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A population dynamics model of cell-cell adhesion incorporating population pressure and density saturation

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Title: A population dynamics model of cell-cell adhesion incorporating population pressure and density saturation
Authors: Carrillo de la Plata, JA
Murakawa, H
Sato, M
Togas, H
Trush, O
Item Type: Journal Article
Abstract: We discuss several continuum cell-cell adhesion models based on the underlying microscopic assumptions. We propose an improvement on these models leading to sharp fronts and intermingling invasion fronts between different cell type populations. The model is based on basic principles of localized repulsion and nonlocal attraction due to adhesion forces at the microscopic level. The new model is able to capture both qualitatively and quantitatively experiments by Katsunuma et al. (2016) [J. Cell Biol. 212(5), pp. 561–575]. We also review some of the applications of these models in other areas of tissue growth in developmental biology. We finally explore the resulting qualitative behavior due to cell-cell repulsion.
Issue Date: 7-Aug-2019
Date of Acceptance: 29-Apr-2019
URI: http://hdl.handle.net/10044/1/69273
DOI: 10.1016/j.jtbi.2019.04.023
ISSN: 0022-5193
Publisher: Elsevier
Start Page: 14
End Page: 24
Journal / Book Title: Journal of Theoretical Biology
Volume: 474
Copyright Statement: © 2019 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
Funder's Grant Number: EP/P031587/1
Keywords: Science & Technology
Life Sciences & Biomedicine
Biology
Mathematical & Computational Biology
Life Sciences & Biomedicine - Other Topics
Cell-cell adhesion
Cell sorting
Mathematical model
TISSUE RECONSTRUCTION
DISSOCIATED CELLS
INTERACTING PARTICLES
NONLOCAL MODELS
AGGREGATION
MECHANISM
PATTERN
NECTIN
LONG
SIMULATION
Cell sorting
Cell-cell adhesion
Mathematical model
01 Mathematical Sciences
06 Biological Sciences
08 Information and Computing Sciences
Evolutionary Biology
Publication Status: Published
Online Publication Date: 2019-05-03
Appears in Collections:Applied Mathematics and Mathematical Physics
Faculty of Natural Sciences
Mathematics