发表机构
Mechanobiology Institute, National University of Singapore; School of Biochemistry, University of Bristol; School of Mathematics, University of Bristol（新加坡国立大学生物力学研究所; 布里斯托大学生物化学学院; 布里斯托大学数学学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究提出一个理论框架，通过将细胞建模为软椭球体并推导相关函数，量化上皮组织中细胞形状和密度的波动，从而确定组织刚度等关键参数。
AI 中文摘要
控制细胞形状的变化对于许多生物过程至关重要，例如组织发育和伤口愈合。组织通常具有异质性，包含多种细胞形状和大小。特别令人感兴趣的是与平均细胞形状和大小的局部偏差。这些波动可能延伸并跨组织传播，可能为组织特性（如有效“刚度”或刚性变化）提供有价值的见解。在本研究中，我们提出了一个理论框架，用于捕捉组织内上皮细胞形状的动态，包括其平均行为和波动模式。我们将细胞建模为具有不同大小和纵横比的相互作用软椭球体。对我们的模型进行粗粒化处理，我们获得了一组连续随机微分方程，从中推导出时空相关函数。这些相关函数与我们来自果蝇蛹翅发育过程的实验数据相拟合。从相关函数中，可以确定代表主动细胞形状变化和有效组织“刚度”的关键参数。
英文摘要
Controlling changes in cell shape are crucial for many biological processes, such as tissue development and wound healing. Tissues typically are heterogeneous with a variety of cell shapes and sizes. Of particular interest are local deviations from an average cell shape and size. These fluctuations may extend and transmit across tissues, potentially offering valuable insights into tissue characteristics such as variations in effective "stiffness" or rigidity. In this study, we present a theoretical framework that captures the dynamics of epithelial cell shapes within tissue, incorporating both their average behaviour and fluctuation patterns. We model cells as interacting soft ellipsoids of varying size and aspect ratio. Coarse-graining our model, we obtain a set of continuum stochastic differential equations from which we derive spatial-temporal correlation functions. These correlation functions fit with our experimental data from the developmental process of the \textit{Drosophila} pupal wing. From the correlation functions, critical parameters representing active cell shape changes and effective tissue "stiffness" can be determined.
