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In silico study of multicellular automaticity of heterogeneous cardiac cell monolayers: Effects of automaticity strength and structural linear anisotropy.
- Source :
- PLoS Computational Biology; 3/12/2018, Vol. 14 Issue 3, p1-28, 28p, 3 Diagrams, 2 Charts, 9 Graphs
- Publication Year :
- 2018
-
Abstract
- The biological pacemaker approach is an alternative to cardiac electronic pacemakers. Its main objective is to create pacemaking activity from added or modified distribution of spontaneous cells in the myocardium. This paper aims to assess how automaticity strength of pacemaker cells (i.e. their ability to maintain robust spontaneous activity with fast rate and to drive neighboring quiescent cells) and structural linear anisotropy, combined with density and spatial distribution of pacemaker cells, may affect the macroscopic behavior of the biological pacemaker. A stochastic algorithm was used to randomly distribute pacemaker cells, with various densities and spatial distributions, in a semi-continuous mathematical model. Simulations of the model showed that stronger automaticity allows onset of spontaneous activity for lower densities and more homogeneous spatial distributions, displayed more central foci, less variability in cycle lengths and synchronization of electrical activation for similar spatial patterns, but more variability in those same variables for dissimilar spatial patterns. Compared their isotropic counterparts, in silico anisotropic monolayers had less central foci and displayed more variability in cycle lengths and synchronization of electrical activation for both similar and dissimilar spatial patterns. The present study established a link between microscopic structure and macroscopic behavior of the biological pacemaker, and may provide crucial information for optimized biological pacemaker therapies. [ABSTRACT FROM AUTHOR]
- Subjects :
- HEART cells
AUTOMATICITY (Learning process)
ANISOTROPY
MYOCARDIUM
PACEMAKER cells
Subjects
Details
- Language :
- English
- ISSN :
- 1553734X
- Volume :
- 14
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- PLoS Computational Biology
- Publication Type :
- Academic Journal
- Accession number :
- 128417746
- Full Text :
- https://doi.org/10.1371/journal.pcbi.1005978