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弹性运动细胞的尖锐界面模型。

Sharp interface model for elastic motile cells.

作者信息

Bresler Yony, Palmieri Benoit, Grant Martin

机构信息

Department of Physics, McGill University, 3600 University Montréal, H3A 2T8, Québec, Canada.

出版信息

Eur Phys J E Soft Matter. 2019 May 3;42(5):52. doi: 10.1140/epje/i2019-11815-x.

Abstract

In order to study the effect of cell elastic properties on the behavior of assemblies of motile cells, this paper describes an alternative to the cell phase field (CPF) we have previously proposed. The CPF is a multi-scale approach to simulating many cells which tracked individual cells and allowed for large deformations. Though results were largely in agreement with experiment that focus on the migration of a soft cancer cell in a confluent layer of normal cells, simulations required large computing resources, making a more detailed study unfeasible. In this work we derive a sharp interface limit of CPF, including all interactions and parameters. This new model scales linearly with both system and cell size, compared to our original CPF implementation, which is quadratic in cell size, this gives rise to a considerable speedup, which we discuss in the article. We demonstrate that this model captures a similar behavior and allows us to obtain new results that were previously intractable. We obtain the full velocity distribution for a large range of degrees of confluence, [Formula: see text], and show regimes where its tail is heavier and lighter than a normal distribution. Furthermore, we fully characterize the velocity distribution with a single parameter, and its dependence on [Formula: see text] is fully determined. Finally, cell motility is shown to linearly decrease with increasing [Formula: see text], consistent with previous theoretical results.

摘要

为了研究细胞弹性特性对运动细胞聚集体行为的影响,本文介绍了一种替代我们之前提出的细胞相场(CPF)的方法。CPF是一种模拟多个细胞的多尺度方法,它能追踪单个细胞并允许大变形。尽管结果在很大程度上与聚焦于软癌细胞在正常细胞汇合层中迁移的实验一致,但模拟需要大量计算资源,使得更详细的研究变得不可行。在这项工作中,我们推导了CPF的尖锐界面极限,包括所有相互作用和参数。与我们原来的CPF实现方式相比,新模型与系统和细胞大小均呈线性比例关系,原来的实现方式在细胞大小方面是二次方的,这带来了显著的加速,我们将在文中进行讨论。我们证明该模型捕捉到了类似的行为,并使我们能够获得以前难以处理的新结果。我们获得了大范围汇合度[公式:见正文]下的完整速度分布,并展示了其尾部比正态分布更重和更轻的区域。此外,我们用一个参数完全表征了速度分布,并且完全确定了它对[公式:见正文]的依赖性。最后,结果表明细胞运动性随[公式:见正文]的增加而线性下降,这与之前的理论结果一致。

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