Back to Search
Start Over
A Feature Selection-Incorporated Simulation Study to Reveal the Effect of Calcium Ions on Cardiac Repolarization Alternans during Myocardial Ischemia.
- Source :
- Applied Sciences (2076-3417); Aug2024, Vol. 14 Issue 15, p6789, 15p
- Publication Year :
- 2024
-
Abstract
- (1) Background: The main factors and their interrelationships contributing to cardiac repolarization alternans (CRA) remain unclear. This study aimed to elucidate the calcium (Ca<superscript>2+</superscript>)-related mechanisms underlying myocardial ischemia (MI)-induced CRA. (2) Materials and Methods: CRA was induced using S1 stimuli for pacing in an in silico ventricular model with MI. The standard deviations of nine Ca<superscript>2+</superscript>-related subcellular parameters among heartbeats from 100 respective nodes with and without alternans were chosen as features, including the maximum systole and end-diastole and corresponding differences in the Ca<superscript>2+</superscript> concentration in the intracellular region([Ca<superscript>2+</superscript>]<subscript>i</subscript>) and junctional sarcoplasmic reticulum ([Ca<superscript>2+</superscript>]<subscript>jsr</subscript>), as well as the maximum opening of the L-type Ca<superscript>2+</superscript> current (I<subscript>CaL</subscript>) voltage-dependent activation gate (d-gate), maximum closing of the inactivation gate (ff-gate), and the gated channel opening time (GCOT). Feature selection was applied to determine the importance of these features. (3) Results: The major parameters affecting CRA were the differences in [Ca<superscript>2+</superscript>]<subscript>i</subscript> at end-diastole, followed by the extent of d-gate activation and GCOT among beats. (4) Conclusions: MI-induced CRA is primarily characterized by functional changes in Ca<superscript>2+</superscript> re-uptake, leading to alternans of [Ca<superscript>2+</superscript>]<subscript>i</subscript> and subsequent alternans of I<subscript>CaL</subscript>-dependent properties. The combination of computational simulation and machine learning shows promise in researching the underlying mechanisms of cardiac electrophysiology. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20763417
- Volume :
- 14
- Issue :
- 15
- Database :
- Complementary Index
- Journal :
- Applied Sciences (2076-3417)
- Publication Type :
- Academic Journal
- Accession number :
- 178949762
- Full Text :
- https://doi.org/10.3390/app14156789