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2
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3
Modulation of fluidic resistance and capacitance for long-term, high-speed feedback control of a microfluidic interface.用于微流体界面长期、高速反馈控制的流体阻力和电容调制。
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A dynamic stochastic model of frequency-dependent stress fiber alignment induced by cyclic stretch.循环拉伸诱导的频率依赖性应力纤维排列的动态随机模型。
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通过粗粒化蒙特卡罗方法研究循环拉伸下肌动蛋白丝网络模型的响应。

Response of an actin filament network model under cyclic stretching through a coarse grained Monte Carlo approach.

机构信息

Lane Center for Computational Biology, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213, USA.

出版信息

J Theor Biol. 2011 Apr 7;274(1):109-19. doi: 10.1016/j.jtbi.2011.01.011. Epub 2011 Jan 15.

DOI:10.1016/j.jtbi.2011.01.011
PMID:21241710
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3501734/
Abstract

Cells are complex, dynamic systems that actively adapt to various stimuli including mechanical alterations. Central to understanding cellular response to mechanical stimulation is the organization of the cytoskeleton and its actin filament network. In this manuscript, we present a minimalistic network Monte Carlo based approach to model actin filament organization under cyclic stretching. Utilizing a coarse-grained model, a filament network is prescribed within a two-dimensional circular space through nodal connections. When cyclically stretched, the model demonstrates that a perpendicular alignment of the filaments to the direction of stretch emerges in response to nodal repositioning to minimize net nodal forces from filament stress states. In addition, the filaments in the network rearrange and redistribute themselves to reduce the overall stress by decreasing their individual stresses. In parallel, we cyclically stretch NIH 3T3 fibroblasts and find a similar cytoskeletal response. With this work, we test the hypothesis that a first-principles mechanical model of filament assembly in a confined space is by itself capable of yielding the remodeling behavior observed experimentally. Identifying minimal mechanisms sufficient to reproduce mechanical influences on cellular structure has important implications in a diversity of fields, including biology, physics, medicine, computer science, and engineering.

摘要

细胞是复杂的动态系统,能够主动适应各种刺激,包括机械改变。理解细胞对机械刺激的反应的核心是细胞骨架及其肌动蛋白丝网络的组织。在本手稿中,我们提出了一种基于最小网络蒙特卡罗的方法来模拟周期性拉伸下肌动蛋白丝的组织。利用粗粒化模型,通过节点连接在二维圆形空间中规定了一个纤维网络。当周期性拉伸时,模型表明,为了最小化纤维应力状态下的净节点力,节点重新定位会导致纤维垂直于拉伸方向排列。此外,网络中的纤维重新排列并重新分布,以通过降低单个纤维的应力来降低整体应力。同时,我们周期性地拉伸 NIH 3T3 成纤维细胞,并发现类似的细胞骨架反应。通过这项工作,我们检验了这样一个假设,即在受限空间中组装纤维的第一性原理力学模型本身就能够产生实验观察到的重塑行为。确定足以重现机械对细胞结构影响的最小机制,在生物学、物理学、医学、计算机科学和工程等多个领域都具有重要意义。