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首页> 外文期刊>Journal of Pharmaceutical and Biomedical Analysis: An International Journal on All Drug-Related Topics in Pharmaceutical, Biomedical and Clinical Analysis >Comprehensive quality assessment for Rhizoma Coptidis based on quantitative and qualitative metabolic profiles using high performance liquid chromatography, Fourier transform near-infrared and Fourier transform mid-infrared combined with multivariate statistical analysis
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Comprehensive quality assessment for Rhizoma Coptidis based on quantitative and qualitative metabolic profiles using high performance liquid chromatography, Fourier transform near-infrared and Fourier transform mid-infrared combined with multivariate statistical analysis

机译:基于使用高效液相色谱法的定量和定性代谢谱的综合质量评估,傅立叶变换近红外线和傅里叶变换中红外结合多元统计分析

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摘要

Rhizoma Coptidis (RC) originated from the dried rhizomes of Coptis herbal species is a widely used traditional Chinese medicine in history. In this study, a comprehensive quality assessment for RC medicines from C. chinensis, C. deltoidea, C. omeiensis and C. teeta species was performed based on quantitative and qualitative metabolic profiles obtained from high performance liquid chromatography (HPLC), Fourier transform near-infrared (FT-NIR) and Fourier transform mid-infrared (FT-MIR) combined with multivariate statistical analysis. Eight alkaloids including magnoflorine, groenlandicine, jatrorrhizine, columbamine, epiberberine, coptisine, palmatine and berberine were simultaneously identified and determined. Epiberberine, berberine, magnoflorine and groenlandicine were identified as possible index components. FT-NIR and FT-MIR profiles presented the holistic metabolic characterization of RC medicines. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were successively performed to clearly illustrate the metabolic variation and taxonomic relationship among four RC medicines. Additionally, taking berberine as an example, spectral quantification potential was investigated by referring HPLC data, using a conventional partial least squares regression (PLSR) algorithm. Data fusion strategy exhibited a better prediction for this compound than a single technique. Summary, these techniques can complement each other and provide a comprehensive and effective quality assessment for RC originated from different Coptis plants. (C) 2018 Elsevier B.V. All rights reserved.
机译:Rhizoma Coptidis(RC)起源于Coptis草药物种的干根木是历史上广泛使用的中药。在这项研究中,基于从高性能液相色谱(HPLC),傅里叶变换,傅立叶变换,对C.Chinensis,C. Deltoidea,C. Omeiensis和C.Teeta物种进行综合性质量评估。 -Infared(FT-NIR)和傅里叶变换中红外(FT-MIR)与多变量统计分析相结合。同时鉴定并确定了八种生物碱,包括致马诺氟,檐毛细胞,JATrorrhizine,哥伦比亚,外形,Coptisine,棕榈原和小檗碱。 Eciberberine,Berberine,致氧化铜和檐褶,被鉴定为可能的指标组分。 FT-NIR和FT-MIR简档呈现了RC药物的整体代谢表征。连续进行主成分分析(PCA)和分层聚类分析(HCA)以清楚地说明四种RC药物之间的代谢变化和分类学关系。另外,以小檗碱为例,通过参考HPLC数据,使用传统的局部最小二乘回归(PLSR)算法来研究光谱量化电位。数据融合策略对该化合物的更好预测而不是单一技术。发明内容,这些技术可以相互补充,并为源自不同的Coptis植物提供全面有效的质量评估。 (c)2018年elestvier b.v.保留所有权利。

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