Published electronically August 10, 2009
Pablo Díaz, Michael Gillespie, Justin Krueger, José Pérez, Alex Radebaugh, Toby Shearman, Garret Vo, and Christine Wheatley (University of North Carolina at Greensboro, St. Augustine's College, Miami University, University of Puerto Rico, Mayagüez Campus, Bucknell University, Virginia Tech, Montana State University, Alma College)Sponsors:
J. Bassaganya-Riera, J. Borggaard , J. Burns , E. Cliff , A. Guri, S. Faulkner, R. Hontecillas-Magarzo, A. Jarrah, C. Koelling, R. Laubenbacher, H. Mortveit, L. Zietsman (Virginia Bioinformatics Institute at Virginia Tech and Interdisciplinary Center for Applied Mathematics at Virginia Tech)Abstract
: Obesity is quickly becoming a pandemic. The low-grade chronic inflammation associated with obesity leads to health risks such as cancer, heart disease, and type 2 diabetes mellitus. To better understand the progression of obesity-related chronic inflammation, mice were fed either a high-fat or low-fat diet over 140 days. At Days 0, 35, 70, and 140, the percentages of macrophage subsets, CD4+ T cells, and regulatory T cells infiltrating the intra-abdominal white adipose tissue (WAT) were examined. Monocyte chemoattractant protein-1 (MCP-1) mRNA expression in WAT was also quantified. Additionally, glucose-normalizing ability was examined by administering peritoneal glucose tolerance tests. A system of ordinary differential equations models this system. The model consists of 8 differential equations, has 25 parameters, and has 1 forcing function. Tools used to characterize the model include parameter estimation, sensitivity analysis, and stability analysis. Based on the data provided, the system describes the growth of adipocyte size and chronic inflammation over 105 days beginning at Day 35, which is approximately when the adipose cells become hypertrophic, or too large to function normally. The model shows that without intervention, chronic inflammation escalates and the related health problems persist.