Literature DB >> 29977132

Bond graph modelling of the cardiac action potential: implications for drift and non-unique steady states.

Michael Pan1, Peter J Gawthrop1, Kenneth Tran2, Joseph Cursons3,4, Edmund J Crampin1,5,6.   

Abstract

Mathematical models of cardiac action potentials have become increasingly important in the study of heart disease and pharmacology, but concerns linger over their robustness during long periods of simulation, in particular due to issues such as model drift and non-unique steady states. Previous studies have linked these to violation of conservation laws, but only explored those issues with respect to charge conservation in specific models. Here, we propose a general and systematic method of identifying conservation laws hidden in models of cardiac electrophysiology by using bond graphs, and develop a bond graph model of the cardiac action potential to study long-term behaviour. Bond graphs provide an explicit energy-based framework for modelling physical systems, which makes them well suited for examining conservation within electrophysiological models. We find that the charge conservation laws derived in previous studies are examples of the more general concept of a 'conserved moiety'. Conserved moieties explain model drift and non-unique steady states, generalizing the results from previous studies. The bond graph approach provides a rigorous method to check for drift and non-unique steady states in a wide range of cardiac action potential models, and can be extended to examine behaviours of other excitable systems.

Entities:  

Keywords:  bond graph; cardiac electrophysiology; conservation law

Year:  2018        PMID: 29977132      PMCID: PMC6030650          DOI: 10.1098/rspa.2018.0106

Source DB:  PubMed          Journal:  Proc Math Phys Eng Sci        ISSN: 1364-5021            Impact factor:   2.704


  41 in total

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2.  Energy balance for analysis of complex metabolic networks.

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Authors:  Peter J Gawthrop
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Review 4.  Identification of sodium-calcium exchange current in single ventricular cells of guinea-pig.

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Review 5.  Network thermodynamics: dynamic modelling of biophysical systems.

Authors:  G F Oster; A S Perelson; A Katchalsky
Journal:  Q Rev Biophys       Date:  1973-02       Impact factor: 5.318

Review 6.  How to deal with parameters for whole-cell modelling.

Authors:  Ann C Babtie; Michael P H Stumpf
Journal:  J R Soc Interface       Date:  2017-08-02       Impact factor: 4.118

7.  Energy-based analysis of biomolecular pathways.

Authors:  Peter J Gawthrop; Edmund J Crampin
Journal:  Proc Math Phys Eng Sci       Date:  2017-06-21       Impact factor: 2.704

8.  A dynamic model of excitation-contraction coupling during acidosis in cardiac ventricular myocytes.

Authors:  Edmund J Crampin; Nicolas P Smith
Journal:  Biophys J       Date:  2006-02-10       Impact factor: 4.033

9.  Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks.

Authors:  Hulda S Haraldsdóttir; Ronan M T Fleming
Journal:  PLoS Comput Biol       Date:  2016-11-21       Impact factor: 4.475

10.  Regulation of cardiac cellular bioenergetics: mechanisms and consequences.

Authors:  Kenneth Tran; Denis S Loiselle; Edmund J Crampin
Journal:  Physiol Rep       Date:  2015-07
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  4 in total

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Authors:  Niloofar Shahidi; Michael Pan; Soroush Safaei; Kenneth Tran; Edmund J Crampin; David P Nickerson
Journal:  PLoS Comput Biol       Date:  2021-05-13       Impact factor: 4.475

2.  Network Thermodynamical Modeling of Bioelectrical Systems: A Bond Graph Approach.

Authors:  Peter J Gawthrop; Michael Pan
Journal:  Bioelectricity       Date:  2021-03-16

3.  Modular assembly of dynamic models in systems biology.

Authors:  Michael Pan; Peter J Gawthrop; Joseph Cursons; Edmund J Crampin
Journal:  PLoS Comput Biol       Date:  2021-10-13       Impact factor: 4.475

4.  A Parameter Representing Missing Charge Should Be Considered when Calibrating Action Potential Models.

Authors:  Yann-Stanislas H M Barral; Joseph G Shuttleworth; Michael Clerx; Dominic G Whittaker; Ken Wang; Liudmila Polonchuk; David J Gavaghan; Gary R Mirams
Journal:  Front Physiol       Date:  2022-04-26       Impact factor: 4.755

  4 in total

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