Date: Thursday, August 1, 2024, at 9:00 AM Eastern Time
Join by Zoom: https://ufl.zoom.us/j/96123363118
Join to view Zoom in person: MSB Room M-434, LSM Conference Room
Speaker: Jason Shoemaker, PhD, Associate Professor
Affiliation: Department of Chemical & Petroleum Engineering & Department of Computational & Systems Biology, University of Pittsburgh
Title: Mechanistic modeling and Big Data approaches to understanding sex disparities and immunopathology during respiratory infection.
Abstract: The severity of a respiratory infection varies between virus strains and important patient groups. Respiratory infection is a top 10 cause of death in the US in a “normal” year, and COVID-19 propelled respiratory infection to the 3rd leading cause of death in the US in 2021. Mounting evidence has suggested that deadly respiratory virus infections are associated with unnecessarily aggressive immune responses. Complementing this, immunomodulation studies have demonstrated that modifying the immune system can improve tissue pathology and disease outcome. Recently, retrospective studies have revealed important differences in infection outcomes between male and female patients, with animal models suggesting that, again, differences in inflammation can help partially explain these sex disparities. In this presentation, we will demonstrate how our interdisciplinary team is using computational modeling and omics-based, Big Data approaches to determine how the immune system is regulated, how that regulation may fail to be effective, and what insights can be gained for treating infections in the future. We will cover a variety of applications, including using omics and molecular interaction data to infer antiviral drug targets and using mechanistic models to identify candidate mechanisms driving outcome differences between (1) H1N1 and H5N1 viruses and (2) male and female infection.