SERC Research

Students’ Project Summary

Elisabeth O. ‘21 investigated the molecular interactions between pain receptors and their ligands. She used a molecule docking model, which allowed her to visualize the region where receptor and ligand interact with one another at the atomic level. Understanding these interactions is essential in the development of drugs that can block pain receptors by mimicking the effect of  ligand binding without stimulating the receptor. (Mentor: NIH)

Ainsley G. ‘22  used atmospheric models to identify nitrous oxide (N2O) as a detectable biosignature in rocky exoplanets’ atmospheres. N2O is considered a strong biosignature candidate due to few abiotic origins. On Earth, most natural formation originates from bacterial breakdown of nitrogen in soil, which led to the hypothesis that if N2O was detected in exoplanets’ atmospheres, it would suggest the presence of microbes. Ainsley used the Planetary Spectrum Generator to generate spectra in more realistic conditions,  and Atmos, a photochemical model that produces chemical profiles for planetary atmospheres. Her work was recently incorporated in a journal article published by her mentor’s laboratory. Read her published work in The Astrophysical Journal. (Mentor: NASA)

Owen D. ‘22 investigated the characterization of aluminum batteries. Most batteries used in today’s society utilize lithium ions to generate the electrical current that powers our phones and computers. But lithium is a rare metal, while aluminum is more accessible. Using molecular dynamics simulations, Owen characterized the organic solvents that worked best with aluminum ions. His work is currently being submitted for publication by his mentor’s laboratory.  (Mentor: University of Windsor, Canada)

Yanna B. ‘22 focused her research on Alzheimer’s disease. The two main proteins that affect Alzheimer’s patients are amyloid-beta and Tau. Yanna’s project developed a cell-based therapy approach to target these two proteins. She genetically engineered cells from the immune system to carry receptors that recognized amyloid-beta and Tau. The efficiency of these cells to remove the two proteins was higher than current FDA-approved drugs. Yanna’s work is at the forefront of potential new treatments for Alzheimer’s patients. (Mentor: University of Pennsylvania)

Olivia A. ‘22 used molecular dynamics simulations to determine the optimal composition of lipid nanodiscs. These structures are essential to better understand the mechanisms of high-density lipoproteins (HDL), which are involved in the removal of cholesterol from the bloodstream. She used a simpler new modeling approach that both speeds the process and reduces the cost compared to more  complex simulations. Her work was recently published by her mentor’s laboratory. (Mentor: NIH)

James J. ‘19 used three-dimensional tetrahedral DNA structures to stimulate an immune system protein expression in Triple-Negative Breast Cancer cells. Once stimulated, the protein elicits an immune reaction against the cancer cells. Four nanostructures were synthesized, each with a higher number of tetrahedra. His research identified the optimal number of tetrahedra to boost the immune reaction and presents a new experimental approach for the targeting of breast cancer cells. (Mentor: NCI)

Carolyn ‘19 investigated the composition of water in Earth’s core melts. Understanding the role of water in breaking apart the structure of the melt is essential to interpreting geological models of liquid magma properties and following its movement through the Earth.  By using nuclear magnetic resonance (NMR) instead of the currently-used infrared spectroscopy (FTIR), Carolyn was able to disprove the established model and demonstrated that an increase in water leads to bond breakages within the molten rock. Understanding the role of water in breaking apart the structure of the melt is essential to interpreting geological models of liquid magma properties and following its movement through the Earth. (Mentor: Carnegie Institute of Sciences)

Evrim ‘20 developed an experimental approach to detect oxidative stress in sweat samples. Oxidative stress is an imbalance between prooxidant and antioxidant, and it can play an important role in the development of disease, including diabetes and several types of cancer. Using an Autonomous Redox Discovery Platform, Evrim collected samples of sweat obtained after a specific exercise routine and analyzed  the effect of sleep pattern on oxidative stress. His results showed that it is possible to detect oxidative stress in sweat and identified a correlation between sleep and oxidative stress levels during exercise, emphasizing the importance of sleep on athletes’ performance. (Mentor: University of Maryland)