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基于模式识别分析的黄蜀葵体内代谢产物研究。

Investigation of in vivo metabolic profile of Abelmoschus Manihot based on pattern recognition analysis.

机构信息

Jiangsu Key Laboratory for High Technology Research of TCM Formulae, Nanjing University of Chinese Medicine, Nanjing 210046, PR China.

出版信息

J Ethnopharmacol. 2013 Jun 21;148(1):297-304. doi: 10.1016/j.jep.2013.04.029. Epub 2013 Apr 28.

DOI:10.1016/j.jep.2013.04.029
PMID:23632309
Abstract

ETHNOPHARMACOLOGICAL RELEVANCE

Abelmoschus manihot (L.) Medik. var. manihot is one of the most commonly used Chinese medicines and has played an important role in treating chronic glomerulonephritis and diabetic nephropathy.

AIM OF THE STUDY

Metabolites identification of traditional Chinese medicine (TCM) is a complex and time-consuming process due to the complicity of TCM and subsequent large number of detected ions. In this paper, UPLC-MS combined with pattern recognition analysis approach were used to simplify and quicken the identification of the metabolites of Abelmoschus Manihot.

MATERIALS AND METHODS

Rat urine samples were collected before (as control sample) and after Abelmoschus Manihot administration. Pattern recognition analysis method was used to differentiate components between Abelmoschus Manihot-treated group and its controlled comparison. These components could be considered as Abelmoschus Manihot-related metabolites in vivo.

RESULTS

LC-MS based metabolomics could be an advanced tool to help us find metabolites with regards to its capacity of processing large datasets, differentiating and classifying of sample groups, as well as its indiscriminative nature of biomarker and metabolite identification. Using this method, seven metabolites were identified, which are flavonoid aglycone glucuronidation, sulfatation, and methylation metabolites.

CONCLUSION

Our results showed that UPLC-MS based- pattern recognition analysis approach can be used to quickly identify Abelmoschus Manihot related metabolites in biological fluids. Furthermore, this work demonstrates the potential application of combining the UPLC-MS approach with the metabolomics approach in identifying the metabolites of TCM.

摘要

民族药理学相关性

黄蜀葵(L.)Medik。变体。黄蜀葵是最常用的中药之一,在治疗慢性肾小球肾炎和糖尿病肾病方面发挥了重要作用。

研究目的

由于中药的复杂性和随后检测到的大量离子,中药代谢产物的鉴定是一个复杂且耗时的过程。在本文中,采用 UPLC-MS 结合模式识别分析方法简化和加速了黄蜀葵代谢产物的鉴定。

材料和方法

大鼠尿液样本在给药前(作为对照样本)和给药后采集。采用模式识别分析方法区分黄蜀葵处理组与其对照比较组之间的成分。这些成分可被认为是体内与黄蜀葵相关的代谢物。

结果

基于 LC-MS 的代谢组学可以作为一种先进的工具,帮助我们找到与处理大数据集、区分和分类样本组以及识别生物标志物和代谢物的无差别性有关的代谢物。使用该方法,鉴定出 7 种代谢物,分别为黄酮苷类葡萄糖醛酸化、硫酸化和甲基化代谢物。

结论

我们的研究结果表明,基于 UPLC-MS 的模式识别分析方法可用于快速鉴定生物体液中的黄蜀葵相关代谢物。此外,本工作证明了将 UPLC-MS 方法与代谢组学方法相结合在鉴定中药代谢物方面的潜在应用。

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