and low-population areas more easily. Other methods of decreasing workload include increasing the number of physician assistants and minimizing unnecessary training requirements (Berg, 2022). Improvements can also be made in how physicians are compensated. While the current system does not favor low-income patients, it also does not fairly reimburse physicians for the quality of work they perform or for the relative burden of their workload. Right now, physicians are compensated on a fee-for-service basis, meaning they are paid based on the quantity of services that they perform, rather than the quality (i.e. the appropriateness of the services and the outcomes) (Pearl, 2015). This system becomes problematic because it rewards healthcare providers with more physicians. Complex operations and medical equipment are expensive, both for the provider and the patient. When a hospital has more resources, it can afford to use those resources and will choose to do so more often, even if less invasive, cheaper options may be available. By switching to a “pay-for-value” system of compensation, physicians would be rewarded for positive outcomes and aptness of their care instead of simply how much care they provide. This system would benefit both physicians and patients. The payers As the name suggests, the payers in in healthcare are the stakeholders that actually pay for a health service. They are responsible for processing eligibility, enrollment, claims, and payments for all of the patients that utilize their service. Examples of payers include insurance companies and government entities like the Centers for Medicare and Medicaid in the United States (“What Is the Difference Between Payers and Providers?”, 2019). There are several things that payers want in healthcare systems. Both the government and private insurers want shorter hospitalization times, shorter delays, shorter wait times, and quick returns to work for patients who are employed (Registry Stakeholders, n.d.). In essence, payers are invested in having more efficient healthcare systems. The policymakers Another stakeholder in the American Healthcare Industry are policymakers. They are essentially public health agencies and regulators with various jobs that create and maintain the healthcare system our nation uses today (Lübbeke et al.,

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Image 2: Patients and physicians are two of the most important stakeholders in the American healthcare system. Image Source: Pixabay

2019). It is through the framework they establish that healthcare is provided and accessible to the country’s citizens (Connecting Health Information Systems for Better Health, 2014). Policymakers undertake ample tasks to help uphold our current healthcare system. They gather and analyze information given to them directly from regional, national, and international patients, providers, and payers to assess and critique health technology and policy nationwide (Lübbeke et al., 2019). The results and outcomes produced by hospitals around the nation are compared to the benchmarks that these health policymakers set (Connecting Health Information Systems for Better Health, 2014). Furthermore, they often go further than just outcomes and assess the equipment used for the care. For example, they supervise implant systems and make sure that the nationally manufactured and the imported products used have met certain standards and specifications so that they are safe and reliable for public usage (Lübbeke et al., 2019). Policymakers also answer crucial questions like who is eligible to receive care, what care services are provided, how services are paid for, whether the services are being delivered well and are accessible, and others (Connecting Health Information Systems for Better Health, 2014). Providers and payers operate within the boundaries that the policymakers lay out. These boundaries aim to maximize health and increase the number of good, non-complicated patient outcomes within the country’s financial and resource constraints.

Sources of private health insurance can be described as a patchwork of privately owned systems and programs that offer private insurance plans to their clients. This includes, but is not limited to, subsidized plans by employers, individually procured private plans outside of employment, coverage through TRICARE and other less regulated private plans that pay for one specific type of service or provide coverage in case of an emergency such as dental insurance, accident coverage or any other miscellaneous coverage for emergency hospital visits. The Health Insurance Organization formally refers to private health insurance as health insurance plans marketed by the private health insurance industry, as opposed to government-run insurance programs such Medicare and Medicaid (“What is private health insurance?” 2022). For years, private sources of American healthcare have remained the most prevalent in most American households. This is evident from the most recent report by the Centers for Disease Control and Prevention (CDC), which shows that in the months JanuaryJuly of 2021, 66.3 percent of adults (aged 18-64) were most likely to receive health care services under a private program (Cohen et al., n.d.). Additionally, the US Census Bureau released data that further concur with this report and provides analysis showing that in 2020, of the subtypes of private health insurance coverage, employmentbased insurance was the most common, covering 54.4 percent of the population for part of or the entire calendar year while 10.5 percent relied on direct purchase. (“Health insurance coverage in the United States”, 2021).

Sources of American Healthcare: Private

The federal Health Insurance Marketplace, which is also called the "Marketplace" or "Exchange," is

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"66.2 percent of adults (aged 18-64) were most likely to receive health care services under a private program (Cohen et al, n.d)."

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the website where individuals can browse various health care plans available under the Affordable Care Act, commonly known as "Obamacare," as well as compare them, and purchase health insurance. (Loftsgordon, 2021) TRICARE is a military health care program for active duty and retired members of the uniformed services, their families, and survivors. (Health Insurance Glossary, 2021)

"Numerous studies have found that ketamine is a promising alternative to traditional antidepressants due to its ability to rapidly onset, be effective, and yield lasting impacts."

Private sources of health insurance are regulated by the government where States primarily regulate health insurance by setting standards for when and on what terms a state-licensed health insurer must accept an applicant. Federal laws also regulate health insurance, including ERISA (Employee Retirement Income Security Act of 1974) and HIPAA (The Health Insurance Portability and Accountability Act of 1996). ERISA establishes national standards for employer- and union-sponsored health plan (Understanding Health Insurance). HIPAA required the creation of national standards to protect sensitive patient health information from being disclosed without the patient's consent or knowledge (Health Insurance Portability and Accountability Act of 1996, 2018). Medicare: Medicare is a federal health program managed by the Centers for Medicare and Medicaid Services (CMS). It provides health coverage regardless of income if you are 65 or older, or if you have a disability and are under 65 years of age (Medicare Rights Center, n.d.). Alternatively, individuals who have been diagnosed with Lou Gehrig’s (ALS) disease or an end-stage renal disease are immediately eligible as well (SAMHSA Soar, n.d.).

Image 3:Ayahuasca, one of the oldest used psychedelics that is part of the culture of many indigenous populations scattered throughout South America, is commonly ingested through tea made from the boiling of the leaves. Image Source: Wikimedia Commons

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The benefits of Medicare are categorized into four different parts. They each provide different coverage at similar prices. Part A covers inpatient care (SAMHSA Soar). One (or one’s spouse) must have paid Medicare taxes for at least ten years to qualify (McWhinney, 2022). Part B covers items like lab work, wheelchairs, outpatient care, etc. Part C uses private Medicare-approved agencies to provide Medicare Advantage Plans (i.e. Health Maintenance Organization or Preferred Provider Organization) (SAMHSA Soar, n.d.). Part C additionally offers vision, hearing, and dental coverage (McWhinney, 2022). Part D covers prescription drugs; however, participants typically pay for Part D out-of-pocket. Typically, Medicare costs vary from plan to plan. In 2022, the cost for Part A premium per month is $499 (McWhinney, 2022). The Part A

hospital inpatient deductible and coinsurance for each benefit period is $1,556. The Part B premium is $170.10, and its deductible and coinsurance are $233. For Part C and D, prices vary by plan considering these plans allow you to use private agencies (McWhinney, 2022). Medicaid Medicaid is a national and state-level program that helps fund health-related necessities for low-income residents of the United States. It was put in place as part of the Affordable Care Act, providing free health insurance to 74 million low-income and disabled people (Coleman, 2021). Medicaid and Medicare can be combined if one satisfies the requirements of being both low-income and elderly, respectively (FAQs Category, n.d.). Before Medicaid's enactment on the federal level, smaller state Medicaid programs only covered children, some parents, and women who are both low-income and pregnant (Gottlieb & Shepard, 2017). Medicaid was one of the first programs of its kind that provided such expansive coverage on a national level (“Status of State Medicaid Expansion Decisions,” 2022). The program brings numerous benefits at the federal level, and states may also opt-in to optional benefits. Mandatory benefits include hospital services at both the impatient and outpatient level, health services at the physician's office and at home, birth center services, x-rays, and transportation to medical care (Mandatory & Optional Medicaid Benefits, n.d.). States may choose among a selection of optional services such as Speech, hearing and language disorder services, prescription glasses, prosthetics, and physical therapy (Mandatory & Optional Medicaid Benefits, n.d.). While Medicaid has a variety of intended benefits, it has also brought certain tradeoffs with no clear ways to resolve such issues. For example, while one of Medicaid's purposes is to reduce last-minute ER visits, emergency room use has increased by 40 percent for people who enter the program. Moreover, doctor's office visits increased by 50 percent, hospitalizations by 30 percent, and prescription drug use by 15 percent (Gottlieb & Shepard, 2017). These increases could reflect potential exploitation of the system, but they could also represent an increased awareness for self-care from a population that could not afford to do so previously. Due to pressures to repeal the Affordable Care Act, the government has reduced spendings for Medicaid by an estimated $800 billion (Gottlieb & Shepard, 2017). Inequities in Health due to Lack of Insurance: Inequities in patient outcomes: insured versus DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

uninsured One of the difficulties in evaluating the discrepancies between those with health insurance and those without is that the utilization of resources will vary for the two groups. Those who aren’t insured will be more reluctant to use resources due to the cost, so much of the data must be adjusted when analyzed. Even after adjustment, there are still stark differences between groups with insurance and their non-insured counterparts. Two 2012 studies completed at the Harvard Chan School found that health care insurance could prevent tens of thousands of premature deaths (Powell, 2019). This is reflected in the life expectancy of people with higher income (who are more likely to afford health care insurance), which has been 12 years longer than that of lower income people since 1940 (Bosworth et al., 2016) Premature deaths caused by inferior healthcare are mostly seen in ages beyond twenty-five and are likely explained by a lack of access to preventative care. As years of poor health care pile up, adverse health effects begin to manifest themselves by age twenty-five and above (McWilliams, 2009). However, those with health insurance will be provided with higher quality resources, as well as be able to seek them out more consistently, resulting in lower rates of premature deaths. The National Library of Medicine conducted a study that found, among other healthcare inequality issues, that rates of influenza vaccination, cholesterol testing, mammography, and diagnosed hypertension rose in ranges of 5-10 percent in people above 65 compared to those below (McWilliams, 2009). Near-elderly adults who had lost their insurance were 82 percent more likely to report a decline in their own health than those who kept their private insurance (McWilliams, 2009). Outside of general care, recent studies have found that uninsured adults who are dealing with hypertension have significantly worse adjusted rates of blood pressure control (McWilliams, 2009). As it stands, patients without health care will continue to have an increase in medical concerns accompanied by a decrease in quality medical assistance to those who are privately insured. Who has access to insurance? Disparities on racial/ethnic lines Data shows that racial and ethnic minority groups in our nation experience higher rates of illness from a wide range of health conditions such as diabetes, hypertension, obesity, asthma, and heart disease compared to the majority people groups (CDC, 2021). Furthermore, numerous projects over the years have shown that racial/ethnic WINTER/SPRING 2022

minority groups have disproportionately higher morbidity rates than their white counterparts (Bridges, 2018). More specifically, the life expectancy of non-Hispanic/Black Americans is four years lower (CDC, 2021). Many factors likely contribute to this, but a major contributor to this problem is the lower quality of care that minority groups on average receive from their providers. It isn’t only implicit biases that are at play here. Undocumented immigrants along with documented immigrants who have been in the country for less than five years are not eligible for public health insurance. There is an evident twotiered health care system that disproportionately affects racial/ethnic minority groups in the United States (Bridges, 2018). The problem lies both within individuals and the system we live in. Regardless of whether the negative bias towards minority groups from providers is implicit or not, its eradication must be encouraged. There must be conversations surrounding these topics, especially considering how such conversations could have tangible effects on the minority healthcare experience. Who has access to insurance? Disparities on economic lines In the United States, economic status poses perhaps the largest barrier to health insurance access; for many Americans, the cost of healthcare is simply too high. According to the 2019 National Health Interview Survey, the largest proportion (73.3 percent) of uninsured U.S. citizens reported being uninsured because coverage was not affordable. Despite the implementation of the Affordable Care Act (ACA) reducing the total of uninsured American citizens by 20 million in 2016, the following years saw another uptick in the percentage of the population who did not receive health coverage. Family income proves to be a large indicator of who is insured and who is not: over 80 percent of uninsured citizens lived 400 or more percent below the poverty line in 2019, and those 200 or more percent below were at the highest risk for being uninsured (Tolbert et al., 2020). Similarly, 72.5 percent of nonelderly, uninsured workers report that their employer does not offer them coverage, or the cost of the coverage they do offer is too steep (Tolbert et al., 2020). Insurance prices are outpacing wage growth, rendering those below 200 percent of the poverty line the most likely to be uninsured (Tolbert et al., 2020). Not only does one’s socioeconomic status itself determine eligibility or likelihood to obtain health insurance, but pairing one’s income status with eligibility for government subsidized aid, specifically Medicaid through the ACA and Marketplace subsidies, has also produced a sizeable coverage gap. In other 132

words, those who make too much to be covered by Medicaid and yet not enough to receive tax credits through ACA Marketplace reside in this “gap” where government aid for insurance is inaccessible and the cost of private health insurance is too steep (Garfied, et al., 2021). In those states which have not expanded coverage programs under the Biden administration, it is estimated that this “coverage gap” accounts for over 2 million low-income adults that are uninsured (Garfied, et al., 2021).

"Though the American government spends trillions of dollars on healthcare every year...health outcomes in American are not significantly better (and often worse) than comparably developed nations."

Who has access to insurance? Gender Disparities Disparities in accessing health insurance spread across gender lines as well. Historically, men have been more likely to be uninsured than women; however, women are more likely to be enrolled in public health insurance coverage, while men are more likely to have coverage through an employer. This difference leads to a whole host of problems; most notably, it becomes more difficult for women to access necessary healthcare services under their insurance plans. For the past twenty years, men have lagged behind women in health insurance coverage. As of 2020, 10.5 percent of women in the United States were uninsured, as compared to 13.4 percent of men who were uninsured at this time (Kaiser Family Foundation, 2022). According to a 2015 census, this gap is primarily among working-aged individuals; the gap shrinks with increasing age. Among both sexes, the uninsured rate peaks at age 26, the age where children are no longer covered under their parents’ health insurance policies, and then falls as individuals approach their mid-60s, wherein the uninsured rate sharply drops for individuals 65+ (United States Census, 2015). While women are more likely than men to be insured, men are more likely to be on private (employer) insurance plans. In 2020, 61.5 percent of men were on their employer’s health insurance plans, as compared to 61.4 percent of women (Kaiser Family Foundation, 2022). While this difference may not seem significant, it significantly impacts woman who are on Medicare and Medicaid or other public insurance coverage mechanisms. 18.5 percent of women reported to be on public insurance in 2020, while only 15.1 percent of men reported themselves as being covered by a public insurance provider (Kaiser Family Foundation, 2022). However, these public insurance plans often make it difficult for women to access necessary care, because insurance companies associate the female gender with more health issues, complications, and interactions

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with the healthcare system. For many insurance providers, being a woman is a “preexisting condition” that they can charge higher prices for (The Commonwealth Fund, 2017). Because of this, women pay more, on average, for health insurance than do their male counterparts. For example, in 2013, the U.S. Government Accountability Office found that individualmarket plans in 38 states charged a nonsmoking 30-year-old single woman a higher premium than her male counterpart (The Commonwealth Fund, 2017). These prices make it increasingly difficult for women to attain and pay for health insurance plans; many women have even found that providers exclude necessary health services related to reproductive health––such as breast and colon cancer screenings, contraceptives, and preventative care––from their plans. Finally, the gender disparity in attaining appropriate health insurance interacts with insurance disparities along racial, ethnic, and geographical lines. Women who identify as Latina and/or Black are more likely to be uninsured than are women who identify as white. From a geographical lens, women reported higher uninsured rates in states such as Texas (25 percent uninsured) and Florida (17 percent uninsured), as compared to much lower uninsured rates in California and New York. These states reported uninsured rates of 10 percent and 5 percent, respectively (The Commonwealth Fund, 2017). The 2010 Affordable Care Act (ACA) allowed both men and women to make strides in their health insurance coverage; after the ACA was passed, women’s uninsured rates decreased 9 percent (The Commonwealth Fund, 2017). Men experienced a similar drop in uninsured rates because of the ACA. Conclusion America’s healthcare system is incredibly complex and can be difficult to navigate. Though the American government spends trillions of dollars on healthcare every year – vastly more than most of its peer governments around the world – health outcomes in America are not significantly better (and often worse) than comparably developed nations. There are deep disparities across racial, economic, and gender lines that crosscut which Americans have access to insurance and therefore which Americans can afford healthcare. By better targeting the root causes of disparities in medicine at the legislative and individual levels, healthcare can become more accessible to all Americans, regardless of background. References 5 critical actions to take now to improve physician DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

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Adults in States that Do Not Expand Medicaid. KFF. https://www.kff.org/medicaid/issue-brief/ the-coverage-gap-uninsured-poor-adults-instates-that-do-not-expand-medicaid/ Gender and Insurance Costs. (n.d.). Investopedia. Retrieved April 25, 2022, from https://www. investopedia.com/gender-and-insurancecosts-5114126 Hartman, M., Martin, A. B., Washington, B., Catlin, A., & The National Health Expenditure Accounts Team. (2022a). National Health Care Spending In 2020: Growth Driven By Federal Spending In Response To The COVID-19 Pandemic: National Health Expenditures study examines US health care spending in 2020. Health Affairs, 41(1), 13–25. https://doi.org/10.1377/ hlthaff.2021.01763 Health financing. (n.d.). Retrieved April 25, 2022, from https://www.who.int/health-topics/healthfinancing Health Insurance Coverage of Men 19-64 (CPS) | KFF. (n.d.). Retrieved April 25, 2022, from https://www.kff.org/other/state-indicator/ health-insurance-coverage-of-men-19-64-cps/?c urrentTimeframe=0&sortModel=%7B%22colId %22:%22Location%22,%22sort%22:%22asc%22 %7D How the Patient-Centered Outcomes Research Institute is engaging patients and others in shaping its research agenda—PubMed. (n.d.). Retrieved April 25, 2022, from https://pubmed. ncbi.nlm.nih.gov/23381533/ Iii, G. B. M. (2008). The U.S. Health Care NonSystem, 1908-2008. AMA Journal of Ethics, 10(5), 324–331. https://doi.org/10.1001/virtualm entor.2008.10.5.mhst1-0805 Implicit Bias and Racial Disparities in Health Care. (n.d.). Retrieved April 25, 2022, from https://www.americanbar.org/groups/crsj/ publications/human_rights_magazine_home/ the-state-of-healthcare-in-the-united-states/ racial-disparities-in-health-care/ Key Facts about the Uninsured Population | KFF. (n.d.). Retrieved April 25, 2022, from https:// www.kff.org/uninsured/issue-brief/key-factsabout-the-uninsured-population/ Learning from Failure in Health Care Reform | NEJM. (n.d.). Retrieved April 25, 2022, from https://www.nejm.org/doi/full/10.1056/ nejmp078201 Leveraging interoperability standards to link patient, P., & Network, J. L. (2014). 3. Introducing the Key Stakeholders: Patients, Providers, Payors, and Policymakers (the Four P’s). https://jln1. pressbooks.com/chapter/3-introducing-the-keystakeholders-patients-providers-payors-andpolicymakers-the-four-ps/ Manchikanti, L., Ii, S. H., Benyamin, R. M., & Hirsch, J. A. (n.d.). Evolution of US Health Care 134

Reform. Pain Physician, 4. Mandatory & Optional Medicaid Benefits | Medicaid. (n.d.). Retrieved April 25, 2022, from https://www.medicaid.gov/medicaid/benefits/ mandatory-optional-medicaid-benefits/index. html McWilliams, J. M. (2009). Health consequences of uninsurance among adults in the United States: Recent evidence and implications. The Milbank Quarterly, 87(2), 443–494. https://doi. org/10.1111/j.1468-0009.2009.00564.x Medicaid and Medicare: An Overview | SOAR Works! (n.d.). Retrieved April 25, 2022, from https://soarworks.samhsa.gov/article/medicaidand-medicare-overview Medicare vs. Medicaid: What’s the Difference? (n.d.). Investopedia. Retrieved April 25, 2022, from https://www.investopedia.com/articles/ pf/07/medicare-vs-medicaid.asp Medicine (US), I. of. (2009). Improving the Nation’s Health Care System. In Informing the Future: Critical Issues in Health: Fifth Edition. National Academies Press (US). https://www. ncbi.nlm.nih.gov/books/NBK219839/ Merzel, C. (2000). Gender differences in health care access indicators in an urban, low-income community. American Journal of Public Health, 90(6), 909–916. Physician Shortage Requires Multi-Prong Solution. (n.d.). Retrieved April 25, 2022, from https://www.ajmc.com/view/physician-shortagerequires-multiprong-solution Physician Stress and Burnout—ScienceDirect. (n.d.). Retrieved April 25, 2022, from https:// www.sciencedirect.com/science/article/pii/ S0002934319307570?via%3Dihub Putsch, R. W., & Pololi, L. (2004). Distributive Justice in American Healthcare: Institutions, Power, and the Equitable Care of Patients. THE AMERICAN JOURNAL OF MANAGED CARE, 10, 9. Registry stakeholders—PMC. (n.d.). Retrieved April 25, 2022, from https://www.ncbi.nlm.nih. gov/pmc/articles/PMC6549107/ The costs of inequality: Money = quality health care = longer life – Harvard Gazette. (n.d.). Retrieved April 25, 2022, from https://news. harvard.edu/gazette/story/2016/02/moneyquality-health-care-longer-life/ The effects of improving hospital physicians working conditions on patient care: A prospective, controlled intervention study | BMC Health Services Research | Full Text. (n.d.). Retrieved April 25, 2022, from https:// bmchealthser vres.biomedcentral.com/ articles/10.1186/1472-6963-13-401 The ethics of excess. - Free Online Library. (n.d.). Retrieved April 25, 2022, from https://www.thefreelibrary.com/ The+ethics+of+excess-a016029057 135

The Gomer: A Figure of American Hospital Folk Speech on JSTOR. (n.d.). Retrieved April 25, 2022, from https://www.jstor.org/stable/539575? origin=crossref&seq=1 Three Ways to Transform American Health Care. (n.d.). Stanford Graduate School of Business. Retrieved April 25, 2022, from https://www.gsb. stanford.edu/insights/three-ways-transformamerican-healthcare Understanding and Addressing Racial Disparities in Health Care—PMC. (n.d.). Retrieved April 25, 2022, from https://www.ncbi.nlm.nih.gov/pmc/ articles/PMC4194634/ Universal Heatlh Care. (n.d.). The Balance. Retrieved April 25, 2022, from https://www. thebalance.com/universal-health-care-4156211 U.S. Health Care Spending Highest Among Developed Countries | Johns Hopkins. (n.d.). Retrieved April 25, 2022, from https:// publichealth.jhu.edu/2019/us-health-carespending-highest-among-developed-countries U.S. health spending as share of GDP 19602020. (n.d.). Statista. Retrieved April 25, 2022, from https://www.statista.com/statistics/184968/ us-health-expenditure-as-percent-of-gdpsince-1960/ What drives health spending in the U.S. compared to other countries. (n.d.). Peterson-KFF Health System Tracker. Retrieved April 25, 2022, from https://www.healthsystemtracker.org/brief/whatdrives-health-spending-in-the-u-s-comparedto-other-countries/ What growing life expectancy gaps mean for the promise of Social Security. (n.d.). Retrieved April 25, 2022, from https://www.brookings. edu/research/what-growing-life-expectancyg a p s - m e a n - f o r- t h e - p r o m i s e - o f - s o c i a l security/#recent/ What Is the Difference Between Payers and Providers? (2019, September 25). Signature Performance. https://www. signatureperformance.com/understanding-thedifference-between-payers-and-providers/ Writer, A. P. H. S. (2016, February 22). The costs of inequality: Money = quality health care = longer life. Harvard Gazette. https://news.harvard.edu/ gazette/story/2016/02/money-quality-healthcare-longer-life/ Zhang, B. P. B., Gary Burtless, and Kan. (2016, February 12). What growing life expectancy gaps mean for the promise of Social Security. Brookings. https://www.brookings.edu/research/ what-growing-life-expectancy-gaps-mean-forthe-promise-of-social-security/

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Assisted Reproductive Technology: An Overview STAFF WRITIERS: MADELEINE CARR '24, ISABELLE KOCHER '22, SUMMER HARGRAVE '25, ELIZABETH LI '25, CAROLINE CONWAY '24 TEAM LEAD: ADITI GUPTA '23 Cover Image: Four Cell-Stage Human Embryos after in-vitro fertilization

Introduction to ART (assisted reproductive technology)

Image Source: Wikimedia Commons

On July 25, 1978, Louise Brown was born at Royal Oldham Hospital in the United Kingdom to her biological mother and father, Lesley and John Brown. This birth marked the dawn of a new age of assistive reproductive technology (ART). After attempting to procreate naturally for nine years without success, Lesley underwent a laparoscopic procedure during her natural ovulation to have an oocyte (more commonly known as an egg) removed. After the oocyte was removed from Lesley’s body, it was fertilized by John’s sperm in a lab. After a few days, a doctor placed an 8-cell stage embryo inside Lesley’s uterine cavity (Kamel, 2013). As of 2022, Louise Brown is 43 years old and is married with two children of her own. The incredible story of Louise Brown’s birth in 1978 was only the beginning of modern ART usage. In 1992, the Centers for Disease Control and Prevention (CDC) defined ART to be “all fertility treatments in which either eggs or embryos are handled” (“Assisted…,” 2022). Over the years, technology has changed, advanced, and multiplied, ushering in a new age of human

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reproduction. Some examples of ART include In Vitro Fertilization (IVF), Intrauterine Insemination (IUI), and Gamete Intrafallopian Transfer (GIFT). Based on the CDC’s 2019 Fertility Clinic Success Rates Report, 2.1% of all infants born in the US are conceived via ART (2021). In the last decade, ART use has more than doubled (“Assisted…,” 2022). The growing use of this technology has allowed millions who have struggled with infertility – which affects 1 in 5 heterosexual women aged 15 to 49 years old – the opportunity to start a family ( “Infertility,” 2022). Major Types of ART A. In Vitro Fertilization (IVF) IVF is by far the most common type of ART (“Assisted…”, 2022). According to the CDC, IVF is a procedure in which a woman’s eggs are removed from her body, and these eggs are fertilized in vitro, or in lab cultures. Once fertilization has occurred, the embryos are transferred back into a woman’s uterus (“Assisted…”, 2022). The success rates for IVF vary for each patient, most notably by age. For example, according to the Society for Assisted Reproductive Technology (SART), the chance that a single cycle of IVF will result in a live singleton birth is 51.0% for women under the DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

age of 35, 38.3% for women between 35-37 years, and just 25.1% for women aged 38-40 years old (SART, 2019). B. Surrogacy In addition to in vitro fertilization (IVF), another major type of ART is surrogacy. The term “surrogate” is derived from the Latin word “subrogare,” meaning “to substitute” (Patel et al., 2018). In the context of an ART, this is essentially what a surrogate does: substitute. There are two main types of surrogacies: traditional and gestational. Traditional surrogacy involves artificial insemination of a surrogate mother with the sperm of the intended father, making the surrogate is the biological mother of the child. On the other hand, gestational surrogacy occurs when an embryo, which contains the genetic makeup of both intended parents, is inserted into the surrogate uterus (Patel et al., 2018). A salient risk associated with the surrogate process is multiple order pregnancy, which occurs when more than one embryo is inserted into the uterus and can result in twins (Patel et al. 2018). In recent years, more clinics are following single embryo transfers to reduce this risk. Additionally, as shown by Foster’s study (1987), surrogates may experience potential psychological trauma when having to cede the child upon birth (Patel et al., 2018). In addition to physical and emotional risks, there are religious, ethical and socioeconomic concerns associated with surrogacy as an ART, which will be discussed later in this paper. Despite its successful utilization, surrogacy has become one of the most controversial forms of ART to date and must be considered alongside its inherent complexities. C. Others: GIFT/ZIFT/IUI Two additional types of ART are gamete intrafallopian transfer (GIFT) and zygote intrafallopian transfer (ZIFT), both modified versions of IVF. Like standard IVF, GIFT and ZIFT both require treatment with female sex hormones (like estridinol and progesterone) to assist implantation and prevent miscarriage. GIFT and ZIFT are often used by intended mothers with fallopian tube problems, as the gamete or zygote, respectively, are inserted in the oviducts below the point of blockage or concern (Jones & Lopez, 2014). After these techniques were developed in the 1980s, they became popularized since they do not require complex IVF culture systems or expertise, allowing for increased accessibility in clinics. They also appear to offer better results than IVF, perhaps because

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fertilization occurs in a natural system within the reproductive tract (Ankeny, 2017). With GIFT, fertilization occurs in vivo in the fallopian tube rather than during incubation in a lab. An incision is made in the abdomen and the gametes (egg and sperm) are inserted into the fallopian tubes (Ankeny, 2017). If successful, the fertilized egg (zygote) will travel to the uterus and pregnancy will occur. The ZIFT method is slightly different, where the fertilization of the egg with sperm occurs in vitro in a laboratory. Then, the fertilized zygotes are placed in the fallopian tubes and can travel down the oviduct before implantation (Jones & Lopez, 2014). Though the success rates of GIFT and ZIFT are comparable to IVF, these techniques are not widely used (Jones & Lopez, 2014). In addition to the aforementioned types of ART, Intrauterine Insemination (IUI) is yet another option. In IUI, the sperm is placed in the uterine cavity during ovulation and does not necessarily require treatment with additional hormones. However, IUI has not been shown to be significantly effective in increasing conception rates (Human Reproduction, 2009). More research is necessary for IUI as a successful mechanism of ART.

"...the chance that a single IVF cycle will result in a live singleton birth is 51% for women under the age of 35...(SART , 2019)."

Use of ART over time The first accomplishment in the field of assisted reproduction occurred in 1779, when Italian priest and physiologist Lazzaro Spallanzani confirmed, through artificial insemination in dogs, that embryo development is the result of fusion between the egg and the sperm (Bozzini et al., 2016). This marked a key period of changing perceptions surrounding human reproduction and intercourse. Spallanzani established that sperm could be frozen and preserved, leading to advancements in ART in the animal industry and, several years later, human medicine. Eleven years after Spallanzani’s innovation, the first successful case of intrauterine insemination in a human took place (Sharma et al., 2018). In the late 1800s, the medical field experienced a mass transition from intrauterine insemination to in vitro fertilization (IVF). By the end of the 19th century, Cambridge professor Walter Heape reported the first case of embryo transfer in rabbits, and almost a century later, Robert G. Edwards and Patrick Steptoe performed the first successful IVF in Leslie Brown, leading to the birth of the world’s first test tube baby in 1978 (Steptoe & Edwards, 1978). However, while demand for ARTs has surged, success rates “remain stagnant with less than one in five IVF treatment cycles resulting in a live

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birth” (“Sex, Science”, 2017). According to the Society for Assisted Reproductive Technologies (SART), the proportion of cycles with no reported outcome surged from 2005 to 2010, contributing to misleadingly high ART success rates (“2019 Assisted”, 2022). In addition, fertility clinics that accept a higher percentage of couples with previously unsuccessful IVFs are more likely to experience lower success rates, further contributing to the stagnant trend (“Reported IVF”, 2013).

"For the patient, the single biggest risk factor is multiple pregancies from IVF..."

ART and associated risk factors Like all medical procedures and interventions, ART carries certain risks. For the patient, the single biggest risk factor is multiple pregnancies from IVF, which has many consequences (Morgan, 2017). The patient can develop high blood pressure and preeclampsia—damage to the kidney or other organs (“Preeclampsia,” 2022). Preeclampsia can lead to symptoms including kidney problems, weight gain, and headaches. Individuals pregnant via ART are also at an increased risk for needing a cesarean section, which is more common in ART-related pregnancies that feature multiple pregnancies, placental abnormalities, and/or congenital fetal anomalies (Morgan, 2017). Moreover, there is a slight increase in the likelihood of severe pregnancy complications and maternal mortality, occurring in 1 in 200 (0.5%) of patients who conceive via ART (Martin et al., 2016). ARTs also has various risk factors for the offspring. Two of the most prominent side effects are low birth weight and prematurity, both of which again may be a result of multiple

pregnancies. For patients who gave birth to twins after IVF, compared to those with two singletons, there were dramatic increases of extremely low birth weight and preterm birth (Rebar, 2013). In addition to low birth weight and prematurity, ART has been shown to increase the risk of placental abnormalities, such as when the placenta separates from the uterine wall in advance (Cochrane et al., 2020). ART and accessibility While ART is hardly a new technology, it remains inaccessible for a significant portion of the global population. In 2000, a mere 45 of the World Health Organization’s 191 members offered IVF services in their nations, and this group was primarily comprised of wealthy Western nations (Collins, 2002). These numbers have since seen drastic growth, as a 2010 evaluation by the International Federation of Fertility Societies identified IVF clinics in over half the world’s countries with Japan, India, and the United States offering the most clinics (Inhorn & Patrizio, 2015). However, there are clear patterns of regional disparities in the distribution of ART services. For instance, while Asia, the Middle East, and Latin America have relatively high ART service offerings, many sub-Saharan African nations lack robust ART resources as represented by the number of clinics; (Jones et al., 2011). This regional disadvantage is particularly problematic because sub-Saharan African nations have especially high rates of secondary infertility–the inability to become pregnant again following another pregnancy. Secondary infertility results from pregnancy-related infections of the reproductive tract, which often result from unsafe

Image 1: Figure 1: Preterm Birth and Low Birth Incidence among ART infants from the CDC’s 2019 ART National Summary Report Image Source: CDC ("Assisted, 2022).

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abortions or substandard maternity care. More than 85% of infertile women in sub-Saharan African nations have been diagnosed due to an infection, while this rate is only 33% for women on a global scale (Mascarenhas et al., 2012). Over 10% of reproductive-aged women in sub-Saharan Africa are estimated to be secondarily infertile. Secondary infertility is also represented in high concentrations in South Asia, East Asia, Central Asia, the Pacific, and Central and Eastern Europe. These patterns of secondary infertility exasperate the insufficiency of ART services in sub-Saharan Africa. However, even when ART services are available, this does not guarantee treatment, as only roughly half of infertile couples actively seek infertility care (Boivin et al., 2007). In some situations, such as those in Iraq and Syria in 2003 and 2011, major political conflicts like war can prevent access to care (Inhorn, 2012). Even once removed from a war zone, refugees may continue to face difficulties in accessing ART services depending on the restrictions of the countries in which they seek asylum. In France, for instance, undocumented immigrants or immigrants without a regular French residence will not receive coverage for ART services, which may ultimately serve as a barrier to care (Schüller, 2021). Undocumented French immigrants are not alone in facing financial hurdles on the path to ART care. Generally, medical coverage of ART services is poor. This is especially true of IVF, which is expensive and mostly restricted to the private medical sector because few governments agree to subsidize the treatment in national health insurance policies. Currently, the average cost of just one IVF cycle in the United States is between $12,000-17,000, posing a significant financial burden to individuals pursuing ART (State Laws…, 2021); and when the chance of a successful singleton birth varies from 25-50% per cycle, the costs associated with multiple cycles can be prohibitively expensive. This expense may prevent some infertile individuals from undergoing even a single IVF treatment, while others may feel that a “catastrophic expenditure,” or a one-time charge amounting to more than 40% of annual non-food expenses, is worth the risk (Dyer & Patel, 2012). Such risk-taking especially applies to poor infertile couples and women, particularly those living in countries lacking ART resources. Additionally, although it is often a financial stretch for such patients to afford a single ART cycle, it is common for three or more cycles to pass before live birth is

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achieved. This financial burden is not alleviated by external philanthropic organizations because aside from the World Health Organization, few such institutions consider infertility care in developing countries to be a priority in healthcare (Ombelet, 2011). In response to financial difficulties, clinicians have attempted to provide low-cost IVF (LCIVF) with simplified culture methods that do not require complex incubators and rely on cheap, common chemicals. These services are provided to the countries that most need ART services, but in cases where LCIVF is unavailable, infertile individuals might be driven to seek cross-border reproductive care. Further research is needed to comprehensively assess the long-term safety and efficacy of LCIVF (Inhorn & Patrizio, 2015). In addition to financial barriers, couples and individuals experiencing infertility may face obstacles to ART care based on their relationship or sexual situation. For example, Law 40 in Italy (which has since been amended but not abolished) only allowed “stable” heterosexual couples access to ARTs, though legal marriage was not a requirement, and explicitly excluded single or homosexual individuals (Rao, 2013). This pattern of preference for heteronormativity was also reflected in the outcomes of Australian antidiscrimination cases from the 1990s. In these cases, a female-identifying plaintiff was more likely to receive a favorable ruling regarding access to ART if her circumstances conformed to the heterosexual nuclear family structure (Statham, 2000). Similarly, in Czechia, legislation hinders access to ART treatment depending on the relationship or sexual condition of infertile couples and individuals. Czech lesbian couples are unable to access ART without conforming to heteronormative expectations, as the father of the child must be declared unknown or the sperm donor at the time of birth, carrying significant implications for parental rights. Czech gay men and couples do not have the option of conforming to the conventions of this system and must seek ART treatment with a surrogate mother in another country. These restrictions reflect the exclusive initial purpose of Czech ART to treat infertile heterosexual couples. Transgender individuals also face challenges in accessing ART care, as Czech law requires surgical elimination of one’s reproductive function prior to an official gender change. As a result, trans individuals who seek ART treatment pre-surgery or who seek to cryopreserve their eggs or sperm are only recognized based on their functional reproductive parts. For instance, a male-tofemale woman with a lesbian partner would be

" In response to financial difficulties, clinicians have attempted to provide low-cost IVF (LCIVF) with simplified culture methods that do not require complex incubators and rely on cheap, common chemicals."

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treated as a man, and her relationship would be considered heterosexual for the purposes of ART (Hašková & Sloboda, 2018). While these examples come from Czechia, the problem of heteronormativity is pervasive and affects ARTseeking couples worldwide, as do expectations of conformity to a gender binary.

"... Truly equiable ART care requies an expansion of affordable treatment options and the mitigation of discriminatory policies surrounding ART."

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Finally, ART-seeking individuals with pre-existing medical conditions have been historically likely to encounter barriers to care. The medical condition most frequently cited as justification for denying ART access is HIV infection, even though since 2002, the American Society for Reproductive Medicine has held that requested reproductive assistance is required unless practitioners can demonstrate an inability to safely treat HIVpositive patients (Coleman, 2002). Even in cases where ART treatment is officially offered to patients with HIV, these offers may be hollow. For instance, one 2010 study on ART centers in the U.K. and in Denmark found that while 30% of included fertility clinics intended to treat HIVpositive patients, a far lower percentage was set up to provide such treatment (Nicopoullos et al., 2010). This policy-care discrepancy was further demonstrated when a 2001 study found that 72% of included ART clinics had policies in place for treating HIV-positive individuals, but only 39% had actually treated such patients in the last year (Apoola et al., 2001). Discrimination based on HIV status remains an issue for patients seeking ART care, as about 33% of HIV-positive patients in Western/Southern Europe and 40% of patients in Central/Eastern Europe reported HIV-related discrimination (Nöstlinger et al., 2014). Non-HIV disabilities are also cited as causes of ART denial, and this form of discrimination has a significant historical basis in the United States. In the early 1900s, many states had involuntary sterilization laws targeting several categories of people, including those with disabilities, to prevent these groups from having children. This precedent of forced sterilization is still federally legal today because of the 1927 Supreme Court case Buck v. Bell, which upheld the involuntary sterilization of a white woman with alleged “feeble-mindedness.” These sterilization laws were passed in the context of the eugenics movement, which sought to shape the genetic makeup of humanity by limiting reproduction to “desirable” groups, and this mindset also motivated the denial of fertility treatment for groups with mental or physical disabilities. In addition to HIV, severe lupus, uncontrolled diabetes, and uncontrolled hypertension have been cited as justifications for the denial of ART treatment. Furthermore, a 1987 study found that

79% of practitioners considered serious risk of transmission of a genetic disorder sufficient cause to deny patients ART treatment (Coleman, 2002). Overall, historically, ART resources often fail to meet demand, and even in cases when they do, financial or discriminatory barriers can prevent infertile individuals and their partners from accessing care. Conclusion ART is a landmark development in fertility science and has vastly broadened the opportunities to create a family for millions of individuals. Since 1987, over one million children have been born via ART in the United States alone (Centers…, 2017). Despite the scientific marvel of aiding millions of individuals – including single parents, LGBT individuals/couples, and biologically older women – to have offspring, success rates in fertility treatment have stagnated since the 90s. Compounding matters, when the current average cost of one IVF cycle is between $12,000 and $17,000, individuals seeking ART often struggle to afford such financially intensive treatments, many of which are not covered by insurance (State Laws…, 2021). In addition to low ART success rates and financial barriers to treatment, many discriminatory medical practices remain entrenched in the field of fertility treatment. Individuals with preexisting medical conditions or those who defy society’s sexuality and gender conventions may be denied care or struggle to find facilities equipped to treat them. Additionally, current ART clinic numbers do not match infertility-driven demand, especially in sub-Saharan African countries. Truly equitable ART care requires an expansion of affordable treatment options and the mitigation of discriminatory policies surrounding ART. Finally, the emotional burden of struggling with infertility coupled with the financial, temporal, and physical challenges associated with ART create considerable pregnancy-related stress, which has been found to negatively impact maternal and fetal health (Conde et al, 2010). Thus, considerable scientific and policy work should be done to improve ART success rates, increase accessibility to expensive and physically demanding ART treatments, and alleviate the stress associated with ART. In writing this review, it is the authors’ hopes to encourage intersectional work in fertility research and public policy to make ART more equitable for all.

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Martin, A. S., Monsour, M., Kissin, D. M., Jamieson, D. J., Callaghan, W. M., & Boulet, S. L. (2016). Trends in Severe Maternal Morbidity After Assisted Reproductive Technology in the United States, 2008–2012. Obstetrics & Gynecology, 127(1), 59–66. https://doi. org/10.1097/AOG.0000000000001197 Mascarenhas, M. N., Flaxman, S. R., Boerma, T., Vanderpoel, S., & Stevens, G. A. (2012). National, Regional, and Global Trends in Infertility Prevalence Since 1990: A Systematic Analysis of 277 Health Surveys. PLoS Medicine, 9(12), 1–12. https://doi.org/10.1371/journal.pmed.1001356 Morgan, J. (2017, June 13). Part One: Assisted reproductive technologies and maternal risk | Your Pregnancy Matters. UT Southwestern Medical Center. http://utswmed.org/medblog/ part-one-art-risk/ Mother’s anxiety and depression and associated risk factors during early pregnancy: Effects on fetal growth and activity at 20-22 weeks of gestation—PubMed. (n.d.). Retrieved April 24, 2022, from https://pubmed.ncbi.nlm.nih. gov/20236029/ National Summary Report. (n.d.). Society for Assisted Reproductive Technology. Retrieved June 15, 2022, from https://www.sartcorsonline. com/rptCSR_PublicMultYear.aspx Nicopoullos, J. D. M., Almeida, P., Vourliotis, M., Goulding, R., & Gilling-Smith, C. (2010). A decade of sperm washing: Clinical correlates of successful insemination outcome. Human Reproduction, 25(8), 1869–1876. https://doi. org/10.1093/humrep/deq134 Nöstlinger, C., Rojas Castro, D., Platteau, T., Dias, S., & Le Gall, J. (2014). HIV-Related Discrimination in European Health Care Settings. AIDS Patient Care and STDs, 28(3),

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Preeclampsia—Symptoms and causes. (2022). Mayo Clinic. https://www.mayoclinic.org/ diseases-conditions/preeclampsia/symptomscauses/syc-20355745 Rao, R. (2013). Hierarchies of Discrimination in Baby Making? A Response to Professor Carroll. Indiana Law Journal, 88(4), 1217–1221. Rebar, R. W. (2013). What are the risks of the assisted reproductive technologies (ART) and how can they be minimized? Reproductive Medicine and Biology, 12(4), 151–158. https:// doi.org/10.1007/s12522-013-0156-y Reported IVF Success Rates Can Be Misleading: Study. (2013, July 4). Reuters. https://www. reuters.com/article/us-reported-ivf-successrates-can-be-mis-idUKBRE9630L320130704 Reported IVF success rates can be misleading: Study. (2013, July 4). Reuters. https://www. reuters.com/article/us-reported-ivf-successrates-can-be-mis-idUKBRE9630L320130704 Schuller, C. (2021). L’AMP pour tous ? Autour d’une discrimination méconnue : l’exclusion des personnes « sans-papiers » de l’accès à la médecine de la reproduction. Sciences sociales et sante, 39(2), 79–101. Sex, Science and Society After 40 Years of IVF. (2017, November 10). The University of Newcastle, Australia. https://www.newcastle.edu. au/newsroom/featured/sex,-science-and-societyafter-40-years-of-ivf Sex, Science and Society after 40 years of IVF. (2017, November 10). The University of Newcastle, Australia. https://www.newcastle.edu. au/newsroom/featured/sex,-science-and-societyafter-40-years-of-ivf Sharma, R. S., Saxena, R., & Singh, R. (2018). Infertility & Assisted Reproduction: A Historical

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& Modern Scientific Perspective. The Indian Journal of Medical Research, 148(Suppl), S10– S14. https://doi.org/10.4103/ijmr.IJMR_636_18 Sharma, R. S., Saxena, R., & Singh, R. (2018). Infertility & assisted reproduction: A historical & modern scientific perspective. The Indian Journal of Medical Research, 148(Suppl 1), S10–S14. https://doi.org/10.4103/ijmr.IJMR_636_18 State Laws Related to Insurance Coverage for Infertility Treatment. (2021). National Conference of State Legislatures. https://www. ncsl.org/research/health/insurance-coverage-forinfertility-laws.aspx Statham, B. (2000). (Re)producing Lesbian Infertility—Discrimination in Access to Assisted Reproductive Technology. Griffith Law Review, 9(1), 112–155. Steptoe, P. C., & Edwards, R. G. (1978). Birth After the Reimplantation of a Human Embryo. The Lancet, 312(8085), 366. https://doi.org/10.1016/ S0140-6736(78)92957-4 Steptoe, P. C., & Edwards, R. G. (1978). Birth After the Reimplantation of a Human Embryo. The Lancet, 312(8085), 366. https://doi.org/10.1016/ S0140-6736(78)92957-4

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Physician Burnout During the COVID-19 Pandemic STAFF WRITERS: VAISHNAVI KATRAGADDA ‘24, JULIETTE COURTINE ‘24, CECELIA PLASS ‘25, AYUSHYA AJMANI ‘24, SOYEON (SOPHIE) CHO ‘24, JENNIFER DO-DAI ‘25, VALENTINA FERNANDEZ ’24, ASH CHINTA ‘24, KEVIN STAUNTON ‘24, ZARA KIGER ‘25 TEAM LED BY: DANIEL CHO ‘22, DINA RABADI ’22, ANAHITA KODALI ‘23

Cover Image Source: Pixabay

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Introduction Physician burnout originates from general burnout, which is defined as a psychological syndrome caused by chronic occupational stress combined with a lack of resources for individuals (Freudenberger, 1974). Physician burnout can also be defined as emotional exhaustion, depersonalization, and lack of purpose for physicians in the clinical field (Maslach et al., 1996). Physicians find themselves unable to interact and empathize with patients and their emotions because of emotional exhaustion. For depersonalization, clinicians treat patients not as individual human beings, but as a series of tasks to be treated. Lack of purpose, or sense of accomplishment, as a physician prevents them from fully appreciating clinical or other work-related outcomes, as they instead focus on their own ineffectiveness as a hindrance in the workplace. Physician burnout, similar to other types of burnout, may resemble phenomena such as depression in terms of emotional exhaustion. However, the decrease in sense of personal accomplishment and depersonalization do not have strong correlations to depression or other psychological issues (Leiter and Durup, 1994; Wurm et al., 2016).

Physician burnout can be analogized to a continued depletion of “energy accounts” (Drummond, 2015). In this analogy, physicians withdraw energy from different “energy accounts” in and out of their workplace. The physical energy account allows physicians to physically carry out tasks for patients, through adequate nutrition, exercise, and rest. The emotional energy account is used to maintain healthy interpersonal relationships with patients as well as family and friends. The spiritual energy account motivates physicians with their purpose for continuing their clinical work. However, as physicians constantly withdraw energy without refilling their accounts through rest, their energy accounts become depleted. This accumulation of energy depletion causes physician burnout and the resulting consequences, ranging from a lack of personal accomplishment in physicians’ work, lack of efficacy in clinical practice to instability in healthcare systems (Drummond, 2015; West et al., 2018). Thus, physician burnout is negatively impacting individual physicians, patients, and healthcare organizations. This review will explain the description and neuroscience of physician burnout, as well as the syndrome in the context of COVID-19. The review will then evaluate steps to be taken to address this syndrome and positively DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

impact the medical field and society. The current Covid-19 pandemic has posed a challenge to physicians everywhere, especially given the surge of cases of the Omicron variant. As of now, Omicron accounts for around 95% of the United States cases (Sohn, 2022). Despite this high surge, a study of around 70,000 Covid-19 cases conducted at Kaiser Permanente in Southern California found that infections with the Omicron variant were associated with substantially reduced risk of death and shorter durations of hospital stay (Lewnard et al, 2022). The chance of hospitalization is about 50% lower for patients infected with omicron compared to the delta variant. However, Omicron is between two and four times more contagious than Delta, creating a large spike in cases that is continuing to overwhelm healthcare systems (Sohn, 2022). While Omicron is milder in severity, the patient load continues to overwhelm hospitals leading to long wait times and severe consequences for both physicians and patients. As the COVID-19 pandemic has uniquely overloaded the US healthcare system, the pandemic provides an important framework to analyze how physician burnout may manifest. Describing Physician Burnout With an increased number of physicians reporting “emotionally exhaustive feelings from the work environment” over the past decade, the importance of understanding burnout at its root has become increasingly imperative (Patel et al., 2019). For many physicians, burnout tends to affect them in different ways due to the sheer factors that contribute to it. While there is no standardized way to label the different types of burnout, there are different metrics by which physician burnout can be better understood. As proposed under the Maslach Burnout Inventory in the late 80’s, these metrics include emotional exhaustion, depersonalization, and low personal accomplishment (Maslach et al., 1997). The metrics are used to assess various aspects of the burnout process and syndrome seen in a wide range of human services professionals. Over the past few decades, the MBI has become the most used tool to assess physician burnout; US health policy discussions surrounding the burnout crisis in medicine have largely been centered around the MBI. The inventory is split into the three component scales, with each one measuring a unique metric of burnout listed above. The inventory uses a 7 level frequency, with 0 being “never” and 6 being “daily” (Jackson, 2018). When looking at the extremes of the MBI scale, it is clear how a physician can experience different WINTER/SPRING 2022

outcomes within burnout. A physician reporting the highest scores on the 9-item emotional exhaustion survey would likely report feeling drained from work, used up at the end of the workday, frustrated from their job, and that they are being worked too hard at the workplace more than once weekly. Meanwhile, a high score on the 5-item depersonalization inventory would mean that a physician likely feels that work is hardening their emotions, treats patients as objects, does not care about work, and thinks patients are blaming them too easily. Finally, under the 8-item personal accomplishment questionnaire, a low score would mean that a physician is not able to create a relaxed atmosphere with patients, fails to address problems effectively, reports feeling lethargic, and is not able to accomplish goals in the workplace (Brady et al., 2020).

"...42% of 15,000 US physicians already exhibited symptoms of burnout (Yates, 2020)."

While these extremes are not the case for most physicians, they also do not paint the reality for most physician outcomes. Since rarely any physician experiences burnout in a onedimensional sense, the syndrome gets further complicated by the intersection of emotional exhaustion, depersonalization, and low personal accomplishment. Trends in Physician Burnout Physician burnout, though becoming especially prominent in recent years, was a serious systemic problem even before the outbreak of Covid-19. In the words of Gary Price M.D., president of the Physicians Foundation, “a bad situation has gotten worse” (Gliadkovskaya, 2021). Three years ago, 42% of 15,000 US physicians already exhibited symptoms of burnout (Yates, 2020). There are multiple reasons for this; the advent of clerical processes such as electronic health record-keeping has forced physicians to spend more time on cumbersome paperwork in recent years (Gliadkovskaya, 2021; Alpert, 2019), and the workload of occupations in healthcare has always been high. One physician’s account describes how she “dread[ed] going to work” and even got into a car accident on account of driving after a 24 hour-shift (Ranjbar, 2018), while another physician describes how his work demands felt like a “cruel and unusual punishment” (Alpert, 2019). The situation is likely worse for physicians who are part of minority groups due to the additional barriers that they already face. The stress levels that physicians face can even become lethally overwhelming. Before the beginning of the pandemic, there was a high suicide rate among physicians, with “roughly one doctor dying a day” (Gliadkovskaya, 2021). 145

Image 1: The structure of cortisol, a critical hormone in stress. Image Source: Wikimedia Commons

"...chronic stress... impact[s] brain architecture and function"

Despite this, very few sought mental healthcare due to the stigma still associated with it, or out of fear of being seen as incompetent (Gliadkovskaya, 2021). Given the generally demanding nature of their profession with the added and long-term complications of the pandemic, it is clear that physician burnout is something that must be addressed quickly. The Neuroscience of Stress One of the main pathways by which chronic stress contributes to bodily dysfunctions is through its impact on brain architecture and function. Specifically, stress disrupts the normal function of the adrenal glands, causing a high level of glucocorticoid release, which has been associated with a reduction in neurogenesis (de Celis et al., 2016). The adrenal gland and the brain have a very tight and intricate relationship; their cooperation is crucial for a properly functioning stress response (de Celis et al., 2016). The two distinct tissues that make up the adrenal gland (the cortex and medulla) each release hormones that help maintain homeostasis. The adrenal cortex predominantly produces steroid hormones, including glucocorticoids, whereas the adrenal medulla mostly secretes catecholamines, such as epinephrine and norepinephrine (de Celis et al., 2016). It is worth noting that despite their diverging functions, many medullacortex communication pathways are critical for regulation. The adrenocortical glucocorticoids have been extensively studied and are strong mediators of brain function. Stress hormones as such have been linked with growth-inhibiting effects, which largely explains the connection between reduced neurogenesis and depression. In addition, animal studies suggest that stress alters

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synaptic plasticity, particularly affecting the firing properties of hippocampal neurons, which play a role in memory and learning (Kim et al., 2015). In both human and animal studies, stress has been found to change the morphology of neurons and decrease the volume of the hippocampus (Kim et al., 2015). Specifically, stress overly activates glucocorticoids (part of stress response), and these have been found to suppress cell proliferation and promote cell death (McConkey et al., 1989). Clearly, the impact of stress on the brain is multifaceted. The functional connection between stress, brain function, and adrenal function is undeniable and, to tie it to a broader context, certainly impact to physician burnout. Today, physicians experience unprecedented amounts of stress and distress, but the the line between burnout and major depression (which likely function through overlapping mechanisms) remains unclear (Yates, 2020). The biological response to stress leads to a signaling cascade pathway that releases stress hormones. When the amygdala, the part of the brain responsible for emotional processing, receives a signal from one of the body’s sensory organs such as the ears and eyes that it interprets as stress or danger, a distress signal is sent to the hypothalamus. Located in the brain, the hypothalamus gland maintains homeostasis within the body by connecting the nervous system with the endocrine system. The first part of the response occurs through the sympathetic nervous system. Upon activation, a signal is sent to the adrenal glands through the autonomic nerves from the hypothalamus. This signal causes the adrenal medulla to release epinephrine and norepinephrine into the bloodstream, leading to various physiological responses including

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heightened heart rate and blood pressure, enhanced senses due to excess oxygen sent to the brain, and increased energy levels because of released glucose and other temporarily stored fats. However, repeated activation of this sympathetic pathway leads to headaches, tear on arteries, and blood clotting. These effects can increase risk for diseases such as coronary heart disease and hypertension. The second part of this pathway involves activation of the HPA axis (a feedback system consisting of hypothalamus, pituitary gland, and adrenal glands). After the release of epinephrine and subsequent decrease in epinephrine levels, the hypothalamus triggers a cascading pathway if danger is still sensed starting with the release of corticotropin-releasing hormone (CRH) to the pituitary gland. CRH stimulates the pituitary gland to release adrenocorticotropic hormone (ACTH) to the adrenal glands which in turn stimulates the release of cortisol into the bloodstream. Cortisol is responsible for freeing up glucose stored in the liver so that the body is energized to deal with the stressor. When levels in the bloodstream are high, cortisol can inhibit the release of the production of CRH or ACTH, which results in decreased cortisol levels thus serving as a negative feedback loop. Cortisol is a glucocorticoid, which has been linked to reduced immune system function by suppressing T-cell proliferation, weakening the cytotoxicity of natural killer cells, and limiting growth and maturation of lymphocytes. The relationship between cortisol and burnout is not completely understood. Some studies have found that burnout is associated with more cortisol, while others have found that burnout is associated with less cortisol (Morera et al., 2020). Thus, it is likely that the impacts of burnout on cortisol will be variable and appear on a spectrum – both high and low cortisol present unique complications to individual’s immune systems, meaning that the biology of burnout will likely result differently across physician populations. Compassion Fatigue Compassion fatigue (CF) is a unique form of burnout that is a combination of both institutional and individual factors affecting a physician’s work-life balance. CF has been characterized as an occupational hazard, in which physician exhaustion, depersonalization, and feelings of reduced personal accomplishment impact a physician’s ability to provide care (Babineau et al., 2019). During the COVID-19 pandemic, 40% of surveyed physicians indicate CF, reporting they

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felt that their work was not properly rewarded or appreciated by the institutions they served (Kase et al., 2021). Many of these feelings are even characteristic of secondary post-traumatic stress syndrome (Babineau et al., 2019). Because CF is not sustainable, it leads to increased physician turnover and greatly decreases the quality of care patients receive as hospital function itself is impacted. Among the physicians that choose to stay, there are increased cases of medical error. Studies on patients with diabetes, hypertension, and other chronic illnesses have even shown that patients are much more likely to adhere to care recommendations when their providers have a higher job satisfaction (Babineau et al., 2019). The biggest drivers of CF are extreme job demands, a lack of resources to provide proper care, a hospital’s culture and values, a lack of control or flexibility over schedule, and minimal social support or community at work. Early on in the pandemic, many physicians saw that they were unable to properly treat patients, resulting in constant emotional tolls that put intesne pressure on providers (Babineau et al., 2019). These personal factors are only increased by stressors involved with the pandemic, such as socioeconomic inequalities, stress of unemployment, limited support services, and worries about family exposure through the provider. A recent survey showed that out of 499 physicians surveyed, nearly all agreed that they felt some source of stress impacting their job satisfaction, whether that was family health, economic uncertainty, or having an uncertain future (Kase et al., 2021). With the pandemic also requiring increased hours and the fact that physicians no longer set their own hours due to working in a corporate setting leads to many providers working 5060 hours per week. This increased work is often not compensated, and instead, enforces a feeling of increased productivity and emotional capacity upon physicians that leads to increased malpractice suits. Interestingly, changes such as the shift patients using the internet to selfdiagnose has contributed to an expectation that physicians will perform at near perfect levels, adding pressure on physicians (Babineau et al., 2019). CF affects physicians as well, with the associated symptoms leading to increased anger, deficits in a physician’s attention span, and increased illnesses. However, studies have indicated institutional and individual effective ways in which this can be reduced. Institutional changes include providing more autonomy for providers to choose their schedules, implementing a culture around self-

"CF has been characterized as an occupational hazard, in which physician exhaustion, depersonalization, and feelings of reduced personal accomplishment impact a physicians' ability to provide care (Babinaeu et al, 2019)."

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"One of the best ways to help physicians maximize the quality of care they give is by directly involving them in workplace culture shifts."

care, promoting effective work-life balance techniques, increasing rewards, and providing peer support networks (Babineau et al., 2019). This is especially important, as many surveys done on physicians indicated that those that had higher levels of CF were those that also agreed that self-care was not a priority (Kase et al., 2021). Individual changes shown to have long term benefits include mindfulness, which increases compassion for others and self by activating neurological pathways associated with empathy. Cognitive behavioral therapy has been effective as well, showing decreased symptomatology of CF. Communication classes addressing patientphysician interaction have shown that the associated decrease in BO and CF had longlasting effects up to three months, with physicians realizing that their practice is more humanistic (Babineau et al., 2019). Thus, implementing these procedures can drastically decrease rates of CF among physicians as they practice self-care and increased empathy on a more sustainable level. Uniqueness of COVID-19 The COVID-19 pandemic is partly the product of modern society’s pace of life. The pandemic has spread faster and has been more deadly than past pandemics due to globalization, urbanization, and global warming. COVID-19 is not associated with the highest case fatality rate compared with other emerging viral diseases such as SARS and Ebola, but the combination of a high reproduction number, superspreading events and a globally immunologically naïve population has led to the highest global number of deaths in the past 20 decade compared to any other pandemic (Smith, 2021). The recent spike in human-to-human interactions and closer living quarters makes respiratory viruses more transmissible. For instance, modern air travel becomes a vector of travel for the virus, similar to how an animal would zoonotically transmit the virus. A virus that starts off as an epidemic can quickly transform into a pandemic if proper protocol is not immediately implemented. COVID-19 is defined as a pandemic because of its rapid global spread (Pitlik, 2020). However, the outbreak was considered an epidemic when it first started in Wuhan, China since it was within a specific community. Other recent pandemics include SARS, Ebola, Measles, Zika, HIV, and H1N1 Influenza. Pandemics are emotionally overwhelming for

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all members of society, but especially for health care personnel (HCP). Not only are physicians and nurses risking their own lives working on the front lines, but they also risk transmitting highly contagious diseases to their co-workers, friends, and family members. This places a great deal of stress on those who work in healthcare settings. However, this is not the only thing HCP worries about. In fact, a unique set of stressors can be associated with COVID-19. Death anxiety, guilt of prioritizing certain patients over others, the uncertainties surrounding novel outbreak, public resistance to preventative policy (i.e vaccines and mask mandates), overall obsessive thoughts, and “superhuman expectations” all plague the mind of a physician amidst a time of crisis. Similar psychological reactions were experienced among HCP during the 2003 SARS pandemic (Lai et al., 2019). Similarly, the 2016 SARS epidemic in Hong Kong presented 68% facing high stress levels in a participant setting of 652 health care workers in one hospital (Chigwedere et al., 2021). Continuing the pandemic trajectory, a hospital in The United States of 657 HCP presented 57% PTSD symptoms, 48% depressive symptoms, and 33% anxiety symptoms during the 2020 COVID-19 pandemic (Chigwedere et al., 2021). The COVID-19 pandemic differs from past pandemics because of its magnitude and severity. However, physicians should be aware that in regard to any public health crisis, it is “common” to feel the emotional and physical stressors. In a complex study done by the BioMed Central Journal over the last 17 years, “results [of psychological symptoms] were consistent with over 90,000 physicians surveyed during and after seven different infectious disease outbreaks (SARS, H7N9, H5N1, MERS, Ebola, COVID-19) in 57 countries” (Fiest 2021). Physician burnout has been an issue throughout past pandemics but has been brought into a sharper focus by the COVID-19 pandemic. The COVID-19 pandemic has led to an extensive negative impact on healthcare systems across the globe, including massive shortages recorded in healthcare personnel (HCP) and hospital and physician equipment. As March 2020 approached, the Centers for Disease Control's (CDC) National Healthcare Safety Network (NHSN) recognized the need to collect and report hospital statistics relevant for the pandemic to inform surveillance on the situation as it progressed (Wu et al., 2021). Their initial categories included: patient counts, bed occupancies, and mechanical ventilators in use, all to be reported on a voluntary basis. Within a month, two additional categories were added: HCP and healthcare supplies (i.e., personal

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Image 2: COVID-19 has presented several unique challenges for physicians, contributing to increased levels of burnout. Image Source: Pixabay

protective equipment (PPE)). The NHSN collected data from 4,535 hospitals regarding COVID-19 patients, finding that in April 2020 there was the highest percentage of inpatient beds occupied by COVID-19 patients and nearly a quarter of their reporting hospitals had more than 76% of their ventilators in-use for COVID-19 patients (Wu et al., 2021). That same month (with data being collected through July), NHSN collected data from 2,349 hospitals regarding staffing levels, of which 29% reported HCP shortages. The categories the NHSN reported (listed in order of the number of hospitals impacted) include: nurses, respiratory therapists, environmental services staff, physicians, and temporary workers (Wu et al., 2021). Additionally, 3,145 hospitals reported critically low supply levels: 11% reported having no on-hand supplies for at least 1 day. The categories for this report (listed in order of the number of hospitals impacted) include: eyes protection (i.e., face shields or goggles), single-use gowns, ventilator supplies, N95 respirators, surgical masks, and gloves (Wu et al., 2021). These data are not wholly surprising, due to the US being the largest importer of face masks, eye protection, and medical gloves in the world (Cohen et al., 2020). These personnel and equipment are integral for a well-functioning and safe hospital environment, two features made even more critical during a global pandemic. The importance of identifying the causes and solutions to these shortages is therefore more pressing than ever before. Interestingly, according to NHSN data, HCP and supply shortages occurred in hospitals seemingly with little correlation to the burden of COVID-19 patients the hospital was experiencing. Researchers speculate possible explanations to include baseline reserve shortages, HCP or HCP

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family members need due to exposures, or supply chain issues (Wu et al., 2021). Further research into the shortage issue reveals deep-rooted structural issues which were aggravated by the spike in demands resulting from the pandemic. These include faulty hospital operating system costing models and the federal government’s failure to maintain and distribute established reserves of PPE coupled with interrupted global supply chains of PPE (Cohen et al., 2021). Possible solutions offered by researchers include modifying hospital costing models by removing the cost-minimization associated with PPE purchases, bolstering government maintenance and ability to dispense reserves, and supporting long term ambitions to reduce US reliance on imported hospital supplies (Cohen et al., 2020). Although these solutions provide a goal to work towards, the reality remains grim as COVID-19 cases surge across the nation and shortages remain a prominent issue. The US Drug & Food Administration (FDA) reports that there are ongoing medical device shortages, including dialysis-related products, PPE, Testing Supplies and Equipment, and ventilation-related products (FDA, 2022). Lack of proper equipment, as well as shortages in HCP, contribute to a strained and perilous workplace for many physicians across the nation, thereby contributing to physician burnout.

"66.2 percent of adults (aged 18-64) were most likely to receive health care services under a private program (Cohen et al, n.d)."

Alleviating Physician Burnout In terms of addressing and preventing burnout across healthcare workers, many pathways to limit stress in the workplace may be effective. Mindfulness, small group discussions, and other individual-focused stress management techniques tend to significantly reduce absolute burnout, emotional exhaustion, and depersonalization. Additionally, duty hour

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limitations, or setting minimum rest periods and maximum work periods, and other structural interventions also seem to reduce stress and burnout (West et al., 2016). Similarly, attempting to improve workplace culture has also been shown to limit stress effectively. Encouraging communication while promoting teamwork and giving healthcare workers a sense of agency over their work-life balance can do wonders in preventing burnout (Panagioti et al. 2017). Other methods in reducing healthcare workers’ stress can come in the way of targeting the bureaucracy of medicine, as reducing the amount of paperwork required of clinics and hospitals and/or streamlining a process for nonphysicians to complete documentation could alleviate some of the burden. Forgoing misbegotten regulations by state licensing boards and unnecessary requirements of insurance companies are also easy targets to lower the strain on hospitals’ shoulders (Shanafelt et al. 2017). Multiple groups have also committed themselves to the fight against physician burnout. The American Medical Association (AMA) has created the Joy in MedicineTM Recognition Program to recognize and honor healthcare organizations for their dedication to reducing stress and burnout in the workplace to encourage others to do the same (Berg, 2019). The Physicians Foundation also launched their Vital Signs campaign in 2019, which is designed to provide resources to manage mental health crises and burnout to prevent physician suicide (The Physicians Foundation 2019). References Analysis_of_covid_19_data_and_preparing_ for_the_future__part_2_.pdf. (n.d.). Retrieved May 18, 2022, from https://fshrmps.org/images/ down lo ads/2021_C onference_/ana lysis_ of_covid_19_data_and_preparing_for_the_ future__part_2_.pdf Babineau, T., Thomas, A., & Wu, V. (2019). Physician Burnout and Compassion Fatigue: Individual and Institutional Response to an Emerging Crisis. Current Treatment Options in Pediatrics, 5(1), 1–10. https://doi.org/10.1007/ s40746-019-00146-7 Berg, S. (2019, September 21). AMA honors 22 organizations’ commitment to cutting doctor burnout. American Medical Association. https:// www.ama-assn.org/practice-management/ sustainability/ama-honors-22-organizationscommitment-cutting-doctor-burnout Biological Stress Response—An overview | ScienceDirect Topics. (n.d.). Retrieved May 18, 150

2022, from https://www-sciencedirect-com. dartmouth.idm.oclc.org/topics/psychology/ biological-stress-response Brady, K. J. S., Ni, P., Sheldrick, R. C., Trockel, M. T., Shanafelt, T. D., Rowe, S. G., Schneider, J. I., & Kazis, L. E. (2020). Describing the emotional exhaustion, depersonalization, and low personal accomplishment symptoms associated with Maslach Burnout Inventory subscale scores in US physicians: An item response theory analysis. Journal of Patient-Reported Outcomes, 4, 42. https://doi.org/10.1186/s41687-020-00204-x Chigwedere, O. C., Sadath, A., Kabir, Z., & Arensman, E. (2021). The Impact of Epidemics and Pandemics on the Mental Health of Healthcare Workers: A Systematic Review. International Journal of Environmental Research and Public Health, 18(13), 6695. https://doi. org/10.3390/ijerph18136695 Clinical outcomes among patients infected with Omicron (B.1.1.529) SARS-CoV-2 variant in southern California | medRxiv. (n.d.). Retrieved May 18, 2022, from https://www.medrxiv.org/co ntent/10.1101/2022.01.11.22269045v1 Cohen, J., & Rodgers, Y. van der M. (2020a). Contributing factors to personal protective equipment shortages during the COVID-19 pandemic. Preventive Medicine, 141, 106263. https://doi.org/10.1016/j.ypmed.2020.106263 Cohen, J., & Rodgers, Y. van der M. (2020b). Contributing factors to personal protective equipment shortages during the COVID-19 pandemic. Preventive Medicine, 141, 106263. https://doi.org/10.1016/j.ypmed.2020.106263 COVID-19 in comparison with other emerging viral diseases: Risk of geographic spread via travel—PubMed. (n.d.). Retrieved May 18, 2022, from https://pubmed.ncbi.nlm.nih. gov/33517914/ de Celis, M. F. R., Bornstein, S. R., AndroutsellisTheotokis, A., Andoniadou, C. L., Licinio, J., Wong, M.-L., & Ehrhart-Bornstein, M. (2016). Erratum: The effects of stress on brain and adrenal stem cells. Molecular Psychiatry, 21(5), 722–722. https://doi.org/10.1038/mp.2016.26 Drummond, D. (2015). Physician Burnout: Its Origin, Symptoms, and Five Main Causes. Family Practice Management, 22(5), 42–47. Fiest, K. M., Parsons Leigh, J., Krewulak, K. D., Plotnikoff, K. M., Kemp, L. G., Ng-Kamstra, DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

J., & Stelfox, H. T. (2021). Experiences and management of physician psychological symptoms during infectious disease outbreaks: A rapid review. BMC Psychiatry, 21, 91. https://doi. org/10.1186/s12888-021-03090-9 Freudenberger, H. J. (1974). Staff Burn-Out. Journal of Social Issues, 30(1), 159–165. https:// doi.org/10.1111/j.1540-4560.1974.tb00706.x Gliadkovskaya, A. (2021, August 10). New survey finds COVID-19 is taking a significant toll on physicians. Fierce Healthcare. https://www. fiercehealthcare.com/practices/new-surveyfinds-significant-toll-covid-19-physicians Health, C. for D. and R. (2022). Medical Device Shortages During the COVID-19 Public Health Emergency. FDA. https://www.fda.gov/medicaldevices/coronavirus-covid-19-and-medicaldevices/medical-device-shortages-during-covid19-public-health-emergency Kase, S. M., Gribben, J. L., Guttmann, K. F., Waldman, E. D., & Weintraub, A. S. (2022). Compassion fatigue, burnout, and compassion satisfaction in pediatric subspecialists during the SARS-CoV-2 pandemic. Pediatric Research, 91(1), 143–148. https://doi.org/10.1038/s41390021-01635-y Kim, E. J., Pellman, B., & Kim, J. J. (2015). Stress effects on the hippocampus: A critical review. Learning & Memory, 22(9), 411–416. https://doi. org/10.1101/lm.037291.114 Lai, J., Ma, S., Wang, Y., Cai, Z., Hu, J., Wei, N., Wu, J., Du, H., Chen, T., Li, R., Tan, H., Kang, L., Yao, L., Huang, M., Wang, H., Wang, G., Liu, Z., & Hu, S. (2020). Factors Associated With Mental Health Outcomes Among Health Care Workers Exposed to Coronavirus Disease 2019. JAMA Network Open, 3(3), e203976. https://doi. org/10.1001/jamanetworkopen.2020.3976 Leiter, M. P., & Durup, J. (1994). The discriminant validity of burnout and depression: A confirmatory factor analytic study. Anxiety, Stress, & Coping, 7(4), 357–373. https://doi. org/10.1080/10615809408249357 Maslach, C., Jackson, S. E., & Leiter, M. P. (1997). Maslach Burnout Inventory: Third edition. In Evaluating stress: A book of resources (pp. 191– 218). Scarecrow Education. May 18, & Fedinick, 2015 Kristi Pullen. (n.d.). Getting to know the HPA axis. NRDC. Retrieved May 18, 2022, from https://www.nrdc.org/ WINTER/SPRING 2022

experts/kristi-pullen/getting-know-hpa-axis McConkey, D. J., Nicotera, P., Hartzell, P., Bellomo, G., Wyllie, A. H., & Orrenius, S. (1989). Glucocorticoids activate a suicide process in thymocytes through an elevation of cytosolic Ca2+ concentration. Archives of Biochemistry and Biophysics, 269(1), 365–370. https://doi. org/10.1016/0003-9861(89)90119-7 Medical Device Shortages During the COVID-19 Public Health Emergency | FDA. (n.d.). Retrieved May 18, 2022, from https://www.fda. gov/medical-devices/coronavirus-covid-19and-medical-devices/medical-device-shortagesduring-covid-19-public-health-emergency Morera, L. P., Gallea, J. I., Trógolo, M. A., Guido, M. E., & Medrano, L. A. (2020). From Work WellBeing to Burnout: A Hypothetical Phase Model. Frontiers in Neuroscience, 14. https://www. frontiersin.org/article/10.3389/fnins.2020.00360 New survey finds COVID-19 is taking a significant toll on physicians | Fierce Healthcare. (n.d.). Retrieved May 18, 2022, from https://www. fiercehealthcare.com/practices/new-surveyfinds-significant-toll-covid-19-physicians Panagioti, M., Panagopoulou, E., Bower, P., Lewith, G., Kontopantelis, E., Chew-Graham, C., Dawson, S., van Marwijk, H., Geraghty, K., & Esmail, A. (2017). Controlled Interventions to Reduce Burnout in Physicians: A Systematic Review and Meta-analysis. JAMA Internal Medicine, 177(2), 195–205. https://doi. org/10.1001/jamainternmed.2016.7674 Patel, R. S., Sekhri, S., Bhimanadham, N. N., Imran, S., & Hossain, S. (2019). A Review on Strategies to Manage Physician Burnout. Cureus, 11(6), e4805. https://doi.org/10.7759/ cureus.4805 Pitlik, S. D. (2020). COVID-19 Compared to Other Pandemic Diseases. Rambam Maimonides Medical Journal, 11(3), e0027. https://doi. org/10.5041/RMMJ.10418 Ranjbar, N., & Ricker, M. (2019). Burn Bright I: Reflections on the Burnout Epidemic (Part One of a Two-Part Series). The American Journal of Medicine, 132(3), 272–275. https://doi. org/10.1016/j.amjmed.2018.09.036 Shanafelt, T. D., Dyrbye, L. N., & West, C. P. (2017). Addressing Physician Burnout: The Way Forward. JAMA, 317(9), 901–902. https://doi. org/10.1001/jama.2017.0076 151

Sohn, E. (2022). How the COVID-19 pandemic might age us. Nature, 601(7893), S5–S7. https:// doi.org/10.1038/d41586-022-00071-0 The Physicians Foundation Launches Campaign to Help Prevent Physician Suicide. (2019, September 17). The Physicians Foundation. https://physiciansfoundation.org/press-releases/ the-physicians-foundation-launches-campaignto-help-prevent-physician-suicide/

"Though the American government spends trillions of dollars on healthcare every year...health outcomes in American are not significantly better (and often worse) than comparably developed nations."

West, C. P., Dyrbye, L. N., & Shanafelt, T. D. (2018). Physician burnout: Contributors, consequences and solutions. Journal of Internal Medicine, 283(6), 516–529. https://doi.org/10.1111/ joim.12752 Wu, H., Soe, M. M., Konnor, R., Dantes, R., Haass, K., Dudeck, M. A., Gross, C., Leaptrot, D., Sapiano, M. R. P., Allen-Bridson, K., Wattenmaker, L., Peterson, K., Lemoine, K., Tejedor, S. C., Edwards, J. R., Pollock, D., Benin, A. L., & Network, for the N. H. S. (2021). Hospital capacities and shortages of healthcare resources among US hospitals during the coronavirus disease 2019 (COVID-19) pandemic, National Healthcare Safety Network (NHSN), March 27–July 14, 2020. Infection Control & Hospital Epidemiology, 1–4. https://doi.org/10.1017/ ice.2021.280 Wurm, W., Vogel, K., Holl, A., Ebner, C., Bayer, D., Mörkl, S., Szilagyi, I.-S., Hotter, E., Kapfhammer, H.-P., & Hofmann, P. (2016). DepressionBurnout Overlap in Physicians. PLOS ONE, 11(3), e0149913. https://doi.org/10.1371/journal. pone.0149913 Yates, S. W. (2020). Physician Stress and Burnout. The American Journal of Medicine, 133(2), 160–164. https://doi.org/10.1016/j. amjmed.2019.08.034

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