School of Mathematics and Statistics, University of Melbourne, Victoria 3010, Australia.
PLoS One. 2018 Mar 12;13(3):e0193975. doi: 10.1371/journal.pone.0193975. eCollection 2018.
Motivated by in vitro time-lapse images of ovarian cancer spheroids inducing mesothelial cell clearance, the traditional agent-based model of cell migration, based on simple volume exclusion, was extended to include the possibility that a cell seeking to move into an occupied location may push the resident cell, and any cells neighbouring it, out of the way to occupy that location. In traditional discrete models of motile cells with volume exclusion such a move would be aborted. We introduce a new shoving mechanism which allows cells to choose the direction to shove cells that expends the least amount of shoving effort (to account for the likely resistance of cells to being pushed). We call this motility rule 'smart shoving'. We examine whether agent-based simulations of different shoving mechanisms can be distinguished on the basis of single realisations and averages over many realisations. We emphasise the difficulty in distinguishing cell mechanisms from cellular automata simulations based on snap-shots of cell distributions, site-occupancy averages and the evolution of the number of cells of each species averaged over many realisations. This difficulty suggests the need for higher resolution cell tracking.
受卵巢癌细胞球体诱导间皮细胞清除的体外时程图像的启发,我们将传统的基于主体的细胞迁移模型从基于简单体积排除的模型扩展到包括这样一种可能性,即一个试图移动到已占用位置的细胞可能会推动驻留细胞和其相邻的任何细胞,从而占据该位置。在具有体积排除的传统离散可动细胞模型中,这样的移动将被中止。我们引入了一种新的推动机制,允许细胞选择推动花费最小推动努力的细胞的方向(以考虑到细胞可能对被推动的抵抗力)。我们将此运动规则称为“智能推动”。我们检查不同推动机制的基于主体的模拟是否可以基于单个实现和许多实现的平均值来区分。我们强调了从细胞分布的快照、站点占用平均值以及每个物种的细胞数量随时间的演变来区分细胞机制和元胞自动机模拟的困难。这种困难表明需要更高分辨率的细胞跟踪。