Evidence-Based Complementary and Alternative Medicine

Evidence-Based ZHENG: A Traditional Chinese Medicine Syndrome


Publishing date
13 Jul 2012
Status
Published
Submission deadline
13 Jan 2012

Lead Editor
Guest Editors

1Research Center for Complex System of Traditional Chinese Medicine,Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China

2Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China

3Bioinformatics Division, Tsinghua National Laboratory for Information Science and Technology/Department of Automation, Tsinghua University, Beijing 100084, China

4Department of Nutrition, University of North Carolina, Greensboro, NC 28081, USA


Evidence-Based ZHENG: A Traditional Chinese Medicine Syndrome

Description

The traditional Chinese medicine (TCM) ZHENG, also known as TCM syndrome, is an integral and essential part of TCM theory. A TCM syndrome, or ZHENG, is in essence a characteristic profile of all clinical manifestations that can be identified by a TCM practitioner. Clinical treatments of a patient rely on the successful differentiation of a specific TCM syndrome. Recent advances in systems biology and medicine have allowed the application of new profiling technologies in the study of the ZHENG differentiation and its biological interpretation. Understanding of the characteristic changes in biochemistry associated with a specific TCM ZHENG will facilitate the development of ZHENG identification, a novel disease diagnostic and stratification approach that will potentially lead to personalized healthcare strategies for a range of diseases that lack therapeutic solutions

We invite investigators to contribute original research articles as well as review articles that will stimulate the continuing efforts to achieving improved clinical diagnosis, patient stratification, and personalized treatment by means of the ZHENG differentiation concept and approach. The information obtained from these studies shall be clearly evidence based. We are particularly interested in articles describing the new modalities for clinical characterization of ZHENG, measuring outcomes, and data mining from those personalized clinical trials; advances in molecular genetics and biologic diagnosis of ZHENG; new insights into ZHENG classification using genes, proteins, metabolites, and their profiles; systems strategies in ZHENG classification and treatment evaluation using the methods of gene polymorphism, transcriptomics, proteomics, metabonomics, metagenomics, and bioinformatics. Potential topics include, but are not limited to:

  • Concept and development of ZHENG
  • Recent advances in ZHENG identification and its clinical applications
  • Latest technologies for ZHENG identification and outcome measurement
  • Role of genotypes in ZHENG classification and treatment evaluation
  • ZHENG classification and treatment evaluation by systematic-omics methods such as transcriptomics, proteomics, metabonomics, and metagenomics
  • Data mining, bioinformatics, and network pharmacology for ZHENG classification and treatment evaluation
  • Recent advances in evaluating therapeutic effects following ZHENG identification

Before submission authors should carefully read over the journal's Author Guidelines, which are located at http://www.hindawi.com/journals/ecam/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/ according to the following timetable:


Articles

  • Special Issue
  • - Volume 2012
  • - Article ID 246538
  • - Editorial

Evidence-Based ZHENG: A Traditional Chinese Medicine Syndrome

Shi-Bing Su | Aiping Lu | ... | Wei Jia
  • Special Issue
  • - Volume 2012
  • - Article ID 735078
  • - Review Article

Classification of Insomnia Using the Traditional Chinese Medicine System: A Systematic Review

Maggie Man-Ki Poon | Ka-Fai Chung | ... | Shi-Ping Zhang
  • Special Issue
  • - Volume 2012
  • - Article ID 521780
  • - Research Article

The Exploration of Disease Pattern, Zheng, for Differentiation of Allergic Rhinitis in Traditional Chinese Medicine Practice

Sienhung Yang | Hsingyu Chen | ... | Yuchun Chen
  • Special Issue
  • - Volume 2012
  • - Article ID 509705
  • - Research Article

Xiaopiyishen Herbal Extract Granule Improves the Quality of Life among People with Fatigue-Predominant Subhealth and Liver-Qi Stagnation and Spleen-Qi Deficiency Syndrome

Xiao-lin Xue | Xiu-yan Wu | ... | Tian-fang Wang
  • Special Issue
  • - Volume 2012
  • - Article ID 783923
  • - Review Article

Clinical Distribution and Molecular Basis of Traditional Chinese Medicine ZHENG in Cancer

Zhen Chen | Peng Wang
  • Special Issue
  • - Volume 2012
  • - Article ID 739642
  • - Research Article

The Quintessence of Traditional Chinese Medicine: Syndrome and Its Distribution among Advanced Cancer Patients with Constipation

Chung-Wah Cheng | Annie O. L. Kwok | ... | Doris M. W. Tse
  • Special Issue
  • - Volume 2012
  • - Article ID 480715
  • - Research Article

Traditional Chinese Medicine ZHENG Identification Provides a Novel Stratification Approach in Patients with Allergic Rhinitis

Kai-Li Liang | Rong-San Jiang | ... | Yi-Chang Su
  • Special Issue
  • - Volume 2012
  • - Article ID 968083
  • - Research Article

Application of Metabolomics in Traditional Chinese Medicine Differentiation of Deficiency and Excess Syndromes in Patients with Diabetes Mellitus

Tao Wu | Ming Yang | ... | Guang Ji
  • Special Issue
  • - Volume 2012
  • - Article ID 546230
  • - Research Article

Clinical Data Mining of Phenotypic Network in Angina Pectoris of Coronary Heart Disease

Jianxin Chen | Peng Lu | ... | Wei Wang
  • Special Issue
  • - Volume 2012
  • - Article ID 409568
  • - Research Article

Traditional Chinese Medicine Zheng in the Era of Evidence-Based Medicine: A Literature Analysis

Miao Jiang | Chi Zhang | ... | Aiping Lu
Evidence-Based Complementary and Alternative Medicine
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Acceptance rate27%
Submission to final decision75 days
Acceptance to publication21 days
CiteScore3.200
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Impact Factor2.650
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