Mustafa Mir, Assistant Professor of Cell and Developmental Biology in the Perelman School of Medicine and member of the Penn Bioengineering Graduate Group, was selected as one of Howard Hughes Medical Institute’s 31 new Freeman Hrabowski Scholars. The group consists of outstanding early career faculty in science who have potential to become leaders in their research fields and to create diverse and inclusive lab environments in which everyone can thrive. Mir and his lab develop and apply new microscopes to directly visualize the molecular scale events that underlie gene expression within live embryos.
Thank you to everyone who attended the 2023 Department of Bioengineering Juneteenth Address. For those who were unable to attend or who may wish to share the opportunity to view the lecture, a recording of Dr. Kevin Johnson’s talk, “A White Neighbor, a Black Surgeon, and a Mormon Computer Scientist Walk into a Bar…” is available below.
Speaker: Kevin B. Johnson, MD, MS, FAAP, FAMIA, FACMI
David L. Cohen University Professor
Computer and Information Science
Biostatistics, Epidemiology and Informatics
Bioengineering
Annenberg School for Communication
Pediatrics
VP for Applied Informatics (UPHS), University of Pennsylvania
Abstract:
As we recognize Juneteenth, a holiday that brings awareness to what journalist Corey Mitchell calls “…a complex understanding of the nation’s past,” we also need to understand how many of our neighbors, staff, and faculty — even those born in the last 100 years — continue to navigate through the environment that made Juneteenth remarkable. In this talk, Dr. Johnson shares a bit of his personal story and how this story informs his national service and passion for teaching.
Nader Engheta was puzzled when he got a call from the psychology department about a fish. In the early 1990s, Engheta, a newly minted associate professor of electrical engineering in Penn’s School of Engineering and Applied Science, was a respected expert in radio wave technologies. But in recent years, his work had been expanding into subjects at once more eccentric and fundamental.
Nader Engheta was puzzled when he got a call from the psychology department about a fish.
In the early 1990s, Engheta, a newly minted associate professor of electrical engineering in Penn’s School of Engineering and Applied Science, was a respected expert in radio wave technologies. But in recent years, his work had been expanding into subjects at once more eccentric and fundamental.
Engheta’s interest in electromagnetic waves was not limited to radio frequencies, as a spate of fresh publications could attest. Some studies investigated a range of wave interactions with a class of matter known as a “chiral media,” materials with molecular configurations that exhibit qualities of left or right “handedness.” Others established practical electromagnetic applications for a bewildering branch of mathematics called “fractional calculus,” an area with the same Newtonian roots as calculus proper but a premise as eyebrow-raising as the suggestion a family might literally include two-and-a-half children.
Electromagnetic waves are organized on a spectrum of wavelengths. On the shorter end of the spectrum are high-energy waves, such as X-rays. In the middle, there is the limited range we see as visible light. And on the longer end are the lower-energy regimes of radio and heat.
Researchers tend to focus on one kind of wave or one section of the spectrum, exploring quirks and functions unique to each. But all waves, electromagnetic or not, share the same characteristics: They consist of a repeating pattern with a certain height (amplitude), rate of vibration (frequency), and distance between peaks (wavelength). These qualities can define a laser beam, a broadcasting voice, a wind-swept lake, or a violin string.
Engheta has never been the kind of scholar to limit the scope of his curiosity to a single field of research. He is interested in waves, and his fascination lies equally in the physics that determine wave behavior and the experimental technologies that push the boundaries of those laws.
So, when Edward Pugh, a mathematical psychologist studying the physiology of visual perception, explained that green sunfish might possess an evolutionary advantage for seeing underwater, Engheta listened.
Soon, the two Penn professors were pouring over microscope images of green sunfish retinas.
Read Devorah Fischler’s full story about Nader Engheta and watch an accompanying video at Penn Today.
Nader Engheta is H. Nedwill Ramsey Professor of Electrical and Systems Engineering at Penn Engineering, with secondary appointments in the departments of Bioengineering, Materials Science and Engineering, and Physics and Astronomy in the School of Arts & Sciences.
We hope you will join us for the 2023 Department of Bioengineering Juneteenth Address by Dr. Kevin B. Johnson.
Date: Wednesday, June 14, 2023
Start Time: 11:00 AM ET
Location: Berger Auditorium (Skirkanich Hall basement room 013)
Zoom link
Meeting ID: 925 0325 6013
Passcode: 801060
Following the event, a limited number of box lunches will be available for in-person attendees. If you would like a box lunch, please RSVP here by Monday, June 12 so we can get an accurate headcount.
Speaker: Kevin B. Johnson, MD, MS, FAAP, FAMIA, FACMI
David L. Cohen University Professor
Annenberg School for Communication, Bioengineering, Biostatistics, Epidemiology and Informatics, Computer and Information Science, Pediatrics
VP for Applied Informatics (UPHS), University of Pennsylvania
Title: “A White Neighbor, a Black Surgeon, and a Mormon Computer Scientist Walk into a Bar…”
Abstract: As we recognize Juneteenth, a holiday that brings awareness to what journalist Corey Mitchell calls “…a complex understanding of the nation’s past”, we also need to understand how many of our neighbors, staff, and faculty—even those born in the last 100 years—continue to navigate through the environment that made Juneteenth remarkable. Dr. Johnson will share a bit of his personal story and how this story informs his national service and passion for teaching.
Bio: Dr. Johnson is a leader of medical information technologies to improve patient care and safety. He is well regarded and widely known for pioneering discoveries in clinical informatics, leading to advances in data acquisition, medication management, and information aggregation in medical settings.
He is a board-certified pediatrician who has aligned the powers of medicine, engineering and technology to improve the health of individuals and communities. In work that bridges biomedical informatics, bioengineering and computer science, he has championed the development and implementation of clinical information systems and artificial intelligence to drive medical research. He has encouraged the effective use of technology at the bedside, and he has empowered patients to use new tools that help them to understand how medications and supplements may affect their health. He is interested in using advanced technologies such as smart devices and in developing computer-based documentation systems for the point of care. He also is an emerging champion of the use of digital media to enhance science communication, with a successful feature-length documentary describing health information exchange, a podcast (Informatics in the Round) and most recently, a children’s book series aimed at STEM education featuring scientists underrepresented in healthcare.
Dr. Johnson holds joint appointments in the Department of Computer and Information Science of the School of Engineering and Applied Science, and secondary appointments in Bioengineering and the Annenberg School for Communication. He serves as Vice President for Applied Informatics in the University of Pennsylvania Health System and as a Professor of Pediatrics at the Children’s Hospital of Philadelphia.
Before arriving at Penn, he served as the Cornelius Vanderbilt Professor and Chair of the Department of Biomedical Informatics at the Vanderbilt University School of Medicine, where he had taught since 2002. As Senior Vice President for Health Information Technology at the Vanderbilt University Medical Center, he led the development of clinical systems that enabled doctors to make better treatment and care decisions for individual patients, and introduced new systems to integrate artificial intelligence into patient care workflows.
The author of more than 150 publications, Dr. Johnson has held numerous leadership positions in the American Medical Informatics Association and the American Academy of Pediatrics. He leads the American Board of Pediatrics Informatics Advisory Committee, directs the Board of Scientific Counselors of the National Library of Medicine, and is a member of the NIH Council of Councils. He is an elected member of the National Academy of Medicine, American College of Medical Informatics and Academic Pediatric Society. He has received awards from the Robert Wood Johnson Foundation and American Academy of Pediatrics, among many others.
They will conduct research, pursue graduate degrees, or teach English in Belgium, Brazil, Colombia, Denmark, Ecuador, Estonia, France, Germany, Guatemala, India, Israel, Latvia, Mexico, Nepal, New Zealand, the West Bank-Palestine territories, South Korea, Spain, Switzerland, Taiwan, and Thailand.
The Fulbright Program is the United States government’s flagship international educational exchange program, awarding grants to fund as long as 12 months of international experience.
Among the Penn Fulbright grant recipients for 2023-24 is Ella Atsavapranee, from Cabin John, Maryland, who graduated in May with a bachelor’s degree in bioengineering from the School of Engineering and Applied Science and a minor in chemistry from the College. She was offered a Fulbright to conduct research at the École Polytechnique Fédérale de Lausanne in Switzerland.
At Penn, Atsavapranee worked with Michael Mitchell, J. Peter and Geri Skirkanich Assistant Professor in Bioengineering, engineering lipid nanoparticles to deliver proteases that inhibit cancer cell proliferation. She has also worked with Shan Wang, Leland T. Edwards Professor in the School of Engineering and Professor of Electrical Engineering at Stanford University, using bioinformatics to discover blood biomarkers for cancer detection. To achieve more equitable health care, she worked with Lisa Shieh, Clinical Professor in Medicine at the Stanford School of Medicine, to evaluate an AI model that predicts risk of hospital readmission and study how room placement affects patient experience.
Outside of research, Atsavapranee spread awareness of ethical issues in health care and technology as editor-in-chief of the Penn Bioethics Journaland a teaching assistant for Engineering Ethics (EAS 2030). She was also a Research Peer Advisor for the Penn Center for Undergraduate Research & Fellowships (CURF), a student ambassador for the Office of Admissions, and a volunteer for Service Link, Puentes de Salud, and the Hospital of the University of Pennsylvania. She plans to pursue a career as a physician-scientist to develop and translate technologies that are more affordable and accessible to underserved populations.
Read the full list of Penn Fulbright grant recipients for 2023-24 in Penn Today.
Candida albicans is a species of yeast that is a normal part of the human microbiota but can also cause severe infections that pose a significant global health risk due to their resistance to existing treatments, so much so that the World Health Organization has highlighted this as a priority issue. The picture above shows a before (left) and after (right) fluorescence image of fungal biofilms being precisely targeted by nanozyme microrobots without bonding to or disturbing the tissue sample. (Image: Min Jun Oh and Seokyoung Yoon)
Infections caused by fungi, such as Candida albicans, pose a significant global health risk due to their resistance to existing treatments, so much so that the World Health Organization has highlighted this as a priority issue.
Although nanomaterials show promise as antifungal agents, current iterations lack the potency and specificity needed for quick and targeted treatment, leading to prolonged treatment times and potential off-target effects and drug resistance.
“Candida forms tenacious biofilm infections that are particularly hard to treat,” Koo says. “Current antifungal therapies lack the potency and specificity required to quickly and effectively eliminate these pathogens, so this collaboration draws from our clinical knowledge and combines Ed’s team and their robotic expertise to offer a new approach.”
The team of researchers is a part of Penn Dental’s Center for Innovation & Precision Dentistry, an initiative that leverages engineering and computational approaches to uncover new knowledge for disease mitigation and advance oral and craniofacial health care innovation.
For this paper, published in Advanced Materials, the researchers capitalized on recent advancements in catalytic nanoparticles, known as nanozymes, and they built miniature robotic systems that could accurately target and quickly destroy fungal cells. They achieved this by using electromagnetic fields to control the shape and movements of these nanozyme microrobots with great precision.
“The methods we use to control the nanoparticles in this study are magnetic, which allows us to direct them to the exact infection location,” Steager says. “We use iron oxide nanoparticles, which have another important property, namely that they’re catalytic.”
Other authors include Min Jun Oh, Alaa Babeer, Yuan Liu, Zhi Ren, Zhenting Xiang, Yilan Miao, and Chider Chen of Penn Dental; and David P. Cormode and Seokyoung Yoon of the Perelman School of Medicine. Cormode also holds a secondary appointment in Bioengineering.
This research was supported in part by the National Institute for Dental and Craniofacial Research (R01 DE025848, R56 DE029985, R90DE031532 and; the Basic Science Research Program through the National Research Foundation of Korea of the Ministry of Education (NRF-2021R1A6A3A03044553).
Neil Sheppard, Adjunct Associate Professor of Pathology and Laboratory Medicine in the Perelman School of Medicine, and David Mai, a Bioengineering graduate student in the School of Engineering and Applied Science, explained the findings of their recent study, which offered a potential strategy to improve T cell therapy in solid tumors, to the European biotech news website Labiotech.
Bella Mirro (left) poses with Penn President Liz Magill. (Image: Prestige Portraits)
For 150 years, Ivy Day has been an annual tradition at Penn, with each graduating class installing at least one new plaque and planting a sprig of ivy. On Saturday, May 13, the class of 2023 added to the 200-plus plaques throughout campus with a stone designed by Marah Sanchez, a Class of 2023 student in the School of Nursing, and remarks from Vice Provost for University Life Karu Kozuma.
“The Ivy Day Award Ceremony is a special celebration that gives us an opportunity to acknowledge the contributions and accomplishments of our graduating student leaders,” Kozuma says. “It is also an occasion to create connections. At the ceremony, we have the privilege of meeting family members and loved ones who have supported the students, while the students can connect with alumni who received the same recognition 25 years ago.”
Among the honorees were several Penn Bioengineering students.
Isabella Mirro was presented with the Penn Student Agencies Award by President Liz Magill. This award recognizes distinguished academic achievement and significant leadership in undergraduate activities by a member of the senior class. Mirro, a graduate of the undergraduate Class of 2023, was recently profiled in 34th Street Magazine.
President Liz Magill (right) with the winners of the President’s Innovation Prize. (Image: Prestige Portraits)
Additionally, Tifara Boyce, Gabriela Cano, Gabriella Daltoso, Sophie Ishiwari, and Caroline Magro were formally presented with the President’s Innovation Prize for their startup Sonura. Sonura was featured in Penn Today for their award-winning beanie for NICU infants.
Read the full list of Ivy Day awards in Penn Today.
Folding@home is led by Gregory Bowman, a Penn Integrates Knowledge Professor who has appointments in the Departments of Biochemistry and Biophysics in the Perelman School of Medicine and the Department of Bioengineering in the School of Engineering and Applied Science. (Image: Courtesy of Penn Medicine News)
Two heads are better than one. The ethos behind the scientific research project Folding@home is that same idea, multiplied: 50,000 computers are better than one.
Folding@home is a distributed computing project which is used to simulate protein folding, or how protein molecules assemble themselves into 3-D shapes. Research into protein folding allows scientists to better understand how these molecules function or malfunction inside the human body. Often, mutations in proteins influence the progression of many diseases like Alzheimer’s disease, cancer, and even COVID-19.
Penn is home to both the computer brains and human minds behind the Folding@home project which, with its network, forms the largest supercomputer in the world. All of that computing power continually works together to answer scientific questions such as what areas of specific protein implicated in Parkinson’s disease may be susceptible to medication or other treatment.
Using the network hub at Penn, Bowman and his team assign experiments to each individual computer which communicates with other computers and feeds info back to Philly. To date, the network is comprised of more than 50,000 computers spread across the world.
“What we do is like drawing a map,” said Bowman, explaining how the networked computers work together in a type of system that experts call Markov state models. “Each computer is like a driver visiting different places and reporting back info on those locations so we can get a sense of the landscape.”
Individuals can participate by signing up and then installing software to their standard personal desktop or laptop. Participants can direct the software to run in the background and limit it to a certain percentage of processing power or have the software run only when the computer is idle.
When the software is at work, it’s conducting unique experiments designed and assigned by Bowman and his team back at Penn. Users can play scientist and watch the results of simulations and monitor the data in real time, or they can simply let their computer do the work while they go about their lives.
Machine learning (ML) programs computers to learn the way we do – through the continual assessment of data and identification of patterns based on past outcomes. ML can quickly pick out trends in big datasets, operate with little to no human interaction and improve its predictions over time. Due to these abilities, it is rapidly finding its way into medical research.
People with breast cancer may soon be diagnosed through ML faster than through a biopsy. Those suffering from depression might be able to predict mood changes through smart phone recordings of daily activities such as the time they wake up and amount of time they spend exercising. ML may also help paralyzed people regain autonomy using prosthetics controlled by patterns identified in brain scan data. ML research promises these and many other possibilities to help people lead healthier lives.
But while the number of ML studies grow, the actual use of it in doctors’ offices has not expanded much past simple functions such as converting voice to text for notetaking.
The limitations lie in medical research’s small sample sizes and unique datasets. This small data makes it hard for machines to identify meaningful patterns. The more data, the more accuracy in ML diagnoses and predictions. For many diagnostic uses, massive numbers of subjects in the thousands would be needed, but most studies use smaller numbers in the dozens of subjects.
But there are ways to find significant results from small datasets if you know how to manipulate the numbers. Running statistical tests over and over again with different subsets of your data can indicate significance in a dataset that in reality may be just random outliers.
This tactic, known as P-hacking or feature hacking in ML, leads to the creation of predictive models that are too limited to be useful in the real world. What looks good on paper doesn’t translate to a doctor’s ability to diagnose or treat us.
These statistical mistakes, oftentimes done unknowingly, can lead to dangerous conclusions.
To help scientists avoid these mistakes and push ML applications forward, Konrad Kording, Nathan Francis Mossell University Professor with appointments in the Departments of Bioengineering and Computer and Information Science in Penn Engineering and the Department of Neuroscience at Penn’s Perelman School of Medicine, is leading an aspect of a large, NIH-funded program known as CENTER – Creating an Educational Nexus for Training in Experimental Rigor. Kording will lead Penn’s cohort by creating the Community for Rigor which will provide open-access resources on conducting sound science. Members of this inclusive scientific community will be able to engage with ML simulations and discussion-based courses.
“The reason for the lack of ML in real-world scenarios is due to statistical misuse rather than the limitations of the tool itself,” says Kording. “If a study publishes a claim that seems too good to be true, it usually is, and many times we can track that back to their use of statistics.”
Such studies that make their way into peer-reviewed journals contribute to misinformation and mistrust in science and are more common than one might expect.
Machine learning (ML) programs computers to learn the way we do – through the continual assessment of data and identification of patterns based on past outcomes. ML can quickly pick out trends in big datasets, operate with little to no human interaction and improve its predictions over time. Due to these abilities, it is rapidly finding its way into medical research.