Institute for Control of Traditional Chinese Medicine and Ethnic Medicine, National Institutes for Food and Drug Control, Beijing 102629, P. R. China.
Institute for Control of Traditional Chinese Medicine and Ethnic Medicine, National Institutes for Food and Drug Control, Beijing 102629, P. R. China.
J Chromatogr B Analyt Technol Biomed Life Sci. 2024 Aug 15;1244:124257. doi: 10.1016/j.jchromb.2024.124257. Epub 2024 Jul 29.
Under the background of digitalization of traditional Chinese medicine (TCM), to realize the quick identification and adulteration analysis of Pulsatilla Radix (PR), adhering to digital conviction, this study conducted UHPLC-QTOF-MS analysis on PR and its adulterant-Pulsatilla Cernua (PC) from different batches and based on digital conversion, the shared ions were extracted from different batches of PR and PC as their "ions representation", respectively. Further, the data set of unique ions of PR relative to PC and PC relative to PR were screened out as the "digital identities" of PR and PC respectively. Further, above the "digital identities" of PR and PC were used as the benchmarks for matching and identifying to feedback give a matching credibility (MC). The results showed that based on the "digital identities" of PR and PC, the digital identification of two herbal samples can be realized efficiently and accurately at the individual level with the MC≥70.00 %, even if 5 % of PC in the mixed samples can still be identified efficiently and accurately. The study is of great practical significance for improving the identification efficiency of PR and PC, cracking down on adulterated and counterfeit drugs, and strengthening the quality control of PR. In addition, it has important reference significance for developing non-targeted digital identification of herbal medicines at the individual level based on UHPLC-QTOF-MS and the "digital identity", which was beneficial to the construction of digital Chinese medicine and digital quality control.
在中药数字化的背景下,为实现白头翁的快速鉴别和掺伪分析,本研究坚持数字化鉴定,采用 UHPLC-QTOF-MS 对不同批次的白头翁及其掺伪品——翻白草进行分析,基于数字化转换,分别从不同批次的白头翁和翻白草中提取共有离子作为它们的“离子表现”。进一步,筛选出相对于翻白草的白头翁特有离子数据集和相对于白头翁的翻白草特有离子数据集,分别作为白头翁和翻白草的“数字特征”。进一步,以上述白头翁和翻白草的“数字特征”作为匹配和识别的基准,反馈给出匹配可信度(MC)。结果表明,基于白头翁和翻白草的“数字特征”,即使在混合样品中含有 5%的翻白草,也可以以 MC≥70.00%的效率和准确性在个体水平上实现对两个草药样本的数字识别。该研究对于提高白头翁和翻白草的鉴别效率、打击掺伪和假冒药品、加强白头翁的质量控制具有重要的实际意义。此外,它对于基于 UHPLC-QTOF-MS 和“数字特征”开发针对中草药个体水平的非靶向数字化识别具有重要的参考意义,这有助于构建数字化中药和数字化质量控制。