Enabling Physiologically Representative Simulations of Pancreatic Beta Cells Imbedded in an Islet
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2010
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Abstract
Diabetes is a collection of diseases marked by high levels of glucose in the blood. The condition results from defects in insulin production or function, which are activities performed by the pancreas. Within the endocrine system of the pancreas lie clusters
of cells called islets. Each islet is composed of four different cells, the most prevalent of which being the beta cell. The main function of beta cells is to secrete insulin in response to blood glucose levels. As a result, the behavior of these cells is an issue of
ongoing interest in diabetes research. Our research aims to take the next step in implementing the mathematical model
governing beta cells by continuing the development of a computational islet. The mechanisms of insulin secretion within beta cells can be modeled with a set of deterministic ordinary differential equations. Considering cell dynamics of a cube of individual heterogeneous cells, the key parameters influencing the time evolution include ionic fluxes, calcium handling, metabolism, and electrical coupling. Capturing sudden changes of cell properties on a millisecond time scale requires the use of a stiff ODE solver. The computational complexity makes the simulation of islet behavior difficult and inefficient without sophisticated software built with careful consideration of robust mathematical numerical techniques. Our research focuses on creating an extensible, efficient, and functional computational beta cell software to aid current and future research in beta cell dynamics. In particular, we adapt existing glycolytic oscillator Matlab code into a numerically robust, modular set of Matlab files. By developing in Matlab, we create code that remains easily modifiable by mathematical biologists for a broad range of future applications. Studies on the cluster tara in the UMBC High Performance Computing Facility demonstrate that simulations up to the desired resolution are now practical.
Application simulations of the beta cell islet model led to an unexpected discovery that warrants further study: For certain intermediate values of the coupling strength, a small increase in the number of fast cells acts by first increasing the burst period,
before falling into the pattern of reducing the burst period with larger proportions of fast cells again.