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Bioengineering 2017, 4(1), 16;

An Attempt to Predict the Preferential Cellular Orientation in Any Complex Mechanical Environment

CNRS, LEMTA, UMR 7563, Université de Lorraine, 2 Avenue de la Forêt de Haye, 54502 Vandoeuvre-lès-Nancy, France
Author to whom correspondence should be addressed.
Academic Editor: Gou-Jen Wang
Received: 23 November 2016 / Revised: 6 February 2017 / Accepted: 20 February 2017 / Published: 22 February 2017
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Cells respond to their mechanical environment in different ways: while their response in terms of differentiation and proliferation has been widely studied, the question of the direction in which cells align when subject to a complex mechanical loading in a 3D environment is still widely open. In the present paper, we formulate the hypothesis that the cells orientate in the direction of unitary stretch computed from the right Cauchy-Green tensor in a given mechanical environment. The implications of this hypothesis are studied in different simple cases corresponding to either the available in vitro experimental data or physiological conditions, starting from finite element analysis results to computed preferential cellular orientation. The present contribution is a first step to the formulation of a deeper understanding of the orientation of cells within or at the surface of any 3D scaffold subject to any complex load. It is believed that these initial preferential directions have strong implications as far as the anisotropy of biological structures is concerned. View Full-Text
Keywords: mechanobiology; cell mechanics; mechanosensing; scaffold; numerical simulation mechanobiology; cell mechanics; mechanosensing; scaffold; numerical simulation

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Laurent, C.P.; Ganghoffer, J.-F.; Rahouadj, R. An Attempt to Predict the Preferential Cellular Orientation in Any Complex Mechanical Environment. Bioengineering 2017, 4, 16.

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