The paper-based tests could be integrated directly into facemasks and provide instant results at testing sites.
When Penn Health-Tech announced its Nemirovsky Engineering and Medicine Opportunity, or NEMO Prize, in February, the center’s researchers could only begin to imagine the impact the looming COVID-19 pandemic was about to unleash. But with the promise of $80,000 to support early-stage ideas at the intersection of engineering and medicine, the contest quickly sparked a winning innovation aimed at combating the crisis.
Judges from the University of Pennsylvania’s School of Engineering and Applied Sciences and Perelman School of Medicine awarded its first NEMO Prize to César de la Fuente, PhD, who proposed a paper-based COVID diagnostic system that could capture viral particles on a person’s breath, then give a result in a matter of seconds when taken to a testing site.
Similar tests for bacteria cost less than a dollar each to make. De la Fuente, a Presidential Assistant Professor in the departments of Psychiatry, Microbiology, and Bioengineering, is aiming to make COVID tests at a similar price point and with a smaller footprint so that they could be directly integrated into facemasks, providing further incentive for their regular use.
“Wearing a facemask is vital to containing the spread of COVID because, before you know you’re sick, they block your virus-carrying droplets so those droplets can’t infect others,” de la Fuente says. “What we’re proposing could eventually lead to a mask that can be infected by the virus and let you know that you’re infected, too.”
De la Fuente’s expertise is in synthetic biology and molecular-scale simulations of disease-causing viruses and bacteria. Having such fine-grained computational models of these microbes’ binding sites allow de la Fuente to test them against massive libraries of proteins, seeing which bind best. Other machine learning techniques can then further narrow down the minimum molecular structures responsible for binding, resulting in functional protein fragments that are easier to synthesize and manipulate.
The spike-shaped proteins that give coronaviruses their crown-like appearance and name bind to a human receptor known as ACE2. De la Fuente and his colleagues are now aiming to characterize the molecular elements and environmental factors that would allow for the most precise, reliable detection of the virus.
An interdisciplinary research team has found statistical evidence of women being under-cited in academic literature. They are now studying similar effects along racial lines.
By Izzy Lopez
Scientific papers are the backbone of a research community and the citation of those papers sparks conversation in a given field. This cycle of publication and citation leads to new knowledge, but what happens when implicit discrimination in a field leads to papers by minority scholars being cited less often than their counterparts? A new team of researchers has come together to ask this question and dig into the numbers of gender and racial bias in neuroscience.
The team members include physicist and neuroscientist Danielle Bassett, J. Peter Skirkanich Professor of Bioengineering at the University of Pennsylvania, with secondary appointments in the Departments of Neurology and Psychiatry in Penn’s Perelman School of Medicine, statistician Jordan Dworkin, then a graduate student in Penn Medicine’s Department of Biostatistics, Epidemiology and Bioinformatics, and ethicist Perry Zurn, an Assistant Professor of Philosophy at American University.
Their study on gender bias, which recently appeared in Nature Neuroscience, reports on the extent and drivers of gender imbalance in neuroscience reference lists. The team has also published a perspective paper in Neuron that makes practical recommendations for improving awareness of this issue and correcting for biases.
They are now working on a second study, led by Maxwell Bertolero, a postdoctoral researcher in Bassett’s lab, that considers the extent and drivers of racial imbalances in neuroscience reference lists.
Together, Bassett, Dworkin and Zurn are using their combined research strengths to uncover the under-citation of women or otherwise minority-led papers in neuroscience and to assess its significance. This research is fundamental in highlighting a true gap in representation in research paper citations, which can have detrimental effects for women and other minorities leading science. In addition, they provide actionable steps to address the problem and build a more equitable future.
Your research team is a distinctive one. How did you come together for a study about gender discrimination in neuroscience citations?
Jordan Dworkin: It was a fortunate coincidence. In the run-up to a big neuroscience conference, I started seeing discussions on Twitter about gender-based discrimination in neuroscience. There were stories being shared of women’s papers being overlooked and reviewers seeing reference lists that were almost entirely made up of men. It was illuminating, especially because some people in the discussion were hesitant to take those experiences at face value. This skepticism, and occasional combativeness, seemed to stem from the view that citations are an untouchable, scientific bastion where researchers’ decisions are fully objective. The tension between that view and scholars’ lived experiences encouraged me to explore the existing literature on this issue.
As it turns out, there is really strong literature on issues of diversity and citation in science. Some disciplines have done field-specific investigations, such as the foundational studies in political science, international relations, and economics, but there wasn’t yet any research in neuroscience. Since biomedical sciences often have different approaches to citation, it seemed that it would be worth doing a deeper neuroscience-specific investigation to give quantitative backing to the issue of gender bias in neuroscience research.
Danielle Bassett: When Jordan and I started working together on this project, I knew it was important. To do it right, we needed to present the information in a way that made it actionable, with clear recommendations about how each of us as scientists can help address the issue. We also needed to add someone to the team with expertise in gender theory and research ethics. We especially wanted to make sure we were discussing gender bias in a way that was informed by recent advances in gender studies. That’s when we brought Perry in.
Perry Zurn: I’m a philosopher by training, with a focus on ethics and politics. Citations are both an ethical and a political issue. Citations reflect whose questions and whose contributions are recognized as important in the scholarly conversation. As such, citations can either bring in marginalized voices, voices that have been historically excluded from a conversation, or they can simply replicate that exclusion. My own field of philosophy has just as much of a problem with gender and racial diversity as STEM fields, something Dani and I have been talking about for a long time. This work seemed like a natural point of collaboration.
Describe this study and what it means for promoting gender diversity in neuroscience.
Bassett: For years now, various scholars and activists in science have drawn attention to issues of gender and racial inequities in the field. Most of these conversations, however, have placed responsibility for change in the hands of people in power, such as journal editors, grant reviewers, department chairs, presidents of scientific societies, etc. But many of the imbalances people notice, whether in conversation with peers or through studies like ours, are perpetuated by researchers at all levels. Given that every research project is built on prior research, and therefore every paper has a reference list of citations, every researcher can make a difference. Who we choose to cite matters.
Dworkin: To understand the role of gender in citation practices, we looked at the authors and reference lists of articles published in five top neuroscience journals since 1995. We accounted for self-citations, and various potentially relevant characteristics of papers, and we found that women-led papers are under-cited relative to what would be expected if gender was not a consideration in citation behavior. Importantly, we also found that the under-citation of women-led papers is driven largely by the citation behavior of men-led teams. We also found that this trend is getting worse over time, because the field is getting more diverse while citation rates are generally staying the same.
For a very simple example, if there were 10 women and 90 men neuroscientists in 1980, then citing 10% women would be roughly proportional. But with a diversifying field, say there are now 200 women and 200 men neuroscientists and citations are still 10% women. Sure, the percentage of women cited didn’t go down, but that percentage is now vastly lower than the true percentage in the field. That’s a dramatic example, but it shows you that if we’re going to call for equality in scientific citation, the number of women-led papers on a given reference list should reflect, or even exceed, the number of available and relevant women-led papers in a field, and our work found that it does not.
Bassett: This under-citation of women scientists is a key issue because the gaps in the amount of engagement that women’s work receives could have detrimental downstream effects on conference invitations, grant and fellowship awards, tenure and promotion, inclusion in syllabi, and even student evaluations. As a result, understanding and eliminating gender bias in citation practices is vital for addressing gender imbalances in a field.
Why are citations important to gender representation in neuroscience?
Dworkin: Unlike hiring and grant funding, citations are something every researcher participates in. For example, as a graduate student I did not have any role on a faculty search committee, or any power in an academic society to decide on conference speakers, but I still have reference lists in all my papers. Citations are a unique area where all researchers play a direct role, where each person has a chance to reflect on their own practices and use those practices to create change in their field. Their ubiquity means that citations function as a conversation within a field, and their presence or absence can signal whose work is valued and whose is not. On a more concrete level, citations are often used as metrics for a variety of important, potentially career-defining, decisions.
Bassett: There are a lot of underrepresented scholars who have fantastic ideas and write really interesting papers but they’re not being acknowledged — and cited — in the way they deserve. And there are great role models for all the young women who are thinking about going into science, but unless the older women scientists are being cited, the younger ones will never see them. Without serious changes in the field, and a deep commitment to gender and racial diversity, many young women and minority scientists won’t stick with it, they won’t be hired, they won’t be promoted, and they won’t be put in the textbooks.
Zurn: Exactly. I think it’s important not only to think about who we’re citing as leading scientists, but also what sorts of people we’re representing as scientists at all. If you are looking at neuroscience as a field and you see predominantly white cisgender men in the research labs and the reference lists, then you begin to think that is what a neuroscientist looks like. But this homogeneity is neither representative of an increasingly diverse field like neuroscience, nor supportive of continuing efforts to diversify STEM in general. We need to expand what a scientist looks like and citations are one way to do that.
Danielle Bassett also has appointments in Penn Engineering’s Department of Electrical and Systems Engineering and Penn Arts & Sciences Department of Physics and Astronomy.
Jordan Dworkin is now an Assistant Professor of Clinical Biostatistics in the Department of Psychiatry at Columbia University.
Kristin Linn, Assistant Professor of Biostatics, Russell Shinohara, Associate Professor of Biostatistics, and Erin Teich, a postdoctoral researcher in Bassett’s lab, also contributed to the study published in Nature Neuroscience. It was supported by the National Institute of Neurological Disorders and Stroke through grants R01 NS085211 and R01 NS060910, the John D. and Catherine T. MacArthur Foundation, the Alfred P. Sloan Foundation, and the National Science Foundation through CAREER Award PHY-1554488.
In May, Lyle Ungar, Professor of Computer and Information Science and Angela Duckworth, Rosa Lee and Egbert Chang Professor in Penn Arts & Sciences and the Wharton School, contributed to a New York Times op-ed on how to slow the COVID-19 pandemic through a culture of mask-wearing.
As infections continue to rise, Ungar and Duckworth are following up with another op-ed. Writing in the Philadelphia Inquirer, they outline the need to rapidly ramp-up the city and state’s contact tracing capacity:
New research finds that works of literature, musical pieces, and social networks have a similar underlying structure that allows them to share large amounts of information efficiently.
By Erica K. Brockmeier
To an English scholar or avid reader, the Shakespeare Canon represents some of the greatest literary works of the English language. To a network scientist, Shakespeare’s 37 plays and the 884,421 words they contain also represent a massively complex communication network. Network scientists, who employ math, physics, and computer science to study vast and interconnected systems, are tasked with using statistically rigorous approaches to understand how complex networks, like all of Shakespeare, convey information to the human brain.
New research published in Nature Physics uses tools from network science to explain how complex communication networks can efficiently convey large amounts of information to the human brain. Conducted by postdoc Christopher Lynn, graduate students Ari Kahn and Lia Papadopoulos, and professor Danielle S. Bassett, the study found that different types of networks, including those found in works of literature, musical pieces, and social connections, have a similar underlying structure that allows them to share information rapidly and efficiently.
Technically speaking, a network is simply a statistical and graphical representation of connections, known as edges, between different endpoints, called nodes. In pieces of literature, for example, a node can be a word, and an edge can connect words when they appear next to each other (“my” — “kingdom” — “for” — “a” — “horse”) or when they convey similar ideas or concepts (“yellow” — “orange” — “red”).
The advantage of using network science to study things like languages, says Lynn, is that once relationships are defined on a small scale, researchers can use those connections to make inferences about a network’s structure on a much larger scale. “Once you define the nodes and edges, you can zoom out and start to ask about what the structure of this whole object looks like and why it has that specific structure,” says Lynn.
Building on the group’s recent study that models how the brain processes complex information, the researchers developed a new analytical framework for determining how much information a network conveys and how efficient it is in conveying that information. “In order to calculate the efficiency of the communication, you need a model of how humans receive the information,” he says.
“Beth Winkelstein has become one of our most essential leaders of teaching, learning, and student life,” said Pritchett, “since she began her tenure as vice provost for education five years ago. Her insight and energy enhance every part of our campus. She leads both undergraduate and graduate education, collaborating with deans, faculty leaders, and the Office of the Vice Provost for University Life, as well as the Council of Undergraduate Deans, Council of Graduate Deans, Graduate Council of the Faculties, and Council of Professional Master’s Degree Deans.
“As deputy provost, she will continue this invaluable work while working closely with me to better integrate and expand our educational initiatives, especially by incorporating new technologies, new ways of teaching, and additional supports for faculty and students that advance our core priorities of innovation, impact, and inclusion,” Pritchett said. “As we enter this new and challenging phase of Penn history, Beth is the perfect person to help us chart the landscape ahead.”
Drawing on her experience as a former Penn undergraduate, Winkelstein has been a dynamic leader of initiatives to enhance undergraduate student life, especially the new Penn First Plus program, which provides targeted support for first-generation and/or low-income students, and the dedicated Second-Year Experience, which offers enhanced programs for second-year students to accompany Penn’s new second-year housing requirement. She has at the same time been a vital advocate for graduate and professional students, overseeing the Graduate Student Center and Family Center, while advancing a series of initiatives to improve every aspect of support for students’ academic progress, professional advancement, and work-life balance. Her leadership spans such key areas as College Houses and Academic Services, New Student Orientation, the Center for Undergraduate Research and Fellowships, and the Office of Student Conduct. And that leadership has been especially critical for the Online Learning Initiative and the Center for Teaching and Learning, in these recent months when that work has become central to Penn’s educational efforts.
Winkelstein’s leadership is based in her deep knowledge of and appreciation for the University, as well as her own scholarly and research distinction. She has taught in the Bioengineering Department in the School of Engineering and Applied Science since 2002, becoming in that time one of the world’s leading innovators in research on new treatments for spine and other joint injuries. Appointed two years ago as the Eduardo D. Glandt President’s Distinguished Professor, she continues to lead her pioneering Spine Pain Research Lab, mentor students and postdocs, and serve as co-editor of the Journal of Biomechanical Engineering. Among her many professional honors, she is a Fellow of the Biomedical Engineering Society and the American Society of Mechanical Engineering and was elected to the American Institute for Medical and Biological Engineering and the World Council of Biomechanics.
Winkelstein earned a Ph.D. in bioengineering from Duke University and a B.S.E. cum laude in bioengineering from Penn as a Benjamin Franklin Scholar.
As scientists continue to battle the novel coronavirus, public health officials maintain that wearing a face mask is a powerful way to curb the spread of the virus and keep communities safe. However, America has struggled to adopt this change, as compared to other countries that have made wearing a face mask an unremarkable aspect of their culture.
In an opinion piece for the New York Times, Lyle Ungar, Professor of Computer and Information Science, Angela Duckworth, Rosa Lee and Egbert Chang Professor in Penn Arts & Sciences and the Wharton School, and Ezekiel J. Emanuel, Professor of Medical Ethics and Health Policy in Penn’s Perelman School of Medicine, propose a new approach to increase consistent face mask use among Americans: make wearing a mask “easy,” “understood,” and “expected.”
In their article, Ungar, Duckworth, and Emanuel make reference to communities that provided face masks free of charge for residents and note the decrease in infection in these areas. In addition, they point out how uncertainty about the necessity of face masks in the U.S. has led to public confusion which inhibits trust and use of masks. Finally, the three researchers push for a shift in social norms to embrace wearing a face mask as standard in America for the near future.
In a recent piece profiling top technologies to watch in 2020, Cremins spoke to Nature about which technological trends she saw as being important for the year to come. In the panel, which highlighted perspectives from a panel of researchers across several fields, Cremins discussed the increasing relevance of innovations that would allow researchers to study the way that folding patterns within the human genome can influence how genes are expressed in healthy individuals and misregulated in human disease.
One such innovation is actually employed by the Cremins Lab: light-activated dynamic looping (LADL). This technique uses both CRISPR/Cas9 and optogenetics to induce folding patterns into the genome on demand, using light as a trigger. In doing so, Cremins and her fellow researchers can more efficiently study the patterns of the human genome, and what effects certain folding patterns can have on the gene expression state of the cell.
Now, with her new promotion, Cremins can continue advancing her research in understanding the genetic and epigenetic mechanisms that regulate neural connections during brain development, with a focus on how that understanding can eventually lead to better treatments of neurological disease. Beyond the lab, she’ll now lead a new Spatial Epigenetics program, bringing together scientists across Penn’s campus to understand how the spatial connections between biomolecules influence biological behavior. She will also continue teaching her hallmark course for Penn Bioengineering undergraduate students, Biological Data Science, and her more advanced graduate-level course in epigenomics. Congratulations, Dr. Cremins!
We wanted you to know that we in BE fully stand behind and reiterate the message from President Gutmann in full support of our Black students, postdocs, staff, colleagues, and friends.
As noted by President Gutmann, we all are feeling outrage, anger, grief, and myriad other emotions. We are at a loss to comprehend and to process the magnitude and implications of the brutality, oppression, and injustice that have come to light once again following the horrific event of George Floyd’s murder.
Several students and colleagues have reached out expressing their desires to contribute actively to effect a positive and progressive change. Our President Gutmann and Provost Pritchett have summarized some of the Penn initiatives towards our local communities in their message linked above. Numerous others are proactively contributing large and small. While we may not agree on many things, we can all agree that a lot remains to be done, and it will take time and sustained effort and commitment on our part. We are committed to the cause: to effect continual and progressive change for nurturing equality and cultural sensitivity as we build a diverse academic ecosystem, and this includes BE, Penn, and our surrounding community. It is our commitment to our Black friends and colleagues.
We take this opportunity to share this article sent by Denise Lay: Answering the Question, ‘What Can I Do?’ and this document compiled by BE Ph.D. student Lasya Sreepada created to share resources and opportunities for members of the University of Pennsylvania community to help their local communities.
Also, here are a few resources to help cope:
Racial Justice and Equity (from Bucketlisters): A listing of resources, organizations and actions, including Philadelphia specific organizations.
Researchers develop a new model for how the brain processes complex information: by striking a balance between accuracy and simplicity while making mistakes along the way.
By Erica K. Brockmeier
The human brain is a highly advanced information processor composed of more than 86 billion neurons. Humans are adept at recognizing patterns from complex networks, such as languages, without any formal instruction. Previously, cognitive scientists tried to explain this ability by depicting the brain as a highly optimized computer, but there is now discussion among neuroscientists that this model might not accurately reflect how the brain works.
Now, Penn researchers have developed a different model for how the brain interprets patterns from complex networks. Published in Nature Communications, this new model shows that the ability to detect patterns stems in part from the brain’s goal to represent things in the simplest way possible. Their model depicts the brain as constantly balancing accuracy with simplicity when making decisions. The work was conducted by physics Ph.D. student Christopher Lynn, neuroscience Ph.D. student Ari Kahn, and Danielle Bassett, J. Peter Skirkanich Professor in the departments of Bioengineering and Electrical and Systems Engineering.
This new model is built upon the idea that people make mistakes while trying to make sense of patterns, and these errors are essential to get a glimpse of the bigger picture. “If you look at a pointillist painting up close, you can correctly identify every dot. If you step back 20 feet, the details get fuzzy, but you’ll gain a better sense of the overall structure,” says Lynn.
To test their hypothesis, the researchers ran a set of experiments similar to a previous study by Kahn. That study found that when participants were shown repeating elements in a sequence, such as A-B-C-B, etc., they were automatically sensitive to certain patterns without being explicitly aware that the patterns existed. “If you experience a sequence of information, such as listening to speech, you can pick up on certain statistics between elements without being aware of what those statistics are,” says Kahn.
To understand how the brain automatically understands such complex associations within sequences, 360 study participants were shown a computer screen with five gray squares corresponding to five keys on a keyboard. As two of the five squares changed from gray to red, the participants had to strike the computer keys that corresponded to the changing squares. For the participants, the pattern of color-changing squares was random, but the sequences were actually generated using two kinds of networks.
The researchers found that the structure of the network impacted how quickly the participants could respond to the stimuli, an indication of their expectations of the underlying patterns. Responses were quicker when participants were shown sequences that were generated using a modular network compared to sequences coming from a lattice network.
KIChE is an organization that aims “to promote constructive and mutually beneficial interactions among Korean Chemical Engineers in the U.S. and facilitate international collaboration between engineers in the U.S. and Korea.”