四极飞行时间
化学
色谱法
植物化学
质谱法
串联质谱法
定性分析
三级四极质谱仪
液相色谱-质谱法
选择性反应监测
社会科学
生物化学
社会学
定性研究
作者
Xiaohua Yang,Shuangqi Wang,Lina Qi,Shujing Chen,Kunze Du,Ye Shang,Jiading Guo,Shiming Fang,Jin Li,Han Zhang,Yanxu Chang
标识
DOI:10.1016/j.jpba.2023.115288
摘要
Qingjin Yiqi Granules (QJYQ) is a Traditional Chinese Medicines (TCMs) prescription for the patients with post-COVID-19 condition. It is essential to carry out the quality evaluation of QJYQ. A comprehensive investigation was conducted by establishing deep-learning assisted mass defect filter (deep-learning MDF) mode for qualitative analysis, ultra-high performance liquid chromatography and scheduled multiple reaction monitoring method (UHPLC-sMRM) for precise quantitation to evaluate the quality of QJYQ. Firstly, a deep-learning MDF was used to classify and characterize the whole phytochemical components of QJYQ based on the mass spectrum (MS) data of ultra-high performance liquid chromatography quadrupole time of flight tandem mass spectrometry (UHPLC-Q-TOF/MS). Secondly, the highly sensitive UHPLC-sMRM data-acquisition method was established to quantify the multi-ingredients of QJYQ. Totally, nine major types of phytochemical compounds in QJYQ were intelligently classified and 163 phytochemicals were initially identified. Furthermore, fifty components were rapidly quantified. The comprehensive evaluation strategy established in this study would provide an effective tool for accurately evaluating the quality of QJYQ as a whole.
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