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通过计算模拟理解内皮糖萼在机械转导中的作用:一篇综述短文

Understanding the Role of Endothelial Glycocalyx in Mechanotransduction via Computational Simulation: A Mini Review.

作者信息

Jiang Xi Zhuo, Luo Kai H, Ventikos Yiannis

机构信息

School of Mechanical Engineering and Automation, Northeastern University, Shenyang, China.

Department of Mechanical Engineering, University College London, London, United Kingdom.

出版信息

Front Cell Dev Biol. 2021 Aug 17;9:732815. doi: 10.3389/fcell.2021.732815. eCollection 2021.

Abstract

Endothelial glycocalyx (EG) is a forest-like structure, covering the lumen side of blood vessel walls. EG is exposed to the mechanical forces of blood flow, mainly shear, and closely associated with vascular regulation, health, diseases, and therapies. One hallmark function of the EG is mechanotransduction, which means the EG senses the mechanical signals from the blood flow and then transmits the signals into the cells. Using numerical modelling methods or experiments to investigate EG-related topics has gained increasing momentum in recent years, thanks to tremendous progress in supercomputing. Numerical modelling and simulation allows certain very specific or even extreme conditions to be fulfilled, which provides new insights and complements experimental observations. This mini review examines the application of numerical methods in EG-related studies, focusing on how computer simulation contributes to the understanding of EG as a mechanotransducer. The numerical methods covered in this review include macroscopic (i.e., continuum-based), mesoscopic [e.g., lattice Boltzmann method (LBM) and dissipative particle dynamics (DPD)] and microscopic [e.g., molecular dynamics (MD) and Monte Carlo (MC) methods]. Accounting for the emerging trends in artificial intelligence and the advent of exascale computing, the future of numerical simulation for EG-related problems is also contemplated.

摘要

内皮糖萼(EG)是一种类似森林的结构,覆盖在血管壁的管腔侧。EG暴露于血流的机械力之下,主要是剪切力,并且与血管调节、健康、疾病及治疗密切相关。EG的一个标志性功能是机械转导,即EG感知来自血流的机械信号,然后将这些信号传递到细胞中。近年来,借助超级计算技术的巨大进步,使用数值建模方法或实验来研究与EG相关的课题越来越受到关注。数值建模和模拟能够实现某些非常特殊甚至极端的条件,这为理解相关问题提供了新的见解,并补充了实验观察结果。本综述探讨了数值方法在与EG相关研究中的应用,重点关注计算机模拟如何有助于理解EG作为一种机械转导器的作用。本综述涵盖的数值方法包括宏观(即基于连续介质的)、介观[例如格子玻尔兹曼方法(LBM)和耗散粒子动力学(DPD)]以及微观[例如分子动力学(MD)和蒙特卡洛(MC)方法]。考虑到人工智能的发展趋势和百亿亿次计算的出现前景,本文还对与EG相关问题的数值模拟未来发展进行了展望。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/512b/8415899/1a9e12ab3d92/fcell-09-732815-g001.jpg

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