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Potential of hyphenated ultra-high performance liquid chromatography-scheduled multiple reaction monitoring algorithm for large-scale quantitative analysis of traditional Chinese medicines
Song, Qingqing1,2; Song, Yuelin1; Zhang, Na1,2; Li, Jun1; Jiang, Yong3; Zhang, Kerong4; Zhang, Qian1; Tu, Pengfei1
刊名RSC ADVANCES
2015
DOI10.1039/c5ra09429a
5期:71页:57372-57382
收录类别SCI
文章类型Article
WOS标题词Science & Technology
类目[WOS]Chemistry, Multidisciplinary
研究领域[WOS]Chemistry
关键词[WOS]TANDEM MASS-SPECTROMETRY ; TIME-OF-FLIGHT ; DIODE-ARRAY DETECTION ; ENANTIOSPECIFIC DETERMINATION ; DRUG-RESISTANCE ; HUMAN SERUM ; QUANTIFICATION ; CANCER ; PLASMA ; METABOLITES
英文摘要

It is a great challenge to perform quality control for traditional Chinese medicines (TCMs) that contain a great number of constituents by holistically monitoring hydrophilic and hydrophobic substances. Theoretically, the relatively low scan rate of triple quadrupole (QqQ) equipment makes it quite difficult to meet the demands of reliable quantitation of the narrow peaks generated from ultra-high performance liquid chromatography (UHPLC). Scheduled multiple reaction monitoring (sMRM) algorithm offers the potential to simultaneously monitor numerous analytes without compromising data quality, in particular for co-eluting compounds, by automatically altering the dwell time to maintain the desired cycle time on a QqQ analytical platform. In the current study, UHPLC and sMRM were hyphenated to develop a practical and robust quantitative method for as many as 133 TCM-derived components, including polar and apolar compounds. Efficient separation was achieved on a core-shell-type column (Capcell core ADME column) with adamantylethyl functional groups to generate appropriate surface polarity along with hydrophobicity in comparison with RP-C-18 and HILIC columns. To verify the applicability of the developed UHPLC-sMRM method, a formula was simulated by mixing eight TCM raw materials that related to those 133 analytes. Moreover, enhanced product ion scans were triggered by sMRM to acquire MS2 spectra to enhance the confidence of peak assignment. Method validation results suggested the developed method to be accurate, precise, and reproducible. In comparison with conventional MRM, sMRM was proved to be advantageous in terms of sensitivity and precision, as well as the dependent MS2 spectral quality. Above all, our current study indicated that the integration of UHPLC and sMRM provides the potential to globally and simultaneously quantify the components in TCMs.

语种英语
WOS记录号WOS:000357805500015
项目编号81403073 ; NCET-13-0693 ; 81222051
资助机构National Science Fund of China ; Ministry of Industry and Information Technology of China ; Program for New Century Excellent Talents in University ; National Science Fund for Excellent Young Scholars
引用统计
被引频次:13[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.bjmu.edu.cn/handle/400002259/59113
专题北京大学药学院
北京大学第三临床医学院_康复医学科
作者单位1.AB SCIEX, Applicat Support Ctr, Shanghai 200233, Peoples R China
2.Beijing Univ Chinese Med, Modern Res Ctr Tradit Chinese Med, Beijing 100029, Peoples R China
3.Beijing Univ Chinese Med, Sch Chinese Mat Med, Beijing 100102, Peoples R China
4.Peking Univ, Sch Pharmaceut Sci, State Key Lab Nat & Biomimet Drugs, Beijing 100191, Peoples R China
推荐引用方式
GB/T 7714
Song, Qingqing,Song, Yuelin,Zhang, Na,et al. Potential of hyphenated ultra-high performance liquid chromatography-scheduled multiple reaction monitoring algorithm for large-scale quantitative analysis of traditional Chinese medicines[J]. RSC ADVANCES,2015,5(71):57372-57382.
APA Song, Qingqing.,Song, Yuelin.,Zhang, Na.,Li, Jun.,Jiang, Yong.,...&Tu, Pengfei.(2015).Potential of hyphenated ultra-high performance liquid chromatography-scheduled multiple reaction monitoring algorithm for large-scale quantitative analysis of traditional Chinese medicines.RSC ADVANCES,5(71),57372-57382.
MLA Song, Qingqing,et al."Potential of hyphenated ultra-high performance liquid chromatography-scheduled multiple reaction monitoring algorithm for large-scale quantitative analysis of traditional Chinese medicines".RSC ADVANCES 5.71(2015):57372-57382.
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