Respiratory Syncytial Virus (RSV) is a common, contagious infection of the lungs and the respiratory tract. Syncytia are multinuclear cells that have fused together. It is so common that it effects all ages, but most people have experienced RSV by age two. Symptoms typically present similar to the common cold, with minimal effects and are easily treatable. RSV can, however, have detrimental effects on young children, the elderly, and those with compromised immune systems. As an individual infected cell can produce virus, so can syncytia cells. But, because of experimental limitations, it is difficult to measure characteristics such as viral production and lifespan of the syncytia cells. We will use mathematical models to study how different assumptions about the viral production and lifespan of syncytia change the resulting infection to determine whether less direct measurements can be used to determine syncytia viral production rates and lifespans.

Rhinovirus is the most prevalent virus in humans and is often the cause of the common cold. Modeling the dynamics of rhinovirus can allow us to observe important aspects of the virus including the general growth of the virus, the remaining target cells, the number of cells in the eclipse phase, and the number of infected cells. Following that, we can attempt to estimate parameters such as how much virus an infected cell produces or how long it takes an infected cell to start producing virus. We can use a method called Markov Chain Monte Carlo (MCMC) to try and gain more accurate estimates of those parameter based off observed data. Modeling rhinovirus will give us deeper insight into the workings of rhinovirus and allow us to try better and more accurate models of the virus.

Non-invasive temperature sensing is necessary for the analysis of biological processes occurring in the human body including cellular enzyme activity, protein expression, and ion regulation. Considering that a variety of such biological processes occur at the microscopic scale, a mechanism allowing for the detection of the temperature changes in microscopic environments is desired. Although several such techniques have been developed involving nanomaterials, there is still a need in deterministic non-invasive biocompatible approach allowing for temperature measurements both outside the cells and in the intracellular compartments. Here we develop a novel approach utilizing graphene quantum dots (GQDs) as agents for such detection. Because of their small 2-5 nm size, non-invasive optical sensitivity to temperature change and high biocompatibility, GQDs enable biologically safe sub-cellular resolution imaging. Both bottom-up synthesized nitrogen-doped graphene quantum dots and quantum dots produced from reduced graphene oxide via top-down approach in this work exhibit temperature-induced fluorescence variations used as sensing mechanism. Distinctive quenching of quantum dot fluorescence by up to 19.8 % is observed, in a temperature range from 25℃ to 49℃, in aqueous solution, while the intensity is restored to the original values as the temperature decreases back to 25℃. A similar trend is observed in vitro in HeLa cells as the cellular temperature is increased from 25℃ to 41℃. Our findings suggest that the temperature-dependent fluorescence quenching of bottom-up and top-down-synthesized graphene quantum dots can serve as non-invasive reversible deterministic mechanism for temperature sensing in microscopic sub-cellular biological environments.

Habituation occurs when responding to a stimulus decreases with repeated exposure. This decrease can be seen in an array of behaviors, including wheel running. In this experiment, rats ran in four different contexts (i.e., running wheels with different backgrounds/scents) for 30 minutes every day. One group ran in the same context daily while the other alternated between contexts. Rats running in different contexts should habituate less and run more consistently and at a higher rate. By increasing our understanding of the influence of habituation on exercise, results will have important implications for those wanting to maintain interest in an exercise routine.

Abstract SRS: Effects of Cross-Situational Generalization on Memory and Attitude Polarization Toward Social Groups

Serena Avitia, Akua Jonah, & Kaleigh Decker

When people generalize about others, they go beyond the information they are given and infer a level of cross-situational consistency that may polarize their attitudes. The current study investigates how cross-situational generalizations about a group’s traits can affect subsequent attitudes and memory. We predicted that participants who generalized about a fictitious groups behavior across various settings will rate the likelihood of cross-situational trait consistency as significantly higher than the scale mid-point, and report more negative attitudes toward the group than participants who reviewed the initial information they were given. Generalizers will also write paragraphs that more depict group members as displaying the original traits in general rather than only in the given situations, mistakenly recall and recognize some of the situations they rated as part of the initial information, and mistakenly report that their reported attitudes (after they generalized) were the same as their impressions immediately after reading the initial information. The predicted results will increase our understanding of the processes by which attitudes toward an entire group can polarize without any additional information.