论文部分内容阅读
目的:建立主要色谱峰化学成分明确的银黄颗粒HPLC指纹图谱,通过化学模式识别的方法全面评价其内在质量。方法:采用HPLC法,确定了100个不同厂家银黄颗粒指纹图谱的20个共有峰,指认了其中14个共有峰的化学成分,采用指纹图谱相似度评价,结合主成分分析和聚类分析对不同生产厂家的质量进行评价。结果:100批银黄颗粒样品图谱与对照图谱比较,相似度均>0.974之间,主成分分析与聚类分析均可将不同生产厂家的银黄颗粒很好地分类,且分类结果一致。结论:所建立的HPLC指纹图谱分析方法全面、准确、稳定,结合化学模式识别研究可有助于银黄颗粒的整体质量控制,同时为其质量评价提供一种有效手段。
OBJECTIVE: To establish a HPLC fingerprinting of silver yellow particles with clear chemical composition of main chromatographic peaks and to evaluate its intrinsic quality through chemical pattern recognition. Methods: HPLC method was used to determine the 20 common peaks of 100 silver nanoparticles from 100 different manufacturers. The chemical constituents of 14 common peaks were identified. The similarity of fingerprints was evaluated by principal component analysis and cluster analysis Evaluation of the quality of different manufacturers. Results: Compared with the control spectrum, the similarity of the samples of 100 samples of Yinhuang granules was> 0.974. Both principal component analysis and cluster analysis could well classify the silver yellow particles from different manufacturers, and the classification results were consistent. Conclusion: The established method of HPLC fingerprint analysis is comprehensive, accurate and stable. Combining with the study of chemical pattern recognition, it can contribute to the overall quality control of Yinhuang granules and provide an effective means for its quality evaluation.