细胞状态转换的前体:在Notch信号通路中的稳定性,弹性和可预测性
Shankha Narayan Chattopadhyay1, Arvind Kumar Gupta1
1Department of Mathematics, Indian Institute of Technology Ropar, Bara Phool, Rupnagar, Punjab 140001, India.
Chaos (Woodbury, N.Y.)
|March 12, 2026
概括
在Notch信号传导中预测细胞命运过渡是疾病干预的关键. 这项研究使用计算模型和统计措施来识别细胞可塑性的动态生物标志物,揭示混合状态是最适合的.
科学领域:
- 细胞动态和信号通路的细胞动态.
- 计算生物学和系统建模.
- 发现生物标志物用于疾病预测.
背景情况:
- 诺奇信号通路对于发育和平衡至关重要,但其失调与癌症等疾病有关.
- 识别Notch信号转换的可靠标志物对于预测疾病进展和指导治疗至关重要.
- 了解单细胞水平的生物化学过程和细胞噪声对于准确的建模至关重要.
研究的目的:
- 使用计算模型开发Notch信号转换的预测框架.
- 为了研究外部Jagged水平对细胞状态动态的影响.
- 评估各种统计措施作为细胞可塑性的动态生物标志物的有效性.
主要方法:
- 开发了Notch路径的确定性模型,包括受体,配体 (Delta,Jagged) 和NICD.
- 将模型扩展到使用化学主方程将细胞噪声纳入的随机配方.
- 采用双叉分析和随机模拟,分析自相关性,差异和相互信息等统计指标.
主要成果:
- 外部Jagged级别的变化驱动细胞状态过渡 (发送者,接收者,混合状态).
- 统计措施有效地预测了这些转变,尽管复合措施显示了局限性.
- 变性指数在弹性景观评估中表现优于雅可比指数.
- 根据盆地稳定性和潜在井的评估,混合状态被确定为最适合的状态.
结论:
- 可以模拟和预测Notch信号通路中的细胞过渡.
- 统计工具显示为细胞可塑性的动态生物标志物具有前景,特定指标的表现优于其他指标.
- 该研究强调了统计方法在理解复杂的生物系统和疾病状态方面的应用和局限性.
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