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上皮伤口闭合的计算建模与模拟。

Computational modeling and simulation of epithelial wound closure.

机构信息

Department of Mechanical Engineering, University of Texas at San Antonio, One UTSA Circle, San Antonio, TX, 78249, USA.

出版信息

Sci Rep. 2023 Apr 17;13(1):6265. doi: 10.1038/s41598-023-33111-4.

Abstract

Wounds in the epithelium may lead to serious injurious events or chronic inflammatory diseases, however, multicellular organisms have the ability to self-repair wounds through the movement of epithelial cell toward the wound area. Despite intensive studies exploring the mechanism of wound closure, the role of mechanics in epithelial wound closure is still not well explained. In order to investigate the role of mechanical properties on wound closure process, a three-dimensional continuum physics-based computational model is presented in this study. The model takes into account the material property of the epithelial cell, intercellular interactions between neighboring cells at cell-cell junctions, and cell-substrate adhesion between epithelial cells and ECM. Through finite element simulation, it is found that the closure efficiency is related to the initial gap size and the intensity of lamellipodial protrusion. It is also shown that cells at the wound edge undergo higher stress compared with other cells in the epithelial monolayer, and the cellular normal stress dominates over the cellular shear stress. The model presented in this study can be employed as a numerical tool to unravel the mechanical principles behind the complex wound closure process. These results might have the potential to improve effective wound management and optimize the treatment.

摘要

上皮组织损伤可能会导致严重的伤害性事件或慢性炎症性疾病,然而,多细胞生物具有通过上皮细胞向伤口区域移动来自我修复伤口的能力。尽管有大量研究探索伤口闭合的机制,但机械因素在上皮伤口闭合中的作用仍未得到很好的解释。为了研究力学性质对上皮伤口闭合过程的作用,本研究提出了一个基于三维连续体物理的计算模型。该模型考虑了上皮细胞的材料特性、细胞-细胞连接处相邻细胞之间的细胞间相互作用,以及上皮细胞与细胞外基质之间的细胞-基底粘附。通过有限元模拟,发现闭合效率与初始间隙大小和片状伪足的突起强度有关。还表明,与上皮单层中的其他细胞相比,伤口边缘的细胞承受更高的应力,并且细胞法向应力占主导地位,超过细胞切向应力。本研究提出的模型可以作为一种数值工具,揭示复杂伤口闭合过程背后的力学原理。这些结果有可能改善有效的伤口管理和优化治疗效果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/666d/10110613/6dc3ec05c73f/41598_2023_33111_Fig1_HTML.jpg

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