PSA 307, Friday January 28th, 2005

Speaker: Clint Mason
               Department of Mathematics and Statistics
               Arizona State University

Title: The Glucose Effects Model, Accounting for Long-term Glucose
        Dynamics in Diabetic Progressors

Abstract: The human metabolic system has been modelled quite accurately on the
               short-time scale by Bergman's Minimal Model (Bergman, 1980). Attempts to
               describe anomalies in human metabolism, specifically Type 2 diabetes, have
               also been recently published (Topp, 2000). To date, no such long-term model has
               been tested against actual data. Recent analyses on data from the local Pima
               Indian population provide such a testing ground. In doing so, it is found
               that the actual progression pattern to diabetes (on a scale of many
               years), can be masked by the use of average glucose growth rates. The
              Glucose Effects Model here proposed describes the movement of individuals from a
               non-diabetic to a diabetic state more realistically from both statistical
              and physiological perspectives.