引用本文: | 李卓群,王海丽,贵书琪,李辉,赵开军.小儿感冒舒颗粒HPLC指纹图谱建立与化学模式识别[J].中国现代应用药学,2021,38(22):2820-2825. |
| LI Zhuoqun,WANG Haili,GUI Shuqi,LI Hui,ZHAO Kaijun.HPLC Fingerprint Establishment and Chemistry Pattern Recognition of Xiaoer Ganmaoshu Granules[J].Chin J Mod Appl Pharm(中国现代应用药学),2021,38(22):2820-2825. |
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摘要: |
目的 建立小儿感冒舒颗粒HPLC指纹图谱,并进行化学模式识别。方法 采用Waters C18反相色谱柱(250 mm×4.6 mm,5 μm);流动相为乙腈(A)-0.1%磷酸水溶液(B),进行梯度洗脱;体积流量1.0 mL·min–1,柱温40℃;检测波长250 nm。通过对指纹图谱进行相似度评价,结合化学模式识别技术对13批样品进行分析。结果 13批样品指纹图谱中有共有峰20个,并指认出其中10个成分,分别为2号峰(绿原酸)、3号峰(3’-羟基葛根素)、4号峰(葛根素)、6号峰(3’-甲氧基葛根素)、7号峰(葛根素芹菜糖苷)、8号峰(大豆苷)、12号峰(甘草苷)、18号峰(大豆苷元)、19号峰(牛蒡苷)、20号峰(哈巴俄苷);13批样品指纹图谱相似度均>0.995。聚类分析、主成分分析可将13批样品聚为2类,结合正交偏最小二乘法-判别分析推测其中7个成分是造成各批次样品产生差异的重要成分。结论 建立的小儿感冒舒颗粒HPLC分析方法简便、稳定,同时指纹图谱结合化学模式识别可为小儿感冒舒颗粒质量控制标准的制定提供参考。 |
关键词: 小儿感冒舒颗粒 指纹图谱 化学模式识别 质量评价 |
DOI:10.13748/j.cnki.issn1007-7693.2021.22.010 |
分类号:R917.101 |
基金项目:江苏省知识产权战略推进计划项目(ZT20210180-33) |
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HPLC Fingerprint Establishment and Chemistry Pattern Recognition of Xiaoer Ganmaoshu Granules |
LI Zhuoqun1, WANG Haili2, GUI Shuqi1, LI Hui2, ZHAO Kaijun2
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1.China Pharmaceutical University, Nanjing 211198, China;2.Nanjing Zhongshan Pharmaceutical Co., Ltd., Nanjing 211198, China
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Abstract: |
OBJECTIVE To establish HPLC fingerprint of Xiaoer Ganmaoshu granules and carry out chemical pattern recognition. METHODS The Waters C18 reverse column(250 mm×4.6 mm, 5 μm) was used, the mobile phase was acetonitrile(A)-0.1% phosphoric acid aqueous solution(B), the gradient elution was performed, the volume flow rate was 1.0 mL·min-1, the column temperature was 40℃, and the detection wavelength was 250 nm. Through the similarity evaluation of fingerprint, combined with chemical pattern recognition technology, 13 batches of samples were analyzed. RESULTS There were 20 common peaks in the fingerprint of 13 batches of samples, and 10 of them were identified. They were peak 2(chlorogenic acid), peak 3(3'-hydroxypuerarin), peak 4(puerarin), peak 6(3'-methoxypuerarin), peak 7(puerarin apigenin), peak 8(daidzin), peak 12(glycyrrhizin), peak 18(daidzein), peak 19(arctiin), peak 20(habaroside). The fingerprint similarity of 13 batches of samples was more than 0.995. Cluster analysis and principal component analysis can cluster 13 batches of samples into two groups, and combined with orthogonal partial least square-discriminant analysis, it inferred that 7 components were important components that cause differences among batches of samples. CONCLUSION The established HPLC analysis method of Xiaoer Ganmaoshu granules was simple and stable, and the fingerprint combined with chemical pattern recognition can provide reference for the establishment of the quality control standard of Xiaoer Ganmaoshu granules. |
Key words: Xiaoer Ganmaoshu granules fingerprint chemical pattern recognition quality evaluation |