物理学进展 ›› 2023, Vol. 43 ›› Issue (2): 41-55.doi: 10.13725/j.cnki.pip.2023.02.002

所属专题: 2022年, 第42卷

• • 上一篇    

基于活性网络模型的细胞组织模拟

  

  1. 南京大学固体微结构物理国家重点实验室, 人工微结构科学与技术协同创新中心, 南京 210093
  • 出版日期:2023-04-20 发布日期:2023-04-23

Cell Tissue Simulations Based on Active Network Models

  1. National Laboratory of Solid State Microstructures and Department of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210093, China
  • Online:2023-04-20 Published:2023-04-23
  • Supported by:
    National Natural Science Foundation of China (No. 11974175, No. 12174184, No. 12247102, No. 12275127).

摘要:

在过去的十年中, 由于细胞生物学的进步, 将细胞组织作为活性物质的理论研究已经成为软 物质物理学的一个新领域。本文综述了近年来基于细胞组织活性网络(AN)模型的理论进展。在介 观尺度上, 细胞组织的非平衡动力学主要由细胞的自我推进和其他非推进活动驱动, 如主动收缩力 或细胞张力/体积振荡。自推进细胞的 AN 模型可以再现体内细胞组织的复杂动力学, 如活性/黏 附驱动的固液转变、集群和活性湍流。结合细胞张力波动的 AN 模型还可以模拟果蝇胚胎细胞中 的体积振荡波, 并预测张力波动驱动的细胞组织固液转变。利用 AN 模型研究细胞组织的结构相 变和密度涨落, 加深了我们对这一独特的非平衡软物质系统的认识。

关键词: 细胞组织, 活性网络模型, 动力学与转变

Abstract:

In the last decade, motivated by advances in cell biology, theoretical studies of the cell tissue as active matter have emerged as a new area in soft matter physics. This article reviews recent theoretical progresses based on the active network (AN) model of cell tissue. In the mesoscopic scale, the non-equilibrium dynamics of cell tissue is mainly driven by the self-propulsion of cells and non-propulsion activities, like active contractility or cellular tension/volume oscillation. AN models of self-propelled cells can reproduce complex dynamics of cell tissue in vivio, such as activity/adhesion driven solid-liquid transition, flocking and active turbulence. The AN model incorporating cellular tension fluctuation can also simulate the cell volume oscillation waves in embryo of Drosophila, and predict the fluctuation-driven solid-liquid transition of cell tissue. The structural phase transition and density fluctuation of cell tissue were also studied by using AN models, which deepens our understanding of this unique non-equilibrium soft matter system.

Key words: cell tissue, active network models, dynamic and transition

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