Danielle Bassett, J. Peter Skirkanich Professor in the departments of Bioengineering and Electrical and Systems Engineering, has been called the “doyenne of network neuroscience.” The burgeoning field applies insights from the field of network science, which studies how the structure of networks relate to their performance, to the billions of neuronal connections that make up the brain.
Much of Basset’s research draws on mathematical and engineering principles to better understand how mental traits arise, but also applies them more broadly to other challenges in neuroscience.
The researchers used machine learning techniques to create a new classification system for neurodegenerative diseases, one which may redraw the boundaries between them and help explain clinical differences in patients who received the same diagnoses.
BioWorld’s Anette Breindl spoke with Bassett about the team’s findings.
Now, investigators have developed a new approach to classifying neurodegenerative disorders that used the overall patterns of protein aggregation, rather than specific proteins, to define six clusters of patients that crossed traditional diagnostic categories.
“We find that perhaps the way that clinicians have been diagnosing these disorders… is not necessarily the way these disorders work,” Danielle Bassett told BioWorld. “The way we’ve been trying to carve nature at joints is not the way that nature has joints. The joints are elsewhere.”
Continue reading Breindl’s article, “For neurodegeneration, a different way to slice the pie,” at BioWorld.
In a Q&A, Bioengineering doctoral candidate Ana P. Peredo explains how the idea of “regeneration” motivated her to join WIVA, Wharton Social Impact’s impact investing program.
Why would you — a bioengineering Ph.D. student — seek to join WIVA?
“As a high school student, I was motivated to study bioengineering because of its potential to generate impact through technical innovation. To me, bioengineering was a way to apply engineering principles to create medical technology in the hopes of devising solutions for global health concerns.
Though I have gained significant understanding of the current pressing healthcare needs, I felt that I was missing a key understanding of how investors think about social impact. To better understand how to apply my science background to the impact space, I joined WIVA. I also wanted to venture outside of healthcare and learn about other important social impact sectors such as education, energy, and environment, all of which WIVA explores in its deal-sourcing process.”
What have you learned through WIVA that you have not been exposed to before?
“I learned how to assess early-stage startups for their impact and return-on-investment potential, as well as how to rigorously analyze company financials and projections.
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.
“Our Bio-MakerSpace” takes viewers on a tour inside BE’s one-of-a-kind educational laboratories.
Produced primarily on smart phones and with equipment borrowed from the Penn Libraries, and software provided by Computing and Educational Technology Services, the videos were made by rising Bioengineering junior Nicole Wojnowski (BAS ‘22). Nicole works on staff as a student employee of the BE Labs and as a student researcher in the Gottardi Lab at the Children’s Hospital of Philadelphia (CHOP), helmed by Assistant Professor of Pediatrics Riccardo Gottardi.
Sevile Mannickarottu, Director of the Educational Labs in Bioengineering, says that the philosophy of the Bio-MakerSpace “encourages a free flow of ideas, creativity, and entrepreneurship between Bioengineering students and students throughout Penn. We are the only open Bio-MakerSpace with biological, chemical, electrical, materials, and mechanical testing and fabrication facilities, all in one place, anywhere.”
Bioengineering doctoral student Dayo Adewole co-founded the company Instahub, which also took home a PIP award in 2019. Dayo also graduated from the BE undergraduate program in 2014. In this video, he discusses the helpfulness and expertise of the BE Labs staff.
Senior Associate Dean for Penn Engineering and Solomon R. Pollack Professor in Bioengineering David Meaney discusses how the Bio-MakerSpace is the only educational lab on campus to provide “all of the components that one would need to make the kinds of systems that bioengineers make.”
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
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.
Once hailed as medical miracles, antibiotics are losing their effectiveness due to the rapid increase of bacterial immunity.
Researchers are scrambling to keep up with evolution, and they are currently exploring how machine learning can be applied to microbiology to develop more effective treatments.
In the past, researchers have studied bacteria behavior and used their findings to work against the natural patterns of bacterial life. In the 1980s, computer-assisted screening methods helped researchers in their efforts but few developments surfaced from their work. It seemed that there were no new antibiotics to be found using traditional methods, and pharmaceutical companies stepped away from funding antibiotic development in favor of more profitable drugs used to treat chronic conditions. But a new field of research shows a way forward, thanks to the massive advances in computing that have occurred over the intervening decades.
Among the pioneering researchers in this field is César de La Fuente, Presidential Assistant Professor in Psychiatry, Microbiology and Bioengineering. De La Fuente is accelerating the discovery of new antibiotics with his Drug Repurposing Hub, a library of more than 6,000 compounds that is using machine learning algorithms to seek out possible solutions for human disease. With his compound library, de La Fuente is able to examine drugs already approved by the FDA and hunt for new, more effective applications.
In addition to this work, de La Fuente and his colleagues are interested in using machine learning to innovate drug design itself. His lab uses a machine learning platform to generate new molecules in silico and perform experiments on them. Once the results of the experiments come in, they are fed back into the computer so the machine learning platform can continuously learn and improve its findings from the data.
In a recent interview with Katherine Harmon Courage in Quanta Magazine, de La Fuente said:
“The hypothesis is that nature has run out of inspiration in terms of providing us with new antibiotics. That’s why we think that machines … could diversify natural molecules to convert them to synthetic versions that would be much more effective.”
Featured on a recent episode of “Choosing to be Curious” on WERA 96.7 Radio Arlington, Bassett discussed her work in studying curiosity and the potential neural mechanisms behind it. In her work, Bassett strives to re-conceptualize curiosity itself, defining it as not just seeking new bits information, but striving to understand the path through which those bits are connected.
Bassett is a pioneering researcher in the field of network science and how its tools can be applied to understand the brain. Now, Bassett and her research team are using the tools of network science and complex systems theory to uncover what common styles of curiosity people share and how individual styles differ. In addition, the team is exploring if there are canonical types of curiosity among humans or if each person’s curiosity architecture is unique.
This isn’t the first time Bassett has combined the tools of disparate fields to pursue her research. For as long as she can remember, Bassett has been insatiably curious and, while she was homeschooled as a child, she often wandered from one subject to the next and let her own interest guide her path. For Bassett, studying curiosity with the tools of physical, biology, and engineering is a natural step in her research journey.
In her interview with host Lynn Borton, Bassett says:
“What took me to curiosity is the observation that there’s a problem in defining the ways in which we search for knowledge. And that perhaps the understanding of curiosity could be benefitted by a scientific and mathematical approach. And that maybe the tools and conceptions that we have in mathematics and physics and other areas of science are useful for understanding curiosity. Which most people would consider to be more in the world of the humanities than the sciences….“Part of what I’m hoping to do is to illustrate that there are connections between disciplines that seem completely separate. Sometimes some of the best ideas in science are inspired not by a scientific result but by something else.”
While genetics and biochemistry research has dominated the conversation about how human bodies are formed, new research — with an old twist — is proposing that there is another star in the show of human development: mechanical forces.
At the turn of the twentieth century, medical research relied on simple mechanics to explain scientific phenomena, including how human cells morph into shape from embryo to newborn and beyond. As better chemistry techniques and DNA research burst onto the scene, however, the idea that cells could be affected by physical forces took a back seat. Now researchers are referring back to this vintage idea and bringing it into the 21st century.
Dennis Discher, Robert D. Bent Professor in the Departments of Chemical and Biomolecular Engineering, Bioengineering and Mechanical Engineering and Applied Mechanics, was featured in a recent article in Knowable Magazine for his research on the human heart and how mechanical forces exerted on heart cells give the vital organ its necessary stiffness during development.
What originally drew me to this field was a “Women in Engineering Day” I attended at a local college while in high school. I had the opportunity to hear incredible women speak about their research regarding biomaterials and tissue engineering. This event showed me the impact this field can have on the world. This drove me to pursue an undergraduate degree in Biomedical Engineering, which only strengthened my passion. As I furthered my studies and began working full-time at a biotechnology company, I learned more about bioengineering. With encouragement from my coworkers and family, I decided to pursue my Master’s in Bioengineering and am delighted to have the opportunity to study at Penn.
What kind of research do you conduct, and what do you hope to focus on for your thesis?
I am actually a part-time student, who works full-time at a drug packaging and medical device company out in Exton, PA. Though I am not doing research on campus, my coursework has tied into previous research projects I have participated in at my job. My latest project entailed understanding different material properties used in container closure systems for mAb-based biologics and how they interact. This work was done to support an understanding of how to pick appropriate vial/syringe systems for various drug products in development.
What’s your favorite thing to do on Penn’s campus or in Philly?
My favorite thing to do is trying all the new restaurants and incredible foods this city has to offer. I think Philadelphia is so unique and has such rich cultural influences. With so many different neighborhoods and restaurant options you really can’t go wrong.
What did you study for your undergraduate degree, how does it pair with the work you’re doing now, and what advice would you give to your undergraduate self?
My undergraduate degree was in Biomedical Engineering. It has supported my graduate coursework very well and has given me a great opportunity to dive deeper into certain parts of my studies.
My advice to my younger self would be to take your time! It took me a little while to evaluate different graduate programs and choose which was right for me. Though it took some time, I ultimately decided what was best for me and couldn’t be happier with my choices.
What are you thinking about doing after graduate school?
Currently, I work full-time as an Associate Packaging Engineer at West Pharmaceutical Services in Exton, PA. I hope to take my degree to further my career and to help support my future aspirations at this company.
Growing up in Sri Lanka and being surrounded by relatives who were doctors, I have been fascinated by both modern and traditional medicine. However, during physician shadowing in high school, I came to the realization that I was far more fascinated with the technology doctors use rather than practicing medicine. Therefore, I made the decision to turn down studying medicine in the U.K. and come to Penn to study Bioengineering in the hopes of being more hands-on with medical technology.
Have you done research with a professor on campus? What did you like, and what didn’t you like about it?
I currently work in the Interventional Radiology Lab at the Hospital of the University of Pennsylvania (HUP) under Assistant Professor of Radiology Chamith Rajapakse. The best thing about research here is that I get to be hands-on with some of the most cutting edge technology in the world and help pioneer medical diagnostic techniques that aren’t traditionally being used anywhere else. The only downside is that the learning curve can be a little too steep.
What have been some of your favorite courses and/or projects in Bioengineering so far?
Without a doubt, my favorite BE class has to be BE 309 (Bioengineering Modeling, Analysis and Design Laboratory I) and especially the Computer-Cockroach Interface we have to develop for this lab.
What advice would you give to your freshman self?
There are way too many things happening at a given time at Penn. Take it easy and plan it out so you can do everything you want to! It’s totally possible. Who says you can’t work hard and play hard?!
What do you hope to pursue after obtaining your undergraduate degree?
My hope is to head my own health-tech startup and create technologies that will aid developing countries, starting out with my humble island of Sri Lanka first.