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A Shift in the Psychedelic Paradigm

Rayyan Darji and Anna Calame

New Yale research supports the therapeutic potential of psilocybin—a compound mired in decades

of controversy—to treat depression and other mental illnesses.

13 The Silent Mental Health Threats of


Shudipto Wahed

Yale researchers studied the impact of the COVID-19 pandemic on paranoia, gaining insights into its

origins in behavior and the brain.

16 Decrypting Dinosaurs of the East

Elisa Howard and Anavi Uppal

Millions of years ago, eastern North America was a landmass with its own flora and fauna. Did the

dinosaurs there evolve differently from those that lived elsewhere?

22 Birds of a Feather Color Together

Ryan Bose-Roy

Birds with non-iridescent blue feathers spontaneously make a nanostructure that can be used to

improve solar panels, paint pigments, and more, Yale researchers report.


Building a Battery Future • Jordan Sahly • 10

Colder and Wiser • Van Anh Tran and Madison Houck • 12


The Mathematically Perfect Egg • Eunsoo Hyun • 25

Bioethics in the Age of COVID-19 • Risha Chakraborty and Justin Ye • 28

A Tech Clairvoyant for Paralyzed Voices • Alex Dong and Malia Kuo • 32


Alumni Profile: Eric Y. Wang (YC ’21) • David Zhang • 35

Into the Newsroom: David Pogue ’85 • Dhruv Patel • 39


October 2021 Yale Scientific Magazine 3






By Crystal Liu

Wildfires. Heatwaves. Strong precipitation and floods.

Extreme weather has been exceedingly common

this decade, destroying natural ecosystems and

claiming hundreds of lives. Global warming has contributed to

its increasing prevalence, according to a new report from the

Intergovernmental Panel for Climate Change (IPCC). And this

trend will continue in the foreseeable future.

"It is unequivocal that human influence has warmed the

atmosphere, ocean, and land," read the report's very first

finding. Skeptics of climate change prefer to blame natural

factors, arguing that there is no need to change human behavior.

But scientific evidence has ruled out this fantasy.

The goal of the Paris Agreement was to limit global warming well

below two degrees Celsius. Earth is now 1.1 degrees Celsius warmer

than it was in the 19th century. Under current policies, the difference

will rise to 2.7 degrees Celsius by the end of this century. If rapid

and massive measures are taken, however, a relatively cooler future

is possible. Adopting more eco-friendly measures, like afforestation

and the usage of cleaner energy sources, can cap warming at two

degrees Celsius in the late-twenty-first century.

But in an interview with the New York Times, Robert Kopp, a

climate scientist at Rutgers University, noted that we shouldn’t

view these standards as rigid. "It's not like we can draw a sharp

line where, if we stay at 1.5 degrees, we're safe, and at two

degrees or three degrees it's game over. But every extra bit of

warming increases the risks," Kopp said. ■

By Odessa Goldberg

If you consider yourself a pretty awesome human being

and your brain remarkably special, wouldn’t you want

your brain preserved and found 310 million years into the

future? Well, first you’d want to find yourself in a low-oxygen

environment at the time of your death. Then you’d want to

be covered in siderite, an iron carbonate. Your brain would

start to degrade, but have no fear: kaolinite would creep in

and form a perfect white mold of your brain in fifty years. And

after many, many years, rock would form around your brain

until you’d be found, studied, and lauded.

Fossils of brains are incredibly rare because lipid-rich brains

are quick to decay. But a fossil of the brain of a horseshoe crab,

Euproops danae, was recently discovered at the Yale Peabody

Museum of Natural History by researchers from the University

of New England, Harvard University, the Natural History

Museum in London, and Pomona College. The artifact was

originally sourced at Mazon Creek, a fossil site in Illinois.

Researchers compared this preserved brain with the brains of

modern horseshoe crabs and found that they were very similar.

They deduced that the organisms likely had similar behavior,

too. This fills a gap in the timeline of the central nervous systems

of euarthopods, one of the best-preserved invertebrate animals.

Finding a fossil of a brain like this is extraordinary: a product

of many processes going exactly the right way at the right time

in the right place. Before you theorize how you might fossilize

your own brain, pay homage to our horseshoe crab pioneer. ■

4 Yale Scientific Magazine October 2021 www.yalescientific.org

The Editor-in-Chief Speaks



After one-and-a-half years of virtual Yale Scientific operations, this

September, we finally reunited. In-person meetings and workshops,

physical copies in residential college dining halls for everyone to peruse—

it’s all back. It has felt surreal, in the best possible way.

We’ve finally regained access to the YSM office, housed in a basement on Old

Campus, which we had been barred from throughout the pandemic as the building

was repurposed for quarantine housing. In the dim, slightly dusty space, we’ve dug

through stacks and stacks of old Yale Scientific magazines, dating all the way back

to the ’30s. A lot has changed throughout the decades—from cover aesthetics, to

the gender demographics of the editorial board, to the types of discoveries that

were considered innovative and important.

This issue highlights how scientific advances of today change our perceptions

of the past. In our cover article (p. 19), we discuss how new Yale research on the

therapeutic potential of psilocybin—the hallucinogenic chemical behind “magic

mushrooms”—adds to a long and contentious history of psychedelics research.

We question how long-standing biases might influence new AI algorithms (p.

28). We learn about microproteins that break our antiquated rules for defining

protein-encoding genes (p. 9). We even travel back to the start of our galaxy, as

new models help us understand matter accretion in black holes (p. 27)

Science, in this way, forms the bounds between the past and the future. And

where the future is concerned, I’m particularly inspired by two young scientists

and Yale undergraduates whose work we highlight in this issue. Chase Brownstein

’23 recently published a paper that looked deep into the past, investigating the

evolutionary history of eastern North American dinosaurs (p. 16). Meanwhile,

Eric Wang ’21 first-authored a paper on autoantibodies, key players in the response

to COVID-19 that might help inform future treatment pathways (p. 7 & p. 35).

I am incredibly proud, honored, and humbled to add to Yale Scientific’s long

history of science journalism with Issue 94.3 of our publication. I’m grateful to our

team, who I’ve had the privilege of meeting in-person this year, and to the years

and years of past teams whose labor has allowed our publication to endure. And,

of course, I’m incredibly grateful to our readers—whether you’ve been reading our

magazine for decades or just stumbled upon this issue for the first time.

About the Art

Isabella Li, Editor-in-Chief

This cover illustrates recent and

important strides made in the

field of psychiatry, where new

connections are being formed

between neuron and neuron,

treatment and disease.

Sophia Zhao, Cover Artist


October 2021 VOL. 94 NO. 3



Managing Editors

News Editor

Features Editor

Special Sections Editor

Articles Editor

Online Editors

Copy Editors

Scope Editors

Newsletter Editor


Production Manager

Layout Editors

Art Editor

Cover Artist

Photography Editor



Operations Manager

Advertising Manager

Subscriptions Manager


Synapse Presidents

Synapse Vice Presidents

Synapse Outreach Coordinators

Synapse Events Coordinator


Web Manager

Web Developer

Web Publisher

Social Media Coordinator

Web Designer


Rayyan Darji

Alex Dong


Ann-Marie Abunyewa

Hannah Barsouk

Ryan Bose-Roy

Breanna Brownson

Sophia Burick

Anna Calame

Risha Chakraborty

Lauren Chong

Katherine Chou

Sarah Cook

Kassi Correia

Sophia David

Chris Esneault

Odessa Goldberg

Saachi Grewal

Hannah Han

Simona Hausleitner

Sydney Hirsch

Dhruv Patel

Anavi Uppal

Madison Houck

Elisa Howard

Eunsoo Hyun

Malia Kuo

Julia Levy

Gina Lee

Sophia Li

James Licato

Zi Lin

Crystal Liu

Jessica Liu

Angelica Lorenzo

Daniel Ma

Katherine Moon

Alex Nelson

Noor Nouaili

Gonna Nwakudu

Ethan Olim

Isabella Li

James Han

Hannah Ro

Jenny Tan

Cindy Kuang

Nithyashri Baskaran

Maria Fernanda Pacheco

Meili Gupta

Cathleen Liang

Alex Dong

Brianna Fernandez

Hannah Huang

Christina Hijiya

Tai Michaels

Beatriz Horta

Ishani Singh

AnMei Little

Catherine Zheng

Elaine Cheng

Sophia Zhao

Crystal Xu

Blake Bridge

Jared Gould

Brian Li

Sophia Zhuang

Lauren Chong

Alice Zhang

Sophia Li

Blake Bridge

Jared Gould

Athena Stenor

Anavi Uppal

Sophie Edelstein

Matt Tu

Brett Jennings

Eten Uket

Megan He

Siena Cizdziel

Sorah Park

Himani Pattisam

Jordan Sahly

Noora Said

Emily Shang

Yu Jun Shen

Anasthasia Shilov

Tori Sodeinde

Zeki Tan

Van Anh Tran

Shudipto Wahed

Sherry Wang

Norvin West

Nathan Wu

Justin Ye

Kayla Yup

David Zhang

Lana Zheng

The Yale Scientific Magazine (YSM) is published four times a year by Yale

Scientific Publications, Inc. Third class postage paid in New Haven, CT

06520. Non-profit postage permit number 01106 paid for May 19, 1927

under the act of August 1912. ISN:0091-287. We reserve the right to edit

any submissions, solicited or unsolicited, for publication. This magazine is

published by Yale College students, and Yale University is not responsible

for its contents. Perspectives expressed by authors do not necessarily reflect

the opinions of YSM. We retain the right to reprint contributions, both text

and graphics, in future issues as well as a non-exclusive right to reproduce

these in electronic form. The YSM welcomes comments and feedback. Letters

to the editor should be under two hundred words and should include the

author’s name and contact information. We reserve the right to edit letters

before publication. Please send questions and comments to yalescientific@

yale.edu. Special thanks to Yale Student Technology Collaborative.


Environmental Studies







Natural gas continues to be one of the most popular

energy sources across the world. The largest

component of natural gas is methane, a potent

greenhouse gas with twenty-five times the global warming

potential of carbon dioxide. Mining natural gas also results

in leaks that pollute the Earth’s atmosphere. However, the

American public perceives natural gas and renewable energy

sources, like wind and solar, similarly. This discrepancy

motivated Karine Lacroix and researchers from the Yale

Program on Climate Change Communication to study

the American public’s perception of natural gas based

on differing terminology, as well as the effect of political

affiliation on perception.

The researchers asked over three-thousand volunteers to take

a survey that questioned their perceptions of one of six energyrelated

terms: natural gas, methane gas, natural methane gas,

methane, fracked gas, and fossil gas. The team chose the terms

based on their prevalence in media and everyday conversation.

Lacroix and her team found that the term “natural gas”

was perceived most positively by a significant margin. Their

findings also suggest that there is a general lack of knowledge

about the ramifications of using natural gas. Partisanship

also affected term perception, with Republicans holding

more positive perceptions than Democrats.

Public opinion is an important driver for policy initiatives.

To more accurately portray the downsides of natural gas in

the public sphere, “climate communicators should refer to

[natural gas] as methane gas,” Lacroix explained. Lacroix

and her team look to continue their work in climate change

communication as greenhouse gas emissions rise. ■








Seafood is tasty, but we are often hesitant to consume

it because of the ocean’s high mercury concentration.

Increased human activities have released mercury

into nearby rivers, where it naturally transforms to

methylmercury, a potent neurotoxin associated with lowered

intelligence, child developmental delays, and cardiovascular

impairments. Methylmercury also bioaccumulates in our

food web, making its health consequences long-lasting. Most

of our exposure to methylmercury comes from coastal fish

consumption. Thus, we could effectively minimize the health

risks of mercury intake by mitigating pollution at the source.

Previously, scientists believed that atmospheric deposition is the

most important contributor to coastal mercury. Yale postdoctoral

researcher Maodian Liu and colleagues recently challenged this

traditional view by developing a high spatial resolution dataset of

global riverine mercury export. They discovered that worldwide

riverine mercury export to coastal oceans is actually three-fold

that of atmospheric deposition, making it an unexpected driving

force of the global mercury cycle.

Riverine mercury measurement data has been scarce in the

past, resulting in large variations in export estimates between

different studies. “The greatest challenge is to verify the

reasonability of our estimates because our results are three times

the recommended value of the United Nations Environment

Programme,” Liu said. Nevertheless, Liu is confident in this

estimate since it matches empirical observation. Building off

this work, Liu and colleagues are developing a global model to

further quantify the spatial differences of river mercury cycling

in coastal oceans. Understanding the overlooked riverine process

will help policymakers better regulate mercury pollution issues,

targeting not only atmospheric but also aquatic releases. ■

6 Yale Scientific Magazine October 2021 www.yalescientific.org

Cellular Biology










As the COVID-19 pandemic rages on, researchers

have puzzled over several mysterious viral outcomes.

Infections are severe in some people yet mild or even

asymptomatic in others, and many have reported long COVID,

in which COVID-19 related health problems last four or more

weeks after infection. Yale undergraduate Eric Wang (YC ’21)

worked alongside members of the Ring and Iwasaki labs to

study the relationship between autoantibodies and COVID-19.

Generally, we consider antibodies to be illness protectors.

Autoantibodies, in contrast, may cause harm. “They are antibodies

that target proteins expressed by your body’s own cells,” Wang said.

They can trigger the killing of specific helpful immune cells and

disrupt general immune system communication.

Using samples from Yale New Haven Hospital patients and

healthcare workers, Wang and the research team tested blood

reactivity with 2,770 human extracellular secreted proteins.

They selected a few examples of autoantibodies and performed

in vitro signaling assays, later assessing their effect on disease

progression in mice. They found that autoantibodies targeted

cytokines, chemokines, and various cell surface protein

receptors, potentially altering disease trajectory.

“A lot of the symptoms and reasons people go to hospitals are

due not to the virus itself, but the body’s response to the virus.

For example, an overactive immune system has been implicated

in a lot of COVID-19 hospitalizations,” Wang said. These

autoantibodies may also be linked to long COVID symptoms.

With this new knowledge that autoantibodies may be risk

factors for more serious COVID-19 outcomes, physicians

may incorporate autoantibody screening in their practice. ■

Editor’s note: elsewhere in this issue, we profiled Wang. See pg. 35.








Every society needs a group of superheroes. And as a

society of proteins, organic molecules, and nucleic

acids, cells are no different. To defend against pathogens,

certain proteins within the cell work vigilantly to secure

its safety. One group of these vigilantes hails from a set of

mysterious genes termed the apolipoprotein L (APOL) family.

Twenty years ago, the discovery of APOL1, which functions

outside of the cell to defend against extracellular parasites, led

scientists to believe that the other five APOL genes may defend

against intracellular pathogens since they lack a secretion signal.

Led by postdoctoral fellow Ryan Gaudet, the MacMicking lab

at Yale and collaborators unearthed the function of one of

these five genes, APOL3, which codes for a protein that attacks

Gram-negative bacteria such as Salmonella.

APOL3 interacts with another host defense protein,

guanylate binding protein (GBP1), which autonomously

binds to the sugar-rich surroundings of Gram-negative

bacteria. When GBP1 invites APOL3 to the inner membrane

of Gram-negative bacteria, APOL3 kills the pathogen by

dissolving the lipid membrane, essentially ripping apart the

bacterial membrane in the cytosol.

With great power comes great responsibility: APOL3 needs

to discriminate between self and non-self-membranes. APOL3

doesn’t surround lipids within the cytosol without specificity—

that would be dangerous. A key ingredient in host cell

membranes, cholesterol, is an inhibitor to APOL3 that prevents

self-destruction. “Cholesterol makes APOL3 less able to insert

its hydrophobic component into the membrane,” Gaudet said.

Gaudet is optimistic about the many avenues of exploration

for APOL3, including future work investigating the protein’s

role in vivo. ■


October 2021 Yale Scientific Magazine 7






New research may aid in

space exploration



Scientists have long been interested in predicting

weather on Earth, but in recent decades, tools developed

for climate science at home have increasingly been

applied to studies of extraterrestrial atmospheres. Inspired

by puzzling patterns in Martian dust storms, researchers at

Yale recently investigated the effects of annular modes of

variability—climate patterns that repeat every few weeks to a

month, independently of the cycle of seasons—on Mars and

Titan, a moon of Saturn.

Joseph Michael Battalio, a postdoctoral associate in Yale’s

Department of Earth and Planetary Sciences, noticed a few

years ago that certain patterns of Martian dust activity seemed

to repeat approximately every twenty sols (Martian days).

This length of time didn’t match the behavior of any known

Martian storm instigator but was quite similar to that of the

annular modes Battalio had previously studied on Earth. This

led him to look for the effects of these modes on Mars.

Supporting this hypothesis, Mars has many other

atmospheric similarities to Earth: it rotates at a nearly identical

speed (one sol is approximately twenty-four hours and thirtynine

minutes) and exhibits similar prevailing winds.

When Battalio began analyzing data from Mars, fluctuations

in atmospheric eddy kinetic energy—a quantity associated

with storms—and shifts in atmospheric mass showed cyclic

behavior that was clearly due to annular modes.

Similar results were also found on Titan, the largest moon

of Saturn and a body of particular interest due to stable

liquids and hydrocarbons on its surface. The moon is studied

via the Titan Atmospheric Model (TAM), a numerical

climate model created by Yale professor Juan Lora. “TAM

enables us to generate realistic simulations of Titan’s global

circulation,” Battalio said. These pronounced effects of

annular modes on Mars and Titan may suggest the ubiquity

of annular modes in terrestrial atmospheres.

This research makes great contributions to our

understanding of extraterrestrial atmospheric dynamics and

may aid our exploration of Mars. Martian dust storms are

notoriously brutal, and occasionally prove lethal to solarpowered

missions, but this research could help protect future

landers. “[Annular modes on Mars] impact the overall climate

and dust storm activity… [and] Mars’s modes may even

enable us to generate predictions of dust activity,” Battalio

said. Activity from annular modes on Mars tends to reliably

foreshadow dust activity, so accurate current observations of

the atmosphere allow prediction of storms in a few days’ time.

Looking forward, Battalio has received a grant from NASA

to continue investigating atmospheric variations on planets

and moons. He plans to look further into modes on Mars

and Titan, particularly as they relate to weather events.

For instance, Titan’s methane storms are currently not

well understood, but they pose a potential hazard to future

landers such as NASA’s Dragonfly. Other bodies, such as

Venus—which has atmospheric patterns similar to Titan’s—

and Jupiter are also on the docket. Finally, his research into

annular modes could prove useful to the study of exoplanets,

helping to provide baseline atmospheric understanding so

that more irregular winds can be spotted.

Battalio and Lora have broken new ground in extraterrestrial

atmospheric science, and their work has countless

applications—on Earth, in our solar neighborhood, and

lightyears away. ■

8 Yale Scientific Magazine October 2021







The NoBody protein changes

all the rules



Sarah Slavoff (left) and Zhenkun Na in front of the Advanced Biosciences

Center at Yale’s West Campus.

Researchers Sarah Slavoff and Zhenkun Na of Yale’s

Department of Chemistry are standing up for the little


More than a hundred years in the making, the Human Genome

Project was born from our need to understand the little parts of

ourselves. With our entire genome sequenced at the turn of the

century, researchers began picking proteins to study as if from a lineup

during gym class. Insulin, flaunting its pharmaceutical applications,

was chosen first. A blood clotting factor went second. Around twenty

thousand picks later, lil’ old NoBody (NBDY) microprotein is ready

for its time in the limelight. Microproteins have and will continue to be

master regulators in cells, even if they’re not winning popularity contests.

Sarah Slavoff entered the field of proteomics—the study of the

proteins that make up life—asking all the right questions but

none of the popular ones. She began working to fill the gaps in our

knowledge of what she calls “the dark matter of the genome” during

her postdoctoral fellowship at Harvard. Like many others taking a

protein-based approach to gene discovery, Slavoff sought to separate

the junk from jewel. And while it would be nice if regions of our DNA

could scream to us, “Hey, I’m important!”, natural selection hasn’t quite

worked that kink out yet. Instead, researchers relied on a strict set of

rules when identifying new protein-coding gene sequences:

1. They must begin with a specific three-letter sequence (AUG)

known as a start codon.

2. A single mammalian transcript encodes one protein.

3. The protein must be longer than a hundred amino acids.

Slavoff ’s proteomic experiments, however, began producing tens

of thousands of potential results that were discounted because they

broke one or more of these rules. “Biology is just as messy and

beautiful as you would expect it to be,” Slavoff noted a decade later.

Through ribosome profiling and bioinformatics approaches, her lab

has discovered exceptions to identifying protein-coding genes. “All

of these rules are actually broken. And they’re not just broken in rare

exceptions, they’re broken very widely,” Slavoff said. After adjusting

experimental parameters to account for this inconsistency, the

floodgates were opened: in the world of proteomics, the mavericks

and outcasts now shared a table at lunch with the jocks and socialites.

In an effort led by postdoctoral fellow Zhenkun Na, the lab further

justified that these “new” proteins aren’t just sitting around. In fact, they

might be serving some of the most important functions in cells. Enter:

NoBody, a microprotein that is a mere sixty-eight amino acids long.

One unique property of NoBody is its ability to behave like a fluid,

forming liquid droplets in cells. While in this droplet state, certain

modifications to NoBody, such as the addition of chemical groups

known as phosphates, cause the dissociation of membrane-less

organelles known as processing bodies, or P-bodies. Small like the

proteins that regulate it, the complexity of P-bodies’ anatomy is not

to be underestimated. They serve as storage sites for enzymes that

function in the processing and breakdown of RNA. Thus, NoBody’s

mood at any given moment—in other words, its phosphorylation

state—can make the difference between whether or not certain RNA

sequences, and the proteins they encode for, are produced by the cell.

What’s even more astounding is that NoBody can regulate P-body

dynamics seemingly without formal or consistent structure. It is not

made of folded sequences such as alpha helices or beta sheets, which

are some of the defining features of secondary structure in typical

proteins. NoBody is just one of many “intrinsically disordered”

microproteins with the power of order over our cells. The very

existence of microproteins challenges everything we know about

what proteins look like, what they do, and where to look for them.

One proteomics database, OpenProt.org, predicts the existence

of over forty thousand microproteins and other proteins missing

from our modern understanding of the human proteome. As of

today, characterized proteins in the human body make up only

half that number. With each one of these unfilled links potentially

representing a new function, location, or structure in the cell, we

should take a long, hard think before choosing the next protein

from our lineup. “It took us over a hundred years to build up and

annotate the human genome right. We don’t have another hundred

years to figure out what these things are doing,” Slavoff said. ■


October 2021 Yale Scientific Magazine 9






Sodium batteries in

a lithium-dominated




Every day around the world, modern luxuries are plugged in,

charged, and drained—and the cycle begins anew. Critical

to this energy dependence is the lithium-ion battery, the

electrochemical backbone behind cell phones, laptops, electric

cars, and most other battery-powered devices. In the US alone,

electronics consume some two thousand metric tons of lithium

annually, of which over fifty percent arrives as imports from other

countries such as China, Chile, and Australia.

Yiren Zhong, a postdoctoral associate in Yale’s Department of

Chemistry, understands the need to find a substitute for lithiumion

batteries. “We all know that lithium is a very very limited

resource, not only in the Earth’s crust but also in the oceans, in the

lakes,” Zhong said. Resource scarcity and related environmental

concerns have inspired chemists—including Zhong—to look

for candidates no further than a row down in the periodic table.

One promising candidate is sodium, an alkali metal like lithium.

Sodium and lithium have many similar qualities due to periodic

trends, with the notable difference that sodium is larger in atomic

size and has less electric potential overall. However, sodium is

also far more abundant naturally on Earth. Would this periodic

similarity make sodium a prime candidate for battery production?

This is what Zhong set out to study with his research, published in

August of 2021 in the Journal of the American Chemical Society.

Despite its natural abundance, sodium has a long way to go

before it can replace lithium as a primary battery component. There

are pros and cons for sodium metal as an electrode. Compared to

lithium, sodium has good reversibility—the ability to return the

electrochemical reaction to its original reactants, meaning that

batteries with good reversibility can be recharged and reused.

However, sodium also cannot be charged or discharged very quickly.

Intrinsic elemental properties stand in the way of sodium’s potential.

Zhong’s research group investigated these properties through rigorous

experiments testing sodium batteries at varying power levels, then

examining the electrode’s physical and chemical structure after

both charging and discharging. The research team performed the

experiments at high currents, which were closer to those of lithium

batteries, and at far lower currents for comparison. When the sodium

electrode was discharged at the higher currents, it performed with only

zero to sixty percent Coulombic efficiency—the ability of a battery to

output the usable electrons, or electricity, that it produces.

An interesting physical reaction indicated a key elemental difference

between lithium and sodium. When built through charging, sodium

metal electrodes naturally form in dendritic structures, which

are long, thin columns of metal that become porous, microscopic

forests on the surface of the electrode. On electrodes charged at high

current densities, these dendritic structures form with non-metallic

impurities. When discharged at high current densities, these impure

porous surfaces reduce the reversibility of the battery overall by

allowing fast-moving current to react unevenly—especially at the base

of the electrode—causing electrode erosion and eventual electrical

disconnection. Thus, the low performance of sodium batteries likely

stems from their elemental characteristics, namely their atomic size:

electrodes made from sodium metal have more spread-out dendritic

structures due to the larger atomic size. This creates the porous surface

that allows for erosion of the electrode foundation layer at high

currents, like waves washing away the base of a sandcastle.

Zhong’s findings, however, also suggest a favorable future for sodium.

At low power levels, the sodium battery did not decay and performed

favorably with Coulombic efficiencies as high as 99.5 percent. At these

low current densities, sodium batteries may demonstrate commercial

usefulness in technologies like short-range transportation tools.

Having observed sodium’s intrinsic characteristic limiting

its potential in batteries, Zhong’s group laid the foundation

for future sodium battery technology. One of his newest ideas

involves the electrode shape itself. “My current thinking

is trying to use a three-dimensional electrode,” Zhong said.

He theorized that a three-dimensional electrode may reduce

local current density across a larger surface area, which could

improve the electrochemical reaction in the battery.

As our society’s energy dependence grows each year, more

environmentally friendly batteries become a necessity rather than

a goal. “We need to develop a battery future,” Zhong said. “By

the year 2050, I would envision that sodium would be one of the

major components in the battery market.” Sodium metal has the

potential to help build a sustainable battery future, and thanks to

the continued work of innovative chemists, that future is in reach. ■

10 Yale Scientific Magazine October 2021 www.yalescientific.org


In scientific experimentation, some information is more attainable

than others, by nature of the method of retrieval. For instance,

clinicians can easily gather blood pressure and other laboratory

values; aptly, this type of data is called easy-to-obtain information

(EI). However, other data may be too expensive, time-consuming,

or both to collect on a larger scale. Flow cytometry, a laser-based

technique to measure the chemical and physical properties of cells,

is an example of this type of hard-to-obtain information (HI). To

circumvent these limitations, a team of Yale researchers, including

graduate student Matthew Amodio and associate professor Smita

Krishnaswamy, developed a model called the Feature Mapping

Generative Adversarial Network (FMGAN) that allows for the

accurate prediction of HI given EI. Their methodology is novel—

in fact, Krishnaswamy’s lab pioneered all of the frameworks used

throughout the study, even those used as comparators to the FMGAN.

The most recent study applied the neural network model in two

contexts. One generated RNA sequences of cells perturbed with

drugs, a form of HI, via the chemical structure of the compound,

a form of EI. The second predicted the flow cytometry data (HI) of

COVID-19 patients using clinical measurements (EI).

The FMGAN’s predictive capabilities come from the addition of

a condition-embedding network. This network transforms the EI

into representations called manifolds that are easier to visualize,

reduce redundancy, and thus simplify data extrapolation. “The

condition-embedding network translates the data from how it

exists naturally to a form more easily used by our model, which it

gradually learns how to do,” Amodio said. The manifold structure

is preferable to the alternative form of data representation in

ambient space, as its smooth structure produces outputs that move

uniformly with changes in input. This point is especially relevant

in the context of Krishnaswamy’s work with chemical structure

and RNA sequencing—small modifications to certain portions of

the input can determine molecular function, so it is important to

maintain such consistency in the magnitudes of movements.

Further, the scientists introduced stochastic mapping, a measure of

randomness, into the model. “The drugs do not produce a single result

every time,” Amodio said. “The cell measurements change even in

applying the same drug to the same system. There are lots of sources of

randomness with respect to the data we looked at. Thus, it makes sense





A neural network

to improve data



Computational Biology


to use models that include randomness to accurately represent that.”

In other words, stochastic mapping was another deliberate addition to

their neural network that further increased prediction reliability.

In applying the FMGAN to predict the RNA sequencing data of

cells treated with drugs, the team performed four experiments. In

the first two, they provided the model with preprocessed data and

good manifold coordinates; the purpose was simply to show that

information could be generated from the data. After demonstrating

the FMGAN’s success under these conditions, the researchers

executed two more challenging experiments that required the full

capabilities of the network in creating its own manifold coordinates.

One tested the condition of drug chemical structure in the form

of simplified molecular-input line-entry system (SMILES) strings,

a specialized notation system. The other instead looked at image

representations of said chemical structure. The latter performed

better than the former, likely due to the more advanced architecture

of the images compared to the strings. Both, however, demonstrated

the efficacy of the FMGAN and its condition-embedding network.

To demonstrate the breadth of the FMGAN’s applications, the

researchers also tested its ability to predict future flow cytometry

information from COVID-19 patients’ clinical measurements

upon entering the ICU. During experimentation, researchers took

both clinical and flow cytometry measurements from all study

participants. They omitted the data of fourteen patients, training the

neural network model on the remaining 115. Ultimately, the FMGAN

was able to use clinical measurements to generate flow cytometry

predictions for the never-before-seen patients. In practice, this data

gives clinicians insight into a patient’s immune function and is a

predictor of mortality. Instantaneous and accurate determination of

this HI would allow physicians to craft optimal courses of treatment.

Through this set of experiments, Krishnaswamy and her team

demonstrated the efficacy of their novel FMGAN neural network

model through its applications in drug discovery and clinical

inference. However, the FMGAN program is not limited to

these spaces—its architecture is not hardwired to address these

structures specifically and can be generalized to other data. This

area of quantitative computational biology is underexplored, but

breakthroughs have the potential to transform how scientists

leverage the information they have readily available. ■

October 2021 Yale Scientific Magazine 11





The impacts of aging on





Babies don’t shiver when they’re cold—at least for the first six

months of their lives. Instead, they keep warm through a

mechanism called non-shivering thermogenesis, in which a

special type of fat called brown adipose tissue generates heat. But as

babies grow older, thermogenesis is no longer their primary means

of keeping warm. According to a study by researchers at multiple

centers, including Yale, age-related changes in thermoregulatory

control arise from changes in the body’s immune system. The

authors discovered that aging impairs a specific kind of immune cell

called type 2 innate lymphoid cells (ILC2s), which are important for

the maintenance of healthy adipose (fat) tissue.

We have two types of fat in our bodies: white adipose tissue

(WAT) and brown adipose tissue (BAT). Aging is marked by a

decline in brown adipose tissue and a shift in the distribution of

white adipose tissue. As we grow older, we have an increase in white

adipose tissue in our trunk and abdomen. This visceral adipose

tissue is subject to enhanced inflammation and insulin resistance,

which increases the risk of obesity among the elderly.

There also exists a third type of body fat midway between

white and brown adipose tissue: beige adipose tissue, which

arises from white fat parent cells but possesses similar features

to brown fat cells. Beige adipose tissue also responds to cold

exposure via energy expenditure and heat production.

The scientists looked into ILC2s because of their role in visceral

adipose tissue “browning,” the production of beige fat cells. They

compared the immune compartment differences between young

and old mice models and found that there was an almost complete

loss of ILC2s in the visceral adipose tissue of older mice.

ILC2s are tissue-specific immune cells, meaning they stay

within the visceral adipose tissue after their generation in the bone

marrow. ILC2 development depends on the proliferation of IL-

33, which belongs to a class of small cell-signaling proteins that

regulate our immune systems. The research team found that IL-33

was produced in different cellular locations in the adipose tissue

of young versus old mice. This switch in cellular source led them

to believe that there is less IL-33 available to develop ILC2s. Less

ILC2s means less browning, and thus a weakened cold tolerance.

The authors hypothesized that if they could supplement IL-33

in old mice, the resulting ILC2 development would restore healthy

cold response. They examined this through the “cold challenge”

method, during which mice were placed alone in cages that were

kept at around forty degrees Fahrenheit. Experimenters checked

on the mice twice a day to monitor mortality rates, then took

adipose tissue samples from mice that survived for two straight

days to look for signs of a healthy cold response.

So, can IL-33 alone fix the immune system of older mice? In short, it

can’t. Actually, mice with supplemented IL-33 had a higher mortality

rate than did other old mice in the cold challenge. Their response

to cold and temperature regulation was still entirely dysfunctional.

Faced with totally unanticipated results, the researchers came to

realize that maybe the problem wasn’t with IL-33 at all: it was with

the ILC2s themselves. Using RNA sequencing, they discovered that

ILC2s of old mice are pathogenic. Simultaneously, there are very

few healthy ILC2s left to offset these negative effects. While the

researchers were unable to determine the exact mechanism of old

ILC2 lethality, it certainly seems to be a double-edged sword that

leads to the dysfunction of the thermogenic response.

The research team tried one last experiment. ILC2s from

young, healthy mice were directly transplanted into older mice.

Only then did the thermogenic response increase and mortality

rates in the cold challenge decrease.

These results caution us that attempting to “fix” an immune

pathway can be tricky—we don’t know if we could be causing more

problems than we solve. “With age, the immune system has already

changed, and we need to be careful how we manipulate it to restore

the health of the elderly,” said principle investigator Vishwa Deep

Dixit, Waldemar Von Zedtwitz Professor of Comparative Medicine

and of Immunobiology at Yale, in an interview with YaleNews.

Fully understanding how to repair the immune system could be

a game changer for the elderly or people with immune deficiencies.

“Immune cells play a role beyond just pathogen defense and help

maintain normal metabolic functions of life,” Dixit told YaleNews.

These other functions include cold response and regulation of fat.

Armed with more knowledge of why the immune system stops

working, researchers like Dixit can continue to work towards solutions

that will lead to a healthier population in more ways than one. ■

12 Yale Scientific Magazine October 2021 www.yalescientific.org







Your feelings

of paranoia

are not

all that


During the Great Depression in 1929, immigrant workers

became scapegoats for economic hardship, accused of taking

jobs away from native-born Americans. After the tragedy of

9/11, many people grew fearful that their lifelong Muslim

neighbors could somehow be implicated in the terrorist attacks. Such

crises have historically caused individuals to see others as a threat. Drastic

changes tend to make people more paranoid.

This trend continues with the COVID-19 pandemic. Toilet paper stock

quickly ran out as shoppers rushed to acquire household supplies as if in

a post-apocalyptic frenzy. Asian Americans experienced an exponential

increase in hate crimes due to fringe conspiracy theories regarding the

origin of the SARS-CoV-2 virus. Differing opinions on mask-wearing

have turned into heated, politicized debates. Everyone seemed to share a

heightened sense of apprehension about the future.

Yale Cognitive Research Scientist Praveen Suthaharan, Associate Professor

of Psychiatry Philip Corlett, and their team recently published a study in

Nature Human Behavior about the effects of the COVID-19 pandemic on

individuals’ paranoia. To these researchers, the widespread uncertainty

caused by the pandemic provided an unprecedented opportunity to track

the impact of an unfolding crisis on human beliefs.










October 2021 Yale Scientific Magazine 13




Praveen Suthaharan, a member of the Corlett Lab, poses underneath a series of brain artwork.

A Pandemic of Paranoia

Constantly wearing a mask to protect

each other from a virus we cannot even see

with our own eyes, against a disease that

is in many cases asymptomatic, can

be overwhelming—enough to

put anyone on edge. Previously

mundane activities, like going

to the grocery store or

visiting grandparents,

now draw concerns: just

by doing them, one could contract

or transmit a potentially fatal disease.

The study’s authors saw that paranoia

significantly increased throughout the

duration of the COVID-19 pandemic,

with self-reported paranoia levels

peaking as states drew closer to

reopening. Overall effects on other

mental illnesses were also negative. “We

have all experienced challenges since

the onset of the pandemic, and we also

noticed this in our data: that over time,

depression and anxiety increased during

the lockdown,” Corlett said.

Ensuring that the general public

remains calm and willing to work

together is essential to overcoming a

crisis such as the COVID-19 pandemic,

especially in efforts like vaccination

and social distancing. While many have

argued for and against the merits of

mandatory lockdowns, this study’s data

demonstrate that divergence in statelevel

response correlated with differential

increases in paranoia—both selfreported

and measured via laboratory

tasks. Vigorous, proactive lockdown

policies were associated with less

paranoia when compared to

lax lockdown policies. One

may similarly expect to

see different outcomes

based on states’ varying

mask mandates, Corlett posited.

To Mask or Unmask

Over a year into the pandemic, wearing

a mask while around others should

seem like a no-brainer. Masks are cheap,

effective, and easy to wear. Suthaharan’s

team was interested in understanding

why so many people were and are still

opposed to wearing a mask, despite the

seemingly clear cost-benefit analysis for

doing so. “It’s similar to when you see a

patient smoking a cigarette outside of

the hospital,” Corlett said. “We wanted

to understand why people engage in

behaviors risky for their health.”

In their study, the researchers found

that paranoia was highest during

reopening in states that required maskwearing.

This supports the notion that, in

social settings, humans are “conditional

cooperators”—we tend to follow rules

as long as we perceive others doing the

same. As soon as this is no longer true,

we tend to stop following these rules. As

the data suggested, when there was a mask

mandate but people saw others without a

mask, that raised confusion and paranoia.

In fact, individuals with paranoia were

far more reluctant to wear masks and

reported wearing them significantly less.

Suthaharan wanted to know whether

mask mandates themselves

could have contributed to the

increased mental health

issues experienced

during the pandemic.

To that end, his team

performed a type of analysis

called “difference-in-differences,”

which allowed them to infer causal

relationships by comparing changes

in paranoia levels in states that

implemented a mask mandate to

states that did not, or only recommended

it. The analysis revealed that mandated

mask-wearing was associated with a forty

percent increase in paranoia levels.

These results could be connected

to a lack of clarity in public health

messaging, Corlett conjectured. Early

in the pandemic, health organizations

such as the CDC and WHO did not

fully support masking, even claiming

inefficacy at times. Later, emerging

evidence supported a reversal in opinion,

which in turn led to mask shortages and

induced worries among people who were

now unsure about whether they would

be able to get masks.

The uncertainty and paranoia caused

by mask mandates possibly led to distrust

of public health organizations as maskwearing

became a politicized topic. “In no

other time in history have we experienced

a pandemic this problematic, and instead

of dealing with it as a community of likeminded

people, what we’ve done is double

down on our differences,” Corlett said.

All in This Together

If there is any comfort

to be taken by those

who have experienced



difficulties since the

14 Yale Scientific Magazine October 2021 www.yalescientific.org



start of the pandemic, it is that nobody

is alone in their struggle. With this

collective aspect in mind, Suthaharan

and his team were keen to study grouplevel

cognition to see if characteristics

and experiences shared by a population

affected mask-wearing or paranoia.

Using an index of cultural tightness and

looseness, developed by psychologists

at the University of Maryland, to

measure a state’s

cultural tolerance

for rulebreaking,



found that

stricter states that

mandated mask-wearing

experienced the lowest rates of

mask-wearing. Individuals in

culturally tight states

may have grown

paranoid seeing

others without masks,

leading to overall lower levels of maskwearing

in these states. Fear of social

reprisal due to anti-mask sentiments

may have further driven their paranoia.

Many of those who were hesitant to

wear a mask were also hesitant to receive

a COVID-19 vaccine, with unproven

conspiracy theories circulating about its

development and its usage in government

surveillance. The research team found that

paranoia was significantly correlated with

belief in these specific conspiracy theories,

as well as belief in other theories, such as

that prominent Hollywood entertainers

are involved in child trafficking.

These results demonstrate that our

surrounding culture and environment

can substantially affect mental health.

“It was very interesting and informative

to show that group-level characteristics

such as rule-following and cultural

tightness impacted peoples’ behaviors

and beliefs,” Corlett said.

Cognitive Origins

The Corlett lab has been interested

in studying the origin and neural

mechanisms of paranoia for several

years—even before the pandemic.

Notably, within the field of psychiatry,

there are mixed opinions regarding the

origins of paranoia in the mind and


brain. Some believe that the brain has a

distinct module for dealing with social

relationships and that problems with this

part of the brain cause paranoia. Corlett,

on the other hand, contends that the

same reward mechanisms in our brains

that tell us whether we like things, such

as different types of food or even money,

are implicated in paranoia. To him, we

do not differently process positive or

negative feelings towards something in

social versus nonsocial settings.

In this study, the authors conducted two

types of experiments to assess paranoia:

social and nonsocial. In the nonsocial

task, participants were instructed to

choose between three cards that each had

a different probability of being “correct.”

They were also told that the underlying

probabilities would change, but not how

often or when. A paranoid individual

would likely switch their choices more

frequently, even after positive feedback

(“win-switching”), incorrectly attributing

probabilistic errors to a shift in underlying

probabilities. In the social task, instead

of using cards, individuals were

told they could collaborate with

one of three individuals

who would either help or

hurt them.

The researchers found that

the win-switching frequency in the

nonsocial task was indeed significantly

correlated with paranoia, validating that

performance on the task was an accurate

measure of one’s paranoia levels. More

importantly, they also found that there

was no difference in behavior between

the social and nonsocial tasks, suggesting

that Corlett’s theory may offer a more


valid and accurate understanding of

paranoia’s origin.

Interestingly, participants in this study

performed the same tasks before and

during the pandemic, yet yielded starkly

different outcomes in each condition.

This may shed light on the replication

problem in psychological research,

where many published findings cannot

be reproduced by other researchers. It is

possible that some of these findings could

be merely artifacts of changing real-world

conditions between replication attempts.

But even so, this study suggests that realworld

changes can have profound impacts

on individual behavior in laboratory tasks.

An Informed Future

This study could have many implications

for the field of psychiatry, and the

authors hope that its insights into human

psychology will help those struggling with

mental illness. They also hope that their

research will affect positive change for the

ongoing COVID-19 pandemic. Given

how paranoia affects individual

responses to worldwide crises, this

study’s results could help guide

future decision-making and

inform effective communication

between the public, governments,

and other organizations.

“Conducting online research during

a pandemic was a challenge, but also

inspiring,” Corlett said. “It is unusual to

be so connected to real-world events and

to study them as they unfold, and for our

data to have implications for how the

situation could be handled differently

now, and in the future.” ■


SHUDIPTO WAHED is a sophomore in Benjamin Franklin from Pittsburgh, Pennsylvania interested in

studying Molecular Biophysics & Biochemistry. Shudipto conducts research on protein engineering in

the Ring Lab at the Yale School of Medicine. Outside of YSM, Shudipto is a senator for the Yale College

Council and an analyst in the Yale Student Investment Group.

THE AUTHOR WOULD LIKE TO THANK Professor Philip Corlett for his time and enthusiasm.


Reed, E. J., Uddenberg, S., Suthaharan, P., Mathys, C. D., Taylor, J. R., Groman, S. M., & Corlett, P. R. (2020).

Paranoia as a deficit in non-social belief updating. ELife, 9.

Suthaharan, P., Reed, E. J., Leptourgos, P., Kenney, J. G., Uddenberg, S., Mathys, C. D., ... & Corlett, P.

R. (2021). Paranoia and belief updating during the COVID-19 crisis. Nature Human Behaviour, 5(9),


October 2021 Yale Scientific Magazine 15



Millions of

years ago,

long before

any of us existed, dinosaurs

roamed the Earth. What might

have stood where you are right now?

Maybe a T. rex or a Triceratops?

If you are somewhere in eastern North

America, the dinosaurs that lived near

you long ago might be unique. Chase

Brownstein, a Yale College junior

pursuing the Ecology and Evolutionary

Biology major, recently conducted

research showing that eastern North

American dinosaurs were probably very

different from the famous species of the

American West. His work sheds light

on the possibility of multiple paths to

evolutionary success.

Dinosaur Island

During the Mesozoic Era, when

dinosaurs like the T. rex existed, the

Earth looked very different from how it

does today. Surrounded by oceans and

seaways, eastern North America was

isolated from the rest of the world for

about thirty million years, constituting

an island landmass named Appalachia.

But since the 1800s paleontologists have

largely neglected the study of what kinds

of life once inhabited Appalachia.

When organisms evolve on an

isolated landmass, it’s considered more

likely for them to develop in ways that

differ substantially from their relatives

elsewhere. This has caused researchers

like Brownstein to ask: was this true for

dinosaurs isolated in Appalachia, and if

so, what unique characteristics did they

have? Poor fossil-forming conditions

and other factors, however, have made

this question difficult to answer.

Firstly, Appalachia has smaller

mountain ranges compared to western

North America. This means that the

shorter rivers created by these mountains

don’t flow as far and therefore cannot

accumulate as much sediment as their

longer counterparts in the West. This

Art by Zi Lin

accumulation of sediment is what

creates fossil-forming regions. Shorter

rivers generate fewer of these regions;

thus, fewer fossils formed on Appalachia

to begin with, making it difficult to

know what kinds of dinosaurs lived

there. Additionally, the fossils that

did form had a high chance of being

destroyed later by glaciers. The same

glaciers that carved out the Great Lakes

dug up much of the fossil-containing

sediment in eastern North America.

Finally, it’s difficult to even access the

fossils that did survive the glaciers, as the

eastern coast of North America is much

more densely populated than the West.

Most of the land is privately owned.

“Nobody wants you to make a giant hole

in their backyard,” Brownstein said.

Many of the major fossil discoveries

that are now in museums like the Yale

16 Yale Scientific Magazine October 2021 www.yalescientific.org





Uncovering records of eastern North

American tyrannosaurs




By Elisa Howard and Anavi Uppal



of Natural

H i s t o r y

w e r e


made in the

19th century, when

populations were less dense and

eastern fossils more accessible.

Uncovering Clues

New Jersey State Museum. The fossil

revealed distinct anatomical features

distinguishing Dryptosaurus from other

tyrannosaurs like the T. rex. In particular,

Dryptosaurus had an elongated skull and

hands ranking among the proportionally

largest for any dinosaur. Furthermore,

it had massive claws reaching up to six

inches long and an unusually shaped

foot with three bones.

While at the Peabody Museum,

Brownstein noticed that the foot

of a tyrannosauroid found in the

Merchantville Formation in Delaware

displayed similar features to that

of Dryptosaurus. To investigate, he

used the Tree Analysis Using New

Technology (TNT) program to

conduct a phylogenetic analysis of

the Merchantville tyrannosauroid

In 2015, while browsing collections at

the Yale Peabody Museum, Brownstein

elucidated connections between two

different tyrannosaurs—Dryptosaurus

and the Merchantville tyrannosauroid—

to answer the question of whether

distinct dinosaur species evolved on the

once-isolated eastern North America.

“This research is the culmination of

several years of work into the question of

eastern North American biogeography,”

Brownstein said.

In 1866, West Jersey Marl Company

workers discovered the enormous fossil

of a dinosaur that lived approximately

sixty-seven million years ago in

modern-day New Jersey. Yale Professor

of Paleontology Othniel Charles Marsh

named the dinosaur Dryptosaurus in

1877. Brownstein had the opportunity

to study the Dryptosaurus fossil at the



Dryptosaurus had an elongated skull and hands, ranking among the proportionally largest for any dinosaur.

October 2021 Yale Scientific Magazine 17



and Dryptosaurus. The program

incorporated the skeletal features of

the two dinosaur species to determine

evolutionary relationships.

From this computational analysis,

Brownstein discovered that the

Merchantville tyrannosauroid and

Dryptosaurus evolved from a common

ancestor and are part of the same clade.

That clade, known as Dryptosauridae,

is a distinct group of tyrannosaurs

that existed solely in Appalachia. For

over a century, paleontologists have

hypothesized the existence of a distinct

set of tyrannosauroids native to the

once-isolated eastern North America.

With Brownstein’s research, we now have

evidence supporting that hypothesis.

Though factors such as poor fossil

records still constitute obstacles to

our knowledge of the dinosaurs that

inhabited the east, Brownstein’s research

underscores the rise of anatomical

differences in the dinosaurs of eastern

and western North America. In a broader

context, such discoveries highlight the

profound interplay between geographical

isolation and the evolution of species.

Searching for History

Evolutionary biologists and

paleontologists often develop “just-so

stories,” speculative explanations for the

origins of a biological trait. The term

comes from Rudyard Kipling’s 1902 “Just

So Stories for Little Children.” The book

includes a collection of animal tales such

as “How the Rhinoceros Got His Skin,”

in which the rhinoceros developed

wrinkles after rubbing against a tree. In

the context of dinosaurs, there are many

speculative hypotheses that tyrannosaurs

evolved a specialized skull, superior

sight, or other specific traits to achieve

supremacy. The T. rex—the “King of the

Dinosaurs” that lived in western North

America—boasted hallmark features of

dinosaur superiority, such as a gigantic

skull, forceful jaw, powerful hindlimbs,

and muscular physique. Yet, whether

those features are indeed necessary for

biological success remains up for debate.

The eastern North American

Dryptosaurus, for example, differed from

the T. rex and other tyrannosaurs: it

had larger hands, extensive claws, and a

distinctive unit of foot bones. “Eastern

North American tyrannosaurs were

really big, were probably predators,

and had a different set of features than

western North American tyrannosaurs,”

Brownstein said. “This may cause us to

rethink the hypothesis that there was

only one way that tyrannosaurs got so big

and successful.” In this way, Brownstein’s

discoveries point towards the possibility

that tyrannosaurs achieved success

through the evolution of differing features.

As Brownstein emphasized, his

research raises broader questions of

evolution that demand further research

and contemplation—the prevailing one

among them being: how many paths

could there be to evolutionary success?

To find out more about eastern North

American dinosaurs, the next step would

be to discover a more complete skeleton

of these species. Currently, research is

limited to the fossils that have already

been found, which do not include the body

part that paleontologists consider to be

the most informative: the skull. However,

looking at living things today could also

shed light on the nature of extinct species.

Analyzing the characteristics of dinosaur

descendants can sometimes help us learn

more about their ancestors.

Behind the Discoveries

Brownstein—who has an impressive

research history, having published about

twenty peer-reviewed articles in journals

including Royal Society Open Science,

the Journal of Paleontology, Scientific

Reports, and the Zoological Journal of the

Linnean Society—intends to go forward


with other research while he waits for

more fossil discoveries. He is currently

studying fishes with Yale Professor and

Chair of Ecology and Evolutionary

Biology Thomas Near.

Brownstein said that he was fortunate

to have access to fossil collections like

those at the Peabody Museum and

described his appreciation for those who

have provided support and advice in his

research endeavors. “I have been very

fortunate to have people who gave me a

chance,” Brownstein said.

Brownstein has a genuine passion

for the field of research. “I have always

been really fascinated with nature, time,

what lived before, and how we got here,”

he said. Research simply makes him

happy. “If I want to do something that

I enjoy, I will do research, write, and

study things,” he said. Based on this

passion, Brownstein described science

in the larger context of the human desire

for exploration. “It is a human thing to

constantly explore. The urge to discover

is a motivator in science, and it’s a

beautiful thing,” he said.

Just like we push the boundaries of

our universe with space travel, we are

now pushing the boundaries of time

by uncovering our planet’s incredible

history. In Brownstein’s case, we now

understand that the geographical

isolation of eastern North America over

the course of thirty million years likely

provided the means for the evolution of

distinct dinosaur species.

As we continue to uncover our planet’s

incredible history, what will we discover

next? ■


ELISA HOWARD is a sophomore neuroscience major in Berkeley College. In addition to writing for YSM,

she volunteers at CT Hospice and Yale Community Kitchen, constructs 3D-printed limb devices through

Yale e-ENABLE, and helps organize blood drives for the American Red Cross at Yale. During the summer,

she researches neural repair in the Strittmatter Lab at the Yale School of Medicine.

ANAVI UPPAL is a sophomore astrophysics major in Pierson College. In addition to writing for YSM, she

is one of Synapse’s outreach coordinators, and she teaches science to elementary schoolers through Yale

Demos. She’s also a fall social media intern at NASA Ames Research Center.

THE AUTHORS WOULD LIKE TO THANK Chase Brownstein for his time and enthusiasm about his



Doran Brownstein, C. (2021). Dinosaurs from the Santonian–Campanian Atlantic coastline substantiate

phylogenetic signatures of vicariance in Cretaceous North America. Royal Society Open Science, 8(8),

210127. https://doi.org/10.1098/rsos.210127

Marsh, O. C. (1896). The Dinosaurs of North America. Govt. Print. Off.

18 Yale Scientific Magazine October 2021 www.yalescientific.org

On a cold November day in 1957,

Laika made history as she rode

into orbit on a Soviet spaceship,

withstanding tremendous

acceleration to become the

first living being to circle the Earth. Laika wasn’t

a trained astronaut—she was a dog, a former

stray from the streets of Moscow chosen for

this historic, but ultimately fatal, mission.

In the name of science, humans have

since launched hundreds of different animals

into space. Now, however, scientists are

sending mice on a very different kind of

trip—one that doesn’t require them to leave

the laboratory, much less the Earth.

Rather, they’re on a mushroom trip.





shake up

the future of












October 2021 Yale Scientific Magazine 19



Research into the neurological effects of

psilocybin, the hallucinogenic compound

found in so-called “magic mushrooms,”

has experienced a powerful revival in

recent years. Psilocybin is a serotonergic

psychedelic, meaning that it has a high

affinity for serotonin receptors and

produces altered states of consciousness,

including positive mood. Clinicians and

academics have long been interested

in the potential of these substances as

therapies for neuropsychiatric disorders,

including depression and addiction, but

their clinical implementation has faced

considerable challenges.

The frontal cortex’s neuroplasticity,

or its ability to adapt over time, has

proven fundamental to the efficacy of

antidepressant therapies. Results of

previous studies suggested a potential

relationship between psychedelics and

neuroplasticity, but the particulars

remained unknown. To address some

of these uncertainties, researchers from

Yale School of Medicine’s Department of

Psychiatry examined psilocybin’s effect on

the brain and demonstrated psilocybininduced

structural neuroplasticity at

cellular resolution for both short and

long timescales.

Structural and Behavioral Effects of


Psilocybin has a centuries-long

tradition of medicinal and spiritual use,

particularly among Indigenous peoples.

Despite this, however, psilocybin has not

been extensively studied in the context

of Western medicine, leaving many

questions about its neurological functions

unanswered. “Psychedelic compounds like

psilocybin produce temporary psychedelic

experiences that last for four to six hours,

but it’s a mystery as to how those shortterm

actions translate to longer-lasting

therapeutic effects on mental illnesses,” said

Alex Kwan, associate professor of Psychiatry

and Neuroscience at Yale and senior author

of the paper. By studying how psilocybin

affects neuron structure, researchers could

bridge this gap and offer a structural

explanation behind its well-observed

lasting therapeutic effects, which include

a substantial reduction in depression and

anxiety symptoms according to early but

promising clinical trials.

20 Yale Scientific Magazine October 2021

In this study, the researchers

administered various doses of psilocybin

to mice and evaluated the neurological

effects through a series of tests.

“One of our focuses is on neuronal

structure. We used two-photon

imaging, a fluorescence

imaging technique used

for live tissues, and

confocal imaging, an

optical laser imaging

technique with high

resolution, to see the

structural changes

caused by singledose


said Ling-Xiao

Shao, first author

of the paper and

a postdoctoral

associate researcher

in Kwan’s lab. The

researchers used the twophoton

imaging technique to

longitudinally track the dendritic

spines—protrusions from the membranes

of dendrites, the branch-like appendages

of neurons that receive communications

from other cells—in neurons within

the mice’s medial frontal cortex. These

spines play a vital role in receiving and

processing electrical impulses.

The study’s results suggest that a

single dose of psilocybin was sufficient

to enhance the formation of dendritic

spines in the medial frontal cortex of

the mouse, increase spine head width,

and boost spine protrusion length. A

month after administration of psilocybin,

approximately a third of psilocybininduced

new dendritic spines remained.

These results are especially promising for

potential therapeutic use, as conditions

like depression are associated with a

loss of synapses in the frontal cortex

region. Psilocybin’s stimulation of lasting

dendritic growth may offer a solution.

While imaging neural modifications

clarifies the physical effects of

psilocybin, it does not fully account

for the functional outcomes of the

compound. To understand the impact

of these structural changes on behavior,

the researchers applied footshocks to

the mice and assessed if single-dose

psilocybin improved their ability to

escape stressful conditions. The results


that mice exposed to psilocybin exhibited

healthier stress-response behavior.

While this study provides compelling

evidence in support of the enduring

actions of psilocybin in the brain, it is

still unclear whether the compound’s

therapeutic potential can be isolated from

its hallucinogenic effects. Kwan and Shao’s

study found that suppressing psilocybin’s

hallucinogenic effects by knocking out

a key serotonin receptor, 5-HT2A, did

not interfere with the therapeutically

promising changes in neuron structure.

However, further research is needed to

determine if this separation of function is

possible in humans.

The Rise (and Fall) of Psychedelic


Kwan and Shao’s recent foray

into the world of hallucinogens is

representative of a larger, ongoing

renaissance in psychedelic research

after decades of fluctuating acclaim and

condemnation. When Swiss researcher

Albert Hofmann first discovered LSD’s

potent hallucinogenic effects in the

early 1940s, he was not alone in his

excitement about the drug’s psychiatric

potential. Hundreds of academic




articles expounding psychedelics’

effects appeared in medical journals

throughout the 1950s. So began a brief

and initially promising affair between

psychedelics and clinical psychiatry

in the United States. Various

clinics and institutions, including

Harvard, devoted significant

resources to researching

the therapeutic potential

of psilocybin and LSD.

Psychedelic researchers,

such as Timothy Leary and

Richard Alpert, became

household names.

However, growing

backlash against the

free-loving, acid-tripping

counterculture of the

1960s—facilitated by

psychedelics’ association

with anti-war dissidence—began

to turn the political tide. In 1965,

the passage of the Drug Abuse Control

Amendments Bill banned the unlicensed

individual manufacturing and sale

of hallucinogenic drugs, signaling

a strengthened political and legal

resistance to hallucinogens and ringing

a death knell for psilocybin. In 1970,

the Controlled Substances Act explicitly

designated psilocybin a Schedule I

drug, the most restrictive classification,

indicating a high potential for abuse and

no accepted medical use. In so doing,

the Act not only subjected psilocybin to

extremely prohibitive regulations, but

also heavily stigmatized its use, taking

the wind out of the sails of psilocybin

research for years.

By Kwan’s own recollection, the

landscape of psychedelic research was

nearly barren even just a decade ago.

“Reading from other labs who were

studying this fifteen years ago, the culture

was very different, very restrictive,” Kwan

said. “There were no suppliers of these

compounds…there were only a few

labs who would [synthesize psychedelic

compounds] in the United States.”

The Psychedelic Revival

In recent years, however, the research

landscape has shifted. With greater

knowledge of how drugs function on a

molecular level, further research into


the science of addiction, and growing

recognition of the failures of the War on

Drugs, popular conceptions of drug use are

shifting. While much of the mainstream

drug debate focuses on recreational use,

these changing perspectives have opened

up the academic and clinical fields as well.

Kwan and Shao’s study adds to a growing

body of research into the therapeutic

potential of psilocybin and other

psychedelics to treat mental disorders.

As a compound used in conjunction with

psychotherapy, psilocybin has a number

of uniquely appealing characteristics—it’s

non-addictive, has low risk of overdose,

and may require less frequent dosing than

selective serotonin reuptake inhibitors, the

most common class of antidepressants.

Financial support for research

from activist organizations, academic

institutions, and commercial entities has

accompanied this growing recognition

of psilocybin’s potential. Echoing the

academic enthusiasm of the 1950s,

centers dedicated to the study of

psychedelic drugs have opened at a

number of research institutions in recent

years, among them Johns Hopkins,

Massachusetts General Hospital, and

New York University. Promising clinical

psilocybin trials in the U.S. led the FDA

to designate psilocybin a “breakthrough

therapy” in 2018, indicating significant

institutional optimism about the

drug’s therapeutic potential. Kwan and

Shao’s own study reflects the growing

acceptance of psychedelic research, given

its publication in Neuron, a prestigious

peer-reviewed research journal.

Even in today’s more liberal

environment, however, obstacles remain


for those interested in conducting

research with psychedelics. “Even

though the public perception is changing

quickly, the funding is still slow,” Kwan

explained. “We had a pilot grant from

Yale, but [this research] is not funded

right now at the federal level, so it’s

tricky.” The National Institutes of Health

has abstained from funding psychedelic

research, even as commercial interest in

psychedelic psychiatry grows.

Moreover, while Kwan and Shao are

optimistic about the therapeutic potential

of psilocybin, they caution against framing

psychedelics as a panacea for mental

illness. Noting “the possibility of adverse

effects,” Kwan described particular risks

for people with a history of psychosis or

cardiovascular issues. “There’s a lot of

hype in terms of what these compounds

can do, but they’re definitely not going to

be a solve-all,” Kwan cautioned.

In the meantime, though, Kwan and

Shao intend to remain an integral part

of this research. The results of their

study offer fertile ground for further

exploration of psilocybin. After observing

the neurological changes induced by

psilocybin, Kwan and Shao are eager

to address new questions regarding

the particular molecular signals, brain

receptors, and neural cell types involved.

Five decades on from the initial

criminalization of psilocybin, the

psychedelic research landscape again

appears bright. While we may not be

“turning on, tuning in, and dropping

out” any time soon, researchers like

Kwan and Shao remind us that the future

of psychiatry may well be psychedelic

after all. ■


ANNA CALAME is a junior in Davenport College studying the history of science, medicine, and public

health. Outside of her work with the YSM, Anna is involved with Yale UAID, YaleBleeds, and the club

tennis team.

RAYYAN DARJI is a sophomore in Grace Hopper interested in studying neuroscience on the pre-med

track. In addition to writing for YSM, Rayyan is involved with the Yale Muslim Students Association,

Alzheimer’s Buddies, and YNEURO.

THE AUTHORS WOULD LIKE TO THANK Alex Kwan and Ling-Xiao Shao for discussing their research

process and findings with them, and the research team would like to acknowledge the non-profit

Usona Institute for providing psilocybin for research.


Shao, L.X., Liao, C., Gregg, I., Davoudian, P.A., Savalia, N.K., Delagarza, K., & Kwan, A.C. (2021). Psilocybin

induces rapid and persistent growth of dendritic spines in frontal cortex in vivo. Neuron, 109(16).

October 2021 Yale Scientific Magazine 21







Studying the structure of bird feathers

could revolutionize engineering

From the bright red-necked tanager to the deep blue crowned pigeon, over ten-thousand

species of birds share the planet with us. Throughout history, their colorful feathers

have flickered ubiquitously into fashion and culture. But where do bird feathers get

their colors from? What makes cardinals red and blue jays blue?

The search for answers to these questions has led to novel discoveries in nanophotonics

and soft-matter physics. A recent Yale study on how birds make blue feathers—led by Vinod

Saranathan, Ornithologist and Applied Physicist at Yale-NUS, and Richard Prum, William

Robertson Coe Professor of Ornithology at Yale—opens new avenues in many line of research,

from understanding the physics of cell biology to creating more efficient solar panels.

22 Yale Scientific Magazine October 2021




Prum, who is also head curator of

vertebrate zoology at the Yale Peabody

Museum, explores the relationship

between the phenotypic diversity of bird

species and their evolutionary history.

“I was interested in paleontological

discoveries in bird feathers, and also a

sideline on pigmentation and coloration,

and before you know it those two worlds

connected,” he said.

How Bird Feathers Have Color

In some birds, feather colors are

produced by pigments, like brown

melanins and orange carotenoids. In many

other birds, however, colors are produced

by the intrinsic structure of the feather.

In these “structurally colored” feathers,

light is scattered off proteins coating

secondary feather barbs—microscopic

comb-like fronts that doubly extend out

from the stiff center of a feather and then

stock together into a vane.

Some structural colors are iridescent:

light bounces off at different angles on

a feather’s surface creating positive and

negative overlap, resulting in a feather

whose color changes depending on the

direction from which you look at it.

Peacocks have iridescent feathers, and

they change from blue to turquoise as the

bird moves around. However, blue jays,

blue grosbeaks, and several other birds

have non-iridescent feathers: they always

look blue, no matter what direction you

look at them. And they never fade. “Birds

that were collected one-hundred years

ago look just as lifelike as if they were

collected today,” Saranthan said.

The barbs of non-iridescent birds’

feathers are made of a protein called

β-keratin, which forms nanostructures

interspaced by pockets of air that evenly

scatter different wavelengths of incoming

light, creating a pure single color.

These structures grow by a process called

phase separation, which also happens

when you pour soda into a glass. In the

pressurized soda can, the carbon dioxide

and water are thoroughly mixed. When

the can is opened, the pressure changes,

and carbon dioxide rises from the liquid

in the form of bubbles, which form foam

on the sides of the glass. Drop a coin in the

glass and you’ll see bubbles form on the

surface of the coin as well; bubbles need

nucleation sites, or central hubs, to form


and grow over time. At the nanoscale,

this is what generally happens in bird

feathers, except that while carbon dioxide

forms spherical bubbles, β-keratin in bird

feathers forms a variety of shapes.

Previously, using scattering patterns from

super-high intensity X-rays, Prum and

Saranathan had identified structures made

from keratin fibrils in the surface patterns

within feathers of every single bird in the

ornithology collection of Yale’s Peabody

Museum. “There are two types of structures

we thought were generated,” Saranathan

said. “One looked like swiss cheese, or

bubbles in a beer foam. The other one

looked like nano-spaghetti—you get this

random jumble of keratin fibrils in the air.”

However, while perusing the feathers

of different bird species, Saranathan and

Prum found something that, as Saranathan

puts it, “looked very funky.” In the leafbird

species, found only in Asia, iridescent colors

were not produced in the secondary feather

barbs, but in the primary feather branches.

“That was really a clue that something

new was going on here,” Saranathan says.

Rather than the swiss-cheese or nanospaghetti

subunits lining the surface of

the feather, the building blocks formed by

β-keratin took the shape of a new, complex

topological structure called a single gyroid.

Gyroids: A Game-Changer

A gyroid is an example of what

mathematicians call a minimal surface,

a shape that takes the least amount of

surface necessary to span a given region

of space. Structures with high-surface

area-to-volume ratios, like a human

brain, consist of lumps and folds and have

a high degree of average curvature. At

any given location on the gyroid surface,

however, the positive bumps

and negative depressions even

out to zero, yielding a mean

curvature of zero.

Gyroids are minimal

surfaces that are triply

periodic, meaning that a small piece

on the surface can be repeated in three

independent directions to assemble the

entire surface. What gives the gyroid its

characteristic shape is that it has no planes

of reflectional symmetry and no straight

lines at any point along its surface. Any

point along its surface lies in a region that

looks something like a saddle.

Ten years ago, Saranathan had

conducted X-ray analysis on iridescent

green butterflies and found these

same single gyroid structures. Though

these structures have been modeled by

scientists and mathematicians since the

1970s, Saranathan’s butterfly discovery

was the first time they had ever been

positively identified in nature.

The single gyroids that Saranathan and

Prum identified in birds and butterflies

represent a game-changer for several

reasons. For one, single gyroids are

structurally distinct from the far more

common double gyroid structures,

which consist of two interlocking gyroid

surfaces enmeshed together. Unlike the

double gyroid, the single gyroid has

both a full electronic bandgap as well

as a full optical bandgap, which means

that it completely traps all directions

and polarization states of light and easily

excites electrons to a conductive state.

This gives single gyroids better electronic

(conductive) and optical (reflective)

properties than double gyroids. Thus,

they could be an incredibly useful tool

in solar cells for sequestering light and

turning it into electricity.

Additionally, Saranathan and Prum’s

discovery could open up new ways

of directly synthesizing single gyroid

nanostructures, which could serve as

a powerful optical tool for a variety of

disciplines. Currently there is no way

for engineers to make the single gyroid

directly. Saranathan and Prum explained

that soft-matter engineers instead embed

Lego-like molecules with hydrophobic

and hydrophilic components in solution,

where they locally reorder into a double

gyroid structure. Engineers

then chemically


one of

October 2021 Yale Scientific Magazine 23




Dr. Vinodkumar Saranathan with models of a double gyroid (left) and single gyroid (right).

these components, backfill the empty

space with gold, and burn away the

remaining organic complement. This

process leaves a single gyroid made

of gold, which can then be used as a

template to form single gyroids from

other materials.

Inherent limits in this double gyroid

etching process make it impossible to

synthesize single gyroids larger than fifty

nanometers in unit size. Unfortunately,

single gyroids that interact effectively

with light are around five-hundred

nanometers. Researchers have yet to

find a way to synthesize one of that size.

Both butterflies and birds, however, have

figured out the process.

Making Single Gyroids

Saranathan used X-ray analysis to observe

the β-keratin structures in other species

that are sister species to single gyroid

leafbirds. He found swathes of keratin

nano-spaghetti, assembled through

phase separation. Prum noted that it is

highly likely that two species diverged

from a common ancestor by way of the

nanostructure formed, keeping the same

general formation process.

Crystal structures produce more

saturated colors. For that reason,

Saranathan suggested that keratin

structures resembling single gyroids were

preferred by some female leafbirds over

those resembling nano-spaghetti.

Nevertheless, these birds somehow form

single gyroid crystals without ostensibly

having to form a double gyroid first.

“The way they are making this is new to

science, period,” Saranathan said. “New

to biology, new to engineering, new to

physics.” Birds’ spontaneous self-assembly

of these structures illuminates the exciting

potential for humans to recreate this selfassembly

in the laboratory.

Single gyroids and their discovery in

living systems represent a breakthrough

in a vast number of scientific disciplines.

The optical structures used by birds to

make colors can also be used to better

manipulate the flow of light. This makes

them highly applicable in solar cell

technology. A structural approach to

creating color, rather than one based off

pigments, could inspire the development

of sustainable and less toxic paints,

tiles, textiles, and cosmetics that resist

fading over time, too. Furthermore, the

formation of networks and gel matrices

from large liquid-like particles, similar

to how keratin forms single gyroids,

is a process nearly ubiquitous in cell

biology. A better understanding of single

gyroid synthesis could lend insight into

organelle-less phase separation—a

widely growing area of interest in cell

biology—soft-condensed matter physics,

and physiological systems.

In an age where nanotechnological

structures in computer chips and rapiddiagnostic

tools are designed to optimally

control the flow of electrons and light,

learning from self-assembled structures

like single gyroids could open up whole

new areas of research. “This is an example

of why I think bird-watching science

matters,” Prum said. “That tension

between irregularity and specificity is

something that I really enjoy, and this

research is a great example of the way in

which that works together.” ■

Curiously, butterflies make single

gyroids the same way researchers do—

only somehow, they’re able to make them

ten-times larger than engineers can.

But “the birds,” Saranthan said, “are

completely revolutionary.” In contrast

to butterflies, there’s no templating.

Birds like the blue jay seem to make

single gyroids spontaneously by phase

separation, as if they dropped a quarter

in a glass of soda and single gyroids

assembled on the coin’s surface.

To ascertain the spontaneous generation

of single gyroids by phase separation,

24 Yale Scientific Magazine October 2021



RYAN BOSE-ROY is a sophomore in Trumbull majoring in Biomedical Engineering and “something else,

we’ll figure out what it is.” In addition to writing for YSM, Ryan works the Trumbull buttery shift on

Sunday nights, where he delights in making quesadillas and regaling customers with stand-up bits while

taking their orders.

THE AUTHOR WOULD LIKE TO THANK Dr. Prum and Dr. Saranathan for their time and willingness to

be interviewed for the article. At the request of Dr. Saranathan (and at the author’s own discretion), the

author would like to acknowledge the Yale Peabody Museum for its existence.


​Saranathan, V., Narayanan, S., Sandy, A., Dufresne, E. R., & Prum, R. O. (2021). Evolution of single gyroid

photonic crystals in Bird Feathers. Proceedings of the National Academy of Sciences, 118(23). https://doi.









Over millennia, the egg has evolved to become one of the

most adaptable shapes in nature: strong, small enough

for safe delivery, and capable of surviving in extreme

conditions. This distinctive shape has long been a subject of

fascination among researchers. “[We are investigating] whether

some mathematical laws were designed first and nature was

created in accordance to them, or vice versa,” said Valeriy

Narushin, a researcher at Vita-Market Ltd and the Research

Institute for Environment Treatment in Ukraine. Narushin’s

recent work on developing a universal mathematical formula

for egg shape demonstrates a collaboration between biologists,

engineers, and scientists, united by a common desire to crack

the mystery of this unique natural phenomenon.

There are four main categories of egg shapes: circular,

elliptical, oval, and pyriform. The most commonly recognized

egg shape, which we encounter in chicken eggs, is the oval. “​As

for me personally, I like pyriform, or speaking in mathematical

language, conical eggs. These are laid by some species of

waders and guillemots,” Narushin said. Pyriform, in contrast

to the oval, is a more unconventional “pear-like” or pointed

shape. There are many hypotheses as to why certain types of

eggs evolved this way, ranging from their structural integrity

to their ability to fit into nests efficiently, but there is no clear

explanation yet as to why some eggs converged to a pyriform

shape over time.

At first glance, it may seem quite straightforward to map the

shape of an egg using mathematical equations. However, while

these equations are very good at creating idealized egg shapes that

can be used in art and architecture, they fall short when it comes

to tracing a real egg. Thus, the challenge was to deduce a universal

mathematical formula that corresponds to all types of egg shapes

and is easily transferable between geometrical figures.


The researchers successfully developed a more complex,

universal formula based on measurements of the egg length,

maximum breadth, vertical axis shift, and diameter at one

quarter of the egg length. This formula allows them to

theoretically describe any avian egg, keeping in mind that

small discrepancies are to be expected due to the diversity of

eggs as a natural object. Importantly, the formula can describe

the shape of any of the four egg types—a feat that has never

before been achieved to this level of accuracy.

In the process of collecting data for this study, the researchers

also furthered a more comprehensive project aimed towards

sustainable and nondestructive methods of egg evaluation.

“Elaboration of non-destructive methods for testing eggs is the

basic goal of our research group, which we call the ‘Eggy-team,’”

Narushin said. The researchers used images instead of actual

eggs whenever possible and did not handle any endangered or

wild bird eggs. This is part of a long-term goal: the development

of non-invasive research methods can improve poultry

management and environmental conservation efforts.

But why the obsession with eggs? “According to Professor

Tim Birkhead, [eggs] are the most perfect things on the Earth.

And we fully agree with him. From ancient times, eggs were

used as cult objects in art, architecture... etc. And of course,

an egg is an excellent food used in more than ten-thousand

recipes,” Narushin said.

The study of eggs has far-reaching impacts. In the food

industry, egg density and the ratio of egg weight to surface area

are crucial in considering egg freshness, shell thickness, storage

conditions, and incubation success. “If you know a geometrical

formula of a given egg, it’s rather simple to recalculate all these

parameters (curvature, a longitudinal length and others) with

equations of the integral geometry,” Narushin said.

The egg also provides a source of architectural inspiration.

“The egg profile has several advantages for architects due to its

harmonic shape, relative strength, and minimal consumptions

of building materials,” Narushin said. “Famous egg

constructions include The National Centre for the Performing

Arts in Beijing and the Gherkin in London.” From food science

to art, the egg has an influence far beyond what its humble

appearance may suggest.

Now that this universal formula has been found, what lies

in the future of oomorphology? “The first [investigation] is

based on deducing universal formulae for calculating volumes

and surface areas of different egg types, and their ingression

into the principles of mathematical evolution,” Narushin said.

“The second one is related to the study of shell mathematical

secrets. Why is the shell relatively thick in some species and

thin in others? Hope we can propose some results very soon.”

So the study of eggs continues, one formula at a time. ■

October 2021 Yale Scientific Magazine 25







These days, it’s hard to escape the reality of climate change

in daily life. Carbon dioxide is one of the main greenhouse

gas drivers of climate change: according to the EPA, 6,558

tons of the gas were emitted in the United States in 2019 alone.

But what if there was a way to ‘harness’ this carbon dioxide and

instead transform it into usable energy? Enter: carbon capture.

Researchers from the US Department of Energy’s Pacific

Northwest National Laboratory (PNNL) recently discovered a

new method of integrated carbon capture that converts carbon

dioxide into methane, a main component

of natural gas. The reactants of this

method include waste carbon

dioxide, a 2-EEMPA solvent, and

renewably sourced hydrogen.

While traditional carbon

capture methods usually boil

the carbon dioxide out (the

capture step) before shipping

it elsewhere to be converted into

methane (the conversion step), this

new process simply passes the carbon

dioxide over a catalyst and mixes it

with hydrogen, all in one chamber,

completing the conversion at one site.

“Rather than just doing the wasteful

regeneration [of carbon dioxide],

we’re just doing the conversion at the

same time,” Heldebrant said.

And best of all? This method presents

the lowest price of carbon capture so far.

The 2-EEMPA solvent used in the method

has been in development for fourteen years

with corporations such as Florida Corporation, GE Global

Research, and University Partners, with twenty-million dollars

of Fluor Corporation funding. Unlike traditional solvents,

2-EEMPA has a low water content and can more easily dissolve

carbon dioxide, while requiring less overall energy to complete

the conversion process. Previous methods required high

temperatures to push the equilibrium in favor of the conversion,

but 2-EEMPA simply allows the chemicals involved to facilitate

the conversion to methane, necessitating only about half of the

typically required temperature and pressure.

Because of this ability to reduce the amount of energy used in

the conversion of carbon dioxide to methane, using 2-EEMPA



in power plants could decrease the price of carbon capture by

nineteen percent. “Right now, everybody talks about wanting

to do carbon capture, but there is a high cost,” Heldebrant said.

Current commercial technology can capture carbon dioxide at

$58.30 per metric ton, but this new method costs only $47.10

per metric ton. This method therefore reduces total capital

investment by thirty-two percent and the minimum selling

price for natural gas by twelve percent.

It’s important to note that while this new process produces

methane, which is itself a harmful greenhouse

gas, synthetic methane’s carbon neutrality

and household and industrial uses still

make it an improvement over other

forms of methane. Furthermore,

Heldebrant’s project was funded

in California, where the new lowcarbon

fuel standard prohibits the use

of methane derived from fossil fuels

in a few years. This makes Heldebrant’s

research even more vital for companies

currently relying on producing natural gas.

“Ultimately in the long term, we would love

to see everything go to renewables, but at

least right now, we would much rather see

something that’s carbon-neutral as opposed

to carbon-positive just pulling the methane

out of the ground,” Heldebrant said.

Compared to previous methods, this

method’s low price creates financial incentives

for carbon capture, but it also creates a potential

problem of oversaturation of the methane

marketplace once the method becomes large-scale. “If

we’re only going to be making methane, you’re going to disrupt

the entire methane marketplace, and then that basically means

there’s no longer an economic driver to do it,” Heldebrant said.

In the future, PNNL hopes they can find new substances to

which they can convert waste carbon dioxide, such as dimethyl

ether (a type of diesel additive), cyclic carbonate (a type of

electrolyte solvent in batteries), and polymer carbon dioxide.

The work to pioneer carbon capture technology at such low

costs has been decades in the making, but this new research

has finally shown that cheap carbon capture technology is not

only feasible, but also has the potential to become a beneficial

driver of the economy and environment. ■

26 Yale Scientific Magazine October 2021 www.yalescientific.org







How do supermassive black holes swallow up matter and help

drive the galaxies of our universe? This fundamental question

in astrophysics has yet to be fully answered, but it strikes at

the heart of our creation and existence. Supermassive black holes,

present in most galaxies, play a key role in galaxy evolution through

their gravity, but nobody knows exactly how. In particular, the way

these supermassive black holes accrete matter has been uncertain. For

example, quasars—active galactic nuclei powered by supermassive

black holes—are so powerful that they can outshine their entire host

galaxies and be seen billions of light-years away. But how can so much

gas accrete so rapidly as to sufficiently power these quasars?

Earlier this year, Daniel Anglés-Alcázar’s research group at the

University of Connecticut made groundbreaking success in modeling

black hole-galaxy interactions, finding a viable mechanism for

black hole gas accretion and quasar luminosity. This

model is unique in its use of novel mathematical

techniques, dubbed “Lagrangian Hyper-refinement,”

to accurately represent the flow of gas into a black

hole on both small and large scales at once.

Previously, researchers had to make simplified

guesses as to how black hole accretion would

influence their galactic models, as the galactic

models didn’t have the necessary resolution to

incorporate existing black hole accretion models.

This was a major limitation, considering how much the

black holes’ mass could influence surrounding structures. But Anglés-

Alcázar’s new model is able to do the equivalent of “adding more pixels to

an image in the region where you want to zoom in,” he said, dynamically

generating more gas circulation elements wherever the black hole is at

any given moment to increase the resolution. Hence, even though the

model begins on a multi-galactic scale, one can zoom in a million times

at its center and see activity on the scale of only a few light-years.

The model’s results have been very promising. The presence of

large asymmetries in galaxy shapes was found to be crucial to the

accretion process. As a galaxy rotates, its asymmetrical parts,

such as spiral arms, exert a constant gravitational pull on

rotating gas. This makes the gas slow down, fall into smaller

orbits, and eventually fall into the black hole. The model

produced fractal-like generations of such spiral arms

from the galaxy scale down to the accretion disk scale,

supporting this theory’s application on all scales.

Most impressively, under some conditions, the inflow

of gas into the black hole was found to be large enough

to explain luminous quasars. In other words, gas was


entering the black

hole fast enough

to account for the

quasar’s energy

output. “This was

the first time that

a single simulation

covering the whole

range of scales had been

able to show that effect,”

Anglés-Alcázar said.

When the researchers studied

the few quasars near enough to

the Earth to observe in detail, they

obtained results that resembled the

model’s. Additionally, the model shows

that, surprisingly, even supermassive black

holes can move substantially over time, and

galaxies change their shapes by the interactions

between their arms and migrating central black holes.

But an even bigger surprise was that the model, with certain

starting conditions, also showed that galaxies often go into and out

of active phases over time. Dormant supermassive black holes—such

as our own galaxy’s Sagittarius A*, which doesn’t accrete much matter

at the moment—can become active again after several million years by

similar steps as described previously. The process, however, occurs at a

much lower level, with galactic features slowing gas down and

making it fall inward. These results greatly enhanced the

team’s confidence in the model, as they not only matched

known statistics on the frequency of dormant versus active

black holes, but also showed that the model could cover

two different situations despite being made for only one.

Anglés-Alcázar is very optimistic about his model’s

future. “We can do these kinds of experiments on dwarf

galaxies or on galaxies more like our own Milky Way, or

the same galaxy but at an earlier phase, or even the very early

universe, back when the first galaxies were forming,” he said. Anglés-

Alcázar also wishes to make the model even more accurate by

including the effects of black holes’ strong winds and relativistic jets.

The door is wide open to new discoveries. And

each discovery is another crucial step towards

understanding our world. “In order to

understand galaxies, we have to first understand

black holes,” Anglés-Alcázar said. ■

October 2021 Yale Scientific Magazine 27


Computational Biology







Over the past year and a half,

our hospitals, overwhelmed by

COVID-19 patients desperate

for oxygen, have been debilitated by

staff and resource shortages. While

many called for vaccines as a hopeful

cure-all, some recognized a faster

alternative: efficient and deliberate

distribution of hospital resources.

Fourth-year PhD candidate Amogh

Hiremath and Professor of Biomedical

Engineering Anant Madabhushi at

Case Western Reserve University were

among the bioengineers who confronted

this problem. “It’s particularly heartwrenching,

as a father myself, to

see pediatric wards filled up… kids

[who] require critical surgeries just

don’t have a bed,” Madabhushi said.

Recognizing that delayed or inaccurate

risk assessments could prove fatal,

Hiremath and Madabhushi developed

CIAIN (integrated clinical and AI

imaging nomogram), the first deeplearning

algorithm to predict the

severity of COVID-19 patients’

prognoses based on patient CT lung

scans as well as clinical factors.

Artificial intelligence, at its core,

endeavors to mimic processes within a

human brain. Similar to how humans

take lessons from past experiences and

apply them to novel situations, computers

“learn” information from a training set

and apply it to a testing set. In the case

of a prediction algorithm like CIAIN,

computers are initially fed information


from existing patient data to correlate

features of CT scans and clinical test

results with patient prognoses. Once

the algorithm is trained, it can then be

applied to novel patient information—

the testing group—and give prognoses

with a high degree of precision. CIAIN

is the “first prediction algorithm

to use a deep learning approach

in combination with clinical

parameters,” Hiremath said.

This makes it more accurate than

algorithms using imaging alone.

Another major advantage of

CIAIN lies in its speed of

deployability: given that

accessing medical datasets

is relatively difficult

compared to obtaining

a set of natural images,

Hiremath and Madabhushi

used roughly one-thousand

patient scans from hospitals

in Cleveland, Ohio and

China to train, fine-tune,

and test their model. And

notably, CIAIN is the

first algorithm designed

for COVID-19.

Given that their

paper only examined

unvaccinated patients,

Madabhushi and Hiremath

now want to investigate

if they can find the risk of

hospitalization for vaccinated

individuals. “As we hear

about new breakthrough infections, the

question is if we need to run the analysis

retrospectively on patients who have been

vaccinated,” Madabhushi said. However,

while it is one thing to create predictive

algorithms retrospectively, it is another

to apply such algorithms to novel patient

data without prior physician evaluation.

A prospective study—a study that follows

patients before their ultimate outcomes

are known—would employ a dualpronged

approach. First, the researchers

would evaluate the algorithm in the pilot

phase of a prospective non-interventional

trial, where radiologists would upload

a CT scan and the algorithm would

generate a risk score for a patient. In a

few months, if the tool performed well,

the study could then transition into a

prospective interventional form, and the

researchers could propose the algorithm

to the FDA for clinical approval.

Despite anticipating the usage of CIAIN

in the emergency room, Madabhushi was

careful to emphasize the limited role

28 Yale Scientific Magazine October 2021 www.yalescientific.org

Computational Biology


even very advanced algorithms can play

in clinical settings. The vast majority of

AI algorithms in the foreseeable future

are intended to be decision support tools;

they merely augment and complement the

physician’s interpretation by aggregating

data and prognosticating patient

outcomes more accurately. Ultimately,

only physicians interact with patients

and thus are the best individuals to make

treatment decisions. Madabhushi likened

the role bioengineers like himself and

Hiremath play in healthcare to the role

aircraft engineers play in improving

functionalities on the console of an

airplane. Ultimately, the physicians are

the pilots in the cockpit.

No discussion on novel AI technology

is complete without considering

possible biases in the model and the

effects of such biases. Imagine an

algorithm trying to classify whether

or not an object is ice cream. If, in

training the algorithm, one only feeds

it images of vanilla ice cream in a cone,

the algorithm is likely to reject images

of any other flavor, since it is not used

to classifying anything but vanilla ice

cream cones as ice cream. Simply put,

algorithms are biased if the correlations

they have learned from a certain

training set (vanilla ice cream cones)

can’t be extrapolated to the testing set

(ice cream of all types).

While this example may be

innocuous, biases in models used

in healthcare can have life-ordeath

consequences. This year, the

American Society of Nephrology

finally updated their model for

calculating glomerular filtration

rate, which was originally

based on assumptions derived

from Caucasian patients.

Their old model was

found to make inaccurate

calculations for African

Americans, culminating in

frequent misdiagnoses of

chronic kidney disease.

Even if AI just provides a

single data point for physicians

to use in decision-making,

AI predictions are often given

precedence over other data points

“The future of AI in healthcare

seems clear, but its implementation

remains challenging.

due to the complex methodology by which

models aggregate information. Hence,

ensuring that AI predictions are as accurate

and unbiased as possible is crucial.

Even without prompting, Madabhushi

and Hiremath highlighted the methods

by which they attempted to avoid

introducing biases to CIAIN. “We

were very deliberate and purposeful

in making sure the data was collected

from a few different sites,” Madabhushi

said. Diversifying the source of data

generalized the algorithm and also

reduced the likelihood of a “leakage

problem,” a known biasing factor

AI models face when data is poorly

separated between the training set and

testing set. The resulting overlap means

the algorithm will learn the training set

well and accurately classify the testing

set, but will demonstrate poor accuracy

in classifying a new “validation”

testing set because it hasn’t learned

enough variation. Both Hiremath and

Madabhushi expressed the need for

further validation to verify CIAIN is

sufficiently generalizable.

While generalizing models might

help decrease bias, it is not a fixall.

With African American patients

three-times more likely to die from

COVID-19 than Caucasian patients,

an algorithm trained on a mixed-race

group may fail to accurately predict

prognoses for either group. Scientists

must integrate how social determinants

of health—including ethnicity, race,

and socioeconomic status—play a role

in disease manifestation and prognosis.

“While we haven’t explicitly explored

these factors with our methodology and

platform yet, it is definitely something

we want to look at,” Madabhushi said,

who is of the strong belief that scientists

need to get away from the idea that “one

model fits all.” In fact, Madabhushi

and Hiremath have compared the

accuracy of models specific to different

ethnic groups for breast, uterine, and

prostate cancer—in each case, the

model designed for the subpopulation

yielded more accurate predictions than

a more general model. Madabhushi

expresses hope that “[scientists] will get

to the point where there is a buffet of

models and a physician can selectively

invoke a model based on the ethnicity

or other attributes of their patient.

Otherwise, we are doing a disservice to

underrepresented populations.”

In theory, the future of AI in

healthcare seems clear: scientists must

identify differences among populations

and incorporate them into increasingly

population-specific algorithms. But its

implementation remains challenging:

one of the biggest hindrances

scientists face is a lack of data from

underrepresented populations. Until

this data can become readily available

via drastic institutional and structural

change, it is up to scientists like

Hiremath “to improve the current

prediction models in a step-by-step

manner, improve the biases that are

involved, and create a usable product.”

As AI becomes increasingly ubiquitous

in healthcare, there are fears that biased

and over-generalized algorithms are

being put into practice faster than

refined and population-specialized

algorithms are being created. We

must remember that the personalized

aspect of medicine—the conversations,

interactions, and human observations—

are just as, if not more, important than

an algorithm’s score. AI can be a fantastic

passenger-seat navigator to a physician

driver. But society must be careful not to

let AI take the wheel, lest the tool meant

to improve patients’ survival endangers

it instead. ■


October 2021 Yale Scientific Magazine 29


Computational Biology






The fact that the Earth rotates

around its axis once every

86,400 seconds seems like a

faraway explanation for the passage of

time, but what if this simple concept

actually relates to the most important

physiological and behavioral processes

in our bodies? Our internal circadian

rhythm is a twenty-four-hour biological

clock that influences everything from

our sleep cycle and metabolism to our

immune system and susceptibility

to disease. Understanding the gene

expression that underlies such a

fundamental adaptation for life poses

many challenges for scientists, but

modern artificial intelligence (AI)

algorithms and machine learning

(ML) models provide new avenues into

exploring such scientific questions.

A team of researchers at the Earlham

Institute in Norwich, England recently

conducted a study to increase the

transparency of how ML systems work,

while also shining light onto the most

advanced computational system we

know of: the human brain.

Circadian rhythms depend on many

factors, including environmental

stimuli like light and temperature. This

is one of the reasons why changing

time zones can cause us to experience

jet lag—a misalignment between our

body’s expectation of the day-night

cycle and the changing cues presented

by a new geographical location. It has

been experimentally determined that

these circadian rhythms are controlled

by the expression of specific genes

that oscillate between on-off states

during the twenty-four-hour intervals.

However, past efforts to detect this

circadian rhythmicity have required

the generation of long, high-resolution

time-series datasets, an effort that

is expensive, inefficient, and timeconsuming.

To work with such large

amounts of data, the researchers took a

new approach, involving a combination

of AI and ML algorithms, to predict

circadian gene expression.

Hussien Mohsen, a researcher in the

Gerstein Lab at Yale who was not involved

in the study, further explained the

intersection between artificial intelligence

and gene expression research. Mohsen

focuses on interpretable machine learning

for cancer genomics—a field where, as

in the circadian rhythm field, there has

been increasing interest in deep learning

algorithms (a subset of machine learning)

in recent years. According to Mohsen,

this is particularly due to technological

advancements, which allow us to generate

the immense archive of data that lies at the

heart of deep learning. “Interpretability

of machine learning has become way

more popular with deep learning for

that particular reason: because you have

enormous amounts of data,” Mohsen

said. “The models become so incredibly

complex that we need to simplify them—

our human cognition can't really follow

what's going on.”

When it

comes to applying

these data analysis

tools to the field of

biology, scientists must

ensure that AI techniques

are simultaneously

efficient and reliable so

that the results generated can be applied

to the whole population being studied.

In computing, the “black box” refers

to systems that are considered only in

terms of their inputs and outputs, with

no real understanding of their inner

workings. As powerful as AI algorithms

are for navigating increasingly complex

issues, this lack of transparency raises

concerns for future research: how

is the model transforming data into

results? How are the ML algorithms

making decisions based only on pattern

identification? And if there are any

issues, how would we know?

To this end, in their study of circadian

rhythms, the Earlham Institute researchers

formulated an approach involving three

key elements: 1) developing ML models

that quantify the best transcriptomic

timepoints for sampling large gene

sequencing datasets while reducing the

overall number of timepoints required;

2) redefining the field by using only

DNA sequence features rather than

transcriptome time point information; and

30 Yale Scientific Magazine October 2021 www.yalescientific.org

Computational Biology



The circadian rhythm, also known as the body’s

“biological clock,” is endogenous (originates

from within an organism), but also influenced

by environmental variables, including light,

temperature, and geographical location.

3) decoding the “black box” of ML models

to explain the mechanism of how AI is

used to predict circadian clock function.

In order to effectively analyze the

expression of circadian rhythms, the

researchers chose the small flowering

plant Arabidopsis thaliana as a model

organism. Arabidopsis was the first plant

to have its entire genome sequenced, and

because some of its regulatory elements

were already known, the researchers used

that pre-existing knowledge to validate

their ML predictions. This allowed them

to understand how their ML model was

reaching its predictions, thereby decoding

the mystery of the AI black box.

When there are tens of thousands,

even millions, of data points, how do

we understand that data and extract

their patterns and trends? Mohsen

explained that we learn by finding

parameters that capture what patterns

exist—the more sophisticated the data,

the more parameters we need. But using

more parameters necessitates a greater

understanding of what each does.

“There are multiple approaches and even

definitions of what interpretability is,”

he said. Fundamentally, though, “it is

just learning how the prediction process

works or which input features are

corresponding to a specific prediction.”

The Earlham Institute researchers

used MetaCycle—a tool for detecting

circadian signals in transcriptomic

data—to analyze a dataset of Arabidopsis

genomic transcripts. Using this

information, the researchers trained

a series of ML classifiers to predict

if a transcript was circadian or noncircadian.

They found that the AI was

not just using gene expression levels,

but also timepoints for its predictions.

However, these predictions were not

always one-hundred percent accurate,

and the researchers thus set out to

ascertain the optimal sampling strategy

and number of timepoints needed.

Circadian gene expression rhythms

follow diverse patterns, but all share a

twenty-four-hour periodicity. Having

fewer timepoints is more efficient, but leads

to concerns over loss of information and

accuracy. The researchers aimed to find the

optimal balance between a low number of

transcriptomic timepoints and improved

accuracy, so they started with a twelve

timepoint ML model and sequentially

reduced it to three timepoints.

The explainablity aspect of their

model comes with understanding how

the model was making its predictions.

The researchers needed to see which

k-mers (short sequences of DNA) were

the most influential in impacting the

ML model's predictions, and found that

the most accurate predictions resulted

from a k-mer length of six.

“[Machine learning] has

already reshaped a significant

part of how we study the

biology of disease.

Overall, the study showed the

possibility for reducing the number of

transcriptomic timepoints while still

maintaining accuracy in predicting

circadian rhythmicity. Since creating

datasets takes significant time and

resources, a reduction in sampling could

have important long-term impacts in

increasing efficiency.

The findings of this study have major

implications for the future of biomedical

science and AI: recent studies have

shown that disruption of clock genes

is associated with sleep disorders,

heightened susceptibility to infections,

Alzheimer’s disease, and metabolic

syndrome. “[Machine learning] has

already reshaped a significant part of

how we study the biology of disease,”

Mohsen said. “I very much see AI playing

a larger role in drug development and in

terms of the way we study biology.”

More recently, Mohsen and the Earlham

Institute researchers have shifted to a

new focus: advancing the clarity of how

and why these powerful algorithms

are providing the predictions that they

do. As scientists explore foundational

questions of how human physiology

works, understanding the powerful tools

used in probing those questions is just

as crucial. According to Mohsen, having

unexplainable AI poses “a huge risk

in medicine and elsewhere” due to its

prevalence in everyday life, including face

recognition, surveillance, and biohealth.

In illuminating the “black box” for

ML models that predict circadian

rhythms, research merging transparent

AI and genomics opens possibilities for

understanding the rapidly-developing

technology in our hands. Ultimately, this

has implications for precision medicine,

novel drug development, and decoding

the genetic basis of disease in the future. ■


October 2021 Yale Scientific Magazine 31






He had not been able to speak

for sixteen years. At the age of

twenty, the patient, known as

BRAVO-1, experienced a severe stroke

resulting in paralysis and anarthria,

the loss of the ability to articulate

speech. But now, after the implantation

of a novel neuroprosthesis, BRAVO-1

can communicate efficiently with the

world—using only his brainwaves.

Edward Chang, neurosurgeon and

Chair of Neurological Surgery at the

University of California San Francisco

(UCSF), spearheaded this decades-long

effort to successfully decode words and

sentences from neural activity.

Chang’s journey with the brain started

during his time in medical school

at UCSF, where with brain mapping

techniques he observed surgeries

where the patients were actually awake.

“It dawned on me that there was a

huge, huge need to better understand

how the human brain works to treat

neurological conditions that we don’t

necessarily have cures for yet,” Chang

said. “I decided to go into neurosurgery

because it not only allowed me to work


directly with the brain, but also take

care of patients in a way that’s hard to

do in other fields.”

In addition to practicing, Chang

conducts research as co-director of

the Center for Neural Engineering and

Prostheses, which is a collaborative

organization between UCSF and UC

Berkeley that focuses on developing

biomedical technology to help people

with neurological disabilities like

paralysis and speech disorders.

Over the last decade, Chang’s lab

intently studied the region of the brain

that controls the vocal tract. “What we

found was a map of the different parts of

the vocal tract and kinematic properties

that give rise to speech,” Chang said.

This neural code for every consonant

and vowel is composed of elemental

movements, such as the tongue moving

forward, that are very precise and highly

coordinated. With this newfound

knowledge, they sought to create a

device that could translate brain activity

into words. Thus, over the past decade,

Chang and his research group have

been working on a “neuroprosthesis”—a

device that can record and decode the

participant’s brain activity, then display

their “speech” on screen.

Helping to lead these efforts is postdoctoral

researcher David Moses,

whose interest in programming,

bioengineering, and their intersection

with medicine and neuroprosthetics

led him to the Chang lab. Thus began

the BRAVO (BCI—brain computer

interface—Restoration of Arm and

Voice) clinical trial, in which Chang and

his team enrolled their first participant,

BRAVO-1, to begin testing the potential

speech neuroprosthesis.

The neural implant, composed of 128

electrodes that record neural activity

from the surface of the brain, was

implanted in BRAVO-1 over the brain

region that controls the vocal tract.

Unlike the telepathic transmission

commonly depicted in sci-fi movies,

this technology relies on the patient

trying to engage in speech: the implant

detects these signals, which are then

analyzed. “This isn’t like mind reading

or any internal monologue… it has to

be controlled by volitional attempts

to speak,” Moses said. Alongside the

development of the hardware, Chang’s

research group primarily focused on

creating and programming the software

behind this new device.

In February of 2019, they implanted

the device in the patient’s sensorimotor

complex, which controls speech. Two

months later, BRAVO-1 began to attend

fifty data-recording sessions over a span

of eighty-one weeks. “[BRAVO-1] is an

incredible person and truly a pioneer.

Even though we had a lot of proof of

principle, there’s a lot of reasons it might

not have worked,” Chang said.

One such concern was that after the

patient had not spoken for over fifteen

years, there was no telling how much

information about his speech attempts

would be represented in the expected

part of his brain. During each session,

the participant performed many trials of

two different tasks: an isolated-word task

and a sentence task. Twenty-two hours of

data were collected from over 9,800 trials

of the former task, which involved the

participant’s attempts to say one word

from a predefined set of fifty common

English vocabulary words. In addition,

250 trials of the sentence task, in which

32 Yale Scientific Magazine October 2021 www.yalescientific.org





the participant attempted to produce

word sequences from the same set, were

also performed. Both tasks helped the

researchers train, fine-tune, improve,

and evaluate their computational models.

Finally, the conversational variant of the

sentence task was implemented, in hopes

of demonstrating a real-time sentencedecoding

process. The participant was

first visually prompted with a question

or statement onscreen. Then, he tried to

speak in response to the prompt from a

predefined set of fifty common English

vocabulary words. The electrode arrays

in the implant detected and collected

the brain signals, which were then

sent and processed in real-time to the

computational processing system.

In the system, first, a speech detection

model identifies when the participant


has been attempting to speak. This

algorithm specifically detects the

onsets and offsets of the participant’s

word production attempts directly

from brain activity, limiting the

temporal window of relevant signals

analyzed in the later steps. Next, a word

classification algorithm predicts the

probability that each of the fifty words

has been attempted. However, this is

not as simple as identifying one signal

associated with one word. “There isn’t

one particular part of my brain that

only lights up when I’m saying just that

word,” Moses said. Instead, when we

pronounce certain words, our brain

relays signals to our vocal tract, which

then performs certain articulatory

gestures such as opening our mouths.

Thus, the brain activity processed by

the neural implant is not necessarily

limited to certain words or phrases,

but rather depends on the pattern of

articulations associated with each word.

A third algorithm yields the

probabilities for the next word in a

sentence given the previous ones. This

language model is based on English

linguistic structure; for instance, “I

am very good” is more likely to be said

than “I am very going.” Finally, the

predicted word or sentence is displayed

onscreen as feedback, demonstrating

the newfound possibility of “speech” for

the paralyzed patient.

Chang’s system better resembles

real-time speech in terms of accuracy

of communication and rapid pace,

achieving a median rate of 15.2 words per

minute decoded and a median word error

rate of 25.6 percent. The research team’s

next steps include replicating these

results in more than one participant: as

long as the patient is cognitively intact

and can attempt to produce speech,

this neuroprosthesis could potentially

be useful for people with a variety of

injuries or disabilities, interpreting

their brain waves and allowing them to

communicate once more.

However, while this device is certainly

ground-breaking, there are still some

limitations with the current system. “It

seems very unlikely that we could just

expand this current form to a thousand

words,” Moses said. The team intends

to keep working on modifications or

alternative approaches to their initial proofof-concept

to expand the neuroprothesis’

potential. The ultimate vision is some

kind of brain-computer interface that

is convenient, portable, and minimally

intrusive, with the ability to decode words

and sentences quickly, facilitating accurate

communication with the outside world.

“Now that we even have this initial

proof of concept, and this first shred of

evidence that this is feasible, it’s really

quite motivating to see how far we can

go with it,” Moses said. The researchers

describe this project as a unique

opportunity to tangibly help paralyzed

people reconnect and communicate with

the outside world, which the team finds

incredibly rewarding and is committed

towards pursuing. Ultimately, Chang

and his research team hope to restore the

individual’s voice—thereby reaffirming

both the patients’ autonomy and

fundamental connection to humanity. ■


October 2021 Yale Scientific Magazine 33



YC ’23


For Anna Albright (YC ’23), caring about our climate is a

way of life. It all began in her high school environmental

science class. As she learned about worrying phenomena

like the greenhouse gas effect and its feedback loops that melt

our ice caps, she couldn’t help but feel deeply frightened. “The

only way I could fight this feeling, fight the fear, was to think,

I have to be a part of the solution,” Albright said.

So, she got to work. Even before she

arrived at Yale, she threw herself

into climate activism.

She testified at the

Massachusetts State

Senate, spoke at

an MIT climate

summit, and

helped draft

the City of


climate goals.

At Yale, she

has made

it a mission

to continue

this work,

exploring her

activism in a

new dimension:

capital allocation.

Early on, Anna

discovered a great

interest in a rapidly

growing area of finance

called environmental, social, and


governance (ESG)-based investing. ESG- based

investing is centered around the idea that an investor should

weigh a company’s achievement of environmentally stable,

socially responsible, and internally ethical practices before

deciding to invest. Albright believes widespread implementation

of ESG holds great potential to galvanize fast and effective

positive change for our climate. “​Trillions of dollars—tens of

trillions of dollars—move through the financial system each

year,” Albright said. “Even if you can get a portion of that to go

to better places, or you change the incentives around where it

goes, or you even change the standard morals or ethics about

what you can invest in—that really has an impact.”

She began her work promoting ESG at Yale with the Yale

Student Investment Group (YSIG). She was one of only

three girls in her YSIG class and, to her knowledge, the only

Environmental Studies major in the group. “My goal is definitely

two things,” she said. “Number one is to make sustainability

central to investment strategy and financial strategy. And

number two is to make these spaces more accepting spaces

for people who face a stigma about entering the industry.” She

became a YSIG board member her sophomore year, and has

been remarkably successful over the last few years in actualizing

both of her missions. With the help of another board member,

she made ESG a required component of every soft pitch given

in the group, and she’s proud to report the group’s newest

applicant class is fifty percent women. Next summer,

Albright will work as an ESG analyst for J.P. Morgan,

bringing her passion for sustainability in finance

to the corporate world.

Last fall, at the height of the pandemic,

Albright was inspired by an Intro to

Marketing course at the School of

Management to apply for a job unlike

anything she’d done before: a social

media manager position for the Yale

School of Public Health Instagram page.

“When I saw this job come up, I was

really excited, because I felt like there

was a lot of latent opportunity there that

Yale had not harnessed,” she said. Before

her arrival, the page featured mostly

student profiles and campus photos and

had less than two-thousand followers.

Albright knew the account could be so much

more—a place for the public to gain knowledge in

an accessible and fun way. “One, they were hungry

for information about Covid,” she said. “And two, they

were hungry for fun, digestible internet content. That’s

all they wanted.” With the help of her boss, Kayla Steinberg,

Albright began to radically change the account. They creatively

communicated essential information about public health during

the pandemic using trending memes and art that captured the

attention of thousands of Instagram users.

In the last year, the account’s reach has skyrocketed to over

fifteen-thousand followers, and they’ve received attention from

some uber-famous public figures. “Ariana Grande reposted one

of the posts, which was huge,” she said. In another instance, her

work (partially) inspired a student’s future. “A student tweeted,

‘I just decided I’m going to Yale School of Public Health. Not

going to lie, their memes had something to do with it,’” she said.

If there’s one running theme in Albright’s work at Yale and

beyond, it’s her passion for cutting through the apathy that so

often plagues society, from climate change to a global pandemic.

“The hardest step is getting past the apathy,” she said. “And when

you can do that, you can change people’s minds.” ■

34 Yale Scientific Magazine October 2021 www.yalescientific.org



YC ’21



For Eric Y. Wang (YC ’21), photography has always been about

seeing things you would normally miss in daily life. And

throughout his four-year research career at Yale, Wang always

approached scientific problems the same way, looking for things other

people would normally miss. The approach has led him to countless

successes. Earlier this year, Wang was first author in a Nature paper on

autoantibodies and is now on his way to a MD/PhD at Weill Cornell.

Coming into Yale, Wang knew he wanted to pursue both research

and photography. Having done both in high school, Wang immediately

joined a lab as well as the Yale Daily News (YDN) during his first year.

Although his very first research project didn’t go as planned, Wang

used these experiences as valuable learning moments. “It was a good

experience because in science, things are bound to go wrong, even

in the best projects, and having that early experience of things not

working reinforced my desire to do research,” Wang said. “The fact

that I still wanted to do research after going through this experience

probably means I am really interested in it.”

During his sophomore year, Wang joined Aaron Ring’s (YC

’08) lab, hoping to have the opportunity to take on

his own project. “For me, what I

really wanted from a lab was

the ability to lead my own

project and take on

something for myself,”

Wang said. With

the support and


of Ring, Wang

quickly translated

his passion for

research into

meaningful work,

taking charge

of a project that

would later become

the foundation for his

autoantibody publication.

Wang would spend two years

tirelessly developing novel technology capable of detecting

autoantibodies, something seen in many autoimmune diseases as

well as in patients with COVID-19.

When COVID-19 forced all the labs to close, Wang was able to make

the most out of his situation, remotely analyzing his screened COVID-19

patient samples, which eventually led to his publication. “Eric had a

totally fearless and gung-ho mindset where he got completely absorbed

in an interesting scientific question and was willing to take any approach

he could to address that question,” Ring said.

Wang’s drive was not only seen in the laboratory, but also in

the photojournalism work he did for YDN. Wang quickly rose


through the ranks, from contributing photographer his first

semester to photo editor by the beginning of his sophomore year.

For Wang, photojournalism was a completely different type of

photography than what he was

used to. “I came from a really

quiet suburb. Our [high]

school didn’t really

have a newspaper, so I

never really had that

exposure,” Wang

said. Nonetheless,

Wang used

photojournalism as

one of his ways to

stay connected to the

Yale community. Wang

documented a diverse

array of events at Yale,

from the opening of Benjamin

Franklin and Pauli Murray Colleges to the protests against a

shooting that involved the Yale Police Department in 2019. “It

was really cool seeing your photos being spread online,” Wang

said. “This was particularly true in the case of protests.

Photos from protests can be very powerful and moving and

can call people to action.”

Although photography and research might not

immediately seem to involve overlapping skills, the ability

to see the things others normally wouldn’t has helped

Wang get to where he is today in both of his passions.

When asked about his future plans and why

specifically he chose to pursue a MD/PhD, Wang

mentioned the unique perspective he will gain on human

diseases as a physician scientist. “When you talk about

things in science, you don’t really talk about the patients as

much. It’s very easy to get disconnected from what actually

matters—which for me is being able to help patients,” he said.

Research-wise, Wang hopes to continue growing as a scientist,

formulating important scientific questions and ideas so that one

day, he can start his own lab. Wang also hopes to continue his

love for photography and to take advantage of all the unique

features that New York has to offer through street photography.

His biggest advice for aspiring scientists? “Not to stress about

things like publications…it’s much more important to focus on

developing yourself as a scientist,” he said. Living by that advice,

Wang has been able to broaden his scientific knowledge and gain

a unique way of thinking that has helped him find success. ■

Editor’s note: Elsewhere in this issue, we covered Wang’s research

paper. See pg. 7.

October 2021 Yale Scientific Magazine 35



Lying in my bed on a Saturday morning, I hesitantly opened my laptop to begin

watching David Attenborough’s latest documentary, Breaking Boundaries: The

Science of Our Planet. I say “hesitantly” because, while I am a huge proponent of

sustainable living and learning about how climate change affects us, I’m honestly not

a big documentary guy. While I have, no doubt, seen my fair share of An Inconvenient

Truth-esque films, sooner or later, they all begin to meld into one big, urgent,

overwhelming, ominous mess. However, after watching this riveting documentary, I

can say with full confidence that if you are someone who wants to learn more about the

ways in which humans have, quite literally, broken the boundaries of Earth’s climate,

biospheres, oceans, and atmosphere, then this is the perfect Netflix quick-fix for you.

Taking a much more climate-forward approach to education than his past

documentaries, David Attenborough starts off by introducing Swedish climate

scientist Johan Rockström. Rockström and his colleagues gained fame within the

scientific community recently when they hypothesized that there are nine boundaries

humans need to respect in order to keep Earth sustainable for human life. While we

currently live within the safe zones for five of the boundaries (freshwater use, ocean

acidification, aerosol pollution, ozone layer depletion, and novel pollutants like nuclear

waste), we have already surpassed four of the boundaries: climate change, land use,

biodiversity integrity, and biogeochemical flows of nitrogen and phosphorus.

The effects of crossing these boundaries can be seen most significantly by

the melting of the ice poles. However, scientists in the documentary also point

out that an increase in drought, wildfires, flooding, and even the onset of the

COVID-19 pandemic can all be tied back to our unsustainable living habits.

Their perspectives show us that this planetary crisis is a metaphorical

asteroid coming to Earth. We are reaching a point where ignorance of this

issue is simply unacceptable. Healthcare services have become overwhelmed,

entire ecosystems face collapse, and novel zoonotic diseases have been

transmitted to humans, all because of the climate disaster. If humans do not

act with responsibility and purpose, our planet will soon be uninhabitable.

After hearing about this incredibly overwhelming climate crisis, where do

you begin to tackle this problem on an individual level?

Watching this documentary is definitely a start. You can also join a club on

campus. If you’re interested in assuming a leadership role, think about applying

to be a Residential College Sustainability Liaison. When eating in the dining

halls, maybe swap out your cheeseburger for tofu tenders every so often, since

transitioning to a more plant-based diet is one of the single most important

ways you can reduce your carbon footprint. When possible, buy your clothes

second-hand, and walk or bike around. Continue to educate yourself about the

problems facing our planet and vote for environmentally conscious politicians.

With these actions in mind, we must now begin to act with a unified

purpose, in search of—as David Attenborough puts it—the perfect home. ■




36 Yale Scientific Magazine October 2021





Animals—they are the lovable beings that are generally seen as allies to

humans, bringing joy and perspective to our lives. But what happens

when there is trouble in paradise—when animals and humans begin

to have conflict? And does nature handle it, or do we take it into our own

hands? Mary Roach, in her new book Fuzz: When Nature Breaks The Law,

analyzes this issue from a humorous and first-person point of view.

Roach demonstrates a beautiful case of nature facilitating cohabitation

between animals and humans in Aspen, Colorado. We’ve all seen animals

snooping for food, but according to Roach, the bears of this mountainous

town take it to another level. Here, residents don’t just find bears dumpsterdiving;

they find bears snatching food off dinner tables and hiding in the

rooms of houses. There is hope for the future though: laid-back bears, like

an infamous one nicknamed “Fat Albert,” are favored by natural selection

because they calmly carry out their food operations in such a suave manner

that homeowners can tolerate it. They are therefore more likely to get away,

survive, and pass on their calm temperaments to their offspring.

Roach finds a contrasting example in India’s more lethal, man-eating leopards.

Expert animal handlers have tried relocating them, but particularly aggressive

species are even more dangerous after being moved. Moreover, relocation would

likely create a dilemma over whether it is ethical to remove animals from their

natural habitats. To address this ostensibly unsolvable problem, scientists attempt

to control the density of these populations, rather than remove them altogether.

Elsewhere, Roach writes, humans are using molecular biology and

chemistry to alter the animals around them. Aaron Shiels, a wildlife

biologist, is working on an escape-proof habitat for mice, which would be

genetically modified to only produce male offspring. This would be done

with CRISPR technology, which targets a gene and cuts it out or replaces it.

In isolation, Shiels’s work would eventually lead to a less dense population

of mice. Additionally, a few US cities are trying a contraceptive on rats

called Contra-Pest, which uses 4-vinylcyclohexen diepoxide and triptolide,

two components that impact the reproductive viability of certain species.

People can also shift their mindsets when it comes to wildlife. On an individual

level, perceiving interactions with nature as an inherent part of life rather than

a burden could give people peace of mind. Perhaps we should remove ourselves

from animals’ natural habitats rather than the other way around. According to

Roach, people have invaded Bengali forests and turned elephant habitats into

their own, forcing the elephants to aggressively come into villages looking for

refuge. Indeed, sometimes we as people are our own worst enemies, villains to

the very animals we love and cherish. We mustn’t maliciously take advantage

of our manpower and intellect, but rather use it to facilitate human-animal

coexistence in a way that is mutually beneficial. ■



October 2021 Yale Scientific Magazine 37





We all know how the story goes. A mysterious

spaceship is detected in the atmosphere. Humans

try to communicate with the aliens on it. Aliens are

hostile and attempt to conquer Earth. Pandemonium ensues.

The “alien invasion” trope and extraterrestrial beings in

general have been parts of movies, books, and other media for

decades, from H. G. Wells’s The War of the Worlds to the cult

classic film Independence Day to everyone’s favorite quarantine

video game, Among Us. The idea of encountering aliens has

captured our imaginations. However, in scientific communities,

the search for extraterrestrial life has yet to find success.

Traditionally, scientists have looked towards planets with

conditions like ours in their search for life. Whether a planet

has appropriate conditions for liquid water has been a primary

concern. These planets can neither be too close nor too far

from the star they orbit: this famed “Goldilocks” region is

usually considered to be the habitable zone for a star. An

additional constraint is that the models used to predict the

bounds of this region assume a small, rocky planet with an

Earth-like atmosphere filled with nitrogen gas, oxygen gas,

and carbon dioxide. However, two recent studies tell us that

we may not be looking in the right places.

Nikku Madhusudhan and his team at the University of

Cambridge proposed a new type of potentially habitable planet.

These planets, known as “Hycean worlds,” are composed of massive

oceans with surrounding atmospheres made mostly of hydrogen

gas. Madhusudhan’s team first explored the range of masses and

radii that Hycean worlds can take on and then determined the

range of temperatures (and, by extension, distances from various

stars) that allow for habitable Hycean surfaces.

Madhusudhan’s team found that Hycean planets offer several

advantages over Earth-like ones when it comes to the search for

life. Hycean worlds can be much larger than rocky, terrestrial

ones, and their thick atmospheres provide insulation that allows

for liquid water far away from a star: some “Cold Hycean”

planets may not need any stellar irradiation at all, with their

only heat source being internal. The increased range of sizes

and distances from a star that Hycean planets have could mean

that scientists can broaden their search for extraterrestrial life.

Meanwhile, Noah Tuchow and Jason Wright of Penn State

questioned the habitability of planets in the traditionally

defined habitable zone. They noted that, while the traditional

definition considers whether liquid water could exist under

current conditions, a planet’s habitability is dependent on

whether it has existed in the habitable zone ever since life there

began. Planets currently observed in a star’s habitable zone may

have entered the zone relatively recently, either due to changes

in a star’s luminosity or planetary migration. These “belatedly

habitable” planets are unlikely to gain the ability to host life: if

Venus somehow took Earth’s spot in our solar system, entering

the “habitable zone,” it would never regain liquid water.

Identifying the “belatedness” of a planet’s habitability is a

difficult task. It requires knowledge of both a star’s life history

as well as when and how planetary formation occurs. However,

while no simple model can tell us which planets we can ignore,

Tuchow and Wright’s research will guide future extraterrestrial

exploration. Considering belated habitability for planets may

change how we approach future mission design, as many planets

found in habitable zones will merely be belatedly habitable.

These two studies are challenging our traditional ideas of

what makes a planet habitable. Our current definition of the

habitable zone, centered around the possibility of finding

liquid water on Earth-like planets, ignores other types of

potentially habitable planets and fails to consider the impact

of stellar history on habitability. These studies teach us that

our initial conceptions about science are often false: life in

the universe need not look like life on Earth. Our current

definition for “habitable zone” may be less useful than we once

thought, and it may be time to reconsider it. Perhaps applying

a new definition will help us find those aliens we’ve fantasized

about for so long—let’s just hope they aren’t as hostile as those

in all the movies. ■

38 Yale Scientific Magazine October 2021 www.yalescientific.org



By Dhruv Patel


David Pogue (YC ’85) is not your average CBS Sunday

Morning science and technology correspondent. He’s

written or co-written more than 120 books, given

five TED Talks, and has hosted twenty NOVA science specials

on PBS. All of this makes him uniquely qualified to provide

insight into what it’s like to communicate with the larger

public through media.

After graduating summa cum laude from Yale with a degree

in music, Pogue conducted and arranged Broadway musicals

for ten years. But on the side, he taught computer lessons.

Over a decade, his hundreds of hours of teaching clients—

including celebrities—how to use computers gave him a good

sense of what the average adult can grasp and how quickly they

can grasp it, a skill that would prove useful later in his career.

Pogue also wrote technology review articles on the side. An

impressed outgoing tech columnist at the New York Times

recommended Pogue to fill his position, where he remained

from 2000 to 2013. Pogue got his first break into covering science

and the environment when he was approached about hosting a

NOVA science special on PBS while at a talk he was giving. “We

had fun working together, so I started doing more shows for

them. The areas that they let me cover began to expand: first it

was tech, then it was tech and science, then it was tech, science,

and environment. So I gradually started doing more stories

on plastic in the ocean, and fracking, and the environment. It

gradually became part of my portfolio,” Pogue said.

Pogue is now a CBS Sunday Morning science and technology

correspondent. What he loves particularly about this position is the

creative control and liberty he has when presenting a story. “Being

able to choose my own story ideas, the ability to write my own script,

the ability to comment on the story as it’s being edited—these are all

luxuries you don’t get in other television,” Pogue said.

To cater science for the audience at home, Pogue relies on

his experience teaching computer lessons and writing books,

six of which have been of the popular For Dummies series. “I

like to imagine that it’s me from twenty years ago—before I

had gotten into the world of science and technology—in the

audience,” Pogue said. Keeping that thought in mind, Pogue is

cautious not to under-explain a concept. “I would much rather

be accused of over-explaining than shooting over the heads

of the audience. If the latter happens, the audience learned

nothing and the segment can be considered a failure.”

In Pogue’s mind, explaining key concepts, regardless of how

trivial they may seem, is a win-win situation: it allows those who

already know the concepts to feel smug about their knowledge,

but it also allows those who didn’t know this concept to learn

something new. This approach of building a segment while

keeping the audience’s perspective in mind, including their

ability to understand certain ideas, allows Pogue and his team to

effectively and adeptly convey scientific information to viewers.

Pogue acknowledges that there is still room for science

writers and reporters to improve. We are, after all, living in a

world where more and more people are becoming hesitant to

accept scientific findings. According to Pogue, there are two

causes of this suspicion. One is that recent scientific findings

are new and unfamiliar to many people; the second is that

modern science phenomena cannot be seen or observed by the

naked eye (e.g., the transmission of the COVID-19 virus from

person to person). As Pogue explains, the way to overcome

this fear is by relentlessly explaining the facts and significance

of these new findings with humor and entertainment value.

Importantly, Pogue mentions that science reporters and writers

must maintain empathy as well—because a person’s mind will

not be changed by facts, but by empathy and understanding.

As one of his favorite sayings goes, “People don’t care what you

know—unless they know that you care.”

Pogue doesn’t have a specific plan on what he’d like to do in the

future. He likes it when life presents a new opportunity. After

all, he didn’t plan anything that has happened in his career; he

simply said yes to the opportunities presented to him.

As for his advice to today’s scientific writers, Pogue mentioned the

necessity of pursuing your passion, trusting that things will turn out

all right. “Don’t wait. Don’t think that because you’re young, you can’t

do or become or start whatever you want,” Pogue said. ■


October 2021 Yale Scientific Magazine 39



Would you like to graduate from medical

school debt-free AND earn a generous

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Welcome to Yale!

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Association is here for you.

Founded in 1914, the YSEA is one of the oldest university student/alumni

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Whether near or far from New Haven, we help our members realize their

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We are excited to be a part of your Yale journey, and we look forward to

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Join us at: ysea.org

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