scholarly journals The Applications and Obstacles of Metabonomics in Traditional Chinese Medicine

2012 ◽  
Vol 2012 ◽  
pp. 1-4 ◽  
Author(s):  
Ping Liu ◽  
Songlin Liu ◽  
Daizhi Tian ◽  
Ping Wang

In the recent years, a wide range of metabonomic technologies are widely used in the modern research of traditional chinese medicine (TCM). At present, the most prevailing methods for TCM research are mainly nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC-MS), and liquid chromatography-mass spectrometry (LC-MS). With these techniques, metabonomics will help to understand syndromes, efficacy and toxicity of TCM. However, every analytical technique has its advantages and drawbacks, and there exist some obstacles of its applications on TCM. So, we discuss metabonomics in TCM and analyze some problems of its applications to study TCM in recent years. We believe that with the further development of metabonomic analytical technology, especially multianalysed techniques, metabonomics will greatly promote TCM research and be beneficial to the modernization of TCM.

2009 ◽  
Vol 63 (5) ◽  
Author(s):  
Jiesheng Ye

AbstractIt is well known that traditional Chinese medicine (TCM) plays a more and more important role in modern pharmaceutical industry. It has been used in the therapy of many diseases for several thousand years because of its high pharmacological activity, low toxicity and rare side effects. In TCM, as an important group of secondary metabolites, essential oils have attracted a great deal of attention in recent years. Gas chromatography-mass spectrometry (GC-MS) is the most commonly used technique for the analysis of liposoluble constituents, especially volatile/semi-volatile compounds, and their metabolites in biological fluids due to its high resolution, selectivity and sensitivity. This review briefly describes the applications of GC-MS for the isolation and characterization of volatile compounds from TCM. In addition, GC-MS methods adopted in the metabolic profiling of volatile compounds in biological matrices are also described.


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