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首页> 外文期刊>Journal of chromatography, A: Including electrophoresis and other separation methods >A strategy for intelligent chemical profiling-guided precise quantitation of multi-components in traditional Chinese medicine formulae-QiangHuoShengShi decoction
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A strategy for intelligent chemical profiling-guided precise quantitation of multi-components in traditional Chinese medicine formulae-QiangHuoShengShi decoction

机译:中药型铜丰芯汤中多组分智能化学分析策略的策略

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摘要

Due to the tremendous clinical value, more and more Traditional Chinese Medicines (TCMs) and their formulae are attracted by world's attention. QiangHuoShengShi (QHSS) decoction is one of classic TCM formulae, which is clinically used for treating various rheumatic diseases. However, the phytochemical constituents of QHSS have rarely been reported. A simple, intelligent, and comprehensive strategy was developed to characterize the phytochemical-fingerprint and quantify the chemical-markers for precise quality evaluation of QHSS. Firstly, a new deep-learning assisted mass defect filter (MDF) method was built for rapid and accurate classification of mass spectrum (MS) ions acquired by ultra-high performance liquid chromatography quadrupole time of flight tandem mass spectrometry (UHPLC-Q-TOF/MS). Subse-quently, herb species-specific chemical-category and characteristic identification were used for further characterization of multi-components. As the result, seven major types of compounds in QHSS were in-telligently differentiated and 183 phytochemical compounds were tentatively identified. Finally, a sensi-tive scheduled multiple reaction monitoring (sMRM) detection method was applied to precisely quantify 37 target analytes in QHSS decoction. This integrated strategy would provide an alternative method for chemical-material basis study of more herbal medicine or natural products.
机译:由于其巨大的临床价值,越来越多的中药及其方剂受到世界各国的关注。强活生食汤是中医经典方剂之一,临床上用于治疗各种风湿性疾病。然而,QHSS的植物化学成分却鲜有报道。建立了一种简单、智能、全面的策略来表征QHSS的植物化学指纹图谱,并对化学标记进行量化,以精确评估QHSS的质量。首先,建立了一种新的深度学习辅助质量缺陷滤波器(MDF)方法,用于超高效液相色谱-四极杆飞行时间串联质谱(UHPLC-Q-TOF/MS)获取的质谱(MS)离子的快速准确分类。随后,草本物种特有的化学类别和特征鉴定被用于进一步表征多组分。结果表明,QHSS中有七种主要化合物存在智能分化,初步鉴定出183种植物化学成分。最后,采用一种敏感的计划多反应监测(sMRM)检测方法,对QHSS汤中的37种目标分析物进行了精确定量。这种综合策略将为更多草药或天然产品的化学物质基础研究提供一种替代方法。

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  • 作者单位

    Tianjin Univ Tradit Chinese Med State Key Lab Component Based Chinese Med Tianjin 301617 Peoples R China;

    Tianjin Hosp Dept Tradit Chinese Med Tianjin 300211 Peoples R China;

    Tianjin Univ Tradit Chinese Med State Key Lab Component Based Chinese Med Tianjin 301617 Peoples R China;

    Tianjin Univ Tradit Chinese Med State Key Lab Component Based Chinese Med Tianjin 301617 Peoples R China;

    Tianjin Univ Tradit Chinese Med State Key Lab Component Based Chinese Med Tianjin 301617 Peoples R China;

    Tianjin Univ Tradit Chinese Med State Key Lab Component Based Chinese Med Tianjin 301617 Peoples R China;

    Tianjin Univ Tradit Chinese Med State Key Lab Component Based Chinese Med Tianjin 301617 Peoples R China;

    Tianjin Univ Tradit Chinese Med State Key Lab Component Based Chinese Med Tianjin 301617 Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 分析化学;
  • 关键词

    Deep-learning; MDF; QiangHuoShengShi decoction; UHPLC-Q-TOF; MS; UHPLC-sMRM;

    机译:深学习;MDF;Qianghuoshengshi汤;UHPLC-Q-TOF;MS;UHPLC-SMRM;

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