[关键词]
[摘要]
目的 采用指纹图谱并结合多种化学计量方法,筛选特征化学成分,区分不同来源的药材,综合评价中药的质量。方法 采用HPLC法建立补骨脂药材指纹图谱,相似性分析(similarity analysis,SA)、聚类分析(hierarchical cluster analysis,HCA)、主成分分析(principal component analysis,PCA)化学计量方法进行分析。色谱柱为Waters X Select HSS T3 xp(150 mm×2.1 mm,2.5 μm),流动相为乙腈(A)-水(B),梯度洗脱,0~10 min,5%~10% A;10~15 min,10%~35% A;15~25 min,35%~60% A;25~35 min,60%~85% A;35~50 min,85%~95% A;体积流量0.3 mL/min,检测波长为246 nm,柱温为30℃,进样量为1 μL。以补骨脂素为参照,绘制11批样品的HPLC图谱,采用《中药色谱指纹图谱相似度评价软件(2012年版)》进行相似性评价分析,确定共有峰,并采用SIMCA 13.0、SPSS 22.0软件进行HCA和PCA。结果 11批补骨脂样品的HPLC图谱有12个共有峰,根据相似度均在是否大于0.95,可将11批次药材分为2类;采用HCA的2种计算方法,分类结果基本一致,说明样品的一致性良好;3个主成分因子的累积方差贡献率为94.524%,以S8样品的主成分因子综合得分最高、整体质量最好。结论 所建HPLC指纹图谱的相似度分析及聚类分析和主成分分析方法结果可为补骨脂药材的质量控制提供参考。
[Key word]
[Abstract]
Objective To distinguish the medicinal materials from different sources and evaluate the quality of Chinese herbal medicines by using chromatographic profiles combined with chemometric methods. Methods HPLC, similarity analysis (SA), cluster analysis (HCA) and principal component analysis (PCA) were used to analyze the original data. The chromatographic column was Waters X Select HSS T3 xp (150 mm×2.1 mm, 2.5 μm), the mobile phase was acetonitrile-water (gradient elution), the flow rate was 0.3 mL/min, the detection wavelength was 246 nm, the column temperature was 30℃, and the injection volume was 1 μL. HPLC profiles of 11 batches of samples were drawn using psoralen as the reference. Similarity evaluation software of Chinese traditional medicine chromatographic fingerprint (2012 edition) was used for similarity evaluation and analysis to determine the common peaks, and hierarchical cluster analysis and principal component analysis were conducted by SIMCA 13.0 and SPSS 22.0 software. Results There were 12 common peaks in the fingerprint of 11 batches of P. corylifolia. samples. According to whether the similarity index was > 0.95 or not, 11 batches of medicinal materials could be divided into two categories. Two methods of hierarchical cluster analysis were adopted, and the classification results were basically consistent, indicating the good consistency of samples. The cumulative variance contribution rate of the three principal component factors was 94.524%, and the S8 sample had the highest comprehensive score of principal component factors and the best overall quality. Conclusion The results of similarity analysis, cluster analysis and principal component analysis of HPLC fingerprint can provide reference for quality control of P. corylifolia samples.
[中图分类号]
R286.2
[基金项目]
上海市卫生和计划生育委员会中医药科研专项(2016ZJP003)