AI Article Synopsis

  • The study aims to create a UPLC fingerprint for Resina Draconis from various manufacturers to enhance quality control.
  • Using specific analytical techniques, the study identified 15 common peaks among 18 batches, with most peaks confirmed by LC-Q-TOF MS.
  • The method proved effective for grouping samples into quality clusters, demonstrating its reproducibility and reliability for evaluating and controlling product quality.

Article Abstract

This study is to establish an UPLC fingerprint of Resina Draconis from different manufacturers, which can provide a comprehensive evaluation for its quality control. The analysis was performed on a Phenomenex Kinetex 2.6 μ C18 100A column by agradientelution program with acetonitrile-water as mobile phase at a flow rate of 1.7 mL x min(-1). The column temperature was 40 degrees C and the detection wavelengthwas 280 nm. The fingerprints of 18 batches of Draconis Resina were further evaluated by chemometrics methods including similarity analysis (SA), hierarchical clustering analysis (HCA) and principal component analysis (PCA). As a result, there were 15 common peaks, 13 of which had been identified by LC-Q-TOF MS, and the similarity degrees of 15 batches of the samples was more than 0.9, and the samples were divided into 4 clusters by their quality difference. The method is reproducible, simple and reliablethat it can be used for quality control and evaluation of Resina Draconis from different manufacturers.

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