Event Description
Dr. Alison Althans, MD
Title: Exploring barriers to giving feedback on the general surgery clerkship: a Group Concept Mapping approach
As part of a series of projects aimed at improving the general surgery clerkship, we explore both faculty and student perspectives about barriers to giving and receiving quality feedback. We investigate this research question utilizing Group Concept Mapping, a qualitative research methodology employed by our group for separate but related projects in the realm of surgical education. We aim to utilize these results to guide targeted interventions for improving the feedback provided to students on the clerkship. Results from this study, and progress on a systematic review examining holistic review in graduate medical education, will be reviewed.
Mentors: Dr. Sara Myers, Dr. Matthew Rosengart
Ashti Shah, MS
Title: A body of Bridges: Spatiotemporal Modeling of Inflammatory Bridges Across Tissues
Summary: Inflammation is a complex process that evolves with time and can spread across tissues throughout the course of a disease. Advances in spatiotemporal modeling have led to a better understanding of how inflammation across tissues differs at various timepoints. However, current spatiotemporal models are limited in their ability to propose how and when inflammation spreads from tissue-to-tissue leading to systemic inflammation. Dynamic spatiotemporal models, particularly the development of dynamic hypergrpahs, allow for the statistically rigorous and visually comprehensible model of the spread of cross-tissue inflammation over time. From the evolution of static hypergraphs to dynamic hypergraphs and beyond, we have been able to infer a nuanced role for IL-17A in mediating cross-tissue inflammation in a number of acute inflammatory pathologies. Here, we will focus on the application of hypergraphs to understand the role of TLR4 on cross-tissue inflammation in response to trauma and hemorrhagic shock as well as the role of the CNS in mediating cross-tissue inflammation during massive wound healing. Dynamic spatiotemporal modeling can be applied to several clinical and experimental paradigms and can be used to model multiple types of data. One such application involves the spatiotemporal modeling of transcriptomics data to better understand the regulation of functional gene modules throughout the process of liver regeneration following partial hepatectomy. The work presented here highlights just a few of many applications of dynamic spatiotemporal modeling to gain insight into the dynamics of disease pathogenesis.
Mentor: Dr. Yoram Vodovotz, PhD