In the quest to develop life-like materials to replace and repair human body parts, scientists face a formidable challenge: Real tissues are often both strong and stretchable and vary in shape and size.
A CU Boulder-led team, in collaboration with researchers at the University of Pennsylvania, has taken a critical step toward cracking that code. They’ve developed a new way to 3D print material that is at once elastic enough to withstand a heart’s persistent beating, tough enough to endure the crushing load placed on joints, and easily shapeable to fit a patient’s unique defects.
Their breakthrough, described in the Aug. 2 edition of the journal Science, helps pave the way toward a new generation of biomaterials, from internal bandages that deliver drugs directly to the heart to cartilage patches and needle-free sutures.
“This is a simple 3D processing method that people could ultimately use in their own academic labs as well as in industry to improve the mechanical properties of materials for a wide variety of applications,” says first author Abhishek Dhand, a researcher in the Burdick Lab and doctoral candidate in the Department of Bioengineering at the University of Pennsylvania. “It solves a big problem for 3D printing.”
Jason Burdick is Bowman Endowed Professor in Chemical and Biological Engineering at the University of Colorado Boulder and Adjunct Professor in Bioengineering at Penn Engineering.
Even today, centuries after he lived, Johann Sebastian Bach remains one of the world’s most popular composers. On Spotify, close to seven million people stream his music per month, and his listener count is higher than that of Mozart and even Beethoven. The Prélude to his Cello Suite No. 1 in G Major has been listened to hundreds of millions of times.
What makes Bach’s music so enduring? Music critics might point to his innovative harmonies, complex use of counterpoint and symmetrical compositions. Represent Bach’s music as a network, however, where each node stands for one musical note, and each edge the transition from one note to another, and a wholly different picture emerges.
In a recent paper in Physical Review Research, Dani S. Bassett, J. Peter Skirkanich Professor in Bioengineering and in Electrical and Systems Engineering within the School of Engineering and Applied Science, in Physics & Astronomy within the School of Arts & Sciences, and in Neurology and Psychiatry within the Perelman School of Medicine, and Suman Kulkarni, a doctoral student in Physics & Astronomy, applied network theory to Bach’s entire oeuvre.
The paper sheds new light on the unique qualities of Bach’s music and demonstrates the potential for analyzing music through the lens of networks. Such analysis could yield benefits for music therapists, musicians, composers and music producers, by giving them unprecedented quantitative insight into the structure of different musical compositions.
“This paper provides a starting point for how one can boil down these complexities in music and start with a simple representation to dig into how these pieces are structured,” says Kulkarni, the paper’s lead author. “We applied this framework to a dozen types of Bach’s compositions and were able to observe quantitative differences in how they were structured.”
The effectiveness of CAR T cell therapy against a variety of cancers, including solid tumors, could be boosted greatly by using CRISPR-Cas9 technology to knock out the gene for CD5, a protein found on the surface of T cells, according to a preclinical study from investigators at the University of Pennsylvania’s Perelman School of Medicine and Abramson Cancer Center.
CAR T cells are T cells that have been engineered to attack specific targets found on cancer cells. They have had remarkable results in some patients with blood cancers. But they have not performed well against other cancers including solid-tumor cancers, such as pancreatic cancer, prostate cancer, and melanoma. Researchers have been searching for techniques to boost the effectiveness of CAR T cell therapy.
The study, published today in Science Immunology, suggests that knocking out CD5 could be a prime technique. Illuminating the protein’s previously murky role, the researchers found that it works as a powerful immune checkpoint, reining in T cell effectiveness. Removing it, they showed, dramatically enhanced CAR T cell anticancer activity in a variety of preclinical cancer models.
“We’ve discovered in preclinical models that CD5 deletion greatly enhances the function of CAR T cells against multiple cancers,” said senior author Marco Ruella, MD, an assistant professor of Hematology-Oncology, researcher with the Center for Cellular Immunotherapies and the scientific director of Penn Medicine’s Lymphoma Program. “The striking effects we observed across preclinical models suggest that CD5 knockout could be a general strategy for enhancing CAR T cell function.”
The study’s first author is Ruchi Patel, PhD, a recent graduate student from the Ruella Laboratory.
Sherry (Xue) Gao, Presidential Penn Compact Associate Professor in Chemical and Biomolecular Engineering (CBE), always knew she had a future in the lab. “I grew up in China, and when I was little, maybe six or seven,” she recalls, “my teacher asked me, ‘What do you want to be when you grow up?’ I said, ‘I want to be a scientist!’”
Neither of her parents had studied beyond high school; when Gao finished her training as a chemical engineer, she became the first person in her family to graduate from college. “One of my greatest motivations is to help first-generation college students,” Gao says.
Now, as the newest faculty member in CBE, Gao is prepared to do just that: support the next generation of chemical engineers, while also conducting groundbreaking research in the development of small molecules to edit genes, pushing the boundaries of precision medicine.
The Presidential Penn Compact Professorships were created by former Penn President Amy Gutmann specifically to recruit and support faculty like Gao: transformative leaders working at the intersection of multiple fields with “a yen for collaboration,” as Gutmann told the Penn Gazette in 2021.
Gao joins Penn Engineering from Rice University, where she collected numerous accolades, including the 2024 BMES-CMBE Rising Star Award, a 2022 NSF CAREER Award, the 2022 Outstanding Young Faculty at Rice School of Engineering Award and the 2020 NIH MIRA R35 Award.
As a member of the Center for Precision Engineering for Health (CPE4H), Gao will partner with colleagues from across the School to develop technologies that bridge disciplines, all in the interest of advancing health care. “We are very excited to have Sherry as a new member of the Center,” says Daniel Hammer, Alfred G. and Meta A. Ennis Professor and inaugural Director of CPE4H. “Gene editing is an important new tool that can precisely alter cell behavior by deleting or redirecting cell pathways, as well as enhancing and suppressing gene expression. She will have significant interactions with other members of the Center, such as Mike Mitchell and myself, as well as the broader Penn community, especially with the CAR therapists.”
How do you make robotics kits affordable for children in low-income countries? Speed up the manufacturing of organs-on-a-chip? Lower the environmental impact of condiments in restaurants?
If you’re a senior at Penn Engineering, the answer is to team up with your peers in the Senior Design Project Competition, which every year draws interdisciplinary groups from across the School’s six majors to solve real-world problems. Championed by the late Walter Korn (EE’57, GEE’68), a past president of the Engineering Alumni Society (EAS), Senior Design also invites alumni back to campus to evaluate the seniors’ year-long capstone projects.
Since the program started nearly two decades ago, hundreds of alumni have shared centuries’ worth of their collective experience with soon-to-be-minted graduates in the form of constructive feedback. “Senior Design is really one of the best days at Penn Engineering,” says Bradley Richards (C’92, LPS’17), Director of Alumni Relations, who manages the program. “Faculty advisors work with students all year long to bring out the best in each group’s efforts, and the results speak for themselves.”
This year, three student teams from each of Penn Engineering’s six departments — Bioengineering (BE), Chemical and Biomolecular Engineering (CBE), Computer and Information Science (CIS), Electrical and Systems Engineering (ESE), Materials Science and Engineering (MSE), and Mechanical Engineering and Applied Mechanics (MEAM) — presented their work to more than 60 alumni in person and online.
Judges’ Choice Award
The Judges’ Choice Award, which recognizes overall excellence, went to ESE’s VivoDisk, which developed a novel machine to manufacture organs-on-a-chip for Vivodyne, a startup launched by Dan Huh, Associate Professor in BE.
As one of the team members, Akash Chauhan (ENG’24), learned while interning for Vivodyne, assembling the stacks of organs-on-a-chip, which are collections of plastic plates containing cells that simulate organs for preclinical drug testing, is extremely finicky and time consuming.
By developing a machine that could automatically align the plates with high precision using computer vision and AI, the team reduced the disks’ manufacturing time and expense, leading Vivodyne to adopt the device for commercial use, accelerating the process of drug discovery. VivoDisk’s team members included Chauhan; Angela Rodriguez (ENG’24), Aliris Tang (ENG’24, W’24), Dagny Lott (ENG’24), Simone Kwee (ENG’24) and Vraj Satashia (ENG’24, GEN’25) and was advised by Sid Deliwala, Alfred Moore Senior Fellow and Director of Lab Programs in ESE, and Jan Van der Spiegel, Professor in ESE.
Technology and Innovation Award
One of the greatest challenges for children with epilepsy is status epilepticus, an abnormal type of long-lasting seizure that is hard to distinguish from typical seizures and that has a mortality rate of 30%. There is currently no way to perform a test for status epilepticus at home, meaning that children suspected of having the condition must be rushed to the hospital for an electroencephalogram.
Epilog, a team from BE, developed a novel, wearable headset that analyzes brainwaves to accurately determine whether or not a child suffering a seizure is actually suffering from status epilepticus. The team, composed of Rohan Chhaya (ENG’24, GEN’24), Carly Flynn (ENG’24), Elena Grajales (ENG’24), Priya Shah (ENG’24, GEN’25) and Doris Xu (ENG’24) and advised by Erin Berlew, Research Scientist in the Department of Orthopaedic Surgery and Lecturer in BE, carefully validated the device’s accuracy.
The judges recognized Epilog’s technological expertise, which ran the gamut from software to hardware, including a custom app to work with the device and carefully considered features like electrodes whose position can be adjusted to accommodate a child’s growth over time.
Academia is a long journey of specialization and behind any professor’s CV are long hours of research and study. While the path can be direct for some, for others there’s a pivot, a moment or experience that changes the course of that journey.
Penn Today spoke with four professors whose academic paths diverged, to learn about the trajectory of their interdisciplinary work. Vijay Balasubramanian traverses the boundaries of physics and neuroscience. Tukufu Zuberi is a demographer-turned-curator. Brittany Watson integrates education, research, and veterinary medicine. Amy Hillier began her career studying historical mortgage redlining and moved into supporting trans youth.
Vijay Balasubramanian The Cathy and Marc Lasry Professor of Physics in the School of Arts & Sciences
Wandering through Kolkata’s markets in India stimulates the mind. Hawkers’ cries pass through the inner ear as electrical signals; the pungent, earthy smell of turmeric enters the brain through olfactory sensory neurons. In 1976, a 7-year-old Vijay Balasubramanian had his own market revelation through a bookseller’s portico, where the cover of a slim volume showed a man peering through a microscope lens and a smattering of white paint scattered like stars across the firmament of man and machine.
“What is a scientist?” the book asked, running through a series of exciting adventure shots: archeologic discovery, venom extraction, missile control. In that moment, Balasubramanian knew he would be a scientist. It looked, he says, “amazingly cool.”
When he arrived at the Massachusetts Institute of Technology, Balasubramanian wanted to study the fundamental laws of nature. “So that’s physics,” he says. While earning his doctoral degree at Princeton University, a mentor suggested Balasubramanian read papers in the burgeoning field of neuroscience. It immediately resonated. “Oh my god, this stuff is so cool,” Balasubramanian thought. “But the final year of a Ph.D. is not the time to switch.”
He earned his degree and took a position as a junior fellow of the Harvard Society of Fellows. During the day, he worked on string theory and the information loss paradox for black holes. But in the evening, he would moonlight in a neuroscience lab.
As a young theoretical physicist at Penn, Balasubramanian met Peter Sterling. A former Freedom Rider and professor of neuroscience at the Perelman School of Medicine, Sterling was “a true intellectual,” Balasubramanian says. He knew everything, was interested in everything, and would talk with anybody.
The pair wrote a series of papers together regarding information processing and transmission. “He’s so quick and so much fun and so lively,” Sterling says of Balasubramanian. “He’s fearless; there’s nothing he won’t try.”
While in Cairo with wife Heather J. Sharkey, professor of modern Middle Eastern and North African history at Penn, Balasubramanian prepared a neuroscience grant and submitted it to the National Science Foundation, “sort of on a whim,” he says. “I put it in from an internet café on an island in the middle of the Nile.” He got the grant and started a research group.
After that, Balasubramanian says, “I was off and running.”
“I was certainly told,” Balasubramanian says of his work in neuroscience, “do not do this before tenure.” But, if he waited, “then I’d be too set my ways,” he says. “I just wouldn’t know enough; it would be too hard to learn; I wouldn’t have the time.”
Younger scientists often ask him about exploring multiple fields, Balasubramanian says. The advice he offers is to “have a central line where you have credibility, where you’ve established that you’re really, really good at what you do, and you can be trusted.” That gives you more latitude, he says.
After that, it’s just sheer discipline. “You’re going to have to wake up earlier than everybody else. You’re going to have to work longer days,” he says. “Otherwise, you know, everybody else is working hard too, and you’ll never be able to achieve the level of expertise and knowledge to be able to do things at that world-class level.”
Balasubramanian wants to see more interdisciplinary collaboration. “Each field trains its students with a certain body of techniques that has been found historically useful in that field,’ he says. “Very often, those techniques also have uses elsewhere, but they don’t know to apply it.”
Traversing borders can be helpful in producing new insights, Balasubramanian says. You can ask questions that people in the field won’t. You might experiment with new ideas or put two disjointed ideas together, he says. “If you’re coming from outside, you have the leeway to do all kinds of silly things. Sometimes, they’re not silly.”
Why not ask new questions and propose new answers? In the end, the data will tell you what’s true. “It gives me comfort to know how things tick.”
This post is adapted from a longer story in Penn Today. Read the full story here.
Balasubramanian is Cathy and Marc Lasry Professor in the Department of Physics and Astronomy in the Penn School of Arts and Sciences and is a member of the Penn Bioengineering Graduate Group. Read more stories featuring his research here.
Neurological disorders such as epilepsy, Alzheimers, Parkinson’s and certain forms of dementia are the leading cause of disability and second-leading cause of disease worldwide. These disorders disproportionately affect low-resourced communities due to lack of access to specialized healthcare, and many of these complex diseases lack curative solutions. The need to address neurological disorders is high, yet current diagnostics and treatments are not effective for preventative or personalized care and are not accessible or affordable enough to meet the needs of more than 3 billion people living with neurological disorders.
Flavia Vitale, Associate Professor in Bioengineering in Penn Engineering and in Neurology in Penn Medicine, works to meet this need, developing accessible and affordable solutions for the diagnosis, treatment and rehabilitation of people with neurological disorders.
“I started my research career in biomedical engineering hoping to one day help humanity,” says Vitale, who is also a 2024 recipient of a National Science Foundation (NSF) CAREER Award for her work. “But it wasn’t until I gained a more diverse skill set during my doctoral and postdoctoral research across chemical engineering and materials science that I was able to do that in a real way.”
Vitale’s multidisciplinary skills are what allow her to develop devices that help people living with brain disorders. The CAREER Award is now helping her further apply those skills and actualize some of her first long-term research projects at Penn.
“This CAREER Award will support my lab’s current research in leveraging innovation in materials and fabrication approaches to develop devices that are able to interface with and control different chemical and electrical signals inside the brain,” she says.
Focused primarily on understanding the brain activity involved in epilepsy-induced seizures, Vitale aims to design and develop brain-interface devices to pinpoint and suppress uncontrolled brain activity to prevent seizures from happening. Her work will lead to revolutionary health care for the 30% of epilepsy patients whose conditions are drug resistant. Currently those patients either wait out the uncontrolled brain activity and oftentimes life-threatening convulsions, or hope to be eligible for invasive surgeries to remove the part of the brain where seizures originate or to implant the seizure-controlling devices that are currently available.
How do we measure chaos and why would we want to? Together, Penn engineers Dani S. Bassett, J. Peter Skirkanich Professor in Bioengineering and in Electrical and Systems Engineering, and postdoctoral researcher Kieran Murphy leverage the power of machine learning to better understand chaotic systems, opening doors for new information analyses in both theoretical modeling and real-world scenarios.
Humans have been trying to understand and predict chaotic systems such as weather patterns, the movement of planets and population ecology for thousands of years. While our models have continued to improve over time, there will always remain a barrier to perfect prediction. That’s because these systems are inherently chaotic. Not in the sense that blue skies and sunshine can turn into thunderstorms and torrential downpours in a second, although that does happen, but in the sense that mathematically, weather patterns and other chaotic systems are governed by physics with nonlinear characteristics.
“This nonlinearity is fundamental to chaotic systems,” says Murphy. “Unlike linear systems, where the information you start with to predict what will happen at timepoints in the future stays consistent over time, information in nonlinear systems can be both lost and generated through time.”
Like a game of telephone where information from the original source gets lost as it travels from person to person while new words and phrases are added to fill in the blanks, outcomes in chaotic systems become harder to predict as time passes. This information decay thwarts our best efforts to accurately forecast the weather more than a few days out.
“You could put millions of probes in the atmosphere to measure wind speed, temperature and precipitation, but you cannot measure every single atom in the system,” says Murphy. “You must have some amount of uncertainty, which will then grow, and grow quickly. So while a prediction for the weather in a few hours might be fairly accurate, that growth in uncertainty over time makes it impossible to predict the weather a month from now.”
In their recent paper published in Physical Review Letters, Murphy and Bassett applied machine learning to classic models of chaos, physicists’ reproductions of chaotic systems that do not contain any external noise or modeling imperfections, to design a near-perfect measurement of chaotic systems to one day improve our understanding of systems including weather patterns.
“These controlled systems are testbeds for our experiments,” says Murphy. “They allow us to compare with theoretical predictions and carefully evaluate our method before moving to real-world systems where things are messy and much less is known. Eventually, our goal is to make ‘information maps’ of real-world systems, indicating where information is created and identifying what pieces of information in a sea of seemingly random data are important.”
One of the most important but least understood aspects of healing is cell migration, or the process of cells moving from one part of the body to another. “If you are an ambulance out in the woods,” says Karen Xu, an M.D/Ph.D. student in Medicine and Bioengineering, “and there are no paths for you to move forward, it will be a lot harder for you to get to a site that needs you.”
Earlier this year, Xu co-authored a paper in Nature Communications describing a new cue to help cells get to where they need to go: a material made chiefly of hyaluronic acid and gelatin, two gooey substances commonly found outside cells in joints and connective tissue.
“Hundreds of thousands of people tear their meniscus every year,” says Robert Mauck, Mary Black Ralston Professor in Orthopaedic Surgery in Penn Medicine and Professor in Bioengineering at Penn Engineering and one of Xu’s advisors, as well as a senior author on the paper. “This material could potentially speed up their recovery.”
What makes the material — known as a hydrogel due to its blend of gelatinous matter and water — unique is that the combination of hyaluronic acid and gelatin forms a complex network of paths, providing cells many different ways to travel between two points.
This property is known as bicontinuity, and is exemplified by two discrete continuous phases that are each connected throughout the entire volume of the material (for example with a sponge, with phases of cellulose and air; in the hydrogel, this is comprised of gelatin and hyaluronic acid) resulting in a dizzying array of patterns that dramatically increase the surface area inside the material.
To test the hydrogel’s efficacy, Xu and her collaborators — including co-advisor Jason Burdick, formerly the Robert D. Bent Professor in Bioengineering at Penn Engineering and now the Bowman Endowed Professor at the University of Colorado Boulder, and the paper’s other senior author — first created several different versions of the hydrogel to find the sweet spot at which the constituents formed the bicontinuous structure and had the highest internal surface area. “We found that a precise combination of the various hydrogel components and control over their mixing was needed to form the bicontinuous structure,” says Burdick.
One of the pillars of science is the idea that experimental results can be replicated. If they cannot be reproduced, what if the findings of an experiment were due just to chance? Over the last two decades, a growing chorus of scientists has raised concerns about the “reproducibility crisis,” in which many published research findings can’t be independently validated, calling into question the rigor of contemporary science.
Two years ago, a group led by Konrad Kording, a Penn Integrates Knowledge Professor in Bioengineering and Neuroscience, founded the Community For Rigor (C4R) to build a grassroots movement to improve the rigor of scientific research.
Supported by a grant from the National Institutes of Health (NIH) and partners at Harvard, Duquesne, Smith College and Johns Hopkins, among other institutions, C4R creates educational materials that teach the principles of rigorous research, from data collection to pre-registration of results. “Everyone has done wrong things,” says Kording. “We’re all making these mistakes and we need to be able to talk about it.”
Last month, Kording appeared on In Plain English, a podcast devoted to making science more accessible, alongside Kaela Singleton, the co-founder and President of Black in Neuro; Arjun Raj, Professor in Bioengineering in Penn Engineering and in Genetics in Penn Medicine; and Jamie Moffa, a physician-scientist in training at Washington University in St. Louis, to discuss scientific rigor, including actionable strategies for students and faculty alike.
The conversation touched on everything from successfully managing the reams of data produced by experiments to the power of community to drive cultural change, as well as the difficulty of filtering useful feedback from the noise of social media. “I hope we can get to a point where people feel comfortable sharing what’s working and what’s not working,” says Raj.