Modelling non-local cell-cell adhesion: a multiscale approach

IF 2.2 4区 数学 Q2 BIOLOGY
Anna Zhigun, Mabel Lizzy Rajendran
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引用次数: 0

Abstract

Cell-cell adhesion plays a vital role in the development and maintenance of multicellular organisms. One of its functions is regulation of cell migration, such as occurs, e.g. during embryogenesis or in cancer. In this work, we develop a versatile multiscale approach to modelling a moving self-adhesive cell population that combines a careful microscopic description of a deterministic adhesion-driven motion component with an efficient mesoscopic representation of a stochastic velocity-jump process. This approach gives rise to mesoscopic models in the form of kinetic transport equations featuring multiple non-localities. Subsequent parabolic and hyperbolic scalings produce general classes of equations with non-local adhesion and myopic diffusion, a special case being the classical macroscopic model proposed in Armstrong et al. (J Theoret Biol 243(1): 98–113, 2006). Our simulations show how the combination of the two motion effects can unfold. Cell-cell adhesion relies on the subcellular cell adhesion molecule binding. Our approach lends itself conveniently to capturing this microscopic effect. On the macroscale, this results in an additional non-linear integral equation of a novel type that is coupled to the cell density equation.

非局部细胞-细胞粘附建模:一种多尺度方法
细胞-细胞粘附在多细胞生物体的发育和维持过程中发挥着至关重要的作用。其功能之一是调节细胞迁移,例如在胚胎发育或癌症中发生的迁移。在这项研究中,我们开发了一种多功能多尺度方法来模拟移动的自粘性细胞群,这种方法结合了对确定性粘附驱动运动成分的细致微观描述和对随机速度跳跃过程的高效介观表示。这种方法产生了具有多重非局部性的动力学输运方程形式的中观模型。随后的抛物线和双曲线缩放产生了具有非局部粘附和近视扩散的一般方程,Armstrong 等人提出的经典宏观模型就是一个特例(J Theoret Biol 243(1):98-113, 2006).我们的模拟显示了两种运动效应的结合是如何展开的。细胞-细胞粘附依赖于亚细胞细胞粘附分子的结合。我们的方法很容易捕捉到这种微观效应。在宏观尺度上,这将产生一个与细胞密度方程耦合的新型额外非线性积分方程。
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来源期刊
CiteScore
3.30
自引率
5.30%
发文量
120
审稿时长
6 months
期刊介绍: The Journal of Mathematical Biology focuses on mathematical biology - work that uses mathematical approaches to gain biological understanding or explain biological phenomena. Areas of biology covered include, but are not restricted to, cell biology, physiology, development, neurobiology, genetics and population genetics, population biology, ecology, behavioural biology, evolution, epidemiology, immunology, molecular biology, biofluids, DNA and protein structure and function. All mathematical approaches including computational and visualization approaches are appropriate.
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