Literature DB >> 20441739

A computer model of engineered cardiac monolayers.

Jong M Kim1, Nenad Bursac, Craig S Henriquez.   

Abstract

Engineered monolayers created using microabrasion and micropatterning methods have provided a simplified in vitro system to study the effects of anisotropy and fiber direction on electrical propagation. Interpreting the behavior in these culture systems has often been performed using classical computer models with continuous properties. However, such models do not account for the effects of random cell shapes, cell orientations, and cleft spaces inherent in these monolayers on the resulting wavefront conduction. This work presents a novel methodology for modeling a monolayer of cardiac tissue in which the factors governing cell shape, cell-to-cell coupling, and degree of cleft space are not constant but rather are treated as spatially random with assigned distributions. This modeling approach makes it possible to simulate wavefront propagation in a manner analogous to performing experiments on engineered monolayer tissues. Simulated results are compared to previously published measured data from monolayers used to investigate the role of cellular architecture on conduction velocities and anisotropy ratios. We also present an estimate for obtaining the electrical properties from these networks and demonstrate how variations in the discrete cellular architecture affect the macroscopic conductivities. The simulations support the common assumption that under normal ranges of coupling strength, tissues with relatively uniform distributions of cell shapes and connectivity can be represented using continuous models with conductivities derived from random discrete cellular architecture using either global or local estimates. The results also reveal that in the presence of abrupt changes in cell orientation, local estimates of tissue properties predict smoother changes in conductivity that may not adequately predict the discrete nature of propagation at the transition sites. Copyright (c) 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 20441739      PMCID: PMC2862160          DOI: 10.1016/j.bpj.2010.01.008

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  28 in total

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  7 in total

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