基于临界慢化理论的中医"未病"状态识别建模研究初探
Preliminary modeling study on the identification of "pre-disease" state in traditional Chinese medicine based on the theory of critical slowing down
王诗尧 1石康乐 2雷聪 3杨方燕 1孟庆刚1
作者信息
- 1. 北京中医药大学 北京 100029
- 2. 中国科学院大学
- 3. 黑龙江中医药大学
- 折叠
摘要
中医"未病"理论关注从健康到疾病动态、连续的演化特点,重视从健康到疾病复杂、渐变演化过程中的早期辨识和干预.从系统整体性、演化性角度来看,"未病"理论和复杂性科学具有相同本质的健康观和疾病观——将机体视为连续、动态变化的复杂系统,呈现"稳态-失稳态-相变-另一稳态"的非线性特点.本文从复杂性科学非线性动力学视角,运用临界慢化理论阐释中医未病-已病演化规律的科学内涵,并基于该理论及其发展产生的动态网络生物标志物方法,结合中医四诊合参的宏观体征及包含转录组学和微生物组学的微观特征,提出融合宏观、微观多层级信息,构建具有中医诊疗特点的"未病"临界状态识别模型,为复杂疾病早期预警提供新视角和新方法.
Abstract
The "pre-disease" theory of traditional Chinese medicine focuses on the dynamic and continuous evolution from health to disease, and emphasizes early identification and intervention in the complex and gradual process of evolution from health to disease. The "pre-disease" theory and complexity science share the same perspective on health and disease from the standpoint of features of the dynamic evolution and holism, i. e., life is considered as a complex system with ongoing dynamic changes, which exhibit the nonlinear features of " homeostasis-destabilization-phase transition-another homeostasis". In this paper, from the perspective of nonlinear dynamics in complexity science, we explain the scientific connotation of the evolution law of "pre-disease"-disease based on the theory of critical slowing down in traditional Chinese medicine. Based on the theory of critical slowing down and the dynamic network biomarker method generated by its development, combined with the macro signs of comprehensive analysis of data gained by four diagnostic method and the micro features including transcriptomics and the microbiomics, this paper proposes to integrate macro and micro multi-hierarchy information to construct a "pre-disease" critical slowing down identification model with the characteristics of traditional Chinese medicine diagnosis and treatment, which provides a new perspective and method for the early warning of complex diseases.
关键词
未病/中医/临界慢化/复杂系统/模型框架/动态网络生物标志物Key words
pre-disease/traditional Chinese medicine/critical slowing down/complex system/model framework/dynamic network biomarkers引用本文复制引用
基金项目
国家自然科学基金(82174530)
中国科学院大学优秀青年教师科研能力提升项目(E0E48979)
出版年
2024
国家科技期刊平台
NSTL
万方数据