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首页> 外文期刊>Journal of Mathematical Biology >A Riemannian manifold analysis of endothelial cell monolayer impedance parameter precision
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A Riemannian manifold analysis of endothelial cell monolayer impedance parameter precision

机译:内皮细胞单层阻抗参数精度的黎曼流形分析

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摘要

Endothelial cell adhesion and barrier function play a critical role in many biological and pathophysiological processes. The decomposition of endothelial cell adhesion and barrier function into cell–cell and cell–matrix components using frequency dependent cellular micro-impedance measurements has, therefore, received widespread application. Few if any studies, however, have examined the precision of these model parameters. This study presents a parameter sensitivity analysis of a representative cellular barrier function model using a concise geometric formulation that includes instrumental data acquisition settings. Both model state dependence and instrumental noise distributions are accounted for within the framework of Riemannian manifold theory. Experimentally acquired microimpedance measurements of attached endothelial cells define the model state domain, while experimentally measured noise statistics define the data space Riemannian metric based on the Fisher information matrix. The results of this analysis show that the sensitivity of cell–cell and cell–matrix impedance components are highly model state dependent and several well defined regions of low precision exist. The results of this study further indicate that membrane resistive components can significantly reduce the precision of the remaining parameters in these models.
机译:内皮细胞粘附和屏障功能在许多生物学和病理生理过程中起着至关重要的作用。因此,利用频率依赖性细胞微阻抗测量将内皮细胞粘附和屏障功能分解为细胞-细胞和细胞-基质成分,得到了广泛的应用。但是,很少有研究检查过这些模型参数的精度。这项研究使用简洁的几何公式​​(包括仪器数据采集设置)提出了代表性细胞屏障功能模型的参数敏感性分析。在黎曼流形理论的框架内考虑了模型状态相关性和工具噪声分布。实验获得的附着内皮细胞微阻抗测量值定义了模型状态域,而实验测量的噪声统计数据则基于Fisher信息矩阵定义了数据空间黎曼度量。分析结果表明,单元-单元和单元-矩阵阻抗分量的灵敏度高度依赖于模型状态,并且存在几个定义良好的低精度区域。这项研究的结果进一步表明,膜电阻元件会大大降低这些模型中其余参数的精度。

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