Dynamics of Computational Islet Simulations

Gemma Gearhart
Division of Science, Mathematics and Computing, Bard College at Simon's Rock

Shuai Jiang
Department of Mathematics, Cornell University

Thomas J. May
Department of Mathematics, Virginia Polytechnic Institute and State University

Jane Pan
Department of Mathematics and Statistics, University of Maryland, Baltimore County

Samuel Khuvis
Department of Mathematics and Statistics, University of Maryland, Baltimore County

Matthias K. Gobbert
Department of Mathematics and Statistics, University of Maryland, Baltimore County

Bradford E. Peercy
Department of Mathematics and Statistics, University of Maryland, Baltimore County

Arthur Sherman
Laboratory of Biological Modeling, National Institutes of Health

Abstract

The study of pancreatic beta-cells comprises a crucial part of the study of the group of diseases known as diabetes. These cells exist in groups known as islets of Langerhans and are responsible for storing and producing insulin. They exhibit electrical bursting behavior during insulin production that correlates with the rate at which insulin is secreted into the bloodstream. Coupling is a natural process within islets that enables the cells to communicate with one another and transfer various ions and electrical currents; coupling of both voltage and metabolites can occur. We model multicellular islets using an existing system of seven ordinary differential equations to model beta cell function. We simulate cells with mutated KATP channels that remain open indefinitely, which have been described in experimental studies but not yet modeled. Simulations ran with these mutations reveal the existence of a bursting death threshold, described by the least percentage of cells in the islet that must be mutated for electrical bursts to completely disappear. We determine that this threshold is independent of coupling strengths, cell distribution, and possibly islet dimension; however, we also determined that this threshold is dependent on the glucose influx rate.

Keywords: Beta cell model ,Computational islet ,Glycolytic oscillations

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