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Aggregation dynamics of active cells on non-adhesive substrate.
Physical Biology ( IF 2.0 ) Pub Date : 2019-05-03 , DOI: 10.1088/1478-3975/ab1e76
Debangana Mukhopadhyay 1 , Rumi De
Affiliation  

Cellular self-assembly and organization are fundamental steps for the development of biological tissues. In this paper, within the framework of a cellular automata model, we address how an ordered tissue pattern spontaneously emerges from a randomly migrating single cell population without the influence of any external cues. This model is based on the active motility of cells and their ability to reorganize due to cell-cell cohesivity as observed in experiments. Our model successfully emulates the formation of nascent clusters and also predicts the temporal evolution of aggregates that leads to the compact tissue structures. Moreover, the simulations also capture several dynamical properties of growing aggregates, such as, the rate of cell aggregation and non-monotonic growth of the aggregate area which show a good agreement with the existing experimental observations. We further investigate the time evolution of the cohesive strength, and the compactness of aggregates, and also study the ruggedness of the growing structures by evaluating the fractal dimension to get insights into the complexity of tumorous tissue growth which were hitherto unexplored.

中文翻译:

活性细胞在非粘性基质上的聚集动力学。

细胞的自组装和组织是生物组织发展的基本步骤。在本文中,在细胞自动机模型的框架内,我们解决了有序组织模式是如何从随机迁移的单个细胞群体中自发出现的,而不受任何外部提示的影响。如在实验中观察到的那样,该模型基于细胞的主动运动及其由于细胞-细胞内聚力而重组的能力。我们的模型成功地模拟了新生簇的形成,并预测了导致紧密组织结构的聚集体的时间演变。此外,模拟还捕获了聚集体生长的一些动力学特性,例如,细胞聚集率和聚集区域的非单调增长,与现有的实验观察结果吻合良好。我们进一步研究了内聚强度的时间演变以及聚集体的紧密度,并通过评估分形维数来研究生长结构的坚固性,以了解迄今为止尚未探索的肿瘤组织生长的复杂性。
更新日期:2019-11-01
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