DICP OpenIR
Rapid discrimination between red and white ginseng based on unique mass-spectrometric features
Zhao, Qiang1,2; Zhao, Nan2; Ye, Xueting1,2; He, Meixi1,2; Yang, Yiren1,2; Gao, Huiyuan1; Zhang, Xiaozhe2
Corresponding AuthorGao, Huiyuan(sypugaohy@163.com) ; Zhang, Xiaozhe(zhangxz@dicp.ac.cn)
KeywordUHPLC-Q-TOF-MS Red ginseng Robust biomarker Nitrogen-containing compound Support vector machine Artificial neural network
Source PublicationJOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS
2019-02-05
ISSN0731-7085
DOI10.1016/j.jpba.2018.10.007
Volume164Pages:202-210
Funding ProjectMinistry of Science and Technology of the People's Republic of China[2015DFG42460] ; National Science Foundation[21475128] ; Bureau of International Cooperation Chinese Academy of Sciences[121421KYSB20160006] ; City Administration of Foreign Experts Affairs Dalian
Funding OrganizationMinistry of Science and Technology of the People's Republic of China ; Ministry of Science and Technology of the People's Republic of China ; National Science Foundation ; National Science Foundation ; Bureau of International Cooperation Chinese Academy of Sciences ; Bureau of International Cooperation Chinese Academy of Sciences ; City Administration of Foreign Experts Affairs Dalian ; City Administration of Foreign Experts Affairs Dalian ; Ministry of Science and Technology of the People's Republic of China ; Ministry of Science and Technology of the People's Republic of China ; National Science Foundation ; National Science Foundation ; Bureau of International Cooperation Chinese Academy of Sciences ; Bureau of International Cooperation Chinese Academy of Sciences ; City Administration of Foreign Experts Affairs Dalian ; City Administration of Foreign Experts Affairs Dalian ; Ministry of Science and Technology of the People's Republic of China ; Ministry of Science and Technology of the People's Republic of China ; National Science Foundation ; National Science Foundation ; Bureau of International Cooperation Chinese Academy of Sciences ; Bureau of International Cooperation Chinese Academy of Sciences ; City Administration of Foreign Experts Affairs Dalian ; City Administration of Foreign Experts Affairs Dalian ; Ministry of Science and Technology of the People's Republic of China ; Ministry of Science and Technology of the People's Republic of China ; National Science Foundation ; National Science Foundation ; Bureau of International Cooperation Chinese Academy of Sciences ; Bureau of International Cooperation Chinese Academy of Sciences ; City Administration of Foreign Experts Affairs Dalian ; City Administration of Foreign Experts Affairs Dalian
WOS SubjectChemistry, Analytical ; Pharmacology & Pharmacy
WOS Research AreaChemistry ; Pharmacology & Pharmacy
WOS KeywordPANAX-GINSENG ; METABOLOMIC APPROACH ; GINSENOSIDES ; DIFFERENTIATION ; QUANTIFICATION ; CHROMATOGRAPHY ; DISCOVERY ; PRODUCTS
AbstractRed ginseng (RG) and white ginseng (WG), two processed products of Panax ginseng C. A. Meyer, are in high demand due to their unique features. In this study, some of these unique features were identified and confirmed as biomarkers of RG by using ultra-high-performance liquid chromatography-mass spectrometry, data mining, support vector machine, and artificial neural network. Principal component analysis showed clear separation between the RG and WG extracts, indicating the presence of potential discriminators. In addition, 20 features that are dominant in RG were found by data mining. Samples of Panax quinquefolium (PQ) and Panax notoginseng (PN), close relatives of Panax ginseng C.A.Meyer, were investigated and it was found that 17 features which were absent in PQ and PN samples, were present in RG and WG. Five of these markers were identified as nitrogen-containing compounds that have not been previously reported. Finally, we found that RG can be identified among different ginseng medicinal herbs including RG, WG, PQ and PN samples, by loading four feature markers corresponding to nitrogen-containing compounds into a discriminating model, based on a support vector machine or an artificial neural network. Thus, this study provides an efficient tool to identify RG during pharmacological research. (C) 2018 Elsevier B.V. All rights reserved.
Language英语
Funding OrganizationMinistry of Science and Technology of the People's Republic of China ; Ministry of Science and Technology of the People's Republic of China ; National Science Foundation ; National Science Foundation ; Bureau of International Cooperation Chinese Academy of Sciences ; Bureau of International Cooperation Chinese Academy of Sciences ; City Administration of Foreign Experts Affairs Dalian ; City Administration of Foreign Experts Affairs Dalian ; Ministry of Science and Technology of the People's Republic of China ; Ministry of Science and Technology of the People's Republic of China ; National Science Foundation ; National Science Foundation ; Bureau of International Cooperation Chinese Academy of Sciences ; Bureau of International Cooperation Chinese Academy of Sciences ; City Administration of Foreign Experts Affairs Dalian ; City Administration of Foreign Experts Affairs Dalian ; Ministry of Science and Technology of the People's Republic of China ; Ministry of Science and Technology of the People's Republic of China ; National Science Foundation ; National Science Foundation ; Bureau of International Cooperation Chinese Academy of Sciences ; Bureau of International Cooperation Chinese Academy of Sciences ; City Administration of Foreign Experts Affairs Dalian ; City Administration of Foreign Experts Affairs Dalian ; Ministry of Science and Technology of the People's Republic of China ; Ministry of Science and Technology of the People's Republic of China ; National Science Foundation ; National Science Foundation ; Bureau of International Cooperation Chinese Academy of Sciences ; Bureau of International Cooperation Chinese Academy of Sciences ; City Administration of Foreign Experts Affairs Dalian ; City Administration of Foreign Experts Affairs Dalian
WOS IDWOS:000456900700025
PublisherELSEVIER SCIENCE BV
Citation statistics
Document Type期刊论文
Identifierhttp://cas-ir.dicp.ac.cn/handle/321008/166233
Collection中国科学院大连化学物理研究所
Corresponding AuthorGao, Huiyuan; Zhang, Xiaozhe
Affiliation1.Shenyang Pharmaceut Univ, Minist Educ, Key Lab Struct Based Drug Design & Discovery, Shenyang, Liaoning, Peoples R China
2.Chinese Acad Sci, Dalian Inst Chem Phys, CAS Key Lab Separat Sci Analyt Chem, Dalian, Peoples R China
Recommended Citation
GB/T 7714
Zhao, Qiang,Zhao, Nan,Ye, Xueting,et al. Rapid discrimination between red and white ginseng based on unique mass-spectrometric features[J]. JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS,2019,164:202-210.
APA Zhao, Qiang.,Zhao, Nan.,Ye, Xueting.,He, Meixi.,Yang, Yiren.,...&Zhang, Xiaozhe.(2019).Rapid discrimination between red and white ginseng based on unique mass-spectrometric features.JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS,164,202-210.
MLA Zhao, Qiang,et al."Rapid discrimination between red and white ginseng based on unique mass-spectrometric features".JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS 164(2019):202-210.
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