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Representation of multiple cellular phenotypes within tissue-level simulations of cardiac electrophysiology

Bowler, Louise A.; Gavaghan, David J.; Mirams, Gary R.; Whiteley, Jonathan P.

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Authors

Louise A. Bowler

David J. Gavaghan

Jonathan P. Whiteley



Abstract

Distinct electrophysiological phenotypes are exhibited 1 by biological cells that have differentiated into particular cell types. The usual approach when simulating the cardiac electrophysiology of tissue that includes different cell types is to model the different cell types as occupying spatially distinct yet coupled regions. Instead, we model the electrophysiology of well-mixed cells by using homogenisation to derive an extension to the commonly used monodomain or bidomain equations. These new equations permit spatial variations in the distribution of the different subtypes of cells and will reduce the computational demands of solving the governing equations. We validate the homogenisation computationally, and then use the new model to explain some experimental observations from stem cell-derived cardiomyocyte monolayers.

Citation

Bowler, L. A., Gavaghan, D. J., Mirams, G. R., & Whiteley, J. P. (2019). Representation of multiple cellular phenotypes within tissue-level simulations of cardiac electrophysiology. Bulletin of Mathematical Biology, 81(1), 7–38. https://doi.org/10.1007/s11538-018-0516-1

Journal Article Type Article
Acceptance Date Jun 20, 2018
Online Publication Date Oct 5, 2018
Publication Date 2019-01
Deposit Date Jul 31, 2018
Publicly Available Date Mar 28, 2024
Journal Bulletin of Mathematical Biology
Print ISSN 0092-8240
Electronic ISSN 0092-8240
Publisher Springer Verlag
Peer Reviewed Peer Reviewed
Volume 81
Issue 1
Pages 7–38
DOI https://doi.org/10.1007/s11538-018-0516-1
Keywords Immunology; General Biochemistry, Genetics and Molecular Biology; Computational Theory and Mathematics; General Neuroscience; Pharmacology; General Agricultural and Biological Sciences; General Mathematics; General Environmental Science
Public URL https://nottingham-repository.worktribe.com/output/940049
Publisher URL https://link.springer.com/article/10.1007%2Fs11538-018-0516-1
Additional Information Received: 17 November 2017; Accepted: 31 July 2018; First Online: 5 October 2018

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