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Phytochem Anal ; 23(4): 387-95, 2012.
Artigo em Inglês | MEDLINE | ID: mdl-22025447

RESUMO

INTRODUCTION: The quality control of Magnoliae officinalis Cortex, a commonly used traditional Chinese medicine, is currently based on the assay of the two active compounds, honokiol and magnolol, by TLC or HPLC. OBJECTIVE: To compare ¹H-NMR-based metabolomics with the HPLC method for controlling the quality of Magnoliae officinalis Cortex. To identify the metabolites contributing to the differences between the samples and to discriminate different medicinal parts and geographic origins of these samples by ¹H-NMR-based metabolomics. METHODOLOGY: ¹H-NMR and several multivariate analysis techniques were applied to analyse the extracts of 18 batches of Magnoliae officinalis Cortex commercial samples, and the contents of honokiol and magnolol in these samples were determined by HPLC. The correlation analysis between the data from ¹H-NMR and HPLC was performed with the mixOmics software based on an unsupervised method. RESULTS: Honokiol and magnolol were the main compounds responsible for the discrimination of samples from different batches, thus proving that the choice of these two compounds as markers for quality assessment by HPLC is relevant. The two sources of Magnoliae officinalis Cortex recorded in the Chinese Pharmacopoeia, Magnolia officinalis and Magnolia officinalis var. biloba, could be differentiated from ¹H-NMR data, but the pattern recognition analysis by PLS-DA was unsuccessful in discriminating samples from various geographical origins. CONCLUSION: The combination of ¹H-NMR that gives a comprehensive profile of the metabolites and HPLC that targets two biomarkers is an efficient means for a better quality control of Magnoliae officinalis Cortex.


Assuntos
Cromatografia Líquida de Alta Pressão/métodos , Espectroscopia de Ressonância Magnética/métodos , Magnolia/química , Metabolômica/métodos , Software , Compostos de Bifenilo/química , China , Medicamentos de Ervas Chinesas/análise , Medicamentos de Ervas Chinesas/química , Ecossistema , Lignanas/química , Metaboloma , Análise Multivariada , Controle de Qualidade , Sensibilidade e Especificidade
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