...
首页> 外文期刊>Journal of separation science. >Applying characteristic fragment filtering for rapid detection and identification of ingredients in rhubarb by HPLC coupled with linear ion trap-Orbitrap mass spectrometry
【24h】

Applying characteristic fragment filtering for rapid detection and identification of ingredients in rhubarb by HPLC coupled with linear ion trap-Orbitrap mass spectrometry

机译:HPLC耦合线性离子阱 - 横塔质谱法快速检测及鉴定大鼠成分的快速检测及鉴定

获取原文
获取原文并翻译 | 示例
           

摘要

Chemical characteristic fragment filtering in MSn chromatograms was proposed to detect and identify the components in rhubarb rapidly using high-performance liquid chromatography coupled with linear ion trap-Orbitrap mass spectrometry. Characteristic fragments consist of diagnostic ions and neutral loss fragments. Characteristic fragment filtering is a postacquisition data mining method for the targeted screening of groups with specific structures, including three steps: first, in order to comprehensively summarize characteristic fragments for global identification of the ingredients in rhubarb, representative authentic standards of dominant chemical categories contained in rhubarb were chosen, from which fragmentation rules and a characteristic fragments schedule were proposed; second, characteristic fragment filtering was used to rapidly recognize analogous skeletons; finally, combined with retention time, accurate mass, characteristic fragments, and previous literature, the structures of the filtered compounds were identified or tentatively characterized. As a result, a total of 271 compounds were detected and identified in rhubarb, including 34 anthraquinones, 83 anthrones, 46 tannins, 17 stilbenes, 24 phenylbutanones, 26 acylglucosides, 26 chromones, and 15 other compounds, 69 of which are potentially new compounds. The proposed characteristic fragment filtering strategy would be a reference for the large-scale detection and identification of the ingredients of herbal medicines.
机译:提出了MSN色谱图中的化学特性片段滤波,以使用高性能液相色谱与线性离子阱 - 横侧质谱法快速检测粗草中的组分。特征碎片由诊断离子和中性损失片段组成。特征片段滤波是针对具有特定结构的组的针对性筛选的后期数据挖掘方法,包括三个步骤:首先,为了全面地总结大黄的全球成分的特征碎片,所包含的代表性正品标准选择大黄,从中提出了碎片规则和特征碎片时间表;其次,使用特征片段滤波来快速识别类似骨骼;最后,结合保留时间,精确的质量,特征碎片和先前的文献,鉴定过滤化合物的结构或暂定表征。结果,总共271种化合物在大黄中检测并鉴定,包括34个蒽醌,83个蒽酮,46个单宁,17个梯形,24个苯基丁酮,26个酰基葡糖苷,26发铬和15个其他化合物,其中69种,其中69种潜在的新化合物。所提出的特征片段过滤策略将是大规模检测和鉴定草药成分的参考。

著录项

  • 来源
    《Journal of separation science.》 |2017年第14期|共9页
  • 作者单位

    Beijing Univ Chinese Med Sch Chinese Mat Med South Wangjing Middle Ring Rd Beijing 100102 Peoples R China;

    Beijing Univ Chinese Med Sch Chinese Mat Med South Wangjing Middle Ring Rd Beijing 100102 Peoples R China;

    Beijing Univ Chinese Med Sch Chinese Mat Med South Wangjing Middle Ring Rd Beijing 100102 Peoples R China;

    Beijing Univ Chinese Med Sch Chinese Mat Med South Wangjing Middle Ring Rd Beijing 100102 Peoples R China;

    Beijing Univ Chinese Med Sch Chinese Mat Med South Wangjing Middle Ring Rd Beijing 100102 Peoples R China;

    Beijing Univ Chinese Med Sch Chinese Mat Med South Wangjing Middle Ring Rd Beijing 100102 Peoples R China;

    Beijing Univ Chinese Med Sch Chinese Mat Med South Wangjing Middle Ring Rd Beijing 100102 Peoples R China;

    Beijing Univ Chinese Med Sch Chinese Mat Med South Wangjing Middle Ring Rd Beijing 100102 Peoples R China;

    Beijing Univ Chinese Med Sch Chinese Mat Med South Wangjing Middle Ring Rd Beijing 100102 Peoples R China;

    Beijing Univ Chinese Med Sch Chinese Mat Med South Wangjing Middle Ring Rd Beijing 100102 Peoples R China;

    Beijing Univ Chinese Med Sch Chinese Mat Med South Wangjing Middle Ring Rd Beijing 100102 Peoples R China;

    Beijing Univ Chinese Med Sch Chinese Mat Med South Wangjing Middle Ring Rd Beijing 100102 Peoples R China;

    Beijing Univ Chinese Med Sch Chinese Mat Med South Wangjing Middle Ring Rd Beijing 100102 Peoples R China;

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

    chemical characteristic fragments; fragmentation pathways; multistage mass spectrometry chromatograms; postacquisition data mining; traditional Chinese medicine;

    机译:化学特征碎片;碎片途径;多级质谱斑点图;后期数据挖掘;中医;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号