用单细胞TNF-NF-κB信号数据建模细胞决策的尼曼-皮尔森框架
bioRxiv : the preprint server for biology
|January 9, 2026
概括
这项研究引入了一个尼曼-皮尔森 (NP) 检测框架来分析细胞信号噪声. 该框架量化了细胞决策的准确性,识别了异常信号如何导致疾病.
科学领域:
- 细胞生物学 细胞生物学
- 系统生物学 系统生物学
- 统计建模 统计建模
背景情况:
- 在噪音信号下,细胞的决策可能导致病理状况.
- NF-κB通路对于细胞存活,细胞亡,免疫信号和应激反应至关重要.
- 了解细胞决策准确性对于识别疾病机制至关重要.
研究的目的:
- 开发一个尼曼-皮尔森 (NP) 检测理论框架,用于分析单细胞对细胞反应的测量.
- 量化细胞信号通路的性能,特别是NF-κB对瘤缩因子 (TNF) 的反应.
- 评估噪音和干扰如何影响细胞决策,并可能导致病理.
主要方法:
- 将尼曼-皮尔森 (NP) 检测理论框架应用于对NF-κB反应的单细胞实验测量.
- 模拟日志响应作为多变量高斯分布.
- 计算的最佳值,检测概率 (P_D) - 误报概率 (P_FA) 的权衡,以及不同时间点的接收器运行特征 (ROC) 曲线.
主要成果:
- 该NP框架成功地捕获了预期的生物反应,显示P_D随着更高的TNF剂量增加.
- 与A20缺乏细胞相比,野生类型的细胞表现出更高的性能.
- 结合来自多个时间点的数据 (双变量分析) 提高了检测准确度.
- 该框架确定了由于干扰而导致决策质量下降的条件.
结论:
- NP检测框架提供了路径性能和失败的定量得分.
- 这种方法将杂的单细胞数据转化为可操作的指标,用于比较条件和干扰.
- 该框架可以帮助解释细胞决策如何偏向病理.
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