Swarthmore Journal of Science

Swarthmore Journal of Science Issue 01- Fall 2014

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Life’s Compelling Puzzle Sun in a Bottle: An Inside look to plasma physics @ Swat

MORE THAN SKIN DEEP: Hansen’s Disease in China

Swarthmore Journal of Science

Claudia Luján

Ariel Parker and Randall Burson

Math and Statistics: Meghana Ranganathan The Missing Link: POC and STEM

Rise of the Machines

Biology: Justin Sui and Madeleine Booth

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How to ask questions in Biology

Chemistry: JeeHae Kang

Engineering: Chrissy McGinn Physics: Samer Nashed Copy Editor: Phoebe Cook

Plasma and Swarthmore

Chemistry: Alice Herneisen Biology: Helen Wang, Azucena

Mayonnaise & Robots: The Physics Behind Jamming Attack of the Parasitoid Maggots: Evolution and Crickets

Lucatero, Zeluleko Sibanda Engineering: Raundi Quevedo Physics: Peter Weck

ORIGIN: Life’s Beginnings and Mysteries

Layout: Deborah Yu

An Energy Dilemma: Climate Change and Fuel Cells

Claudia Luján Leela Breitman

More than Skin Deep: Hansen’s Disease in China The Success and the Failure: Publication Bias

swatjournalscience@gmail.com Connect with us on: www.facebook.com/SwatJournalScience

EBOLA: A look into Epidemiology Models

http://www.pinterest.com/sciencejournal/

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Letter from the Editors Dear Reader, In the Fall of 2011, the doors of Science Center 101 welcomed our eager selves into the world of science. Like many before us, our initial years in the natural sciences were as turbulent as they were rewarding. Though we grew to love our classes for all their richness and complexity, we oftentimes found ourselves struggling amid their rigor. With each passing semester we began noticing trends characteristic of STEM (science, technology, engineering, and mathematics) fields, particularly, the underrepresentation of women and people of color. What you now hold in your hands is the product of these conversations that hopes to address several questions:   

How do we highlight and address the shortcomings in STEM fields?

How can we increase scientific literacy across campus?

How can we incorporate diverse perspectives and make science an inclusive dialogue?

These questions guided us as we paved our way toward the college’s first science journalism publication: Swarthmore Journal of Science. This first issue represents the cumulative work of students from a variety of scientific backgrounds, eager to share their experiences with the Swarthmore community. We hope to provide a space for students to ask questions, share their work, and engage in conversations about our articles. As seniors, we hope our work will inspire a lasting space for these conversations to occur and invite you to participate. We thank you for joining us in this endeavor and hope you enjoy!

-Claudia, Randy, and Ariel

QA &

SJS is powered entirely by Swattie energy, bringing together editors and contributors from across the STEM disciplines to produce the journal in front of you. In the hopes of improving science literacy, we have crafted pieces that are accessible as they are informative and fun!

Did you know the Physics department has a plasma wind tunnel? Ever wonder how life began? Answers to these questions, and more await! Our contributors have written about an array of topics. But one thing remains constant: we’ve put together this journal to share our love of science with you! From everyone at SJS, we hope that you’ll find something to enjoy!

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Claudia Luján ‘15

Ariel Parker ‘15

Biology and English Literature

Biology + French Minor

Peter Weck ‘15

Physics + Philosophy Minor

Samer Nashed ‘15

Physics + Computer Science

Randy Burson ‘15 Chrissy McGinn ‘16

Biology + Anthropology Minor

Alice Hernaisen ‘17

Chemistry + BIology

Justin Sui ‘15

Biology + Film & Media Minor

Phoebe Cook ‘15

Helen Wang ‘17

Biology + GenSex and Edu Minor

Economics + Math/Stat Minor

Madeleine Booth ‘15 Raundi Quevedo ‘16 JeeHae Kang ‘17

Biology and Linguistics

Chemistry + Engineering Minor

Neurobiology + Public Policy Minor

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Engineering + Physics

Azucena Lucatero ‘16

Biology + Asian Studies

Zeluleko Sibanda ‘17

Neuroscience

Deborah Yu ‘15

Biology + English Literature

SCIENCE IN THE NEWS

The study of social media trends is an important topic for today’s scientific community. Recently, researchers studying social networking sites have unveiled trends in app installation, producing a model for how often people “copy” the behavior of their Facebook friends.

This particular study was able to separate individuals' decisions to install apps based upon suggestions from their friends from installations based off of Facebook’s “bestseller” lists —another fascinating example of the power of mathematics in the analysis of social networks.

Ever wonder why hipsters, known for their counterculture attitudes and hand-knit beanies, all look eerily the same? A recent model proposed by Parisian mathematician Jonathan Touboul helps explain this curious trend. After studying patterns of individuals in society, Touboul alleges that hipsters are “largely aligned, towards a constant direction which is imposed by the mainstream choices” (Toubol, 2014). Fighters of the norm, Touboul argues, form a unified front because rebellion can only manifest in so many ways. Looks like the lovable hipsters are doomed to drink the same craft beers for all eternity!

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Recent sequencing of ADH4 proteins, used for the dehydrogenation of ethanol during alcohol digestion, from 19 modern primates has given us insight into the origins of the desire and ability to consume alcohol in humans. Analysis of ADH4 proteins reveals that around 10 million years ago, an ancestor of humans developed an ADH4 with a dehydrogenation potential 40x higher than its predecessors (Carrigan et al., 2014). Researchers explain this change through the framework of evolutionary adaptation. As human ancestors began to utilize fallen, fermenting fruits as a key food resource, there was an associated selection for more efficient ADH4 proteins among the greater population, allowing for better digestion of ethanolcontaining foods.

In summer of 2014, Swarthmore student David Ranshous studies the human immunodeficiency virus (HIV). His work was three pronged seeking to model differential equations to describe the virus in vivo, observing how residual viral load responds to drug efficacy, and lastly, attempting to isolate parameters leading to higher-thancontrolled viral load.

While findings showed very different levels of drug effectiveness, one differential equation parameter was identified that overtly affected the residual viral load. In this way, a correspondence was found between high death rates of infected cells and higher residual loads. Keep up the good work David!

By Samer Nashed are disordered. Unlike a crystal, where every atom or molecule occupies a specific position in a lattice, these systems contain no macroscopic order.

Their particles are packed randomly, making them much less predictable. In fact, these systems’ state of matter is probabilistic. Given two disordered systems with the same conditions, one may be jammed while the other is not. It depends on the arrangement of particles within the substance.

The solution is to do what physicists are best at, ignoring the small details. To do this, we study an ideal system. By making computer models, we can add just enough complexity to reproduce the physical results while ignoring features which may differ depending on the substance. The model typically used is a collection of disks in 2D (or spheres in 3D) which interact through strictly

Although we know much about the universe and its inner workings, many seemingly mundane phenomena still elude mathematical description. The splashing of liquids, for instance, or the diffusion of one liquid into another, remain incredibly difficult problems. In fact, there is some complex physics happening in your refrigerator right now – not in the fridge’s cooling system, but inside your jar of mayonnaise. Mayonnaise is an emulsion, or a fine mixture of liquids which are not soluble. A mixture of egg and oil droplets, mayonnaise can behave both like a solid and a liquid. Other substances that display similar characteristics are colloids (solid mixed with liquid) like toothpaste, and foams (gas mixed with liquid) like shaving cream. One goal for physicists studying these types of materials is to determine what conditions prompt these substances to undergo phase changes from solid to liquid, or vice versa. The act of going from a liquid to a solid is called jamming.

A quantitative characterization of jamming faces two primary obstacles. First, all of these substances interact in different ways at the molecular level. In a foam, surface tension must be accounted for; in a colloid, frictional or thermal forces may be a factor; in Jell-O, long molecules actually intertwine, and the list goes on. Second, these particles

From http://willneverfly.files.wordpress.com/2011/07/mayonnaise-1a.jpg

Figure 1: Left – Mayonnaise under an electron microscope. Right – Graphical display of a jamming simulation. Black stars arranged in a square lattice are pinned, while the blue circles are free to move around during simulation. Note the disorder in both systems.

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repulsive forces. Essentially, as long as two particles are not trying to occupy the same space, they do not interact. This means frictional and attractive electromagnetic forces are completely ignored. We also model these systems at zero temperature and pressure. This eliminates the effects of thermal motion and any strange behavior at the boundaries of the system.

solid. The relationship between change in parameter and change in measureable variable can be quantified by a susceptibility. The computational physics lab at Swarthmore led by Professor Amy Graves, in conjunction with Professor Andrea Liu at the University of Pennsylvania, was able to calculate for the first time this socalled pinning susceptibility for systems in both two and three dimensions. Future work with lattices of fixed particles will likely find direct application in a wide variety of engineering endeavors.

In the summer of 2013, the physics of jamming already had a solid foundation. It is known that temperature, shear stress – think knife spreading mayonnaise, and packing fraction all affect the probability of a substance jamming. The packing fraction is the fraction of the volume of interest occupied by particles, so a bucket filled with 60% sand and 40% water has a packing fraction of .60. Figure 2 shows a jamming phase diagram.

Although the theory of jamming is relatively theoretical, abstracting away many details necessary for working with a specific substance, further understanding continues to motivate and inspire innovation in areas outside of physics. In robotics, for instance, grasping objects of indefinite size and shape is a formidable problem which has found a partial solution with the help of research on jamming. The Boston based company Empire Robotics has a product they call the Versaball Gripper which uses the phenomenon of jamming to grasp irregular objects.

The ball-shaped, flexible rubber gripper begins filled with a mixture of granular material and air at a low packing fraction. Once the gripper is positioned around the object of interest, air is pumped out of the gripper, dramatically increasing the packing fraction and causing a phase change inside the gripper head. After enough air has exited the gripper, it is completely solid yet molded to the object. If the release of an object is desired, air is simply pumped back into the gripper, decreasing the packing fraction and causing a phase change from solid back to liquid. This causes the gripper to exert less and less frictional force on the object until it is finally released. New theories related to jamming in the presence of obstacles and lattices will continue to influence solutions to problems in both academia and industry. As the field grows to encompass larger classes of problems, and techniques from other areas of physics are adopted within the jamming community, the pace of advances in related fields will hopefully follow suit.

From http://www.physics.upenn.edu/liugroup/figs/jamming_phase_diagram3.png

Figure 2: Jamming phase diagram. Operation at zero temperature and pressure restricts motion in phase space to one dimension – along the 1/Density axis.

Point J is where all the interesting physics happens; it is a critical point where, if our system had infinitely many particles, a phase transition would be guaranteed to occur. Since we cannot simulate an infinite number of particles, point J marks the packing fraction where the probability of being liquid or a solid is equal. Our lab’s goal was to measure the effect of randomly pinned particles on systems near point J. A pinned particle is an immobile particle which does not move during the simulation, even if it experiences a net force. Near point J, small changes in parameters like packing fraction or the density of pinned particles can cause large changes in physically measureable quantities, like the number of contacts between each particle or the probability that the substance is a

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Attack of the Parasitoid Maggots anda b i S o k le

By Zelu

John B. Smith Economic Entomology (Philadelphia and London: J.B. Lippincott Co, 1896)

When I was growing up in Zimbabwe, crickets were an altogether common aspect of life, extending to my grandmother’s kitchen where she loved preparing the large edible African cricket, Brachytrupes membranaceus, a weekly delicacy. My interest in entomology has since developed from the culinary to encompass the evolution of crickets under the force of selection pressures such as environmental alterations and novel predator relationships. I recently came across entomological research led by the evolutionary biologist Marlene Zuk, who incorporates her interest in feminism and women in science into her investigations.

cricket hosts (Robert & Willi 2000). O. ochracea females then oviposit numerous planidia, larvae at the initial developmental stage, directly onto the host (Lehmann 2008). After planidia have infected the cricket host, they lodge into muscle cavities before migrating into the abdomen and feeding on the cricket’s abdominal and thoracic tissues (Adamo et al. 1995). After 7 to 10 days, the larvae emerge from the cricket’s body, a gruesome process that gradually kills the host (Figure 1).

Recent research by Zuk highlights the convergent evolution of wild Polynesian crickets, Teleogryllus oceanicus, on two Hawaiian islands, Oahu and Kauia (Pascoal et al. 2014). Convergent evolution describes the acquisition of similar adaptational traits by geographically isolated lineages that are subjected to similar selection pressures. Sexual selection promotes the evolution of conspicuous traits that attract the opposite sex, such as elaborate ornamentation and behaviors, even though they may hinder survival.

Consequently, the net effect on fitness of a sexual trait reflects the balance between natural and sexual selection.

Figure 1: O. ochracea parasitoid maggots emerging from infected T. oceanicus abdomen. Image courtesy: J. Rotenberry

A species that has recently come under the spotlight as it totters on the natural-sexual selection scale is the wild cricket, Teleogryllus oceanicus. The cricket species is native to Australia and was first introduced to Kauai prior to 1877. It has since spread to the neighboring island of Oahu (Kevan 1990, Otte 1994). T. oceanicus males rely on a unique acoustic sexual signaling system to attract females but this comes at a very high cost: the singing also attracts droves of the parasitoid fly, Ormia ochracea.

To counteract the deadly attack of the parasitoid maggots, male crickets on the Hawaiian island of Kauai have undergone rapid evolution, with 90% of the normal-wing morphology being replaced by the mutated flatwing morphology within 20 generations (Zuk et al.

2006). The song suppressing mutation is due to an alteration of a single sex-linked locus of a gene with mutant males being hemizygous for the mute trait (Tinghitella 2007). Normal T. oceanicus males produce the acoustic tone as the wings are raised and the plectrum (scraper) of the left wing catches and releases the teeth on the underside of the right wing, thereby pro-

O. ochracea use scolopidia, a mechanoreceptor organ characteristic of most hearing insect species, to detect mechanical vibrations produced by potential 8

ducing a phasic excitation that translates into vibrations of both wings and the production of approximately pure-tone sound (Bennet-Clark 2003). With flatwing males, the mutation leads to the loss of the scraper along with the resonating structures of the wing. However, it is important to note that the mutant male wings do still differ from the female wings as SEM micrograph scans show the presence of a stridulatory apparatus on mutant male wings that is absent in females (Zuk et al. 2006) (Figure 2, 3).

Figure 3: Comparison of flatwing and wild type wing phenotype. Image courtesy: Bailey.

Whilst the flatwing mutation safeguards these male crickets from predation, it prevents them from attracting females. Mutant flatwing males consequently act as “satellites” to the remaining callers by relying on enhanced phonotaxis to the calling song and move towards calling male crickets. In doing so the mutant crickets may be more likely to successfully copulate with females. This display of behavioral plasticity explains the relatively stable flatwing male-female encounter rate observed in the field.

nomic architectures that ultimately led to divergent wing morphologies (Pascoal et al. 2014). The Oahu mutant flatwing males still posses remnants of the toothy, noise producing vein on the wing, unlike the Kauai mutant males (Pascoal et al. 2014). The two populations have thus undergone rapid convergent evolution, with two distinct evolutionary origins.

Futhermore, the persistence of the mutant flatwing trait, despite the disadvantage it confers in sexual competitions, can be explained by the Hamilton-Zuk model of sexual selection. The model relies on the principle that the expression of male traits is associated with their resitance to parasites and pathogens, and females utilize these traits as indicators of beneficial traits which may be passed onto their offspring. Therefore, in the case of T. oceanicus crickets, the evolution of the mutant flatwing trait also causes the evolution of a more extreme female preference. However, the critical aspect of this hypothesis is that the mutant male trait and female sexual preference never reach an equilibrium since genes for O. ochracea infection resistance, as well as female mate preference constantly evolve in response to O. ochracea adaptation. With O. ochracea parasitoids and their T. oceanicus hosts coFigure 2: Wing morphologies evolving, the most of T. oceanicus. Forewings from a) flatwing male, b) nor- fit host genotype in mal male and c) female. The file terms of parasite resistance oscillates (1), scraper and stridulatory between generastructures of the harp (2) and mirror (3) are only present on tions (Hamilton & Zuk 1982). the normal male (Tinghitellla 2007).

The discovery of silent T. oceanicus males on the neighboring Hawaiian island of Oahu two years ago was initially hypothesized to be due to gene flow caused by interbreeding between the two populations. However, recent genome scans using RAD-seq reveal the two island populations to have different ge9

The rapid convergent evolution of T. oceanicus males to defend against O. ochracea predation illustrates the amazing power of natural selection in shaping a species. It remains to be seen whether T. oceanicus females of both populations will change their preferences, or whether mutant flatwing males shall continue to rely on the remaining normal males to act as “satellites” in the search for a mate.

In the midst of this continuing compelling entomological research, what’s next for these silent crickets?

This evolutionary defence story is far from over.

Literature Cited: Adamo S, Robert D, Hoy R 1995 Effects of a tachinid parasitoid, Ormia ochracea, on the behaviour and reproduction of its male and female field cricket hosts (Gryllus spp.), J. Insect Physiol. 41: 269-217 Bennet H C 2003 Wing resonances in the Australian field cricket Teleogryllus oceanicus, The Journal of Experimental Biology 206:1479-1496 Hamilton W D, Zuk M 1982 Heritable true fitness and bright birds: a role for parasites? Science 218: 384-387 Kevan D K M 1990 Introduced grasshoppers and crickets in Micronesia Bol Sanid Veg. Plagas 20:105–123 Kolluru G, Zuk M, Chappell M 2002 Reduced reproductive effort in male field crickets infested with parasitoid fly larvae, Behavioral Ecology 13 (5): 607–614.

Lehmann G U 2008 How different host species influence parasitism patterns and larval competition of acoustically-orienting parasitoid flies (Tachinidae: Ormiini) Animal Behaviour: New Research, 93-132 Pascoal S, Cezard T, Eik-Nes A, Gharbi K, Majewska J, Payne E, Bailey N W 2014 Rapid convergent evolution in wild crickets, Current Biology 24: 1369-1374 Pascoal S, Cezard T, Eik-Nes A, Gharbi K, Majewska J, Payne E, Bailey N W 2014 Rapid Convergent Evolution in Wild Crickets, Current Biology 24:12, 1369-1374 Robert D, Williw U 2000 The histological architecture of the auditory organs in the parasitoid fly Ormia ochracea, Cell and Tissue Reaserch 301:3, 447-457 Tinghitella R M 2007 Rapid evolutionary change in a sexual signal: genetic control of the mutation ‘flatwing’ that renders male field crickets (Teleogryllus oceanicus) mute, Heredity 100: 261-267 Zuk M, Rotenberry J T, Tinghitella R M 2006 Silent night: adaptive disappearance of a sexual signal in a parasitized population of field crickets, Biol. Letter 2:4, 521-524 Zuk M, Simmons L, Cupp L 1993 Calling Characteristics of Parasitized and Unparasitized Populations of the Field Cricket Teleogryllus oceanicus, Behavioral Ecology and Sociobiology 33 (5): 339–343

Swarthmore’s

Sun in a Bottle: Plasma and Physics at SSX

by Peter Weck

It drives everything from ocean currents to life as we know it, yet we still lack a detailed understanding of what drives the sun itself.

From the 11-year sunspot cycle to the mechanism behind the coronal mass ejections throwing storms of charged particles towards earth, there is a lot to solar physics we haven’t completely figured out. Most physicists interested in understanding the sun do so by analyzing data from satellites and telescopes. However, we can also learn about solar physics by doing experiments in the lab, not with the sun of course, but with the stuff it’s made of: plasma.

This is the approach physics professor Michael Brown uses at his one-of-a-kind plasma wind tunnel known as the Swarthmore Spheromak Experiment, or SSX. The work done here at Swarthmore using the SSX device contributes not only to solar physics, but also the fundamental plasma physics needed to make fusion energy an efficient source of electricity.

Figure 1:The SSX plasma wind tunnel. Photo by David Schaffner.

Just apply voltage and stir The recipe for making a spheromak, or donut-shaped blob of plasma, is pretty straightforward. Plasmas are gases so hot that the negative electrons and positive nuclei from individual atoms are free to whiz around on their own. These plasmas can be created by taking room temperature hydrogen gas and applying a voltage which is so large that it tears virtually all of the electrons away from their proton pairs. The resulting soup of charged particles is around a million degrees Kelvin, substantially hotter than the surface of the sun. If the right strength and shape magnetic field is then applied, the plasma can be twisted and pushed at tens of kilometers per second. This part of SSX is called the plasma gun. The gun launches the spheromak of plasma into a long vacuum tube equipped with instruments to measure temperatures, magnetic field, densities, and other quantities as the plasma swirls down the tube. Voila! You have a plasma wind tunnel.

Any way the solar wind blows Ever since SSX was started in 1994, students have played an integral role. Over 40 Swarthmore students have worked with the lab, and have been involved in every stage of research. SSX has received over $2.5 million in funding from the U.S. Department of Energy, the National Science Foundation, and others. Originally, the focus of the research was to explore the process known as magnetic reconnection, which is thought to be the mechanism for the release of energy from coronal loops on the surface of the sun, one of the main drivers of interplanetary weather. Coronal loops are massive, twisted braids of plasma bound to the sun’s surface.

When pieces of these loops break away from the sun, energy is released, heating the sun’s upper atmosphere, or corona, and sending streams of energetic particles out into space. As scientists figured out the role of reconnection in these events, the lab’s focus shifted to other features of the low-density plasma shed by the sun, or solar wind. Understanding solar wind better equips us to miti-

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gate blackouts and damage to spacecraft. Just as conventional wind tunnels study the laws of aerodynamics, the SSX wind tunnel studies the magnetohydrodynamics governing the solar wind. The motions of charged particles in plasmas are affected by electric and magnetic fields, and these motions in turn alter the fields, making them even more difficult to predict than conventional fluids.

smoke or coffee. This summer, I used some new mathematical tools to compare different turbulent plasmas. By representing each system with a position on a plane with a different type of complexity on each axis, I found that the solar wind appears significantly more turbulent than laboratory plasmas like SSX. More work will be required to understand why.

Understanding plasma turbulence has particular importance for fusion energy, the source of the sun’s power. Fusion is often seen as the holy grail of renewable energy sources, as it would be completely clean and reliable, run on plentiful sea water, and take up less space than solar or wind alternatives. One of the biggest impediments to making fusion a viable source of electricity is magnetic confinement. To ignite a self-sustaining fusion reaction, you have to make plasmas either very hot, very dense, or held together for a long period of time, preferably all of the above. Like the smell of baking cookies spreading through a house, dense plasma wants to diffuse into areas of lower density. Strong magnetic fields are used confine the plasma, but if it becomes too turbulent, the resulting fluctuations can give the plasma the chance to escape. SSX is not focused on understanding turbulence in magnetically confined plasmas per se, but in understanding turbulence more generally as it appears in the solar wind and the SSX wind tunnel.

Coffee creamer and sun-power

From http://solarsystem.nasa.gov/planets/profile.cfm?

Figure 2: Coronal mass ejection from 2012, with earth overlaid for size comparison. Photo from the NASA Goddard Space Flight Center’s website.

Although we have a long way to go before understanding exactly how the sun works or learning to harness its power for ourselves, Swarthmore’s own sun in a bottle has an important role to play in the process. SSX occupies a unique position at the interface of space and fusion physics, expanding our understanding of basic plasma physics without the usual exorbitant costs. Along the way, the lab provides an exciting opportunity for Swarthmore students to engage in world-class research on a scale to make proponents of the liberal arts everywhere proud.

When a fluid flows steadily and smoothly, physicists call it laminar. When it moves at many different speeds and directions, it is called turbulent. Turbulence is everywhere, in the cream mixing with your coffee or the smoke rising from a campfire. The streams of plasma blown off the sun in the solar wind are turbulent too, but is it the same kind of turbulence? After all, plasmas interact with electromagnetic fields. Does that make plasma turbulence more structured? Scientists think so, but still don’t understand turbulence in plasmas nearly as well as in

Figure 3: An example of the kind of plot I created this summer to compare different turbulent plasmas. The black crescent shape marks max and min mathematically possible positions on this plane. Markers included in the legend indicate different kinds of plasma, and the other markers show the positions of various mathematical models for comparison. Systems farther down and to the right are less “structured” and more “random”, both characteristics of turbulence.

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By Alice Herneisen

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That is, proteins transcribe an RNA strand from DNA, which is then translated into an amino acid chain that will eventually become a protein.

Scientists regard the universality of these processes as evidence that all extant organisms inherited them from an ancestor billions of years ago.

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Although scientists have learned much about the mysteries of the cell, they would readily admit that there remains much more to be unearthed, centrifuged, or computed. If one does, as many scientists do, refer to what is called the NASA "working definition" of life as "a self-sustaining system capable of Darwinian evolution,” (1) then there arises what scientists of the Salk Institute have dubbed the “chicken and egg problem:” DNA requires proteins to replicate, yet proteins need a transcript from DNA in order to come together. Many scientists take this as a cue that the messenger between the two, RNA, may once have played both roles, as self-replicator and catalyzer of reactions in the cell. This view, appropriately, has been labeled the “RNA World”(2).

Scientists have long struggled with the question of the origin of life. Among the Big Three – who are we, where are we going, and where do we come from – it is the question that may never be answered. The challenges seem insurmountable: no one can predict with certainty the nature of the microenvironments that were most hospitable to nascent life, and not even the window of geology allows us to see back four billion years ago. Add to that undesirable combination an unfettered definition of life that falls (philosophical debates aside, and there are many) along a continuum of biological organization with the line drawn “nearest to my area of research” (1), and you may wonder why scientists don’t balk at attempts to answer an unanswerable question. Many do. But those who haven’t, have taken us from theories of solutions miraculously filled with organic compounds (Darwin’s “warm little pond”) to Renaissance man RNA (ribozymes) to isolated crevices in minerals. This is the world of prebiotic chemistry, where the roots of the tree of life have taken hold.

If it existed, the RNA World would explain many of the diverse roles RNA plays in current cells. One of many such examples includes the fact that the ribosome, the cellular machinery that reads RNA and creates proteins, is itself largely composed of RNA. Catalytic RNA molecules, or “ribozymes”, were discovered in 1982 and have been an area of vibrant research ever since (2).

At the most basic level, it would only take one ribozyme with a crude self-replicating mechanism to generate a population capable of undergoing chemical evolution. Mistakes in replication – sure to be many in the absence of protein quality control – could create a new type of ribozyme, giving rise to variability. In an environment where nucleotides are few and disintegration of longer strands is imminent, only the best self-replicators – the fastest and most accurate – would make it to the next round. This past year scientists at The Scripps Research Institute were able to create just such a highly efficient self-replicating ribozyme using “directed evolution”, a finding admittedly confined to a test tube, but extending possibilities nonetheless (3).

Before we begin our examination of the most encompassing theories of how life might have originated, it would be prudent to consider what we do, in fact, know. Conventional wisdom holds that the chemical subunits of life consist of amino acids, nucleotides, and sugars. When combined, these monomers respectively form proteins; nucleic acids, deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) in terrestrial life, which store the genetic code; and carbohydrates. Add to the mix lipids, whose waterloving heads and water-fearing tails align into bubble-like vesicles, and you have the major components of all known cells.

In what has been dubbed “the molecular biologist’s dream”, all of the necessary nucleotides, freely floating about in solution (colloquially referred to as “Darwin’s ‘warm little pond’” or “primordial soup”), would assemble into a strand of RNA and, perhaps on a mineral surface such as montmorillonite clay, undergo nonenzymatic replication. Follow evolution, RNA World, life. And some dream this is,

All terrestrial cells follow the so-called “central dogma”. In the most basic of schematics it is DNA

RNA

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? for nucleotides are a nightmare to synthesize under prebiotic conditions (2).

Nucleotides consist of three parts: a phosphate group, the sugar ribose, and a unique nitrogenous base. Under biological conditions these parts are brought together easily enough, but without catalysts, creating nucleotides is an uphill battle (1). Aware that attempting to mimic the way current cells synthesize nucleotides was getting other scientists nowhere, scientists at the University of Manchester decided to use a more creative approach. Using the same starting materials used to make nucleotides the tried-anddone way, they produced an intermediate that looks halfway between a sugar and base. Adding on a phosphate group leads to a rearrangement and produces a compound that can be converted by light into a derivative of the nucleotide uracil. It is an admittedly indirect path, but one that proponents of the RNA World can use to traverse a painfully conspicuous barrier (4).

positively-charged portion of a mineral – he specifically identifies pyrite (FeS2) in his manuscript – as a “surface metabolism”(5).

Using Darwinian evolution as a metaphor, autocatalysis could be heredity and growth, as chemical compounds that work together to catalyze their own production – “surface metabolists” – are attracted to positively-charged mineral surfaces, creating metabolic “shuttles”. “Autocatalytic novelty” in these shuttles becomes pre-cellular evolution and speciation as old pathways branch or attach to an entirely different pathway, perhaps one with a shared intermediate, in a process of “chemical symbiosis”. Enclosure by a lipid layer would both allow metabolic communities to influence the internal environment and detach from the mineral surface, thereby jumping from two dimensions to three. Wächtershäuser envisions the lipid layer as ideally enclosing the entire mineral grain, leaving the catalytic surface available for especially uphill syntheses (5).

If all of this seems dubious to you, an inexcusable violation of Occam’s razor – that a better solution is a simpler one – you are not alone. While proponents of the RNA World hypothesis have zeroed in on the “Darwinian evolution” part of the working definition of life, other scientists have paid greater attention to the “self-sustaining system”. They have instead focused on the creation of a metabolism, and their path may eventually join with the one we have already seen.

The central tenet of the so-called “metabolism-first” model is that metabolic pathways have to have been significantly developed before any sort of RNA takeover could occur. One of the most influential pieces of work in this area came from Günter Wächtershäuser, German patent layer-trainedchemist. He envisions life taking hold on the isolated

Wächtershäuser’s chemistry is extremely specific and theoretically beautiful. He starts with simple iron ions, hydrogen sulfide and carbon dioxide, elements and compounds believed to have been abundant on the early earth, and traces how one could get organic molecules and metabolic pathways that resemble those we see in life today. He even goes on, incredibly, to propose how this surface metabolism could transition to nucleic acids, creating heredity in the sense that we know today While the larger scientific community has met Wächtershäuser’s exact proposed pathways with scrutiny, his views nonetheless reflect the ideas of scientists pursuing origin of life research along the lines of early metabolism. So, too, do his meditations on his own theory mirror assessment of his critics: his ideas are “thermodynamically possible but mechanistically obscure” (5).

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There arises what scientists of the Salk Institute have dubbed the “chicken and egg problem”: DNA requires proteins to replicate, yet proteins need a transcript from DNA in order to come together.

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All of these findings fall into a larger paradigm as building blocks not yet assembled into a tower. We have not yet produced an architect who can best Nature by creating life out of the same materials 14

piece together a string of likely events from physical records provided by our young solar system. But chemistry does not play by the rules of biology. We may be blinded by our and recreation in the laboratory. And just as we value the love of efficiency; even now we scorn the idea of needless work of prehistorians for providing the knowledge of events that may have shaped the human condition, so too should we waste. Chemistry, in comparison, is disgustingly opporvalue the work of origin of life researchers for not just figurtunistic. A certain step in a pathway may happen only ing out what cells are, but why they came to be this way. once per hour, producing an intermediate that will fall back What makes biology different apart in half a second unless a certain (perhaps equally short- compared to chemistry is that lived) compound happens to Literature Cited occupy the same area, but that biology has a history. great unlikelihood does not 1. "Forming a Definition for Life : Interview with Gerald Joyce." Interview by Leslie preclude such a reaction from —Gerald Joyce Mullen. Astrobiology Magazine. NASA, 25 happening. For the one thing July 2013. Web. 10 June 2014.

2. Orgel, Leslie E. "Prebiotic Chemistry and the Origin of the RNA World." Critical prebiotic chemistry did not lack was time – hundreds of Reviews in Biochemistry and Molecular Biology 33 (2004): 99-123. Web. 10 June millions of years of it.

2014.

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Gerald Joyce, a prominent researcher of the origins of life, remarked in an interview, “what makes biology different compared to chemistry is that biology has a history” (1). Scientists will never be able to read the true history of early life but, like prehistorians, they may try to

”

3. Joyce, Gerald F., and Michael P. Robertson. "Highly Efficient Self-Replicating RNA Enzymes." Abstract. Chemistry & Biology 21.2 (2014): 238-45. Web. 10 June 2014.

4. Powner, Matthew W., Beatrice Gerland, and John D. Sutherland. "Synthesis of Activated Pyrimidine Ribonucleotides in Prebiotically Plausible Conditions." Nature 459 (2009): 239-42. Web. 10 June 2014.

5. Wächtershäuser, Günter. "Before Enzymes and Templates: Theory of Surface Metabolism." MICROBIOLOGICAL REVIEWS 52.4 (1988): 452-84. Web. 10 June 2014.

OPINION

By Azucena Lucatero

*Editor’s Note: A bridge program will be established in Summer 2015

Perhaps unbeknown to most, students had been working towards a bridge program for years. In 2010, a student initiative led by an IC/BCC coalition tasked themselves with envisioning how “to address the needs of a diverse group of students, including both domestic and international students who would benefit from additional science, math, humanities and social science preparation.” To this end, they conducted a survey of, then current, Swarthmore students. Among their findings, were:

During the spring semester of 2013, many Swarthmore students came together in a series of demonstrations to express a wide variety of frustrations they felt were not being addressed by the administration. One of the issues students brought up during the discussions and workshops that followed was the need for more academic support for minority students, specifically in the form of a revival of Swarthmore’s discontinued bridge program .

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The need for more academic support, in particular among students of color and students on financial aid.

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Across ethnic and racial divisions, less preparedness for the academic rigor of the natural sciences in comparison to the humanities and social sciences.

Students who identified as Black and Latino were mostly unprepared for the natural sciences while students who identified as White, Multiracial, Asian, and Other, contained higher percentages of prepared students. Attending a summer program assisting the academic transition from high school to Swarthmore upon entering college was desired by 62% of international students and 77% of first generation college students compared with 50% of total respondents.

Despite their findings, these students were unable to reestablish a bridge program due mainly to lack of funding and staffing. Opinions may be divided about whether a bridge program is appropriate 15

for Swarthmore, but the challenges faced by minority students are still very real and relevant. Obstacles such as inadequate science preparation in high school, feeling isolated in a field largely dominated by the Caucasian and affluent, and not knowing how to navigate the world of science and academia may ultimately dissuade minority students from pursuing the sciences.

Beyond difficulties in transitioning, minority students indicate they sometimes feel uncomfortable and isolated as one of a handful of students of color in the natural sciences. This affects their confidence in asking questions during lecture or seeking out help during office hours and help sessions out of the concern that they may appear less intelligent or capable than their peers. Low diversity among science faculty, both at Swarthmore and at potential graduate schools, makes some students wonder just how accessible the field of science is for them, and they worry about being taken seriously in academia. Lack of professors of color who they can relate to can thus make it difficult for these students to establish their own identity as a scientist and pursue science as a profession. Cognizant of these demographic disparities, many professors at Swarthmore reach out to minority students. Minority students who choose to continue in the sciences often depend on this support, as it helps them overcome difficulties that can act as barriers to the sciences. One current biology major, Jannette Alston, feels that “good professors know how to be mindful of [student diversity of access and experience] and create meaningful experiences in the classroom that accommodate students with different strengths and weaknesses.” Additionally, getting to know peers facing similar challenges is enormously helpful.

Students have expressed that reaching out to other minorities is immensely heartening. Upperclassmen students’ experiences both validate and reassure younger students, encouraging them to keep going. Currently, a student initiative led by Jannette is gathering testimonials from minority students to document their struggles and create a student association to connect minorities in STEM fields in an effort to facilitate and strengthen peer support systems and networks.

Upon entering college, students’ past experiences and abilities color their college science experience. Taking science at the college level for the first time can be quite the rude awakening for any student, but in particular for students whose high schools did not adequately prepare them for lab work, writing scientific papers, or simply thinking and handling material in ways required by the sciences. For these students, introductory science courses can be incredibly discouraging, as they must play catch up to learn what many of their peers already learned in high school as well as understand the class material being thrown at them. It is at this point that many students decide to drop their science major, but this does not have to be the case! There are support systems in place at Swarthmore that are worth looking into. Firstly, many introductory courses offer help sessions run by older students; however, it is often the case that students feel uncomfortable and vulnerable at these sessions. One key to navigating them is finding a smaller group of people that one works well with. Not everyone works at the same pace or benefits from the larger masses of student discussions that tend to form. Going to a professor’s office hours is another, more one-on-one option. Students find that professors are more than happy to answer questions, go over problems, or offer study tips. For lab reports, the Writing Center has students who specialize in science writing who can help steer students in the right direction. These are some of the resources available for students who may be struggling in their first few college-level science courses.

As a minority and, particularly, firstgeneration student, it can be tricky to figure out how the world of science and academia in general works.

Research experience and networking are often emphasized as of utmost importance, but for someone who has never had experience with either of those, it can be hard to decide how or where to start. Moreover, a disconnect between students and their family often exists in which parents find it difficult to understand the demands placed on their children and are unable to provide help or guidance. This is where advisors/mentors become fairy godparents. Advisors often help students find summer research positions, which are useful for providing insight into what grad school and a career in the sciences means in the real world, outside of lecture and lab. Some programs, like NSF funded REUs, provide stipends—especially valuable for students who would have to forsake summer opportunities out of financial constraints—and may even specifically look for students from underrepresented groups in their first couple years of college.

Swarthmore science can be tough for any student, but barriers exist that make taking on the sciences more difficult for certain students. Increasing the accessibility of the sciences at Swarthmore and beyond is a monumental endeavor that requires the collaboration of many. In particular, student efforts articulating the deficiencies they see and acting to correct them and strengthen existing support systems will be hugely important. Mentoring and guidance from professors and faculty is very important, but it leaves out the most vital component in diversifying the sciences. Involving those affected, namely students, is essential in the solution-making process. Only then will the gap between those historically advantaged and disadvantaged begin to close in any significant way.

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An Energy Dilemma

By Raundi Quevedo Because of climate change and the increasing depletion of the Earth’s natural sources of fossil fuels, there is a growing incentive to transition from fossil fuel-based energy sources to more efficient and environmentally-friendly energies. Interest is growing in alternative energy technologies, including fuel cells.

Fuel cells are devices that transform the chemical energy stored in fuels, such as hydrogen gas, into electrical energy. With efficiencies of 40% and higher, versus an average 30% efficiency seen in internal combustion engines; green byproducts (water and heat); and a capacity to run for extended periods of time with little manufacturing limitations, fuel cells are slowly but surely becoming an alternative sustainable energy.

How does a fuel cell work?

Every fuel cell has three things in common: the anode, the cathode, and the electrolyte. The anode is a positively charged electrode (a conductor through which electricity is passed) that attracts negatively charged particles, or anions. A cathode, on the other hand, is a negatively charged electrode that attracts positively charged particles, or cations. The electrolyte serves as a medium – it can ionize into

Figure 1: Schematic of operation of a fuel cell . From http://en.wikipedia.org/wiki/ File:Solid_oxide_fuel_cell_protonic.svg

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particles of either charge depending on the type of fuel cell. As Figure 1 shows, the fuel is injected near the anode. It reacts there to form electrons (e-) and hydrogen ions (H+) through a reductive process. A reductive process occurs when a molecule or atom loses one or more electrons. Most of those electrons are then used to generate the electric current, but some are transferred back into the system. The latter electrons react with the surrounding oxygen and the newly synthesized H+ ions to produce water through an oxidative process. An oxidative process occurs when a molecule or atom gains one or more electrons.

Most of these reactions are not very efficient at room temperature and pressure; so all fuel cell electrodes are coated with a thin layer of a catalyst, usually platinum. This increases efficiency.

Why fuel cells?

One advantage of fuel cells is that they use hydrogen, the most abundant element on earth and also one which is readily producible, as its main fuel. There are many ways to synthesize or obtain hydrogen: through natural gas reforming, coal gasification, or electrolytic processes such as water splitting.

These varied sources make hydrogen a sustainable energy, and its environmentally-friendly byproducts (water and heat) make it a clean energy. As mentioned previously, fuel cells have favourable efficiencies of 40% to 80% (1). By capturing the heat generated in the reductive and oxidative processes and using it as energy (a process called cogeneration), fuel cell efficiencies can be at least double those of internal combustion engines. Because fuel cells’ operating times depend on the amount of fuel they have

and not on the capacity of the fuel cell itself, these devices are more similar to generators than to batteries, which entails a greater life expectancy. Their generator-like qualities make these devices great for residential, commercial and industrial large-scale usage. Small-scale usage is also possible: some fuel cells can be adapted to a portable size, for usage on cars, airplanes, boats and other vehicles. Proton Exchange Membrane fuel cells (PEMFCs) are often used in vehicles such as cars.

the technology required for the synthesis and distribution of hydrogen, as well as its conversion to a more sustainable energy. There is also the possibility that increasing the use of hydrogen as a fuel could have a severe impact on the environment. The increase in water vapour in the stratosphere could lead to an increase in the destruction of ozone molecules via heterogeneous chemistry, thus weakening the ozone layer around Earth.

It is undeniable that fuel cells are a good alternative to fossil fuel combustion, and that many of the problems that are associated with these devices can be ameliorated through the development of this technology. But what do we do with the fact that increasing the amount of water vapour in our atmosphere could affect our environment? If even a clean, sustainable energy such as hydrogen fuel can topple nature’s structure, doesn’t that indicate that perhaps the human race has reached the limit of the race to better technologies? That despite our best attempts, no technology can both meet the requirements imposed by our society and protect our planet Earth? Are we simply asking for too much?

What are the limitations?

There are several problems associated with fuel cells. The first and foremost is that hydrogen is not an energy source but an energy carrier. It is not naturally found in a useful form, rather, it needs to be transformed or synthesized. No energy can be produced without an initial energy cost, and even then only about half the amount of energy originally put into the system can be used. The other half is used up as heat (2). Another problem associated with fuel cells is storage. Storing hydrogen is very difficult, due to its highly flammable nature. It is also inefficient. It can only be stored in either liquid or gas form, and in these forms the hydrogen’s energy density is only about a sixth of that of gasoline (3). Moreover, transitioning from our fossil fuel based economy to a hydrogen economy would not only take time but also a substantial amount of money. Millions or even billions of dollars would be necessary to develop

Literature Cited (1) Fuel Cell Today, Johnson Matthey “SOFC”. Web. 11 May 2014 http://www.fuelcelltoday.com/technologies/sofc 2) Duncan Clark, What’s the ‘hydrogen economy’?, The Guardian 11th October 2012, Grantham Institute and Imperial College London (3) Puru Jena, Materials for hydrogen storage: past, present, and future, The Journal of Physical Chemistry Letters 2011, 2, 206-211

Swattie Feature

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My chemical ecology research over the summer at Cornell University investigated how plants defend themselves against a variety of different herbivores, using goldenrod (Solidago altissima) as a model system. Insects use proteases to digest proteins and obtain amino acids. Plants fight back with herbivore-induced protease inhibitors that inhibit insect proteases, which results in stunted herbivore growth. We wondered if induction was species-specific or perhaps based on feeding guild. Instead, the data indicates that protease inhibitors are induced by herbivore suites, which are groups of herbivores that induce a similar response from plants with disregard to feeding guild or taxonomy. Suites contain extraordinarily different insects and it’s unclear what causes them to induce similar plant responses. Additional findings indicate that herbivores prefer plants previously damaged by a different suite since the plants defense response is already targeted towards the previous suite. Research funded by the S. Theodore Lande fund.

David Tian ‘17

David presenting in this year’s Sigma Xi poster session.

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More than Skin Deep : Hansen’s Disease in China

By Helen Wang In June 2014, I stumbled off of a motorcycle and arrived in the village of Gaoming, a leprosy or Hansen’s disease (HD) recovery village in Canton, China. The one-night stay was supposed to give me a glimpse into the living conditions of the other 600 similar villages in China, a handful of which I would be visiting during my 7-week volunteering internship with the NGO Joy in Action (JIA).

Immediately, I was struck by the physical beauty of the broad-leafed vegetation next to the high mountains and glistening lakes. The scorching sun made the temperature a whopping 95 degrees. One village grandpa offered to take us around the fishpond and harvested some fresh lychee for us to eat. When we said we were from America, he smiled enormously and communicated something enthusiastically in Cantonese. From a translator, I learned that he said, “You came all the way from the other side of the world to see us. We are so grateful.”

What is Leprosy or Hansen’s Disease?

Hansen’s disease (HD) or leprosy is a bacterial illness caused by Mycobacterium leprae. The bacillus multiplies at such a slow rate that symptoms may fully manifest as long as twenty years after initial contraction. Patients suffer from deformed skin, impairment of peripheral nerves, infection of mucosa of the respiratory tract, and drooping eyes or blindness. Many have their fingers, hands, legs, and/or arms amputated to avoid further injury and infection. In the 1960s, the multidrug therapy (MDT) cure for HD was discovered to cure early stages of HD and prevent future cases. Nonetheless, patients who contracted the disease before the treatment suffer lifelong deformities.

Many fall victim to depression and commit suicide.

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Hansen’s Disease through History to the Modern Age As Professor Angela Ki-che Leung of Columia University describes in her book Leprosy in China: A History, HD was the only chronic disease for which isolation was used to prevent infection in imperial China. Social stigma against HD patients in China dates as far back as the Ming-Qing dynasty transition, during which the disease began to be associated with the poverty and disgraceful family blood of “inferior” minority groups of the south, especially in the province of Canton. In severe cases of the disease, patients were burned in their homes along with their possessions. For other patients, disgust from family members fueled the formation of remote HD villages. In their new home, the

recovering HD villagers were given a measly plot of land and told to farm for a living, which only exacerbated their health problems.

Even after the discovery of the MDT treatment in 1960, unnecessary isolation of the HD patients and widespread social stigma against them continues. While familial reverence remains a pillar of Chinese culture, family members refuse to visit the HD villagers with the exception of settling debts.

Sellers in the marketplace may refuse to sell to the villagers, or spit on them and call them “ma feng lao,” a derogatory term meaning “old leper.” Even among the educated class, there is fear of venturing too close to these villagers for risk of contagion. The solitary life of the HD villagers is physically, emotionally, and psychologically difficult. It seems that even with all the advances of Chinese modernization and villagers being completely healed today, the mindset toward these Hansen’s disease villagers remains ancient.

through unimaginable hardships, organizations like JIA strive to preserve their stories for future generations. Through treating these villagers with respect and love, we learn that the science of healing is much more than medical.

It is my last day of volunteer camp in Jianyu.

I find Mao Jie, one of the village grandmas, sitting in her usual spot on the wooden stool outside her house.

At this hour right before noon, I usually come to play “Hey Soul Sister” for her on the ukulele. Although we cannot communicate verbally because she speaks solely Cantonese and I speak Mandarin and English, my dancing and singing always make her laugh. But today, the ukulele is already packed in the van. For the first time, I squat down next to her with a translator. She asks me how much money my plane ticket was, how many siblings I have, and when I am going back home. After a short pause, she smiles and says that she will miss our conversations. Tears well up in my eyes, but she tells me not to cry because it makes her upset. After a few deep breaths, I ask whether she wants to hear one more song, a traditional Cantonese song that I memorized word by word a couple weeks ago. She nods and holds my hand as she hums along.

Relief Efforts Without family or government officials to advocate for these villagers, much of the relief effort in China has begun only in the past two decades by nonprofit organizations like JIA, founded by Ryotaro Harada. JIA organizes its efforts through “volunteer camps” in which workers, mostly college students, live alongside the villagers for weeks at a time. The primary task is to improve living conditions by constructing toilets, houses, and irrigation systems. They also ensure that villagers are receiving routine doctor checkups and are not being cheated into purchasing counterfeit medicine. As a product of these efforts, the standard of living has significantly improved in the recent past.

The more important role that JIA plays is psychosocial intervention to foster “mental healing.”

Simple gestures are used to eliminate the barrier between villager and camper. Volunteers eat meals with the villagers, share stories, play games, and put on shows together to foster a spirit of family. At the camps, I always felt as if I were taking care of my own grandparents. Regular volunteer camps have helped villagers regain the confidence to go to the marketplace, trust in outsiders, and recognize their own inner strength. In the same way that cancer patients are known to survive longer with positive support, we hope that these villagers will be able to live happier lives knowing that they are not disabled but rather “differently abled” by their past.

Future Goals The tale of leprosy has shown us how cultural factors and government interference can profoundly extend the consequences of a disease. Although the WHO recognized eradication of leprosy in China in 1982, political commitment is necessary to rapidly improve living conditions and reverse the social stigma against HD. Recognizing these HD villagers as survivors who have prevailed 20

Forget results, I want to hear about failure: How publication pressure is affecting research and why we need to recognize the importance of discussing negative results and experimental mistakes.

W

hen was the last time you read a paper in which the results did not support the hypothesis? When have you ever seen a paper title saying ‘X has no effect on Y’, or a methods section in a published piece which contained an experimental error section? Have you heard of the Journal of Negative Results in Biomedicine, or the to-be-launched Journal of Errology? No? Few people have, but both journals exist to publish the negative-result papers and experimental method failures that high-impact journals won’t (1, 2).

Any scientist will tell you that a result, whether negative or positive, adds to the body of knowledge so long as the experimentation leading to that result is sound. Information can come in the form of discovering that a proposed effect does not occur (a negative result, also called null result) or that a method does not work (failure). Negative results and experimental failures expand our knowledge and allow ourselves and others to avoid time- and resourceconsuming dead ends. When we first learn about the scientific method, we are taught that positive

and negative results are equally important. Increasingly, however, that theory is not reflected in scientific and publishing practice.

In one study that analyzed more than 4,600 papers in a variety of fields between 1990 and 2007, the frequency of positive-result papers has increased by over 22% (3, 4). The increase in positive-result papers was most pronounced in social and some biomedical fields. Writes Mahboob Imtiyaz, creator of the Journal of Errology: ‘There is absolutely no point in approaching high impact closed or open access journals [with a negativeresult paper] since they outright reject papers with negative results on the grounds that they won’t get the amount of citations necessary to maintain their high impact factors or because they are not interesting enough for their readers.’(3) Many researchers point specifically to the growing competition for grants and academic positions as the cause of this trend (5, 6). A scientist’s career is increasingly being measured by ‘bibliometric parameters’—how much he or she publishes, and in what journals (5). No publications results in no funding or promotion. This in turn encourages researchers to produce papers written for high-impact journals that are cur-

& failure The

success

The

rently more likely to publish a paper demonstrating a positive result than a negative one. Discussing this trend towards suppressing negative results is not just an exercise in publication ethics: it affects the way new researchers like us and our peers design experiments and ask questions, and it influences what we think is worth knowing. It affects science pedagogy, since an integral part of science education is reading primary literature, which teaches us what “real” research looks like. Valuing positive results over negative ones teaches us to strive for only one type of result and ignore the other, shaping how we conceive of experiments and what we decide to discuss, whether in class or on paper.

It sounds reasonable that positive results are more productive than negative ones, especially in the realm of biomedicine. Reading of a new working treatment for HIV/ AIDS or cancer would be infinitely more relieving and enjoyable than reading that a current treatment has been ruled ineffective. Finding new working solutions seems progressive, while proving a method does not produce the desired effect appears to return research back to square one. But this positive resultfavoring mindset does not allow us to recognize that knowing what does not work is also progress.

In truth, experiments may be elegant, but they are rarely clean. There are perplexing data; unsuccessful methods; rejected hypotheses; and, in the case of one Drosophila fly lab, data which literally flew out the window. Admittances of error almost never make it into the methods section of a paper.

Recently, however, the Twitter hashtag #overlyhonestmethods has become the popular version of a lab report’s experimental error section.

By Maddy Booth

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It is a forum for scientists in all fields to confess anonymously to less-than-perfect aspects of their work in the lab and field. Most of the stories are refreshingly candid, reminding scientists at all stages that experimentation is not the graceful or sanitized image we see in publication, but rather is full of crossed fingers, caffeine, bewildered stares, and financial difficulties.

Underlying the 140-character-max stories is a larger problem—we as students, researchers, and scientists, are not discussing experimental problems and negative results openly enough. The hashtag should be #honestmethods, not #overlyhonestmethods, and copies in Cornell Library of The Journal of Biochemistry should be accompanied by The Journal of Negative Results in Biochemistry. Failed experiments and negative results are witness to the never-ending struggle that is research.

Hiding them at best feeds into the illusion of spotless experimentation and progression, and at worst leads to papers that should have been published not being so and papers which should not have been published—false positive results—finding their way even into Nature (4, 7-9).

It seems like it is time we stopped thinking about reporting negative results and method failure as a confession, as being overly honest, and started thinking about it as being good science.

Will the Ebola Outbreak Become an Epidemic?

Literature Cited: 1. Marcus A, Oransky I. 2014. Retraction Watch: Your experiment didn't work out? The Journal of Errology wants to hear from you. http://retractionwatch.com/2012/01/17/yourexperiment-didnt-work-out-the-journal-of-errologywants-to-hear-from-you/ 2. 2014, posting date. Journal of Negative Results in BioMedicine. http://www.jnrbm.com 3. Imtiyaz M. 2014. The Conundrum of Publishing Papers with Negative Results. In Nature (ed.), SpotOn: science policy, outreach, and tools online. Nature. http:// www.nature.com/spoton/2012/10/the-conundrumofpublishing-paper-with-negative-results/ 4. Fanelli D. 2012. Negative results are disappearing from most disciplines and countries. Scientometrics 90:891-904.

5. Fanelli D. 2010. Do Pressures to Publish Increase Scientists' Bias? An Empirical Support from US States Data. Plos One 5:7.

6. Anderson MS, Ronning EA, De Vries R, Martinson BC. 2007.

The perverse effects of competition on scientists' work and relationships. Science and Engineering Ethics 13:437461.

7. Conrad S, Renninger M, Hennenlotter J, Wiesner T, Just L, Bonin M, Aicher W, Bühring H-J, Mattheus U, Mack A, Wagner H-J, Minger S, Matzkies M, Reppel M, Hescheler J, Sievert K-D, Stenzl A, Skutella T 2014-07-30 2014, posting date. Retraction: Generation of pluripotent stem cells from adult human testis. Nature Publishing Group. http://www.nature.com/nature/journal/vaop/ncurrent/ full/nature13661.html 8. Marcus A, Oransky I. 2014. Crack Down on Scientific Fraudsters.

The New York Times. http:// www.nytimes.com/2014/07/11/opinion/crack-down-onscientific-fraudsters.html?_r=0 9. Marcus A, Oransky I 2014, posting date. Retraction Watch. http://retractionwatch.com

A Look Into Epidemiology Models a n a h eg M y B an h t a n a g n Ra 22

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# of people infected

he recent outbreak of Ebola gained a lot of media attention as it spread through West Africa, with some cases appearing in other countries around the world. Many news articles appeared with the question: will this spread enough to become a pandemic? Panic ensued, especially because there is no known vaccine for Ebola and the symptoms that arise from the disease are something out of a horror movie. When diseases start to spread unusually or appear more threatening than usual, mathematicians and statisticians have to figure out what the probability is that the disease will become an epidemic, and this is most often done using mathematical models. If we can model the spread of the disease, using certain parameters specific to the pathogen, we can get a sense of how many people could be infected and how we should respond to the threat.

The most common model for diseases is known as the SIR model. which stands for “Susceptible Infected Resistant.” In this model, people in the population are either susceptible to the disease (meaning they have not contracted it yet), infected with the disease, or they have been infected and recovered and are now resistant to the disease. We can plot the spread of the disease as a function of the number of people in the population, the transition rate, and the number of people with the disease at a certain time t, and we get a curve that looks like Figure 1:

Time

Figure 1: Logistic growth curve. Adapted from http://commons.wikimedia.org/wiki/ File:Logistic.png.

This curve is known as a logistic growth curve. As this graph shows, the disease starts out slow, infecting only a few people. As more people get it, they pass on the disease to more people, and the disease spreads faster. Then, it hits a time when so many people are infected and now resistant that the spread slows down and eventually stops.

This could be a useful model, but, as far as we know, Ebola is not one of the diseases where people who get it once are necessarily completely resistant. So then, how should we change the model? We can use the SIS (Susceptible Infected Susceptible) model; people can recover from the disease but once they have recovered, they are then susceptible to the disease again.

Say that people are recovering at some rate a, and the transmission rate is t. If a > t (meaning people are recovering faster than the disease transmits) then the disease won’t spread. If a < t, then people recover slower than the disease can pass from person to person. If the contact rate (the rate of infected people contacting not infected people) is c, then with some math we can figure out that the disease will spread if the expression c*t-a is positive, and if c*t-a is negative, the disease won’t spread. We call that expression c*t-a “R0,”

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these models they looked at what would happen if it took medical interventions (including medical treatments, hospitalizations, and quarantines) into account. They found that the R0 value dropped significantly (to 0.4 and 0.3, meaning the disease would not spread because R0 < 1). They also found that the time it took for these interventions to happen was one of the determining factors in how big the epidemic would be (as well as decreasing the rate of transmission after death; there have been cases where people have contracted the virus while burying victims of the disease). Models are never perfect; for example, this particular one did not take into account animal to human transmissions. However, even simplifications can tell us a lot.

Epidemiology, the study of disease spread, is only one example of the numerous fields that benefits from mathematical models. Understanding how a disease spreads can let organizations such as the Center for Disease Control determine the level of alert to put out, how many vaccines to administer, and how much effort and concern they should dedicate to a particular outbreak over another. Grasping epidemiological models on an individual level can prevent undue panic about disease that are unlikely to spread or allow people to shift panic to the most threatening diseases.

also known as the basic reproduction number. R0 represents the number of susceptible people infected from a single infected person. If R0 < 1 the disease does not spread, and if R0 > 1, the disease spreads, which makes logical sense because if a single person can infect more than one person, the disease will spread. If a single person cannot infect one person, than the disease will slowly decline.

We have calculated the R0’s (basic reproduction numbers) of certain common diseases; for example, the R0 of measles is 15 and the R0 of the flu is 3. We can tell from the R0 value that both diseases spread easily, but measles way more than the flu.

The R0 for Ebola is hard to say for sure, because R0 is calculated using data from past cases. However, as of 2004, there have only been a few big Ebola outbreaks, including one in Congo in 1995 and one in Uganda in 2000. From these two cases, a group of researchers determined that the R0 is about 1.83 for the Congo outbreak and 1.34 for the Uganda outbreak (Chowell et al. 2004). Another group of researchers found the R0 value to be around 2.7 instead (Legrand et al. 2006). This does not necessarily mean that this will also be the R0 value for the most recent outbreak because there isn’t enough data to be as accurate as possible, but it does suggest that while the Ebola virus does spread, it does not spread as well as diseases we interact with a lot, like the flu.

Why might Ebola have a (comparatively) low R0 value? One reason could be the low transmission rate; Ebola requires direct contact with bodily fluids of an animal or another human, which occurs far less than contact with airborne viruses. Ebola patients are also contagious for a relatively short amount of time before showing symptoms, so if Ebola is correctly identified quickly (and that is a big “if” because Ebola is notorious for being misdiagnosed), patients may not be able to spread the disease to many people. Finally, Ebola tends to kill its host (or show bad enough symptoms that an infected person is hospitalized and under quarantine) fairly quickly, making it harder for an infected person to transmit the disease to many people.

Now, this is not to say that the possibility of an Ebola epidemic is zero, because this last spread was the biggest Ebola outbreak and it spread farther than is usual. However, there is some good news to come of mathematical models. Some researchers (Legrand et al. 2007) looked into modeling an Ebola outbreak, and in

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Understanding how a disease spreads can let organizations such as the Center for Disease Control determine the level of alert to put out, how many vaccines to administer, and how much effort and concern they should dedicate to a particular outbreak over another.

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Literature Cited: Astacio, J., et al, Mathematical Models to Study the Outbreaks of Ebola, 1996 Chowell, et al., The basic reproductive number of Ebola andthe effects of public health measures: the cases of Congo and Uganda, Journal of Theoretical Biology, 2004 Coursera Course, Model Thinking Jones, James H., Notes on R0, Stanford University, May 2007 Legrand, J., et al, Understanding the dynamics of Ebola epidemics, Epidemiol Infect. May 2007; 135(4): 610–621.

MedTV, Ebola Incubation Period, http://ebola.emedtv.com/ ebola/ebola-incubation-period.html World Health Organization, Ebola virus disease, http:// www.who.int/mediacentre/factsheets/fs103/en/ Yarus, Z., A Mathematical look at the Ebola Virus, May 2012, http://home2.fvcc.edu/~dhicketh/DiffEqns/ Spring2012Projects/Zach%20Yarus%20-Final%20Project/ Final%20Diffy%20Q%20project.pdf

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by Samer Nashed

Rise of the Machines As popular as it is, few pop-science notions or fad fears step so far outside the realm of possibility as the ‘Rise of the Machines’. Ask a roboticist about your favorite machine-dominated, apocalyptic scenario, and they’ll likely respond “If only we were so lucky!” While robots and computers excel at planning, and engineers build faster, lighter, more physically capable devices every year, human abilities in areas like learning, and sensing and perception of the environment, still dwarf those of robots.

Sensing and Vision For a robot to do anything – useful, harmful, or otherwise – it must have an idea of where it is in the world. The process of determining relative location is called localization. Humans are incredible localizers. Combining our five senses, we can navigate novel, dynamic environments with relative ease. Walking down a crowded city street, we see, hear, and feel people moving in all directions and synthesize all our sensory data to create a map of our surroundings. Next, we project how the position of all objects in our world will change relative to us in the next instant, and plan a path so as to both avoid contact with other pedestrians, buildings, fire hydrants, etc. as well as navigate towards our destination. What our brains and nervous systems lack in speed, compared to modern computers, we more than make up for with our accurate, robust, and highly integrated sensory system.

Building a comparable sensory system out of non-biological elements is challenging. Imagine your average doomsday cyborg; at the very least it has cameras to see its surroundings, a wireless network for 25

From http://upload.wikimedia.org/wikipedia/en/4/44/Terminator1001.jpg

Figure 1: Robot soldiers? Not so fast.

Decades of work still exist for those looking to recreate Terminator-like machines. communicating to other robots, and a device to sense acceleration or inertia, similar to the cochlear fluid in our inner ears.

The problem for roboticists is to integrate all of the data from these sensors in real time. Image data for instance, is represented by pixels, where each pixel has red, green, and blue values. Some more advanced cameras, like those used in the Xbox Kinect, also report a distance value determined via laser. Even if the camera only has the resolution of an iPhone, this representation will still produce millions of values every frame. Common motion tracking techniques, such as optical flow, pick out features like corners and edges and track them from frame to frame to estimate the motion of the robot relative to its surroundings. These techniques are computationally intense since each pixel and its neighbors must be analyzed every frame, and effective navigation requires tens of frames per second. Not to mention, these sensors often have noise and error, and become less accurate over time.

Human brains track features and correct for error automatically, and not only that,

Figure 2: Maps like this are made using reflected laser light instead of camera images. Often, these maps are combined with information from camera systems for a more complete picture.

From http://2.bp.blogspot.com/_E_PQqc3YTtA/SwQmX3sE96I/AAAAAAAAAJ0/i7HtGx1So_8/s1600/3dmapping_robot.jpg

but they integrate all senses seamlessly, without any conscious effort. Object identification and mapmaking are still frustratingly difficult tasks for robots.

very long time, and 2) the training only applies to that specific environment. If placed in a novel environment, the robot must retrain. Some current work focuses on life-long learning algorithms, which try to learn about multiple environments and maximize the shared knowledge between them.

Lifelong Learning Humans are also excellent learners, with unparalleled pattern identification skills. We combine intuition, common sense, and life experience to learn and propose abstract rules about our environment. We can extrapolate information from very limited sensory data because of our large, highly adaptable knowledge base. Consider a caveman tracking and hunting an animal; a fairly primitive behavior and certainly one we expect a robot soldier to be capable of. Humans learn how to tell if tracks are fresh or old, which types of animals leave which tracks, where their prey likes to go during different parts of the day, and what its physical strengths and weaknesses are. This knowledge is developed over many years â&#x20AC;&#x201C; we are lifelong learners â&#x20AC;&#x201C; and every time the caveman tracks, he slightly modifies his theory of how to best track and hunt by adding information from his newest experience.

Where are we now?

Some of the work Iâ&#x20AC;&#x2122;m involved in right now, at the University of Pennsylvania GRASP Laboratory, focuses on developing devices and algorithms which will allow a quadrotor to perch on a branch or cling to a vertical planar surface using only one camera and an inertial measurement unit to identify where its targets are and calculate a trajectory to the target. These tasks are natural to birds and insects, yet they push our current sensors, algorithms, and robotics platforms to the limit. Other projects, like BigDog from Boston Dynamics (recently acquired by Google), champion our engineering abilities and possess autonomous decision making as one would expect in a soldier, but cannot learn generally about their world. In general, we can

Artificial intelligence has had instances of success, such as Deep Blue, the chess playing computer, or Watson, the Jeopardy champion. However, these computers were already given all the knowledge they needed and simply organized and applied it appropriately. For a robot soldier to survive in more than one or two scenarios, it would have to create knowledge itself based on physical data from its sensors. A common motivation for machine learning systems is the search and rescue problem, where a robot in an unknown environment searches for a particular target at an unknown location. One learning technique, called reinforcement learning, begins with a training session wherein the robot wanders around randomly and measures how good or bad a certain sequence of moves is. After the robot has done thousands of these training missions, it develops enough knowledge about its world to complete the task. The two major drawbacks are that 1) training takes a

From http://www.dvice.com/sites/dvice/files/big-dog.jpg

Figure 3: BigDog uses a variety of sensors and path planning algorithms to navigate difficult terrain while carrying hundreds of pounds of gear. develop robots that excel in many specific tasks, often times beating humans, but designing systems which learn more generally and have robust and adaptable perception abilities is a task whose end is far, far in the future.

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By Justin Sui

A

ll my life, teachers have told me that there are no silly questions. Although I have heard some interesting queries, I whole-heartedly believe in this dogma. Curiosity is integral to our growth as humans.

Experiencing the natural world around us, we ask questions and strive to find answers, leading to innovation and discovery. Yet how can we be sure our answers accurately represent the natural world and actually address the questions at hand? Moreover, how do we even begin to interrogate observable natural phenomena? Today, we have focused our curiosity with the scientific method, the step by step process that all scientific investigations follow:    

body of knowledge unless placed within a broader context. Furthermore, biologists face the challenge of validating why an organism or set of organisms are worth studying among the menagerie that exist. Given these standards for biological inquiry, developing initial questions can be a tricky process. Overall, there are two main approaches biologists take to formulate these questions. First: inquiry derived from specific organisms, or an organism-oriented approach. Here, biologists base questions off of observations of organisms, asking in such a way that incorporates further reaching implications. The second: interrogation of fundamental questions by way of model organisms, a principle-oriented approach.

Biologists would ask fundamental questions and then choose a suitable system that can be used to explore these questions.

Make observations of phenomena and formulate initial questions.

Hypothesize –answer these questions with current knowledge available.

Experimentally test these hypotheses as specifically and controlled as possible.

Determine if results support the hypothesis, and if not, formulate new hypotheses to test.

To best demonstrate an organismoriented approach, let us use a hypothetical “real world” example. We take a stroll in the Crum woods and stumble upon a caterpillar inching along a leaf using its feet. A gust of wind blows, rustling the tree leaves, yet the caterpillar remains firmly attached. Amazed by this, we generate questions by taking the caterpillar into the lab to examine the animal more closely. Our observations yield a multitude of questions, but one in particular lingers: do caterpillars with large feet, relative to body size, stick more tenaciously than those with small feet? This is an interesting question by itself, but could be developed further. Suppose we carry out a project addressing this question, and our data suggest that big feet are stickier. Well…so what? The original question inevitably leads us to a sort of data-collection for data’s sake –we could answer the question, but

While the scientific method appears straightforward on paper, when put into practice, science can feel like more of an art. Levels of creativity, skill, and training are essential to all steps of the scientific method, but none more so than during the first, question-generating step. There are no silly questions, but scientists are taught to ask the right questions – ones that are experimentally viable and, most importantly, draw broad implications. However, among the natural science divisions, these carefully crafted initial questions are especially vital in biology. Inquiries within biology can appear far removed from being directly applicable to humans or important for our growing 27

the importance of our findings would not be obvious. Let us expand our original question: what does caterpillar foot morphology imply about the ability of different species of caterpillar to cling to substrates? Placed into a larger context, our question becomes more robust. Studying multiple species of caterpillar allows us to make comparisons, much more powerful for drawing conclusions about the significance of morphological traits than if we studied a single species. We still get at the question we originally posed, but broad implications are now inherent in our improved question, relating how the form of an organism influences its function. However, in the case that examining multiple species does not quite pique our interest, a potential project may examine the effect of the environment (temperature, humidity, etc.) on the stickiness of these caterpillars’ feet. We could also ask questions about trade-offs between mobility and adherence. Expanding our original question not only addresses our initial puzzlement over the caterpillar in the Crum, but most importantly is a way to further enrich our inquiry by framing the question within larger biological contexts.

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the caterpillars are easily collected, abundant, and maintainable in laboratory conditions. In order to address the bigger question at hand, we need to ask more specific ones.

Fundamental questions are so broad that they are unanswerable in single experiments and require case-by-case instances of exploration. We could ask about the caterpillar’s foot morphology, and interestingly, our question becomes similar (or identical) to the one we generated through the organismoriented approach. The organism- and principleoriented approaches can converge onto the same questions, the main difference being the initial motivation behind the inquiry. What is important is that the question we ask incorporates broad implications, whether we begin or expand to this point.

Science is an endless chain of inquiry and pursuit of answers. By asking richer questions, the results will be ever more interesting and illuminating.

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Science is an endless chain of inquiry and pursuit of answers. By asking richer questions, the results will be ever more interesting and illuminating. In both the organism- and principle oriented approaches, biologists must also consult literature in order to learn about particular organisms and discern which questions have been answered and which remain. Our caterpillar example is a simplified model for demonstrating the organism—and principle—oriented approaches because usage of the literature is absolutely crucial throughout the process. Drawing from the literature is a way to gain insight into our current understanding of fundamental questions—science does not exist within a vacuum. The bar is set high: projects must hold up critics challenging the research, who ask why the question at hand is important. Developing projects with links to fundamental questions is a way to inherently enhance the applicability and significance of the research. Scientists build on previous research by asking slightly different questions or can refute past results with their own data. These check -and-balances make science a dynamic community, one that builds on top of itself, retains validity, and feeds our endless curiosity.

Contrary to the organism-oriented approach, the main motivation of a principleoriented approach of the project is not to study a particular organism but to answer fundamental questions. Evolution is center to many questions in biology, but these questions may also explore, for example, cellular mechanisms such as mitosis; plasticity, which is the ability of certain organisms to change their behavior or shape as a response to changes in environmental conditions; or, very generally, how structure determines function. To answer these questions, biologists use model organisms, organisms which have been extensively studied due to certain features that make them easily experimentally manipulated, while still being representative of larger groups of organisms. If current model organisms are unsuitable for exploring particular biological principles, a biologist can establish a system suitable for exploring this question. Going back to our caterpillar example, let’s say a fundamental question we want to study is insect biomechanics, more specifically about insect foot adhesion to substrates. Based on our observations in the lab, we believe that the caterpillar in the Crum may be a good system to study this –

From http://etc.usf.edu/clipart/7300/7353/caterpillar_7353.htm

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