Literature DB >> 23913749

An effective method for determining the ingredients of Shuanghuanglian formula in blood samples using high-resolution LC-MS coupled with background subtraction and a multiple data processing approach.

Guang-li Yan1, Ai-hua Zhang, Hui Sun, Ying Han, Hui Shi, Ying Zhou, Xi-jun Wang.   

Abstract

Shuanghuanglian formula (SF) is a combination of Flos lonicerae japonicae, Radix scutellariae, and Fructus forsythiae, commonly used to treat viral or bacterial infections. However, the constituents absorbed into the blood after oral administration of SF are difficult to determine and thus remain unclear. Here, we report the application of an accurate background subtraction and multiple data processing approach (Bs-Mpa) for the comprehensive detection of compounds of SF in vivo. A sensitive and reliable ultra-performance LC coupled with ESI quadrupole TOF MS (UPLC-ESI-Q-TOF-MS) approach coupled with Bs-Mpa, which is implemented in the Strip tool from UPLC to remove nonrelated ion signals from accurate mass LC-MS data, was established to characterize the chemical constituents and rat metabolites of SF. In the loading plot of the principal component analysis, 68 ions of interest were extracted from blood samples, among them, 39 absorbed prototype components of SF and 29 metabolites were identified in vivo. It is concluded that the integrative Bs-Mpa method can be successfully applied for the rapid discovery of multiple components from a traditional Chinese medicine. The above challenge was addressed by using the proposed Bs-Mpa method and it was particularly suitable for applying to the global characterization of the constituents or metabolites in rat blood after oral administration of other well-known formulae.
© 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  Background subtraction; Constituent identification; Principal component analysis; Shuanghuanglian formula; UPLC-ESI-Q-TOF-MS

Mesh:

Substances:

Year:  2013        PMID: 23913749     DOI: 10.1002/jssc.201300529

Source DB:  PubMed          Journal:  J Sep Sci        ISSN: 1615-9306            Impact factor:   3.645


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