Oscillatory dynamics of an intravenous glucose tolerance test model with delay interval
Published: 2019-08-15  

Title:  Oscillatory dynamics of an intravenous glucose tolerance test model with delay interval

Reporter:  Prof. Yang KuangArizona State University

Date:  2019.8.19    2:30-3:30

Place:  School of Science  Room 212

Abstract:  Type 2 diabetes mellitus (T2DM) has become prevalent pandemic disease largely due to the modern life style. The intravenous glucose tolerance test (IVGTT) is an effective protocol to determine the insulin sensitivity, glucose effectiveness and pancreatic β-cell functionality, through the analysis and parameter estimation of a proper differential equation model. In this talk we propose a novel approach to model the time delay in IVGTT modeling. This approach uses two parameters to simulate not only both discrete time delay and distributed time delay in the past interval, but also the time delay distributed in a past sub-interval. Longer time delay, either a discrete or distributed delay, often destabilize a system. This may not be true for time delay over a sub-interval. We present analytically some basic model properties which are desirable biologically and mathematically. We show that this relatively simple model provides good fit to fluctuating patient data sets and reveals some intriguing dynamics. Moreover, our numerical simulation results indicate that our model may remove the defect in well known Minimal Model which often overestimates the glucose effectiveness index.

Reporter Background:  Yang Kuang is a professor of mathematics at Arizona State University (ASU) since 1988. He received his B.Sc from the University of Science and Technology of China in 1984 and his Ph.D degree in mathematics in 1988 from the University of Alberta. Dr. Kuang is the author or editor of more than 180 refereed journal publications and 12 books or journal special issues. He is the founder and editor-in-chief of Mathematical Biosciences and Engineering. He has directed more than 20 Ph.D dissertations in mathematical and computational biology. In addition, he directed several large scale NSF or NIH founded multi-disciplinary research projects in US. He is well known for his efforts in developing practical theories to the study of delay differential equation models and models incorporating resource quality in biology and medicine. His recent research interests focus on the formulation and validation of scientifically well-grounded and computationally tractable mathematical models to describe the rich and intriguing dynamics of various within-host diseases (especially cancers) and their treatments. These models have the potential to speed up much-needed personalized medicine development.


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