北京中医药大学学报2024，Vol.47Issue(3)：312-319,8.DOI:10.3969/j.issn.1006-2157.2024.03.004
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
摘要
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分类
医药卫生引用本文复制引用
王诗尧,石康乐,雷聪,杨方燕,孟庆刚..基于临界慢化理论的中医"未病"状态识别建模研究初探[J].北京中医药大学学报,2024,47(3):312-319,8.基金项目
国家自然科学基金项目(No.82174530) （No.82174530）
中国科学院大学优秀青年教师科研能力提升项目(No.E0E48979) National Natural Science Foundation of China(No.82174530) （No.E0E48979）
