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Evidence-Based Complementary and Alternative Medicine
Volume 2013 (2013), Article ID 956967, 10 pages
Review Article

Understanding Acupuncture Based on ZHENG Classification from System Perspective

Center for Traditional Chinese Medicine and Systems Biology, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China

Received 30 July 2013; Revised 24 September 2013; Accepted 14 October 2013

Academic Editor: Shi-bing Su

Copyright © 2013 Junwei Fang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Acupuncture is an efficient therapy method originated in ancient China, the study of which based on ZHENG classification is a systematic research on understanding its complexity. The system perspective is contributed to understand the essence of phenomena, and, as the coming of the system biology era, broader technology platforms such as omics technologies were established for the objective study of traditional chinese medicine (TCM). Omics technologies could dynamically determine molecular components of various levels, which could achieve a systematic understanding of acupuncture by finding out the relationships of various response parts. After reviewing the literature of acupuncture studied by omics approaches, the following points were found. Firstly, with the help of omics approaches, acupuncture was found to be able to treat diseases by regulating the neuroendocrine immune (NEI) network and the change of which could reflect the global effect of acupuncture. Secondly, the global effect of acupuncture could reflect ZHENG information at certain structure and function levels, which might reveal the mechanism of Meridian and Acupoint Specificity. Furthermore, based on comprehensive ZHENG classification, omics researches could help us understand the action characteristics of acupoints and the molecular mechanisms of their synergistic effect.