Lushnikov Pavel M, Chen Nan, Alber Mark
Department of Mathematics and Statistics, University of New Mexico, Albuquerque, New Mexico 87131, USA.
Phys Rev E Stat Nonlin Soft Matter Phys. 2008 Dec;78(6 Pt 1):061904. doi: 10.1103/PhysRevE.78.061904. Epub 2008 Dec 3.
A connection is established between discrete stochastic model describing microscopic motion of fluctuating cells, and macroscopic equations describing dynamics of cellular density. Cells move towards chemical gradient (process called chemotaxis) with their shapes randomly fluctuating. Nonlinear diffusion equation is derived from microscopic dynamics in dimensions one and two using excluded volume approach. Nonlinear diffusion coefficient depends on cellular volume fraction and it is demonstrated to prevent collapse of cellular density. A very good agreement is shown between Monte Carlo simulations of the microscopic cellular Potts model and numerical solutions of the macroscopic equations for relatively large cellular volume fractions. Combination of microscopic and macroscopic models were used to simulate growth of structures similar to early vascular networks.
在描述波动细胞微观运动的离散随机模型与描述细胞密度动态的宏观方程之间建立了联系。细胞朝着化学梯度移动(此过程称为趋化作用),其形状随机波动。利用排除体积法从一维和二维的微观动力学中推导非线性扩散方程。非线性扩散系数取决于细胞体积分数,并且已证明它能防止细胞密度的坍塌。对于相对较大的细胞体积分数,微观细胞Potts模型的蒙特卡罗模拟与宏观方程的数值解之间显示出非常好的一致性。微观和宏观模型相结合用于模拟类似于早期血管网络的结构生长。