关键词: 三七皂苷提取物, 血塞通注射液, UPLC-QTOF-MSE, 代谢组学, 整体质量评价

Abstract:

In the present study, we established an UPLC-QTOF-MS^E based metabolomic approach in order to evaluate the holistic qualities and compare the quality difference by finding characteristic components of Panax notoginseng extracts (PNE) and Xuesaitong (XST) injection samples from different manufacturers. The data were processed through unsupervised principal component analysis (PCA) and supervised orthogonal partial least squared discrimination analysis (OPLS-DA) to compare the quality differences. Two-dimensional PCA score plots showed a tendency to separate the XST injections and extracts, and most XST injection samples were clearly clustered into two groups. Especially, the injections from He and YB companies were distinguishedinto two groups. In addition, only injection samples of Hu company were near the cluster of PNE. To explore the potential chemicalcomponents contributing most to the differences between XST injection samples from different manufacturers and PNE, an S-plotwas constructed following the OPLS-DA. Ginsenoside Rd, ginsenoside Rg₁, ginsenoside Re, ginsenoside Rb₁, 20(S)-ginsenoside Rh₁, gypenoside VII, ginsenoside Rg₂, ginsenoside Rh₄, ginsenoside Rk₁ or Rg₅, notoginsenoside Fc, 20(R)-ginsenoside Rg₃, ginsenoside F₂ and protopanaxadiol were recognized as characteristic chemical markers that contributed most to reflect the difference between XST injections and PNE. Ginsenoside Rd, ginsenoside Rg₁, ginsenoside Re, ginsenoside Rb₁ and gypenoside VII were revealed as index components contributing most to the differences of PNE and XST injections, and quantitative analysis of these components could ensure the consistent quality of XST injections. Based on the fact that the injections should be standardized with the characteristic components as quality control chemical markers, it is most important to keep the quality of extracts of raw materials stable and reliable.

Key words: Panax notoginseng extract, XST injection, UPLC-QTOF-MSE, Metabolomics, Holistic quality evaluation