透视图(图形)
机制(生物学)
传统医学
中医药
中草药
医学
认识论
心理学
哲学
替代医学
计算机科学
人工智能
病理
作者
Boyang Wang,Pan Chen,Peng Zhang,Li Shao
标识
DOI:10.4103/wjtcm.wjtcm_41_23
摘要
Abstract Cold and Hot syndrome, also known as “ZHENG” in Mandarin, is a fundamental theory in traditional Chinese medicine (TCM) and plays a pivotal role in the differentiation of diseases in TCM. Diseases are treated with varying formulas according to the specific syndrome differentiations in TCM. A way of the principles followed in TCM medical strategy is “cold herbs for hot syndrome, and hot herbs for cold syndrome.” Therefore, from the perspective of cold/hot syndrome, we summarizes the present research regarding the characteristics and mechanisms of cold/hot herbs (including herbs with cool and warm properties) in digestive system diseases, respiratory diseases, and autoimmune diseases, among others. As novel technologies have advanced, various methods, such as those based on network target, machine learning, and deep learning, have emerged to reveal the mechanisms underlying cold/hot syndrome and cold/hot herbs. With the help of these technologies, it has been found that cold and hot herbs, as well as formulae with cold or hot intentions, have similarities and differences in the treatment of these diseases. In conclusion, cold and cool may have stronger antibacterial, antiviral, and anti-inflammatory effects, whereas hot and warm herbs may specifically enhance immune regulation. With the assistance of advancing data algorithms, uncovering the mechanisms of cold/hot herbs may accelerate and provide a new research paradigm for further achieving precision in TCM.
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