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IMAGE- AND NUMERICS-BASED ANALYSIS OF CONSTITUTIVE PROPERTIES OF CELLULAR SRUCTURES

机译:基于图像和数值的蜂窝结构组成特性分析

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External forces, cell adhesion and soluble signaling molecules influence fundamental functions of cells like shape, migration, proliferation or differentiation. Thus, investigating how mechanical forces affect 3D cell structure and function is of crucial significance in order to gain a better understanding healthy and malignant cell behavior during embryogenesis, regeneration or malignancy [1]. Micromanipulation of cells in a controlled environment is a widely used approach for understanding cellular responses with respect to external mechanical forces. While experimental data provide optical information about the overall cell shape, the 3D deformation state of intracellular structures is not accessible by direct observations and measurements. However, the continuous description of the intracellular deformation state can be calculated as a numerical solution of the boundary value problem given by the partial differential equations of structural mechanics, including a set of canonic material constants (stiffness, compressibility), and the boundary conditions derived from time series of images, e.g. change of visible cell contours. The main idea of our approach is to reformulate the problem of finding optimal modeling parameters as an image registration problem. That is the optimal set of modeling parameters corresponds to the minimum of a suitable similarity measure between computationally predicted and experimentally observed deformations. In this article, we focus on the numerical analysis of uniaxial stretching of a rat embryonic fibroblast 52 (REF 52) based on a series of 2D images reflecting the successive alteration of cell contours during deformation. The goal of this study consists in finding an optimal set of material constants within a non-linear hyperelastic material law, which is able to reproduce results of experimental observations.
机译:外力,细胞粘附和可溶信号分子影响细胞的基本功能,如形状,迁移,增殖或分化。因此,研究机械力如何影响3D细胞结构,功能是至关重要的,以便在胚胎发生,再生或恶性肿瘤期间更好地理解健康和恶性细胞行为[1]。受控环境中细胞的微观素是一种广泛使用的方法,用于了解对外部机械力的蜂窝反应。虽然实验数据提供了关于整体细胞形状的光学信息,但是通过直接观察和测量不能通过细胞内结构的3D变形状态。然而,细胞内变形状态的连续描述可以计算为由结构力学的部分微分方程给出的边界值问题的数值解,包括一组码态材料常数(刚度,可压缩性)和衍生的边界条件从时间序列的图像,例如变化可见细胞轮廓。我们方法的主要思想是重构作为图像登记问题的最佳建模参数的问题。这是最佳的建模参数集对应于计算预测和实验观察的变形之间的合适相似度测量的最小值。在本文中,我们专注于基于一系列2D图像的大鼠胚胎成纤维细胞52(REF 52)的单轴拉伸的数值分析,反映变形期间细胞轮廓的连续改变。本研究的目标包括在非线性超弹性材料法中找到最佳的材料常数,能够再现实验观察结果。

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