THURJ Vol. 1 Issue 2

Vo l u m e 1 I s s u e 2 | F a l l 2 0 0 8 | w w w . t h u r j . o r g

L e t t e r s

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Dear Harvard Community,

It gives me great pleasure to introduce the second issue of The Harvard Undergraduate Research Journal (THURJ). More so than at any other institution in the world, Harvard undergraduates are deeply embedded in the transformative, cutting-edge research of our faculty. Our students work

arts education—an education that invites our students to tackle major societal challenges, from global health and lifelong learning to energy and the environment. Simply put, student research is at the heart

this important work.

collaborations in important new areas—from stem cell science to biologically-inspired engineering and more. We should not forget, however, that this call to cross the boundaries of disciplines and to collaborate broadly has been at the heart of Harvard’s approach to the sciences for more than a

to see all these branches of science prosecuted with vigor, and moving forward in perfect harmony at Cambridge.” We have made great progress in achieving this harmony. We are now connecting faculty

discovery at an unprecedented level.

These collaborations are underpinned by fundamental values that are essential to our success as a learning community. They include a willingness to adapt, an inclination toward creativity, a love of fresh ideas, an openness to connect with others, and a strong desire to share knowledge and our

and I am grateful to you for creating a space that celebrates the creativity of student researchers and recognizes the collective good resulting from undergraduate research.

Sincerely,

Michael D. Smith Dean of the Faculty of Arts and Sciences John H. Finley, Jr. Professor of Engineering and Applied Sciences

OFFICE OF THE DEAN OF THE FACULTY OF ARTS AND SCIENCES

L e t t e r s

T h e H a r v a r d U n d e r g r a d u a t e R e s e a r c h J o u r n a l ii

Dear Harvard Community,

(THURJ), a biannual publication that showcases the outstanding research conducted by Harvard

to include the social sciences as well. We believe this broadening of scope allows THURJ to better

important public policy implications.

In addition to presenting peer-reviewed research, this issue showcases feature articles by our staffers.

appreciated: Harvard Medical School (HMS) recently received a multimillion-dollar grant from the

Clinical and Translational Science Center (CTSC).

being performed everyday around campus. We owe thanks to the many people who made this issue possible, including our Peer Review Board staffers and the Harvard faculty and graduate students who peer-reviewed manuscript submissions. Likewise, THURJ’s Content, Business, Social & Public

Lastly, we thank all of the authors who submitted their manuscripts and who appear in these pages; it is their work that we take great pride in sharing with you.

Sincerely,

Shoshana Tell, Co-Editor-in-Chief John Zhou, Co-Editor-in-Chief

THE HARVARD UNDERGRADUATE RESEARCH JOURNAL


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FeaturesSophomore Noor Beckwith showcases nature photography from the island of Borneo

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Manuscript SummariesPreview the manuscripts before you read them in their entirety

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A new way of thinking about evolution: math in evolutionary dynamics

8

THURJ Co-Editor-in-Chief Shoshana Tell’s experience doing research among the Amish

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Eliot House tutor Lionel Lynch shares his wisdom about a career path less traveled

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The Encyclopedia of Life: a “Wikipedia” of species

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Radcliffe Dean Barbara Grosz and her experience as a woman in computer science

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Co n t e n t s

T h e H a r v a r d U n d e r g r a d u a t e R e s e a r c h J o u r n a l iv

Manuscripts

Targeting factor VIIa: in silico prediction of new potent antithrombotics

The automation of metrics useful in evaluating the regeneration of skeletal muscle

ECONOMICSENGINEERING

CHEMISTRY

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56

The impacts of stricter high school graduation requirements on youth crime

42

CELL BIOLOGYCharacterization of a novel small molecule inhibitor of the anaphase-promoting complex/cyclosome (APC/C)

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Characterization of epoxidized Carthamus tinctorius oil (ECTO) as a novel polyvinyl chloride plasticizer

CHEMISTRY38

sale decisions: evidence of a reverse disposition effect in unsophisticated investors

48

NEUROSCIENCEThe effects of sleep on emotional recognition64

Visit http://www.thurj.org for news, details about the organization, guidelines for submission, and other information on research at Harvard.


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Shawn AchorChristian Boutwell, Ph.D

Chen-Yu Chi, Ph.DTimothy Cook

Michael DouganNatalie FarnySteven Flavell

Mihaela Gadjeva, Ph.DJessica Glazer

Nate HathawayCaramai Kamei

Ethan KarpYevgeny Kats

Stanley LoTania Lupoli

Yakov Peter, Ph.DDavid RandAbbas Rizvi

Jihye SeoCharisios Tsiairis

Tamily Weissman, Ph.DJason Wood, Ph.D

Peter WrightZhizhong (Joel) Yao

EXECUTIVE BOARD

CO-EDITOR-IN-CHIEF

Shoshana Tell ’10 ([email protected])

CO-EDITOR-IN-CHIEF

John Zhou ’10 ([email protected])

BUSINESS MANAGER

Xin Pan ’10 ([email protected])

MANAGING EDITOR OF CONTENT

Aditi Balakrishna ’10 ([email protected])

MANAGING EDITOR OF PEER REVIEW AND SUBMISSIONS

Lisa Rotenstein ’11 ([email protected])

DESIGN CHAIR

Justine Chow ’10 ([email protected])

MANAGER OF SOCIAL AND PUBLIC RELATIONS

Matthew Young ’12 ([email protected])

FACULTY ADVISORY BOARD

ALÁN ASPURU-GUZIK, PH.DASSISTANT PROFESSOR OF CHEMISTRY AND CHEMICAL BIOLOGY

PAUL BAMBERG, PH.DSENIOR LECTURER ON MATHEMATICS

MICHAEL BRENNER, PH.DGLOVER PROFESSOR OF APPLIED MATHEMATICS AND APPLIED PHYSICS

MYRON ESSEX, D.V.M., PH.DMARY WOODARD LASKER PROFESSOR OF HEALTH SCIENCES IN THE FACULTY OF PUBLIC HEALTH

BRIAN FARRELL, PH.DPROFESSOR OF BIOLOGY

JEFFREY FLIER, M.D.DEAN, HARVARD MEDICAL SCHOOL, AND GEORGE C. REISMAN PROFESSOR OF MEDICINE

NICOLE FRANCIS, PH.DASSOCIATE PROFESSOR OF MOLECULAR AND CELLULAR BIOLOGY

STEVEN FREEDMAN, M.D., PH.DASSOCIATE DEAN FOR CLINICAL AND TRANSLATIONAL RESEARCH AND ASSOCIATE PROFESSOR OF MEDICINE

GUIDO GUIDOTTI, PH.DHIGGINS PROFESSOR OF BIOCHEMISTRY

DAVID HAIG, PH.DGEORGE PUTNAM PROFESSOR OF ORGANISMIC AND EVOLUTIONARY BIOLOGY

MARC HAUSER, PH.DPROFESSOR OF PSYCHOLOGY

DUDLEY HERSCHBACH, PH.DFRANK B. BAIRD JR. PROFESSOR OF SCIENCE

JOHN HUTCHINSON, PH.DABBOTT AND JAMES LAWRENCE PROFESSOR OF ENGINEERING AND GORDON MCKAY PROFESSOR OF APPLIED MECHANICS

DAVID JERUZALMI, PH.DASSOCIATE PROFESSOR OF MOLECULAR AND CELLULAR BIOLOGY

EFTHIMIOS KAXIRAS, PH.DGORDON MCKAY PROFESSOR OF APPLIED PHYSICS AND PROFESSOR OF PHYSICS

GEORGE LAUDER, PH.DPROFESSOR OF BIOLOGY AND ALEXANDER AGASSIZ PROFESSOR OF ZOOLOGY

RICHARD LOSICK, PH.DMARIA MOORS CABOT PROFESSOR OF BIOLOGY

L. MAHADEVAN, PH.DLOLA ENGLAND PROFESSOR OF APPLIED MATHEMATICS

DAVID MOONEY, PH.DASSOCIATE DEAN FOR APPLIED CHEMICAL/BIOLOGICAL SCIENCES AND ENGINEERING AND GORDON MCKAY PROFESSOR OF

BIOENGINEERING

HONGKUN PARK, PH.DPROFESSOR OF CHEMISTRY AND CHEMICAL BIOLOGY

STEVEN PINKER, PH.DJOHNSTONE FAMILY PROFESSOR OF PSYCHOLOGY

TOBIAS RITTER, PH.DASSISTANT PROFESSOR OF CHEMISTRY AND CHEMICAL BIOLOGY

EUGENE SHAKHNOVICH, PH.DPROFESSOR OF CHEMISTRY AND CHEMICAL BIOLOGY

IRWIN SHAPIRO, PH.DTIMKEN UNIVERSITY PROFESSOR

ZHIGANG SUO, PH.DALLEN E. AND MARILYN M. PUCKETT PROFESSOR OF MECHANICS AND MATERIALS

DAVID WEITZ, PH.DMALLINCKRODT PROFESSOR OF PHYSICS AND OF APPLIED PHYSICS

(POST) DOCTORAL ADVISORY BOARD

SPECIAL GUEST PHOTOGRAPHER: NOOR BECKWITH ’11

Cover photograph: Moths, mantises, and other insects litter a light trap, consisting of a piece of white cloth stretched in front of a light source, in Lambir Hills National Park, Malaysian Borneo.

Cover image and photo essay images on pages 6 and 7 provided by Noor Beckwith. Noor, who hails from Philadelphia, PA, is an undergraduate concentrating in Organismic and Evolutionary Biology. His academic interests include entomology, behavioral

he enjoys photography and playing the piano. After graduation, he plans to obtain an MD and/or PhD.

Co n t e n t s

T h e H a r v a r d U n d e r g r a d u a t e R e s e a r c h J o u r n a l vi

BUSINESS BOARD

Alec Pinero ’11

DESIGN BOARD

Yan Yan Mao ’10 Alec Piñero ’11 Helen Yang ’11

Hyeon Jin (Gordon) Bae ’12Eva Gillis-Buck ’12

Lisa Chen ’12 Francis Deng ’12

John Mei ’12Jessica Zeng ’12

CONTENT BOARD

Fernando Racimo ’11Sophie Wharton ’11Alissa D’Gama ’11Jessica Villegas ’11

SOCIAL AND PUBLIC RELATIONS BOARD

Grace Cho ’12

The Harvard Undergraduate Research Journal (THURJ) showcases peer-reviewed undergraduate student research from all science and quantitative social science disciplines. As a biannual publication, THURJ familiarizes students with the process of manuscript submission and evaluation. Moreover,

edge research that impacts our world today. At its core, THURJ allows students to gain insight into the peer review

are rigorously reviewed by the Peer Review Board (consisting of Harvard undergraduates), and the top manuscripts that they select are further reviewed by Harvard graduate students, post-doctoral fellows, and professors. This process not only stimulates faculty-student collaboration and provides students with valuable feedback on their research, but also promotes collaboration between the College and Harvard’s many graduate and professional schools. In addition to publishing original student research papers, THURJ is also an important medium for keeping the Harvard community updated on science research-related news and developments.

CONTACTPlease email: [email protected]

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WEBSITE

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Copyright 2008 The Harvard Undergraduate Research Journal. No material appearing in this publication may be reproduced without written

permission of the publisher, with the exception of the rights of photographs which may only be granted by the photographer. The opinions expressed in this magazine are those of the contributors and are not necessarily shared by the editors. All editorial rights are reserved.

About us

PEER REVIEW BOARD

John Liu ’11 - Head Copy EditorMeng Xiao He ’11 - Copy EditorCharlotte Seid ’10 - Copy Editor

Ayodele Osasona ’08

Kelly Fitzgerald ’10 Alterrell Mills ’10

Vanisha Yarbrough ’10Daniel Brenner ’11

Ana Garcia ’11Daniel Handlin ’11

Johnny Hu ’11Joe Pollard ’11

Abby Schiff ’11Ke Xu ’11

Thilini Ariyawansa ’12Eva Gillis-Buck ’12

Ioana Calcev ’12Jacob Cedarbaum ’12

Eric Chen ’12Lisa Chen ’12Sway Chen ’12Grace Cho ’12

Ben Dobkin ’12Francis Deng ’12Jen Jian Gong ’12Edward Kogan ’12David Levary ’12

Darius Li ’12Richard Li ’12Monica Liu ’12

Shravani Mikkilineni ’12Alex Palmer ’12

Briana Prager ’12Nicholas Tan ’12

Jacob Weatherly ’12Helen Yang ’12Chi Zhang ’12


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A major cause of heart disease and stroke in America is unregulated blood clotting. Current preventative measures mainly include the blood-thinning drugs Coumadin and Heparin. However, these drugs are relatively

effects. This study examines a known alternative treatment that

involved in the blood-clotting process, factor VIIa. One of the

is that, as opposed to current treatments, it does not inhibit external clotting due to cuts.

computer programs to determine which inhibitor bound most

The optimal structure was then

time through the use of resin, which also served as an indicator. HPLC was used to remove contaminants

from the solution, and the purity

using mass spectroscopy. An assay was conducted in vitro to

inhibitor in comparison to a control sample of untreated factor VIIa. This compound proved effective in inhibiting factor VIIa. The study shows promise for the development of a new, more effective anticoagulant.

T

TARGETING FACTOR VIIA: IN SILICO PREDICTION OF NEW POTENT ANTITHROMBOTICS

jmei

Typewritten Text

his article has been omitted from the online version of this issue. For the full issue please inquire at [email protected]

S umma r i e s

T h e H a r v a r d U n d e r g r a d u a t e R e s e a r c h J o u r n a l 2

One of the three most common plastics in the world is polyvinyl chloride (PVC), which is used for everything from construction to automobiles to medical equipment. However, health and environmental concerns have risen regarding one

but long-term exposure may have adverse effects on infants, human fertility, and aquatic life.

Carthamus tinctorius

PVC plastics using different concentrations of either DEHP or ECTO, and they compared the plastics’ mechanical properties. In the key characteristics of elasticity, toughness, and brittleness, plastics made with ECTO performed similarly to those made with

to 30% by weight, it presented a viable and likely safer alternative to DEHP.

If implemented on a large commercial scale, ECTO

In addition to reducing health concerns, it is a cost-effective, environmentally sustainable alternative

CHARACTERIZATION OF EPOXIDIZED CARTHAMUS TINCTORIUS OIL (ECTO) AS A NOVEL POLYVINYL CHLORIDE PLASTICIZER

against heat, thus reducing the need for separate

non-toxicity, this naturally-derived chemical holds great promise for industry and medical applications.

Muscular and skeletal diseases are an immense burden, not only

also on the nation as a whole. In this issue, the author develops a novel, semi-automated method for the evaluation of skeletal muscle regeneration, a crucial step in increasing the pace of diagnosis and study. Although computer programs have traditionally been used to evaluate regeneration,

user participation. This leads to

to-quantify errors due to subjective inputs. The author’s automated

analysis of traditional metrics such

but also integrates variables related to the overall patterning of the tissue. His method allows for rapid, large scale analysis of tissue

samples and correlates strongly with results from traditional evaluations. Additionally, the author shows that his technique of dynamic image analysis can predict ideal tissue regeneration conditions. Overall, semi-automated histological analysis will allow for the examination of large tissue samples while maintaining

THE AUTOMATION OF METRICS USEFUL IN EVALUATING THE REGENERATION OF SKELETAL MUSCLE

Picture courtesy of Wikipedia

PVC


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In recent decades, many states have implemented exit examinations and increased the number of

school. Whereas previous studies focused on dropout

standards, the author directly examined the correlation between these requirements and the crime rate among affected students. Using multiple regression models based on crime reports, incarceration rates, and self-reported crime, the author found that an increase in graduation requirements correlated with

old experienced an increase. Additionally, while both whites and blacks had a decline in arrest rates, blacks experienced a larger decrease than whites. Furthermore, the author noted that individuals who

disproportionately from these stricter requirements.

implementation of exit examinations and increased course graduation requirements.

THE IMPACTS OF STRICTER HIGH SCHOOL GRADUATION REQUIREMENTS ON YOUTH CRIME

by Justine Chow, THURJ Staff

S umma r i e s


Stock investors face the decision to buy, hold, and sell stocks everyday, and there have been numerous studies on the decision-making process that these investors follow. The disposition effect is the tendency of individuals to sell winning investments and hold losing stocks. Past studies have generally shown a negative relationship between investor sophistication and the disposition effect.

The author tested undergraduate students for the effect of the disposition effect in a simulated

AN EXPERIMENTAL TEST OF SELF-JUSTIFICATION IN STOCK SALE DECISIONS: EVIDENCE OF A REVERSE DISPOSITION EFFECT IN UNSOPHISTICATED INVESTORS

stock experiment. Participants were compensated based on the performance of their portfolio over nine market trading days. Males were more prone to the disposition effect than females. A surprising reverse disposition effect in which individuals hold on to winning stocks and sell losing stocks was found among less sophisticated traders. This reverse disposition effect seemed to decrease as people increased their investment skills. Based on this evidence, the author showed a new model between the people’s

investment knowledge and the likelihood of following the disposition effect. Contrary to past

effect seemed to increase as investors reach a medium level of knowledge but then decrease as investor sophistication grew. The author also suggested that a further direction for his research may be to further test the effects of the reverse disposition effect on unsophisticated investors as well as the role of self-image as a cause of these effects.



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Previous studies on sleep have focused on the cognitive effects of sleep and sleep deprivation. However, few have examined the role of sleep in the emotional functioning of the human brain. In this

sleep by showing how a daytime nap selectively alters individual sensitivity to facially expressed emotion. In this study, subjects were asked to evaluate a series of facial expressions, rating them according to the degree of emotion shown in each of four categories: fear, sadness, anger, and happiness. Participants performed the task twice. Half the subjects took a 90-minute nap between trials while the other half performed normal waking activities. The group that remained

THE EFFECTS OF SLEEP ON EMOTIONAL RECOGNITION

awake showed an increased perception of anger and fear in the second trial, while the nap group showed

emotions. The nap group showed increased sensitivity to happy faces, and those who achieved REM sleep during that nap also showed a decrease in perception

perception of sadness. Overall, this study suggests

day to negative emotional stimuli. However, sleep, and REM sleep in particular, can reverse this negative bias by restoring sensitivity to positive affects and decreasing sensitivity to negative emotions.

by Eva Gillis-Buck, THURJ Staff

Fe a t u r e s


I remember falling into rapture at the notion of “monkey cups” – Nepenthes pitcher plants hanging high in trees, laden with endosymbiotic ants – or at the thought of orangutans sleeping soundly in their arboreal nests. My earliest memories are pervaded by a love of biology, ecology, and the tropics.

As a member of the class of 2011, I am concentrating in Organismic and Evolutionary Biology, and I’m exploring species interactions with my own line of entomological research in the Pierce Lab. However, so far in my studies, there has been no better experience for me than attending the Harvard Summer School study abroad course, “The Biodiversity of Borneo.”

As I had never been outside of the United States before last summer, tales of tropical adventure and enlightenment rang bittersweet in my jealous ears. Professors Naomi Pierce, Noah Whiteman, and Andrew Berry all cited their early visits to the tropics as some of the most formative experiences in their biological careers, and they all strongly urged me to immerse myself in that unique biome as quickly as possible. Hearing of Harvard’s study abroad opportunity, I wished desperately to be able to follow their guidance and expand my horizons by attending, so I canceled my other plans and got on board.

It was worth it, and here is some of what I saw.

THE BIODIVERSITY OF BORNEOBY NOOR BECKWITH, SPECIAL GUEST PHOTOGRAPHER


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Scientists have been trying to decipher how life on Earth has changed over time for the past 150

evolution in his 1858 treatise, On the Origins of Species, a complete

many questions still linger: How can cooperation evolve by natural selection? How do new levels of complexity arise in biology? How did culture evolve in human beings?

At the forefront of the enterprise to solve these and many

the forefront of mathematical biology are Harvard Professor

(PED).From the top of a grey concrete building above a Mexican

restaurant in Harvard Square, the PED belies its true identity as

mathematicians, computer scientists and

the complexity behind a vast array of phenomena, ranging from the evolution of cancer and other diseases to the evolution of cooperation, culture and language.

But what are the fundamental tools they use to understand the mechanisms of evolution? Simple: math.

“Just as physics did in the 20th century, evolutionary biology is

himself with helping set this foundation in place.

Evolutionary

Dynamics

the quest for a mathematical

explanation of life

BY FERNANDO RACIMO, THURJ STAFF

by Helen Yang, THURJ Staff


Fe a t u r e s

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Learning to cooperate by playing games

Among the PED’s many endeavors is the study of cooperation (between people, animals, and now, even

computer programs) and its

constructs a completely new level of organization—from

societies—cooperation is

says. Since the 1970s, biologists have been using game theory to try to explain how cooperation arises among populations of organisms.

are to replicate and perpetuate themselves in the struggle for life. Dr. Robert Neugeboren, who teaches game theory at Harvard University, explains: “Game theory has provided simple tools to

involves two criminals who have been arrested and are being held in separate rooms. Each of them has two options: testify against

one gets 5 years in prison, while the second one gets to go free.

The natural outcome for a player in this game is to betray one’s partner. The consequence, however, is that both are worse off

The Prisoner’s Dilemma could be the key to understanding how cooperation may have evolved in a world of seemingly altruistic organisms like these fishes.


Fe a t u r e s


This type of interaction abounds in nature. The archetypal examples are the wrasse and the groupers, two

coral reefs. These organisms frequent the same marine areas and tend to form cooperative relationships due to repeated

have evolved a propensity to clean the grouper of ectoparasites in exchange for defense from predators.

such an interaction could easily be explained using an iterated version of the Prisoner’s Dilemma game. Both organisms pay a cost for cooperating with the other but the fact that there is a good chance they will meet again assures the stability of their

understanding how cooperation may have evolved in a world of

and reproduction is effectively enhanced through cooperation with others.

Punishment, reciprocity and retaliation

Iterated instances of the Prisoner’s Dilemma are now

based on a version of the repeated Prisoner’s Dilemma. His results provided new clues in understanding punishment and

punishment with a cost. As Rand explains, “costly punishment is doing something that’s bad for you in order to impose a cost on

person a lot more.

in contexts where there are no repeated interactions between

world, there is always some chance that you meet the same player

the idea of reliable interactions between reputable individuals. Nobody wants to form a partnership with a cheater. And if someone inside a partnership cheats, the other members will

included possibilities for retaliation and building of reputation.After conducting behavioral experiments and analyzing the

results, Rand and his collaborators came to the conclusion that

more players punish, the worse they do: punishment usually generates downward spirals of

punish more get lower payoffs and end up worse than those

show that the mighty hand of evolution tends to crush those who punish in cooperative

games, suggesting that societal punishment must have evolved

Not just about genes

The impact of evolution reaches further than simply genetics. As Dave Rand explains, “Evolution is anything

demonstrated that the regularization of verbs in English follows a simple mathematical behavior that can be modeled using

conditions under which language could have evolved in the distant past.

Mathematical biology is growing faster than ever, and

of the past few years, the possibilities for exploration and

launched a program called ROME (Research Opportunities in Mathematical Evolution) targeted towards undergraduate and graduate students who want to pursue their own research in mathematical biology and its applications.

attentively listening and encouraging others to listen too.

the regularization of verbs in English follows a simple mathematical behavior that can be modeled using evolutionary dynamics.


Fe a t u r e s

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BY JESSICA VILLEGAS, THURJ STAFF


A CONVERSATION WITH LIONEL LYNCH

Many science concentrators in college may believe that their career options are limited after graduation

to traditional research or medical tracks. Lionel L.

Lynch ’02 is a tutor in Eliot House and a student at Harvard Business School. Like many undergraduates, he

was interested in exploring several

concentrate in Social Studies while completing pre-med

off from school and worked for

Lynch sat down with THURJ to discuss his path after graduation

and provide students with a new and interdisciplinary perspective on science-

related careers.

Fe a t u r e s


THURJ: What career did you originally have in mind? Lionel Lynch: I initially wanted to be a doctor,

requirements—I realized that I was still interested in a lot of the stuff that I had been thinking about in Social Studies…Over time I realized that there were a lot of other things I wasn’t

really want to go to med school. And then that’s when I decided to start looking into jobs and stuff, and that’s when I looked into the health care info thing.

THURJ:consulting?

LL: I heard about it mostly from friends, I think, as a senior. Obviously I’d heard about consulting and banking and stuff like that. To be honest, I had never really considered it because I was sure that if not a doctor [I would be] an academic…A good

friend of mine, who was a year above [me], had just started

called Eastern Associates]. He had just graduated, and I was a senior and we started talking about what they did and it sounded really interesting.

THURJ: What exactly do you do at a life sciences consulting

LL: A lot of what you actually do in the health sciences—

opportunity assessments. We would essentially get a lot of feedback from physicians and insurance companies and other

out what their reaction would be if something would come to market.

[For example,] if there was a new drug for a neurological disorder, we could call up the neurologist that we had in the database and say, this company is thinking about developing this product, what do you think about it? What worries you about it? How would you probably use it? And a series of phone

You get to learn a lot about how physicians think, what they worry about in a new product. We would also talk to the

think the price would be too much, how they would like to cover it or not cover it.

And then we would bring all this information together into a

[physicians and insurance companies] would probably use it, by Justine Chow, THURJ Staff

“Over time I realized that there were a lot of other things I wasn’t ready to give up to become a doctor. So

okay, you’re going to take

you really want to go to med school.”


Fe a t u r e s

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and this is how the competition may respond, and this is how much revenue you can probably anticipate over the ‘x’ number of years.

THURJ: What about the job was particularly interesting or rewarding?

LL: It was really sort of interesting work because you were

thought…and [learn] to be able to speak with a physician intelligently about various things that he is concerned about.

so learning how to interpret that

to project revenues and come to understand sort of the industry [was interesting]. And we did that with a whole host of different types of products ranging from new drugs to new devices.

The types of clients that we worked for were really interesting—we were able to work for big multi-national pharmaceutical companies and also for startup companies that could have been just a couple of scientists who had discovered a new molecule that they thought was promising,

--

cal company] wanted a new drug to expand their portfolio of products.

We also worked for private equity companies or investment

company was good or not. We would actually help evaluate a potential target for them and tell them based on our analysis yes, it is potentially worth it, or no, it’s not worth the investment you are thinking about doing.

THURJ: So what are your plans after business school? LL: Well, I have actually taken quite a change in direction.

As I mentioned in the beginning, I was interested in a lot of things other than just medicine. So in my two and a half years

addition to healthcare. So I left the healthcare industry and went

and worked in urban development in New York and around the country, actually, advising cities and developers on how to redevelop neighborhoods, balancing public interests with private

things like that. So that is actually my long term goal, but to be honest, even

though I’m not going to be in the healthcare industry in the future, just the skills that I gained as a consultant were really helpful for me. And I would have never considered consulting if I hadn’t worked for a health care consulting

mindset of being a physician at that time…I was able to give myself the time to see if I was actually interested in other things.

THURJ: Do you have any advice for the students that are thinking about concentrating in the life sciences, being premed, and going off to medical school?

LL: I think the biggest piece of advice that I would give is to not think that you have to get it all done in the four years that you’re here.

I have several friends who didn’t make the mistake that I made and who decided that they would much rather pursue their various academic and personal interests here while they were here for the four years and still had time for a lot of electives and just took the time off afterwards and did a post-bac program and did their pre-meds then and have gone to all the top med schools as well. They don’t regret the fact that they took an extra year to get to med school because they had a lot fun here and a lot less stress, because they were able to prioritize what was more meaningful to them.

I think there are a lot of great reasons to go straight through if that’s what you want to do, but I think that giving yourself the freedom is best. If you are second guessing yourself, there are multiple ways of getting to med school and [try not to] be caught in the notion that there is only one way to get there and you have to do it that way.

THURJ: Thank you for your time.LL: No problem. It was really cool.

“I think there are a lot of great reasons to go straight through if that’s what you want to do, but I think that giving yourself the freedom is best. “

Fe a t u r e s


Amish medicine:The Clinic for Special Children

T hrough the window, tall stalks of corn, a tire swing, a hitching post for a horse and buggy, and an occasional deer populated the landscape. But inside, modern

laboratory of The Clinic for Special Children in rural Lancaster County, Pennsylvania.

shadowing physicians at The Clinic for Special Children, a non-

cares for Plain (Amish and Old Order Mennonite) children

with complex genetic disorders, many of which severely disrupt normal metabolic functioning.

The Clinic was constructed in 1989 in a barn-raising— a community gathering in which a group of Amish carpenters “raised” the building. The pastel blue building sits atop a hill on land donated from an Amish farmer named Jacob Stoltzfoos.

Plain community, including Maple Syrup Urine Disease (MSUD) and Glutaric Aciduria type 1 (GA1).

By approaching these genetic disorders with a highly personal perspective on science and medicine, the Clinic has built a


This account is based on my summer experiences as a research intern at The Clinic for Special Children in Lancaster County, Pennsylvania.

BY SHOSHANA TELL, THURJ CO-EDITOR-IN-CHIEF


Fe a t u r e s

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The Clinic for Special Children


place within the Plain community.

A brief history of the Plain communityThe Amish and Old Order Mennonites, both Swiss-German Anabaptist

(adult baptism) religious groups, settled in Pennsylvania beginning in the early 18th century seeking religious freedom.

But the number of founders for each population was small, in time resulting in a genetic founder effect—meaning that alleles present in the founders dramatically increased

However, some of the alleles that suddenly became highly prevalent were deleterious, resulting in a higher proportion of certain autosomal recessive disorders within the Plain population.

These Amish and Mennonite families, whose native language is Pennsylvania Dutch (a German dialect), refer to the “outbred” population as “the English.” Because very few “English” join the Plain community,

into the Plain populations. This results in a measure of inbreeding, which encourages the persistence of those deleterious alleles.

Though the two groups are similar theologically, their distinctive founder populations resulted in different characteristic genetic disorders for the Amish and Old Order Mennonite populations, respectively.

though these disorders occur with a higher

GA1 is a metabolic autosomal recessive genetic disorder... [that leaves the a!ected] child permanently neurologically damaged, unable to speak, eat, or walk for the rest of his/her life.


worldwide.

"e founders’ e!ectClinic co-founder and pediatrician Holmes Morton (Harvard Medical

disorders—glutaric aciduria type 1 (GA1)—as a researcher at Children’s Hospital of Philadelphia in 1988. At the time, there was very little medical literature on

labeled as cerebral palsy. GA1 is a metabolic autosomal recessive genetic disorder that leaves the body

Fe a t u r e s


unable to properly catabolize proteins into amino acids, causing glutaric acid (an intermediate in the degradation process), to

age of two, this sudden, excessive accumulation of glutaric acid can cause permanent basal ganglia injury. This leaves children permanently neurologically damaged, unable to speak, eat, or walk for the rest of their lives.

Caroline (Harvard Graduate School of Education ’76), 95% of his GA1 patients had been irreversibly neurologically damaged. Today, as a result of the special dietary formulations Dr. Morton has developed, only 25% of GA1 children experience this devastating neurological injury. After the age of two, GA1 children can resume a normal diet, however, as the risk of basal ganglia damage has subsided.

The importance of Dr. Morton’s work became strikingly

expanded newborn screening, is an extremely healthy, intelligent preteen girl. She plays several musical instruments, enjoys dance classes, eats a regular diet, and only visits Dr. Morton for annual check-ups.

Meanwhile, the second patient, an Amish woman in her thirties, is part of the Special Hearts Club, a group of physically and/or mentally disabled Amish adults who meet from Wednesdays through Fridays in the Clinic’s basement. The patient remains

me wonder how she may have turned out had the Clinic been around 30 years ago.

Clinic awards and expansionThe worldwide medical community has taken notice of the work the Clinic is doing, culminating in Dr. Morton’s

distinction as a 2006 MacArthur “genius grant” award recipient. Dr. Morton has also been named one of Time Magazine’s

through an article featured in The New York Times Magazine.Over the years, the Clinic has also expanded to meet the

growing needs of the Plain community. The Clinic currently has three physicians: pediatrician Dr. Morton, pediatrician Dr. Kevin Strauss (Harvard Medical School ’98), and Dr. Nicholas

fellowship in immunology). As more and more Clinic patients survive into adulthood, having a physician trained to treat adults is essential—which is in part why Dr. Rider joined the staff this

Robinson and Christine Hendrickson are valued members of the Clinic’s medical staff. And Dr. Morton’s wife, Mrs. Caroline Morton, serves as the Clinic’s Executive Director.

The Clinic’s in-house laboratory is run by Dr. Erik Puffenberger, who has a PhD in human genetics. The lab performs the Clinic’s routine diagnostic tests while engaging in original, translational

assisted by lab technician Chris Mitchell.Though the majority of the staff is “English,” the Clinic’s

both have familial ties to the Plain community. Rebecca remains Amish, while Miriam was raised Amish but left the church as a young adult (before adult baptism).

A di!erent paradigm of scienceThe Clinic is an interesting place not only because of its

and the Howard Hughes Foundation supports research that

have the disease he or she is studying.

Francis Peabody’s famous dictum, “The secret of the care of the patient is in caring for the patient.” The Clinic utilizes the advances of the Human Genome Project to practice individualized

..."e Clinic sta! lives by former Harvard professor Francis Peabody’s famous dictum, “"e secret of the care of the patient is in caring for the patient.”

Less than 3% of research funding from the National Institutes of Health (NIH) and the Howard Hughes Foundation supports research that requires the doctor to actually shake hands with individuals who have the disease he or she is studying.


Fe a t u r e s

17

genomic medicine and improve the lives of children and their families in Lancaster County. This translational research uses

cost-effectively solve patient problems that are recognized via primary care treatment.

Unlike a traditional university research laboratory, which investigates often abstract and obscure facets of understanding

arise. For example, in recent years, several babies in the Plain

transplant. As a result, the Clinic is currently working to start a bone

marrow database for the Amish and Mennonites of Lancaster

community. (At a traditional hospital, bone marrow matching testing alone can cost upwards of $50,000, which many Amish

number don’t participate in traditional insurance programs for religious reasons.) Helping to set up this database was my research project over the summer.

Clinic patients and their families often form strong bonds with the patient staff—despite the culture gap—as a result of

the course of his treatment. Since the son’s passing 5 years ago, the family has invited the Clinic staff to their home every year for dinner.

This past summer, the dinner fell on the last night of my internship. The dinner provided me with an incredible glimpse into the life of the Amish. Seeing an Amish home with a trampoline, slide and play area, as well as children’s rollerskates scattered about shatters many preconceived notions about the Amish attitude toward modernity. While the home is run on propane gas rather than electricity, it appears similar to any typical “English” home in most regards.

Adjusting to economic realitiesThe economics of the Clinic are much different than a typical university hospital or private medical practice. Due

to religious reasons, many Amish and Old Order Mennonite families do not have health insurance. The Amish and Old Order Mennonites believe it is the religious community’s responsibility to care for its sick, not the responsibility of any outside organization or government. For this reason, they are exempt from Social Security payments, and thus are also ineligible for Medicaid or Medicare coverage. Some families do have Amish Aid plans, which function similarly to health insurance plans but are viewed as acceptable because they involve only mutual Amish aid. But many Plain families do not have such aid plans and must pay completely out-of-pocket.

costs $35, which is usually less than the cost of transportation to the Clinic. (Most Plain families must hire an “English” driver, since their beliefs prevent them from driving or owning cars themselves.) As a result, patient fees only provide 20% of the Clinic’s budget, while 48% is provided by charitable gifts, 4% comes from the Clinic’s research endowment, and 28% is gathered during the Clinic’s annual fund-raising auctions.

The biggest auction—which draws thousands—takes place in Lancaster County in September, after my internship was

a smaller auction (with about 500 in attendance) in nearby Shippensburg, Pennsylvania. All of these auctions are organized by patient families, and Plain families donate goods and food to be auctioned off. All of the proceeds go to the Clinic.

puppies, a buggy and carriage, and a number of other items to attendees. Off to the side, Old Order Mennonite women hand-rolled soft pretzels and fried and powdered donuts to sell for

between the Clinic and the Plain community, a relationship made possible by the revolutionary way the Clinic approaches science and medicine in a modern era.

Fe a t u r e s


!rough the window, tall stalks of corn, a tire swing, a hitching post for a horse and buggy, and an occasional deer populated the landscape. But inside, modern scienti"c equipment whirred as I pipe#ed away inside the laboratory of !e Clinic for Special Children in rural Lancaster County, PA. - Shoshana Tell


Fe a t u r e s

19

!e Encyclopedia of Life:BY ALISSA D’GAMA, THURJ STAFF

As a young graduate student at the entomology department of the Smithsonian, Brain D. Farrell

Airport in New York City or the quarantine team at another port

a multi-million dollar shipment with a beetle on it. That beetle

world, he added.

I have a dream…of public access

T2003.

“Its principal achievement will be a single-portal electronic encyclopedia of life.”

who happens to be working late and gets the

The information would be easily and

from the National Institutes of Health, and

a “Wikipedia” of species

Fe a t u r e s


...The EOL can be used by scientists and educators, especially in the face of environmental issues like global climate change and population growth.

population growth.Institution.

Photograph of Pissodes strobi from www.eol.org


Fe a t u r e s

21

said Hanken, who is also a professor of Biology and Zoology,

Funding the future

T

Hanken.

What about Harvard?

B

said Hanken, who is also a professor of Biology and Zoology,

“There’s a lot of opportunity for Harvard students to get involved in EOL.”

3..2..1..Go!

T

on the beetle Pissodes strobi

and those who work at hospitals and need information for

Fe a t u r e s


ONE WOMAN’S JOURNEY IN SCIENCE: BARBARA J. GROSZ

Dr. Barbara J. Grosz is the Dean of the Radcliffe Institute for Advanced Study and the Higgins Professor of Natural Sciences in the Harvard School of Engineering and Applied Sciences.

BY SOPHIE WHARTON, THURJ STAFF

AN U PHILL JOU R N EY

When Barbara J. Grosz was in third grade, a teacher told her: “Girls can’t do math.” Today, as a

For as long as she says she can

interested in math, because you didn’t need a kit to do math.”

school, she began to show her

teachers.

by Tony Rinaldo


Fe a t u r e s

23

in college, Grosz says she was hooked,

her that she was wasting

mathematics and that she would “get bored

during the summer between her junior

and senior years, Grosz worked

that her

l a y not in

the summer, Grosz says her boss told

her, “You really did an

amazing job,

a girl could do anything.”

Her boss told her, “You really did an amazing job, I didn’t think a girl could do anything.”

Grosz’s math teacher taught the class binary mathematics, she says,

they use binary math, so you should understand what that is.” This teacher’s encouragement carried Grosz through high school, she

were teaching, nursing, and

was a clear message that the kits, and the science and the

to do something else.”

MAKING HER SPACE

to graduate school and began

instead, Grosz says, telling her that it was

would get her the degree. Though she was

Grosz has made seminal contributions

dialogue systems that could communicate

into substructures, and that this can be

in intelligent cognition extends beyond

says she has been interested in making

Fe a t u r e s


to research in the

later, she became the

by Benjamin Franklin and considered

was elected to the

not just in her research, but

BRINGING SCIENCE TO RADCLIFFE

“Science is a social activity,” Grosz says. “You’re in a lab, you’re in a research group. Even if you’re a mathematician you’re part of a community. We really want to get across that community aspect, to change students’ perceptions of what it means to do science.”

The institute was led at the time by now

humanities and social sciences. “There was a lot

to whether a really serious science

be built,” says Judith Vichniac,

meet with undergraduates and graduates


Fe a t u r e s

25

WORKING FOR CH ANGE

whether or not women were innately as good at math and science as

and Engineering. The Task Force

students, to undergraduates, to

undergraduate scientists to graduate student scientists, the

community.”

really want to get across that

it means to do science.”

LOOKING FORWAR D

women and science, but much work remains to be done.

But the search led right back to Grosz, who Hyman describes as “absolutely committed to excellence and interdisciplinarity, and is also a key actor in improving the status of women both at Harvard and nationally.”


Ma n u s c r i p t s

33

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Targeting factor VIIa: in silico prediction of new potent antithrombotics

LISA E. GINGOLD*,1, CHRISTINA CLEMENT1, AND MANFRED PHILIPP1

1Department of Chemistry, Lehman College/City University of New York, Bronx, NY 10468*Corresponding author: Harvard College ’10; [email protected]

Diseases of the blood coagulation system include heart disease and stroke. Parts of the system are inhibited by antithrombotic compounds, which therefore constitute potential therapies. D-Phe-Phe-Arg-chloromethylketone (FFACK) is a known antithrombotic, acting as an active site-directed alkylating inhibitor of factor VIIa, an important component of the blood coagulation system. A new class of compounds lacking the reactive chloromethylketone group of FFACK was developed in this work. The ability of these compounds to inhibit factor VIIa was then examined using computational predictions of van der Waals and electrostatic free energy scores. The compound predicted to be the most effective (Gly-Ser-Ala-D-Phe-Phe-Arg-NH2) was synthesized and effectively inhibited factor VIIa enzymatic activity in vitro. These results provide support for the viability of computational simulation in drug design.

____________________________________________________

INTRODUCTION

Unregulated blot clotting, which can be prevented by compounds targeting the blood coagulation pathway, is often the cause of heart attacks and strokes. The leading pharmaceutical anticoagulants on the market today are Coumadin and heparin, both of which pose problems for patients. Coumadin inhibits vitamin K reductase, thus preventing the formation of vitamin KH2.

1 The absence of vitamin KH2glutamic acid residues in prothrombin, which plays an essential role in blood thickening and clot production.2,3 However, the effects of Coumadin do not begin until approximately three days after it is taken, so patients must adjust their dosages for vitamin K intake days prior to treatment.4 Heparin, produced

obtained from animals that activates antithrombin, which then inhibits thrombin.6heparin require frequent coagulation monitoring and dose adjustments, and

7,8 Neither of

blood coagulation cascade to stop the blood clotting process, although direct

The system required for blood coagulation is a cascade chain reaction

factor VIIa, together with serum tissue factor (TF), is a critically important component of this process. The factorfactor

formation of factor Xa and thrombin require the factorand any agent that inhibits the formation of active factor Xa suppresses blood coagulation, inhibitors of factor VIIa have potential therapeutic value.11,12 Such inhibitors would likely prevent blood clotting due to vascular injury as part of the extrinsic pathway while having little impact on blood clotting in response to cuts as part of the intrinsic pathway (Figure 1). Thus, factor VIIa inhibitors could potentially bypass the substantially increased bleeding propensity caused by inhibitors of thrombin and factor Xa, which are involved in both the intrinsic and extrinsic pathways.13 Inhibitors of factor VIIa, which could become viable alternatives to currently available anticoagulants, have not been put to clinical use as antithrombotics, although factor VIIa’s action is known to be inhibited by D 14

MATERIALS AND METHODS

To discover potentially effective inhibitors of factor VIIa, various analogs of in silico

15 The factorincluded atomic coordinates of the entire protein as well as coordinates for the

D

MSI Sculpteffectiveness of the initial inhibitor, D

The initial inhibitor was redrawn in Isis Draw to allow the addition of other amino acids and amino acid derivatives to the structure (Figure 3). The new inhibitors created in Isis Draw MSI Sculpt.

with the template inhibitor, so that when the original inhibitor is deleted, the new one will be spatially situated in the protein active site. The new inhibitors were

optimal structures. The best inhibitor length was determined by experimenting with carbon chains

were replaced by different amino acids or polypeptide derivatives in Isis Draw and tested in MSI Sculpt. The chirality of the initial amino acids, additional amino

Figure 1. Blood clotting cascade: enzymes involved in the blood coagulation system are shown in maroon.10



CHEMISTRY

acids, and polypeptide derivatives bonded to phenylalanine were also altered and

laboratory and assayed to verify the computational predications and assess the potency of the inhibitors in vitro. In order to predict compounds that could be

in silico testing was restricted to short chain

Fmoc peptide synthesis. Fluorenylmethoxycarbonyl (Fmoc) peptide synthesis began with preparation of the synthetic support, or resin. The synthesis support (Novabiochem rink amide resin, 0.64 mmoles/g) was mixed with 2 ml

The resin was deprotected with 6 ml 40% piperidine in DMF and shaken for

minutes and with 10 ml methanol 5 times for 3 minutes (Figure 5).The resin was tested before and after adding each amino acid to the chain to

ensure the completion of the previous peptide bond synthesis step using the

M KCN, 5 drops of 80 g phenol in 20 ml ethanol, and 3 drops of 5 m/v % ninhydrin in ethanol, administered using separate pipettes. The resin was placed

were deprotected at the amino terminus (and the peptide bond synthesis step had not gone to completion), the liquid and the synthesis beads would have turned a

peptide bond synthesis step had been completed), the liquid was brown and the beads were clear.

was prepared and mixed with the resin so that it could be bonded to the peptide chain. The peptide bond synthesis step was performed by adding 1.125 ml of

separate bottle, the amino acid was added in a 4:1 ratio of amino acid to resin.

amino acid and shaken for 5 minutes to activate the amino acid. The activated amino acid was added to the resin and shaken overnight to allow for the two to couple. The next day, the resin was washed with DMF and methanol with 10 ml each 5 times for 3 minutes. The Kaiser Test was performed, followed by the addition of 40 % piperidine in DMF. The mixture was shaken, washed, and the

was added. This process was repeated for each successive amino acid until all the amino acids were attached.

was applied. The reaction was incubated for two hours followed by addition of 15

Figure 2. The initial inhibitor, D-Phe-Phe-Arg-chloromethylke-tone, was modified to obtain an inhibitor that would bind with the greatest affinity.

NH3NH

NH

O

NH O

NH

O

NH

O

NH

NH2+NH2

NH2O

OHO

+

Figure 3. Gly-Ser-Ala-D-Phe-Phe-Arg-NH2, as it appears in Isis

Draw.

Figure 4. The inhibitor is analyzed in MSI Sculpt, showing it in-serted into the 3-dimensional protein to determine the potential inhibitor’s bonding energy.

Figure 5. Fmoc synthesis. R: side chains. X: temporary –amino protecting group. Y: side chain protecting group17



35

CHEMISTRY

resuspended in 200 µl to 500 µl of water, in preparation for chromatography, mass

Mass spectroscopy was performed with the LCQ mass spectrometer to

Tune Pluswithin 2 units of the theoretical mass of the peptide, the synthesis was considered successful. The peptide could appear with an added sodium ion, potassium ion, or both. In these cases, the peptide appeared both in its original form and at higher mass with an additional sodium and/or potassium ion.

Contaminants were removed by use of high performance liquid chromatography

Separation Module observed eluted compounds by ultraviolet (UV) absorbance

could be collected separately. The samples collected should be tested again in the mass spectrometer and if the target sample is not pure, it should be rerun on the

Factor VIIa inhibition assay.factor

factor VIIa mediates hydrolysis of the substrate nitroanilide DD

factor VIIa and factor VIIa treated with putative inhibitor were gauged using measurements of the concentration of

Figure 6. Mass spectroscopy shows that the target peptide, Gly-Ser-Ala-D-Phe-Phe-Arg-NH2 is pure. Although there are two peaks, they

both represent the same peptide; the peptide with a sodium ion has a peak at 705.3 m/z.

Figure 7. Hydrolysis of nitroanilide D-Phe-Phe-Arg-pNA to D-Phe-Phe-Arg and p-nitroaniline

Human factor

Sigma Plot. By comparing the control and the inhibitor in absorbance units per second at 405 nm, one can determine the inhibitory strength of the peptide. The reaction curve of an inhibitor that prevents the cleavage of p



CHEMISTRY

have a smaller slope, signifying greater inhibition.

RESULTS

D 2 was the peptide chosen for synthesis

D 2 was successful; the expected presence of minor

D 2 was tested with factor VIIa in vitro, it was an effective inhibitor, reducing factor VIIa activity approximately

inhibit the reaction by 50% (IC50 50 was calculated according to the formula below:

concentrations, meaning that substrate concentrations were much higher than the substrate Km

the reaction. The more meaningful Ki might be much lower than the observed IC50 (i.e. the inhibitor might exhibit tighter binding) in the likely event that the inhibitor was in competition with the saturating substrate for access to the

the available factor VIIa substrates, it is impossible to run the experiment under conditions in which the substrate concentration is near its Km, which would have allowed the determination of Kicompetition between the inhibitor and the substrate, however, the inhibitor’s Ki can be estimated according to the following equation18:

m

0 5i

K] substrate [1

C IK

Using this equation, the Ki is estimated to be 2 × 10 M, meaning that a 2 × 10 D 2, would inhibit factor VIIa 50%. Considering the form of design, namely computational analysis, this is very powerful.

DISCUSSION

19 Those who survive are sometimes forced to medicate for the rest of their lives. In these patients, blood coagulation must be tightly controlled, for if blood clots too little, they could suffer hemorrhages, and if blood clots too much, they could have a heart attack or stroke. The currently available anticoagulants

anticoagulants. The pharmaceutical market does not yet have a drug that inhibits factor VIIa, although such an inhibitor could act as a more effective anticoagulant than the drugs currently available.

inhibitors of factorand to assess the accuracy of the computer simulations. The production of a strong inhibitor from computational simulations, as was shown in this study, demonstrates the great potential of computational chemistry in the future of drug development. In silico modeling using computer programs such as Isis Draw and MSI Sculpt to determine the potency of an inhibitor could predict a drug superior to what the pharmaceutical market offers today. Given that computers can calculate theoretical energy minima fairly accurately and quickly, such computational chemistry approaches to drug design could prove

laboratory experimentation.

REFERENCES

Adv Exp Med Biol.

Annu Rev Nutr.

4. Voora, D, HL McLeod, C Eby and Gage BF. “The pharmacogenetics of Pharmacogenomics

Blood Coagul FibrinolysisSemin

Vasc Surg.

Pharmacotherapy

Table 1. Potential peptide inhibitors were tested in MSI Sculpt, minimizing van der Waals and electrostatic energies. Selected re-sults are given.

Figure 8. Absorbance at 405 nm with peptide inhibitor at 0 µM (red) or inhibitor at 20 µM (blue)

Amino acid sequence of potential inhibitor

Minimization Values (kcal/mol)

Ala-Ala-Ala-D-Phe-Phe-Arg-NH2

-330

Ala-Ser-Ala-D-Phe-Phe-Arg-NH2

-320

Ala-Ser-Gly-D-Phe-Phe-Arg-NH2

-340

Gly-Ala-Ala-D-Phe-Phe-Arg-NH2

-330

Gly-Ser-Gly-D-Phe-Phe-Arg-NH2

-345

Gly-Gly-Gly-D-Phe-Phe-Arg-NH2

-345

Gly-Ser-Ala-D-Phe-Phe-Arg-NH2

-350



37

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osteoblasts following low molecular weight heparin or Fondaparinux European Cells and Materials Vol. 7. Suppl. 1, 2004.

9. Kilby, JM. “Therapeutic potential of blocking HIV entry into cells: focus Expert Opin Investig Drugs

of anticoagulant therapy. Seminars in Thrombosis & Hemostasis418.

Cardiovascular Drug Review

Thrombus Formation with Minimal Hemorrhagic Complications by a Small Molecule Tissue Factor/Factor VIIa Inhibitor: Comparison to Factor Xa

The Journal of Pharmacology and Experimental Therapeutics

Haemophilia. 2005 May.

Journal of Biological Chemistry

Biochem Pharmacol.108



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Characterization of epoxidized Carthamus tinctorius oil (ECTO) as a novel polyvinyl

chloride plasticizerROBYN THOM*,1, THOMAS SUN1

1University of British Columbia, 2146 East Mall, Vancouver, BC V6T 1Z3, Canada * Corresponding author: Harvard College ’11; 460 Eliot Mail Center, 101 Dunster Street,

Cambridge, MA 02138; [email protected]

Polyvinyl chloride (PVC) is among the top three most widely used plastics globally. Di(2-ethylhexyl) phthalate (DEHP) is often

cause environmental contamination. This study investigates the suitability of epoxidized Carthamus tinctorius oil (ECTO) as a

INTRODUCTION

Polyvinyl chloride (PVC), a thermoplastic resin, is among the top three most widely used plastics in the world. PVC plastics are used in construction projects, automobiles, packaging, and water transportation. A phthalate ester, di(2-ethylhexyl) phthalate (DEHP), is often added as a PVC plasticizer.

1-7. Commercial PVC plastics contain up to 40 wt% of this plasticizer.

There has been increasing concern regarding the impact of DEHP exposure on human health and the environment. Humans are exposed to DEHP through ingestion, inhalation, and dermal exposure8. Medical procedures which employ PVC, including intravenous therapy, nutrition support, blood transfusion, and hemodialysis, also pose risks of hazardous DEHP exposure 9. Though DEHP is suggested to be of low acute toxicity, long-term exposure may have an adverse effect on human health. Risk assessment studies have shown that DEHP critically affects male fertility10. Additionally, the Food and Drug Administration (FDA) has issued a report acknowledging that PVC medical devices are a concern to critically ill infants 11. In addition to affecting human health, DEHP exposure may also have a negative impact on

12. Previous studies have indicated that phthalate compounds can be detrimental to aquatic organisms at low chronic concentrations13.

Our study investigates the suitability of epoxidized Carthamus tinctorius

an oxygen atom to a carbon-carbon double bond to form a 3-membered ring with epoxide (or oxirane) functionality. Epoxidized soybean oil (ESO) as a phthalate replacement has shown some comparable physical properties to DEHP in PVC 14. Our study shows that the ECTO plasticizer produced comparable results to the DEHP plasticizer in resilience, elastic modulus, and toughness at up to 30 wt%. Thus, for products employing low wt% plasticizer, ECTO may be a suitable DEHP replacement because of its environmentally friendly synthesis, abundance, and low cost of raw materials.

METHODS AND MATERIALS

Polyvinyl chloride (PVC) was provided by Sigma Inc. Carthamus tinctorius oil, DEHP, tetrahydrofuran, Polysorbate 80, hydrogen peroxide, Novozym 435 (lipase B from Candida antarctica), and toluene were used. A Thermo-Mechanical Analyzer (TI Q400) and Instron (Model 1122) were used for performance tests.

Synthesis of epoxidized Carthamus tinctorius oil (ECTO). ECTO was synthesized by epoxidizing Carthamus tinctorius oil via a chemo-enzymatic reaction, as suggested by Orellana-Coca et al. 15. Epoxidation was achieved by reacting ethane with a peracid and hydrogen peroxide (see Fig. 1 15).

Epoxidation was performed via a chemo-enzymatic reaction with Novozym 435, a lipase; 7 mL of Carthamus tinctorius oil, 25 mL of toluene, and 0.75 g of Novozym 435 were constantly stirred at 260 rpm at room temperature for 24 hours. Over the same

pump. After agitation, the two phases were separated. The hydrophilic-toluene phase containing the enzyme was removed, leaving the hydrophobic ECTO. Remaining toluene solvent was removed through roto-evaporation at 80 ºC.

in plasticizer wt% of 0, 10, 20, 30, and 40. Vinyl chloride and the plasticizer were dissolved in tetrahydrofuran (THF) for the vinyl chloride to polymerize. An ultrasonic stirrer was used to promote dissolution until all components had completely dissolved. One mL of each solution was pipetted onto microscope slides laid with 2.5 cm x 2.5

Stress-strain and related physical properties analysis. Films of approximately

Figure 1. Reaction mechanism of chemo-enzymatic epoxidation between a peracid and hydrogen peroxide.



39

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5 mm x 1.5 mm were loaded into an Instron (Model 1122). Strain rate was kept constant at 0.625 mm/min, and cross-head rate was adjusted accordingly. Films were

then extended at a 0.625 mm/min strain rate until fracture. Stress-strain curves were generated, and properties of elastic modulus, resilience, and toughness were calculated. All physical property analysis was done at room temperature, approximately 23.0 °C.

Elastic modulus. Elastic Modulus, a measure of stiffness, was determined by

calculating stress over strain. Resilience. Resilience, a measure of a material’s ability to absorb energy, was

obtained: Toughness. Toughness, a measure of the amount of energy a material can absorb

before fracture, was calculated by determining the area under the stress-strain curve. Glass transition temperature analysis. Film strips 5 mm x 15 mm were loaded

into a Thermo-Mechanical Analyzer (TI Q400) with a starting temperature of 0 ºC, temperature change of 20 ºC/min to 170 ºC, and constant force of 0.05 N. TMA Analysis software was used to determine the glass transition temperature.

RESULTS

Elastic modulus of PVC with DEHP or ECTO. A lower modulus indicates a more elastic sample. Generally, samples with a higher plasticizer concentration had a lower elastic modulus. Thus, a clear plasticizing trend with increase in wt% plasticizer is shown. However, ECTO40 had a higher elastic modulus than ECTO30, disturbing the trend of decreasing elastic modulus with increasing plasticizer concentration. Generally, samples plasticized with DEHP had a lower elastic modulus than samples plasticized with ECTO.

acceptable range of values for samples with 10%, 20%, and 30% plasticizer.

Thus, the elastic modulus of samples plasticized with ECTO and DEHP at

to the otherwise rigid PVC polymer. (N=3, n=1). (Figure 3a, 3b)Resilience Modulus of PVC with DEHP or ECTO. A higher resilience

modulus indicates higher ability to absorb energy. Generally, the higher the plasticizer concentration, the lower the resilience modulus. A t-test was

acceptable data ranges for samples of 10%, 20%, and 30% concentration plasticizer. Thus, the resilience modulus of samples plasticized with ECTO

Figure 2. Stress-strain curve of a DEHP10 sample.

Figures 3a & 3b. Elastic Modulus of PVC with DEHP or ECTO.

a b

Figures 4a & 4b. Resilience Modulus of PVC with DEHP or ECTO.

a

b



CH

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at the 40% plasticizer concentration, ECTO does not appear to be a suitable replacement for DEHP in terms of resilience. (N=3, n=1). (Figure 4a, 4b)

Toughness of PVC with DEHP or ECTO. A higher toughness indicates a higher amount of energy required to induce rupture. A t-test at

and 30 wt% plasticizer. Thus, it is only at the 40% concentration of plasticizer

n=1).

ECTO has a high proportion of polar versus non-polar groups, perhaps enabling it to have effective solvating power for PVC, thereby making it a suitable plasticizer. (Figure 5)

Glass transition temperature of PVC with DEHP or ECTO. Glass transition temperature (Tg) was measured, as shown in Fig. 6. A general increase is observed with the amount of plasticizer added, resulting in a lower Tg. A plastic assumes its glass phase below its Tgits Tg. Thus, a lower Tg is desirable. Glass transition temperature is often used as an indicator of general plasticizing effect, with a low ideal transition temperature. ECTO had the lower Tg at each plasticizer concentration. A

effective because its high number of non-polar groups can cause reduction in polar forces between polymer chains, thus lowering Tg and improving low-

CONCLUSION

Epoxidized Carthamus tinctorius oil was found to be a possible alternative for DEHP at up to 30 wt%, displaying statistically similar physical properties in the areas of elastic modulus, resilience modulus, and toughness. In terms of

than DEHP at all wt%. ECTO has potential in replacing DEHP, as it exhibits similar plasticizing

effects. With the inclusion of epoxy groups, this plasticizer should also have the added advantage of being a heat stabilizer. Previous studies have shown that epoxides are effective PVC thermal stabilizers 16. The use of ECTO not only has the potential to reduce the production of DEHP but may also minimize the manufacture of heat stabilizers, chemicals that are also often hazardous to the environment. ECTO, the derivative of a renewable natural vegetable oil, may be more environmentally friendly than DEHP and other petroleum-based plasticizers. If ECTO were implemented on a broad-scale basis, this could alleviate the health and environmental concerns caused by widespread use of DEHP.

Figure 5. Toughness of PVC with DEHP or ECTO.

Figure 6. Glass transition temperature of PVC with DEHP or ECTO.

ACKNOWLEDGEMENTS

We would like to thank Dr. Helen Burt and Dr. Margo Lillie for their support and for allowing us to conduct our research in their respective laboratories. We are also grateful to Dr. Katherine Haxton, a postdoctoral fellow, who assisted us with our epoxidation reaction and to Mr. John Jackson, Burt laboratory manager, who trained us in the use of the Thermo-Mechanical Analyzer. Last but not least, sincere thanks to Dr. Geoffrey Gabbott, who provided us with guidance and support for each step of the way.

REFERENCES

1. Krauskopf, L. G. Encyclopedia of PVC; Dekker: New York, 1988; Vol. 2, p 140. Gachter, R., & Muller, H. Plastics Additives Handbook 3rd ed.; Carl Hanser Verlag: New York, Wien, 1990.

2. Murphy, J. Additives for Plastics Handbook; Elsevier Science: New York, 2001.

3. Rahman, M. & Brazel, C. S. Prog Polym Sci 2004, 29, 1223.4. Sommer, W. In Plastic Additives Handbook; Gachter, R.; Muller, H.,

Eds.; Hauser Publishers: Vienna, 1984; p 253.5. Stepek, J. & Daoust H. Additives for Plastics; Springer-Verlag: New York,

1984.6. Wickson, E. J. Handbook of Polyvinyl Chloride Formulating; Wiley: New York,

1993.7. Hong, K. Z. Poly(vinyl chloride) in medical device and packaging

applications. Journal of Vinyl and Additive Technology 2(3), 193-197 (1996).8. Huber, W. W., Grasl-Kraupp, B., & Schulte-Hermann, R. Donor

exposure to the plasticizer di(2-ethylhexyl) phthalate during plateletpheresis. Critical Reviews in Toxicology 26, 365-481 (1996).

9. Heudorf, U., Mersch-Sundermann, V., & Angerer, J. Phthalates: toxicology and exposure. Int J Hyg Environ Health 210(5), 623-34 (2007).

10. Liu, X., He, D. W., Zhang, D. Y., Lin, T., Wei, G. H. Di(2-ethylhexyl) phthalate (DEHP) increases transforming growth factor-beta1 expression in fetal mouse genital tubercles. J Toxicol Environ Health A. 71(19), 1289-94 (2008).

Containing the Plasticizer DEHP. <http://www.fda.gov/cdrh/safety/dehp.html> Accessed July 20, 2008.

Nature 396, 638 (1998).13. Rhodes, J. E., Adams, W. J., & Biddinger, G. R. Chronic toxicity of 14

phthalate esters to Daphnia magna and rainbow trout. Environmental Toxicology and Chemistry 14, 1967-1976 (1995).

14. Ishiaku, U. S., Shaharum, A., Ismail, H., & Ishak, Z. A. M. The effect



41

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of an epoxidized plasticizer on the thermo-oxidative ageing of poly(vinyl chloride)/epoxidized natural rubber thermoplastic elastomers. Polymer International 45(1), 83-91 (1997).

15. Orellana-Coca, C., Camocho, S., Adlercreutz, D., Mattiasson, B., & Hatti-Kaul, R. Chemo-enzymatic epoxidation of linoleic acid: Parameters

Eur J Lipid Sci Technol 107(12), 864-870 (2005). 16. Patel, P.G., Patel, G. R., & Parmar, J.S. Epoxy based thermal stabilizer

for poly(vinyl chloride). Polymers and Polymer Composites 9(4), 283-290 (2001).



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The impacts of stricter high school graduation requirements on youth crime

ALICE JENG-YUN CHEN*

*Corresponding author: Harvard College ’08; [email protected]

This study empirically examines the relationship between state high school exit examinations and course graduation requirements and three different crime outcomes: 1) property crime, violent crime, and murder crime arrest rates using state-level panel data spanning 1980-2003, 2) incarceration rates for affected state birth cohorts using individual-level Census data, and 3) self-reports

negatively related to crime. This suggests that the increased education standards induced by stricter graduation requirements

ASVAB (Armed Services Vocational Aptitude Battery) individuals.

INTRODUCTION

For the past 25 years, education reform has remained at the forefront of governmental agendas. Since the 1980s, a growing number of state governments have mandated stricter high school graduation requirements through the introduction of exit examinations and an increase in the number of core courses a student must pass to graduate. In this paper, I rely on the exogenous variation in implementation dates of exit exams (EEs) and course graduation requirements (CGRs) to investigate their impact on youth crime.

Such an examination is important for several reasons. First, the relationship between a more rigorous education system and a youth’s tendency to commit crime is not immediately obvious. For example, stricter graduation requirements can cause studying to be more arduous and can increase dropout rates, leading to an increased share of youths who are susceptible to committing crime. Alternatively, stricter graduation requirements can make the obtainment of a high school diploma more meaningful, providing an incentive for students to

Second, existing literature focuses almost solely on how EEs and CGRs affect high school dropout rates, and not other determinants of crime. Several researchers have used the same datasets to reach opposing conclusions. Carnoy and Loeb (2002) and Amrein and Berliner (March 2002) both use data from the National Association of Educational Progress (NAEP), but

gains on math tests while Amrein and Berliner conclude that 55% of states with EEs experienced decreases in standardized exam scores. Similarly, while Muller (1998), Warren and Jenkins (2001), and Reardon and Galindo (2002) use the National Educational Longitudinal Survey (NELS) to argue that there is no relationship between passing an exam and dropping out of high school, Bishop and Mane (2001) and Jacob (2001) use the NELS to illustrate an increased dropout associated with EEs and CGRs.

Finally, it is important to fully understand the consequences of policies

initiation, EEs have been implemented in 27 states while CGRs have been implemented in over 40 states (Zabala et al. 2007). About 65% of the nation’s public high school students are affected by EEs, and according to NAEP, high school students graduating in 2005 had to take on average three extra courses, equivalent to 360 extra classroom hours, compared to those who graduated in 1990.

I determine the impact of stricter graduation requirements on youth

24 from the FBI’s Uniform Crime Reports (UCR). The second strategy

2000 Integrated Public Use Microdata Series (IPUMS). The third approach

level characteristics can be controlled for in the second and third approaches, I ensure that the effects of EEs and CGRs on arrest rates correspond to changes in criminality rather than educational differences in the probability of arrest.

with a decrease in youth crime. While these estimates are sensitive to controls included in the regression, this negative relationship holds through various

adds credibility to the conclusions drawn.

DATA AND METHODS

To provide further intuition on how stricter graduation requirements impact crime, I present a simple economic model.2behavior where in period 1, the individual decides how much education to invest. In period 2, the individual chooses whether or not to commit crime. This is represented by Figure 1.

The presence of an EE or CGR is represented by the indicator E which is a 0 or 1

is a constant for

Figure 1. The tree above shows the different payoffs that result from choosing to 1) graduate versus drop out and 2) work versus commit crime.3



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the increased studying cost induced by an EE or CGR, is the probability of being caught committing a crime, p is the cost of the punishment that results from being caught, CL and CH with CL < CH are psychological costs associated with committing crime, wH and wL with wL < wH are wages from legitimate market work, and wCH and wCL with wCL < wCH are wages resulting from crime. Finally, w1, w2, and w3 are wage changes resulting from having an EE or CGR.

I use my model to examine the effects of an EE or CGR on crime. The presence of an EE or CGR affects the payoffs for high school graduates in two ways. First, it increases the cost from studying, represented by S*E. Second, for graduates, it increases both wages from legitimate work and wages from crime. The key tradeoff in predicting the effect of EEs and CGRs on crime is determining whether individuals will improve their labor market productivities or dropout from school earlier, thereby increasing their risk of crime participation.

To empirically determine which effect dominates, I measure crime according to the

for time, t* as the year if 15 < age < 18 and t* = year – (age – 18) if 19 < age < 24, a

Case 1: state level arrests using 1980-2003 Uniform Crime Reports (UCR) data

The basic empirical strategy is given by the following regression form: (1) ln(Arrestsst) = 1 (effectiveEEst) + 2 (effectiveCGRst) + ln(Populationst) + Xst + s + t + i *t

+ st

violent, or murder crimes committed by individuals age 15 through 24. Per capita arrests rates are taken into account by the inclusion of the right hand term ln(Populationst) which is the log of population of individuals age 15 through 24.4 The two main independent variables, effectiveEEst and effectiveCGRst,increase in youths affected by a stricter graduation requirement. In other words, if an

but in 2001, both those in high schools during 2001 and those who graduated in 2000 are affected.5 Thus, following Donohue and Levitt (2001):

The actual EEst and CGRst variables are coded as follows: EEst = 1 if state s had an

EE for the graduating class in year t; otherwise, EEst = 0. Similarly, CGRst = 1 if state s had a CGR for the graduating class in year t; otherwise CGRst = 0.

over time. Further unobserved heterogeneity is accounted for through s, t, and i

stresidual.

. The 2000 IPUMS data consists of 2,808,457 respondents, and it is particularly useful for several reasons. First, the large sample size allows for a more

to the impact of EEs and CGRs on criminality. Third, the availability of important

attainment, and labor market performance allows for the control of individual characteristics. Fourth, as Dee and Jacob (2006) note, a particularly useful feature of the IPUMS are the multiple birth cohorts within each state, which allow exploitation

6 Since criminal participation is concentrated among men, I analyze male respondents

ages 18 through 38 where the EE and CGR variables correspond to the policy in

quarters question with “institutionalized,” and the basic regression model is now given by:

(3) Incarceratedist = 1 (EEist) + 2 (CGRist) + Xist + s + b + stThe vector Xist is as before, s b represents

st is the mean zero random error.7 Case 3: self-reported crime from 1997 National Longitudinal Survey of Youth

(NLSY97). Administered by the Bureau of Labor Statistics, the NLSY97 is an annual

survey given to a nationally representative sample of youths. As of December 31, 1996, these approximately 9,000 youths were between the ages of 12 and 16. From the NLSY97 data, I create several measures of criminality: Arrests which equals 1 if the respondent admits to being arrested at least once since the date of the last interview, and Incarcerated which equals 1 if the respondent was surveyed in prison, reported incarceration as the reason for unemployment, or answered that their permanent dwelling was a jail. I also look at particular crimes. If the respondent agrees to having purposely stolen property under $50, stolen something worth over $50, destroyed property, or committed other types of property crime, I designate the Property Crime variable as 1.8 If the respondent concedes to using a weapon to forcibly take something

Violent Crime variable Drug Crime variable is 1 if the respondent admits to having sold

or helped sell illegal drugs.9 There are several advantages to using the NLSY97 data. First, unlike Census data,

the NLSY97 differentiates among several different types of criminal offenses. Second, unlike UCR data, detailed demographic information—obtained through extensive

interviews—is available. Third, in 1997 and early 1998, NLSY97 respondents were given a computer version of the Armed Services Vocational Aptitude Battery (ASVAB), which serves as a measure of individual cognitive ability.10 Fourth, an extremely high retention rate of those surveyed offers valuable information on an individual’s true level of educational attainment.

crime while others may overstate their criminal participation out of a feeling of pride. The NLSY97 surveys attempt to minimize these sources of dishonesty by having

interviewer. The degree of effectiveness that this method promotes is unknown, but as Lochner and Moretti (2003) note, self reported data nonetheless remains one of the most direct measures of criminal participation available.

(4) Crime Measurementist = 1 (EEist*) + 2 (CGRist*) + Xist + s + b + t + st+ st

Crime Measurementist is a vector that includes the Arrests, Incarcerated, Property Crime,

(2)

a total

astst Arrests

ArreststmeasuremeneasurementEffectiveM )(**



ECONOMICS

Violent Crime, and Drug Crime variables. The vector Xist relies on the NLSY97’s rich set

11 s b

t st

st is the zero mean random error.

RESULTS

Table 1. All standard errors are clustered by state. For each crime category,

10.8%, violent arrests decreasing 22%, and murder arrests dropping 28.3%.

arrests increasing by 6.6%, violent crimes increasing by 5%, and murder

and property and violent crimes suggests that stricter graduation requirements are generally associated with decreases in crime.

For an analysis by age, Figure 2 and Table 2 show the effect of

Figure 2. These plots show the relationship between stricter graduation requirements and arrest rates of individuals over dif-ferent age cohorts. The graph on the left shows the impact of EEs on arrests while the graph on the right shows the impact of CGRs on arrests.

stricter graduation requirements on arrests rates across different ages 15 to 24.

trend. The graph on the left represents the impact of EEs on arrests while the graph on the right represents the impact of CGRs on arrests. The table

the results for those ages 17 to 21—the age range of the typical high school

It is interesting to note the stark contrast between the way EEs and CGRs affect arrests over age. For individuals ages 15 to 24, as age increases, CGRs either have a relatively constant impact on arrests or a decline in the probability of arrests. EEs show a more prominent decline in the probability of arrests for individuals ages 15 to 21, but for individuals ages 21 to 24, EEs correlate with a steady rise in the probability of arrest. Individuals age 21 realize the greatest

so much is that unlike CGRs, EEs can lead to a decrease in material learned at school. It is not unreasonable to assume that under pressure, teachers in schools with EE policies will set aside topics normally taught to cover topics



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guaranteed to show up on the exit exam. Employers may not recognize this decrease in material learned due to asymmetric information and the inaccurate signaling effects. Eventually, employers will realize this effect and may decrease the market wages offered.12

Next, the analysis by race using the IPUMS data is shown in Table 3. All

support the conclusions drawn from Table 1, namely that stricter graduation

association between stricter graduation requirements and incarceration, and the following discussion examines this negative bias, keeping in mind that estimates are not robust. Column (3) suggests that for whites, EEs and CGRs decrease incarceration rates by 0.049 and 0.145 percentage points respectively, and for blacks, the incarceration rate decreases by 0.019 and 0.397 percentage points respectively.

There are some interesting observations that can be drawn from these

blacks than whites, and this holds across all education categories. Second, even though the incarceration rates for both blacks and whites decreases monotonically with education, the rate of decline is much larger for blacks than it is for whites. Third, the inclusion of covariates affects the estimates for blacks more than they do for whites, suggesting that family background variables such as the household income, number of families per household, and living with stepparents affect the probability of incarceration more for blacks than for whites.

NLSY97, Table 4 presents the results when a much richer set of covariates

again, the presence of an EE or CGR leads to a decrease in crime across all measurements of crime, but here, I can also conduct an analysis based

those having scores < 25 and high ability as those having scores > 75, and

The magnitudes of estimates presented in column (2) are much larger than the magnitudes of estimates shown in column (4) for almost all measurements of crime, meaning that low ability individuals are affected much more by

in columns (1) and (3), it is evident that EEs and CGRs impact low ability

DISCUSSION AND CONCLUSION

seem implausibly large. However, these large estimates are not unprecedented:

increase in the average years of schooling correlates with murders and assaults falling by 30% and motor vehicle thefts dropping by 20%. Furthermore, the

log of population is not exactly 1, the inaccuracies involved with estimating population by year, state, and age can account for the differential. Consistent with Marvell and Moody (1994), Levitt (1996), and Levitt (1997), increases

in the number of prisons per capita and number of police per capita both generally decrease crime. 13 As shown by Freeman (2000), higher state unemployment is associated with increases in property crimes, but not violent crimes. Furthermore, the presence of a concealed gun law decreases crime (Lott and Mustard 1997) while the effective abortion rate corresponds to a drop in crime (Donohue and Levitt 2001).

The estimates presented in Table 3, though seemingly small, are also consistent with related existing literature. Using IPUMS data, Lochner and Moretti (2003) estimate that an additional year of schooling reduces the probability of incarceration by 0.1 percentage points for whites and 0.37 percentage points for blacks. Furthermore, one would expect the estimates on incarceration to be small since only a small share of the population is ever incarcerated. In 2004, only 25% of aggravated assault arrests and 31% of violent felonies such as murder and robbery led to convictions, and not all convictions result in jail time (Durose and Langan 2007).

In the preceding sections, I have conducted investigations on the impact of

for crime is used, stricter graduation requirements lead to a decrease in crime. The consistency of this result across datasets and measurements of crime provides compelling evidence in support of my conclusion.

graduation requirements impact blacks more than they do whites and affect lower ability students more than they do high ability students. An interesting age trend— where the impact of EEs on crime became increasingly negative for individuals ages 15 to 21 and increasingly positive for individuals ages 21 to 24—presented itself, but many of the estimates were statistically

Given the high cost associated with implementing EEs and CGRs, these



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REFERENCES

1. Amrein, Audrey L. and David C. Berliner. “An Analysis of some Unin

2. Bishop, John H. and Ferran Mane. “The Impacts of Minimum Competency Exam Graduation Requirements on High School Graduation, College Attendance and Early Labor Market Success.” Labour Economics, 8, no. 2 (5,

3. Brewer’s Almanac. “Annual Consumption of Malt Beverages in Gallons per Capita.” Beer Institute: Washington, DC (annual).

4. Bureau of Justice Statistics. “Correctional Populations in the United States.” <http://www.ojp.usdoj.gov/bjs/abstract/cpusst.htm>

5. Bureau of Labor Statistics. “Current Population Survey.” < http://www.census.gov/cps/>

6. ———. “National Longitudinal Survey of Youth 1997 Geocode Data.”7. Carnoy, Martin and Susanna Loeb. “Does External Accountability Affect

Educational Evaluation and Policy Analysis

8. Digest of Education Statistics. “Ages For Compulsory School Atten

Schools, and Kindergarten Programs, by State.” < http://nces.ed.gov/programs/digest/>

9. ———. “State Requirements for High School Graduation, in Carnegie Units.” <http://nces.ed.gov/programs/digest/>

10. Donohue, John J. III and Steven D. Levitt. “The Impact of Legalized Abortion on Crime.” The Quarterly Journal of Economics 116, no. 2 (May, 2001):

11. Durose, Matthew R and Patrick A. Langan. “Felony Sentences in State Courts, 2004.” Bureau of Justice Statistics Bulletin, NCJ 215646 (July 2007).

12. Federal Bureau of Investigations. “Uniform Crime Reports.” <http://www.fbi.gov/ucr/ucr.htm>

13. Foote, Christopher and Christopher Goetz. “The Impact of Legalized Abortion on Crime: Comment.” Quarterly Journal of Economics 123, no. 1 (Feb.,

14. Freeman, Richard B. “The Economics of Crime.” In Handbook of Labor Economics

15. Integrated Public Use Microdata Series. “2000 1% Census.” <http://usa.ipums.org/usa/>

ation Exams.” Educational Evaluation and Policy Analysis 23, no. 2 (Summer,

17. Levitt, Steven D. “Using Electoral Cycles in Police Hiring to Estimate the Effect of Police on Crime.” The American Economic Review 87, no. 3 (Jun.,

18. ———. “The Effect of Prison Population Size on Crime Rates: EviThe Quarterly Journal of Economics

19. Lillard, Dean R and Philip DeCicca. “Higher Standards, More DropEconomics of Education Review, 20, no.

20. Lochner, Lance and Enrico Moretti. “The Effect of Education on American

Economic Review

The Journal of Legal Studies 26, no. 1 (Jan.,

graduation requirements. While literature on how EEs and CGRs affect dropout has been mixed, their effect on crime is unambiguous: EEs and CGRs lead to a decrease in youth crime. This can happen through several mechanisms, such as better signaling to future employers or the raising of human capital of high school graduates who have learned more in school. Individuals who earn higher market wages are then more risk averse, face higher opportunity costs of time spent in jail, and suffer a greater stigma from criminal convictions (Western et al. 2002).

Further analysis is needed to pinpoint the exact mechanism through which EEs and CGRs decrease crime, but the observations I have made serve as an initial foundation for future research. Education will continue to remain an important national issue, and as such, the need to understand the effects of stricter high school requirements on youth crime remains crucial.

FOOTNOTES

1The author would like to thank Lawrence Katz and Richard Freeman for their extremely helpful guidance and insights, Chris Foote, Thomas Dee, and the Bureau of Labor Statistics for providing portions of the data, and the Harvard College Research Fund for funding this research.

2This model is not meant to be comprehensive, but it serves as a helpful tool in understanding the underlying intuition between stricter requirements and crime.

3The payoff values for crime are based on Freeman (1999).4The use of arrests versus arrests per capita has been debated by Donohue and

Levitt (2001) and Foote and Goetz (2008). Foote and Goetz maintain that to test

the regression to reduce measurement error bias. For this paper, I have found that when population is included on the left as ln(arrests per capita), the results are comparable to when ln(population) is included on the right. Hence I have chosen to include population on the right so that the relationship between ln(arrests) and ln(population) can be gleaned.

5

Dee. Since Lillard and DeCicca (2001) note that the average state graduation

Almanac, Bureau of Justice Statistics, Bureau of Labor Statistics, Digest of Education Statistics, and the US Census Bureau.

6

attended secondary school. 7

model.8

or selling stolen property, or cheat[ing] someone by selling them something that was worthless or worth much less than you said it was.”

9

and violent crime question was not asked in 1997, and according to Steve McClaskie from the Center for Human Research, only a select sample of respondents were

10The ASVAB consists of 10 tests: general science, arithmetic reasoning, word knowledge, paragraph comprehension, numerical operations, coding, speed, auto and shop information, mathematics knowledge, mechanical comprehension, and electronics information.

11

race dummies. Family background measures include the parents’ highest grade completed, whether the individual lived with both natural parents at age 14, whether the individual’s mother was a teenager at the time of the respondent’s

controls include the local unemployment rate and a dummy for urban versus rural residence.

12Evidence for the inaccurate signaling effect of the EE can be seen through the advocacy of research institutions such as the American Education Research Association, the National Council on Measurement in Education, and the National

Research Council Board on Testing and Assessment, which all maintain that no

13Levitt (1996) uses prison overcrowding litigation as an instrument for prison

increases in the police per capita negatively impacts crime.



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22. Muller, Chandra. “The Minimum Competency Exam Requirement, Teachers’ and Students’ Expectations and Academic Performance.” Social Psychology of Education

Presented at the Annual Meeting of the American Educational Research As

24. United States Census Bureau. “Population Estimates for the U.S. and States by Single Year of Age and Sex.” < http://www.census.gov/popest/estimates.php>

25. ———. “United States Statistical Abstract.” <http://www.census.gov/statab/www/>

26. Warren, John Robert and Krista N. Jenkins. “High Stakes Graduation Tests and High School Dropout in Texas and Florida, 1979–2001.” Sociology of Education

27. Western, Bruce, Jeffrey R. Kling, and David F. Weiman. “The Labor Market Consequences of Incarceration.” Crime and Delinquency Vol. 47, (July,

28. Zabala, Dalia, Angela Minnici Dr., Jennifer McMurrer, Deanna Hill Dr., Alice P. Bartley, and Jack Jennings. State High School Exit Exams: Working to Raise Test Scores. Washington, D.C.: Center on Education Policy, Sept. 2007.



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____________________________________________________

INTRODUCTION

Individuals, as market participants, constantly make decisions about when to purchase and what to purchase, from groceries to mutual funds to newspapers. At the same time, individuals must decide when, if ever, they wish to sell these assets. Behavioral economists have shown that individuals violate assumptions of rationality for both purchase and sale decisions such as the disposition effect (Shefrin & Statman, 1985), where individuals sell appreciated goods more frequently than depreciated goods.

This paper presents an experimental investigation of the disposition effect, and more generally, an individual’s propensity to sell assets. The motivation for this paper is to test an anecdote from Colin Camerer

effect: they sold or realized winners and held losers1

swapped positions to de-bias traders and allow them to cut their losses. Camerer claimed: “The new traders feel less emotional attachment to the new position they inherited from the other trader … and exhibit less or no disposition effect” (Camerer, 2003, p.15). Through a natural stock experiment, this paper directly tests the strategy of limiting investors’ disposition effect through the removal of purchase responsibility.

The experiment consisted of two tasks: an investment choice task and a sell/hold decision task. The investment choice task asked participants to invest in 3 companies of their choice from a twenty-company portfolio. The responsibility of the undergraduate participants was manipulated by allocating them 3 more stocks from a different twenty-company portfolio. After a week of market trading individuals could hold or sell a stock and after another week of market trading, all stocks were liquidated and returns were calculated. Evidence of an effect of responsibility on the disposition effect was not strongly supported.

In addition to illustrating the motivation for this study, Camerer’s

relationship between sophistication and the disposition effect in professional traders. The linear relationship is challenged by the contrast between the reverse disposition effect among unsophisticated participants and the lack of a disposition effect for more sophisticated participants.

This leads to a proposal of a non-linear relationship between investor sophistication and the disposition effect, based upon involvement of self-image in the investment task. Gender effects were also found: males were much more willing to sell a stock than females, consistent with literature on

LITERATURE REVIEW

tendency to “sell winners too early and ride losers too long.” The theoretical proposal of the disposition effect was supported on the aggregate market level by Lakonishok and Schmidt (1986) and Ferris, Haugen, and Makhija (1988) who showed that trading volume was higher for stocks whose prices had increased than for stocks whose prices had decreased. Odean (1998)

of 10,000 accounts at a large discount brokerage from 1987-1993, winners were more than 50 percent more likely to be sold than losers.

The disposition effect has been replicated within the U.S. (Dhar & Zhu, 2006; Barber, Odean, & Zhu, 2003) and can be characterized as prevalent in professionals and across different types of markets, countries, and experiments. (Heath, Huddart, and Lang, 1999; Hartzmark & Solomon, 2007; Genesove & Meyer, 2001; Crane & Hartzell, 2007; Bremer & Kato, 1996; Grinblatt & Keloharju, 2000, 2001; Shapira & Venezia, 2000; Chen, Kim, Nofsinger & Rui, 2004; Shu, Yah, Chiu, & Chen, 2005; Choe & Eom, 2006; Brown, Chappel, Silva, Rosa, & Walter, 2006). In addition to the vast

Camerer, 1998; Chui, 2001; Weber & Welfens, 2006; Camerer & Weber, 1998; Oehler, Heilmann, Läger, & Oberländer, 2002).

The disposition effect has also been studied in professionals who are assumed to operate as rational agents able to correct the errors of naïve investors and have a larger market impact (Locke & Mann, 2000; Frino, Johnstone, & Zheng, 2004; Jordan & Diltz, 2004; Garvey & Murphy, 2004; Coval & Shumway, 2005; Garvey, Murphy, & Wu, 2007). While more

BENJAMIN T. WRIGHT**Corresponding author: Harvard College ’08; Bain Capital

111 Huntington Ave. Boston, MA, 02199; [email protected]



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laboratory have generally shown a negative relationship between investor sophistication and the disposition effect (Feng & Seasholes, 2005; Shumway & Wu, 2005; Brown, Chappel, Da Silva Rosa, & Walter, 2006; Dhar & Zhu, 2006; Weber & Welfens, 2006; Krause, Wei, & Yang, 2007).

The disposition effect is costly to investors, and affects market prices. Odean (1998) showed that disposition behavior is irrational since sold winners have an excess return that is 3.4 percent more than held losers.

no predictive value. Several studies have shown that disposition investors cause stock prices to underreact to news yielding return predictability and post-announcement drift (Goetzmann & Massa, 2003; Grinblatt & Han 2005; Frazzini, 2006).

There is both theoretical and empirical evidence that some investors exhibit behavior contrary to the disposition effect by holding winners and selling losers. This reverse disposition effect may result from mental integration or segregation of outcomes. Thaler and Johnson (1990) proposed the house money effect, where future losses are integrated with a previous gain, resulting in risk seeking behavior such as holding winning assets. Outcomes following a loss, however, are segregated resulting in risk aversion and the sale of losers. Empirical evidence includes examples of the reverse disposition effect across assets and investors (Krause, Wei, & Yang, 2007; Ranguelova, 2001; Cici, 2005; Ivkovic & Weisbenner, 2006). Other studies found a minority group that exhibits a reverse disposition effect (Oehler, Heilmann, Läger, & Oberländer, 2002; Weber & Welfens, 2006).

THEORY

Researchers have proposed several psychological hypotheses for why an individual might realize or sell more winners than losers. These hypotheses fail to capture the full extent of the disposition effect. A theory based upon

experimental test of the disposition effect.The most widely accepted and cited explanation of the disposition effect

comes from the combination of prospect theory (Kahneman & Tversky, 1979) and mental accounting (Thaler, 1985). The disposition effect arises from prospect theory through risk averse behavior in the domain of gains and risk seeking behavior in the domain of losses. The prospect theory explanation relies upon the theory of mental accounting in order to describe when prospect theory can be applied to compound outcomes rather than just single choices (Thaler, 1985). Several studies have criticized prospect theory as an explanation of the disposition effect because under prospect theory, individuals who show the disposition effect would not purchase the

Hens & Vlcek, 2006; Barberis & Xiong, 2006).Mean reversion could also drive disposition behavior because if an

investor believes that a losing stock will increase in value and winning stocks will decrease in value, they will pursue a contrarian strategy, consistent with the disposition effect. However, empirical evidence discredits mean reversion as an explanation of the disposition effect (Odean, 1998; Barber & Odean, 1999; Chui; 2001).

disposition effect because individuals who seek to avoid regret will hold onto a losing stock with the hope that it will go back up. While the regret hypothesis has a theoretical grounding, empirical support is lacking and criticisms of the theory have surfaced (Fogel & Berry, 2006).

The weaknesses in the previously outlined explanations for the disposition effect motivate this paper to experimentally test a relatively untried framework based on entrapment. This hypothesis has many moving parts but can be summarized as follows: individuals become entrapped in a losing

course of action, such as holding a losing stock, as a result of escalating commitment and sunk costs. Escalation of commitment and entrapment

previous decisions with current ones. This need to justify results directly from cognitive dissonance, which is moderated by choice responsibility.

Zuchel (2001) formally suggested that the disposition effect might arise from individuals staying with failing courses of action based upon entrapment, escalating commitment, and sunk costs. Entrapment occurs when an individual, over repeated one-shot decisions under uncertainty, does not deviate from a losing course that includes high sunk costs (Staw, 1981; Brockner, 1992). Escalation of commitment is an increased investment in a losing course in an effort to recoup losses, often resulting in entrapment as sunk costs increase. Investment decisions parallel cases of entrapment because the purchase, holding, and sale of an asset are a series of one-shot decisions under uncertainty, where negative feedback escalates commitment.

Individuals escalate their commitment to a losing course as a result of a

with current decisions (Brockner, 1992). “[P]eople do not like to admit

the correctness of those earlier decisions than by becoming even more committed to them” (Brockner, 1992, p. 41). The need to justify previous decisions comes from a desire to avoid cognitive dissonance. Festinger (1957) summarizes the theory of cognitive dissonance in three points:

elements.2. The existence of dissonance gives rise to pressures to reduce the

dissonance and to avoid increases in dissonance.3. Manifestations of the operation of these pressures include behavioral

changes, changes of cognition, and circumspect exposure to new information and new opinions. (Festinger, 1957, p. 31)

dissonance. An individual considering a losing investment is confronted with the cognition that the asset is performing poorly. This cognition is dissonant with the belief that the individual is a skillful investor who can pick winning assets. The individual feels dissonance, which drives a need to justify the original behavior of purchasing the stock. Investors, motivated to remove this uncomfortable dissonance, will seek to justify the cognitions by rationalizing the initial decision to purchase the stock. By forging new cognitions that the stock will increase in value or that the losses are temporary, the investor regains consonance and holds the stock. Changing the belief is less costly than the behavioral change of selling the asset.

Responsibility for the course of action plays a crucial role in moderating an

Festinger’s (1957) theory by arguing that cognitive dissonance arises when an individual has a commitment with responsibility. Zuchel (2001) proposed that the disposition effect is most likely to be found when an individual is responsible for an initial purchase decision because both entrapment and cognitive dissonance are more likely.

Experimental support for an interaction of responsibility and the disposition effect is mixed (Weber & Zuchel, 2005; Weber & Camerer, 1998). Chui (2001) showed that individuals who had a more internal locus of control were more likely to display the disposition effect than individuals who had a more external locus of control, consistent with the idea that a more internal locus of control yields a feeling of greater responsibility, which in turn leads to need to justify and the disposition effect.

Jin and Scherbina (2005) tested the effect of responsibility on the disposition effect in mutual funds by comparing funds that changed managers with funds that did not change managers. Mutual funds that made a full change of managers were more likely to sell losers than funds that did not change managers. However, new managers also sold more winners



ECONOMICS

so it is unclear if they were still susceptible to the disposition effect or just turning over the old portfolio. asldkfa sdfkasd

HYPOTHESES

This study seeks to build on the mixed evidence of Weber and Zuchel

hypothesis by manipulating responsibility for the choice of stocks. The proposed study presents an experimental scenario in between the

unrealistic experimental study of Weber and Zuchel.

previous decisions with current decisions only for stocks that they purchased. In other words, individuals will feel a stronger need to justify their purchase decisions for chosen stocks and as a result will hold more chosen losers than allocated losers and realize more chosen winners compared to allocated winners.

Hypothesis 1: Individuals will hold more losing stocks and sell more winning stocks when the stocks are chosen compared to when they are allocated. The disposition effect will be greater for chosen stocks compared to allocated stocks.

Hypothesis 2: Participants with high investment sophistication will show a smaller disposition effect than participants with low investment sophistication by holding more winners and realizing more losers.

METHOD

. The experiment was conducted in February 2008 and consisted of nine market trading days. The study was conducted through email: participants were recruited via emails to Harvard upper class dormitory email lists as well as the introductory economics class list. Participants were required to return a consent form and provide

study, gender, and address. Participants were then asked to complete the investment task.

After one week of market trading participants had to complete their sell/hold decisions. After one more week of trading, total returns were

their compensation. A follow-up email was sent to participants in order to measure investor sophistication through four questions about their absolute

scale as well as the number of years of investment experience and the time to the nearest minute spent on the experiment.

The remaining sample consisted of 69 individuals, resulting in a total attrition rate of 51%. The mean age was 19.9 years old. Gender distribution was even with 50.7% of the participants being female. The sample consisted of 31.8% economics concentrators and the average participant was in his or her 3rd year of study. Participants had a mean investment experience of 0.69 years (0-12 year range, =2.0). Participants rated themselves as having slightly below average absolute

=1.3) and

=1.4).

Each participant was endowed with $5 to invest equally in 6 real companies. In order to test Hypothesis 1, participants were asked to choose 3 companies from a portfolio of 20 to invest in and were allocated 3 companies from a different 20-company portfolio. The two 20-company portfolios were created by randomly allocating stocks from an overall portfolio of 40 companies.

Once the two portfolios were created, participants were randomly allocated to choose from one of the two portfolios. Accordingly, each group of participants was then allocated stocks from the portfolio that the other group chose from, controlling for differences in the portfolios.

Participants were emailed a document with a series of one-page long descriptions of 20 companies in which they could invest. All information in the company summary was public and drawn from Yahoo! Finance. Summaries of companies included the company name, the stock symbol, a graph of the stock’s price over the last year, a business summary, and the names of the competitors. In addition, participants were encouraged to research the companies elsewhere in order to amplify their cognitive investment in the choice task and increase their perceived responsibility for the choice.

The 40-company portfolio was created in order to provide a diverse universe of companies along four dimensions: historical performance, beta, price to earnings ratio, and market capitalization. Using the Yahoo! Stock screener and the Morningstar Stock screener, 5 stocks were selected from each extreme (high and low) of each dimension while attempting to ensure a diverse mix of industries and a representative sample of American stock exchanges.

via email, and asked whether or not they would like to hold or sell each individual stock in their portfolio. Participants were not able to replace the stocks that they sold in their portfolio, because the decision to sell a stock must be isolated from the decision to buy a different stock. Participant compensation was determined by the percent return of a stock. The percent returns across all six stocks was summed and multiplied by 100. Total compensation was the sum of the market return applied to the $5 investment (a negative 5% return would wipe out the $5 investment) and $2 compensation for participation.

RESULTS

The disposition effect can be analyzed using several methods. Logit regressions provide the most basic evidence for the impact of group

effects logit regressions as well as ratios of the proportion of gains realized

For the logit regression, the dependent variable is binary with sell = 1, and hold = 0. I ran two series of logit regressions that differ only in the measure

winner, codes a stock’s performance, uses

the percent change in price as a measure of the return of the stock. The fundamental difference between these two measures depends on how the individual mentally codes changes in prices. The regression results for these

on winner. Regression 12: P(Sell = 1) = F ( 0 + 1winnert + 2chosen + 3economics + 4 female +

5log(size)t-1 + 6peratiot-1 + 7upwardtrendt-1 + 8momentum + 9contrarian + 10economics*winnert + 11economics*chosen + 12know + 13know*chosen +

14know*winner) Table 3 shows that winner, female, economics*winner, and know*winner are all

winner: z = - 5.85, p < 0.0001; female: z = - 2.27, p = 0.023; economics*winner: z = 2.20, p = 0.028; know*winner winner is negative, showing evidence of a reverse disposition effect: since when a stock was in the domain of gains it was less likely to be sold. Females were less likely to

know*winner, which suggests that individuals with higher perceived sophistication were more likely to sell a winner and thus were more likely to exhibit the disposition


M a n u s c r i p t s

51

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effect.

DISCUSSION

Experimental evidence does not suggest that the choice manipulation affected the propensity to sell a stock. The responsibility distinction may not have been salient because participants were sent their performance without distinguishing between chosen and allocated stocks. Mental accounting for participants may have occurred at the time of choice but did not linger to

sell stocks likely is stronger in real markets because individuals invest more time in making higher stake decisions over longer horizons.

. gender on the propensity to sell with males being more willing to sell a stock than females. Previous literature has shown contradictory evidence for the effect of gender on the propensity to sell a stock. Barber and Odean (2001) show that men trade 45% more than women. Krause, Wei, and Yang (2007)

are more willing to sell losers. However, Grinblatt and Keloharju (2001)

propensity to sell. The results of this experiment directly support Barber and Odean.

Overall, the reverse disposition effect was found among the majority of participants. An analysis of post hoc explanations demonstrates that the reverse disposition effect most likely did not arise from the experimental context but rather suggests that the disposition effect is limited to certain subsets of the population. Several characteristics of the experimental design such as description format, low reward, and few trading periods may have resulted in momentum trading and the reverse disposition effect. The description format of the experiment may have resulted in the house money effect following gains. Weber and Zuchel (2005) showed that the house money effect dominates when investment decisions were framed as a two-stage betting game while the escalation of commitment dominated in a portfolio allocation frame. My experiment used a hybrid description similar to both frames. Barberis and Xiong (2006) found the reverse disposition effect when the number of trading periods was low similar to the presented study. Krause, Wei, & Yang (2007) found a reverse disposition effect when the market return was low, consistent with the results of this experiment.

The differences in the reverse disposition effect across levels of sophistication discredits these explanations and instead suggests other explanations for the reverse disposition effect. If unsophisticated individuals believe in momentum in stock price movements, price decreases will lead to loss realizations before the price continues to slide. Similarly, a winner is held in anticipation of momentum. However, individuals who purchased

stock sale decisions. Building on the reverse disposition effect literature and the self-

show the disposition effect: self-image. The reverse disposition effect could have resulted from the interaction between cognitive dissonance and self-image. Self-image is the set of self-schemata or ideas that individuals maintain about their personal characteristics. Larrick (1993) argues that individuals attempt to maintain a certain self-image, which can often lead to entrapment. If a task is highly relevant to one’s self-image, one may maintain a losing course of action simply to preserve that image. This theory extends cognitive dissonance from the internal dissonance one feels as a result of inconsistency of beliefs and behaviors to the inconsistency that can exist

For example, an individual with a self-image of being a good investor may neglect to realize a losing stock (disposition behavior) in an effort to avoid producing a behavior that undermines the self-image of being a good investor (selling a good stock). The reverse disposition effect may arise when a task has no personal relevance to an individual’s self-image. A lack of self-image involvement frees the individual from feeling cognitive dissonance and makes

Table 1. Where age is a participant’s age in years, year is a participant’s year of graduation, time is a participant’s self-report of time spent on the experiment, invexperience is the number of years a participant has invested in mar-kets, female*economics = 1 if the participant is both fe-male and studies economics, chosen*winner = 1 if the stock both increased in value and was chosen by the participant,

momentum trader and the particular stock has increased in value.

M a n u s c r i p t s


ECONOMICS

behavioral changes to reduce dissonance less costly. This theory mirrors the theory of responsibility as a moderator of the disposition effect.

. The support for an explanation of the reverse disposition effect based on involvement of self-image is rooted in the rejection of Hypothesis 2. The experimental evidence strongly shows that more sophisticated participants,

hold losers more readily than unsophisticated participants. However, it must be stressed that the experimental design does not provide a direct measure

involvement across sophistication levels and conclusively prove that self-image cause this relationship.

A good proxy for self-image involvement is the length of purchase rationalizations. Sophisticated individuals did seem to be more involved in

stock (23.5 words compared to 15.3 words for unsophisticated, t = - 2.27, p = 0.0265). While there is some empirical support that self-image involvement may drive the reverse disposition effect, it is important to stress that the theory has yet to be tested directly.

The argument for involvement of self-image in creating a reverse disposition effect also leads to a new relationship between sophistication and the disposition effect. In contrast to Hypotheses 2, sophisticated participants, actually show a relatively larger disposition effect (smaller reverse disposition effect) than unsophisticated participants. While the majority of disposition effect literature asserts that sophistication causes the disposition effect to decrease, the results presented suggest that the relationship is more complicated (see Figure 1 and 2). The nonlinear relationship between sophistication and the disposition effect hinges on distinct mechanisms that operate on different segments of the investor sophistication dimension: self-image for low sophistication and learning for high sophistication.

yield a positive relationship with the disposition effect as demonstrated by the results of this experiment. More sophisticated investors have higher

to invest more time, cognitive effort, and emotion in each purchase decision. This temporal, cognitive, and emotional investment in each decision leads sophisticated investors to tie their self-image more closely to the performance

of the stock. As a result, sophisticated investors feel a stronger need to justify past decisions with current decisions, leading them to hold more losers and sell more winners. Unsophisticated individuals invest neither their money nor their self-image in the market, and as a result display the reverse disposition effect.

At levels of high sophistication, the literature shows a negative relationship between the disposition effect and sophistication. This decrease in the disposition effect can been explained as learning by rational agents. Professional investors observe their own disposition behavior, appreciate its costly nature, and thus take action to reduce it in an effort to

of doing so are most salient. The learning may also arise subconsciously as professionals simply steer away from that behavior without cognitively

The proposed non-linear relationship between sophistication and the disposition effect is not a careless extrapolation of experimental results but is supported by the narrow sampling of existing disposition effect literature. No studies have investigated the disposition effect in individuals who are not market participants or have some sort of business or economics background. As a result of the self-selection of participants

sophistication or experience. Experimental literature of the disposition effect only provides one

sample that is representative of my experimental sample. Most student participants have largely been more sophisticated and familiar with

students (Weber & Camerer, 1998; Chui, 2001; Oehler, Heilmann, Läger, & Oberländer, 2002; Weber & Zuchel, 2005). Weber and Welfens (2006) had a sample with half of the participants studying economics and business administration. Depending on the task, 21-44% of participants demonstrated a reverse disposition effect buttressing the robustness of the evidence of the reverse disposition effect and the theory of investor sophistication presented in this study. In addition to the sample bias in

other empirical papers (Krause, Wei, & Yang, 2007; Chen, Kim, Nofsinger,

Figure 2. Experimental relationship between investor so-phistication and the disposition effect

Figure 1. Model of the relationship between investor sophisti-cation and the disposition effect



53

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& Rui, 2004). The self-image explanation lacks direct empirical support but serves as

a catalyst for future research. The robustness of the reverse disposition effect in unsophisticated investors, and the relationships among self-image,

relationship of investor sophistication and the disposition effect can be directly tested through an experimental investment task using uneducated

market participants. Another study could manipulate sophistication

participants would show a larger disposition effect relative to untrained participants since overall levels of sophistication are low. Experimental research can directly manipulate self-image involvement to test the proposed role it plays in moderating the disposition effect. Self-image could be manipulated through priming individuals as a good or poor investor. This study serves as a catalyst for further research that would expand the understanding of the disposition effect and its relationship with sophistication and self-image.

As is typical with most experiments, external validity issues challenge the extrapolation of the results to real markets. For example, the limited downside (a 5% loss wipes out the entire investment) may have led individuals to practice extreme loss aversion for losing investments, resulting in the reverse disposition effect. The presented study, however, is very similar to the stock market by tracking the performance of real companies. While the experiment is natural, it was not representative of real markets in several ways.

CONCLUSION

explanation of the disposition effect. Participant responsibility for stock choices was manipulated in order to vary the need to justify past decisions,

for the role of responsibility in moderating the disposition effect was not found. A gender effect appeared in the study as males traded more than

investors. As a result of the rejection of hypothesis 2, the relationship between

non-linear relationship. Unsophisticated individuals show a reverse disposition effect but as sophistication increased, individuals engage in disposition behavior possibly because of the effects of self-image. Once sophistication becomes very high, learning takes over and the disposition effect decreases with sophistication.

This study presents evidence of a reverse disposition effect and for

relationship not only challenges the literature but also suggests that unsophisticated individuals can make better investment decisions than active individual investors and even professionals. As a result of less investment of self-image, these unsophisticated individuals may actually

losers and sell their winners. Only at the very high extreme of experience and sophistication can individuals overcome the disposition effect, and

than these unsophisticated individuals who are often not even market participants. Even in the stock market, ignorance may be bliss.

1Presented in a paper at the Federal Reserve of Boston conference on “How Humans Behave” in 2003

2 Where F(x) = (1 + e-x)-1 is the cumulative logistic probability function, winnert = 1 if the stock return was positive at time t , chosen =

1 if the stock was chosen by the participant rather than allocated, economics = 1 if the participant is concentrating (primary or secondary) in economics, female = 1 if the participant is female, log(size)t-1 = market capitalization of the stock at time t, peratiot-1 = price to earnings ratio of the stock at time t-1, upwardtrendt-1 = 1 if the stock return is positive over the last 12 months at time t-1, momentum = 1 if the participant gave a majority of momentum explanations for stock purchase decisions, contrarian = 1 if the participant gave a majority of contrarian explanations for stock purchase decisions, economics*winnert = 1 if a stock has a positive return at time t and the participant is an economics concentrator, economics*chosen = 1 if the participant is an economics concentrator and the stock was chosen, know is

1-7 scale yielding a range of 2 – 14, know*chosen is the interaction of know and chosen, and know*winner is the interaction of know and winner.

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The automation of metrics useful in evaluating the regeneration of skeletal muscle

SAMMY SAMBU*

*Corresponding author: Harvard College ’08; [email protected]

between semi-automated histological metrics and traditional manual metrics used to evaluate tissue regeneration. The semi-automated techniques utilize a combination of image processing functions and libraries that are available on open source programs and commercial software. Additionally, we hypothesized (secondary hypothesis) that for the in vitro sample conditions that closely approximate the most regenerative in vivo conditions per histological examination, computational models of in vitro cellular migration would yield maximized parameters for cell speed and persistence time. Hence, if this latter assertion were proven true, the ability to use dynamically acquired image attributes to evaluate the regenerative potency of different sample conditions would have been shown to be feasible.

The above hypotheses posit the ability for digitized image attributes such as target area, circularity, location, feret width, pixel co-occurrence, textural correlation and spatiotemporal pixel positioning to yield trends similar to those derived from a manual examination. To gauge the level of similarity, a Spearman rank correlation analysis was performed between results from the digitization of regenerating tissue images and results from manual examinations. Hence, it shows that there is a correspondence

p-value and thence, whether the relationship is inverse (shown by a negative sign value) or direct (a positive sign value). All data and resultant information presented here are uniquely associated with regenerating tissue architecture. The automated metrics yielded highly-to-perfectly correlated results when compared to traditional metrics. Computationally modeled cell migration data

rejected.

INTRODUCTION

The National Center for Health Statistics estimated the 2002-2004 average annual direct and indirect costs for the treatment of musculoskeletal diseases in the US at $849 billion.1 Comparable costs in developing nations approach $100 billion.2 Research into skeletal muscle disease and degeneration could unearth solutions to lessen annual expenses related to these problems.

To increase the pace of research into musculoskeletal diseases, one can automate the processes involved in evaluating skeletal muscle regeneration. Metrics traditionally used to evaluate the regeneration of skeletal muscle include linear nuclear density1

is a clear necessity for research into musculoskeletal diseases, the automation

approaches in skeletal muscle regeneration are a common feature in journal

automated analysis of results from experiments in regeneration.19

Regeneration is broadly summarized in six steps3

of necrotic tissue4 5

6 through biochemical and/or biomechanical cues7 8

myoblasts into myotubes8 8 To estimate the number of myoblasts participating in processes 3-6 above,

subjectivity in selections. The alternative proposed in this report is the semi-

to inspect perceptible attributes unique to each sample condition. Later, to test the secondary hypothesis, it is recommended that myoblast migration be modeled to identify the best conditions for regeneration.

Background.

9

modulate cell function i.e. cell migration and the maintenance of cell viability through biomechanical cues.10,11

sulfate dehydrate. Pure alginate hydrogels exhibit little cellular interactions;

most nuclei centrally located. Centrally-located nuclei are a

a streak of centrally-located nuclei



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12

at physiologic concentrations,13

14 In short, alginate deters hyperplasia.

instance, both factors have angiogenic roles in addition to mirrored roles in myoblast migration, differentiation and survival.15,16

165hence selected for use on the impregnated scaffolds. It should be noted that

an interesting investigation, it is not the subject matter of this paper.


2.2 The ischemic model

by severing and ligating femoral arterioles and veins on a single hind limb in

approved the animal study protocols. 2.3 The injectable alginate scaffold

2.4 The administration of growth factors

injectable alginate: 3 165: 3 165 injectable alginate: 3 Phosphate

165: 3

2.5 The semi-automation of metrics

stains structures containing nucleic acid, such as nuclei and ribosomes. Only

automatically determined. In general, semi-automated metrics utilize target characteristics such as area, shape, location, intensity, texture and distribution.

automatically determined results. 2.5.1 Procedures for identifying and tallying centrally-located

nuclei Point-by-point procedures for manually counting nuclei are provided

Procedures for performing semi-automatic nuclei counts are provided in

The semi-automated process uses a combination of target characteristics including the target’s area, shape and location on the image. Furthermore,

is thresholded. Targets on the edge of the image are eliminated to exclude truncations and peripherally-located nuclei.

In particular, using Feret’s diameter2

Figure 3. A sample histological image from a regenerating

Figure 4. A sample histological image from a non-regenerating sample

corresponding to the local maxima in the correlation curve approximates the

ji ji

jijjii p,

),())((ss

mm

2.5.3 Textural analysis Textural analysis refers to deduction of patterns in the occurrence of distinguishable elements on a given image. It is “the



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19

nucleus is variable.

the outlines, the ratio of area to square perimeter is obtained and multiplied

the area of the image. 2.5.5 The cell migration model To determine the best sample conditions

modeled.

density of 3E5 cells/ 0.2 cm3

up is illustrated in Figure 6. Imaris

chosen to model the migration of myoblasts perpendicular to the reference line. It is demonstrable that the mean speed and persistence time3 account for the effects of chemotaxis and chemokinesis.17

RESULTS

3.1 The semi-automation of metrics3.1.1 Manual & semi-automatic nuclear densities are highly

correlated

-

))1((3 22 pt

ePtPsd

Figure 6. A diagrammatic representation of the set up used to

determined by carrying out a nonlinear re-gression using the values t, s and d2 supplied by the empirical results from the in vitro model.

Figures 7A & 7B. Counts at the end of the 2nd and 7th weeks.

A

B

manual results contrasted against the semi-automated results. In both analyses, 165

higher linear nuclear densities than the administration of either one of them



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defense of the similarity in the semi-automated and manual measurement of

correlated. This means that trends observed in manual evaluations by trained

feature against the stained cytoplasmic background is the streak of nuclei.

increasing offset. Hence, high correlations typical of near-zero offsets are

of nuclei in the corresponding image. It is expected that this method can be applied to all tissue sections regardless of the centrality of the nuclei if the staining for the endomysium4

process. Indeed, this measurement method could be a technique for measuring

more accurate than longitudinal measurements While longitudinal

to be measured using specimen cross-sections because cross-sectional measurements are of a higher accuracy than longitudinal measurements of

intensity, circularity and connectivity are accounted for. Only longitudinal

While linear nuclear densities

widths Similar to the semi-automation of the measurement of linear nuclear

quantifying errors for standardized inputs.

corresponding to the highest peak in the correlation-offset graph is a valid

Note that the semi-automation technique uses the code given for tex2 in

peak corresponding to an analysis of a longitudinally sectioned image. The peak occurs at the 22nd offset (translates to 26 µm since 1 offset equals approxi-



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to the effectiveness of the condition over the other 165

viability of these cells leading to a successful fusion of migratory myoblasts

3.1.3 Textural analyses of sample images may reveal the underlying regenerative process

be used as a metric for regeneration.

y = 0. The lack of peaks in the poor-performing specimens is indicative of the lack of tissue dynamics typical of regenerating tissue since nuclei are not

imperceptibility of a pattern. In contrast, regenerating tissues have relatively

weeks and at 7 weeks measured manually and

A

B

Figure 12. A graph of correlation against horizontal offset. Better-performing scaf--

conditions. IGF-1 diffusing from alginate scaffolds has a remark-



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Textural analyses capture patterns on longitudinally-sectioned histological images indicating the extent of regeneration. Textural analyses therefore utilize information gathered from the full image matrix for longitudinal sections. While histological cross-sections exhibit no such pattern, they have

unaccounted for in the preceding analyses. For instance, other than ,

progress

progressively circular in the other sample conditions. In order to capture this

against each other.

tissues, the net change in each specimen’s mean circularity above the control

highest change in circularity above the baseline. The circularity of regenerating samples approaches 1 as regeneration peaks may be due to a change in the cellular surface morphology, decreased cell movement or both.

circularity measurements gave an SRCC of 0.667 and a p-value of 0.15. The

3.2 General commentary on semi-automated histological analysis

that are stained for the human eye, the poor adaptation of histological techniques to fully computerized procedures rendered the task an arduous

program requirements: to perform semi-automated histological analysis, the staining process must distinguish as many targets as are necessary for semi-

4.1 Myoblast migration parameters reveal pro-regenerative conditions

markedly higher than normal. For the latter, manual measurements are less

The solution may be to fortify the conclusions from histological analysis by identifying and modeling a key cellular-fate process underlying regeneration.

165alginate sample condition consistently had the highest indication of

165 and

vivo.18 The cell migration assays demonstrated that realized a high

condition Figure 16. Mean persistence time against sample condition using



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condition had a high persistence time and cell speed. Hence, it is

The choice of the PRW model

matlab command, nlintoola non-linear regression to the data. Using nlintool

data in a given track could be explained by the PRW model. Hence, the model

The PRW

derived and may carry over errors in the tracking process. Cell speed may be

Lastly, using Markovian models may provide more information regarding migration such as probabilities for movements in different directions and the nature of rhythmic migration.

4.2.2 Using cell-seeded scaffolds derived from experiments that used acellular scaffolds. This investigation

165

participatory host cells for regeneration is uncertain. Provisions for donor

involve the use of cellular scaffolds.

DISCUSSION

during the development of automated cytology has proven too simple to apply directly to the images of complex tissue.19

20,21 In

analyzing tissue regeneration. This investigation stands to impact the techniques employed in regeneration

techniques for measuring the regeneration of muscle tissue and overall, a

the entire investigation reproducible because image analysis is more objective. While the end points are similar to those intended in other endeavors in automating tissue regeneration, there are differences in the approach herein.

the patterning that underlies the increase in tissue architectural complexity. This latter direction looks at the utilization of somatic space via scalars like

seen in textural analyses.

are attributed to the high connectivity of targets in certain specimens.

observed in manual counts are reproduced in the semi-automated counts.

eight-point connectivity improved the ability to distinguish highly connected

the endomysium. Thereafter, semi-automated measurements may approach

for regeneration-associated changes may have been the basis for the ranking

regeneration progresses. Therefore, textural analysis can help distinguish

-



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In addition to the analysis of histological sections, this article recommends

strategies adopted in regenerating skeletal muscle. For instance, the application of the PRW model for cell migration to the movement of a population of

165 delivered via

maximized parameter-pair of migratory cell speed and persistence time. Previous research in the migration of MM14dy myoblasts on composite

5,22

In summary, this project has implications on the methods usable by researchers in skeletal muscle regeneration. Semi-automated histological

from semi-automated histological analysis by modeling a cellular-fate process that is essential to regeneration. These lessons can be transferred to other

FOOTNOTES1 Refers to the linear density of centrally-located nuclei2

outline3 Mean speed refers to the average speed of the cell for the entire path length

4

5

REFERENCES

Med Sci Sports Exerc.Path

Res Pract

myogenesis. Current Opinion in Cell Biology

Development. 109: 943-952, 1990.Clinics in Sports Med.

Journal of Biomedical Materials Res. 60, 217, 2002

extracellular matrices for tissue engineering. Trends in Biotechnology.224-230

Journal of

Thrombosis and Haemostasis

controlling muscle development. Domestic Animal EndocrinologyOctober 1999 .

regeneration. Neurol Res

American Journal of Pathology

reciprocally and in a matrix-dependent manner. Journal of Cell Science 111: 2423-

Fibrin Scaffold Improves Cell Transplant Survival, Reduces Infarct Expansion, and Induces Neovasculature Formation in Ischemic Myocardium. Journal of the American College of Cardiology

sections. Comput. Biol. Med

Cytometry

University of Ljubljana, Slovenia.

Subfragment of Laminin Promotes Locomotion of Myoblasts over Extracellular Matrix. J Cell Biol.



NEUROSCIENCE

The effects of sleep on emotional recognition

STEVEN MCDONALD*

*Corresponding author: Harvard College ’08; Sleep and Neuroimaging Laboratory, Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical

School, Boston, MA 02115; [email protected]

While a vast number of studies have investigated the impact of sleep loss on cognitive faculties, no study to date has yet examined the

by examining how a daytime nap selectively alters an individual’s recognition of another’s facially expressed emotion. Participants rated a series

fear, sadness, anger, and happiness. After baseline measures, half the subjects (“nap group”) received a 90 minute polysomnography-monitored

fear at the later test. In contrast, the nap group shows no such increase in emotional sensitivity. Moreover, the nap group displayed an increased rating of happy stimuli following sleep. Most interestingly, only those nap subjects who achieved rapid eye movement (REM) sleep during the

that during the day, the human brain becomes emotionally unbalanced, showing a stronger sensitivity to negative affect. In contrast, sleep,

REM sleep, may prime or refresh the brain’s empathetic capacity for positive emotions, while redressing the balance for negative emotions.

INTRODUCTION

I. Sleep: a history. research subjected to most of human behavior. Although scientists do not possess a complete knowledge of sleep function, experimentation has enabled scientists to probe the effects of sleep on brain and body.

Until the 1950s the predominant theories about sleep assigned it a role opposite waking.1because of the paucity of meaningful memories and actions performed during

movement—rapid, jerky, and binocularly symmetrical,”2 REM sleep, upset

intermittent periods between bouts of REM sleep are now known as non-

to the anterior cingulate cortex, entorhinal cortex, thalamic nuclei, dorsal mesencephalon, and pontine tegmentum.5decreased activation during REM sleep in the posterior cingulate, dorsolateral prefrontal, and parietal cortices.5which posited activation of the brainstem, emotional limbic system, and associated anterior cingulate cortex during REM sleep.

of sleep. Intuitively, people need sleep and feel better having slept than not. Sleep deprived individuals can exhibit darker and more unstable moods and emotions than their well-rested counterparts. Since many emotions have associated memory traces, one ought to expect a close functional relationship between sleep and emotional state. Sleep in depressed individuals, for

7

Similarly, parts of the brain that are active during sleep also become active

5

II. Emotion: a primer.

transient neurological response to a given stimulus, which may be external or internal to the organism.7

of an emotion. Emotions such as fear and anger have negative valences

valence, representing a physiological state of activation. Given these valuations, emotions such as surprise have a high arousal value, whereas sadness occupies the other end of the spectrum with low arousal.

much of the neuroanatomical foundation of emotion to the limbic system. As originally conceived, the limbic system consists of a variety of structures including the thalamus, hypothalamus, hippocampus, cingulate cortex, amygdala, and, in its extended form, midline aspects

15 Debate still exists as to whether the minimal roles of certain limbic structures (i.e. the anterior thalamus)

15 While many stimuli may trigger emotional responses, the following will focus on emotional

focus on sadness, anger, fear, and happiness, since they were the emotions studied.

Emotional processes have precise neuroanatomical correlates in the brain. While the amygdala most strongly correlates with fear, it also has

orbitofrontal and cingulate cortices.19 Happiness shares some of the

activates during recognition of sadness and happiness. Activation in the ventral mesial frontal cortex appears to distinguish happiness from sadness.20 Happiness correlates with a depression of activity in centers for negative emotions such as the amygdala.19 Despite shared neuroanatomical centers, little research has examined sleep and emotion together.

III. The intersection of sleep and emotion. Very little knowledge



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exists regarding the interaction of sleep and emotion. Given the obvious, intuitive relationship between these two aspects, it is especially surprising how little research has focused on this intersection. Anecdotally, college students will testify to the increase in negative affect following a night of

causative relationship between each phenomenon. As stated previously, few studies have been conducted regarding this crucial intersection – the goal of my thesis. Given the overlap of cerebral architecture involved in sleep and

enhance the ability to recognize positive affect and modulate the ability to recognize negative affect.


I. Subjects.evenly divided between males and females. Subjects were asked to sleep seven or more hours on average prior to the beginning of the experiment and to avoid caffeine, nicotine, and alcohol. In addition, to prevent the interference of sleep inertia subjects were asked to spend at least three hours awake before beginning the experiment. We randomly assigned subjects to either the control or experimental (nap) groups.

II. Protocol overview.

reported to the Beth Israel Deaconess Medical Center (BIDMC) research psychiatry department for experimentation only for the duration of each

recording.

phase in the lab. Neither group spent the “SLEEP” phase in the laboratory.

III. Experimental task. In order to gauge emotional perception, we presented subjects with four sets of achromatic photos taken from a set of photographs collected for use in psychological experiments. Each individual set corresponded to one of four distinct affects (sad, happy, angry, and fearful) and contained 10 images ranging in a gradient spectrum from neutral to increasingly emotional, presented to subjects in a random order. I was therefore able to produce a curve (and mean) of emotional recognition responding to increased facial affect of four separate kinds: anger, fear, happiness, and sadness.

one of the emotions in random order, allowing them to appreciate the range of

the emotional spectrum they would rank. After this initial primer, a computer program randomly selected one of the four emotional categories, alerting the subjects to which emotional category was forthcoming, and proceeded to present the 10 gradient faces in random order, one at a time, and soliciting a

they found the face on a four-point scale: (1) neutral, (2) more neutral than

was repeated at each of the additional test session, with the exception of the

I. Sadness.

control and nap subjects to the sad faces decreased across sessions, but not t-test comparing the subtracted differences of all 18 control

groups (t=0.079, pII. Anger. Whereas the responses to sad faces changed little across either

group, the anger faces produced a much more pronounced effect. A student’s t

in response (t pIn contrast, the nap group exhibited a very

group. Unlike the control group, there was

period of sleep (nap) (t=1.12, p

whereby sleep interferes with some

anger perception.

(t=2.24, pincreased sensitivity to the perception of anger, while a daytime sleep period slightly ameliorated

at an interaction whereby sleep interferes with a

Figure 4. Mean subtracted difference scores (Test2-Test1) of the control and nap groups. Error Bars represent the SEM. Control (SEM=0.098). Nap (SEM=0.063).

Figure 5. Mean subtracted difference scores (Test2-Test1) of the control and

compared to the null hypothesis (t>2.03, pbetween groups (t>2.03,p<0.05). Error bars represent the SEM. Control (SEM=0.072). Nap (SEM=0.059).



NEUROSCIENCE

III. Fear. Despite an increase in the responses of control subjects, the

t=1.24, pmean decrease in response, as opposed to an increase. Nap subjects initially reported an average ranking of 2.97, which fell to an average of 2.81 in the

a t-test comparing the subtracted difference values of the control group against the

between group result (t=2.24, p

only prevents and counteracts a waking process which normally exacerbates the recognition of fear in faces, but actually appears to reduce it.

IV. Happiness.

t=1.15, p

t=2.06, p

t=1.98, p=0.056). Although the nap group showed an increase in sensitivity to happiness, a comparison of the difference scores between the control and the nap groups did not return a

t-test, t=0.875, pVI. The comparison of the REM and no-REM groups.

of sleep can vary considerably between individuals and even within individuals. We performed additional exploratory analyses of my hypothesis, isolating the REM effect.

minutes of REM sleep. However, of the 18 subjects only 8 achieved REM sleep while the remaining 10 subjects obtained no REM sleep at all. Due to the resulting large number of zero data points for REM sleep, a correlational approach to investigating the role of REM was unattainable. Instead, I

performed a mean split of the nap group based upon the average REM sleep amount (4.5 minutes) resulting in a comparison of those who achieved REM sleep (n=8) and those who did not (n=10). I called these groups the REM

who received at least some REM sleep (mean=10.1 minutes, SEM=0.596).

(mean=0 min, SEM=0). I was therefore able to re-evaluate the nap condition on the basis of REM versus no-REM, to examine whether the observed overall group differences reported in the nap group were being driven by a

VI.i. Sadness. A comparison of the no-REM and REM groups yields no

REM group was 0.007 (SEM=0.054). In contrast, the average REM group’s subtracted difference measure was –0.120 (SEM=0.151). A t-test comparing

both the no-REM group (t<0.26, p>0.8) and REM group (t<0.86, p>0.4).

the response to sadness.VI.ii. Anger.

group response increased from 2.50 (SEM=0.072) to 2.56 (SEM=0.050) (t p>0.2) in the second test, while the REM group average response increased from 2.76 (SEM=0.122) to 2.85 (SEM=0.084) (t>0.689, p>0.5).

to the null hypothesis, nor in comparison to the other (t<0.256, p>0.8). It is still

perception was mitigated in the nap group,

be due to REM.

VI.iii. Fear. In contrast to sadness and anger, the REM sleep split analysis revealed a difference for the emotion fear. While both groups demonstrated

to the null hypothesis, only the subtracted difference score (and difference in raw scores

REM group (t=2.57, p

the overall difference observed in the main analysis between the nap and control groups, describing a reduction in fear sensitivity with sleep, appears to have been driven most preferentially by those subjects who obtained REM sleep.

No-REM Group (n=10)

REM Group (n=8)

Nap Group (n=18)

Total Sleep Time (min)

REM Latency (min) 0Stage 1 (min)Stage 2 (min)REM (min) 0SWS (min)

Table 1. Mean duration and SEM in minutes of total sleep time, latency to REM sleep onset, stage 1, stage 2, REM, and SWS. Sleep

subjects actually spent asleep: (total sleep time/time in bed) * 100. Time in bed was 90 minutes.

Figure 6. Mean subtracted difference scores (Test2-Test1) of the control and nap groups. Error bars represent the SEM. Control (SEM=0.065). Nap (SEM=0.089).

Figure 8. Mean subtracted difference scores (Test2-Test1) of the no-REM and REM groups. ‘*’ indicates

null hypothesis (p<0.05). Error bars represent the SEM. No-REM (SEM=0.108). REM (SEM=0.067).

Figure 9. A) No-REM group mean responses to happy faces. Error bars represent the SEM. No-REM Test1 (SEM=0.116). No-REM Test2 (SEM=0.076). B) REM group mean responses to happy faces. ‘*’ indicates a between Test

p<0.05). Error bars represent the SEM. REM Test1 (SEM=0.131). REM Test2 (SEM=0.119).



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VI.iv. Happiness. Within the nap group, comparing the REM and no-REM groups reveals another remarkable and dissociable

increased sensitivity to happy faces, from 2.66

examining the subtracted difference scores, which for the no-REM and REM

t ponce again indicate that the main group differences between the nap group and control group is a difference driven substantially if not exclusively by the REM sleep.

VII. Summary. Considering the results in their entirety, it appears that sleep

of anger across continued awake hours. Responses to fear exhibited an interesting divergent result. Control responses are higher than baseline in the

difference between groups suggests that the nap not only abates the effects

happiness increased across trials and across groups; however the nap group

DISCUSSION

I.

Synopsis.Across an extended waking period, a marked increase in the sensitivity to aversive negative emotions of anger and fear developed (but not for sad). A

(2) In addition to the amelioration of negative emotional sensitivity, naps

group, particularly for the emotions fear and happy, appears to be strongly driven by REM sleep, since those subjects that napped but did not achieve

summarizes these points.II. Findings explainedII.i. Sleep and negative affect. Continued waking experience, without

within associated circuitry supporting negative emotions may cause this change in response. Areas germane to the production of anger include the orbitofrontal and anterior cingulate cortices. Studies debate the importance of the amygdala but consensus seems to indicate its activation is the exception not the rule in response to angry stimuli. A search for potential neural correlates of the substantial decrease in fear response inevitably leads to the amygdala – the gate linking fearful stimuli with fear responses.cortex and amygdala comprise part of the limbic system, the evolutionary seat of emotional response in the brain. All these aforementioned limbic areas – the orbitofrontal and anterior cingulate cortices, together with the amygdala – become markedly more active during REM sleep relative to NREM sleep

hypothesized “resetting” of the limbic system, preventing the development

perception of positive affect.

Figure 10 Mean subtracted difference scores (Test2-Test1) of the no-REM

-cance between the groups (p<0.05). Error bars represent the SEM. No-REM (SEM=0.115). REM (SEM=0.118).

Figure 11. Mean subtracted differences scores for the control and nap groups for all four emotions (fear, sad, anger, and hap-py). A “C” in the upper left-hand corner of the bar graph indi-cates a mean that corresponds to the control group. A “N” in the lower right-hand corner of the bar graph indicates a mean

subtracted difference as compared to the null hypothesis, which predicts no change from Test1 to Test2 (p<0.06). A “#” indicates

p<0.04). Error bars represent SEMs. Fear Control (SEM=0.099); Fear Nap (SEM=0.065); Sad Control (SEM=0.111); Sad Nap (SEM=0.072); Anger Control (SEM=0.098); Anger Nap (SEM=0.062); Happy Control (SEM=0.065); Happy Nap (SEM=0.089).

Control v. Nap Group Within Nap Group ConditionEmotion

Control Nap No-REM REM

Sadness – – – –Anger – – –Fear – –Happiness – –

Table 2. Emotional conditions are listed in the leftmost column. Experimental conditions are listed in the second row under the appropriate headings. The arrows and dashes represent how subjects’ responses to emotional faces changed from Test1 to

change (pchange (p<0.05). Upward arrows indicate increases from Test1 to Test2, while downward arrows indicate decreases from Test1 to Test2.



NEUROSCIENCE

Sadness’ singular place amongst the other negative emotions surveyed may give rise to this result. While fear, anger and sadness all share a negative valence (are negative emotions), only sadness holds a low arousal status.

emotion taxes the autonomic nervous system (high arousal emotions produce greater autonomic responses) may determine how REM sleep modulates the particular emotion. Looking at neurochemistry may alleviate the tension between these two sets of emotions (sad vs. fear and anger).

Since arousal is the key difference between sadness versus anger and fear, an examination of the differential effects on arousal of the waking and

anger and fear but not sadness. In REM sleep, the hypothalamic branch of the ascending arousal system (which depends upon monoaminergic

arousal. It may be this cessation of central aminergic arousal systems during REM sleep, combined with potential affective reprocessing within the limbic systems which are strongly activated during REM (perhaps through cholinergic stimulation), which results in a rebalanced set-point of the limbic brain following sleep. Such a mechanism would simultaneously explain the decline in affective sensitivity to anger and fear following sleep in the nap group, without an observed effect upon the emotion of sadness.

II.ii. Sleep and positive affect.

assuaged sensitivity to certain negative emotions, it dramatically increased the

this is a symbiotic effect, rather than an oppositional result: that the overall “goal” of sleep is to balance brain function towards a more positive overall affective disposition, rather than oppositely calibrating positive and negative

the nap group than for the control group. A similar increase occurred in the

recognition minimally during waking yet actively during REM sleep.

relate to that same process responsible for extinguishing increases in response to fear and anger. Happiness differs from anger and fear by its valence rather than its arousal (as with sadness): happiness is a positive emotion possessing

REM group and not the no-REM or waking groups. II.iii. The REM sleep effect.

emotional perception appears to be driven most precipitously by REM

stimuli similarly emphasize the selective importance of REM sleep to the modulation of affective brain processing, although in the opposite direction.

processing dynamics towards a less negative (fear) and more positive (happiness) appreciation.

ratings following the nap at test2 (r=-0.45, pthe difference measure was essentially zero). Moreover, this effect was not

p

NREM SWS a subject obtained, the lower the mean rating of anger there was

brain deactivation during SWS, or at least the partial reduction of aminergic tone in NREM (relative to wake), is associated with the amelioration of affective brain reactivity to anger perception. During SWS slow oscillations appearing as delta waves on the EEG emanate from the prefrontal cortex hyperpolarizing cortical neurons.authors postulate these waves to cause may “refresh” the prefrontal cortex –

the redressing of anger recognition that arises in nap subjects’ responses.In opposition to anger, the amelioration of fear responses does appear to

be mostly REM-driven. Compared to the null hypothesis (no change between

between fear and NREM SWS (either the subtracted change score from p>0.19).

Explanatory clues for this observed result may come from the extent of amygdala activation during REM – the seat of fear perception and possibly processing within the brain. Relative to a group that obtained a full night of sleep, a recent study demonstrated a hyper-sensitive amygdala in those

that one critical function of sleep may be to refresh the amygdala overnight, allowing controlled responses the next day – potentially due to a stronger top-

waking, even across the course of a normal day without intervening sleep,

stimuli. It is precisely this pattern of activity (increased fear sensitivity) in the control group yet decreased sensitivity in the nap group, especially those who

during REM results in a lowered set-point of reactivation upon awakening – potentially due to the strong aminergic demodulation of the brain during REM. Lowered aminergic activity would have this effect because autonomic brain (and therefore bodily) reactions depend upon aminergic activity.

effect. Nap subjects demonstrated a noticeable increase in sensitivity to this

group’s scores did not. At a mechanistic level, areas key to the recognition of happiness include the ventral mesial frontal cortex and the thalamus. It should be noted that the thalamic nuclei are particularly active during REM sleep,

during REM sleep could amplify happiness recognition circuitry after the nap phase. Alternatively, interactions between the areas responsible for negative affect and positive affect could ameliorate responses to happiness.

fashion. As an example, an individual typically feels one primary emotion at a

activity and corresponding strengthened cortical connections after sleep

of happiness.In addition, the effect was not uniform: sleep enhanced positive affect,

for sleep in affective regulation of the human brain, and by doing so, facilitate not only appropriate individual behavioral responses, but perhaps at a supra-ordinate level, appropriate societal functioning and interaction.

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