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|Title:||Multi-scale models of gastrointestinal electrophysiology|
|Authors:||Buist, M.L. |
|Citation:||Buist, M.L.,Corrias, A.,Poh, Y.C. (2009). Multi-scale models of gastrointestinal electrophysiology. IFMBE Proceedings 23 : 1809-1813. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-540-92841-6_449|
|Abstract:||We have developed quantitative mathematical descriptions of a gastric smooth muscle cell (SMC) and a gastric interstitial cell of Cajal (ICC). Together these two cell types, with input from the enteric nervous system, govern the electrical and mechanical actions of the stomach that combine to generate motility. Each of these models has been developed from the underlying physiology and has been validated against whole cell experimental recordings. Such models form the building blocks necessary to construct multi-cellular and multi-scale simulations that link sub-cellular behavior to whole organ function. With these building blocks, tissue and organ level models have been developed. The geometry of the stomach has been digitized from photographic images from the visible human project and a derivative continuous serosal surface has been fitted using an iterative linear minimization technique. The volume of the muscularis externa, representing the layers in the stomach wall responsible for gastric motility, was created through an inward projection from the serosal surface. Within this volume a high resolution hexahedral finite element mesh was created over which a non-linear reaction diffusion equation was solved to describe the macroscopic propagation of electrical activity in the stomach. At the other end of the spectrum, a mutation in the gene encoding the gastrointestinal sodium channel has been described and linked to clinical symptoms. To elucidate the effects of subcellular maladies such as this, a true multi-scale framework has been developed to investigate gastrointestinal electrophysiology; from ion channel to cell to tissue to organ. This framework will allow us to better understand the emergent behavior of the system in a way that would be difficult, if not impossible, to decode experimentally. The development of the framework and the first results from its implementation are presented.|
|Source Title:||IFMBE Proceedings|
|Appears in Collections:||Staff Publications|
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