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Models of collective cell motion for cell populations with different aspect ratio: Diffusion, proliferation and travelling waves

Abstract:
Continuum, partial differential equation models are often used to describe the collective motion of cell populations, with various types of motility represented by the choice of diffusion coefficient, and cell proliferation captured by the source terms. Previously, the choice of diffusion coefficient has been largely arbitrary, with the decision to choose a particular linear or nonlinear form generally based on calibration arguments rather than making any physical connection with the underlying individual-level properties of the cell motility mechanism. In this work we provide a new link between individual-level models, which account for important cell properties such as varying cell shape and volume exclusion, and population-level partial differential equation models. We work in an exclusion process framework, considering aligned, elongated cells that may occupy more than one lattice site, in order to represent populations of agents with different sizes. Three different idealisations of the individual-level mechanism are proposed, and these are connected to three different partial differential equations, each with a different diffusion coefficient; one linear, one nonlinear and degenerate and one nonlinear and nondegenerate. We test the ability of these three models to predict the population-level response of a cell spreading problem for both proliferative and nonproliferative cases. We also explore the potential of our models to predict long time travelling wave invasion rates and extend our results to two-dimensional spreading and invasion. Our results show that each model can accurately predict density data for nonproliferative systems, but that only one does so for proliferative systems. Hence great care must be taken to predict density data with varying cell shape. © 2012 Elsevier B.V. All rights reserved.

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Publisher copy:
10.1016/j.physa.2012.01.009

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Journal:
Physica A: Statistical Mechanics and its Applications More from this journal
Volume:
391
Issue:
14
Pages:
3729-3750
Publication date:
2012-07-15
DOI:
ISSN:
0378-4371


Language:
English
Keywords:
Pubs id:
pubs:325284
UUID:
uuid:6a68e1aa-11d7-4ecf-9b84-3bd617a89065
Local pid:
pubs:325284
Source identifiers:
325284
Deposit date:
2013-11-17

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