Week in BioE (July 12, 2019)

by Sophie Burkholder

DNA Microscopy Gives a Better Look at Cell and Tissue Organization

A new technique that researchers from the Broad Institute of MIT and Harvard University are calling DNA microscopy could help map cells for better understanding of genetic and molecular complexities. Joshua Weinstein, Ph.D., a postdoctoral associate at the Broad Institute, who is also an alumnus of Penn’s Physics and Biophysics department and former student in Penn Bioengineering Professor Ravi Radhakrishnan’s lab, is the first author of this paper on optics-free imaging published in Cell.

The primary goal of the study was to find a way of improving analysis of the spatial organization of cells and tissues in terms of their molecules like DNA and RNA. The DNA microscopy method that Weinstein and his team designed involves first tagging DNA, and allowing the DNA to replicate with those tags, which eventually creates a cloud of sorts that diffuses throughout the cell. The DNA tags subsequent interactions with molecules throughout the cell allowed Weinstein and his team to calculate the locations of those molecules within the cell using basic lab equipment. While the researchers on this project focused their application of DNA microscopy on tracking human cancer cells through RNA tags, this new method opens the door to future study of any condition in which the organization of cells is important.

Read more on Weinstein’s research in a recent New York Times profile piece.

Penn Engineers Demonstrate Superstrong, Reversible Adhesive that Works like Snail Slime

A snail’s epiphragm. (Photo: Beocheck)

If you’ve ever pressed a picture-hanging strip onto the wall only to realize it’s slightly off-center, you know the disappointment behind adhesion as we typically experience it: it may be strong, but it’s mostly irreversible. While you can un-stick the used strip from the wall, you can’t turn its stickiness back on to adjust its placement; you have to start over with a new strip or tolerate your mistake. Beyond its relevance to interior decorating, durable, reversible adhesion could allow for reusable envelopes, gravity-defying boots, and more heavy-duty industrial applications like car assembly.

Such adhesion has eluded scientists for years but is naturally found in snail slime. A snail’s epiphragm — a slimy layer of moisture that can harden to protect its body from dryness — allows the snail to cement itself in place for long periods of time, making it the ultimate model in adhesion that can be switched on and off as needed. In a new study, Penn Engineers demonstrate a strong, reversible adhesive that uses the same mechanisms that snails do.

This study is a collaboration between Penn Engineering, Lehigh University’s Department of Bioengineering, and the Korea Institute of Science and Technology.

Read the full story on Penn Engineering’s Medium blog. 

Low-Dose Radiation CT Scans Could Be Improved by Machine Learning

Machine learning is a type of artificial intelligence growing more and more popular for applications in bioengineering and therapeutics. Based on learning from patterns in a way similar to the way we do as humans, machine learning is the study of statistical models that can perform specific tasks without explicit instructions. Now, researchers at Rensselaer Polytechnic Institute (RPI) want to use these kinds of models in computerized tomography (CT) scanning by lowering radiation dosage and improving imaging techniques.

A recent paper published in Nature Machine Intelligence details the use of modularized neural networks in low-dose CT scans by RPI bioengineering faculty member Ge Wang, Ph.D., and his lab. Since decreasing the amount of radiation used in a scan will also decrease the quality of the final image, Wang and his team focused on a more optimized approach of image reconstruction with machine learning, so that as little data as possible would be altered or lost in the reconstruction. When tested on CT scans from Massachusetts General Hospital and compared to current image reconstruction methods for the scans, Wang and his team’s method performed just as well if not better than scans performed without the use of machine learning, giving promise to future improvements in low-dose CT scans.

A Mind-Controlled Robotic Arm That Requires No Implants

A new mind-controlled robotic arm designed by researchers at Carnegie Mellon University is the first successful noninvasive brain-computer interface (BCI) of its kind. While BCIs have been around for a while now, this new design from the lab of Bin He, Ph.D.,  a Trustee Professor and the Department Head of Biomedical Engineering at CMU, hopes to eliminate the brain implant that most interfaces currently use. The key to doing this isn’t in trying to replace the implants with noninvasive sensors, but in improving noisy EEG signals through machine learning, neural decoding, and neural imaging. Paired with increased user engagement and training for the new device, He and his team demonstrated that their design enhanced continuous tracking of a target on a computer screen by 500% when compared to typical noninvasive BCIs. He and his team hope that their innovation will help make BCIs more accessible to the patients that need them by reducing the cost and risk of a surgical implant while also improving interface performance.

People and Places

Daeyeon Lee, professor in the Department of Chemical and Biomolecular Engineering and member of the Bioengineering Graduate Group Faculty here at Penn, has been selected by the U.S. Chapter of the Korean Institute of Chemical Engineers (KIChE) as the recipient of the 2019 James M. Lee Memorial Award.

KIChE is an organization that aims “to promote constructive and mutually beneficial interactions among Korean Chemical Engineers in the U.S. and facilitate international collaboration between engineers in U.S. and Korea.”

Read the full story on Penn Engineering’s Medium blog.

We would also like to congratulate Natalia Trayanova, Ph.D., of the Department of Biomedical Engineering at Johns Hopkins University on being inducted into the Women in Tech International (WITI) Hall of Fame. Beginning in 1996, the Hall of Fame recognizes significant contributions to science and technology from women. Trayanova’s research specializes in computational cardiology with a focus on virtual heart models for the study of individualized heart irregularities in patients. Her research helps to improve treatment plans for patients with cardiac problems by creating virtual simulations that help reduce uncertainty in either diagnosis or courses of therapy.

Finally, we would like to congratulate Andre Churchwell, M.D., on being named Vanderbilt University’s Chief Diversity Officer and Interim Vice Chancellor for Equity, Diversity, and Inclusion. Churchwell is also a professor of medicine, biomedical engineering, and radiology and radiological sciences at Vanderbilt, with a long career focused in cardiology.

Week in BioE: March 29, 2019

by Sophie Burkholder

New Studies in Mechanobiology Could Open Doors for Cellular Disease Treatment

When we think of treatments at the cellular level, we most often think of biochemical applications. But what if we began to consider more biomechanical-oriented approaches in the regulation of cellular life and death? Under a grant from the National Science Foundation (NSF),Worcester Polytechnic Institute’s (WPI) Head of the Department of Biomedical Engineering Kristen Billiar, Ph.D., performs research that looks at the way mechanical stimuli can affect and trigger programmed cell death.

Billiar, who received his M.S.E. and Ph.D. from Penn, began his research by first noticing the way that cells typically respond to the mechanical stimuli in their everyday environment, such as pressure or stretching, with behaviors like migration, proliferation, or contraction. He and his research team hope to find a way to eventually predict and control cellular responses to their environment, which they hope could open doors to more forms of treatment for disorders like heart disease or cancer, where cellular behavior is directly linked to the cause of the disease.

Self-Learning Algorithm Could Help Improve Robotic Leg Functionality

Obviously, one of the biggest challenges in the field of prosthetics is the extreme difficulty in creating a device that perfectly mimics whatever the device replaces for its user. Particularly with more complex designs that involve user-controlled motion for joints in the limbs or hands, the electrical circuits implemented are by no means a perfect replacement of the neural connections in the human body from brain to muscle. But recently at the University of Southern California Viterbi School of Engineering, a team of researchers led by Francisco J. Valero-Cuevas, Ph. D.,  developed an algorithm with the ability to learn new walking tasks and adapt to others without any additional programming.

The algorithm will hopefully help to speed the progress of robotic interactions with the world, and thus allow for more adaptive technology in prosthetics, that responds to and learns with their users. The algorithm Valero-Cuevas and his team created takes inspiration from the cognition involved with babies and toddlers as they slowly learn how to walk, first through random free play and then from pulling on relevant prior experience. In a prosthetic leg, the algorithm could help the device adjust to its user’s habits and gait preferences, more closely mimicking the behavior of an actual human leg.

Neurofeedback Can Improve Behavioral Performance in High-Stress Situations

We’re all familiar with the concept of being “in the zone,” or the feeling of extraordinary focus that we can sometimes have in situations of high-stress. But how can we understand this shift in mindset on a neuroengineering level? Using the principal of the Yerkes-Dodson law, which says that there is a state of brain arousal that is optimal for behavioral performance, a team of biomedical engineering researchers at Columbia University hope to find ways of applying neurofeedback to improving this performance in demanding high-stress tasks.

Led by Paul Sajda, Ph.D., who received his doctoral degree from Penn, the researchers used a brain-computer interface to collect electroencephalography (EEG) signals from users immersed in virtual reality aerial navigation tasks of varying difficulty levels. In doing so, they were able to make connections between stressful situations and brain activity as transmitted through the EEG data, adding to the understanding of how the Yerkes-Dodson law actually operates in the human body and eventually demonstrating that the use of neurofeedback reduced the neural state of arousal in patients. The hope is that neurofeedback may be used in the future to help treat emotional conditions like post-traumatic stress disorder (PTSD).

Ultrasound Stimulation Could Lead to New Treatments for Inflammatory Arthritis

Arthritis, an autoimmune disease that causes painful inflammation in the joints, is one of the more common diseases among older patients, with more than 3 million diagnosed cases in the United States every year. Though extreme measures like joint replacement surgery are one solution, most patients simply treat the pain with nonsteroidal anti-inflammatory drugs or the adoption of gentle exercise routines like yoga. Recently however, researchers at the University of Minnesota led by Daniel Zachs, M.S.E., in the Sensory Optimization and Neural Implant Coding Lab used ultrasound stimulation treatment as a way to reduce arthritic pain in mice. In collaboration with Medtronic, Zachs and his team found that this noninvasive ultrasound stimulation greatly decreased joint swelling in mice who received the treatment as opposed to those that did not. They hope that in the future, similar methods of noninvasive treatment will be able to be used for arthritic patients, who otherwise have to rely on surgical remedies for serious pain.

People and Places

Leadership and Inspiration: EDAB’s Blueprint for Engineering Student Life

To undergraduates at a large university, the administration can seem like a mysterious, all-powerful entity, creating policy that affects their lives but doesn’t always take into account the reality of their day-to-day experience. The Engineering Deans’ Advisory Board (EDAB) was designed to bridge that gap and give students a platform to communicate with key decision makers.

The 13-member board meets once per week for 60 to 90 minutes. The executive board, comprised of four members, also meets weekly to plan out action items and brainstorm. Throughout his interactions with the group, board president Jonathan Chen, (ENG ‘19, W ‘19), has found a real kinship with his fellow board members, who he says work hard and enjoy one another’s company in equal measure.

Bioengineering major Daphne Cheung (ENG’19) joined the board as a first-year student because she saw an opportunity to develop professional skills outside of the classroom. “For me, it was about trying to build a different kind of aptitude in areas such as project management, and learning how to work with different kinds of people, including students and faculty, and of course, the deans,” she says.

Read the full story on Penn Engineering’s Medium Blog. Media contact Evan Lerner.

Purdue University College of Engineering and Indiana University School of Medicine Team Up in New Engineering-Medicine Partnership

The Purdue University College of Engineering and the Indiana University School of Medicine recently announced a new Engineering-Medicine partnership, that seeks to formalize ongoing and future collaborations in research between the two schools. One highlight of the partnership is the establishment of a new M.D./M.S. degree program in biomedical engineering that will allow medical students at Indiana University to receive M.S.-level training in engineering technologies as they apply to clinical practice. The goal of this new level of collaboration is to further involve Purdue’s engineering program in the medical field, and to exhibit the benefits that developing an engineering mindset can have for medical students. The leadership of this new partnership includes