“Weibing” in traditional Chinese medicine—biological basis and mathematical representation of disease-susceptible state

IF 14.7 1区 医学 Q1 PHARMACOLOGY & PHARMACY
Wanyang Sun , Rong Wang , Shuhua Ouyang , Wanli Liang , Junwei Duan , Wenyong Gong , Lianting Hu , Xiujuan Chen , Yifang Li , Hiroshi Kurihara , Xinsheng Yao , Hao Gao , Rongrong He
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Abstract

“Weibing” is a fundamental concept in traditional Chinese medicine (TCM), representing a transitional state characterized by diminished self-regulatory abilities without overt physiological or social dysfunction. This perspective delves into the biological foundations and quantifiable markers of Weibing, aiming to establish a research framework for early disease intervention. Here, we propose the “Health Quadrant Classification” system, which divides the state of human body into health, sub-health, disease-susceptible state, and disease. We suggest the disease-susceptible stage emerges as a pivotal point for TCM interventions. To understand the intrinsic dynamics of this state, we propose laboratory and clinical studies utilizing time-series experiments and stress-induced disease susceptibility models. At the molecular level, bio-omics technologies and bioinformatics approaches are highlighted for uncovering intricate changes during disease progression. Furthermore, we discuss the application of mathematical models and artificial intelligence in developing early warning systems to anticipate and avert the transition from health to disease. This approach resonates with TCM’s preventive philosophy, emphasizing proactive health maintenance and disease prevention. Ultimately, our perspective underscores the significance of integrating modern scientific methodologies with TCM principles to propel Weibing research and early intervention strategies forward.
中医“病感”——易感状态的生物学基础和数学表示
“不平衡”是中医的一个基本概念,代表一种过渡状态,其特征是自我调节能力下降,但没有明显的生理或社会功能障碍。这一视角深入探究微痛的生物学基础和可量化的标志物,旨在建立疾病早期干预的研究框架。在此,我们提出了“健康象限分类”体系,将人体状态分为健康状态、亚健康状态、易感状态和疾病状态。我们建议疾病易感期成为中医干预的关键点。为了了解这种状态的内在动力学,我们建议利用时间序列实验和应激诱导疾病易感性模型进行实验室和临床研究。在分子水平上,生物组学技术和生物信息学方法在揭示疾病进展过程中的复杂变化方面得到了强调。此外,我们讨论了数学模型和人工智能在开发早期预警系统中的应用,以预测和避免从健康到疾病的过渡。这种方法与中医的预防哲学相呼应,强调积极的健康维护和疾病预防。最后,我们的观点强调了将现代科学方法与中医原理结合起来,推动微病研究和早期干预策略向前发展的重要性。
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来源期刊
Acta Pharmaceutica Sinica. B
Acta Pharmaceutica Sinica. B Pharmacology, Toxicology and Pharmaceutics-General Pharmacology, Toxicology and Pharmaceutics
CiteScore
22.40
自引率
5.50%
发文量
1051
审稿时长
19 weeks
期刊介绍: The Journal of the Institute of Materia Medica, Chinese Academy of Medical Sciences, and the Chinese Pharmaceutical Association oversees the peer review process for Acta Pharmaceutica Sinica. B (APSB). Published monthly in English, APSB is dedicated to disseminating significant original research articles, rapid communications, and high-quality reviews that highlight recent advances across various pharmaceutical sciences domains. These encompass pharmacology, pharmaceutics, medicinal chemistry, natural products, pharmacognosy, pharmaceutical analysis, and pharmacokinetics. A part of the Acta Pharmaceutica Sinica series, established in 1953 and indexed in prominent databases like Chemical Abstracts, Index Medicus, SciFinder Scholar, Biological Abstracts, International Pharmaceutical Abstracts, Cambridge Scientific Abstracts, and Current Bibliography on Science and Technology, APSB is sponsored by the Institute of Materia Medica, Chinese Academy of Medical Sciences, and the Chinese Pharmaceutical Association. Its production and hosting are facilitated by Elsevier B.V. This collaborative effort ensures APSB's commitment to delivering valuable contributions to the pharmaceutical sciences community.
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