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:
Guidelines from health officials suggest Pennsylvania needs about 4,000 contact tracers, including 2,000 for the Philadelphia metro area. Our state has been operating with fewer than 200.
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.
Examples of statistical network analysis of characters in two of Shakespeare’s tragedies. Two characters are connected by a line, or edge, if they appear in the same scene. The size of the circles that represent these characters, called nodes, indicate how many other characters one is connected to. The network’s density relates to how complete the graph is, with 100% density meaning that it has all of the characters are connected. (Image: Martin Grandjean)
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.
The Chan Zuckerberg Initiative (CZI) has announced $14 million in funding to support 29 interdisciplinary teams who are investigating the role of inflammation in disease. Among these recipients is Dan Huh, Associate Professor in Bioengineering, whose placenta-on-a-chip research will “explore how maternal and fetal cells respond to specific inflammatory signals and analyze the network of placental cells and immune cells that impact pregnancy outcomes in chronic inflammatory diseases.”
Kellie Ann Jurado, Presidential Assistant Professor in the Perelman School of Medicine’s Department of Microbiology, will lead the research team. She and Huh will collaborate with Monica Mainigi, William Shippen, Jr. Assistant Professor of Human Reproduction in Penn Medicine.
A version of the Huh Lab’s placenta-on-a-chip from 2018
Huh’s placenta-on-a-chip consists of a small block of silicone containing microfluidic channels separated by a membrane of human cells. Variations in designs and cell types allow researchers to study how different molecules cross that barrier, allowing for experiments that would be otherwise impossible or unethical. For example, Huh and his group previously used a placenta-on-a-chip designed to model the placental barrier to research the effect of maternally-administered medications on the fetal bloodstream.
In this new study, Huh, Jurando and Mainigi were motivated by even more fundamental questions of pregnancy.
“It has been known for quite some time that women with chronic inflammatory diseases are at increased risk of developing various complications during pregnancy,” Huh says. “Despite accumulating clinical evidence, we understand little about how inflammation contributes to adverse pregnancy outcomes.”
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.
Lyle Ungar, Ph.D.
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.
Some of Ungar’s recent research is also focused on the pandemic, including a “COVID Twitter map,” created with colleagues at the World Well-Being Project and Penn Medicine’s Center for Digital Health. Their map helps show, in real time, how people across the country perceive the virus and how it is affecting their mental health.
Read more about Ungar, Duckworth, and Emanuel’s strategy for normalizing face masks in their opinion piece for the New York Times.
Jennifer Phillips-Cremins, Ph.D., was recently promoted to the tenured position of Associate Professor in Penn’s Department of Bioengineering. Cremins, leads a lab on campus in 3D Epigenomes and Systems Neurobiology.
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!
Though BE 472 was able to quickly pivot to an entirely online curriculum, some in-person aspects of the course were unfortunately lost. Pictured: BE 472’s Spring 2019 MedTech panel discussion with industry leaders Katherine High, MD (President of Spark Therapeutics), Lucas Rodriguez, PhD (CEO of CerSci Therapeutics), and Penn BE alumnus Brianna Wronko (CEO of Group K Diagnostics) (credit: Lauren McLeod BE 2020).
by Sophie Burkholder
Given the closing of schools in response to the coronavirus pandemic, professors teaching lab-based courses were forced to make some changes. One such course, the Department of Bioengineering’s Medical Device Development (BE 472) taught by Matthew R. Maltese, Ph.D., usually requires students to develop a medical device and learn how to lead a startup venture for it. Over the semester, students design prototypes for unmet needs in the medical device community, and then go on to learn about business-related aspects of the project, like fundraising, regulations, teamwork, and leadership. Maltese often encourages junior engineering students to take the course, in the hopes that their projects might become launchpads for their senior design projects the following year.
But with the pandemic’s interruptions to education restricting access to the lab, or even to some of the schematics for their earlier designs, Maltese’s Spring 2020 students had to re-focus on the business side of their projects.
Fortunately, the shift to online learning came late enough in the semester that most students had already come up with solid project ideas. Maltese then shifted gears to the less hands-on parts of the course. “There’s lots of elements to this course that are not focused on putting hands on hardware,” he says. “They’re focused on distilling and disseminating information about your endeavor to people that are interested.”
While some of those more hands-off assignments originally had some face-to-face aspects, like the final pitch competition, they’re also easy to transition to an online format. Maltese had students record videos of their pitches, which he notes is perhaps more akin to what they might have to do for external pitch competitions. And even though students couldn’t make their physical prototypes, Maltese says that they were all able to make virtual prototypes through CAD or other modeling software.
In his opinion, this renewed focus on out-of-lab prototype models might be a good thing for real-world experience. Investors and stakeholders often want the full picture of a device or startup before they even have to start working with physical material, for the sake of cost efficiency.
Students had already been working on their projects for a couple of months before the pandemic started to affect classes, so most of them stuck to their original ideas instead of adapting them to meet the needs of the current medical crisis. “Next year, I think we’re going to focus the class on COVID-19 ideas though,” says Maltese.
In fact, Medical Device Development will likely be one of many Penn Bioengineering courses that adapts its curriculum to the challenges the pandemic presented. “As a medical device community, a pharmaceutical community, a healthcare community, we were not ready for this,” Maltese notes, “but history teaches us that some of our greatest innovations emerge from our greatest trials.” He is excited for the future.
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.
Mostly and immediately, we write this note to reiterate that we stand with and support our Black students, postdocs, staff, colleagues, and friends in this difficult period.
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
New research finds that the human brain detects patterns in complex networks by striking a balance between simplicity and complexity, much like how a pointillist painting can be viewed up close to see the finer details or from a distance to see its overall structure.
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.
In a Q&A, researcher Lyle Ungar discusses why counties that frequently use words like ‘love’ aren’t necessarily happier, plus how techniques from this work led to a real-time COVID-19 wellness map.
By Michele W. Berger
Lyle Ungar, Ph.D. (Photo: Eric Sucar)
People in different areas across the United States reacted differently to the threat of COVID-19. Some imposed strict restrictions, closing down most businesses deemed nonessential; others remained partially open.
Such regional distinctions are relatively easy to quantify, with their effects generally understandable through the lens of economic health. What’s harder to grasp is the emotional satisfaction and happiness specific to each place, a notion Penn’s World Well-Being Project has been working on for more than five years.
In 2017, the group published the WWBP Map, a free, interactive tool that displays characteristics of well-being by county based on Census data and billions of tweets. Recently, WWBP partnered with Penn Medicine’s Center for Digital Health to create a COVID map, which reveals in real time how people across the country perceive COVID-19 and how it’s affecting their mental health.
That map falls squarely in line with a paper published this week in the Proceedings of the National Academy of Sciences by computer scientist Lyle Ungar, one of the principal investigators of the World Well-Being Project, and colleagues from Stanford University, Stony Brook University, the National University of Singapore, and the University of Melbourne.
By analyzing 1.5 billion tweets and controlling for common words like “love” or “good,” which frequently get used to connote a missing aspect of someone’s life rather than a part that’s fulfilled, the researchers found they could discern subjective well-being at the county level. “We have a long history of collecting people’s language and asking people who are happier or sadder what words they use on Facebook and on Twitter,” Ungar says. “Those are mostly individual-level models. Here, we’re looking at community-level models.”
In a conversation with Penn Today, Ungar describes the latest work, plus how it’s useful in the time of COVID-19 and social distancing.
