Article(id=1241779360592629903, tenantId=1146029695717560320, journalId=1205117023404326918, issueId=1241779355555266850, articleNumber=null, orderNo=null, doi=10.16155/j.0254-1793.2024.05.17, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1687622400000, receivedDateStr=2023-06-25, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773992870710, onlineDateStr=2026-03-20, pubDate=1717084800000, pubDateStr=2024-05-31, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773992870710, onlineIssueDateStr=2026-03-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773992870710, creator=13701087609, updateTime=1773992870710, updator=13701087609, issue=Issue{id=1241779355555266850, tenantId=1146029695717560320, journalId=1205117023404326918, year='2024', volume='44', issue='5', pageStart='737', pageEnd='920', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773992869509, creator=13701087609, updateTime=1773992925624, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241779590985749489, tenantId=1146029695717560320, journalId=1205117023404326918, issueId=1241779355555266850, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241779590985749490, tenantId=1146029695717560320, journalId=1205117023404326918, issueId=1241779355555266850, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=882, endPage=892, ext={EN=ArticleExt(id=1241779365038592281, articleId=1241779360592629903, tenantId=1146029695717560320, journalId=1205117023404326918, language=EN, title=Quality evaluation of leaves of Cunninghamia lanceolata from different habitats by fingerprint and multi-component quantification combined with chemical pattern recognition*, columnId=1239148841803501731, journalTitle=Chinese Journal of Pharmaceutical Analysis, columnName=Quality Control, runingTitle=null, highlight=null, articleAbstract=
Objective:

To base on the method of HPLC fingerprint,multi-component quantification and chemical pattern recognition,to evaluate the quality of leaves of Cunninghamia lanceolata from different producing areas and to provide basis for further development and utilization.

Methods:

High-performance liquid chromatography (HPLC) was used to determine the contents of amentoflavone,bilobetin,hinokiflavone,ginkgetin,isoginkgetin and sciadopitysin in the Cunninghamia lanceolata. Fingerprints of 10 batches of Cunninghamia lanceolata from different habitats were established. Based on the common peak area of the fingerprint,the overall quality of Cunninghamia lanceolata was evaluated by principal component analysis(PCA),orthogonal partial least squares discriminant analysis(OPLS-DA),statistical analysis,and pattern recognition chemometrics methods.

Results:

A total of 14 common peaks in 10 batches of leaves of Cunninghamia lanceolata,and the similarity ranged from 0.955 to 1.000 with good consistency. The mass fractions of six biflavones in the sample were 2.42-5.24 mg·g-1,0.10-0.24 mg·g-1,1.55-3.67 mg·g-1,0.21-0.89 mg·g-1,0.10-0.24 mg·g-1 and 0.51-2.39 mg·g-1,respectively,including amentoflavone,bilobetin,hinokiflavone,ginkgetin,isoginkgetin and sciadopitysin. According PCA,the difference in the quality of Cunninghamia lanceolata from different habitats was further evaluated. Ten batches of medicinal materials were divided into three major categories,and four main factors affecting the classification of Cunninghamia lanceolata were found. Finally,OPLS-DA screened the excellent spectral peaks 6,12,7 (7-demethylated ginkgo biloba biflavone),13 (kumatsu biflavone),5 (Amentotaxus argotaenia biflavone),9 (chamaecypress biflavone) and 2,etc,seven differential markers can be used to distinguish different batches of Cunninghamia lanceolata.

Conclusion:

The established method is simple to stable and reliable. Combined with chemical pattern recognition,it can be used for the quality evaluation of Cunninghamia lanceolata.

, correspAuthors=Jian-you HUANG, Ling-feng JIANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Mei-mei GAO, Jian-you HUANG, Ya-nan ZHAI, Ling-feng JIANG, Guo-shou LU, Xiao-xi HU, Xue-qing XIA, Dong-mei LI), CN=ArticleExt(id=1241779368607945138, articleId=1241779360592629903, tenantId=1146029695717560320, journalId=1205117023404326918, language=CN, title=指纹图谱和多成分定量结合化学模式识别法评价不同产地杉木叶质量*, columnId=1239148842025799861, journalTitle=药物分析杂志, columnName=质量分析, runingTitle=null, highlight=null, articleAbstract=
目的:

基于指纹图谱、多成分定量及化学模式识别法结合的方法,评价不同产地杉木叶质量,为其深入开发利用提供依据。

方法:

采用HPLC法测定杉木叶中穗花杉双黄酮、7-去甲基银杏双黄酮、扁柏双黄酮、银杏双黄酮、异银杏双黄酮、金松双黄酮的含量;建立10批不同产地杉木叶指纹图谱;基于指纹图谱共有峰峰面积结果,采用主成分分析(PCA)、正交偏最小二乘判别分析(OPLS-DA)、统计学分析、模式识别的化学计量学方法评价杉木叶整体质量。

结果:

10批杉木叶共确定14个共有峰,相似度范围为0.955~1.000,具有较好的一致性;样品中穗花杉双黄酮、7-去甲基银杏双黄酮、扁柏双黄酮、银杏双黄酮、异银杏双黄酮、金松双黄酮6个双黄酮成分的质量分数分别为2.42~5.24、0.10~0.24、1.55~3.67、0.21~0.89、0.10~0.24、0.51~2.39 mg·g-1;通过PCA,进一步评价不同产地间杉木叶质量差异,将10批药材分为三大类,得到4个影响杉木叶分类的主要因子,最后采用OPLS-DA筛选出色谱峰6、12、7(7-去甲基银杏双黄酮)、13(金松双黄酮)、5(穗花杉双黄酮)、9(扁柏双黄酮)、2等7个差异标志物,可用于区分不同批次杉木叶。

结论:

建立的杉木叶质量评价方法稳定,结果可信,结合化学模式识别可用于杉木叶药材的质量品质评价。

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** 黄建猷 Tel:13077705656;E-mail:;
蒋凌风 Tel:18677179514;E-mail:
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J Shanghai Jiaotong Univ (Agric Sci)201129(5):67, articleTitle=Study on chemical constituents of the branches and leaves of Cunninghamia lanceolata, refAbstract=null)], funds=[Fund(id=1241779382293959579, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, awardId=桂科AD22035055, language=CN, fundingSource=广西科技基地和人才专项(桂科AD22035055), fundOrder=null, country=null), Fund(id=1241779382394622881, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, awardId=GZSY21-04, language=CN, fundingSource=广西中医药适宜技术开发与推广项目(GZSY21-04), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241779368867992005, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, xref=1., ext=[AuthorCompanyExt(id=1241779368876380614, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, companyId=1241779368867992005, language=EN, country=null, province=null, 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figs=[ArticleFig(id=1241779377780888373, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=EN, label=Fig.1, caption=HPLC overlay fingerprints(S1-S10)and reference fingerprint (R) of 10 batches of the leaves of Cunninghamia lanceolata, figureFileSmall=oD59qdxu34aTA+AcY03NCA==, figureFileBig=Ilt+R4aLelb3DsZyinsf6g==, tableContent=null), ArticleFig(id=1241779377923494712, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=CN, label=图1, caption=10批杉木叶样品的HPLC叠加指纹图谱(S1~S10)和对照指纹图谱(R), figureFileSmall=oD59qdxu34aTA+AcY03NCA==, figureFileBig=Ilt+R4aLelb3DsZyinsf6g==, tableContent=null), ArticleFig(id=1241779378149987139, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=EN, label=Fig.2, caption=HPLC chromatograms of mixed reference substance solution (A) and test solution (B), figureFileSmall=m9da5oRIhqxpAVzl/VP8BA==, figureFileBig=tdeTetGSuZ2z98ygC1CUcQ==, tableContent=null), ArticleFig(id=1241779378284204871, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=CN, label=图2, caption=混合对照品溶液(A)和供试品溶液(B)HPLC色谱图

1.穗花杉双黄酮(amentoflavone) 2. 7-去甲基银杏双黄酮(bilobetin) 3.扁柏双黄酮(hinokiflavone) 4.银杏双黄酮(ginkgetin) 5.异银杏双黄酮(isoginkgetin) 6.金松双黄酮(sciadopitysin)

, figureFileSmall=m9da5oRIhqxpAVzl/VP8BA==, figureFileBig=tdeTetGSuZ2z98ygC1CUcQ==, tableContent=null), ArticleFig(id=1241779378447782732, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=EN, label=Fig.3, caption=Dendrogram of CA of 10 baches of leaves of Cunninghamia lanceolata, figureFileSmall=1oLWkTfZEg2xF+bIp0K7+Q==, figureFileBig=WqcCLfm3dYuJmmOk74FUxw==, tableContent=null), ArticleFig(id=1241779378561028944, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=CN, label=图3, caption=10批杉木叶CA树状图, figureFileSmall=1oLWkTfZEg2xF+bIp0K7+Q==, figureFileBig=WqcCLfm3dYuJmmOk74FUxw==, tableContent=null), ArticleFig(id=1241779378678469462, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=EN, label=Fig.4, caption=PCA plot (A) and scattered score plot of OPLS-DA (B), figureFileSmall=dLtfIsgDzclGrXS9l+GSyw==, figureFileBig=F1YxVijhd2Bc1TFAaXZREA==, tableContent=null), ArticleFig(id=1241779378800104281, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=CN, label=图4, caption=PCA (A)和OPLS-DA (B)得分散点图, figureFileSmall=dLtfIsgDzclGrXS9l+GSyw==, figureFileBig=F1YxVijhd2Bc1TFAaXZREA==, tableContent=null), ArticleFig(id=1241779378917544796, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=EN, label=Fig.5, caption=OPLS-DA replacement test chart (A) and VIP chart of each component of 10 batches of samples (B), figureFileSmall=EKAEBq6cKm8ruGRjI4ui9A==, figureFileBig=cbtENsV6G0M7WGlGJ954Eg==, tableContent=null), ArticleFig(id=1241779379026596704, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=CN, label=图5, caption=OPLS-DA置换检验图(A)和10批样品各成分VIP图(B), figureFileSmall=EKAEBq6cKm8ruGRjI4ui9A==, figureFileBig=cbtENsV6G0M7WGlGJ954Eg==, tableContent=null), ArticleFig(id=1241779380607849318, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=EN, label=Tab.1, caption=

Source of medicinal materials of leaves of Cunninghamia lanceolata

, figureFileSmall=null, figureFileBig=null, tableContent=
编号
(No.)
产地
(habitat)
收集时间
(collection date)
编号
(No.)
产地
(habitat)
收集时间
(collection date)
S1广西柳州市融水县(Rongshui County,Liuzhou City,Guangxi Zhuang Autonomous Region)2020-11-16S6贵州六盘水市(Liupanshui City,Guizhou Province)2022-07-20
S2广西来宾市象州县(Xiangzhou County,Laibin City,Guangxi Zhuang Autonomous Region)2020-11-13S7广西桂林市全州县(Quanzhou County,Guilin City,Guangxi Zhuang Autonomous Region)2022-07-16
S3广西贵港市平南县(Pingnan County,Guigang City,Guangxi Zhuang Autonomous Region)2020-11-12S8广西钦州市(Qinzhou City,Guangxi Zhuang Autonomous Region)2022-07-19
S4广西贵港市平南县(Pingnan County,Guigang City,Guangxi Zhuang Autonomous Region)2020-12-17S9广东揭阳市揭西县(Jiexi County,Jieyang City,Guangdong Province)2022-07-17
S5福建福清市(Fuqing City,Fujian Province)2022-07-18S10湖南湘西土家族苗族自治州(Xiangxi Tujia and Miao Autonomous Prefecture,Hunan Province)2022-05-21
), ArticleFig(id=1241779380700124010, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=CN, label=表1, caption=

杉木叶药材来源信息

, figureFileSmall=null, figureFileBig=null, tableContent=
编号
(No.)
产地
(habitat)
收集时间
(collection date)
编号
(No.)
产地
(habitat)
收集时间
(collection date)
S1广西柳州市融水县(Rongshui County,Liuzhou City,Guangxi Zhuang Autonomous Region)2020-11-16S6贵州六盘水市(Liupanshui City,Guizhou Province)2022-07-20
S2广西来宾市象州县(Xiangzhou County,Laibin City,Guangxi Zhuang Autonomous Region)2020-11-13S7广西桂林市全州县(Quanzhou County,Guilin City,Guangxi Zhuang Autonomous Region)2022-07-16
S3广西贵港市平南县(Pingnan County,Guigang City,Guangxi Zhuang Autonomous Region)2020-11-12S8广西钦州市(Qinzhou City,Guangxi Zhuang Autonomous Region)2022-07-19
S4广西贵港市平南县(Pingnan County,Guigang City,Guangxi Zhuang Autonomous Region)2020-12-17S9广东揭阳市揭西县(Jiexi County,Jieyang City,Guangdong Province)2022-07-17
S5福建福清市(Fuqing City,Fujian Province)2022-07-18S10湖南湘西土家族苗族自治州(Xiangxi Tujia and Miao Autonomous Prefecture,Hunan Province)2022-05-21
), ArticleFig(id=1241779380813370221, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=EN, label=Tab.2, caption=

Inspection the linearity of six biflavones of leaves of Cunninghamia lanceolata

, figureFileSmall=null, figureFileBig=null, tableContent=
成分(component)回归方程(regression equation)r线性范围(linearity range)/μg
穗花杉双黄酮(amentoflavone)Y=3.448×105X+6.123×1050.999 40.124~1.24
7-去甲基银杏双黄酮(bilobetin)Y=4.560×103X+6.758×1030.999 50.005 76~0.057 6
扁柏双黄酮(hinokiflavone)Y=4.826×103X+7.950×1040.998 90.071 68~0.716 8
银杏双黄酮(ginkgetin)Y=1.692×104X+2.720×1040.997 80.010 8~0.108
异银杏双黄酮(isoginkgetin)Y=9.072×103X+1.561×1040.999 80.003 68~0.036 8
金松双黄酮(sciadopitysin)Y=2.226×105X+3.074×1040.999 30.036 08~0.360 8
), ArticleFig(id=1241779380935005042, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=CN, label=表2, caption=

杉木叶药材中6个双黄酮成分线性关系考察

, figureFileSmall=null, figureFileBig=null, tableContent=
成分(component)回归方程(regression equation)r线性范围(linearity range)/μg
穗花杉双黄酮(amentoflavone)Y=3.448×105X+6.123×1050.999 40.124~1.24
7-去甲基银杏双黄酮(bilobetin)Y=4.560×103X+6.758×1030.999 50.005 76~0.057 6
扁柏双黄酮(hinokiflavone)Y=4.826×103X+7.950×1040.998 90.071 68~0.716 8
银杏双黄酮(ginkgetin)Y=1.692×104X+2.720×1040.997 80.010 8~0.108
异银杏双黄酮(isoginkgetin)Y=9.072×103X+1.561×1040.999 80.003 68~0.036 8
金松双黄酮(sciadopitysin)Y=2.226×105X+3.074×1040.999 30.036 08~0.360 8
), ArticleFig(id=1241779381031474037, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=EN, label=Tab.3, caption=

Recovery results of six biflavones of the leaves of Cunninghamia lanceolata

, figureFileSmall=null, figureFileBig=null, tableContent=
成分
(component)
样品含量
(content)/mg
加入量
(added)/mg
测得量
(measured)/mg
回收率
(recovery)/%
平均回收率
(average recovery)/%
RSD/%
穗花杉双黄酮(amentoflavone)0.6170.6201.22698.298.70.99
0.6150.6201.237100.3
0.6100.6201.22599.2
0.6240.6201.23698.7
0.6210.6201.22597.4
0.6310.6201.24198.4
7-去甲基银杏双黄酮(bilobetin)0.027 50.028 80.056 8101.7101.01.6
0.027 40.028 80.056 9102.4
0.027 20.028 80.056 3101.0
0.027 80.028 80.057 2102.1
0.027 70.028 80.055 997.9
0.028 10.028 80.057 1100.7
扁柏双黄酮(hinokiflavone)0.3660.3580.72098.999.11.6
0.3650.3580.725100.6
0.3620.3580.725101.4
0.3710.3580.72197.8
0.3690.3580.72298.6
0.3750.3580.72497.5
银杏双黄酮(ginkgetin)0.1070.1080.21297.299.72.2
0.1070.1080.21499.1
0.1060.1080.21298.2
0.1080.1080.21599.1
0.1080.1080.219102.8
0.1090.1080.219101.8
异银杏双黄酮(isoginkgetin)0.036 60.036 80.072 898.498.52.0
0.036 50.036 80.072 497.6
0.036 20.036 80.072 097.3
0.037 10.036 80.072 997.3
0.036 90.036 80.072 997.8
0.037 50.036 80.075 2102.4
金松双黄酮(sciadopitysin)0.3650.3610.72098.3100.32.1
0.3640.3610.71697.5
0.3610.3610.725100.8
0.3690.3610.738102.2
0.3680.3610.739102.8
0.3730.3610.735100.3
), ArticleFig(id=1241779381161497464, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=CN, label=表3, caption=

杉木叶药材中6个双黄酮加样回收结果(n=6)

, figureFileSmall=null, figureFileBig=null, tableContent=
成分
(component)
样品含量
(content)/mg
加入量
(added)/mg
测得量
(measured)/mg
回收率
(recovery)/%
平均回收率
(average recovery)/%
RSD/%
穗花杉双黄酮(amentoflavone)0.6170.6201.22698.298.70.99
0.6150.6201.237100.3
0.6100.6201.22599.2
0.6240.6201.23698.7
0.6210.6201.22597.4
0.6310.6201.24198.4
7-去甲基银杏双黄酮(bilobetin)0.027 50.028 80.056 8101.7101.01.6
0.027 40.028 80.056 9102.4
0.027 20.028 80.056 3101.0
0.027 80.028 80.057 2102.1
0.027 70.028 80.055 997.9
0.028 10.028 80.057 1100.7
扁柏双黄酮(hinokiflavone)0.3660.3580.72098.999.11.6
0.3650.3580.725100.6
0.3620.3580.725101.4
0.3710.3580.72197.8
0.3690.3580.72298.6
0.3750.3580.72497.5
银杏双黄酮(ginkgetin)0.1070.1080.21297.299.72.2
0.1070.1080.21499.1
0.1060.1080.21298.2
0.1080.1080.21599.1
0.1080.1080.219102.8
0.1090.1080.219101.8
异银杏双黄酮(isoginkgetin)0.036 60.036 80.072 898.498.52.0
0.036 50.036 80.072 497.6
0.036 20.036 80.072 097.3
0.037 10.036 80.072 997.3
0.036 90.036 80.072 997.8
0.037 50.036 80.075 2102.4
金松双黄酮(sciadopitysin)0.3650.3610.72098.3100.32.1
0.3640.3610.71697.5
0.3610.3610.725100.8
0.3690.3610.738102.2
0.3680.3610.739102.8
0.3730.3610.735100.3
), ArticleFig(id=1241779381266355067, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=EN, label=Tab.4, caption=

Determination results of samples

, figureFileSmall=null, figureFileBig=null, tableContent=
编号
(number)
质量分数(quality score)/(mg·g-1
穗花杉双黄酮
(amentoflavone)
7-去甲基银杏双黄酮
(bilobetin)
扁柏双黄酮
(hinokiflavone)
银杏双黄酮
(ginkgetin)
异银杏双黄酮
(isoginkgetin)
金松双黄酮
(sciadopitysin)
S14.040.182.420.700.242.39
S25.220.122.710.460.131.43
S33.600.101.550.320.141.18
S43.710.101.650.350.141.23
S54.170.192.200.680.131.28
S62.420.111.600.210.100.51
S74.040.123.670.860.101.94
S84.100.242.050.890.121.30
S95.240.192.530.860.162.34
S103.900.112.060.560.111.05
), ArticleFig(id=1241779381404767105, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=CN, label=表4, caption=

样品含量测定结果(n=2)

, figureFileSmall=null, figureFileBig=null, tableContent=
编号
(number)
质量分数(quality score)/(mg·g-1
穗花杉双黄酮
(amentoflavone)
7-去甲基银杏双黄酮
(bilobetin)
扁柏双黄酮
(hinokiflavone)
银杏双黄酮
(ginkgetin)
异银杏双黄酮
(isoginkgetin)
金松双黄酮
(sciadopitysin)
S14.040.182.420.700.242.39
S25.220.122.710.460.131.43
S33.600.101.550.320.141.18
S43.710.101.650.350.141.23
S54.170.192.200.680.131.28
S62.420.111.600.210.100.51
S74.040.123.670.860.101.94
S84.100.242.050.890.121.30
S95.240.192.530.860.162.34
S103.900.112.060.560.111.05
), ArticleFig(id=1241779381538984837, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=EN, label=Tab.5, caption=

Characteristic value and cumulative contribution rate

, figureFileSmall=null, figureFileBig=null, tableContent=
主成分
(principal component)
特征值
(eigenvalue)
贡献率
(contribution rate)/%
累积贡献率
(accumulated contribution rate)/%
15.28837.77137.771
23.19822.84560.616
32.14815.34375.959
41.53410.95686.915
), ArticleFig(id=1241779381635453831, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=CN, label=表5, caption=

特征值与累计贡献率

, figureFileSmall=null, figureFileBig=null, tableContent=
主成分
(principal component)
特征值
(eigenvalue)
贡献率
(contribution rate)/%
累积贡献率
(accumulated contribution rate)/%
15.28837.77137.771
23.19822.84560.616
32.14815.34375.959
41.53410.95686.915
), ArticleFig(id=1241779381773865867, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=EN, label=Tab.6, caption=

Factor load matrix

, figureFileSmall=null, figureFileBig=null, tableContent=
共有峰编号
(common peak number)
主成分1
(principal component 1)
主成分2
(principal component 2)
主成分3
(principal component 3)
主成分4
(principal component 4)
60.9020.057-0.1090.160
120.890-0.3660.0070.197
50.8600.127-0.1290.196
130.746-0.283-0.399-0.276
100.7110.5220.002-0.423
90.7000.347-0.2940.113
110.689-0.4390.401-0.159
70.5760.3470.465-0.538
140.2310.7900.558-0.012
80.270-0.7760.2790.423
20.1810.689-0.1050.548
10.583-0.5890.1700.064
30.0720.2920.7640.536
40.2620.355-0.6960.280
), ArticleFig(id=1241779381916472207, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=CN, label=表6, caption=

因子载荷矩阵

, figureFileSmall=null, figureFileBig=null, tableContent=
共有峰编号
(common peak number)
主成分1
(principal component 1)
主成分2
(principal component 2)
主成分3
(principal component 3)
主成分4
(principal component 4)
60.9020.057-0.1090.160
120.890-0.3660.0070.197
50.8600.127-0.1290.196
130.746-0.283-0.399-0.276
100.7110.5220.002-0.423
90.7000.347-0.2940.113
110.689-0.4390.401-0.159
70.5760.3470.465-0.538
140.2310.7900.558-0.012
80.270-0.7760.2790.423
20.1810.689-0.1050.548
10.583-0.5890.1700.064
30.0720.2920.7640.536
40.2620.355-0.6960.280
), ArticleFig(id=1241779381996163987, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=EN, label=Tab.7, caption=

Factor scores and sorting of principal components of 10 batches of leaves of Cunninghamia lanceolata

, figureFileSmall=null, figureFileBig=null, tableContent=
编号(No.)F1F2F3F4F排序(sort)
S11.040-1.7551.099-0.8240.0815
S20.767-0.8030.0191.5520.3213
S3-0.537-0.689-0.485-0.038-0.5059
S4-0.503-0.733-0.4060.045-0.4778
S5-0.0631.4001.9530.8850.7971
S6-2.0750.0140.1090.445-0.82310
S70.6910.893-1.626-0.1000.2354
S8-0.0010.8180.483-2.1590.0286
S91.2810.912-0.4450.4420.7742
S10-0.601-0.057-0.701-0.248-0.4317
), ArticleFig(id=1241779382096827287, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1241779360592629903, language=CN, label=表7, caption=

10批杉木叶的主成分因子得分和排序

, figureFileSmall=null, figureFileBig=null, tableContent=
编号(No.)F1F2F3F4F排序(sort)
S11.040-1.7551.099-0.8240.0815
S20.767-0.8030.0191.5520.3213
S3-0.537-0.689-0.485-0.038-0.5059
S4-0.503-0.733-0.4060.045-0.4778
S5-0.0631.4001.9530.8850.7971
S6-2.0750.0140.1090.445-0.82310
S70.6910.893-1.626-0.1000.2354
S8-0.0010.8180.483-2.1590.0286
S91.2810.912-0.4450.4420.7742
S10-0.601-0.057-0.701-0.248-0.4317
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指纹图谱和多成分定量结合化学模式识别法评价不同产地杉木叶质量*
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高美美 1, 2 , 黄建猷 3, 4, ** , 翟雅南 1, 2 , 蒋凌风 2, ** , 陆国寿 3 , 胡筱希 3 , 閤雪晴 1 , 李冬梅 3
药物分析杂志 | 质量分析 2024,44(5): 882-892
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药物分析杂志 | 质量分析 2024, 44(5): 882-892
指纹图谱和多成分定量结合化学模式识别法评价不同产地杉木叶质量*
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高美美1, 2 , 黄建猷3, 4, ** , 翟雅南1, 2, 蒋凌风2, ** , 陆国寿3, 胡筱希3, 閤雪晴1, 李冬梅3
作者信息
  • 1.广西中医药大学研究生院,南宁 530200
  • 2.广西中医药大学科学实验中心,南宁 530200
  • 3.广西壮族自治区中医药研究院,南宁 530022
  • 4.广西中药质量标准重点实验室,南宁 530022
  • Tel:17884801854;E-mail:

通讯作者:

** 黄建猷 Tel:13077705656;E-mail:;
蒋凌风 Tel:18677179514;E-mail:
Quality evaluation of leaves of Cunninghamia lanceolata from different habitats by fingerprint and multi-component quantification combined with chemical pattern recognition*
Mei-mei GAO1, 2 , Jian-you HUANG3, 4, ** , Ya-nan ZHAI1, 2, Ling-feng JIANG2, ** , Guo-shou LU3, Xiao-xi HU3, Xue-qing XIA1, Dong-mei LI3
Affiliations
  • 1.Graduate School of Guangxi University of Chinese Medicine, Nanning 530200, China
  • 2.Scientific Experimental Center of Guangxi University of Traditinal Chinese Medicine, Nanning 530200, China
  • 3.Guangxi Institute of Traditional Medical and Pharmaceutical Sciences, Nanning 530022, China
  • 4.Guangxi Key Laboratory of Traditional Chinese Medicine Quality Standards, Nanning 530022, China
出版时间: 2024-05-31 doi: 10.16155/j.0254-1793.2024.05.17
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目的:

基于指纹图谱、多成分定量及化学模式识别法结合的方法,评价不同产地杉木叶质量,为其深入开发利用提供依据。

方法:

采用HPLC法测定杉木叶中穗花杉双黄酮、7-去甲基银杏双黄酮、扁柏双黄酮、银杏双黄酮、异银杏双黄酮、金松双黄酮的含量;建立10批不同产地杉木叶指纹图谱;基于指纹图谱共有峰峰面积结果,采用主成分分析(PCA)、正交偏最小二乘判别分析(OPLS-DA)、统计学分析、模式识别的化学计量学方法评价杉木叶整体质量。

结果:

10批杉木叶共确定14个共有峰,相似度范围为0.955~1.000,具有较好的一致性;样品中穗花杉双黄酮、7-去甲基银杏双黄酮、扁柏双黄酮、银杏双黄酮、异银杏双黄酮、金松双黄酮6个双黄酮成分的质量分数分别为2.42~5.24、0.10~0.24、1.55~3.67、0.21~0.89、0.10~0.24、0.51~2.39 mg·g-1;通过PCA,进一步评价不同产地间杉木叶质量差异,将10批药材分为三大类,得到4个影响杉木叶分类的主要因子,最后采用OPLS-DA筛选出色谱峰6、12、7(7-去甲基银杏双黄酮)、13(金松双黄酮)、5(穗花杉双黄酮)、9(扁柏双黄酮)、2等7个差异标志物,可用于区分不同批次杉木叶。

结论:

建立的杉木叶质量评价方法稳定,结果可信,结合化学模式识别可用于杉木叶药材的质量品质评价。

杉木叶  /  指纹图谱  /  相似度评价  /  含量测定  /  化学模式识别  /  聚类分析  /  主成分分析  /  双黄酮  /  正交偏最小二乘判别分析
Objective:

To base on the method of HPLC fingerprint,multi-component quantification and chemical pattern recognition,to evaluate the quality of leaves of Cunninghamia lanceolata from different producing areas and to provide basis for further development and utilization.

Methods:

High-performance liquid chromatography (HPLC) was used to determine the contents of amentoflavone,bilobetin,hinokiflavone,ginkgetin,isoginkgetin and sciadopitysin in the Cunninghamia lanceolata. Fingerprints of 10 batches of Cunninghamia lanceolata from different habitats were established. Based on the common peak area of the fingerprint,the overall quality of Cunninghamia lanceolata was evaluated by principal component analysis(PCA),orthogonal partial least squares discriminant analysis(OPLS-DA),statistical analysis,and pattern recognition chemometrics methods.

Results:

A total of 14 common peaks in 10 batches of leaves of Cunninghamia lanceolata,and the similarity ranged from 0.955 to 1.000 with good consistency. The mass fractions of six biflavones in the sample were 2.42-5.24 mg·g-1,0.10-0.24 mg·g-1,1.55-3.67 mg·g-1,0.21-0.89 mg·g-1,0.10-0.24 mg·g-1 and 0.51-2.39 mg·g-1,respectively,including amentoflavone,bilobetin,hinokiflavone,ginkgetin,isoginkgetin and sciadopitysin. According PCA,the difference in the quality of Cunninghamia lanceolata from different habitats was further evaluated. Ten batches of medicinal materials were divided into three major categories,and four main factors affecting the classification of Cunninghamia lanceolata were found. Finally,OPLS-DA screened the excellent spectral peaks 6,12,7 (7-demethylated ginkgo biloba biflavone),13 (kumatsu biflavone),5 (Amentotaxus argotaenia biflavone),9 (chamaecypress biflavone) and 2,etc,seven differential markers can be used to distinguish different batches of Cunninghamia lanceolata.

Conclusion:

The established method is simple to stable and reliable. Combined with chemical pattern recognition,it can be used for the quality evaluation of Cunninghamia lanceolata.

leaves of Cunninghamia lanceolata  /  fingerprints  /  similarity evaluation  /  content determination  /  chemical pattern recognition  /  cluster analysis  /  principal component analysis  /  biflavone  /  orthogonal partial least squares discriminant analysis
高美美, 黄建猷, 翟雅南, 蒋凌风, 陆国寿, 胡筱希, 閤雪晴, 李冬梅. 指纹图谱和多成分定量结合化学模式识别法评价不同产地杉木叶质量*. 药物分析杂志, 2024 , 44 (5) : 882 -892 . DOI: 10.16155/j.0254-1793.2024.05.17
Mei-mei GAO, Jian-you HUANG, Ya-nan ZHAI, Ling-feng JIANG, Guo-shou LU, Xiao-xi HU, Xue-qing XIA, Dong-mei LI. Quality evaluation of leaves of Cunninghamia lanceolata from different habitats by fingerprint and multi-component quantification combined with chemical pattern recognition*[J]. Chinese Journal of Pharmaceutical Analysis, 2024 , 44 (5) : 882 -892 . DOI: 10.16155/j.0254-1793.2024.05.17
瑶药杉木叶为杉科植物杉木Cunninghamia lanceolata(Lamb.)Hook.的干燥叶或带叶嫩枝,又名杉木叶,杉树叶。杉木广泛分布于广西、广东、湖南等地,为南方主要经济林种之一[1]。杉木叶入药始载于《本草纲目》,《中华本草》《广西民族药简编》《广西本草选编》、1996年版《广西中药材标准》等均有收载,即将颁布的《广西瑶药材质量标准》第二卷也将其收录。中医认为其味辛,微温,归肺、脾经,祛风止痛,散瘀止血,用于慢性气管炎、胃痛、风湿关节痛、跌打损伤、烧烫伤、外伤出血、过敏性皮炎、淋病、疥癣、蜈蚣咬伤、毒虫咬伤、风疹;瑶医认为其淡,温,属打药,解表祛痧、利湿消肿、活血通络,用于扑哈(感冒)、风闷(风湿骨痛、风湿关节炎)[2-3]。杉木叶现有的质量控制手段相对滞后,尚无对杉木叶质量进行综合评价的研究报道。如1996年版《广西中药材标准》与拟颁布的《广西瑶药材质量标准》第二卷建立的杉木叶药材质量标准仅有性状、显微鉴别、理化鉴别项[3]。此外,刘娟等[4]、张曼等[5]、刘进鹏等[6]开展了杉木枝叶中2个双黄酮类成分的含量测定研究工作,所测定的成分较少,指纹图谱也尚未确立,难以对杉木叶的质量差异进行系统评价。
色谱指纹图谱质量控制模式是一种综合的、可量化的质量控制模式,将其用于中药材的质量控制,对中药材的真实性和质量的一致性、稳定性均能较好地进行检测及控制[7]。在指纹图谱质量控制的基础上,结合多成分定量及化学模式识别法已经成为中药材质量综合评价的一种发展趋势,可较好地建立全面合理的中药材质量评价方法,用来促进药材的规范化应用及开发利用[8]
本研究开展并建立了杉木叶药材的指纹图谱,指认并测定了杉木叶中穗花杉双黄酮、7-去甲基银杏双黄酮、扁柏双黄酮、银杏双黄酮、异银杏双黄酮、金松双黄酮等6个双黄酮类成分的含量,并采用数据统计分析软件SPSS 25.0,对10批杉木叶药材指纹图谱进行了聚类分析(cluster analysis,CA)及主成分分析(principal component analysis,PCA),对不同产地杉木叶药材质量进行评价,旨在为完善杉木叶药材质量标准提供参考。
Waters高效液相色谱仪(2998 PDA Detector,Waters e2695 Separations Module,Empower 3色谱工作站,Waters公司);XS-205型万分之一电子天平(梅特勒公司);KS-3200DE液晶超声波清洗器(昆山洁力美超声仪器有限公司)。
对照品穗花杉双黄酮(批号P01D11F132895,含量以98.0%计)、金松双黄酮(批号P20N10F103774,含量以98.0%计)、扁柏双黄酮(批号R11A9F54295,含量以98.0%计)均购于上海源叶生物科技有限公司,银杏双黄酮(批号210923,含量以98.0%计)、异银杏双黄酮(批号211219,含量以98.0%计)、7-去甲基银杏双黄酮(批号220326,含量以98.0%计)由成都植标化纯生物技术有限公司、四川质标生物科技有限公司联合研制。色谱纯乙腈(默克股份两合公司),娃哈哈纯净水,其余试剂均为分析纯。
共收集杉木叶药材10批,经广西中医药研究院陆国寿主任药师鉴定为杉科植物杉木Cunninghamia lanceolata(Lamb.)Hook.的叶。具体信息见表1
Waters XBridge® C18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),梯度洗脱(0~5 min,10%A→30%A;5~35 min,30%A→80%A;35~40 min,80%A→10%A;40~45 min,10%A),体积流量1 mL·min-1,柱温25 ℃,检测波长340 nm,进样量10 μL。
取杉木叶药材粉末(过60目筛)约0.3 g,精密称定,置圆底烧瓶中,精密加入80%乙醇水25 mL,称定质量,水浴上加热回流1 h,放至室温,用80%乙醇水补足减失的质量,摇匀,0.45 μm微孔滤膜滤过,取续滤液,即得。
分别精密称取对照品穗花杉双黄酮、7-去甲基银杏双黄酮、扁柏双黄酮、银杏双黄酮、异银杏双黄酮和金松双黄酮适量,加甲醇制成质量浓度分别为310.0、14.4、179.2、54.0、18.4、180.4 μg·mL-1的混合对照品储备液。精密吸取该储备液2 mL,置10 mL量瓶中,加甲醇稀释并定容至刻度,摇匀,即得。
取杉木叶药材(S1)粉末约0.3 g,精密称定,按“2.2”项下方法制备供试品溶液,按“2.1”项下色谱条件连续进样6次,记录色谱图,以9号峰(扁柏双黄酮)为参照峰(S),计算各共有峰相对保留时间的RSD均<0.12%,相对峰面积的RSD均<2.0%,表明仪器精密度良好。
取杉木叶药材(S1)粉末约0.3 g,精密称定,按“2.2”项下方法制备供试品溶液,按“2.1”项下色谱条件,分别在0、2、4、8、12、24 h进行测定,记录色谱图,以9号峰(扁柏双黄酮)为参照峰(S),计算各共有峰相对保留时间的RSD均<0.14%,相对峰面积的RSD均<2.8%,表明供试品溶液在24 h内稳定性良好。
取杉木叶药材(S1)粉末约0.3 g,精密称定,按“2.2”项下方法平行制备6份供试品溶液,按“2.1”项下色谱条件测定,记录色谱图,以9号峰(扁柏双黄酮)为参照峰(S),计算各共有峰相对保留时间的RSD均<0.13%,相对峰面积的RSD均<1.8%,表明该方法的重复性良好。
取10批不同产地杉木叶药材,分别按“2.2”项下方法制备供试品溶液,按“2.1”项下色谱条件进样测定,记录色谱图。将10批杉木叶药材样品的HPLC图谱导入“中药色谱指纹图谱相似度评价系统(2004A版)”,以样品S1的色谱图为参照指纹图谱,采用中位数法生成对照指纹图谱(R),经多点校正后自动匹配,得到10批样品的HPLC色谱叠加指纹图谱(图1)。
以对照指纹图谱为参照,对各样品图谱的相似度进行评价,结果显示各样品图谱与对照指纹图谱的相似度在0.955~1.000,说明10批杉木叶药材样品具有较高的相似度,化学成分稳定。
10批杉木叶样品中共标定了14个共有峰,与对照品色谱图进行比对,指认了其中6个成分,分别为穗花杉双黄酮(5号峰)、7-去甲基银杏双黄酮(7号峰)、扁柏双黄酮(9号峰)、银杏双黄酮(10号峰)、异银杏双黄酮(11号峰)、金松双黄酮(13号峰)。
Waters XBridge® C18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),梯度洗脱(0~30 min,30%A→80%A;30~35 min,80%A→30%A;35~40 min,30%A),体积流量1 mL min-1,柱温25 ℃,检测波长340 nm,进样量为10 μL。按此色谱条件进行分析,穗花杉双黄酮、7-去甲基银杏双黄酮、扁柏双黄酮、银杏双黄酮、异银杏双黄酮和金松双黄酮6个成分的理论塔板数均≥5 000,分离度均>1.5,各成分测定均不受其他成分干扰。混合对照品和供试品色谱图见图2
分别精密吸取“2.3”项下混合对照品溶液2、4、8、12、16、20 μL,按“2.6.1”项下色谱条件分别进样并记录各成分峰面积,以各成分的质量X为横坐标,峰面积均值Y为纵坐标进行线性回归(表2)。由表2可知,6个双黄酮成分在各自的质量浓度范围内与峰面积呈良好的线性关系。
取杉木叶药材(S1)粉末约0.3 g,精密称定,按“2.2”项下方法制备供试品溶液,按“2.6.1”项下色谱条件连续进样6次,记录各成分峰面积。穗花杉双黄酮、7-去甲基银杏双黄酮、扁柏双黄酮、银杏双黄酮、异银杏双黄酮和金松双黄酮峰面积的RSD分别为1.0%、1.2%、1.5%、1.1%、1.2%、0.90%,表明仪器精密度良好。
取杉木叶药材(S1)粉末约0.3 g,精密称定,按“2.2”项下方法制备供试品溶液,按“2.6.1”项下色谱条件,分别在0、2、4、8、12、24 h进行测定,记录各成分峰面积。穗花杉双黄酮、7-去甲基银杏双黄酮、扁柏双黄酮、银杏双黄酮、异银杏双黄酮和金松双黄酮峰面积的RSD分别为2.1%、1.8%、2.6%、1.4%、1.9%、1.6%,表明供试品溶液在24 h内稳定性良好。
取杉木叶药材(S1)粉末约0.3 g,精密称定,按“2.2”项下方法平行制备6份供试品溶液,按“2.6.1”项下色谱条件测定,记录各成分峰面积并计算其含量。结果穗花杉双黄酮、7-去甲基银杏双黄酮、扁柏双黄酮、银杏双黄酮、异银杏双黄酮和金松双黄酮的平均质量分数分别为4.04、0.18、2.40、0.70、0.24、2.39 mg·g-1,RSD分别为1.8%、2.0%、2.0%、2.0%、1.5%、1.1%,表明该方法的重复性良好。
取已知含量的杉木叶药材(S1)粉末6份,每份约0.15 g,精密称定,加入“2.3”项下混合对照品储备液2 mL,按“2.2”项下方法制备供试溶液,按“2.6.1”项下色谱条件测定,计算平均回收率,结果见表3。由表3可知,该方法的准确度良好。
取10批不同产地的杉木叶药材粉末,按“2.2”项下方法制备供试品溶液,平行2份,按“2.6.1”项下色谱条件测定,记录色谱峰面积,计算样品中穗花杉双黄酮、7-去甲基银杏双黄酮、扁柏双黄酮、银杏双黄酮、异银杏双黄酮、金松双黄酮6个成分的含量。结果见表4
将10批杉木叶样品指纹图谱中14个共有峰面积为变量导入SPSS 25.0软件,采用组间连接法,以平方欧式距离进行聚类分析(CA),结果见图3。结果显示,当分类距离为5时,10批样品可分为3类,S1、S3~S5、S8、S10为第Ⅰ类,S2、S7、S9为第Ⅱ类,S6为第Ⅲ类。
以10批杉木叶药材指纹图谱的共有峰面积为变量,使用SPSS 25.0软件进行主成分分析(PCA)。共提取了4个主成分,其中主成分1的特征值为5.288,方差贡献率为37.771%,主要反映了1、5~7、9~13号峰的信息;主成分2的特征值为3.198,方差贡献率为22.845%,主要反映了2、10、14号峰的信息;主成分3的特征值为2.148,方差贡献率为15.343%,主要反映了3、14号峰的信息;主成分4的特征值为1.534,方差贡献率为10.956%,主要反映了2、3号峰的信息。4个主成分的累积方差贡献率为86.915%,表明这4个主成分能够反映杉木叶药材提取的大部分信息,能代表10批药材中14个共有峰的峰面积,也提示多个成分影响了杉木叶药材质量。结果见表56
运用SPSS 25.0软件计算10批杉木叶的主成分得分,根据各主成分的贡献率,计算出综合得分F,其公式为F=37.771F1/86.915+22.845F2/86.915+15.343F3/86.915+10.956F4/86.915(F1F2F3F4依次为主成分1、2、3、4的得分),结果见表7。排序前3位的样品分别为S5、S9、S2,说明这3个批次的杉木叶药材质量较好;样品S2和S9综合排名靠前,与其他样品差异较大,这与CA结果一致。
为了进一步探寻杉木叶不同批次之间产生差异性的主要标志物,采用正交偏最小二乘判别分析(OPLS-DA)对杉木叶样品进行分析。将10批杉木叶样品的14个共有峰导入SIMCA 14.1软件中,相关模型图见图4-B。该OPLS-DA模型中,累积解释能力参数()和()均为0.999,预测能力参数(Q2)为0.9,均>0.5,接近1,说明所建立的模型稳定、可靠。由OPLS-DA得分图可知,10批杉木叶样品被很好地分为3类,根据模型中变量权重重要性排序VIP预测值筛选具有统计学意义的差异标志物,结果见图5-B,在0.95的置信区间内,选出VIP>1.0的色谱峰为差异标志物,峰6、12、7(7-去甲基银杏双黄酮)、13(金松双黄酮)、5(穗花杉双黄酮)、9(扁柏双黄酮)、2的VIP值分别为1.166 51、1.145 01、1.121 32、1.105 42、1.094 23、1.054 21、1.019 54,均>1,可作为鉴别和区分杉木叶质量的标志物。为防止该模型过拟合造成假阳性结果,设置分类Y矩阵变量随机排列200次做置换检验,得置换检验图(图5-A),R2回归线在Y轴截距为0.92,Q2回归线在Y轴截距为-3.88,说明所建立的模型没有出现过拟合现象,可用于判别分析10批样品的组间差异。计算差异标志物峰面积在共有峰峰面积中的占比,可知10批样品的差异标志物中穗花杉双黄酮平均占比最高(53.14%),扁柏双黄酮占比其次(21.95%),且这些成分RSD均>18.82%,表明这些成分在各批次间含量差异较大。
综上所述,结合OPLS-DA中VIP值筛选、对照品指认,7-去甲基银杏双黄酮、金松双黄酮、穗花杉双黄酮、扁柏双黄酮可作为杉木叶药材的差异标志物。
本研究收集了10批不同产地杉木叶样品进行指纹图谱和多成分含量测定研究,并通过相似度评价、CA、PCA及OPLS-DA等对杉木叶药材的质量进行综合评价。通过检索文献发现,杉木叶的提取物具有抗炎作用[1],双黄酮类成分具有抗肿瘤、抗病毒、抗炎、抗氧化活性等作用[10]。其中,穗花杉双黄酮具有降低血糖、抗炎、抗氧化、抗病毒、抗辐射及抗肿瘤等多种生物学功能[11],扁柏双黄酮具有抗氧化和抗肿瘤活性等作用[12],银杏双黄酮具有抗氧化、抗凝及扩血管、神经保护、抗炎、抗肿瘤及抗感染等作用[13],这与杉木叶的传统功效相符合。本课题组前期研究发现,杉木叶的化学成分以双黄酮类成分为主,且含量较高[14],因此,选择穗花杉双黄酮、7-去甲基银杏双黄酮、扁柏双黄酮、银杏双黄酮、异银杏双黄酮、金松双黄酮6个双黄酮类成分作为杉木叶的未知峰指认的目标峰。采用OPLS-DA快速筛选出不同产地杉木叶的差异标志物,发现穗花杉双黄酮、7-去甲基银杏双黄酮、扁柏双黄酮和金松双黄酮可作为差异标志物,为杉木叶的质量研究提供参考。
实验考察了不同试剂(不同浓度乙醇、甲醇)、提取方式(超声和回流提取)、提取时间对提取结果的影响,最终选择用80%乙醇水加热回流1 h。通过HPLC-PDA在210~400 nm波长范围内进行全波长扫描,穗花杉双黄酮、7-去甲基银杏双黄酮、扁柏双黄酮、银杏双黄酮、异银杏双黄酮、金松双黄酮在269 nm处有共同较大(或最大)吸收波长,但在此波长下个别成分峰形不好,且分离度达不到要求;6个目标成分依次在335.9、332.3、337.1、331.1、328.7、329.9 nm处有较大(或最大)吸收,其中在340 nm处检测时各目标峰的分离度均>1.5、基线平稳,因此,选择340 nm作为检测波长。在流动相的选择上,曾对甲醇-水、乙腈-水、甲醇-0.1%磷酸水溶液、乙腈-0.1%磷酸水溶液等进行考察,发现乙腈-0.1%磷酸水溶液作为流动相所得色谱峰的分离度及峰形较好,因此选择为流动相。在洗脱程序的考察上,指纹图谱与含量测定的侧重点不一样,最后所造成的梯度洗脱程序略有不同。根据指纹图谱相似度评价结果,10批杉木叶药材的指纹图谱有较好的一致性,说明收集到的药材样品质量较稳定。
杉木在国内主要被用作经济木材,杉木叶则被当作废弃物,没有得到充分的开发利用。目前有关杉木叶的研究报道较少,而杉木叶作为一种被丢弃的药用资源,具有量大且容易获得的优势,其中富含的双黄酮成分,也具有很大的药用开发价值[15]。本实验建立指纹图谱与含量测定相结合,应用化学模式识别法对杉木叶药材质量进行全面评价,不仅可以为杉木叶中黄酮类化合物开发提供理论基础,还可为杉木叶的质量评价提供参考依据。
  • 广西科技基地和人才专项(桂科AD22035055)
  • 广西中医药适宜技术开发与推广项目(GZSY21-04)
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2024年第44卷第5期
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doi: 10.16155/j.0254-1793.2024.05.17
  • 接收时间:2023-06-25
  • 首发时间:2026-03-20
  • 出版时间:2024-05-31
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  • 收稿日期:2023-06-25
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广西科技基地和人才专项(桂科AD22035055)
广西中医药适宜技术开发与推广项目(GZSY21-04)
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    1.广西中医药大学研究生院,南宁 530200
    2.广西中医药大学科学实验中心,南宁 530200
    3.广西壮族自治区中医药研究院,南宁 530022
    4.广西中药质量标准重点实验室,南宁 530022

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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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