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建模非局部细胞-细胞黏附:一种多尺度方法。

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

机构信息

School of Mathematics and Physics, Queen's University Belfast, University Road, Belfast, BT7 1NN, Northern Ireland, UK.

School of Mathematics, Watson Building, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK.

出版信息

J Math Biol. 2024 Apr 3;88(5):55. doi: 10.1007/s00285-024-02079-8.

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.

摘要

细胞间的黏附在多细胞生物的发育和维持中起着至关重要的作用。其功能之一是调节细胞迁移,例如在胚胎发生或癌症中发生的迁移。在这项工作中,我们开发了一种通用的多尺度方法来模拟移动的自粘细胞群体,该方法将确定性粘附驱动运动成分的精细微观描述与随机速度跳跃过程的有效介观表示相结合。这种方法产生了以具有多个非局部性的动力学输运方程形式出现的介观模型。随后的抛物线和双曲缩放产生了具有非局部粘附和近视扩散的一般类方程,其中一个特例是 Armstrong 等人提出的经典宏观模型(J Theoret Biol 243(1):98-113,2006)。我们的模拟表明了这两种运动效应的组合如何展开。细胞-细胞黏附依赖于亚细胞细胞黏附分子的结合。我们的方法方便地适用于捕捉这种微观效应。在宏观尺度上,这会导致一个与细胞密度方程耦合的新型非线性积分方程。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37ca/10991076/5f5c107c31f5/285_2024_2079_Fig1_HTML.jpg

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