YSM Issue 93.2
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Yale Scientific
THE NATION’S OLDEST COLLEGE SCIENCE PUBLICATION • ESTABLISHED IN 1894
SEPTEMBER 2020 VOL. 93 NO. 2 • $6.99
16
THE ROLE OF DEATH
IN PLANT LIFE
DRIVERS PREDICTING
13
THE FUTURE
DOGS ON
21
DUTY
KEEPING DRY
26
UNDERWATER
THE NEW
28
98.6 DEGREES
T A B L E O F
VOL. 93 ISSUE NO. 2
More articles online at www.yalescientific.org & https://medium.com/the-scope-yale-scientific-magazines-online-blog
COVER
16 The Role of Death in Plant Life
A R T
I C L E
Cindy Kuang
As agriculture adapts to fit modern demands, organizations such as the USDA are pushing forth
policies based on the idea that more soil organic matter will lead to increased crop productivity.
Yale researchers investigate the scientific basis behind this idea.
10 Tracking Drugs
Anna Sun
Yale researchers from the Department of Biomedical Engineering have developed a quantitative
microscopy approach to efficiently measure circulation half-life of fluorescently tagged agents.
With the power to detect subtle changes in concentrations for nanoparticles and antibodies,
scientists may soon be able to rapidly screen a wide range of therapeutic agents for clinical trials.
13 Drivers Predicting the Future
Maria Fernanda Pacheco
Yale researchers create a model that uses driver mutations to estimate tumor growth patterns and
to predict the development of cancer.
18 Building Better Qubits
Shoumik Chowdhury
A key step towards building robust quantum computers is designing quantum bits (qubits)
protected against noise. We report on a recent development from quantum information
researchers at Yale that demonstrates a new kind of qubit that may achieve this.
2 Yale Scientific Magazine September 2020 www.yalescientific.org
C O N T E N T S
4
6
20
28
30
Q&A
NEWS
FEATURE
SPECIALS
PROFILES
Why Does Stress Turn Your Hair Gray? • Anmei Little
Does Being Kind Make You Feel Less Pain? • Selma Abouneameh
Let Them Grow • Athena Stenor
Implications of Impella • Mia Jackson
Tectonic Plate Deformation • Dhruv Patel
Analyzing Autoinducer-3 • Jerry Ruvalcaba
The Duality of the Ebola Virus • Sydney Hirsch
Micro Molecule, Huge Impact • Beatriz Horta
Show and Tell • Eva Syth
Dogs on Duty • Makayla Conley
An Algorithmic Jury • Mirilla Zhu
Letting Experience Guide the Way • Zoe Posner
Keeping Dry Underwater • Yu Jun Shen
Counterpoint: The New 98.6 Degrees • Kelly Farley
Science vs. The Apocalypse: Antibiotic Resistance • Victoria Vera
Undergraduate: Alon Millet (BR '20) • Katherine Dai
Alumni: Tze-Chiang Chen (PhD '85) • Nadean Alnajjar
www.yalescientific.org
September 2020 Yale Scientific Magazine 3
DOES BEING KIND MAKE
YOU FEEL LESS PAIN?
&
WHY DOES STRESS TURN
YOUR HAIR GRAY?
By Anmei Little
Have you ever noticed that politicians and CEOs develop
grey hairs fairly quickly? Usually the growth of grey
or white hairs accompanies old age due to the natural
depletion of melanocyte stem cells (MeSCs), which are responsible
for the hair pigmentation. A recent study by Ya-Chieh Hsu’s lab at
the Harvard Stem Cell Institute discovered that acute stress caused
mice to develop grey hairs by the same process as aging: MeSC
depletion. This could explain the premature greying of politicians,
CEOs, and others who experience stress on a daily basis.
In their experiment, the researchers stimulated stress in mice by
injecting them with a chemical called resiniferatoxin (RTX). RTX
acts similarly to the compound in chili peppers that is responsible
for the burning sensation of spice. In response to this stressor, the
researchers observed that the sympathetic nervous system in mice
became overstimulated and activated a “fight-or-flight” response,
releasing a neurotransmitter called noradrenaline. Noradrenaline
caused MeSCs to multiply and migrate, depleting the reservoir
and leading to premature greying. Interestingly enough, if
noradrenaline release was blocked, the mice’s hair did not lose
color. This suggests that noradrenaline is associated with, perhaps
even necessary for, the mechanism for hair greying.
While it may sound like bad news that your stress spawns
grey hairs, scientists are deeply interested in further exploring
the mechanisms of MeSC depletion. Future research may well
discover a way to prevent both stress-induced and age-induced
greying. To the next generation of politicians and leaders: do not
fret—the era of hair dye might pass soon. ■
By Selma Abouneameh
From morphine to ibuprofen, modern medicine has made
enormous progress in the field of pain management.
However, a recent study conducted by Professor Xiaofei
Xie’s lab at Peking University showed that medicine might not be
the only means by which we can attain pain relief. The proposed
alternative? Helping others.
Why do people help others? The question has plagued
scientists for centuries—after all, altruism is a costly behavior.
The researchers’ study sought to address this paradox. “Our
experiments suggest that altruism is not just other-benefiting, but
it benefits the performers as well,” said Yilu Wang, lead author of
the study. According to their results, a key benefit is pain relief.
In order to get a deeper understanding into how altruism
affects our biology, the authors conducted three experiments
that placed individuals in either altruistic or non-altruistic roles,
then either induced pain or measured naturally existing pain. In
one of these experiments, the researchers used functional MRI
(fMRI) to measure how brain activity changed after participants
performed the altruistic task of donating money to orphans.
The fMRI results showed that those who had donated money
exhibited decreased activity in the right insula, the area of the
brain responsible for feeling pain.
Thus, performing altruistic behaviors regularly can serve as
a “low-cost, side effect-free approach to supplement current
therapies for chronic pain,” Wang and Xie said. Their research
not only sheds light on different psychological and biological
motivations behind our behaviors but may also provide insight
into a new method for pain management. ■
Wang, Y., Ge, J., Zhang, H., Wang, H., & Xie, X. (2020). Altruistic
behaviors relieve physical pain. Proceedings of the National
Academy of Sciences, 117(2), 950-958.
Zhang, B., Ma, S., Rachmin, I., He, M., Baral, P., Choi, S., Gonçalves, W. A.,
Shwartz, Y., Fast, E. M., Su, Y., Zon, L. I., Regev, A., Buenrostro, J. D., Cunha,
T. M., Chiu, I. M., Fisher, D. E., & Hsu, Y.-C. (2020). Hyperactivation of
sympathetic nerves drives depletion of melanocyte stem cells. Nature,
577(7792), 676–681. https://doi.org/10.1038/s41586-020-1935-3
4 Yale Scientific Magazine September 2020 www.yalescientific.org
The Editor-in-Chief Speaks
WORKING THROUGH CRISES
Last issue, I touted the Yale Scientific Magazine’s steadfast commitment to
communicate science “through . . . epoch-making events,” thanks to our forebears’
tireless efforts over the past 126 years. Through the events of the past few months,
we at YSM have truly come to understand what it means to push forward in our
mission, even as Yale and the world have been rocked by crisis after crisis.
It is thanks to an incredible feat of dedication and passion by our masthead
and contributors that we are publishing this issue. Writers and editors conducted
interviews and worked on drafts through spring break, against unprecedented
academic uncertainty. Thanks to our webmasters, the content for this issue has
been online since May; the production and business teams have also been working
tirelessly in their respective domains to ensure a successful launch for Issue 93.2.
This issue’s cover article by Cindy Kuang (page 16) gives an incisive account of
a research study to determine how, and whether, soil organic matter contributes
to crop productivity. We continue to highlight the best research from all corners
of the Yale campus, be it harnessing the deadly Ebola virus to treat brain tumors
(page 8), or building better superconducting qubits for quantum computing (page
18). Two Features articles in this issue are of note. One addresses the implications
of an AI-driven jury (page 22), while the other covers the Angiosarcoma Project,
a pioneering model for public and patient involvement in disease research (page
24). These represent a new effort to spotlight the social impacts of scientific
advances, and we will tell more stories like these in the future.
The past few months have given us the COVID-19 pandemic and the tragedies
leading to the Black Lives Matter movement. COVID-19 will change how we
live our lives and how we do science. In a short span of months, we have gone
from knowing nothing about SARS-CoV-2 to developing promising vaccines.
YSM has attempted to capture this rapid—albeit meandering—progress in
our summer COVID-19 Catch-Up series, which covers the latest COVID-19
literature on our social media. On the other hand, the Black Lives Matter
movement has made us recognize the dearth of recognition and participation
by minority groups in science. As a science publication, YSM needs to do more.
In our future coverage, we will strive to highlight more underrepresented voices
in science. You can find our full statement on our website.
Wherever you are, please stay safe, take care, and wear a mask.
ABOUT THE ART
Marcus Sak, Editor-in-Chief
Soil is arguably nature’s underdog.
The substance reinforces extensive
plant root systems, houses a
diversity of fauna, and acts as a
key player within nutrient cycles,
yet its multifacetedness is often
not fully acknowledged throughout
our day-to-day lives. In this
issue’s cover, I explore soil as the
focal point of the illustration.
Sophia Zhao, Cover Artist
MASTHEAD
September 2020 VOL. 93 NO. 2
EDITORIAL BOARD
Editor-in-Chief
Managing Editors
News Editor
Features Editor
Articles Editor
Online Editors
Copy Editors
Scope Editors
PRODUCTION & DESIGN
Production Manager
Layout Editor
Art Editor
Cover Artist
Photography Editor
Webmasters
Social Media Coordinator
BUSINESS
Publisher
Operations Manager
Advertising Managers
OUTREACH
Synapse Presidents
Synapse Vice President
Outreach Coordinators
STAFF
Selma Abouneameh
Nadean Alnajjar
Shoumik Chowdhury
Makayla Conley
Katherine Dai
Maria Fernanda Pacheco
Sydney Hirsch
Beatriz Horta
ADVISORY BOARD
Priyamvada Natarajan
Sandy Chang
Kurt Zilm, Chair
Fred Volkmar
Stanley Eisenstat
James Duncan
Stephen Stearns
Jakub Szefer
Werner Wolf
John Wettlaufer
William Summers
Scott Strobel
Robert Bazell
Craig Crews
Ayaska Fernando
Robert Cordova
Mia Jackson
Cindy Kuang
Anmei Little
Dhruv Patel
Zoe Posner
Jerry Ruvalcaba
Noora Said
Marcus Sak
Kelly Farley
Anna Sun
Xiaoying Zheng
Hannah Ro
James Han
Tiffany Liao
Maria Fernanda Pacheco
Nithyashri Baskaran
Serena Thaw-Poon
Lorenzo Arvanitis
Brett Jennings
Antalique Tran
Julia Zheng
Ellie Gabriel
Sophia Zhao
Kate Kelly
Siena Cizdziel
Matt Tu
Megan He
Sebastian Tsai
Jenny Tan
Stephanie Hu
Cynthia Lin
Michelle Barsukov
Katherine Dai
Chelsea Wang
Nadean Alnajjar
Blake Bridge
Yu Jun Shen
Anastasia Shilov
Ishani Singh
Athena Stenor
Eva Syth
Victoria Vera
Mirilla Zhu
Astronomy
Biological and Biomedical Sciences
Chemistry
Child Study Center
Computer Science
Diagnostic Radiology
Ecology & Evolutionary Biology
Electrical Engineering
Emeritus
Geology & Geophysics
History of Science, Medicine, & Public Health
Molecular Biophysics & Biochemistry
Molecular, Cellular, & Developmental Biology
Molecular, Cellular, & Developmental Biology
Undergraduate Admissions
Yale Science & Engineering Association
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
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yale.edu. Special thanks to Yale Student Technology Collaborative.
NANOMOLDED
INTO PERFECTION
SCIENTISTS DISCOVER NOVEL WAY
TO PRODUCE NANOMATERIALS
BY ATHENA STENOR
ILLUSTRATION COURTESY OF ELLI E GABRIEL
Increasingly today, nanotechnology is coming into our lives,
allowing us to design more efficient batteries, build lightweight
vehicles, and even administer needleless vaccines. However, a
major barrier to accessing the full potential of nanoscale materials
is their fabrication. A team of researchers from Yale University and
Wuhan University recently discovered that thermomechanical
nanomolding is a reliable method for the nanofabrication of
ordered phases (OPs).
OPs, a class of materials consisting of sublattices occupied by
atoms, are fundamental to various functional applications. Most
functional materials, including superconductors, magnetic materials
and plasmonic materials, belong to this class. Creating nanoscale
OPs is challenging because traditional techniques, such as chemical
vapor deposition growth, are not practical. For example, chemical
vapor deposition growth, a technique in which a film of vaporized,
decomposing chemical is deposited onto a substrate’s surface, only
works for easily vaporized OPs and cannot produce certain shapes.
But thermomechanical nanomolding can be scaled up for mass
production, fine-tuned to obtain specific characteristics, and used
with a variety of starting materials. In this technique, raw material was
pushed into a nanomold at steady pressure and a temperature below
its melting point, to produce single-crystalline nanowires of consistent
composition and structure. The process could be tuned so that the
nanowires’ aspect ratios were high, enabling easier access to different
morphologies. The researchers attribute their results to OPs’ tendency
to self-organize via a thermodynamic (stability-driven) rather than
kinetic (speed-driven) mechanism. This new process will make OPs a
more accessible class of nanomaterials, and enable the development of
exciting new applications for nanotechnology. ■
Liu, N., Xie., Y., Liu, G., Sohn, S., Raj, A., Han, G., Wu, B., Cha,
J.J., Liu, Z., & Schroers, J. (2020). General Nanomolding of
Ordered Phases. Physical Review Letters, 124(3). https://doi.
org/10.1103/physrevlett.124.036102
IMPLICATIONS
OF IMPELLA
RETHINKING TREATMENTS FOR
CARDIOGENIC SCHOCK
BY MIA JACKSON
ILLUSTRATION COURTESY OF NOORA SAID
More than one million Americans have a heart attack each
year. Four to twelve percent of these patients develop
cardiogenic shock, a condition that prevents one’s heart
from pumping the blood necessary to meet the body’s needs.
Two common treatments for cardiogenic shock include the
left ventricular assist device (LVAD) and the intra-aortic balloon
pump (IABP). While LVADs are more commonly used, Yale
University researchers recently reported the results of a study
examining the discrepancies in in-hospital clinical outcomes
between the two devices.
The study found that LVADs were associated with higher inhospital
mortality and in-hospital major bleeding. “Because there
is relatively little evidence in this area, we think that the analysis
that we did, and the conclusion that we made … would have
both policy implications and regulatory implications,” explained
Nihar Desai, an assistant professor at the Yale School of Medicine
who worked on this study.
Given the two-and-a-half-fold increase in the utilization of
LVADs between 2015 and 2017, Desai’s research suggests that
hospitals might need to rethink treatment plans for cardiogenic
shock. “We hope everyone is trying to integrate these data into
their practice, as it is on everyone to be a little more judicious of
[LVADs], given little evidence that would support their use,” Desai
said. Hopefully, this research will influence the way many doctors
treat cardiogenic shock patients. After all, for every patient that
enters the emergency room, the most common treatment option
available should be the best one for them. ■
Desai, N.R. (2020). Association of Use of an Intravascular
Microaxial Left Ventricular Assist Device vs Intra-aortic
Balloon Pump With In-Hospital Mortality and Major
Bleeding Among Patients With Acute Myocardial Infarction
Complicated by Cardiogenic Shock. JAMA, 323(8), 734–45.
https://doi.org/10.1001/jama.2020.0254
6 Yale Scientific Magazine September 2020 www.yalescientific.org
WHAT’S IN THE
EARTH’S MANTLE?
HOW WEAKER MATERIAL IN OLDER PLATES
MAY INCREASE DEFORMATION
BY DRUHV PATEL
ILLUSTRATION COURTESY OF ANMEI LITTLE
Tectonic plates and subducting slabs, portions of
tectonic plates that have slid under other plates, hold
the secrets to the movement of land masses. Previous
evidence showed that older slabs, which are colder and
supposedly stronger, deform in the mantle more than warm,
and presumably weaker, plates. This phenomenon puzzled
researchers and scientists. Professor Jennifer Girard of Yale
University’s Department of Earth and Planetary Sciences,
along with a team of researchers including Anwar Mohiuddin
and Shun-ichiro Karato, aimed to uncover the basis for this
unexpected deformation. They used a high-pressure and
high-temperature press to simulate the conditions in the
Earth’s mantle, allowing them to study the deformation and
subduction of slabs on a smaller scale.
The team found that when a subducting slab made
mostly of large olivine mineral plunges into the mantle, the
increased pressure causes olivine to transform into finegrained
ringwoodite. “The study clearly shows that newly
formed fine-grained ringwoodite is significantly weaker
than the coarse-grained olivine,” Girard said. While newly
formed ringwoodite in cold slabs grows slowly, higher
temperatures in warmer slabs cause grains of ringwoodite
to grow much faster; this causes the young slabs to become
much stronger as the grain grows. In fact, the team believes
that this inhibited growth rate may be the reason that cold
slabs deform while warmer slabs do not. These findings
will help researchers further explore and understand the
unexpected behavior of tectonic plates. ■
Mohiuddin, A., Karato, S. & Girard, J. (2020). Slab
weakening during the olivine to ringwoodite transition
in the mantle. Nature Geoscience, 13, 170–4. https://doi.
org/10.1038/s41561-019-0523-3
www.yalescientific.org
ANALYZING
AUTOINDUCER-3
UNDERSTANDING
CRITICAL BACTERIA
BY JERRY RUVALCABA
ILLUSTRATION COURTESY OF SOPHIA ZHAO
Escherichia coli is a dominant bacterial member of the human
intestinal tract and a major model organism in biology. Some
members of E. coli contribute to a healthy gut ecosystem, whereas
others are pathogens causing over a million infections worldwide
that often develop antibiotic resistance. Despite this, mechanisms for
regulation of its population-level phenotypes, which are associated
with pathogenesis, have remained elusive. Researchers in Professor
Jason Crawford’s group in the Departments of Chemistry and
Microbial Pathogenesis at Yale University, however, have illuminated a
key pathway underlying this phenomenon at the molecular level. They
have discovered the structure and pathway of autoinducer-3 (AI-3), an
uncharacterized signal responsible for regulating virulence.
This signal is secreted from the bacteria during growth, accumulating
as cells divide and allowing the bacteria to assess their numbers.
Researchers isolated the metabolite by applying cellular stress. Then,
the structure was determined using one- and two-dimensional
Nuclear Magnetic Resonance spectroscopy. Additionally, the effects of
AI-3 were tested on both bacteria and human tissue. Upon introducing
the metabolite to a strain of E. coli that causes intestinal lesions and
kidney failure, the bacteria became more virulent. When introduced
to human tissue, an inflammatory effect was observed, indicating
human cells can detect and combat these signals.
The elucidation of the AI-3 structure and pathway is a crucial step
forward in microbial pathogenesis. “It can be used to determine
the collection of genes regulated by the AI-3 molecule in other
pathogenic bacteria,” Crawford said. These findings pave the way to
combatting virulence in a variety of pathogens. ■
Kim, C.S., Gatsios, A., Cuesta, S., Chong Lam, Y., Wei, Z.,
Chen, H., Russell, R.M., Shine, E.E., Wang, R., Wyche, T.P.,
Piizzi, G., Flavell, R.A., Palm, N.W., Sperandio, V., & Crawford,
J.M. (2020). Characterization of Autoinducer-3 Structure and
Biosynthesis in E. coli. ACS Central Science, 6(2), 2020, 197–206.
https://doi.org/10.1021/acscentsci.9b01076
September 2020 Yale Scientific Magazine 7
NEWS
Biochemistry
THE DUALITY
OF THE
EBOLA VIRUS
How a Deadly Viral Infection
Can Be Harnessed for Healing
BY SYDNEY HIRSCH IMAGE COURTESY OF FLICKR
When we hear “Ebola,” we often think of its contagion and
lethality, and of the outbreaks in recent years. Ironically,
scientists are exploring the potential of the deadly Ebola
virus (EBOV) as a treatment against a fatal form of cancer: brain
tumors. Cancer cells lack the ability to generate an immune response
against viruses, making viruses a good starting point for developing
treatments. Of course, infecting someone with a lethal virus is risky; to
circumvent this, scientists use chimeric viruses, which contain a mix of
genes from multiple parent viruses. A team of researchers, including
Yale professor Anthony Van den Pol, recently reported their efforts to
test three variations of a chimeric virus, pairing an EBOV glycoprotein
with the vesicular stomatitis virus (VSV). They chose the Ebola gene,
given the virus’s propensity to infect—and for their purposes, target—
nerve tissue. Specifically, they took interest in the mucin-like domain
(MLD) of the Ebola virus, and how it modulates the viral ability to
target brain tumors. Interestingly, it seemed as if the MLD protected
normal cells from infection, while cancer cells still became infected.
They were hopeful that VSV-EBOV could be a promising treatment,
as the combination had been an effective and safe vaccine in humans
during the African Ebola outbreak.
The team tested three viruses on severe combined immunodeficient
(SCID) mice, which had human brain tumor cells injected into their
brains: VSV-EBOV, which contains the mucin-like domain (MLD);
VSV-EBOVΔMLD, which is a parallel construct but lacks the mucinlike
domain; and VSV-EBOVΔMLD-GFP, which is almost identical
to VSV-EBOVΔMLD with an added green-fluorescent protein (GFP)
reporter gene to visualize a virus. All three showed some increase in
the mice’s survival. The researchers found that the VSV-EBOV was
most effective in treating the brain tumors while maintaining the
health of the mouse. At 120 days after the tumor implant, only mice
infected with the MLD-containing virus remained alive.
The researchers considered VSV-EBOV successful because it
minimally infected healthy neural cells while still targeting tumor
cells. Van den Pol’s team quantified the extent of the brain infection
by counting the number of infected neurons and glial cells in coronal
brain sections. The other two virus forms showed widespread infection
throughout the brains of the animals. The VSV-EBOVΔMLD-GFP was
the least effective. While it modestly extended the survival of the mice,
all of the mice died. Some were incompletely infected by the virus, and
many still had brain tumors. The VSV-EBOVΔMLD injected tumors
had similar tissue structure, and a greater survival rate.
The lethality of the VSV-EBOVΔMLD-GFP virus may have been
due to the VSV backbone itself; this differs from those of the non-
GFP chimeric viruses in all four of their base proteins, which may
alter the behavior of the virus. Van den Pol explained that the Ebola
virus may release the MLD as a “false leader, causing the immune
system to be lured away from the infected cells.” This slowed
replication of the virus and lessened the amount of infectious viral
offspring. With a slower replication rate, the innate immune system
has more time to upregulate antiviral defenses. The low number of
infected normal cells suggested that the innate immune system was
sufficient to prevent the spread of the virus.
Researchers also compared the effects of intravenous versus
intracranial injection. Both methods had degrees of success.
Intracranial injection showed greater tumor infection and elimination,
indicating this type of delivery may be more reliable for treating larger
tumors. Intravenous injections, which are done through the tail-vein
in mice, could on the whole be more effective for smaller or undetected
types of metastatic cancer, such as melanomas.
Van den Pol and his team were able to monitor the impact of the
MLD on the treatment and survival of SCID mice. The chimeric
virus containing the mucin-like domain, VSV-EBOV, was the most
successful treatment, confirming their initial expectations. This
research is promising, as it could open the door for new forms of
glioblastoma treatment. “VSV-EBOV has been successfully used in
the human population in the past, showing that it’s relatively safe. If
we’re ultimately trying to move toward clinical studies, that’s a hurdle
already jumped over,” Van den Pol said. Future directions include
looking at tumors in immunocompetent mice or exploring other
VSV-based viruses. ■
Zhang, X., Zhang, T., Davis, J.N., Marzi, A., Marchese, A.M., Robek,
M.D., & van den Pol, A.N. (2020). Mucin-Like Domain of Ebola
Virus Glycoprotein Enhances Selective Oncolytic Actions against
Brain Tumors. Journal of Virology, 94(8), e01967-19.
8 Yale Scientific Magazine September 2020 www.yalescientific.org
Molecular Biology
NEWS
MICRO
MOLECULE,
HUGE IMPACT
How microRNAs Inhibit
Asthmatic Reactions
IMAGE COURTESY OF RYAN JEFFS
Despite its name, microRNA helps the body on a macro
scale. The small molecule, only about 22 nucleotides
long, plays an important role in the regulation of
gene expression by binding to mRNA at certain points in its
sequence. At the Yale School of Medicine, Shervin Takyar and
his team investigated the role microRNAs played in controlling
eosinophilia through endothelial cells. Eosinophilia occurs when
large numbers of white blood cells called eosinophils are recruited
to a site in the body, leading to the allergic airway reaction
characteristic of asthma and chronic rhinosinusitis (CRS).
The paper’s first point of analysis was investigating which
inhibitory factors interact with VEGF (vascular endothelial
growth factor). “We looked at a vascular factor [endothelial cells]
and inhibition, investigating their role in asthma and CRS,” Takyar
explained. Takyar’s team found that microRNA-1 levels went down
when VEGF went up. “The next step[s] [were] figuring out first,
whether microRNA-1 levels are important in the disease, and
second, why,” Takyar said. The team was then able to show, through
biological and mathematical models, that the molecule was
important. They also proved that asthmatic eosinophilia reactions
were reduced by increased levels of microRNA-1 in the blood.
Takyar and his team recreated the conditions first in
transgenic mice and in an engineered lentivirus (retroviruses
with long incubation periods) and then created a model for
a human vessel in the lab. “We isolated endothelial cells and
reversed the change [in microRNA levels], and only changing
microRNA-1 levels in these cells [could] decrease the features
of asthma,” Takyar said.
The next step was to understand where the molecule was
acting in the cell. The results revealed that microRNA was
inhibiting the asthmatic reaction by acting in a known protein
complex, the RNA induced silencing complex. This was
especially hard to investigate because microRNA cannot be
tagged, since this would inhibit the molecule from entering
the complex. Within the complex, there is an Argonaute
protein, which acts as a “matchmaker” for microRNA and
the inhibiting molecules; this protein was used to understand
how microRNA was influencing the eosinophilic reaction.
www.yalescientific.org
BY BEATRIZ HORTA
“We captured the Argonaute when microRNA was entering
to see what microRNA-1 was acting on,” Takyar said. With
this strategy, the team identified four genes that control
eosinophilia, an important breakthrough.
After this discovery, the researchers extracted cells from
humans with CRS and created a model for the human
endothelium environment. In this model, they passed
eosinophils over the cells to see how many would stick to them
in varying levels of microRNA. As expected, they found that in
increased levels of microRNA, less eosinophils would adhere
to the cells, which revealed the mechanism of action for the
inhibition of the symptoms.
To the researchers, the discovery shows promise for clinical
treatments. “Right now, we are starting a collaboration with
clinical groups and some companies to use [this mechanism]
as a complementary treatment for some patients who do not
respond to drug treatments,” Takyar said. He explained that
treatment for CRS and asthma is difficult because patients
have different symptoms and mechanisms; therefore, many
drugs do not have any effect on certain individuals. The role
of microRNA in the eosinophilic mechanism is an exciting
development in the area and could represent a step forward to
improve treatments. ■
Korde, A., Ahangari, F., Haslip, M., Zhang, X., Liu, Q., Cohn, L., Gomez,
J.L., Chupp, G., Pober, J.S., Gonzalez, A., Takyar, S.S. (2020). An
endothelial microRNA-1-regulated network controls eosinophil
The Journal of Allergy
and Clinical Immunology, 145(2), 550–62. https://doi.org/10.1016/j.
jaci.2019.10.031
Jeffs, R. (2011). MicroRNA and mRNA visualization in differentiating
C1C12 cells. Retrieved 22 March 2020, from https://commons.
wikimedia.org/wiki/File:MicroRNA_and_mRNA_visualization_in_
differentiating_C1C12_cells.jpg
Lentivirus.aspx
September 2020 Yale Scientific Magazine 9
FOCUS
Nanoscience
Searching through Nanoparticle Libraries
TRACKING
DRUGS
In the wake of the COVID-19 pandemic, clinical trials for
potential drugs and treatments have never seemed more
paramount. Scientists must carefully evaluate a drug’s interactions
within the body and observe possible side effects.
Particularly for drugs that must be administered intravenously,
it is critical for researchers to determine the circulation halflife,
or time it takes for a drug’s concentration to be halved, to
gain insight into how long a drug remains in the body.
One useful technology to visualize and measure concentration
is fluorescence microscopy. The principles of fluorescence
rely on excitation of fluorophore molecules and emission
of light. With fluorescent dyes or probes to track a target
molecule, fluorescence microscopes allow biomedical researchers
to perform experiments in vivo, or directly in the
organism, providing strong spatiotemporal resolution to visualize
physiological systems in normal and diseased states.
This is a primary research focus of the laboratory of Mark
Saltzman, professor of Biomedical Engineering at Yale University.
From generating polymeric nanoparticles that aid
drugs in targeting brain tumors to producing bioadhesive
biodegradable nanoparticles to be used in sunscreen, the
Saltzman research group has aimed to devise safer and more
effective technologies to prevent disease. For the past fifteen
years, the Saltzman laboratory has also generated libraries
of nanoparticles to determine how their chemical composition
may affect the behavior of and interaction with biological
specimens, including impacts to circulation half-life.
“We use nanoparticles to facilitate the delivery of therapeutic
molecules, protecting them from things in the blood like
a protective shell, until they arrive at the target destination.
Depending on the properties of the nanoparticles, you can
deliver a package of molecules all at once or gradually,” said
Laura Bracaglia, a postdoctoral researcher who has worked
on developing these nanoparticle libraries. Evaluating the efficacies
of these nanoparticles relies on an accurate method
of measuring concentration over time, such as via correlating
fluorescence intensity of fluorescently tagged injected agents.
In a recent paper published in PNAS, co-first authors Bracaglia
and postdoctoral colleague Alexandra Piotrowski-Daspit
designed a quantitative microscopy approach to efficiently
measure the circulation half-lives of fluorescently tagged
agents, such as nanoparticles encapsulating fluorescent dye or
PHOTOGRAPH COURTESY OF KATE KELLY
PHOTOGRAPH
COURTESY OF
KATE KELLY
fluorescently labeled antibodies.
BY ANNA SUN
10 Yale Scientific Magazine September 2020 www.yalescientific.org
Nanoscience
FOCUS
Limitations of Traditional Methods
A commonly used protocol for determining
concentration of fluorescently
dyed nanoparticles after administration
involves three steps: collecting at least
twenty microliters of blood from experimental
animals, separating dyed nanoparticles
from the blood samples, and measuring
the dye’s concentration by dissolving
the nanoparticles to create a uniform solution.
The process, however, can be laborious,
expensive, and error-prone.
One of the greatest challenges of the
traditional method is the volume of blood
needed for a plate reader to detect even
trace amounts of fluorescent dye within
the sample. The catch-22 is that removing
too much blood from an experimental
animal can interfere with studying how
injected drugs affect disease outcomes,
since circulating drug molecules can be
removed during blood collection.
Revamped Microscopy
The researchers realized that the plate
reader machine typically used to measure
fluorescent dye concentrations was ineffective.
“You need a uniform amount of
blood in the plate reader, but the measurement
tends to be inaccurate depending
on where in the solution you
are measuring,” Piotrowski-Daspit said.
To address the limitations of using large
blood volumes, the researchers decided
to switch to quantitative microscopy,
which requires only a drop of blood on
a microscope slide. “Depending on the
strength of the microscope, you can see
in the sub-micron level, so you don’t need
that much blood to see everything,” she
said. With their revamped method, only
two microliters of blood, compared to the
twenty microliters needed for the existing
protocol, are needed to accurately measure
circulation half-life.
The concentration of a drug in circulation
decreases exponentially until it approaches
zero, when it has been mostly
eliminated from the body. A drug’s halflife
is a useful measurement in understanding
circulation time, and the goal
of this quantitative microscopy method
is to understand how the drug is transported
and reacts within the body. “You
can make design changes to a molecule
www.yalescientific.org
or drug via physical or chemical methods
to make it less likely to be degraded
or phagocytosed in order to be circulated
for a longer time in the blood,” Bracaglia
said. “Sometimes, it’s also beneficial
for a drug to have extended circulation
to allow more time to reach a target,” Piotrowski-Daspit
added.
Where to Inject?
In their study, the researchers initially
focused on quantifying rodent drug delivery.
Because there are two standard
ways of intravenously injecting drugs to
rodents—retro-orbital (RO, or behind the
eye) and tail-vein (TV, or in the tail) administration—the
researchers tested both
routes of administration to better understand
possible changes in circulation
half-life. “RO is easier for some people,
so we were thinking if one experimenter
injects RO and another does TV, then
does that matter?” Bracaglia explained.
Whereas the previous protocol might
not have had the resolution to accurately
measure differences in half-lives between
RO and TV routes, the researchers detected
subtle differences in nanoparticle
concentrations measured within the first
thirty minutes of blood collection—a testament
to the powerful resolution of their
method. TV injection had higher measured
concentrations, but these concentrations
equalized after one hour. This
initial variability was not too concerning,
because “we’re sampling blood from the
tail, so it makes sense that the TV concentration
was higher at first than the RO,
which needed more time to pass through
circulation,” Piotrowski-Daspit said. Bracaglia
pointed out that detecting changes
in circulating concentration based on the
route of administration may also be relevant
for humans, since drugs are also administered
using various methods.
Expanding the Data
To determine whether this improved
method of measuring fluorescence concentration
could be applied to molecules
of different sizes, the research team also
successfully tested fluorescent antibodies.
“Whereas nanoparticles are usually
sized between 180-250 nm, antibodies are
smaller at around 10 nm. We wanted to
PHOTOGRAPH COURTESY OF KATE KELLY
A photograph of Dr. Piotrowski-Daspit looking
through a microscope, accompanied by Dr.
Laura Bracaglia. These research scientists
see if we can detect a wide range of agents
that might be injected into an animal
model,” Piotrowski-Daspit said. Because
their circulation measurements of these
antibodies matched the decay profiles
gathered from literature, the researchers
were confident that their method could
even detect small antibodies in the blood.
The data from the quantitative microscopy
method can also be combined with
further multivariable analyses. Saltzman
emphasized the importance of observing
biodistributions from these experiments—understanding
what kind
of tissues and what types of cells the
nanoparticles are found in over time. “By
coupling with other methods, you end up
with a powerful high-throughput, comprehensive
look at how long these particles
circulated and where they end up,” he
said. Furthermore, because only a small
amount of blood is needed for each sample,
more data can be collected from a
single experiment and animal. “Using
different nanoparticles each with separate
dyes, you can track these nanoparticles
in one animal. Because this can also
introduce differences in half-life and biodistribution
than when injected alone, it’s
an interesting way to see what happens
when you administer more than one drug
September 2020 Yale Scientific Magazine 11
FOCUS
Nanoscience
at once,” Piotrowski-Daspit explained.
This method could provide researchers
opportunities to better understand combination
therapies in humans as well.
Overcoming Obstacles
The researchers faced a few challenges
on their path to developing this improved
microscopy method. First, a major
concern with nanoparticle research
is the possibility that the fluorescent dye
(which is visualized) and the nanoparticle
itself have unexpectedly separated, so
the dye is no longer indicating where the
nanoparticle is. To address this, the team
ordered a commercially available polymer
that is chemically linked to a fluorescent
dye, and then imaged both the
polymer and a separate encapsulated dye.
“The observation that they colocalized
served as evidence that going forward, if
we look only for the encapsulated dye, we
can be confident that it is also with the
nanoparticle of interest,” Bracaglia said.
Another concern was that measuring fluorescent
agents might not be as accurate
as measuring radiolabeled agents, so the
team carefully compared their experimental
half-lives with examples from literature.
Not only did they confirm similar
half-life values, but their method was
also less complicated and more accessible
for the average lab, which may not have
equipment for measuring radioactivity.
Future Projects
Armed with a more effective method to
measure circulation half-lives of drugs,
the Saltzman research group plans to
ABOUT THE AUTHOR
rapidly screen through their nanoparticle
libraries. “We are excited to see where
these new nanoparticles go and how long
they stay in the blood, and to learn more
about how changes to physical and chemical
properties can affect drug delivery
success,” Bracaglia said.
An upcoming challenge for these researchers
involves what happens after
nanoparticles are delivered into circulation.
Because the liver functions to detoxify
drugs from the blood, nanoparticles
often accumulate in the liver instead
of the desired target organ. The researchers
hope to discover ways to bypass
the liver, using “decoy” nanoparticles.
“These molecules potentially may be
used to pre-treat and take up residence in
the liver, such that anything that comes
afterwards can remain in circulation longer
and reach other organs,” Piotrowski-Daspit
explained.
The main advantage of this novel protocol
is that the improved quantitative
fluorescent microscopy has drastically
reduced sample blood volume. Previous
limitations from sample blood volume
often prevented experiments involving
essential animals with rare tumors or diseases.
“You normally don’t want to waste
these animals doing a half-life experiment.
If you’re treating the tumor, you
want to save these animals to see if the
treatment worked,” Bracaglia said. Drug
circulation, however, might significantly
differ between non-experimental and
diseased animals. With this new timeand-cost
effective, accessible microscopy
method, scientists may soon be able to
screen a wide range of therapeutic agents
and provide more accurate measurements
for preclinical studies, enabling researchers
everywhere to answer the growing
need for innovative drugs. ■
ANNA SUN
ANNA SUN is a senior in Jonathan Edwards College majoring in Molecular, Cellular and Developmental
Biology. She currently serves as Managing Editor for the . Outside of , she
studies riboswitches, volunteers in the hospital, and reads with New Haven youth. She also enjoys
dancing and exploring the food scene in New Haven with her friends.
THE AUTHOR WOULD LIKE TO THANK Laura Bracaglia, Alexandra Piotrowski-Daspit, and Mark
Saltzman for their time and thoughtful discussions about their research.
FURTHER READING
Bracaglia, L. G., Piotrowski-Daspit, A. S., Lin, C., Moscato, Z. M., Wang, W., Tietjen, G. T., & Saltzman, W.
M. (2020). High-throughput quantitative microscopy-based half-life measurements of intravenously
injected agents. PNAS, 117(7), 3502-3508.
Bracaglia, L. G., Piotrowski-Daspit, A. S., & Saltzman, W. M. (Personal interview, March 4, 2020).
FDA. (2018, January 4). Step 3: Clinical research. The Drug Development Process. https://www.fda.gov/
patients/drug-development-process/step-3-clinical-research
Smith, Yolanda. (2018, August 23). News Medical Life Sciences. https://
www.news-medical.net/health/What-is-the-Half-Life-of-a-Drug.aspx
Fluorescence fundamentals.
biological and biomedical research. , 14067-14090.
Saltzman Research Group. (n.d.). Our research. https://saltzmanlab.yale.edu/gallery/our-research
Le, J. (2019, June). Merck Manual Consumer Version. https://www.merckmanuals.
com/home/drugs/administration-and-kinetics-of-drugs/drug-administration
12 Yale Scientific Magazine September 2020 www.yalescientific.org
Computational Biology
FOCUS
DRIVERS
PREDICTING
THE FUTURE
IMAGE COURTESY OF WIKIMEDIA COMMONS
using driver
mutations
to estimate
tumor growth
patterns
BY
MARIA
FERNANDA
PACHECO
Ever since that split second in which
your parents’ gametes fused to
generate your life, the cells that make
up who you are have not stopped
dividing, even right now. As they
replicate, it is likely that their DNA will mutate,
incorporating new traits into the genetic code
that writes their fate—what structure they will
adopt, what function they will perform, what
purpose they will serve. While some mutations
can be responsible for traits like ginger hair
or the absence of wisdom teeth, or even at
times go completely unnoticed, other far more
dangerous ones hold the power to corrupt a
cell’s machinery, culminating in grave ripple
effects that can make all systems go haywire.
www.yalescientific.org
September 2020 Yale Scientific Magazine 13
FOCUS
Computational Biology
How the Model Works
PHOTOGRAPH COURTESY OF WIKIMEDIA COMMONS
Photograph of a driving wheel, symbolizing how some mutations drive tumor progression.
The word “tumor” is laced with
terrifying potential. Possibilities of
anarchical growth, silent spread, and
rapid lethality render these neoplasms’
behavior difficult to predict. In an
effort to circumvent this uncertainty, a
group of Yale researchers led by Mark
Gerstein, Albert L. Williams Professor
of Biomedical Informatics and Professor
of Molecular Biophysics & Biochemistry,
Computer Science, and Statistics & Data
Science, published a paper in February
reporting a mathematical model they
developed. The model looks at a specific
kind of mutation called driver mutations
to estimate a tumor’s growth pattern.
to detect because those are the ones that
actually play a role in tumor progression.”
Conversely, mutations identified as nonsignificant
in terms of tumor development
are dubbed passenger mutations.
According to Gerstein, driver mutations
can be defined as the “few mutations that
accumulate in the cell and drive its growth
forward.” In the paper, the authors discuss
different means through which these
mutations can trigger the formation of
tumors, including hindering the ability of
tumor-suppressor genes from impeding
tumor growth and enhancing the level of
expression of oncogenes, which are genes
that can cause cancer.
When tumors are biopsied, a sample is
often extracted and sequenced to reveal
its genetic composition. According to
Salichos, the number of times a specific
position in the genome is sequenced is
very important. The deeper the sequencing,
the more accurate you can expect the
measurement of a mutation’s frequency
within a population-to-be. At the end of
the process, you have acquired a run-down
that details all of the mutations detected as
well as their respective frequencies, which
paints a clear picture of their expressivity
within the cell’s genetic code.
“Based on the frequency, you can already
make an assessment of whether that
mutation happened early or late in the tumor,
because, if it happened early in the tumor
progression, we are expecting it to have a
higher frequency at the end,” Salichos said.
Therefore, ordering mutations from those
that appear most to least provides insight
into the order in which they occurred. This
information contextualizes what mutations
might have stimulated tumor growth and
which ones occurred as collateral damage,
helping frame their relevance with respect
to tumor progression.
Salichos explained that, based on this
idea, he developed a mathematical model
that uses the frequency of some of the
mutations that happened exactly before
the driver mutation to detect presence of
the driver and estimate tumor growth at
the precise moment when it first emerged.
This examination allowed the group to
gauge the impact of this phenomenon,
since the introduction of a driver mutation
Driver Mutations
The development of cancer is an
evolutionary process, punctuated by
mutations. Historically, several theories
have been put forward as to how researchers
can study such genetic alterations, but, most
recently, mutations have been increasingly
labeled as either drivers or passengers to
categorize them according to their relevance
in tumor progression. Leonidas Salichos,
a postdoctoral associate and first author
of the paper, explained that “we have a lot
of mutations in every tumor, sometimes
thousands of mutations, and a few of them
are what we call drivers, … which we try
With this kind of model, you
can look into an individual’s
tumor in a more direct way.
14 Yale Scientific Magazine September 2020 www.yalescientific.org
Computational Biology
FOCUS
into a sample often creates a detectable
perturbation in the variant allele frequency
distribution. “Once you introduce a
driver into a population that grows, now
the population starts growing faster, and
that has an impact on the frequency of
the mutations that happen before that,”
Salichos said.
Driving Towards More Accurate Cancer
Prognosis
“Traditionally, the way people find these
drivers is they look at cohorts of cancer
patients at the same time,” Gerstein said.
Salichos also highlighted that over a thousand
samples are often needed in traditional
methods, since large numbers are required to
ground observations that something deviates
from the normal. At least computationally,
this is how scientists normally validate a
suspicion that a specific mutation is important
for the development of a tumor.
However, the need to examine a whole
cohort can serve as a limitation in the study
of cancer genomics. If several samples
are required every time physicians want
to understand the role of a driver in a
tumor’s progression within a particular
patient, individualized assessments of how
specific growths will develop become more
complicated to attain. In that regard, this
is where their model adds something new.
“This method doesn’t require a cohort, but
only one tumor to be very deeply sequenced,”
Gerstein said. The approach incorporates
ultra-deep sequencing, a method that
entails the sequencing of the same location
in the genome several times to identify rare
variations, into their analysis. “The novelty
of this method was, instead of looking
into many different samples, we actually
harnessed the frequency of the mutations
based on growth models and analyzed both
the mutations and their frequency in the
population to try to make an assessment of
which of them mattered and which did not,
all within that individual sample,” Salichos
said.
This model could enable scientists to
account for how cancer heterogeneity
results in no two tumors ever being
completely alike. While reliance upon
averages is often important when looking
at growths that behave differently
depending on their genetic make-up,
as well as the context in which they are
www.yalescientific.org
inserted, every tumor—even ones of the
same kind—will behave differently. “With
this kind of model, you can look into
an individual’s tumor in a more direct
way… you don’t have to think about a
cohort or a database very much,” Gerstein
said. Considering how this framework’s
applicability does not require more than a
single tumor, it could lay the foundation
for more specialized evaluations that take
only the characteristics of the studied
tumor into account, making more specific
assessments possible.
Testing the Model’s Efficacy
In order to test the model’s effectiveness,
simulations were run to see if it could,
in fact, predict the presence, time of
occurrence, and effect of a driver mutation.
In addition to testing the algorithmic
function upon which the model relied
by applying it under different growth
models, such as exponential growth and
logistic growth, the group also sought to
demonstrate the framework’s efficacy on
real samples. To that end, the model was
applied to 993 tumors obtained from the
Pan-Cancer Analysis of Whole Genomes
Consortium—an online database that
provides information obtained through
whole genome sequencing and integrative
analysis data of over 2,600 tumors across
thirty-eight diverse types of tumor.
After observing that the identified
drivers were correlated with periods of
positive growth in the samples examined,
ABOUT THE AUTHOR
the group sought to further consolidate
their framework by applying it to a sample
of an Acute Myeloid Leukemia (AML)
tumor. According to Gerstein, this tumor
was chosen due to its history of having
been deeply sequenced in the past. For
AML, the growth patterns they predicted
showed significant similarities with those
exhibited by the tumor.
The promising evidence surrounding the
model’s effectiveness provides reasons to
be optimistic about its future applications.
This novel way to look into tumors could
make a big difference in the future of cancer
treatments. Instead of just relying on broad
data, this could allow doctors to tailor their
evaluations of a patient’s prognosis to what
their specific tumor sample shows. In this
way, this kind of personalized assessment
could herald a new era in cancer genomics. ■
MARIA FERNANDA PACHECO
MARIA FERNANDA PACHECO
YSM
Yale Global Health ReviewYale Daily News
FURTHER READING
Deep Sequencing.
Oncogene
IMAGE COURTESY OF PIXABAY
Three-dimensional illustration of DNA.
September 2020 Yale Scientific Magazine 15
FOCUS
Ecology
THE ROLE OF
IN PLANT
How does soil organic matter help crop growth?
BY CINDY KUANG
Death, SOM, and Soil
Death often stays in the soil. Over time,
organisms and residues in varying
states of decomposition form a vital
component of the soil: soil organic matter
(SOM). SOM has always been thought of as
an indicator of soil fertility, contributing to
healthier soil and better crop growth. Thus,
building SOM, or raising its levels through the
addition of compost or manure, is assumed to
be a cost-effective way of reducing reliance
on external inputs such as fertilization and
irrigation. But how well are the effects of
SOM actually understood? In various studies,
higher SOM has been shown to correlate with
both higher and lower productivity, so until
now, the effects of added SOM on soil fertility
are inconsistent and unclear.
The question is further complicated by
the possibility that this causative pathway is
bidirectional: Does SOM lead to increased
crop productivity, or do increased plant
inputs lead to higher SOM levels? In order
to figure out this relationship between SOM,
agricultural inputs, and productivity, we
need to be able to isolate and investigate
SOM’s effect on plant growth. Emily Oldfield,
a postdoctoral fellow at the Yale School of
Forestry and Environmental Studies, works
in the Bradford lab to study SOM’s effects. “A
lot of the policies that are being put forth by
organizations like the USDA, the Food and
Agriculture organization rest on the premise
of the more organic matter, the better, but
there’s really no hard quantification of how
much more and how much better,” Oldfield
said. “The goal of my research was to try to
put some numbers behind it.” She described
this greenhouse study as an effort to use
a controlled environment to establish a
causative pathway between SOM and crop
productivity.
What is soil?
Soil itself is a complex mixture of elements,
consisting of around forty-five percent
minerals, (including sand, silt, clay) and fifty
percent air and water. In particular, plants
require nitrogen more than any other nutrient,
but they can only take up mineral forms of it,
including nitrate and ammonia, which only
make up two percent of the nitrogen in soil.
The other ninety-eight percent of nitrogen is
organic and inaccessible to plants, meaning
many farmers rely on mineral N-fertilizer to
facilitate crop growth.
The remaining five percent of soil
composition is soil organic matter—anything
that was once living. Though SOM is a very
small percentage by volume, its influence is
disproportionately large. SOM dictates the
structure of the soil, increasing aeration and
water-holding capacity, and acts as a habitat
for other soil organisms. SOM also powers
the cycling, retention and release of various
nutrients essential to productivity.
The Experimental Setup
Oldfield was determined to quantify the
effect that SOM, fertilization, and irrigation
have on crop productivity, both used
separately and in tandem. She designed an
experiment with four target levels of SOM
(1%, 2.5%, 5.5%, 8.5%) crossed with two
different fertilization treatments (none
versus 100 kg N/ha as urea) and further
crossed with two irrigation treatments
(optimum versus half of optimum). To
verify reliability of results, each treatment
was replicated 10 times—for a grand total of
160 experimental pots.
A dilution approach of organic-rich A
horizon soil (obtained from the Yale Farm in
New Haven, Connecticut) was used to create
these varying SOM levels. By mixing the soil
with an external mineral component (sand
and clay) in different ratios, Oldfield was able
to create a wide gradient of organic matter
concentrations without having to artificially
manipulate SOM (which can lead to other
experimental issues).
This greenhouse experiment was
conducted from May to July, and automatic
ventilation ensured that the pots of
spring wheat (Triticum aestivum, L.), the
experimental crop, never exceeded a daily
temperature of 30 degrees Celsius. A drip
irrigation system was calibrated to emit 0.25
gallons to each pot per hour, though this was
later modified to create different treatments
for various pots. “Optimum irrigation” was
determined to be around 127.2 mL of water
each day and “suboptimum irrigation” was
63.6 mL. At the end of the growing period,
all plants were cut at soil level at the same
time, dried at 65 degrees Celsius and then
weighed in aboveground biomass. Soils were
then passed through a sieve and measured
in terms of SOM content, water-retaining
capacity, pH, microbial biomass, and rates of
net mineralization and nitrification.
16 Yale Scientific Magazine September 2020 www.yalescientific.org
Ecology
FOCUS
Results
To analyze the effect of SOM on growth,
the researchers used a statistical method
called regression to quantify the impact of
each measured variable on plant growth. The
regression models showed that aboveground
plant growth increased as SOM levels
increased until a threshold concentration
of around five percent, after which wheat
biomass began to decline. For soils with
optimum irrigation, this decline started
occurring at around six percent SOM.
Across all SOM concentrations, the
biggest difference in aboveground biomass
was observed between the two experimental
extremes: the pots with optimum fertilizer
and irrigation versus the pots with no
fertilizer and half irrigation. However, this
difference was largest at the lowest one
percent SOM concentration (pots with
optimum treatment produced 3.45 times
more aboveground biomass) and became less
dramatic when SOM levels were at or greater
than give percent (optimum pots produced
1.6 times more biomass). This supports the
hypothesis that SOM contribution can, in
some cases, compensate for plants that are
not receiving any supplemental input and
substitute in for mineral N fertilizer. But this
raises more questions of cost and reward—
will productivity of mineral fertilized soils
always outpace that of soils sustained by
organic matter alone? And what about
the reverse hypothesis: can added mineral
nitrogen fertilizer easily compensate for
lower SOM levels?
Nitrification
Though SOM levels did not seem to
exhibit a strong correlative relationship
with net rates of nitrification, they did have
an impact on net rates of N mineralization,
the process by which organic nitrogen is
converted to plant accessible inorganic
forms. As SOM levels increased, rates of
N mineralization increased. This effect
was greater in fertilized soils compared
to unfertilized soils. However, after SOM
concentrations passed a specific threshold
(around seven percent), pots with optimum
treatment began experiencing decreases in
net rates of nitrification: the plants had less
nitrogen accessible to them at eight percent
SOM as opposed to five percent SOM.
Oldfield hypothesizes that this eventual
decrease in nitrification rate may be related
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to increased microbial biomass that is
correlated with higher SOM concentrations.
These microbes themselves need to draw
upon specific nutrients in the soil, including
nitrogen, phosphorous and sulfur, which
may lead to a competitive environment
for nutrients and oxygen in the soil. In
such an environment, less resources
are available for plant use, which could
explain why productivity began to decline
instead of leveling off at the highest SOM
concentrations. “However, it’s very hard
to get a holistic picture of the forms of
nitrogen. A follow up study would be almost
the exact same experimental setup, just
with different levels of nitrogen fertilizer,”
Oldfield said. This would help determine if
these nutritional elements become limiting
at high levels of SOM.
Final Conclusions
Returning to the original question,
can soil organic matter substitute for
agricultural inputs such as insufficient
fertilization and irrigation? These results,
obtained by the systematic variation of
variables, demonstrate an optimistic
answer: building up SOM levels in soil will
have beneficial impacts on productivity.
Though it may not be a perfect replacement
for N fertilizer, SOM can still help cut back
on costly fertilizer inputs without risking
a lowered yield. “We know through other
research that’s being done right now that
agricultural soils tend to have very low
organic matter concentrations as a result of
tillage and other conventional practices...
You rarely see farm soil that is nine percent
organic matter,” said Oldfield when asked
whether the SOM threshold of five percent
would pose a problem.
Some scientists and agriculturists
continue to argue that though productivity
may increase with higher SOM
concentrations, these benefits will never
outpace or outweigh those brought about
by additional mineral fertilizer. However,
this perspective fails to take into account
the cost and availability of fertilizer. “There
are potential outcomes that don’t directly
translate to yield but are enhancements
in other environmental outcomes that we
do care about. This could be mitigating
agricultural runoff to improve water
quality, improving biological activity of
microbial communities, and enhancing
carbon sequestration,” Oldfield said.
What’s next?
Given that many groups such as the
USDA and policy makers rely on the
general notion that “more is better” when
it pertains to SOM levels in soil, Oldfield
is determined to continue delving into the
nuances and intricacies of organic matter
in soil. She briefly explains how increasing
organic matter could pose drawbacks:
increased SOM concentrations are related
to increases in nitrous oxide emissions, a
very potent greenhouse gas. “I’m interested
in linking [this research] to other outcomes
besides yield,” she says. Her ultimate
research goal is to run this experiment on
a much larger scale and get the “full farm
look,” so she can not only measure crop
growth, but also bigger profitability issues
such as balancing yield against costs and
observing ecosystem outcomes. ■
ART BY ANASTHASIA SHILOV
CINDY KUANG
CINDY KUANG is a first-year prospective Neuroscience major in Timothy Dwight College. In
addition to writing for YSM, she also participates in Danceworks and the Chinese American
Students Association.
for threshold effects of soil organic matter on crop growth. Ecological Applications
Soil Use and
Management
of temperate regions: a review. Soil & Tillage Research
September 2020 Yale Scientific Magazine 17
FOCUS
Physics
THE PROMISE OF TWO-COPPER-PAIR TUNNELING
BY SHOUMIK CHOWDHURY
Every day, hundreds of Yale students
take classes in Davies Auditorium and
work in the Center for Engineering,
Innovation, and Design. Likely only several
will know that just a few stories above them—
on the 4th floor of Becton Center—reside
some of the world’s most powerful quantum
computers. These devices are housed in
the Yale Quantronics Laboratory—Qulab
for short—and are operated by cooling
superconducting circuits in microwave
cavities down to millikelvin temperatures, at
which point their behavior is aptly described
by the laws of quantum mechanics.
First proposed in the 1960s by physicist
Richard Feynman, using quantum
mechanical systems (such as atoms) for
computation is not a new concept. Much of
the progress in experimentally implementing
these devices, however, has come in the last
twenty years, with superconducting circuits
(behaving as artificial atoms) emerging as a
leading platform for quantum information
processing. Unfortunately, quantum bits,
or qubits, built from these circuits are still
highly sensitive to various types of noise
from the environment. This has driven
widespread effort in the field to build better
qubits. Recently, a team of researchers at
Qulab—led by principal investigator Michel
Devoret and graduate student Clarke
Smith—designed a new type of protected
superconducting qubit that is robust at the
hardware-level against several different
noise channels.
Notions of Quantum Computing
Quantum computers are based on a
fundamentally different set of rules than
so-called classical computers—a broad
label characterizing most devices in use
today. Classical data are stored in bits,
and a single binary digit can take on two
logical values: 0 or 1. In practice, this could
be realized by the passage of current, and
the lack thereof, through a wire, or by the
magnetization state of a small region of a
hard drive. At the lowest level, under many
layers of abstraction, all classical algorithms
and operations reduce to manipulating
some pattern of bit strings from an input
state to an output state. The key takeaway
here is that bits take on definite values.
In contrast, quantum computers encode
information in the quantum states of
a system—for instance, in the states
representing the lowest two energy levels
of an atom. These two states, which we
can abstractly label as |0> and |1>, form
what is known as qubit subspace, and by
sending appropriate pulses of light to the
atom, one can perform logical operations
on the qubit. The key difference from the
classical model, however, is that we can also
form admixtures of the two states, called
superpositions, of the form α|0> + β|1>. The
outcomes of measuring such superposition
states are determined by rules of probability,
giving either |0> and |1> with probabilities
|α|2 and |β|2 respectively. While this may
seem counterintuitive, it turns out that
several classes of problems are very wellsuited
to a quantum computer that does
not have definite 0 or 1 bits. Some notable
examples include cryptography and prime
number factorization, optimization and
machine learning, and simulating quantum
mechanical systems (such as molecules) for
applications in fundamental physics and
chemistry. However, the aforementioned
sensitivity of quantum information means
that quantum computers are also more
susceptible to noise and other errors that
arise from coupling to the environment. Any
spurious interaction can lead to unwanted
changes to the desired quantum state, and
thus introduces errors into a calculation.
The fragility of quantum information has
led to what Michel Devoret describes as a
two-pronged effort in the field. “The first
approach is to discover a better method
for quantum error correction … while the
second [approach] is to design physical
qubits with better lifetimes and faster
gate operations,” Devoret said. Research
into quantum error correction (QEC)
involves finding ways to encode a logical
bit of quantum information across many
physical qubits—the benefit is then that
the information becomes more robust
to noise, being distributed non-locally
across the system. However, these kinds of
QEC protocols are often very theoretical
in nature, and the authors of the present
study chose to focus on the more tractable
18 Yale Scientific Magazine September 2020 www.yalescientific.org
second approach: engineering qubits
to have properties that make them less
susceptible to noise.
Building Better Qubits
Ultimately, the researchers would develop
a novel type of superconducting qubit better
protected against noise, which Devoret
and coworkers recently reported. The
new design is based on a proposed circuit
element that allows only pairs of Cooperpairs
of electrons to tunnel across the circuit.
“It is an elaboration on the transmon and
fluxonium qubits that we had previously
worked on,” noted Devoret.
The idea of building qubits from
superconducting circuits was first proposed
in 1997; progress in the field followed
rapidly. In such quantum electromagnetic
circuits, charge carriers are pairs of bound
electrons—known as Cooper pairs—which
may quantum mechanically tunnel through
a junction. The quantum mechanical states
of the circuit can be labelled by the number
N of Cooper pairs that tunnel. Although
these circuits are macroscopic objects—
made up of many millions of electrons and
atoms—the number of effective degrees
of freedom is quite small. This gives
superconducting qubits a relatively simple
energy spectrum and is why these systems
are often referred to as artificial atoms.
The transmon qubit is one such type of
superconducting qubit, and it is the qubit
of choice for many of the commercial
players in the field of quantum information,
including IBM, Rigetti, and Google. It
consists of a nonlinear inductance—the
Josephson junction, marked by a crossed
box—in parallel with a capacitor, where
the charging energy of the circuit is much
smaller than the so-called tunnelling energy.
The transmon has a oscillating potential
energy U = EJ cos(φ), where φ is the
superconducting phase in the circuit, and E J
is the tunneling energy for the Cooper pairs
across the junction. “The Josephson junction
is very precious [in superconducting
quantum computing] because it is the
only non-dissipative [lossless] nonlinear
element we have,” explained Xu Xiao, one
of the researchers on the project. “The
cosine potential is therefore the only kind of
nonlinearity we usually have access to,” Xiao
continued. This nonlinearity—stemming
from the cosine potential of the Josephson
junction—is necessary to ensure that the
(frequency) level-spacing is unequal; this
www.yalescientific.org
makes it possible to address only the lowest
two-levels as a qubit, without exciting the
higher energy level states.
The proposed “two-Cooper-pair” qubit
includes a novel circuit element which is
itself composed of two Josephson junctions
in a loop. The current through this loop is
controlled by an external magnetic field
or flux, which, when tuned carefully, gives
rise to an effective potential energy term
of the form U = E J
cos(2φ), i.e., it now has
two energy wells, rather than one. Thus, by
connecting several Josephson junctions, it
is possible to engineer an effective potential
that would not otherwise have been realizable
using a single transmon qubit alone.
The “cos(2φ)” potential reflects the feature
that only pairs of Cooper-pair electrons can
tunnel across the circuit element at a time.
It follows that the number N of Cooperpairs
that have tunneled must have constant
parity (i.e., be even or odd), leading to two
different ground states (of equal energy but
opposite parity). These degenerate ground
states—of equal energy—can be used to
store quantum information in a way that
is resistant towards noise. Like discussed
earlier, this system protects its quantum
information by distributing it across more
than one state. “In experiments, there are
various noise channels, which couple to
the system via some operator. Because of
the special parity of this new potential,
transitions via many such noise channels
between the logical zero and one states are
prohibited,” Xiao said. The researchers at
Qulab tested this new design in simulations
to show that the characteristic lifetimes of
the “two-Cooper-pair” qubit are competitive
with other state-of-the-art implementations,
at around one millisecond. “This [result]
shows how much we can gain … it seems
like if we build more complex circuits, we
could go a long way towards building better
qubits,” Devoret said.
Outlook and Implications
“I think the field as a whole is realizing
how to exploit the specific features of a
quantum system to store information,” said
Xiao, when reflecting on the significance
of their result. “This work is theoretically
quite a successful tactic in understanding
how we go from a circuit design to a
desired Hamiltonian [a mathematical
description of a quantum system], and
then to understanding why it is robust,”
he continued. “Even though this may not
be the ultimate qubit used in a generic
quantum computer, it still educates us a lot
about what types of resources we have.”
Engineering qubits with better coherence
properties can be thought of as a passive form
of error correction, in contrast to the explicit
active quantum error correction protocols
described earlier. “Actually, both methods
are needed,” Devoret said, referring to two
other articles from Qulab to be published
soon. These both try to implement an active
QEC, via two other types of qubit: the Kerr-
Cat qubit (that encodes information in
the phase space of a harmonic oscillator)
and the bridge-state qubit. “This research
takes place on various fronts; you get here
an example of a concerted effort [in our
group] to improve quantum information
science,” Devoret continued. Indeed, as the
field continues to progress, each of these
developments will be crucial steps towards
ultimately realizing a scalable and faulttolerant
quantum computing architecture—
an idea which, unlike in decades prior, now
seems within reach. ■
A R T B Y E L L I E G A B R I E L
ABOUT THE AUTHOR
Physics
SHOUMIK CHOWDHURY
SHOUMIK CHOWDHURY is a junior in Saybrook College studying Mathematics
and Physics. In addition to writing for YSM, he works on research at the Yale
Quantum Institute and Yale Quantronics Lab and is also co-president of the
Society of Physics Students at Yale.
THE AUTHOR WOULD LIKE TO THANK Professor Michel Devoret and Xu Xiao for
their time and enthusiasm for talking about their research.
FURTHER READING
Smith, W.C., Kou, A., Xiao, X., Vool, U., & Devoret, M.H. (2020). Superconducting circuit
protected by two-Cooper-pair tunneling. npj Quantum Inf 6(8). https://doi.org/10.1038/
s41534-019-0231-2
FOCUS
September 2020 Yale Scientific Magazine 19
FEATURE
Research Culture
SHOW AND TELL
SELF-PROMOTION INFLUENCES THE REACH OF SCIENTIFIC DISCOVERIES
BY EVA SYTH
ILLUSTRATION COURTESY OF ANMEI LITTLE
Gender gaps in society continue to persist in everything
from wages to doctoral appointments. Indeed, recent
research from Harvard Medical School and Yale School
of Management suggests a new addition to the chasm: men and
women may differ in how positively they present their research.
University of Mannheim assistant professor and Yale School
of Management (SOM) research fellow Marc J. Lerchenmueller,
Yale SOM professor Olav Sorenson, and Harvard Medical School
professor Anupam B. Jena explored this topic more in-depth by
looking at a number of clinical research and life science articles
published between 2002 and 2017. They then used an algorithm
called “Genderize” to determine the genders of the articles’ first
and last authors, positions which often hold special significance in
life science papers. Lerchenmueller explained that the Genderize
algorithm, which assigns gender to first names based on a database,
was chosen for its accuracy in gender assignment against a US
government-data control sample. The researchers then analyzed
the frequency of 25 words often used in life science articles, which
prior research identified as “distinctly positive,” such as “novel” or
“remarkable”, in the selected articles. The data showed that papers
with both female first and last authors presented their research
positively 12% less than articles with at least one male first or last
author. Additionally, the study found that downstream citations,
which is when a research article is cited in a future article, are
linked with positive terms (9.4% greater citations).
This begs the question: what are the implications of this
research on the greater scientific community? According to
Lerchenmueller, there are two main ones. First, if we observe this
gender difference, there could be multiple reasons. For example,
this study examined published products, not the work originally
submitted to the journals. “Women [may] originally submit
with positive language, but it gets edited out,” Lerchenmueller
explains. Another possibility he proposes is that women may
innately self-screen their writing and not include these terms.
Erin Hengel, a lecturer at the University of Liverpool explored
the question of whether the peer-review editorial process
opined women specifically in the economics field. Hengel found
that in economics, female researchers write 7% more “clearly”
(referring to simple sentence structure and overall readability)
due to higher writing standards for women during peer review.
Lerchenmueller hopes similar work gets done in the life sciences,
pointing out that nowadays, people more often put their papers
up online before they are published in a journal. According to
Lerchenmueller, this could be a good place for mining papers
before the editorial process begins.
The second implication applies more broadly to papers authored
by all genders. According to Lerchenmueller, in science today
versus past years and decades, “We generally observe an increase
in [positive] adjectives to describe research regardless of gender.”
In the most influential journals, the use of positive adjectives
was up by over 80% comparing 2017 to 2002. This represents
a different kind of potential danger. If more and more authors
are promoting their research findings as “novel” and “unique”
without actually supporting these claims in the body of the article,
a new issue develops that calls the scientific community itself into
question. “Science is depicted as a voice of reason in the world
of fake news,” Lerchenmuller explains. If science is beginning to
tread a similar path with these exaggerated claims, it may lose
some of its credibility as an objective source. This increase in
positive research promotion could be happening for a number
of reasons. In science today, there is an exploding amount of
papers being published, and authors are thus motivated to draw
attention to their work in order to have it stand out in the sea
of new research. It is also reasonable to imagine that scientific
journals don’t discourage this type of promotion. After all, editors
need to include high-profile articles to be high-profile journals.
In order to combat this trend, the scientific community may need
to make a concerted effort towards encouraging reasonable claims
surrounding research findings. In the meantime, the gender gap
with regard to scientific publications continues to persist. ■
Hengel, E. (2017). Publishing while Female. Are women held to higher
standards? Evidence from peer review. Cambridge Working Papers in
Economics CWPE1753. https://doi.org/10.17863/CAM.17547
Lerchenmueller, M. J., Sorenson, O., & Jena, A. P. (2019). Gender differences
in how scientists present the importance of their research: observational
study. BMJ, 2019(367). https://doi.org/10.1136/bmj.l6573
20 Yale Scientific Magazine September 2020 www.yalescientific.org
Agricultural Science
FEATURE
DOGS ON DUTY
CANINE DETECTION OF PLANT PATHOGENS BY MAKAYLA CONLEY
As technological advancement allows the world to become
increasingly connected through trade and travel, exotic
pathogens spread more easily across the globe. These
pathogens are not limited to human disease but include plant
pathogens as well. According to Tim Gottwald, the lead researcher
of the Pathology Department at the US Department of Agriculture,
exotic pathogens are especially dangerous to plant populations.
Gottwald explained that most plant species and their pathogens
“develop together evolutionarily, whereas citrus developed in
the absence of its most devastating exotic pathogen, a bacterium
Liberibacter asiaticus (CLas).” Rather, CLas was
introduced to citrus about one hundred years ago by an insect vector
most likely originating in the southeast of Asia near India. Because of
this, citrus lacks a natural resistance to CLas.
In recent years, Gottwald’s lab has studied diseases that plague the
citrus industry in the United States, specifically the CLas bacteria.
Gottwald explained that insects act as “little hyperdermic needles”
and spread the CLas bacterium from tree to tree. Infected insects
with CLas on their proboscis and in their gut deposit some bacteria
into plant cells when they feed on a tree’s phloem. In order to stop a
widespread epidemic, it is important to catch a tree in the early stages
of infection before the bacteria can spread to the rest of an orchard.
A recent paper published by Gottwald’s team reported that dogs could
be trained to smell a CLas infection with near-perfect identification of
infected trees when surveying orchards. In the first year of the study,
the team trained ten dogs to smell citrus trees and sit next to trees
they identified as infected with CLas. To test the dogs’ accuracy, one
hundred tree test grids were set up with infected trees placed randomly
throughout. The dogs were taken through the ten grids in the same
manner they would survey a commercial orchard. Each dog had nearly
a perfect hit rate and identified infected trees with over ninety-nine
percent accuracy over the one thousand trees tested by each dog.
This research was prompted by a great need for new methods of early
detection of plant pathogens. Gottwald’s research group
began to study the use of canine olfaction as a more
IMAGE COURTESY OF
PIXABAY
effective and accurate early detection method back
in 1998. At that time, citrus canker was an exotic
plant disease that was causing an epidemic in
fruit trees. Following a suggestion by one
of his colleagues, Gottwald’s team
explored the use of dogs as a
viable
method for early detection of the disease, but their research came
to an abrupt halt in 2001. After 9/11, canine detection research was
diverted away from the agricultural business and instead focused
on detection of explosives. It wasn’t until 2005 that funding became
available, and the Pathology Department could once again study the
promising field of canine detection.
Before the use of canine olfaction, farmers previously relied on
human visual detection and PCR confirmation to determine if a
tree was infected with the CLas bacterium. However, each of these
methods presented severe shortcomings. Visual detection consists of
a trained surveyor walking through an orchard and looking for host
responses to the infection, i.e. symptoms of the disease. There are two
main challenges to visual detection: latency and absence of visual clues.
“The latency in symptom development can be anywhere from months
to years after an infection takes place,” Gottwald said. By the time a
surveyor observes an infected leaf, the tree could have already served
as a reservoir of bacteria and spread the infection to surrounding
trees. Furthermore, even if a leaf does display symptoms, it is often
difficult for a person to see them. The orientation and location of a
symptomatic leaf on a tree can lead to missed infections. On the other
hand, PCR confirmation is a molecular assay run on tissue samples
from leaves that indicate whether the tissue is infected (i.e. has CLas
DNA) or not. “PCR is almost a perfect assay. If you have infected
tissue, [it will test positive],” Gottwald said. However, PCR presents
a sampling problem: There are a tremendous number of leaves on a
mature tree, and early in the infection, only a few leaves are infected.
In more advanced infections, the CLas bacterial infection may still be
confined to sectors in a tree, so not every leaf will be infected. Even
within a leaf that is infected, not every cell will contain the bacteria.
Canine olfaction solves many of the limitations faced by these
other methods. Dogs can detect very early infections in only a few
leaves anywhere in a tree. Thus, the latency problem associated with
visual signs of infection is eliminated, allowing for earlier diagnosis.
Canine detection is much more accurate than a human performing a
visual search of tree leaves. There is no reliance on a molecular assay
performed only on a few leaves, so canine detection also sidesteps the
sampling problem of PCR. Overall, the use of canine olfaction for the
detection of plant pathogens is a highly effective and accurate method
that does not suffer from the limitations present in conventional
detection methods. This new technique is already being implemented
in orchards across the country, saving the lives of countless trees and
livelihoods of many farmers. ■
Gottwald, T., Poole, G., McCollum, T., Hall, D., Hartung, J., Bai, J.,
... Schneider, W. (2020). Canine olfactory detection of a vectored
phytobacterial pathogen, Liberibacter asiaticus, and integration
with disease control. PNAS, 117(7). https://doi.org/10.1073/
pnas.1914296117
September 2020 Yale Scientific Magazine 21
FEATURE
Computer Science
AN ALGORITHMIC
JURY
PREDICTING
RECIDIVISM
RATES WITH
ARTIFICIAL
INTELLIGENCE
BY MIRILLA ZHU
Over the last two decades,
predictive risk assessment tools
have been used to determine
the fates of millions of individuals in the
criminal justice system, deciding whether
a defendant will be detained or released
based on an algorithmic calculation of
risk. This technology has been embraced
by courts and policymakers alike, with one
Congressional bill going as far as to call
for the implementation of risk assessment
systems in every federal prison. But in
2018, researchers Julia Dressel and Hany
Farid published a surprising result: a
commonly used risk assessment tool
named COMPAS was incorrect almost
half the time. With the accuracy rate of
COMPAS only a few percentage points
higher than that of humans with no
judicial experience, some judges were left
wondering whether they would be better
off not using algorithms at all.
When Stanford graduate student
Zhiyuan Lin heard about Dressel and
Farid’s study, he was equally surprised at its
findings—although for a different reason
than the public. As a computer scientist
in Stanford’s Computational Policy Lab,
Lin had encountered dozens of studies
demonstrating that algorithms performed
better than humans, and he was puzzled
why Dressel and Farid had found otherwise.
Together with a team of researchers from
Stanford and Berkeley, Lin decided to see
whether he could fill in the missing pieces
to understand what was going on.
Lin and his colleagues began by
attempting to replicate the 2018 study,
giving over six hundred participants
the same set of profiles that Dressel and
Farid used and asking them to predict
whether the defendants would recidivate.
When they provided participants with
immediate feedback after each response,
they found that the participants guessed
correctly sixty-four percent of the time,
compared to the sixty-two percent
accuracy rate reported in the 2018 study.
The COMPAS algorithm’s accuracy rate
of sixty-five percent matched the 2018
study exactly.
Next, the researchers investigated
whether these results would hold if they
modified the experiment to resemble the
real world more closely. They did so in
three ways: providing the respondents
with more detailed criminal profiles,
lowering the average recidivism rates
to reflect the rate of violent crime,
and most significantly, not telling the
respondents whether they were right
or wrong. “Receiving this kind of
immediate feedback is something that
rarely happens in reality, because when
the judges are making bail decisions,
they don’t find out whether a defendant
22 Yale Scientific Magazine September 2020 www.yalescientific.org
Computer Science
FEATURE
will recidivate until two years later,” Lin
said. “More often than not, they don’t
see the outcome at all.”
Under these new conditions, the
algorithm performed substantially
better than humans. This accuracy gap
was especially pronounced in the case
of violent crime, for which the study
participants consistently overestimated
the risk of recidivism.
When feedback was
present, the participants
adjusted
their
predictions to reflect
the lower recidivism
rate, but when they
didn’t receive feedback,
they continued to
guess incorrectly forty
percent of the time.
In comparison, the
algorithm was correct
eighty-nine percent of
the time. Lin noted that
this percentage may have
been skewed by the low
recidivism rates, since
a simple algorithm that
guessed “no” each time
could have achieved the
same score. But even
under a different measure that accounted
for variations in the base recidivism rates,
the algorithm still performed better than
humans by achieving sixty-seven percent
accuracy. The researchers were able to
replicate their results with various risk
assessment tools including their own
statistical model, suggesting that these
improvements in performance were not
unique to the COMPAS algorithm.
For researchers like Dressel, however,
Lin’s findings emphasize just how limited
algorithms can be. Accuracy rates under
seventy percent are still “really low,” she
said, given that “the consequences of
making mistakes is so high.” Dressel also
expressed concerns about racial bias,
citing a 2016 ProPublica study which
found that COMPAS predicted false
positives for black defendants at almost
twice the rate of white defendants.
“A fundamental principle of machine
learning is that the future will look like
the past, so it’s not surprising that the
predictions being made are reinforcing
inequalities in the system,” she said.
“A FUNDAMENTAL
PRINCIPLE OF
MACHINE LEARNING
IS THAT THE FUTURE
WILL LOOK LIKE THE
PAST, SO IT'S NOT
SURPRISING THAT
THE PREDICTIONS
BEING MADE ARE
REINFORCING
INEQUALITIES IN
THE SYSTEM.”
Lin acknowledged the shortcomings
of algorithms, but he said that humans
exhibit bias too—and that the biases now
embedded in algorithms initially arose
from humans themselves. Since people
often make decisions in an inconsistent
manner, even imperfect algorithms
could inject a degree of objectivity into
an arbitrary criminal justice system.
Lin emphasized that
these algorithms should
only be used for their
intended purpose—
risk assessment—and
that judges should
consider other factors
when making their final
decision. “There’s this
dichotomy of whether
we should rely only
on humans or only on
artificial intelligence,
and that’s not really how
things work around here,”
Lin said. “Algorithms
should be complementary
tools that help people
make better decisions.”
In order to ensure that
algorithms are being
used correctly, Lin
believes that policymakers must be aware
of how they work. With its black-box
formulas that are protected as intellectual
property, the COMPAS software has not
been conducive to fostering this kind
of understanding. However, developing
transparent and interpretable algorithms
is very much possible. In another
study, to demonstrate accessibility
without compromising accuracy, Lin
created an algorithm with an eight-step
checklist that can be scored manually by
prosecutors to track exactly how risk can
be calculated. The checklist is simpler
than many traditional machine learning
models, yet it performs just as well in
real-life situations.
But given that neither algorithms
nor humans are perfect predictors of
recidivism, Dressel suggests that our focus
should not be on developing better tools,
but rather reducing our reliance on them.
Enacted this January, the New York bail
reform law is an instance where the role
of risk assessment has become essentially
obsolete—all pretrial detainees arrested
for nonviolent crimes are allowed to go
free without posting bail, regardless of
perceived risk. According to a report
by the Center for Court Innovation, the
reform could decrease the number of
pretrial detainees by forty-three percent,
which is especially significant given that
eighty-five percent of them are Hispanic or
black—by no coincidence the same races
overrepresented in algorithmic predictions
of high-risk individuals. “I think what
New York did is great,” Dressel said. “The
decisions we’re making in a pretrial context
shouldn’t be based on someone’s risk. We
shouldn’t sacrifice anyone’s liberty until
they’ve had a fair trial.”
Still, many researchers believe there’s a
place for algorithms within the criminal
justice system. “It’s a bit premature to be
using these kinds of algorithms now, but
I think we will be seeing more of them
in the future,” said Nisheeth Vishnoi, a
computer science professor and founder of
the Computation and Society Initiative at
Yale. “It’s good that people are scrutinizing
them, because what that is doing is creating
new dialogue around these issues.” A
proper application of machine learning
algorithms, he says, will require learning
in all directions—from policymakers,
scientists, and each other. ■
A R T B Y E L L I E G A B R I E L
Dressel, J. & Farid, H. (2018). The accuracy, fairness, and limits of predicting recidivism. Science
Advances, 4(1). https://doi.org/10.1126/sciadv.aao5580
Lin, Z., Jung, J., Goel, S., & Skeem, J. (2020). The limits of human predictions of recidivism.
Science Advances, 6(7). https://doi.org/10.1126/sciadv.aaz0652
Lin, Z., Chohlas-Wood, A., & Goel, S. (2019). Guiding prosecutorial decisions with an interpretable
statistical model. In AAAI/ACM Conference on AI, Ethics, and Society (AIES ’19). https://doi.
org/10.1145/ 3306618.3314235
www.yalescientific.org
September 2020 Yale Scientific Magazine 23
FEATURE
Genomics / Clinical Research
LETTING
EXPERIENCE
GUIDE THE WAY
The ultimate goal of clinical and
translational research is to leverage
scientific discovery and innovation
to drive improved treatments and patient
outcomes. In light of this goal, it seems
reasonable that patients and the public
should be involved in the research process.
Yet, there is a disconnect between researchers
and the public, even in translational settings.
There is increasing awareness of the
necessity of patient and public involvement
in both clinical and preclinical research.
There are several disadvantages at play
when these partnerships are absent.
For one, scientists often lack personal
experience with the diseases they study.
As a result, they may not be attuned to the
most pressing treatment needs in disease
communities, potentially limiting their
ability to translate knowledge production
into knowledge use. In other words, lack of
patient input on the research process can
result in research waste––in which scientific
communities produce research findings
that have minimal real-world application.
Moreover, given that a great deal of research
is publicly funded, scientists have a duty to
be accountable and transparent with the
public. This is greatly facilitated by public
involvement in research, which therefore
has inherent democratizing value.
What is patient and public involvement?
The patient and public involvement (PPI)
model is an approach that acknowledges
the need to include patients and the
public in research. PPI is flexible and can
consist of varying degrees of participation
BY ZOE POSNER
in the research process. Involvement often
focuses on including patients in research
design and in disseminating results. Less
commonly, it encompasses participation
in data analysis and methodological
design. Significantly, PPI methods can be
implemented in a broad range of research
areas, from clinical studies and cancer
research to groundbreaking research in
the basic life sciences.
PPI offers several benefits over traditional
research, which is executed solely by the
investigating team of scientists. As implied
by its name, PPI democratizes research by
increasing the number of voices included
in the research process. Researchers are
optimistic that including public voices
can produce studies that are more ethical
and practical in nature. In health studies
especially, patients can offer critical and
overlooked perspectives in the research
process. They can highlight aspects
of the disease and treatment that are
deprioritized in the academic community
(such as drug-induced cytotoxicity), and
also help researchers identify the most
pressing pathobiological questions in the
patient community.
Recently, PPI is gaining traction for
its potential to address representational
inequality in research. There is an extreme
lack of representation in biomedical
sciences and health professions. As a
result, the unique health perspectives and
grievances of minority populations are
easily overlooked. Additionally, those who
participate in clinical trials or experimental
drug treatments are typically those with the
best access to healthcare––most frequently,
individuals who are affluent and white.
These factors contribute to persistent
disparities in health outcomes. PPI, by
including a diverse patient population, can
help foreground the health experiences
of marginalized populations. Researchers
who conduct PPI studies are aware of the
need to increase diversity in research.
While this awareness is encouraging, many
of these researchers recognize that thus
far, a majority of patient involvement in
research is by wealthier white patients.
Groups like the Community and Patient
Partnered Research (CPPRN), which
focuses on improving mental and
behavioral health outcomes for Black and
Hispanic populations, are working towards
ensuring greater diversity in patient
networks to overcome this challenge.
Finally, patient-centered research holds
promise for improving the study of rare
pathologies, including rare cancers.
Rare diseases are difficult to study due to
restricted availability of patient samples.
Patient-centered approaches to rare
diseases, by generating patient networks,
can facilitate the collection of patient
samples and data over a broad geographic
range. This can compensate for the low
frequency of disease incidence. The Count
Me In Initiative has spearheaded five
projects involving patient-partnered cancer
research. Most recently, the initiative has
launched The Angiosarcoma Project,
which focuses on angiosarcoma—a rare,
notoriously aggressive cancer that develops
in the lining of blood and lymph vessels.
The Angiosarcoma Project: A model for PPI
The Angiosarcoma Project, with 338
patients, is the largest angiosarcoma
project to date and has produced several
novel and high-impact findings. The
project was led by Corrie Painter of the
Broad Institute. In the initial stages of
the project, Painter ensured that patients
were involved in the development
of the online platform that would
then be accessible to them and other
patients. After receiving guidance from
angiosarcoma patients, Painter and
her team built out the project, received
direct patient feedback, and synthesized
that feedback in an iterative process.
This serial generation-feedback-revision
IMAGE COURTESY OF FLICKR
24 Yale Scientific Magazine September 2020 www.yalescientific.org
Genomics / Clinical Research
FEATURE
loop was done for everything seen on the
Angiosarcoma Project Website.
Once the project was launched,
high participation rates were almost
immediate. After joining the project,
participants could give consent to share
online medical records, and send in saliva,
blood, and tumor samples. Throughout
the process, research updates were
continuously disseminated to patients
through the online platform, allowing
patients to provide feedback.
Through the project, over seventy tumor
samples were obtained, allowing for large-
scale whole exome sequencing, a method
that sequences protein-coding regions
in the genome. Painter’s team could also
access medical history data. Integrating
these types of data enabled robust analysis
of multiple subclasses of angiosarcoma.
Sequencing data obtained for patient
tumor-samples elucidated three genes––
PIK3CA, GRIN2A, and NOTCH2––that
were consistently altered in angiosarcoma.
Subsequent analysis of mutation frequency
indicated that the PIK3CA gene is one
of the most commonly mutated in breast
angiosarcoma. This finding is clinically
relevant, pointing to PIK3-alpha inhibitors
as a potential therapeutic route for primary
breast angiosarcoma treatment. Finally,
Painter looked at the mutational burden,
which is the number and type of somatic
mutations in the DNA of cancer cells.
She found that the number of mutations
in head-neck-face-scalp (HNFS)
angiosarcoma is significantly enriched, in
a pattern consistent with UV-light induced
DNA damage. This finding suggests that
this angiosarcoma cohort might respond
well to immune checkpoint inhibitors.
The novel findings produced by this
project are already making an impact. “[Our
project is] decoupled from the publication
process entirely, so we’ve been releasing
data for well over a year,” Painter said. By
presenting at Clinical Oncology Alliance
Meetings and to The American Society of
Clinical Oncology (ASCO), Painter was able
to share her results with clinical researchers.
As a result, “There are three different groups
working on drafting clinical trials. One
of them was able to get angiosarcoma as a
cohort in an existing checkpoint inhibitor
study,” she said. Painter also mentioned that
two additional studies are being currently
developed based on her data. Painter also
anticipates the potential for pre-clinical
researchers, who are not necessarily
studying angiosarcoma, to see results from
her project that involve pathways or genes
of interest and to become interested in
partaking in angiosarcoma research.
The Angiosarcoma Project is a significant
step forward for patient-partnered
research. Painter demonstrated how a
sincere and deep level of collaboration
between patients and researchers can
stimulate the most meaningful and
translationally relevant results.
Challenges and future directions for
PPI in research
Successful patient-partnered research,
like the Angiosarcoma Project, is
popularizing PPI. This is reflected in an
increasing number of PPI studies, as well
as the proliferation of grant applications
that require researchers to describe how
they plan to involve patients of the public
in their studies. As this approach becomes
more popular, it is important to consider
current challenges and future directions
of this type of research.
The single greatest challenge to expanding
PPI in research is scientists’ lack of clarity
on the most effective ways to facilitate
engagement with patients. Painter, when
discussing the Angiosarcoma Project,
noted that building the project, “was
much easier than the metastatic breast
cancer project because we were going off
a vision.” For her, the metastatic breast
cancer project provided a scaffold that
was subsequently utilized to build out the
Angiosarcoma Project in a way that was
tailored to that specific patient community.
Painter’s insight highlights how researchers
can draw from previous studies in order to
guide and facilitate their own PPI studies.
Painter notes that it is imperative to adapt
each project to the needs of the specific
disease community, but that having a pre-
existing vision is still highly useful.
As PPI expands, ensuring a continued
commitment to patient diversity is
critical. One way to facilitate this is by
ensuring that patient-advocates from
diverse backgrounds are included, since
these advocates are the cornerstone of
research outreach efforts.
Finally, while most research integrating
a patient-centered approach involves
clinical research or translational research
that makes use of patient samples,
there is a strong argument for patient-
public involvement in pre-clinical and
basic science research as well. Emma
Dorris is a molecular biologist at The
University College Dublin who also leads
a PPI initiative for Arthritis Research.
She argues that PPI elevates research by
increasing the relevance and impact of
projects. Dorris believes that patients can
provide novel insights that direct scientists
towards areas of a disease’s biology that
haven’t been previously studied. While
in a wet-lab setting patients cannot be
involved in the data collection or analysis,
there is a clear and meaningful space for
their involvement in defining research
questions and goals. In order to encourage
researchers in preclinical labs to effectively
integrate PPI, experts recommend training
in patient-communication, as well as
top-down incentives and infrastructure
support from research institutions.
Patient-partnered research holds immense
promise for biomedical science. It offers to
improve the quality and relevance of research,
improve relationships between researchers and
the public, overcome boundaries to studying
rare diseases, and help ameliorate racial
and socioeconomic inequalities in research.
As PPI studies continue to expand, critical
examination of what types of engagement are
most effective will be necessary. ■
Burns, J. A., Korzec, K., & Dorris, E. R. (2019). From intent to implementation: Factors affecting public
involvement in life science research. doi: 10.1101/748889
Jayadevappa, R. (2017). Patient-Centered Outcomes Research and Patient-Centered Care for Older
Adults. Gerontology and Geriatric Medicine, 3, 233372141770075. doi: 10.1177/2333721417700759
Pii, K. H., Schou, L. H., Piil, K., & Jarden, M. (2018). Current trends in patient and public involvement in
cancer research: A systematic review. Health Expectations, 22(1), 3–20. doi: 10.1111/hex.12841
Staniszewka, S. (2020). A patient–researcher partnership for rare cancer research. Nature Medicine,
26(2), 164–165. doi: 10.1038/s41591-020-0766-y
www.yalescientific.org
IMAGE COURTESY OF PXHERE
September 2020 Yale Scientific Magazine 25
FEATURE
Bioengineering
KEEPING DRY UNDERWATER
LEARNING SUPERHYDROPHOBICITY FROM PLANTS
BY YU JUN SHEN
ART BY ANMEI LITTLE
Hydrophobic materials have many
applications, yet many are easily
disrupted by the environment,
losing their dryness. To find the key
to the next generation of highly waterrepellent
materials, scientists have
turned to Mother Nature for inspiration,
studying species that thrive in water,
like lotus plants and ferns.
Recently, Xiang Yaolei and his team
at Peking University investigated the
hydrophobic leaves of Salvinia molesta,
a sturdy fern species best known for
being highly invasive. The researchers
discovered that the Salvinia leaf
had evolved surface patterns ideal
for generating a smooth layer of air
underwater. They then replicated this
design on a 3D printed specimen.
This work paves the way for improved
underwater applications, such as reduced
drag on underwater vehicle and improved
protection against corrosion in pipes.
In a laboratory study of carefully
degassed underwater Salvinia leaves, the
researchers observed that an air layer
forms spontaneously on the leaf surface.
For accuracy purposes, the researchers
applied a high water pressure to remove
any trapped air on underwater Salvinia
leaves first, then injected new air via a
small syringe. “It is different from a lotus
leaf. Here, a whole layer of air forms, while
for the lotus only a few individual bubbles
appear. The Salvinia mechanism is an
active replenishment of air,” Xiang said.
Scientists and engineers sought to
discover the underlying design behind
the Salvinia leaf ’s
active replenishment
mechanism. Using
a scanning electron
microscope, the team
found three key
features of the Salvinia
leaf ’s hydrophobicity:
i n t e r c o n n e c t e d
w e d g e - s h a p e d
microgrooves on the
leaf ’s surface, long hair
stems, and egg-beater
shaped heads. The wedgeshaped
microgrooves
enabled stable air pockets to
form and expand by capillary
action, going against the flow
of gravity. The interconnected and
widespread microgrooves allow air to
spread efficiently and spontaneously
across the leaf surface.
The researchers found that, once
formed, the air layer then rises along
the frame provided by the hairy stems.
Moreover, the eggbeater-shaped head,
which caps the microgrooves and hair
stems, stabilizes the entire air layer by
surface tension. As the stems of the plant
are irregular, the air layer arrived at the
top of short stems will pin and “wait” for
the air layer arrived to the top of high
stems. These three features combine
to actively replenish the air layer, even
in the presence of water flow. Hence,
compared to passive hydrophobic
materials, the Salvinia design is more
reliable in sustaining an air layer.
Xiang is enthusiastic about the
industrial applications of Salviniainspired
hydrophobic materials. “As it is
an efficient way to protect the air mattress
in different environmental conditions, it
will expand the applications of superhydrophobic
surfaces, especially in
extreme environments,” Xiang said.
An application of particular interest
is the anti-corrosive coating on ship
keels. Corrosion below the waterline
weakens and damages the ship. A passive
solution is anti-corrosion chemical
paint, though it degrades over time and
leaves environmental residues. Current
active systems inject bubbles to stick
to the surface, but this must be done
continuously and while fully submerged.
26 Yale Scientific Magazine September 2020 www.yalescientific.org
Bioengineering
FEATURE
IMAGE COURTESY OF WIKIMEDIA COMMONS
Hydrophobic leaves help aquatic plants thrive in
wet environments.
Xiang believes an industrial translation
of the Salvinia system—microgrooves,
long stems and eggbeater-shaped
heads—could create a self-replenishing
active system that prevents prolonged
wetting along the ship hull. A similar
approach might protect pipelines as
well, reducing maintenance costs and
improving water quality.
Another potential application is drag
reduction to enable faster underwater
vehicles. An object moving in a fluid
experiences a resistance to its motion,
which can be reduced significantly
if the object is enveloped in an air
cocoon. Compared to current methods
of generating this air cocoon, Xiang’s
research may have wider usage. “Methods
like supercavitation work only at high
speeds,” Xiang said. The Salvinia-based
design could achieve drag reduction
“even at lower Reynolds numbers,”
where the object moves slowly in a less
turbulent manner. In the lab, the air
layer is retained at low fluid velocity of
half a meter per second. Further research
would be needed to scale up this speed
for use in ships, where the water flows at
a few meters per second.
To replicate Salvinia’s natural patterns
on artificial surfaces, the Peking
University researchers 3D printed a
specimen with regular microgrooves,
long stems, and eggbeater bulbs. Due
to the extreme precision required, the
overall sample size was a square of four
millimeters in length. The team printed
a Salvinia-inspired design (complete
with microgrooves, stems and eggbeater
heads) as well as a control specimen
(with stems and eggbeater heads only).
Using a confocal microscope, Xiang and
the researchers found that a smooth layer
of air only appeared in the first sample.
In the control, individual air bubbles
formed instead. Hence the Salvinia’s
microgrooves are an essential component
to achieving a smooth air layer, even more
so than the hydrophobic lotus leaf, which
only has long stems and eggbeater bulbs.
The lotus, as represented by the control,
cannot recover its air layer once disrupted.
In a further investigation using the
3D printing apparatus, the researchers
varied the microgroove angles to test the
predictions of their air layer formation
theory. Using a thermodynamic free
energy model, the researchers calculated
the angle requirement for a stable air
layer to form spontaneously. The natural
Salvinia leaf ’s microgroove angle matched
that range, and additional 3D printed
tests verified the range of full, partial,
or no expansion. Again, experiments
showed that the microgroove pattern
is critical for the Salvinia plant’s strong
hydrophobic capability.
Following his lab’s focus on boundary
layer stability research, Xiang and his
team’s research on the Salvinia leaf gives
new understanding of the boundary
layers of a submerged body. “We wanted
to find out what made the air layer on
Salvinia plant so stable. It turns out
the hydrophobicity gives an extremely
strong adaptability to environmental
conditions. This also provides a
theoretical basis for the design of
artificial bionic materials,” Xiang said.
The Salvinia leaf, which actively
replenishes its air layer through a discreet
anatomy, is one of the most effective waterrepellent
surfaces we know of currently. A
humble leaf holds many secrets. ■
Xiang, Y., Huang, S., Huang, T., Dong, A., Cao, D., Li, H., Xue, Y., Lv, P., & Duan, H. (2020). Superrepellency
of underwater hierarchical structures on Salvinia leaf. PNAS, 117(5), 2282-2287.
www.yalescientific.org
September 2020 Yale Scientific Magazine 27
THE NEW 98.6 DEGREES
How and why human body temperature has lowered
COUNTERCOUNTER
BY
KELLY
FARLEY
KELLY
POINT
IMAGE COURTESY OF ROY PERRY
When you go to the doctor, the first measurement
taken—whether it’s an annual check-up or a sick
call—is your body temperature. Over the years, the
method has varied, from mercury thermometers under the
armpit to infrared thermometers scanned over the forehead. But
the standard indicator of health has remained the same since
1851, when it was first reported by the German physician Carl
Reinhold August Wunderlich. As you’ve probably heard before,
the normal human body temperature is 98.6 degrees Fahrenheit.
Julie Parsonnet and her colleagues at Stanford, however, have found
evidence that disrupts this paradigm: they recently reported that that
human body temperature has steadily decreased over the past two
centuries to a current average of 97.9 degrees Fahrenheit. In the most
comprehensive analysis to date, their study examined hundreds of
thousands of temperature measurements from three databases ranging
from the end of the Industrial Revolution to present day. In the end,
they found a constant decrease in temperature from decade to decade.
Parsonnet’s study is important not because it shows that human
body temperature is lower but because it shows that it has dropped
since the nineteenth century. Medical professionals have known for
the past few decades that healthy human body temperature is lower
than the 98.6 degrees Fahrenheit standard. A Russian pharmacy
chain founded in 1991 is even named 36.6—the Celsius equivalent
to 97.9 degrees Fahrenheit—in honor of the more accurate lower
temperature. Scientists previously assumed that 98.6 degrees
Fahrenheit must have been wrong at the time of measurement
as well, blaming differences in historical measurement methods
and instrument calibration. According to Parsonnet, the original
number may not have been wrong at all. It is just no longer accurate
for modern humans. The question is: why?
“Temperature is a marker of metabolism,” Parsonnet said. With
lower body temperatures, our metabolism must be slower. Perhaps
this change is caused by our more temperate environments.
With heating and air conditioning, modern Americans live
in the “thermoneutral zone” of sixty-four to seventy-two
degrees Fahrenheit in which our bodies do not have to increase
metabolism to keep warm. With inactive modes of transport and
sedentary desk jobs, we also move less, further suppressing our
metabolic rate and possibly explaining the rise in obesity.
Parsonnet prefers an alternate explanation: our cleaner
environments. Thanks to sewage systems, hand sanitizer, antibiotics,
and modern infrastructure, we have decreased the rates of formerly
widespread infections, such as syphilis, rheumatic heart disease, and
tuberculosis. Thanks to vaccination, we have minimized infectious
diseases of the past and have hopes to apply the same to infectious
diseases of the present. All of this leads to decreased inflammation,
which in turn leads to lower metabolism and thus a lower body
temperature. It is uncertain whether this decreased inflammation is
true everywhere; the modern temperatures in the study were collected
in the United States. Moving forward, Parsonnet is interested in
examining temperatures in developing countries as well.
If the “normal” human body temperature is lower, does this
challenge the way we approach fever and medical diagnosis?
Though taking your temperature may be the first thing your doctor
does, it is never the last. Think about the family history, blood
pressure readings, throat swabs, blood draws, and everything else
that goes into a sick call. We are drawn towards binaries: sick versus
healthy, feverish versus normal. But temperature varies from
person to person and even within a person over the course of a day.
The real question is not why our 98.6 degrees Fahrenheit
standard was wrong but rather why we rely on it so heavily
when every person is an individual. There is no overall “normal”
human standard. Instead, “There is a ‘normal’ for each person
that depends on their age, sex, weight, height, and the time
of day their temperature was measured,” Parsonnet said. Her
team is already working on an algorithm that determines what
is abnormal for an individual patient at any particular time. In
the age of big data and personalized medicine, we are beginning
to see patients as individuals instead of averages. Today, we are
surprised that the 98.6 degrees Fahrenheit standard has been
replaced by 97.9 degrees Fahrenheit. In the future, we may be
surprised that we relied on an average at all. ■
Barondess, J. (2014). Scanning the Chronic Disease Terrain: Prospects
and Opportunity. Transactions of the American Clinical and Climatology
Association, 125(2014), 45-56.
Fischer, K. (2020, January 20). Forget 98.6 degrees Fahrenheit. Humans Are
Cooling Off — Here’s Why. Healthline.
Protsiv, M., Ley, C., Lankester, J., Hastie, T., & Parsonnet, J. (2020). Decreasing
Human Body Temperature in the United States Since the Industrial
Revolution. eLife 9e49555.
28 Yale Scientific Magazine September 2020 www.yalescientific.org
VS.
SCIENCE
THE APOCALYPSE
ANTIBIOTIC
RESISTANCE
BY VICTORIA
VERA
IMAGE COURTESY OF WIKIMEDIA COMMONS
Since the discovery of penicillin, the first commercialized
antibiotic, in 1928, our society has dramatically improved.
We have raised life expectancy, improved quality of life,
and altogether created a healthier world. However, it’s not just
us who have adapted. Bacteria have entered a new age as well,
one characterized by increasing resistance to the antibiotics we
create. Antibiotic resistance was first observed in 1947, around
six years after commercial production of penicillin began. Since
then, the problem has become much more widespread. This poses
a scary new problem for us. In the future, might it be possible
for an infected piercing or scrape to bring us to our deathbeds?
Worldwide, scientists have been working tirelessly to prepare for
when our main line of defense finds itself compromised. While
studying antibiotic-producing bacteria known as actinomycetes,
researchers in the Wright lab at McMaster University in
Canada stumbled upon possible solutions: two new functional
antibiotics, and a way to predict more.
All this was a result of mapping ancestry. Rather than directly
searching for a new antibiotic, Wright’s research team sought to
investigate more broad-ended ideas. The motivating factor was a
simple question: “What are the origins of antibacterial resistance?”
Wright said. Many antibiotics, including penicillin, are derived from
biological organisms. Wright and his team first sought out ancestral
history of the antibiotic properties of actinomycetes, bacteria
found in soil that manufacture many of our current antibiotics.
Actinomycetes derive their antibiotic-producing capabilities from
biosynthetic gene clusters (BGCs)—groups of two or more genes
that, coupled together, encode a pathway for the production of a
specific metabolite, such as a product with the antibiotic properties
we need. The researchers first gathered sequences of antibiotic
BGCs from multiple actinomycete species. Then, they began slowly
building phylogenetic trees—diagrams mapping out evolutionary
relationships—of the BGCs, looking for a common ancestor. As
this effort advanced, they noticed previously untapped antibiotic
BGCs. This gave rise to another fundamental question: “Where do
these things come from?” Wright asked.
As the researchers continued to investigate, they found that some
of these newly discovered gene clusters encoded products that
blocked bacteria in entirely different ways than existing antibiotics.
These genes could then be purified and expressed—taken from the
bacteria in question and “shown [without other genes] in the way,”
www.yalescientific.org
Wright said—to create new antibiotics. The researchers had found
a way to predict possible antibiotics derived from actinomycetes.
Due to this mapping, they were able to specifically find two new
functioning glycopeptide antibiotics: complestatin and corbomycin.
Glycopeptide antibiotics combat bacteria by binding to peptidoglycan,
an important substance that makes up cell wall. Complestatin and
corbomycin have a novel mode of action. Unlike other antibiotics,
which prevent the bacterial cell wall from being built, complestatin
and corbomycin keep it from being broken down, a critical step
during bacterial reproduction. As a result, the targeted bacteria cannot
divide and increase their numbers, and their harmful properties are
blocked. In mouse models, complestatin and corbomycin diminished
infection while maintaining a low rate of resistance development, a
promising sign in this early stage of research.
Wright’s team faced several challenges on the way. For one, the mere
act of constructing phylogenetic trees presented difficulties, as they had
to comb through many genetic sequences to find the links proving their
evolutionary relationships. Similarly, challenges also arose in purifying
and expressing these genes once they were identified. The researchers
faced a game of trial and error, changing a range of conditions to
investigate their effects on the production of functional antibiotics by
the bacteria. It was “like fishing in a pond,” Wright said; in this case,
they were looking for a rather small fish in a very large pond.
Where will this new discovery head? “Our plan is to continue to
look for new antibiotics of this new family,” Wright said, noting that
his lab has already identified several potential leads. He also hopes to
extend the methods used in this paper to investigate another antibiotic
family. “We have not yet decided on which one, but we are very hopeful
that the method will uncover new compounds,” Wright said.
Antibiotic resistance, especially today, is a larger problem than
you might envision. A world where antibiotics no longer work is
a world where a small cut could have a prognosis as foreboding as
cancer. We have to start looking at more creative ways to solve this
growing crisis. Wright’s team has begun thinking outside the box
already, which begs the question: what can we expect next? ■
Culp, E.J., Waglechner, N., Wang, W. et al. (2020). Evolutionguided
discovery of antibiotics that inhibit peptidoglycan
remodelling. Nature 578, 582–587. https://doi.org/10.1038/
s41586-020-1990-9
September 2020 Yale Scientific Magazine 29
ALON MILLET (BR ’20)
BY KATHERINE DAI
IMAGE COURTESY OF ALON MILLET
No one can capture themselves in three
words—let alone someone who juggles
writing a master’s thesis, giving campus and
science tours, and peer tutoring for the introductory
biology sequence for the sixth semester. But when
asked about it, Alon Millet (BR ’20) rose to the
challenge: greedy for knowledge.
“What’s amazing about biology is that you can start at
the atomic level with biophysics and scale up to systems
biology, which is my field. Every step along the process,
you can see subtle connections as the scale changes,”
Millet said. Drawn to the unsolved mysteries in biology,
he satisfies his curiosity in the lab—probably even more
than in the classroom—a habit that started during his
freshman year of high school. Looking for a “nice side
thing to do,” he joined his high school’s cell biology lab
on a whim. After designing his first set of experiments,
however, Millet knew that research would not only
become a full-time commitment but also a lifelong one.
He dedicated every spare second to tackling a daunting
challenge: addressing the global food insecurity crisis.
His solution of a plant steroid—specifically, a seed
coating that increased the agricultural yield per plant—
earned him meetings with Barack Obama and Bill Nye,
a patent, and the opportunity to work with the U.S.
Agency for International Development.
After four years focused on research over
conventional high school experiences, Millet gained
the confidence and initiative to join a lab within a week
of his first year at Yale. He hit the ground running,
ready to go all-in on research through the BS/MS track
for Molecular, Cellular and Developmental Biology.
Halfway through his sophomore year, he co-authored
his first publication in Science Immunology.
But his end goal of research extends beyond
publications. He finds fulfillment from saying yes to
two questions: if he learned something new, and if
he satisfied his curiosity. The possibility of reaping
new knowledge, and perhaps the thought of a few
lines in the next edition of a biology textbook, keeps
him motivated. “If I’m on a question, maybe I can be
the person who cracks it. If I stopped, I would never
know the answer,” Millet said.
UNDERGRAD
PROFILE
The next big step for Millet is his master’s defense.
His thesis focuses on his research at the forefront of
cancer immunology, in Professor Sidi Chen’s lab. He
is working to understand how the metabolic state of
immune cells influences their response to tumors.
This work holds the potential to open undiscovered
therapeutic avenues, as insights about immune cell
metabolism can be translated into new approaches in
cancer immunotherapy.
In April, Millet will present his thesis to a
committee of illustrious scientists: Nobel laureate
James Rothman, Mark Mooseker, Tom Pollard,
and Sidi Chen. “It’s not every day you have a Nobel
laureate on your thesis committee. But beyond the
fact that they’re incredible scientists, they have been
unbelievably supportive whether I struggled with the
actual science or more personal issues,” Millet said. He
says this is a rare find: scientists who are doing worldclass
work and want to train the next generation of
scientists who could be doing that world-class work.
And he does not take this mentorship for granted.
Guided by the desire to follow in their footsteps and
invest in the development of others, Millet has the longterm
goal of becoming a professor. Next year, he will
attend the Tri-Institute PhD Program in Computational
Biology and Medicine. Meanwhile, he has taken up peer
tutoring for the introductory biology sequence as an
intermediate along the path of academic mentorship. “I
have given some great tours and have done some good
science in the lab. But out of all the things I’ve done on
campus, I think the one I’m proudest of is being a peer
tutor and how I have peer tutored,” Millet said. He finds
excitement in bonding with students over encountering
new information and reliving his experience of learning
it for the first time. At his many late-night review
sessions, his passion is palpable as he discusses biological
principles, experimental design, and his legendary mock
exam questions in front of over a hundred students.
For Millet, the connections he has formed with
students are more than channels to share knowledge.
He hopes that they have become avenues to transmit
his love for biology and greed for knowledge—his way
of paying the favor forward. ■
30 Yale Scientific Magazine September 2020 www.yalescientific.org
ALUMNI ALUMNI
PROFILE
From his humble upbringings in Taiwan to his
current position as Vice President of Science and
Technology in the Research Division at IBM, Tze-
Chiang Chen (PhD ’85) has established himself as one of
the most influential researchers in electrical engineering.
Born in 1951 to two teachers, Chen has maintained his
scientific curiosity since childhood. “I always wanted to
make something work by using mechanical, electrical, or
optical components,” Chen said. “That is what inspired
me to study science and technology.”
He used his childhood interests in science to pursue both
a bachelor’s (’74) and master’s degree (’76) in physics at
the National Cheng-Kung University in Taiwan, and paid
special attention to particle physics for his MS degree. After
serving in the army for two years, Chen then received a
scholarship from Yale to study physics. “Not only did Yale
have a very strong particle physics team, but it also had a
long history with China,” Chen said. “It was a dream to
come to Yale.” Chen arrived in 1978, receiving a master’s
degree a year later in Engineering and Applied Science and
pursuing the field until he graduated with a PhD in 1985.
Chen has worked on many impressive projects over
the years. While at Yale, around 1980, Chen was offered
an opportunity to work at PerkinElmer, a company
commissioned by NASA to help develop the Hubble
Space Telescope. Consequently, Chen drove between
New Haven and Wilton, Connecticut for nine months
as he balanced his studies and research work, ultimately
developing a process that allowed for the mirror coatings
used on the Hubble project. Thanks in part to his effective
contributions, the Hubble Space Telescope launched in
1990 and is still in operation today. For Chen, this first
work project still occupies a special place among all his
achievements. “I solved a problem and designed all the
thin-film coating parameters… It is perhaps the project I
am most proud of today,” he said.
Chen continued to solve problems and design parameters
when he joined the IBM team in late 1984 as a research
staff member. “IBM was known to be an innovation
company, and it provided a great opportunity for pioneering
semiconductor research,” he said. In fact, Chen’s primary
focus was on semiconductors, materials that partially
conduct current and are essential for many electrical
IMAGE COURTESY OF TZE-CHIANG CHEN
devices. His groundbreaking work during the eighties
on double-poly bipolar technology production laid the
foundation for semiconductor devices being implemented
in IBM mainframe computers used worldwide for scientific,
banking, and other commercial applications. Throughout
the nineties, Chen advanced dynamic random-access
memory (DRAM) density, allowing semiconductors to
store more data efficiently. And at the turn of the twentyfirst
century, Chen led a team of researchers in innovating
a dielectric material for complementary metal–oxide–
semiconductor (CMOS) chips, which store small amounts
of memory on computers. This work resulted in a global
push for silicon microelectronic use at many semiconductor
companies. Since joining IBM thirty-five years ago, Chen
remains an indispensable part of the company, overseeing
the science and technology strategy for five laboratories
across the world and continuing to monitor multinational
work on other engineering projects.
Chen has accumulated many accolades throughout
the years, receiving IBM’s highest honor when he was
appointed to be a fellow for the company in 1999. He later
became a fellow for the American Physical Society and the
IEEE. In 2011, Chen received the Institute of Electrical and
Electronics Engineers (IEEE) Ernest Weber award for his
high managerial achievement.
Underlying Chen’s ambitions to come to Yale was an
admiration for Yung Wing, a Yale graduate of 1854 who
was the first Chinese student to receive a diploma from
an American university. Given his illustrious career,
it comes as no surprise that Chen was named Asian
American Engineer of the Year in 2005.
“I want to encourage Yale undergraduate students
to engage more in science and technology, given Yale’s
enormous amount of resources,” Chen said, when asked
to offer some advice to current Yale students. He also
advised students to persist in the face of science’s many
challenges. “[View hurdles] as an opportunity rather
than a barrier… Through passion and perseverance, you
can achieve something that makes you happy,” he said.
Once a recruiter for IBM, Chen now returns
occasionally to Yale’s campus—when he’s here, he can
typically be found at the Becton Center. If you’re lucky,
perhaps one day you’ll meet him! ■
BY NADEAN ALNAJJAR
TZE-CHIANG CHEN (PHD ’85)
www.yalescientific.org
September 2020 Yale Scientific Magazine 31
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IMAGE COURTESY OF GIUSEPPE DONATIELLO