Article(id=1208489279894962320, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1208489265789518263, articleNumber=null, orderNo=null, doi=10.16438/j.0513-4870.2021-0955, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1624809600000, receivedDateStr=2021-06-28, revisedDate=1627574400000, revisedDateStr=2021-07-30, acceptedDate=null, acceptedDateStr=null, onlineDate=1766055896971, onlineDateStr=2025-12-18, pubDate=1636646400000, pubDateStr=2021-11-12, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1766055896971, onlineIssueDateStr=2025-12-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1766055896971, creator=13701087609, updateTime=1766055896971, updator=13701087609, issue=Issue{id=1208489265789518263, tenantId=1146029695717560320, journalId=1189982191388893191, year='2021', volume='56', issue='11', pageStart='2881', pageEnd='3202', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1766055893609, creator=13701087609, updateTime=1766137012710, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1208829504026448153, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1208489265789518263, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1208829504026448154, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1208489265789518263, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=3141, endPage=3152, ext={EN=ArticleExt(id=1208489280515719399, articleId=1208489279894962320, tenantId=1146029695717560320, journalId=1189982191388893191, language=EN, title=Comprehensive quality evaluation of Scutellaria baicalensis Georgi by determination of multi-component content, columnId=1190335348761793317, journalTitle=Acta Pharmaceutica Sinica, columnName=Original Articles, runingTitle=null, highlight=null, articleAbstract=

A model for quality evaluation was developed by determination of multi-index components in Scutellaria baicalensis Georgi. Eight flavonoids in Scutellaria baicalensis Georgi were quantified by high performance liquid chromatography (HPLC), and a quantitative analysis of multi-components with a single marker (QAMS) method with baicalin as the internal reference substance was established. The 2, 2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS+) method was applied to determine the antioxidant activity of different batches of Scutellaria baicalensis Georgi. Grey relevance analysis was conducted to calculate the grey correlation coefficients of each antioxidant in the herb. The holistic quality of 75 batches of collected samples from different product regions was evaluated to distinguish different commercial types of Scutellaria baicalensis Georgi. The relative correction factor (RCF) of each index component with baicalin as the internal reference indicated good applicability, and there was no significant difference in assay results between the QAMS method and the external standard method (ESM). The results of grey correlation analysis showed that the content of eight index components including baicalin correlated strongly with the antioxidant activity of Scutellaria baicalensis Georgi. The calculated grey relational coefficient ranged from 0.772 4 to 0.808 6. The content of oroxylin A-7-O-β-D-glucuronide, norwogonin-7-O-β-D-glucuronide, baicalein, wogonin and oroxylin A showed positive correlations with the antioxidant potency. In contrast, baicalin, wogonoside and viscidulin Ⅲ content exhibited negative correlations. The ratio of the flavonoid glycosides and flavonoid glycoside aglycones were found to be a critical factor to distinguish the different types of commercial herbs. The crude herbs could be characterized as Scutellaria baicalensis pith-decayed with a G/A ratio less than 10, and the ratio in Scutellaria baicalensis pith-not decayed should be more than 10. The QAMS method established in this study is simple and accurate, and can be used for the determination of eight flavonoids in Scutellaria baicalensis Georgi. Combined with ABTS+ antioxidant activity and grey correlation analysis, a comprehensive model for Scutellaria baicalensis Georgi quality determination based on biological activity was established, which provides new ideas and methods for the establishment of quality standards consistent with the characteristics of traditional Chinese medicine.

, correspAuthors=Yuan-yuan XIE, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright ©2021 Acta Pharmaceutica Sinica. All rights reserved., 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=Jing-rong XU, Qin-chuan YU, Li LAI, Shu-mei WANG, Guo-an LUO, Yuan-yuan XIE), CN=ArticleExt(id=1208489283086827962, articleId=1208489279894962320, tenantId=1146029695717560320, journalId=1189982191388893191, language=CN, title=基于多指标成分含量测定探索黄芩药材质量综合评价模式, columnId=1190335348896011050, journalTitle=药学学报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=

本研究基于多指标成分含量测定探索黄芩药材质量综合评价模式,采用高效液相色谱(HPLC)建立黄芩中8种黄酮类成分同时定量分析的方法,建立以黄芩苷为内参比物质的一测多评法(QAMS);采用2,2'-联氨-双(3-乙基苯并噻唑啉-6-磺酸)二胺盐(ABTS+)法测定不同批次黄芩药材抗氧化活性,并以这8种成分的含量与抗氧化活性效价进行灰色关联度分析,评价不同成分对黄芩药材抗氧化活性的贡献;比较不同产地、不同商品规格、不同采收年限黄芩药材的综合质量。结果表明,以黄芩苷为内参比物质测得的各指标成分相对校正因子系统适应性良好,QAMS法测定结果与外标法无显著差异;黄芩苷等8种指标成分与黄芩药材抗氧化活性关联性较强,灰色关联系数在0.772 4~0.808 6之间,其中黄芩苷、汉黄芩苷和粘毛黄芩素Ⅲ等的含量与药材抗氧化活性负相关,而黄芩素、汉黄芩素、千层纸素A、去甲汉黄芩素苷和千层纸素A-7-O-β-D葡萄糖醛酸苷等的含量则与药材抗氧化活性正相关。黄酮苷与黄酮苷元含量比值(G/A)结合药材性状特征可作为划分不同品类黄芩药材的评价指标。G/A小于10为枯芩,G/A大于10为子芩或含有枯心的子芩。本研究所建立的QAMS简便、准确,可用于黄芩8种黄酮类成分含量测定,结合ABTS+抗氧化活性与灰色关联度分析法建立了基于生物活性的黄芩质量综合评价模式,为建立符合中药自身特色的质量标准提供了新的思路和方法。

, correspAuthors=谢媛媛, authorNote=null, correspAuthorsNote=
*谢媛媛, Tel: 13902294350, E-mail:
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Beijing: Beijing Science and Technology Press, 1986., articleTitle=null, refAbstract=null)], funds=[Fund(id=1208489293669056808, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1208489279894962320, awardId=2017YFC1700800, language=CN, fundingSource=国家重点研发计划“中医药现代化研究”重点专项课题资助(2017YFC1700800), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1208489283439149552, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1208489279894962320, xref=null, ext=[AuthorCompanyExt(id=1208489283447538160, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1208489279894962320, companyId=1208489283439149552, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1. 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Key Laboratory of Digitalized Quality Evaluation Technology of Traditional Chinese Medicine, State Administration of Traditional Chinese Medicine, Guangzhou 510006, China), AuthorCompanyExt(id=1208489283996992041, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1208489279894962320, companyId=1208489283942466078, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.国家中医药管理局中药数字化质量评价技术重点研究室, 广东 广州 510006)]), AuthorCompany(id=1208489284152181308, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1208489279894962320, xref=null, ext=[AuthorCompanyExt(id=1208489284160569917, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1208489279894962320, companyId=1208489284152181308, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=4. Department of Chemistry, Tsinghua University, Beijing 100084, China), AuthorCompanyExt(id=1208489284177347136, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1208489279894962320, companyId=1208489284152181308, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=4.清华大学化学系, 北京 100084)])], figs=[ArticleFig(id=1208489289814491206, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1208489279894962320, language=EN, label=null, caption=null, figureFileSmall=8/Vr6WTafV3pZgkf0LxJxg==, figureFileBig=uQLkV8mC/CxLeK/8bkjwMQ==, tableContent=null), ArticleFig(id=1208489291110531159, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1208489279894962320, language=CN, label=Figure 1, caption= HPLC chromatograms of blank solvent (A) mixed standard solution (B) and sample solution (C). 1: Viscidulin Ⅲ; 2: Baicalin; 3: Norwogonin-7-<i>O</i>-<span class="mag-xml-inline-formula">$ \beta $</span>-<i>D</i>-glucuronide; 4: Oroxylin A-7-<i>O</i>-<span class="mag-xml-inline-formula">$ \beta $</span>-<i>D</i>-glucuronide; 5: Wogonoside; 6: Baicalein; 7: Wogonin; 8: Oroxylin A , figureFileSmall=8/Vr6WTafV3pZgkf0LxJxg==, figureFileBig=uQLkV8mC/CxLeK/8bkjwMQ==, tableContent=null), ArticleFig(id=1208489291399938168, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1208489279894962320, language=EN, label=null, caption=null, figureFileSmall=CV8CrzXQipQ0wSBI0svsWw==, figureFileBig=WijMDR/cgTEWeC3u4cWbcw==, tableContent=null), ArticleFig(id=1208489291546738823, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1208489279894962320, language=CN, label=Figure 2, caption= Pearson correlation analysis of 8 analytes in 75 batches <i>S. baicalensis</i>. The histogram in catercorner exhibited the distribution of each analyte in 75 batches <i>S. baicalensis</i>. B: Baicalin; WA: Wogonoside; OAG: Oroxylin A-7-<i>O</i>-<i>β</i>-<i>D</i>-glucuronide; NWG: Norwogonin-7-<i>O-β-D</i>-glucuronide; BA: Baicalein; W: Wogonin; OA: Oroxylin A; Ⅷ: Viscidulin Ⅲ. The upper triangle (upper right of diagonal) area showed the Pearson correlation coefficient between the eight analytes (<sup>***</sup>Significant correlation, means the correlation coefficient between the two compared components was more than 0.4; <sup>*</sup>Correlation, means the correlation coefficient between the two compared components was more than 0.2); The lower triangle (bottom left of diagonal) area showed scatter plot between the two correlated variables , figureFileSmall=CV8CrzXQipQ0wSBI0svsWw==, figureFileBig=WijMDR/cgTEWeC3u4cWbcw==, tableContent=null), ArticleFig(id=1208489291710316693, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1208489279894962320, language=EN, label=null, caption=null, figureFileSmall=Jqly6BqbNg7tp7F7LoIlRg==, figureFileBig=w9PXx4ueMpykOkYALZjxIw==, tableContent=null), ArticleFig(id=1208489291869700258, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1208489279894962320, language=CN, label=Figure 3, caption= Clustering heat map upon the content of 8 active ingredients in 75 batches <i>S. baicalensis</i> , figureFileSmall=Jqly6BqbNg7tp7F7LoIlRg==, figureFileBig=w9PXx4ueMpykOkYALZjxIw==, tableContent=null), ArticleFig(id=1208489292192661685, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1208489279894962320, language=EN, label=null, caption=null, figureFileSmall=mu2Sj8atY7CQ3Q7rqxV6yw==, figureFileBig=Eo8Vg88l+rsVFE2wcaw+bA==, tableContent=null), ArticleFig(id=1208489292381405380, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1208489279894962320, language=CN, label=Figure 4, caption= Total contents of 8 active ingredients and activity potency in 4 clustering classes of <i>S. baicalensis</i>. A: Total content of different types of components in <i>S. baicalensis</i> from different classes; B: Activity potency of <i>S. baicalensis</i> from different classes. FG: Flavonoid glycoside; FA: Flavonoid aglycones. <span class="mag-xml-inline-formula">$ \overline{x} $</span> ± <i>s</i>, <i>n</i> = 28 (Class 1), 15 (Class 2), 17 (Class 3), 15 (Class 4) , figureFileSmall=mu2Sj8atY7CQ3Q7rqxV6yw==, figureFileBig=Eo8Vg88l+rsVFE2wcaw+bA==, tableContent=null), ArticleFig(id=1208489292528206036, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1208489279894962320, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
Sample No.BatchOriginTypeSample No.BatchOriginType
S1181105ShandongZiqinS39BZ0202ShanxiZiqin
S2181106ShandongZiqinS40BZ0203ShanxiKuqin
S3181109ShandongZiqinS41BZ0204ShanxiKuqin
S4181110ShandongZiqinS42HX0201NeimengguKuqin
S5181111ShandongZiqinS43HX0202NeimengguKuqin
S6181112ShandongZiqinS44HX0203NeimengguKuqin
S7181201ShandongZiqinS45HX0204GansuKuqin
S8181202ShandongZiqinS46HX0205GansuKuqin
S9181203ShandongZiqinS47HX0206GansuKuqin
S10181204ShandongZiqinS48HX0207ShanxiZiqin
S11150601ShandongZiqinS49HX0208ShanxiKuqin
S12150701ShandongZiqinS50HX0210HebeiKuqin
S13150702ShandongZiqinS51HX0211HebeiKuqin
S14160502ShandongZiqinS52HX0212HebeiKuqin
S1520170716-1ShandongZiqinS53HX0213HebeiKuqin
S1620170716-2ShandongZiqinS54GZ0201GansuKuqin
S1720170716-3ShandongZiqinS55HB0201GansuKuqin
S1820170725-1ShandongZiqinS56HB0202ShanxiKuqin
S1920170725-2ShandongZiqinS57HB0203ShanxiKuqin
S2020170725-3ShandongZiqinS58HB0204ShanxiKuqin
S2120170803-1ShandongZiqinS59HB0205NeimengguKuqin
S2220170803-2ShandongZiqinS60HZ0201ShanxiKuqin
S23170501ShandongZiqinS61HZ0202ShanxiKuqin
S24170601ShandongZiqinS62HZ0203ShanxiKuqin
S25170801ShandongZiqinS63HZ0204ShanxiKuqin
S26170901ShandongZiqinS64HZ0205ShanxiKuqin
S27171001ShandongZiqinS65HZ0206HebeiKuqin
S28171101HebeiKuqinS66190701ShandongZiqin
S29171102HebeiKuqinS67190802ShandongZiqin
S30171103HebeiKuqinS68191101ShandongZiqin
S31171207ShandongZiqinS69191102ShandongZiqin
S32171209ShandongZiqinS7020200818NeimengguKuqin
S33171222ShandongZiqinS7120200810ShanxiKuqin
S34171223ShandongZiqinS7220200819NeimengguKuqin
S35171224ShandongZiqinS7320200817NeimengguKuqin
S36S150801ShandongZiqinS7420200102HebeiKuqin
S37S150802ShandongZiqinS7520190705HebeiKuqin
S38BZ0201NeimengguKuqin
), ArticleFig(id=1208489292716949728, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1208489279894962320, language=CN, label=Table 1, caption=

The source of samples

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Sample No.BatchOriginTypeSample No.BatchOriginType
S1181105ShandongZiqinS39BZ0202ShanxiZiqin
S2181106ShandongZiqinS40BZ0203ShanxiKuqin
S3181109ShandongZiqinS41BZ0204ShanxiKuqin
S4181110ShandongZiqinS42HX0201NeimengguKuqin
S5181111ShandongZiqinS43HX0202NeimengguKuqin
S6181112ShandongZiqinS44HX0203NeimengguKuqin
S7181201ShandongZiqinS45HX0204GansuKuqin
S8181202ShandongZiqinS46HX0205GansuKuqin
S9181203ShandongZiqinS47HX0206GansuKuqin
S10181204ShandongZiqinS48HX0207ShanxiZiqin
S11150601ShandongZiqinS49HX0208ShanxiKuqin
S12150701ShandongZiqinS50HX0210HebeiKuqin
S13150702ShandongZiqinS51HX0211HebeiKuqin
S14160502ShandongZiqinS52HX0212HebeiKuqin
S1520170716-1ShandongZiqinS53HX0213HebeiKuqin
S1620170716-2ShandongZiqinS54GZ0201GansuKuqin
S1720170716-3ShandongZiqinS55HB0201GansuKuqin
S1820170725-1ShandongZiqinS56HB0202ShanxiKuqin
S1920170725-2ShandongZiqinS57HB0203ShanxiKuqin
S2020170725-3ShandongZiqinS58HB0204ShanxiKuqin
S2120170803-1ShandongZiqinS59HB0205NeimengguKuqin
S2220170803-2ShandongZiqinS60HZ0201ShanxiKuqin
S23170501ShandongZiqinS61HZ0202ShanxiKuqin
S24170601ShandongZiqinS62HZ0203ShanxiKuqin
S25170801ShandongZiqinS63HZ0204ShanxiKuqin
S26170901ShandongZiqinS64HZ0205ShanxiKuqin
S27171001ShandongZiqinS65HZ0206HebeiKuqin
S28171101HebeiKuqinS66190701ShandongZiqin
S29171102HebeiKuqinS67190802ShandongZiqin
S30171103HebeiKuqinS68191101ShandongZiqin
S31171207ShandongZiqinS69191102ShandongZiqin
S32171209ShandongZiqinS7020200818NeimengguKuqin
S33171222ShandongZiqinS7120200810ShanxiKuqin
S34171223ShandongZiqinS7220200819NeimengguKuqin
S35171224ShandongZiqinS7320200817NeimengguKuqin
S36S150801ShandongZiqinS7420200102HebeiKuqin
S37S150802ShandongZiqinS7520190705HebeiKuqin
S38BZ0201NeimengguKuqin
), ArticleFig(id=1208489293023133939, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1208489279894962320, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
AnalyteCalibration curver2Linear range/mg·mL-1
Viscidulin ⅢY = 212.04 X $ - $ 0.143 10.999 80.001 0 $ - $ 0.100 0
BaicalinY = 366.92 X $ + $ 0.014 70.999 70.003 7 $ - $ 0.370 0
Norwogonin-7-O-β-D-glucuronideY = 507.74 X $ - $ 0.213 60.999 90.008 0 $ - $ 0.079 0
Oroxylin A-7-O-$ \beta $-D-glucuronideY = 353.75 X $ - $ 0.288 90.999 90.001 6 $ - $ 0.158 0
WogonosideY = 505.14 X $ - $ 0.454 10.999 90.003 3 $ - $ 0.330 0
BaicaleinY = 570.70 X $ - $ 0.907 40.999 90.037 0 $ - $ 0.365 0
WogoninY = 748.22 X $ - $ 0.426 60.999 90.011 0 $ - $ 0.113 0
Oroxylin AY = 513.90 X $ - $ 0.160 90.999 90.000 5 $ - $ 0.054 0
), ArticleFig(id=1208489293157351679, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1208489279894962320, language=CN, label=Table 2, caption=

Linear relations of eight analyzed flavonoid compounds in Scutellaria baicalensis

, figureFileSmall=null, figureFileBig=null, tableContent=
AnalyteCalibration curver2Linear range/mg·mL-1
Viscidulin ⅢY = 212.04 X $ - $ 0.143 10.999 80.001 0 $ - $ 0.100 0
BaicalinY = 366.92 X $ + $ 0.014 70.999 70.003 7 $ - $ 0.370 0
Norwogonin-7-O-β-D-glucuronideY = 507.74 X $ - $ 0.213 60.999 90.008 0 $ - $ 0.079 0
Oroxylin A-7-O-$ \beta $-D-glucuronideY = 353.75 X $ - $ 0.288 90.999 90.001 6 $ - $ 0.158 0
WogonosideY = 505.14 X $ - $ 0.454 10.999 90.003 3 $ - $ 0.330 0
BaicaleinY = 570.70 X $ - $ 0.907 40.999 90.037 0 $ - $ 0.365 0
WogoninY = 748.22 X $ - $ 0.426 60.999 90.011 0 $ - $ 0.113 0
Oroxylin AY = 513.90 X $ - $ 0.160 90.999 90.000 5 $ - $ 0.054 0
), ArticleFig(id=1208489293333512462, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1208489279894962320, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
Sample No.ClassAntioxidant activity /mg·U-1Content/mg·g-1
BNWGOAGWBAWAOA
ESMQAMSESMQAMSESMQAMSESMQAMSESMQAMSESMQAMSESMQAMSESM
S1Class 33.20 ± 0.13155.541.371.316.596.379.829.5126.6226.171.771.721.261.220.290.28
S2Class 33.88 ± 0.02154.521.381.337.477.2212.4912.0928.3027.822.342.271.531.480.410.40
S3Class 33.64 ± 0.19169.781.251.207.467.218.708.4230.0229.512.092.021.231.190.210.20
S4Class 33.03 ± 0.15144.552.031.946.326.119.769.4525.6825.243.233.131.721.660.500.48
S5Class 33.37 ± 0.09154.511.321.276.886.6610.279.9427.0426.592.061.991.581.530.330.32
S6Class 33.24 ± 0.16151.831.321.277.517.2610.7510.4127.8727.402.192.121.671.610.320.31
S7Class 33.53 ± 0.12160.581.711.647.777.5115.2614.7729.7329.232.642.551.681.620.550.53
S8Class 33.96 ± 0.02153.731.531.477.857.5910.9410.5928.5928.112.182.111.371.320.330.32
S9Class 32.70 ± 0.16142.822.352.266.236.029.459.1524.2523.853.052.951.681.620.350.34
S10Class 35.76 ± 0.07161.590.860.828.748.4510.9110.5630.4329.921.831.771.401.350.350.34
S11Class 19.98 ± 0.62160.221.571.507.186.949.909.5924.7524.3410.139.814.704.541.461.41
S12Class 111.27 ± 0.35162.761.931.856.796.579.589.2825.2724.8510.5610.224.334.181.201.15
S13Class 19.88 ± 0.34159.541.931.857.126.8911.0210.6725.7025.2711.1710.804.554.401.461.40
S14Class 15.83 ± 0.46156.124.043.886.266.0511.1610.8023.9223.5210.209.873.683.561.361.31
S15Class 36.46 ± 0.19160.351.641.576.386.1711.2310.8727.8427.374.674.512.262.180.650.63
S16Class 37.43 ± 0.28165.843.313.187.216.9610.7310.3927.2326.775.785.592.412.330.690.66
S17Class 14.27 ± 0.18145.395.405.186.276.069.939.6124.8424.428.047.782.622.530.720.70
S18Class 17.11 ± 0.59145.351.771.705.385.2010.049.7125.5425.116.416.203.313.200.820.80
S19Class 18.76 ± 0.93127.852.732.625.185.019.529.2223.2922.9014.5914.124.424.281.151.11
S20Class 18.43 ± 0.63158.781.381.328.077.8015.7215.2229.0028.527.387.144.023.891.761.70
S21Class 19.85 ± 0.73152.941.271.227.196.9510.7110.3623.5823.187.076.843.873.741.461.40
S22Class 19.90 ± 0.22168.361.561.507.987.7111.9411.5628.2627.795.635.453.393.281.000.96
S23Class 19.68 ± 0.53152.781.511.456.586.3612.7712.3623.2622.878.838.544.274.131.711.65
S24Class 34.52 ± 0.07180.211.621.558.197.9211.9611.5832.9632.402.862.771.641.590.390.38
S25Class 14.72 ± 0.33148.531.741.676.105.8910.9810.6323.6623.266.756.543.253.141.121.08
S26Class 16.69 ± 0.51140.793.163.036.326.119.028.7323.1222.7412.7512.344.994.821.561.51
S27Class 17.13 ± 0.74150.332.832.716.626.408.888.6021.1520.7915.4314.945.104.931.931.86
S28Class 211.22 ± 0.57118.481.281.235.945.7413.0612.6419.5419.2114.9414.456.816.593.623.50
S29Class 112.07 ± 0.31106.151.291.245.485.309.769.4515.2314.9710.4410.113.883.761.611.56
S30Class 211.40 ± 0.84103.541.911.834.964.8013.9813.5315.8915.6213.0012.584.123.993.313.19
S31Class 13.20 ± 0.29156.942.061.986.386.169.569.2623.8323.437.767.513.213.111.151.11
S32Class 16.85 ± 0.53162.532.312.216.786.5611.1710.8124.7624.348.358.083.673.551.351.30
S33Class 16.19 ± 0.50159.352.092.006.766.5411.4511.0824.9124.496.786.563.042.941.141.10
S34Class 15.12 ± 0.20165.032.542.436.586.3611.9611.5826.3125.877.577.333.163.061.171.13
S35Class 14.76 ± 0.17156.941.721.656.746.5210.089.7623.7423.346.035.832.902.801.000.96
S36Class 13.11 ± 0.19141.432.512.415.325.148.638.3522.0821.7114.1213.664.964.801.601.54
S37Class 13.66 ± 0.32158.483.993.835.835.638.708.4224.8224.4013.4112.985.585.391.131.09
S38Class 210.18 ± 0.46102.471.591.534.784.627.817.5616.5916.3111.1210.764.274.131.491.44
S39Class 14.93 ± 0.44140.492.712.607.357.1113.7713.3322.2921.928.177.913.373.261.241.20
S40Class 110.67 ± 0.12115.011.651.595.845.648.828.5316.2515.985.525.342.732.641.521.47
S41Class 19.28 ± 0.38120.563.022.907.567.309.098.8015.9815.716.866.641.941.881.171.13
S42Class 211.38 ± 0.08128.043.153.026.376.1619.7919.1519.3719.0512.5712.163.893.764.434.28
S43Class 214.99 ± 0.8099.893.253.125.945.749.999.6714.1213.8911.1710.815.305.124.694.53
S44Class 413.60 ± 0.65161.601.421.377.747.4815.7715.2629.0428.557.587.332.932.831.381.33
S45Class 220.51 ± 0.6496.354.794.595.345.165.945.7511.1911.0010.4710.133.673.551.861.79
S46Class 210.47 ± 0.55118.091.491.436.185.9812.6712.2618.8118.5015.8315.325.865.673.002.89
S47Class 210.46 ± 0.4794.482.302.204.534.386.866.6414.6614.4229.4628.519.879.543.173.06
S48Class 27.46 ± 0.08137.822.182.095.895.6912.2711.8819.6419.3118.5517.956.085.882.382.30
S49Class 27.74 ± 0.87117.368.227.885.315.1411.0310.6817.0916.8030.9429.948.658.364.194.04
S50Class 28.96 ± 0.69102.451.861.785.104.9313.5813.1514.8314.5811.1810.825.645.454.404.25
S51Class 47.26 ± 0.88164.351.411.359.739.4114.7914.3228.0327.566.666.453.563.441.381.34
S52Class 110.48 ± 0.66109.052.762.645.945.7412.3211.9320.8420.495.515.332.972.871.111.07
S53Class 212.76 ± 0.97131.402.842.736.376.1614.6214.1620.6420.2910.5610.224.244.102.312.23
S54Class 44.44 ± 0.07145.091.311.267.467.2214.8514.3825.0224.604.654.501.431.380.780.75
S55Class 26.06 ± 0.26124.131.841.775.885.6810.299.9622.6922.3119.6519.023.783.661.581.52
S56Class 48.68 ± 0.23155.671.551.499.349.0316.1115.5923.8123.416.616.391.831.771.281.24
S57Class 48.63 ± 0.38122.761.981.907.727.4615.6215.1219.8819.556.266.062.592.501.711.65
S58Class 32.98 ± 0.27136.391.131.086.386.1714.6214.1521.9221.552.432.360.570.550.370.35
S59Class 48.13 ± 0.62134.551.621.567.827.5613.3712.9522.3521.976.766.552.772.671.571.51
S60Class 18.35 ± 0.57121.341.881.807.497.2413.0312.6119.5219.1911.6411.273.513.402.262.18
S61Class 48.58 ± 0.77133.891.421.368.338.0515.0314.5521.9321.577.837.582.362.281.681.62
S62Class 23.09 ± 0.3299.093.042.915.365.188.788.5013.9713.7312.9412.524.043.912.082.01
S63Class 48.50 ± 0.08147.571.771.709.168.8615.2214.7322.8322.4410.6210.282.922.831.941.87
S64Class 45.36 ± 0.45133.421.511.459.308.9916.2515.7324.6924.285.255.082.162.091.201.16
S65Class 410.90 ± 0.07156.111.381.339.319.0020.2819.6428.9928.519.138.843.503.381.911.84
S66Class 315.60 ± 0.06144.921.191.147.236.999.689.3726.6626.212.382.301.561.510.320.31
S67Class 36.96 ± 0.12154.430.880.857.467.2110.7710.4328.6028.123.163.061.971.900.600.58
S68Class 13.26 ± 0.06159.411.821.758.047.7710.209.8726.5626.116.986.753.693.570.960.93
S69Class 315.54 ± 0.03147.591.541.476.366.1511.4711.1026.3125.873.533.421.641.580.580.56
S70Class 41.94 ± 0.05102.331.421.365.175.0017.5516.9918.5718.263.863.742.272.201.611.56
S71Class 49.84 ± 0.03137.031.271.228.057.7914.0813.6323.0922.712.922.831.311.270.940.91
S72Class 26.18 ± 0.04100.923.193.065.695.5017.0716.5219.3419.0210.3810.043.843.713.062.95
S73Class 49.98 ± 0.01132.411.131.097.877.6013.3612.9320.3820.045.805.611.981.911.401.35
S74Class 43.25 ± 0.08154.611.431.378.277.9916.8216.2924.4724.064.174.041.991.921.081.04
S75Class 43.94 ± 0.04160.611.271.228.438.1517.6317.0726.2425.803.813.681.561.510.840.81
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), ArticleFig(id=1208489293492896024, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1208489279894962320, language=CN, label=Table 3, caption=

Determination results of 8 analytes determined by ESM and QAMS (mg·g-1) together with the antioxidant potency of each sample. ESM: external standard method; QAMS: Quantitative analysis of multi-components with a single marker

, figureFileSmall=null, figureFileBig=null, tableContent=
Sample No.ClassAntioxidant activity /mg·U-1Content/mg·g-1
BNWGOAGWBAWAOA
ESMQAMSESMQAMSESMQAMSESMQAMSESMQAMSESMQAMSESMQAMSESM
S1Class 33.20 ± 0.13155.541.371.316.596.379.829.5126.6226.171.771.721.261.220.290.28
S2Class 33.88 ± 0.02154.521.381.337.477.2212.4912.0928.3027.822.342.271.531.480.410.40
S3Class 33.64 ± 0.19169.781.251.207.467.218.708.4230.0229.512.092.021.231.190.210.20
S4Class 33.03 ± 0.15144.552.031.946.326.119.769.4525.6825.243.233.131.721.660.500.48
S5Class 33.37 ± 0.09154.511.321.276.886.6610.279.9427.0426.592.061.991.581.530.330.32
S6Class 33.24 ± 0.16151.831.321.277.517.2610.7510.4127.8727.402.192.121.671.610.320.31
S7Class 33.53 ± 0.12160.581.711.647.777.5115.2614.7729.7329.232.642.551.681.620.550.53
S8Class 33.96 ± 0.02153.731.531.477.857.5910.9410.5928.5928.112.182.111.371.320.330.32
S9Class 32.70 ± 0.16142.822.352.266.236.029.459.1524.2523.853.052.951.681.620.350.34
S10Class 35.76 ± 0.07161.590.860.828.748.4510.9110.5630.4329.921.831.771.401.350.350.34
S11Class 19.98 ± 0.62160.221.571.507.186.949.909.5924.7524.3410.139.814.704.541.461.41
S12Class 111.27 ± 0.35162.761.931.856.796.579.589.2825.2724.8510.5610.224.334.181.201.15
S13Class 19.88 ± 0.34159.541.931.857.126.8911.0210.6725.7025.2711.1710.804.554.401.461.40
S14Class 15.83 ± 0.46156.124.043.886.266.0511.1610.8023.9223.5210.209.873.683.561.361.31
S15Class 36.46 ± 0.19160.351.641.576.386.1711.2310.8727.8427.374.674.512.262.180.650.63
S16Class 37.43 ± 0.28165.843.313.187.216.9610.7310.3927.2326.775.785.592.412.330.690.66
S17Class 14.27 ± 0.18145.395.405.186.276.069.939.6124.8424.428.047.782.622.530.720.70
S18Class 17.11 ± 0.59145.351.771.705.385.2010.049.7125.5425.116.416.203.313.200.820.80
S19Class 18.76 ± 0.93127.852.732.625.185.019.529.2223.2922.9014.5914.124.424.281.151.11
S20Class 18.43 ± 0.63158.781.381.328.077.8015.7215.2229.0028.527.387.144.023.891.761.70
S21Class 19.85 ± 0.73152.941.271.227.196.9510.7110.3623.5823.187.076.843.873.741.461.40
S22Class 19.90 ± 0.22168.361.561.507.987.7111.9411.5628.2627.795.635.453.393.281.000.96
S23Class 19.68 ± 0.53152.781.511.456.586.3612.7712.3623.2622.878.838.544.274.131.711.65
S24Class 34.52 ± 0.07180.211.621.558.197.9211.9611.5832.9632.402.862.771.641.590.390.38
S25Class 14.72 ± 0.33148.531.741.676.105.8910.9810.6323.6623.266.756.543.253.141.121.08
S26Class 16.69 ± 0.51140.793.163.036.326.119.028.7323.1222.7412.7512.344.994.821.561.51
S27Class 17.13 ± 0.74150.332.832.716.626.408.888.6021.1520.7915.4314.945.104.931.931.86
S28Class 211.22 ± 0.57118.481.281.235.945.7413.0612.6419.5419.2114.9414.456.816.593.623.50
S29Class 112.07 ± 0.31106.151.291.245.485.309.769.4515.2314.9710.4410.113.883.761.611.56
S30Class 211.40 ± 0.84103.541.911.834.964.8013.9813.5315.8915.6213.0012.584.123.993.313.19
S31Class 13.20 ± 0.29156.942.061.986.386.169.569.2623.8323.437.767.513.213.111.151.11
S32Class 16.85 ± 0.53162.532.312.216.786.5611.1710.8124.7624.348.358.083.673.551.351.30
S33Class 16.19 ± 0.50159.352.092.006.766.5411.4511.0824.9124.496.786.563.042.941.141.10
S34Class 15.12 ± 0.20165.032.542.436.586.3611.9611.5826.3125.877.577.333.163.061.171.13
S35Class 14.76 ± 0.17156.941.721.656.746.5210.089.7623.7423.346.035.832.902.801.000.96
S36Class 13.11 ± 0.19141.432.512.415.325.148.638.3522.0821.7114.1213.664.964.801.601.54
S37Class 13.66 ± 0.32158.483.993.835.835.638.708.4224.8224.4013.4112.985.585.391.131.09
S38Class 210.18 ± 0.46102.471.591.534.784.627.817.5616.5916.3111.1210.764.274.131.491.44
S39Class 14.93 ± 0.44140.492.712.607.357.1113.7713.3322.2921.928.177.913.373.261.241.20
S40Class 110.67 ± 0.12115.011.651.595.845.648.828.5316.2515.985.525.342.732.641.521.47
S41Class 19.28 ± 0.38120.563.022.907.567.309.098.8015.9815.716.866.641.941.881.171.13
S42Class 211.38 ± 0.08128.043.153.026.376.1619.7919.1519.3719.0512.5712.163.893.764.434.28
S43Class 214.99 ± 0.8099.893.253.125.945.749.999.6714.1213.8911.1710.815.305.124.694.53
S44Class 413.60 ± 0.65161.601.421.377.747.4815.7715.2629.0428.557.587.332.932.831.381.33
S45Class 220.51 ± 0.6496.354.794.595.345.165.945.7511.1911.0010.4710.133.673.551.861.79
S46Class 210.47 ± 0.55118.091.491.436.185.9812.6712.2618.8118.5015.8315.325.865.673.002.89
S47Class 210.46 ± 0.4794.482.302.204.534.386.866.6414.6614.4229.4628.519.879.543.173.06
S48Class 27.46 ± 0.08137.822.182.095.895.6912.2711.8819.6419.3118.5517.956.085.882.382.30
S49Class 27.74 ± 0.87117.368.227.885.315.1411.0310.6817.0916.8030.9429.948.658.364.194.04
S50Class 28.96 ± 0.69102.451.861.785.104.9313.5813.1514.8314.5811.1810.825.645.454.404.25
S51Class 47.26 ± 0.88164.351.411.359.739.4114.7914.3228.0327.566.666.453.563.441.381.34
S52Class 110.48 ± 0.66109.052.762.645.945.7412.3211.9320.8420.495.515.332.972.871.111.07
S53Class 212.76 ± 0.97131.402.842.736.376.1614.6214.1620.6420.2910.5610.224.244.102.312.23
S54Class 44.44 ± 0.07145.091.311.267.467.2214.8514.3825.0224.604.654.501.431.380.780.75
S55Class 26.06 ± 0.26124.131.841.775.885.6810.299.9622.6922.3119.6519.023.783.661.581.52
S56Class 48.68 ± 0.23155.671.551.499.349.0316.1115.5923.8123.416.616.391.831.771.281.24
S57Class 48.63 ± 0.38122.761.981.907.727.4615.6215.1219.8819.556.266.062.592.501.711.65
S58Class 32.98 ± 0.27136.391.131.086.386.1714.6214.1521.9221.552.432.360.570.550.370.35
S59Class 48.13 ± 0.62134.551.621.567.827.5613.3712.9522.3521.976.766.552.772.671.571.51
S60Class 18.35 ± 0.57121.341.881.807.497.2413.0312.6119.5219.1911.6411.273.513.402.262.18
S61Class 48.58 ± 0.77133.891.421.368.338.0515.0314.5521.9321.577.837.582.362.281.681.62
S62Class 23.09 ± 0.3299.093.042.915.365.188.788.5013.9713.7312.9412.524.043.912.082.01
S63Class 48.50 ± 0.08147.571.771.709.168.8615.2214.7322.8322.4410.6210.282.922.831.941.87
S64Class 45.36 ± 0.45133.421.511.459.308.9916.2515.7324.6924.285.255.082.162.091.201.16
S65Class 410.90 ± 0.07156.111.381.339.319.0020.2819.6428.9928.519.138.843.503.381.911.84
S66Class 315.60 ± 0.06144.921.191.147.236.999.689.3726.6626.212.382.301.561.510.320.31
S67Class 36.96 ± 0.12154.430.880.857.467.2110.7710.4328.6028.123.163.061.971.900.600.58
S68Class 13.26 ± 0.06159.411.821.758.047.7710.209.8726.5626.116.986.753.693.570.960.93
S69Class 315.54 ± 0.03147.591.541.476.366.1511.4711.1026.3125.873.533.421.641.580.580.56
S70Class 41.94 ± 0.05102.331.421.365.175.0017.5516.9918.5718.263.863.742.272.201.611.56
S71Class 49.84 ± 0.03137.031.271.228.057.7914.0813.6323.0922.712.922.831.311.270.940.91
S72Class 26.18 ± 0.04100.923.193.065.695.5017.0716.5219.3419.0210.3810.043.843.713.062.95
S73Class 49.98 ± 0.01132.411.131.097.877.6013.3612.9320.3820.045.805.611.981.911.401.35
S74Class 43.25 ± 0.08154.611.431.378.277.9916.8216.2924.4724.064.174.041.991.921.081.04
S75Class 43.94 ± 0.04160.611.271.228.438.1517.6317.0726.2425.803.813.681.561.510.840.81
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药学学报 | 研究论文 2021, 56(11): 3141-3152
基于多指标成分含量测定探索黄芩药材质量综合评价模式
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徐境荣1, 2, 3, 于钦川1, 2, 3, 赖莉1, 2, 3, 王淑美1, 2, 3, 罗国安4, 谢媛媛1, 2, 3, *
作者信息
  • 1.广东药科大学中药学院, 广东 广州 510006
  • 2.广东省中药质量工程技术研究中心, 广东 广州 510006
  • 3.国家中医药管理局中药数字化质量评价技术重点研究室, 广东 广州 510006
  • 4.清华大学化学系, 北京 100084

通讯作者:

*谢媛媛, Tel: 13902294350, E-mail:
Comprehensive quality evaluation of Scutellaria baicalensis Georgi by determination of multi-component content
Jing-rong XU1, 2, 3, Qin-chuan YU1, 2, 3, Li LAI1, 2, 3, Shu-mei WANG1, 2, 3, Guo-an LUO4, Yuan-yuan XIE1, 2, 3, *
Affiliations
  • 1. College of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou 510006, China
  • 2. Guangdong Research Center for Quality Engineering Technology of Traditional Chinese Medicine, Guangzhou 510006, China
  • 3. Key Laboratory of Digitalized Quality Evaluation Technology of Traditional Chinese Medicine, State Administration of Traditional Chinese Medicine, Guangzhou 510006, China
  • 4. Department of Chemistry, Tsinghua University, Beijing 100084, China
出版时间: 2021-11-12 doi: 10.16438/j.0513-4870.2021-0955
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本研究基于多指标成分含量测定探索黄芩药材质量综合评价模式,采用高效液相色谱(HPLC)建立黄芩中8种黄酮类成分同时定量分析的方法,建立以黄芩苷为内参比物质的一测多评法(QAMS);采用2,2'-联氨-双(3-乙基苯并噻唑啉-6-磺酸)二胺盐(ABTS+)法测定不同批次黄芩药材抗氧化活性,并以这8种成分的含量与抗氧化活性效价进行灰色关联度分析,评价不同成分对黄芩药材抗氧化活性的贡献;比较不同产地、不同商品规格、不同采收年限黄芩药材的综合质量。结果表明,以黄芩苷为内参比物质测得的各指标成分相对校正因子系统适应性良好,QAMS法测定结果与外标法无显著差异;黄芩苷等8种指标成分与黄芩药材抗氧化活性关联性较强,灰色关联系数在0.772 4~0.808 6之间,其中黄芩苷、汉黄芩苷和粘毛黄芩素Ⅲ等的含量与药材抗氧化活性负相关,而黄芩素、汉黄芩素、千层纸素A、去甲汉黄芩素苷和千层纸素A-7-O-β-D葡萄糖醛酸苷等的含量则与药材抗氧化活性正相关。黄酮苷与黄酮苷元含量比值(G/A)结合药材性状特征可作为划分不同品类黄芩药材的评价指标。G/A小于10为枯芩,G/A大于10为子芩或含有枯心的子芩。本研究所建立的QAMS简便、准确,可用于黄芩8种黄酮类成分含量测定,结合ABTS+抗氧化活性与灰色关联度分析法建立了基于生物活性的黄芩质量综合评价模式,为建立符合中药自身特色的质量标准提供了新的思路和方法。

黄芩  /  黄芩苷  /  一测多评  /  相对校正因子  /  抗氧化  /  灰色关联度分析

A model for quality evaluation was developed by determination of multi-index components in Scutellaria baicalensis Georgi. Eight flavonoids in Scutellaria baicalensis Georgi were quantified by high performance liquid chromatography (HPLC), and a quantitative analysis of multi-components with a single marker (QAMS) method with baicalin as the internal reference substance was established. The 2, 2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS+) method was applied to determine the antioxidant activity of different batches of Scutellaria baicalensis Georgi. Grey relevance analysis was conducted to calculate the grey correlation coefficients of each antioxidant in the herb. The holistic quality of 75 batches of collected samples from different product regions was evaluated to distinguish different commercial types of Scutellaria baicalensis Georgi. The relative correction factor (RCF) of each index component with baicalin as the internal reference indicated good applicability, and there was no significant difference in assay results between the QAMS method and the external standard method (ESM). The results of grey correlation analysis showed that the content of eight index components including baicalin correlated strongly with the antioxidant activity of Scutellaria baicalensis Georgi. The calculated grey relational coefficient ranged from 0.772 4 to 0.808 6. The content of oroxylin A-7-O-β-D-glucuronide, norwogonin-7-O-β-D-glucuronide, baicalein, wogonin and oroxylin A showed positive correlations with the antioxidant potency. In contrast, baicalin, wogonoside and viscidulin Ⅲ content exhibited negative correlations. The ratio of the flavonoid glycosides and flavonoid glycoside aglycones were found to be a critical factor to distinguish the different types of commercial herbs. The crude herbs could be characterized as Scutellaria baicalensis pith-decayed with a G/A ratio less than 10, and the ratio in Scutellaria baicalensis pith-not decayed should be more than 10. The QAMS method established in this study is simple and accurate, and can be used for the determination of eight flavonoids in Scutellaria baicalensis Georgi. Combined with ABTS+ antioxidant activity and grey correlation analysis, a comprehensive model for Scutellaria baicalensis Georgi quality determination based on biological activity was established, which provides new ideas and methods for the establishment of quality standards consistent with the characteristics of traditional Chinese medicine.

Scutellaria baicalensis Georgi  /  baicalin  /  quantitative analysis of multi-components with a single marker  /  relative correlation factor  /  antioxidant  /  grey correlation analysis
徐境荣, 于钦川, 赖莉, 王淑美, 罗国安, 谢媛媛. 基于多指标成分含量测定探索黄芩药材质量综合评价模式. 药学学报, 2021 , 56 (11) : 3141 -3152 . DOI: 10.16438/j.0513-4870.2021-0955
Jing-rong XU, Qin-chuan YU, Li LAI, Shu-mei WANG, Guo-an LUO, Yuan-yuan XIE. Comprehensive quality evaluation of Scutellaria baicalensis Georgi by determination of multi-component content[J]. Acta Pharmaceutica Sinica, 2021 , 56 (11) : 3141 -3152 . DOI: 10.16438/j.0513-4870.2021-0955
黄芩为唇形科植物黄芩Scutellaria baicalensis Georgi的干燥根, 始载于《神农本草经》, 性味苦寒, 归肺、胆、脾、胃、大肠、小肠经, 具有清热燥湿, 泻火解毒, 止血等功效, 现代临床上常用于治疗湿热证、肺热咳嗽、血热出血等病症, 还具有抗炎、抗肿瘤、抗氧化、保肝、神经元保护等药理作用, 是常用大宗中药材之一[1-4]。我国黄芩资源丰富, 主产于河北、河南、山东、山西、内蒙古, 道地产区位于河北省承德市、山东莒县, 产地及采收年限的温度、湿度、光照等环境因素均会影响黄芩的内在质量[5-8]
但长期以来, 一直根据药材外观性状评价黄芩药材与饮片质量等级[9]。随着黄芩需求逐年增加, 很多黄芩等级在市场流通中已很少见或消失。如自南北朝开始至上世纪70年代, 黄芩药材按照性状及功效可分为枯芩与子芩两种规格: 根据黄芩生长规律, 生长至三年以上者, 其根部上段(老根) 木心出现中空、腐朽, 称为枯芩, 善清肺胃上焦之火; 下段仍然致密、坚实, 称为子芩, 善清大肠下焦之火[10, 11]。但现今临床用黄芩已无枯芩与子芩之分, 市场主流商品是坚实黄芩(子芩) 或含有少量枯心的子芩。因此, 基于主观经验“辨状论质”的黄芩药材与饮片规格分级标准已不能适应黄芩饮片流通现状。
以黄芩苷为代表的4′-脱氧黄酮及其苷类是黄芩药材主要代表性成分。2020版《中国药典》一部“黄芩”药材项下将黄芩苷作为评定黄芩药材质量的重要指标成分, 规定黄芩苷含量不得低于9.0%[12]。但黄芩素、汉黄芩素、千层纸素A及白杨素, 以及汉黄芩苷、千层纸素A-7-O-β-D-葡萄糖醛酸苷及白杨素-7-O-β-D-葡萄糖醛酸苷等黄酮苷类化合物均为表征不同生长年限、不同产地、不同商品规格的黄芩药材的特征成分, 也都具有一定的抗菌、抗病毒及解热抗炎的功效[13]。根据黄芩素、汉黄芩素、千层纸素A及其对应的葡萄糖醛酸苷之间含量的比值可区分枯芩和子芩[14], 它们也是子芩和枯芩药效差异的物质基础[10, 15-17]。因此, 有必要建立基于多指标成分定性定量分析来评价不同商品规格黄芩药材质量的分析方法[13]
通过“一测多评” (QMAS) 分析方法实现“对照品替代”, 是解决当前中药化学对照品种类有限, 货源不足, 价格昂贵等制约多指标成分含量测定分析方法推广难题, 实现中药检测方法“绿色化”的有效途径[18-20]。越来越多的学者参照该思路开展了相似的研究, 提出了如替代对照品法、内标多控法、系统内标法、内标校正法等策略, 并考察了检测波长等对定量分析结果准确性的影响[21-26]。2020版《中国药典》在穿心莲、黄连、丹参等多个品种的含量测定项下应用了QAMS的含量测定方法[27]
黄芩中的黄酮类化合物通过阻止机体内过量的自由基攻击蛋白质、脂类、核酸等生物大分子, 避免氧化应激损伤是其发挥抗炎活性、抗肿瘤活性、抗衰老及心脑血管疾病等的生物学基础[28-31]。2, 2'-联氨-双(3-乙基苯并噻唑啉-6-磺酸) 二胺盐[2, 2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt, ABTS+] 法是目前常用的抗氧化能力测定方法, 可避免黄芩药材中过氧化物、内源性酶等造成的干扰, 能准确测定多成分混合物的抗氧化能力[32, 33]
本研究以黄芩苷为内参比物质建立QAMS法测定黄芩药材中的多指标成分含量, 并进行系统耐用性考察; 采用ABTS+法比较不同黄芩药材的抗氧化活性, 根据2020版《中国药典》1431生物检定统计法中的质反应平行线法计算其抗氧化效价[34], 采用灰色关联度分析法快速筛选与黄芩药材抗氧化活性关系密切的指标性成分, 探索基于生物活性的黄芩药材质量综合评价模式。
材料  本研究所用75批黄芩药材均来源于山东、河北、内蒙古、甘肃、山西等不同产区的黄芩药材种植基地, 详细信息见表 1, 由上海市食品药品检验研究院提供, 经上海市食品药品检验研究院季申教授鉴定均为黄芩(Scutellaria baicalensis Georgi) 的干燥根, 凭证标本储存于广东药科大学中药学院。
仪器与试剂  Thermo Ulti Mate 3000超高效液相色谱(配有LPG-3400SD二元液相泵、二极管阵列检测器, WPS-3000TRS自动进样器、在线脱气机、TCC-3200柱温箱, 美国赛默飞公司), 戴安U-3000变色龙工作站6.8 (Chromeleon 6.8, 美国赛默飞公司); SQP型十万分之一电子天平(德国赛多利斯科学仪器有限公司); ME104/02型万分之一电子天平(瑞士梅特勒-托利多仪器有限公司); 数控超声清洗仪(KQ-300DE型, 昆山市超声仪器有限公司); EYELA N-1300旋转蒸发仪(配有EYELA CCA-1112A冷却水循环装置和EYELA DPE-1250型溶剂回收装置); 全波长酶标仪(Multiskan SKY型, 美国赛默飞公司); 乙腈(OCEANPAK, 色谱纯); 甲酸(Aladdin, 色谱纯); 甲醇(广东光华有限公司, 分析纯); ABTS+、过硫酸钾(potassium persulfate, K2SO4) 均购自上海麦克林生化科技有限公司, 水为屈臣氏蒸馏水, 其他试剂均为分析级。
黄芩苷(baicalin, 批号110715-201821)、黄芩素(baicalein, 批号111595-201808)、汉黄芩苷(wogonoside, 批号112002-201702) 和汉黄芩素(wogonin, 批号111514-201706) 购自中国食品药品检定研究院, 粘毛黄芩素Ⅲ (viscidulin Ⅲ, 批号92519-91-0)、去甲汉黄芩素苷(norwogonin-7-O-β-D-glucuronide, 批号119152-50-5)、千层纸素A-7-O-β-D-葡萄糖醛酸苷(oroxylin A-7-O-β-D-glucuronide, 批号36948-76-2) 和千层纸素A (oroxylin A, 批号480-11-5) 均购自诗丹德生物技术有限公司, 本研究所用对照品纯度均大于98%。
色谱条件  色谱柱: YMC-Pack ODS-A (250 mm × 4.6 mm, 5 μm); 流动相: 乙腈(A)-0.1%甲酸水(B), 梯度洗脱, 洗脱条件: 0~20 min, 10%→20% A; 20~28 min, 20%→25% A; 28~32 min, 25% A; 32~35 min, 25%→30% A; 35~40 min, 30%→40% A; 40~50 min, 40%→50% A; 50~60 min, 50% A; 柱温为35 ℃; 检测波长为280 nm, 流速为1 mL·min-1, 进样量为10 μL。
对照品储备溶液的制备  取粘毛黄芩素Ⅲ、黄芩苷、去甲汉黄芩素苷、千层纸素A-7-O-β-D-葡萄糖醛酸苷、汉黄芩苷、黄芩素、汉黄芩素和千层纸素A适量, 精密称定, 以50%甲醇配制成每1 mL中含有各对照品浓度分别为粘毛黄芩素Ⅲ 0.10 mg、黄芩苷0.37 mg、去甲汉黄芩素苷0.08 mg、千层纸素A-7-O-β-D-葡萄糖醛酸苷0.16 mg、汉黄芩苷0.34 mg、黄芩素0.36 mg、汉黄芩素0.11 mg和千层纸素A 0.06 mg的混合对照品储备溶液, 即得。
供试品溶液的制备  称取黄芩粉末(过4号筛) 0.300 g, 精密称定, 置于具塞锥形瓶中, 加入50 mL 75%甲醇, 摇匀, 称重; 超声处理(功率250 W, 频率40 kHz) 30 min, 取出, 放冷, 再称量, 用甲醇补足减失的重量, 摇匀, 0.22 μm微孔滤膜滤过, 取续滤液, 即得。
黄芩冻干粉制备  称取3.0 g不同批次黄芩粉末于锥形瓶中, 按“供试品溶液的制备”项下方法制备黄芩提取液, 将提取液减压浓缩并盛入称量瓶中, 置于-20 ℃冰箱冷冻12 h以上后放入冷冻干燥机中冷冻干燥, 得黄芩冻干粉, 用于抗氧化活性评价。
方法学考察
专属性   取混合对照品溶液、供试品溶液、空白溶液, 分别注入液相色谱仪, 比较色谱图。
线性关系   精密吸取混合对照品储备溶液适量置于容量瓶中, 加入50%甲醇逐级稀释成5个不同浓度的混合对照品溶液, 按照HPLC-DAD色谱条件进样测定, 以对照品浓度(X) 为横坐标, 峰面积(Y) 为纵坐标, 进行线性回归, 计算线性回归方程和相关系数。
精密度   取S5黄芩药材, 按“供试品溶液的制备”项下方法制备供试品溶液, 按照HPLC-DAD色谱条件连续进样6次, 记录8种指标成分的峰面积, 并计算同一供试品溶液连续进样6次的各指标成分峰面积的RSD值。
重复性   精密称取S5黄芩药材6份, 按“供试品溶液的制备”项下方法制备供试品溶液, 按照HPLC-DAD色谱条件测定8种指标成分的含量, 计算RSD。
稳定性   取S5黄芩药材, 按“供试品溶液的制备”项下方法制备供试品溶液, 按照HPLC-DAD色谱条件, 分别于0、1、2、4、6、12、24 h进样分析, 记录8种指标成分的峰面积, 并计算放置24 h内供试品溶液中各指标成分峰面积的RSD值。
加样回收率   取已知含量的黄芩药材0.15 g, 精密称定, 共6份, 分别按样品-对照品(1∶1) 的比例加入一定量的各对照品, 按“供试品溶液的制备”项下方法制备供试品溶液, 按照HPLC-DAD色谱条件进样分析, 计算各指标成分的回收率。
QAMS与外标法测定结果比较  取75批不同产地的黄芩药材, 按照供试品溶液制备方法制备供试品溶液, 并按照HPLC-DAD色谱条件进行测定, 利用平均相对校正因子计算黄芩药材中粘毛黄芩素Ⅲ、黄芩苷、去甲汉黄芩素苷、千层纸素A-7-O-β-D-葡萄糖醛酸苷、汉黄芩苷、黄芩素、汉黄芩素和千层纸素A的含量, 并与外标法计算得到的结果进行比较。
抗氧化活性实验  称取过硫酸钾粉末3.51 mg, 加入蒸馏水5 mL充分溶解, 并称取ABTS粉末21.6 mg, 充分混合后, 置于4 ℃冰箱中避光静置12~16 h, 得ABTS+储备液; 静止后每次取1 mL母液于100 mL量瓶中, 并加入75%甲醇至刻度摇匀即得ABTS+工作液。
另称取各批次黄芩冻干粉20 mg, 分别加入75%甲醇溶液5 mL溶解, 并逐级稀释成不同浓度的黄芩溶液作为供试品溶液, 每次吸取30 μL不同浓度的黄芩溶液至含300 μL ABTS+工作液的96孔板中, 设置3个复孔, 避光孵育7 min, 结束后测量其在734 nm处的吸光度, 记为As; 另测得30 μL 75%甲醇与300 μL ABTS+工作液孵育后的吸光度, 记为Ac; 计算公式见式(1):
$自由基清除率 \left( {\%} \right) = 1-\frac{A\mathrm{s}}{A\mathrm{c}}*100\% $
计算不同浓度的黄芩供试品溶液自由基清除率, 采用2020版《中国药典》附录通则1431项下生物检定统计法[34]中的质反应平行线法计算效价: 将维生素C的标示效价AT定为1 U·mg-1, 采用概率单位(probit) 模型转换平行线法、Bliss迭代法计算模型参数, 得到不同黄芩的抗氧化活性效价PT及其可信限FL。
数据处理  采用ANOVA方法分析检验差异显著性, 数据统计运算采用SPSS 25.0 for Windows统计软件进行处理; 热图分析采用MetaboAnalyst 5.0网站线上绘制, 采用Origin 2017软件、Prism 7.0软件绘制聚类热图中各聚类的箱形图与柱状图。灰色关联度的计算基于75批黄芩药材的8种成分含量, 建立不同批次黄芩质量灰色模式识别数据集, 以抗氧化活性效价评定黄芩质量; 首先, 由于其量纲不统一, 需对原始数据采用归一化法进行标准化处理, 本实验研究采用平均值归一化法, 即用各列化合物含量分别除以相应列平均含量。选择最优参考序列和最差参考序列, 最优参考序列为n个样品对应指标的最大值, 最差参考序列为各样品对应指标的最小值, 分别记为△min与△max, 计算公式如公式(2) 和(3) 所示:
$ y\left({x}_{0}\left(k\right),{x}_{i}\left(k\right)\right)=\frac{△\mathrm{m}\mathrm{i}\mathrm{n}+\rho △\mathrm{m}\mathrm{a}\mathrm{x}}{\left|{x}_{0}\left(k\right)-{x}_{i}\left(k\right)\right|+\rho △\mathrm{m}\mathrm{a}\mathrm{x}} $
$ y({x}_{0},{x}_{i})=\frac{1}{n}{\sum }_{1}^{n}y({x}_{0}\left(k\right),{x}_{i}\left(k\right)) $
式(2) 和(3) 中x0为进行归一化后的抗氧化活性效价, xi为归一化后的8种黄酮类成分含量, ρ为分辨系数, 取值区间为(0, 1), 本实验取ρ = 0.5; y(x0, xi) 即为两者之间的相对关联度。
关联极性($ {\sigma }_{i} $) 分析: 序列$ {x}_{i}\left(k\right) $$ {x}_{0}\left(k\right) $之间的关联极性, 计算公式如公式(4):
$ {\sigma }_{i}={\sum }_{k=1}^{75}k\bullet {x}_{i}\left(k\right)-\frac{{\sum }_{k=1}^{75}{x}_{i}\left(k\right)\bullet {\sum }_{k=1}^{75}k}{n} $
式(4) 中(i = 1、2、3、…、75, k = 1、2、3、…、8, n = 75), 若sgn($ {\sigma }_{i} $) = sgn($ {\sigma }_{0} $), 则$ {y}_{i} $$ {y}_{0} $正关联, 关联极性($ {\sigma }_{i} $) 为“+1”, 说明前者对后者起到增强作用; 若sgn($ {\sigma }_{i} $) = -sgn($ {\sigma }_{0} $), 则$ {y}_{i} $$ {y}_{0} $负关联, 关联极性($ {\sigma }_{i} $) 为“-1”, 前者对后者起到削弱作用。
测得样品色谱图如图 1所示。空白溶液未出现与对照品及黄芩药材中8种待测成分保留时间一致的色谱峰, 表明空白溶液对8种待测成分均无干扰, 方法专属性良好。
8个指标成分的线性回归方程及相关系数见表 2。8个黄酮类成分在实验条件下显示出良好的线性关系。
同一供试品溶液, 连续进样6次, 粘毛黄芩素Ⅲ、黄芩苷、去甲汉黄芩素苷、千层纸素A-7-O-β-D-葡萄糖醛酸苷、汉黄芩苷、黄芩素、汉黄芩素和千层纸素A峰面积的RSD (n = 6) 分别为1.45%、0.05%、0.30%、0.26%、0.14%、0.31%、0.05%和0.29%, 表明仪器具精密性良好。
同一样品, 平行制备6份供试品溶液, 粘毛黄芩素Ⅲ、黄芩苷、去甲汉黄芩素苷、千层纸素A-7-O-β-D-葡萄糖醛酸苷、汉黄芩苷、黄芩素、汉黄芩素和千层纸素A含量的RSD (n=6)分别为1.20%、0.85%、0.87%、0.65%、0.80%、1.90%、1.88%、1.64%, 表明供试品溶液制备方法重复性良好。
供试品溶液室温下放置24 h, 粘毛黄芩素Ⅲ、黄芩苷、去甲汉黄芩素苷、千层纸素A-7-O-β-D-葡萄糖醛酸苷、汉黄芩苷、黄芩素、汉黄芩素和千层纸素A峰面积的RSD分别为1.65%、0.21%、0.20%、0.29%、0.28%、1.27%、0.26%和1.64%, 表明供试品溶液在室温下放置24 h时间内稳定。
8个指标成分的加样回收率在99.81%~103.26%, 各指标成分加样回收率的RSD分别为3.42%、1.57%、1.72%、3.48%、1.99%、1.77%、2.43%和3.82%, 结果表明本研究所建立的分析方法准确性良好。
采用多点校正法, 分别吸取不同浓度的混合对照品溶液(“线性关系考察”项下6个浓度), 依次注入高效液相色谱仪, 记录色谱图。黄芩苷对粘毛黄芩素Ⅲ (fs/A)、去甲汉黄芩素苷(fs/B)、千层纸素7-O-β-D-葡萄糖醛酸苷(fs/C)、汉黄芩苷(fs/D)、黄芩素(fs/E)、汉黄芩素(fs/F) 和千层纸素A (fs/G) 的相对校正因子分别为1.805 9、0.748 0、1.071 8、0.739 4、0.682 1、0.507 4和0.740 0, RSD值均小于3%, 不同浓度对相对校正因子没有显著影响。
采用同一色谱柱: YMC-Pack ODS-A (250 mm × 4.6 mm, 5 μm), 分别使用3种型号的液相色谱仪: 赛默飞世尔Unimate-3000、岛津SPD-M20A、Waters e2695等3种型号高效液相色谱仪, 测定黄芩苷对其余7种黄酮类成分的相对校正因子, 各指标成分在3个不同液相色谱仪上相对校正因子RSD均小于3%, 表明不同高效液相色谱仪对相对校正因子的测定没有影响。
采用同一台HPLC仪(赛默飞世尔Unimate-3000), 分别用相同类型、不同品牌的色谱柱: YMC-Pack ODS-A (250 mm × 4.6 mm, 5 μm; 1)、Agilent 5TC-C18 (2) (250 mm × 4.6 mm, 5 μm; 2) 和Venusil XBP C18 (250 mm × 4.6 mm, 5 μm; 3) 色谱柱, 测定黄芩苷对各指标成分的相对校正因子, 各指标成分在3根不同色谱柱上相对校正因子RSD均小于3%, 表明相同类型、不同品牌色谱柱对相对校正因子的测定结果没有影响。
其他色谱条件不变, 比较不同柱温30、35、40 ℃对各指标成分相对校正因子的影响。不同柱温下, 各指标成分相对校正因子的RSD值均小于3%, 说明不同柱温对黄芩各指标成分相对校正因子无显著影响。
其他色谱条件不变, 比较不同流速(0.8、1.0和1.2 mL·min-1) 对各指标成分相对校正因子的影响, 计算不同流速下各成分相对校正因子的RSD。各成分相对校正因子RSD均小于3%, 说明不同流速对黄芩各指标成分相对校正因子无显著性影响。
表 3所示, 所有黄芩药材中黄芩苷含量均符合2020版《中国药典》黄芩项下相关要求(黄芩含黄芩苷不得少于9.0%)。以黄芩苷为内参比物质建立的QAMS法与外标法相比, 8种黄芩黄酮类成分含量之间的相关性r > 0.99, 两种含量测定方法测定结果间无显著性差异(P > 0.05)。
本研究8个含量测定指标成分主要分为两类, 一类为黄酮苷元类成分, 包括粘毛黄芩素Ⅲ、黄芩素、汉黄芩素和千层纸素A; 另一类为黄酮苷类成分, 包括黄芩苷、去甲汉黄芩素苷、千层纸素A-7-O-β-D-葡萄糖醛酸苷和汉黄芩苷。75批黄芩药材来源于山东、内蒙古、河北、山西和甘肃等主产区规范种植基地, 黄芩苷含量在9.4%~18.0%之间, 均符合药典标准。粘毛黄芩素Ⅲ、黄芩素、汉黄芩素和千层纸素A等4个黄酮苷元类成分含量分别在0.086%~0.820%、0.180%~3.10%、0.057%~0.990%和0.021%~0.470%之间, 在不同批次黄芩药材中黄酮苷元类成分含量差异更为显著一些, 最高含量与最低含量相差9.55~22.33倍。而黄酮苷类成分的含量变化幅度在1.91~3.41倍之间。相关性分析结果(图 2) 表明, 黄芩苷含量与汉黄芩苷和去甲汉黄芩苷呈显著正相关, 而与千层纸素A等黄酮苷元类成分呈现负相关。
所测得的75批次黄芩药材抗氧化效价评价结果见表 3, 黄芩药材的抗氧化效价在1.94~20.51 U·mg-1之间, 平均效价为7.56 ± 3.61 U·mg-1, 不同批次黄芩药材抗氧化活性差异较为显著, 相差10.57倍。
采用灰色关联度分析法, 考察黄芩8种黄酮类成分与抗氧化活性的灰色关联系数分别为0.772 4 (-1)、0.779 7 (-1)、0.794 8 (+1)、0.802 6 (+1)、0.769 7 (-1)、0.802 6 (+1)、0.808 6 (+1) 和0.795 7 (+1)。各指标成分均与抗氧化活性呈现出较高的关联度。除了黄芩苷、汉黄芩苷和粘毛黄芩素Ⅲ对抗氧化起到削弱作用外, 其他成分都起到促进作用。可见, 仅以黄芩苷含量作为评价黄芩药材品质优劣的指标并不合适。
根据75批不同来源黄芩药材/饮片中8种指标成分含量, 采用MetaboAnalyst 5.0进行系统聚类, 75批黄芩药材可分为4类(图 3), 黄酮苷与黄酮苷元含量比值(G/A) 差异是区分这四类黄芩药材的关键指标, 第1类(Class 1, n = 28) 中G/A在7.25~18.70之间, 第2类(Class 2, n = 15) G/A在2.69~8.67之间, 第3类(Class 3, n = 17) G/A在17.31~47.67之间, 第4类(Class 4, n = 15) G/A在11.29~28.46之间(图 4A)。4类黄芩药材抗氧化效价为第2类 > 第4类 > 第1类 > 第3类(图 4B), 黄酮苷元类成分含量第2类 > 第1类≈第4类 > 第3类, 而黄酮苷类成分的含量第3类 > 第4类 > 第1类 > 第2类。各类药材抗氧化活性与总黄酮苷类成分含量呈负相关, 而与总黄酮苷元类成分含量呈正相关, 黄芩药材中G/A值是评价其抗氧化活性的重要指标。
观察药材性状, 第2和4类中共计29批黄芩药材具有枯芩的“木心中空、腐朽”等性状特征, 而其余“质地坚实”的子芩则聚类在第1和3类。研究表明, 枯芩中黄芩素、汉黄芩素和千层纸素A的含量显著高于子芩, 而黄芩苷和汉黄芩苷的含量显著低于子芩[12, 15]。本研究中, 根据8种指标成分的含量将枯芩和子芩均分为两类, 其中第2类枯芩药材中4种黄酮苷元类成分的总含量是第4类中的2.35倍; 而第4类枯芩药材中4种黄酮苷类成分的总含量是第2类中的1.32倍; 两类药材的G/A值相差3倍。成分的差异也体现在其抗氧化活性方面, 第2类枯芩抗氧化活性效价是第4类枯芩药材的1.4倍。两类子芩药材中, 黄芩苷、汉黄芩苷等黄酮苷类成分含量基本相同, 但第1类中黄芩素、千层纸素A和汉黄芩素等黄酮苷元类成分的含量分别是第3类中相应成分的3.25、2.98和2.35倍, 两类药材的G/A值相差2.69倍。第1类子芩抗氧化活性效价是第4类子芩药材的1.15倍。上述结果表明, 不同类别黄芩药材化学成分含量及各类成分含量比例之间存在显著差异, 抗氧化活性也明显不同, 将它们无差别地用于中医临床和中成药的原料, 势必会造成临床疗效的不稳定, 也终将影响最终产品质量的均一性。
黄芩中存在的内源性β-葡萄糖醛酸酶可将根部储存的黄芩苷高效水解为黄芩素, 并迅速诱导细胞凋亡, 产生“枯心”, 被认为是枯芩中黄酮苷元类成分含量高于子芩的主要原因[35]。生长年限不同, 内源性β-葡萄糖醛酸酶表达水平差异, 导致黄芩苷等黄酮苷类成分水解转化为苷元诱导细胞凋亡的水平不同。因此, 本研究中观察到具有“枯心”的第2类和第4类两类枯芩药材中G/A值差异显著, 分别为5.82 ± 1.50和17.89 ± 5.42, 而没有“枯心”的第1类和第3类两类子芩药材的化学轮廓也不相同, G/A值分别为11.88 ± 3.08和33.38 ± 8.28。第3类中S1~S10子芩药材来源于山东临沂的药材基地, 为一年生的鲜品黄芩药材, 其G/A比值在24.59~47.67之间, 与第1类中子芩相比, 黄酮苷元类成分含量较低, 抗氧化活性也比较低。对于具有典型特征的子芩和枯芩而言, 如第3类(生长年限短的子芩, G/A值为17.31~47.67) 与第2类(典型枯芩, G/A值为2.69~8.67), 可用G/A值进行区分, G/A值低于10可认为是枯芩; G/A值大于10以上则为子芩(第1类和第3类) 或含有枯心的子芩(第4类)。第4类(G/A值为11.29~28.46) 与第1类(G/A值为7.25~18.70) 的G/A比值范围有重合, 二者可以通过是否含有枯心这一性状特征来区分。
本研究前期通过单因素实验, 系统考察了不同提取方法(超声提取和加热回流提取) 和不同提取溶剂(水、25%甲醇、50%甲醇、75%甲醇、甲醇5种提取溶剂) 的提取效率, 以各待测成分含量为评价指标, 最终确定黄芩药材的最优提取方法为超声提取, 提取溶剂为75%甲醇。
本研究在对75批黄芩药材多指标成分含量测定基础上, 发现G/A值可能用于区分子芩和枯芩, 并表征黄芩药材生长年限。因此, 可结合药材性状和黄酮苷与黄酮苷元含量比值区分黄芩药材规格: 首先根据是否具有“木心中空、腐朽”等性状特征, 将药材分为具有“枯心”特征(第2类和第4类) 和不具“枯心”特征(第1类和第3类) 的两类, 进一步可根据G/A值和抗氧化活性进行分级划分。但由于收集药材生长年限等信息不足, 产地分散, 所得结论还需要进一步验证; G/A值与枯芩形成过程的关联性也还有待进一步深入研究。此外, 8个指标成分含量与抗氧化活性之间的回归分析和偏最小二乘拟合均不理想, 一方面是由于ABTS+抗氧化活性本身的局限性导致, 其仅停留在分子层次上, 缺乏基于黄芩传统功效的系统评价, G/A值与黄芩药材品质和临床疗效的关系仍有待深入研究; 另一方面药材中还有其他未被检测的抗氧化活性成分, 后续也将采用液质联用等灵敏度更高的检测方法深入探讨。
在传统中医理论和古代经典名方中, 子芩与枯芩多区分使用, 如在定喘汤、防风通圣散和防风消毒散等宣肺疏风、清热化痰的经典方剂中, 均明确使用枯芩; 而在陈皮滑石散、大安胎如胜饮和钩藤皮汤等中均使用子芩治疗下焦病证。可谓是“中枯而大者, 清肺部而止嗽化痰, 并理目赤疔痈, 坚实而细者, 泻大肠而除湿治痢, 兼可安胎利水”“轻漂者上行, 坚重者下降, 不可不别也”[36]。在新型冠状病毒肺炎的防治过程中, 黄芩是清肺排毒汤和金花清感颗粒处方的关键药味, 显然以枯芩为原料效果更优。而首批公布的《古代经典名方目录(第一批)》中共有16个方剂以黄芩药材为原料, 多个方剂均是用其“宣肺热”之功效, 宜用枯芩为佳。可见, 未来市场对子芩和枯芩的精准使用提出了明确的需求, 建议在对不同产地、不同生长年限代表性枯芩和子芩药材化学物质基础和药理作用深入研究基础上, 发现表征功效的质量标志物, 建立科学合理的黄芩药材商品等级质量评价标准, 精准区分可做枯芩使用和可做子芩使用的药材原料。同时, 建议在含有黄芩药材的经典名方制剂研究开发中, 应注重缕清经典名方中子芩和枯芩应用的发展脉络, 尊重历史演变规律, 正本清源。在物质基准研究中, 一方面要注意收集药材的代表性, 另一方面也应同时考察黄芩药材中黄酮苷元类成分和黄酮苷类成分在药材、饮片、物质基准对应实物和经典名方制剂间的物质传递规律, 在“尊古”的基础上, 明确古代经典名方物质基准的化学特征; 既考虑药材资源情况, 又要充分考虑传统用药经验、临床疗效和患者需求, 才能真正的“以精品传承经典、以价值驱动市场”。
本研究建立了以黄芩苷为内参比物质的QAMS法, 并验证了黄芩苷作为内参比物质的合理性, 该方法高效、快捷、准确, 适合应用于黄芩药材多指标成分含量测定。整合多指标成分含量测定与抗氧化活性, 发现黄芩药材中总黄酮苷和总黄酮苷元含量比值可区分不同商品规格、不同生长年限的黄芩药材, 为建立基于生物活性的黄芩质量综合评价模式提供了数据基础, 也为建立符合中药自身特色的质量标准提供了新的思路和方法。
作者贡献: 徐境荣和于钦川负责实验操作、数据处理及文章撰写与修改。赖莉协助完成样品抗氧化活性测定。王淑美和罗国安指导确立实验思路。谢媛媛指导本文的选题设计、实验思路与方法建立、实验数据处理、文章撰写。
利益冲突: 本文不存在任何利益冲突。
  • 国家重点研发计划“中医药现代化研究”重点专项课题资助(2017YFC1700800)
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2021年第56卷第11期
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doi: 10.16438/j.0513-4870.2021-0955
  • 接收时间:2021-06-28
  • 首发时间:2025-12-18
  • 出版时间:2021-11-12
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  • 收稿日期:2021-06-28
  • 修回日期:2021-07-30
基金
国家重点研发计划“中医药现代化研究”重点专项课题资助(2017YFC1700800)
作者信息
    1.广东药科大学中药学院, 广东 广州 510006
    2.广东省中药质量工程技术研究中心, 广东 广州 510006
    3.国家中医药管理局中药数字化质量评价技术重点研究室, 广东 广州 510006
    4.清华大学化学系, 北京 100084

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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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