Syncytia formation is the fusion of cells by a virus to create a multinucleated cell (syncytium) that shields the virus from outer factors in the extracellular space, such as antibodies. However, this process is much more energy intensive for a virus than tunneling between cells, which also shelters the virus. Why would a virus fuse cells together rather than save energy and tunnel? In order to determine what the benefits of syncytia formation are for viruses, a mathematical model including syncytia formation and antibodies was developed to simulate viral dynamics. Characteristics like viral duration, viral titer peak, and time of peak were measured while changing parameters such as fusion rate, which allowed comparison of infections with and without syncytia formation. Mathematically modeling and analyzing these comparisons and changes helps us understand whether syncytia formation helps protect viruses from the effect of antibodies.

To track drug delivery within the body, the vehicle must be biocompatible, soluble, and transparent in the human body. Being transparent in the human body means the vehicle exhibits fluorescence in the near-infrared (NIR) III biological transparency window (1500 – 1800 nm). These traits will respectively not oppose health defects in the subjects, will be stable within the blood and cells of the body, and be able to be found within the body through the means of infrared detectors. This is where graphene quantum dots (GQDs) come into the picture. GQDs prepared by a one-step hydrothermal method from glucosamine and ascorbic acid precursors are biocompatible and soluble in water. On their own, they do not demonstrate fluorescence in the NIR-III. To add this capability, we dope GQDs with erbium ions (Er-GQDs) as they demonstrate a fluorescence peak at 1550nm followed by excitation at 980nm laser. Fluorescence light coming from erbium ions at 1550 nm covers the NIR-III biological window, which is the last specification needed to have an eligible vehicle. In our work, we synthesized Er-GQDs at 200℃ for 8 h and 17 h in deuterium oxide. The fluorescence of erbium ions is known to be quenched by OH functional groups. The average size of Er-GQDs is growing from 3 to 5 nm after 8 h and 17 h treatment times, respectively, and exhibit fluorescence with 1550 nm emission peak in deuterium oxide. All aforementioned results make Er-GQDs a potential imaging agent for bioimaging.

COVID-19 now has antiviral treatments to help prevent hospitalization. Paxlovid is the most prevalent and effective of these medications. Paxlovid consists of two medications taken twice daily for five days, however, there have been anecdotal reports of rebound infection after a course of Paxlovid. This project aims to use mathematical models to investigate the infection conditions that result in rebound cases. Stochastic modeling is used to simulate the time course of infections with different doses and durations of Paxlovid to determine when rebound will occur. These findings could help physicians develop more consistent treatment regimens for Paxlovid.

Graphene quantum dots (GQDs) are a frontier of research in the interdisciplinary world of biology and medicine. They have been hallmarked for their remarkable applications, from cellular imaging to drug delivery. Due to their unique physicochemical and optical properties, there is a strong desire to bring them to clinical application. However, prior to any therapeutic and bioimaging studies comprehensive analysis of GQDs cytotoxicity has to be done in vitro. In our research, we assess the biocompatibility of a variety GQDs synthesized from different carbon-based precursors in non-cancerous cells through cell viability assay. Our results show that GQDs prepared from chitosan and glucosamine demonstrate 80% cell availability at 1.2 and 2.2 mg/mL concentrations, respectively, making them the most promising candidates for further therapeutic applications among over 15 GQD candidates tested.

The SARS-CoV-2 virus, which induced a global pandemic in 2020, is a serious pathogen that can cause acute respiratory distress in infected individuals. In order to garner a greater understanding of the SARS-CoV-2 virus and attenuate its effects, researchers have aimed to estimate key viral kinetic parameters. In this study, data from a previously published challenge study on the impacts of SARS-CoV-2 on young adults, including viral load, upsit score, and symptom score, was used to calibrate a system of ordinary differential equations, generating pathogenic parameters. In addition, Pearson covariance values and the Lyapunov exponents were calculated for each participant from the challenge study. For a majority of participants, the Lyapunov exponents were positive and finite, indicating chaotic behavior in vector space. Similarly, for most participants, there was a weak positive correlation between upsit/symptom scores and viral load. Future research will consist of implementing a newer system of ordinary differential equations that may be a better fit for the data