提出细胞力测量的统计重构框架，实现误差量化与假设检验
How accurate is mechanobiology? A statistical test of cell force
- 构建通用反演框架，为微尺度细胞力提供误差条与置信区域
- 首次实现对细胞力学实验中抽象问题的统计假设检验
- 适用于牵引力显微镜等间接测量，推动机制生物学可信度提升
机械生物学日益受到重视，因其揭示了物理力在生物功能中的基础作用。由于生物实验难以直接使用物理探针，微尺度力常通过逆问题（如牵引力显微镜）间接测量，但这类结果缺乏误差条、置信区间或p值。本文旨在揭示此问题，并提出一种通用重构框架作为初步解决方案。该框架使复杂实验问题可进行统计假设检验，为机制生物学的定量分析提供新工具。
原文摘要 · Abstract (English)
Mechanobiology is gaining more and more traction as the fundamental role of physical forces in biological function becomes clearer. Forces at the microscale are often measured indirectly using inverse problems such as Traction Force Microscopy because biological experiments are hard to access with physical probes. In contrast with the experimental nature of biology and physics, these measurements do not come with error bars, confidence regions, or p-values. The aim of this manuscript is to publicize this issue and to propose a first step towards a remedy therefor in the form of a general reconstruction framework. We also show that this opens the door to hypothesis testing of seemingly abstract experimental questions.
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