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基于指纹图谱和多指标定量测定的鹿茸饮片质量控制研究
引用本文:孙伟杰,吕程,杨重晖,刘莉,李江丹,李冰慧,王任晶,许宁,杨洋,尹程程,赵大庆,齐滨.基于指纹图谱和多指标定量测定的鹿茸饮片质量控制研究[J].中草药,2019,50(22):5448-5454.
作者姓名:孙伟杰  吕程  杨重晖  刘莉  李江丹  李冰慧  王任晶  许宁  杨洋  尹程程  赵大庆  齐滨
作者单位:长春中医药大学吉林省人参科学院, 吉林 长春 130117,长春中医药大学, 吉林 长春 130117,长春中医药大学吉林省人参科学院, 吉林 长春 130117,长春中医药大学, 吉林 长春 130117,长春中医药大学, 吉林 长春 130117,长春中医药大学, 吉林 长春 130117,长春中医药大学, 吉林 长春 130117,长春中医药大学, 吉林 长春 130117,长春中医药大学吉林省人参科学院, 吉林 长春 130117,长春中医药大学吉林省人参科学院, 吉林 长春 130117,长春中医药大学吉林省人参科学院, 吉林 长春 130117,长春中医药大学, 吉林 长春 130117
基金项目:国家重点研发计划(2018YFC1706604);吉林省科技发展计划(20190101010JH);长春市科技局医药健康产业科技创新重大专项(18YJ013);国家中药标准化项目(ZYBZH-Y-JL-26)
摘    要:目的采用HPLC法建立鹿茸饮片指纹图谱,并测定核苷类成分含量,进行聚类分析与主成分分析(PCA),比较鹿茸饮片中6种核苷成分(尿嘧啶、腺嘌呤、次黄嘌呤、尿苷、肌苷和鸟苷)的差异。方法采用HPLC法对16批不同批次鹿茸饮片6种核苷类成分进行测定,运用国家药典委员会"中药色谱指纹图谱相似度评价软件(2012版)"进行评价,并结合PCA和正交偏最小二乘判别分析(OPLS-DA)等化学计量学方法对4种饮片(蜡片、粉片、纱片和骨片)进行区分与比较。结果建立了鹿茸核苷类成分HPLC指纹图谱,相似度均达0.960以上,确定了6个共有峰(尿嘧啶、腺嘌呤、次黄嘌呤、尿苷、肌苷和鸟苷)构成鹿茸饮片的特征峰,尿嘧啶、次黄嘌呤和肌苷是差异性化合物,可作为鉴别和区分鹿茸饮片质量控制指标。结论该法所建立的鹿茸核苷类成分指纹图谱特征性强、方法简便,结合6种核苷类成分含量测定可更好控制其质量,对鹿茸饮片的鉴定及质量控制具有指导意义和参考价值。

关 键 词:鹿茸饮片  指纹图谱  核苷成分  主成分分析  正交偏最小二乘判别分析  质量控制
收稿时间:2019/6/5 0:00:00

Quality evaluation of Cervi Cornu Pantotrichum based on fingerprint analysis and quantitative analysis of multi-components
SUN Wei-jie,LV Cheng,YANG Chong-hui,LIU Li,LI Jiang-dan,LI Bing-hui,WANG Ren-jing,XU Ning,YANG Yang,YIN Cheng-cheng,ZHAO Da-qing and QI Bin.Quality evaluation of Cervi Cornu Pantotrichum based on fingerprint analysis and quantitative analysis of multi-components[J].Chinese Traditional and Herbal Drugs,2019,50(22):5448-5454.
Authors:SUN Wei-jie  LV Cheng  YANG Chong-hui  LIU Li  LI Jiang-dan  LI Bing-hui  WANG Ren-jing  XU Ning  YANG Yang  YIN Cheng-cheng  ZHAO Da-qing and QI Bin
Institution:Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun 130117, China,Changchun University of Chinese Medicine, Changchun 130117, China,Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun 130117, China,Changchun University of Chinese Medicine, Changchun 130117, China,Changchun University of Chinese Medicine, Changchun 130117, China,Changchun University of Chinese Medicine, Changchun 130117, China,Changchun University of Chinese Medicine, Changchun 130117, China,Changchun University of Chinese Medicine, Changchun 130117, China,Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun 130117, China,Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun 130117, China,Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun 130117, China and Changchun University of Chinese Medicine, Changchun 130117, China
Abstract:Objective To establish the fingerprints of nucleosides in Cervi Cornu Pantotrichum (CCP) pieces by HPLC method, perform cluster analysis and principal component analysis (PCA), and compare the differences of six nucleosides in CCP pieces. Methods A total of 16 batches of CCP pieces from different origins were determined by HPLC. Sixteen batches from different origins in China were collected to assess the similarities according to similarity evaluation for "chromatographic fingerprint of traditional Chinese medicine" (2012), and four kinds of decoction pieces were distinguished and compared by chemometric methods such as principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). Results The HPLC fingerprints of CCP nucleosides were established and the similarity was above 0.960. Six common peaks of uracil, adenine, hypoxanthine, uridine, inosine, and guanosine were identified. Among them, uracil, hypoxanthine, and inosine were different compounds, which can be used as a quality control indicator for identifying and distinguishing CCP pieces. Conclusion The CCP nucleoside fingerprints established by the method are characterized by strong features and simple methods. The combination of six nucleosides can better control the quality, which has guiding significance and reference value for the identification and quality control of CCP.
Keywords:Cervi Cornu Pantotrichum pieces  fingerprint  nucleoside  principal component analysis  orthogonal partial least squares discriminant analysis  quality control
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