Article(id=1240709666213261914, tenantId=1146029695717560320, journalId=1205117023404326918, issueId=1240709662501294254, articleNumber=null, orderNo=null, doi=10.16155/j.0254-1793.2024-0450, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1720627200000, receivedDateStr=2024-07-11, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773737835696, onlineDateStr=2026-03-17, pubDate=1743350400000, pubDateStr=2025-03-31, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773737835696, onlineIssueDateStr=2026-03-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773737835696, creator=13701087609, updateTime=1773737835696, updator=13701087609, issue=Issue{id=1240709662501294254, tenantId=1146029695717560320, journalId=1205117023404326918, year='2025', volume='45', issue='3', pageStart='361', pageEnd='542', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1773737834810, creator=13701087609, updateTime=1773737909503, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240709975845163177, tenantId=1146029695717560320, journalId=1205117023404326918, issueId=1240709662501294254, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240709975845163178, tenantId=1146029695717560320, journalId=1205117023404326918, issueId=1240709662501294254, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=504, endPage=513, ext={EN=ArticleExt(id=1240709667303780971, articleId=1240709666213261914, tenantId=1146029695717560320, journalId=1205117023404326918, language=EN, title=Study on quality evaluation of Yankening tablets based on fingerprint combined with multivariate statistical analysis and multi-component quantification, columnId=1239148841803501731, journalTitle=Chinese Journal of Pharmaceutical Analysis, columnName=Quality Control, runingTitle=null, highlight=null, articleAbstract=

Objective: To establish a method for determining the fingerprint of Yankening tablets and evaluate their quality combined with multivariate statistical analysis and multi-component quantification. Methods: The seperation was performed on a 30 ℃ thermostatic InertSustain C18(250 mm×4.6 mm, 5 μm) column,with the mobile phase comprising of methanol-acetonitrile-0.2% phosphoric acid flowing at 1.0 mL · min-1 in a gradient elution manner, and the detection wavelength was set at 254 nm to establish HPLC fingerprint of Yankening tablets,contents of 10 components (berberine hydrochloride, baicalin, wogonoside, baicalein, aloe emodin, wogonin, rhein,emodin, chrysophanol, emodin methyl ether) in 17 batches of Yankening tablets were determined, and similarity evaluation, cluster analysis, entropy weight TOPSIS method, and entropy weight grey correlation analysis were used to comprehensively evaluate the quality of Yankening tablets. Results: There were significant differences in the quality of Yankening tablets of the current market. 33 common peaks were obtained by matching in the fingerprints of 17 batches of samples, and the similarity evaluation and cluster analysis results showed differences among different samples. The comprehensive quality ranking and multi-component content determination revealed that the important factors affecting drug quality were the quality and process control level of the three medicinal herbs,Phellodendri Chinensis Cortex, Coptidis Rhizoma and Scutellariae Radix. Conclusion: The fingerprint established by this method, combined with a multivariate statistical model, can provide reference for the quality evaluation research and products quality improvement of Yankening tablets.

, correspAuthors=Xue-li XU, 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=Hong-ming WANG, Xiao-bing WANG, Xue-li XU, Xiu-kun LIANG), CN=ArticleExt(id=1240709673104503713, articleId=1240709666213261914, tenantId=1146029695717560320, journalId=1205117023404326918, language=CN, title=基于指纹图谱结合多元统计分析及多指标定量的炎可宁片质量评价研究, columnId=1239148842025799861, journalTitle=药物分析杂志, columnName=质量分析, runingTitle=null, highlight=null, articleAbstract=

目的:建立测定炎可宁片指纹图谱的方法,结合多元统计分析及多指标定量评价炎可宁片质量。方法:采用InertSustain C18(250 mm×4.6 mm,5 μm)色谱柱,以甲醇-乙腈-0.2%磷酸溶液为流动相,梯度洗脱,体积流量1.0 mL · min-1,柱温30 ℃,检测波长254 nm,建立炎可宁片的HPLC指纹图谱,对17批炎可宁片中的10个成分(盐酸小檗碱、黄芩苷、汉黄芩苷、黄芩素、芦荟大黄素、汉黄芩素、大黄酸、大黄素、大黄酚、大黄素甲醚)进行含量测定,并结合相似度评价、聚类分析、熵权TOPSIS法、熵权-灰色关联度分析法对炎可宁片质量进行综合评价。结果:目前市场上的炎可宁片质量差异较大,17批样品指纹图谱共匹配得到33个共有峰,相似度评价、聚类分析结果均显示不同样品之间存在差异,综合质量排名及多指标含量测定结果,揭示了影响药品质量重要因素是黄柏、黄连、黄芩3味药材的质量及工艺控制水平。结论:本法建立的炎可宁片的指纹图谱结合多元统计模型,可为炎可宁片的质量评价研究及产品质量提高提供参考。

, correspAuthors=许学丽, authorNote=null, correspAuthorsNote=
*Tel:(0543)8610062;E-mail:
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tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, language=CN, orderNo=5, keyword=灰色关联度分析)], refs=[Reference(id=1240722377479344789, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, doi=null, pmid=null, pmcid=null, year=2009, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[1], rfOrder=0, authorNames=null, journalName=null, refType=null, unstructuredReference=YBZ08602009 炎可宁片.国家食品药品监督管理局药品标准[S].2009, articleTitle=null, refAbstract=null), Reference(id=1240722377605173913, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, doi=null, pmid=null, pmcid=null, year=2009, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[1], rfOrder=1, authorNames=null, journalName=null, refType=null, unstructuredReference=YBZ08602009 Yankening Tablets.National Drug Standard of China Food and Drug 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url=null, language=null, rfNumber=[19], rfOrder=29, authorNames=ZHANG TJ, BAI G, CHEN CQ, journalName=Chin Tradit Herb Drugs, refType=null, unstructuredReference=ZHANG TJBAI GCHEN CQ,et al.Research approaches of quality marker(Q-marker)of Chinese materia medica formula based on “five principles”[J].Chin Tradit Herb Drugs201849(1):1, articleTitle=Research approaches of quality marker(Q-marker)of Chinese materia medica formula based on “five principles”, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1240722372370682236, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, xref=null, ext=[AuthorCompanyExt(id=1240722372391653757, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, companyId=1240722372370682236, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1. Binzhou Inspection and Testing Center, Binzhou 256600, China), AuthorCompanyExt(id=1240722372400042366, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, companyId=1240722372370682236, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.滨州市检验检测中心,滨州 256600)]), AuthorCompany(id=1240722372479734151, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, xref=null, ext=[AuthorCompanyExt(id=1240722372492317064, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, companyId=1240722372479734151, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2. Shandong Institute for Food and Drug Control, Jinan 250000, China), AuthorCompanyExt(id=1240722372500705673, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, companyId=1240722372479734151, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.山东省食品药品检验研究院,济南 250000)])], figs=[ArticleFig(id=1240722375218614821, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, language=EN, label=Fig. 1, caption=Fingerprint and reference fingerprint of 17 batches of Yankening tablets, figureFileSmall=V4g2BvLJG1U9MDfBBi91AA==, figureFileBig=h4HqJw4JAnXX09Wkj9QPGQ==, tableContent=null), ArticleFig(id=1240722375306695211, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, language=CN, label=图1, caption=17批炎可宁片指纹图谱及对照指纹图谱, figureFileSmall=V4g2BvLJG1U9MDfBBi91AA==, figureFileBig=h4HqJw4JAnXX09Wkj9QPGQ==, tableContent=null), ArticleFig(id=1240722375428330034, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, language=EN, label=Fig. 2, caption=Chromatogram of 10 mixed standard solution, figureFileSmall=d93OTcMa5+vmzQhzTPQJvQ==, figureFileBig=UJaZm6TcuK8Ru1kJBm5S0g==, tableContent=null), ArticleFig(id=1240722375566742072, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, language=CN, label=图2, caption=10种混合对照溶液色谱图, figureFileSmall=d93OTcMa5+vmzQhzTPQJvQ==, figureFileBig=UJaZm6TcuK8Ru1kJBm5S0g==, tableContent=null), ArticleFig(id=1240722375663211069, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, language=EN, label=Fig. 3, caption=Cluster analysis heatmap, figureFileSmall=SortbwYTwz3VNseh0N0O0w==, figureFileBig=CvaAN+f1gDgCyDbB2y7P5w==, tableContent=null), ArticleFig(id=1240722375738708545, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, language=CN, label=图3, caption=聚类分析热图, figureFileSmall=SortbwYTwz3VNseh0N0O0w==, figureFileBig=CvaAN+f1gDgCyDbB2y7P5w==, tableContent=null), ArticleFig(id=1240722375805817413, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, language=EN, label=Fig. 4, caption=Bar charts of the content of three types of components in 17 batches of samples, figureFileSmall=oswAeMHBG44b1SkbuOH+XQ==, figureFileBig=c8dKHlL52KSGykHBsO+wlw==, tableContent=null), ArticleFig(id=1240722375889703499, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, language=CN, label=图4, caption=17批样品中3类成分含量柱状图, figureFileSmall=oswAeMHBG44b1SkbuOH+XQ==, figureFileBig=c8dKHlL52KSGykHBsO+wlw==, tableContent=null), ArticleFig(id=1240722375990366799, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, language=EN, label=Tab. 1, caption=

Gradient elution program

, figureFileSmall=null, figureFileBig=null, tableContent=
t/min流动相比例(ratio of mobile phase)/%
ABC
0~6030→50→6070→35
60~80560→7535→20
), ArticleFig(id=1240722376078447187, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, language=CN, label=表1, caption=

梯度洗脱程序

, figureFileSmall=null, figureFileBig=null, tableContent=
t/min流动相比例(ratio of mobile phase)/%
ABC
0~6030→50→6070→35
60~80560→7535→20
), ArticleFig(id=1240722376174916185, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, language=EN, label=Tab. 2, caption=

Similarity results of 17 batches of samples

, figureFileSmall=null, figureFileBig=null, tableContent=
厂家及批号(manufacturer and batch number)相似度(similarity)厂家及批号(manufacturer and batch number)相似度(similarity)
A 200925*0.985C 2107050.754
A 2107160.974C 2211020.946
A 2109230.980C 2212020.980
A 2204110.975D 170608*0.973
B 2111110.953D 180404*0.878
B 2206090.917D 2201070.981
B 2209090.930D 2205120.974
C 190501*0.847D 2207050.971
C 2011010.767
), ArticleFig(id=1240722376258802269, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, language=CN, label=表2, caption=

17批样品相似度结果

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厂家及批号(manufacturer and batch number)相似度(similarity)厂家及批号(manufacturer and batch number)相似度(similarity)
A 200925*0.985C 2107050.754
A 2107160.974C 2211020.946
A 2109230.980C 2212020.980
A 2204110.975D 170608*0.973
B 2111110.953D 180404*0.878
B 2206090.917D 2201070.981
B 2209090.930D 2205120.974
C 190501*0.847D 2207050.971
C 2011010.767
), ArticleFig(id=1240722376346882661, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, language=EN, label=Tab. 3, caption=

Information entropy and entropy weight coefficient calculation results of 33 indicators in Yankening tablets

, figureFileSmall=null, figureFileBig=null, tableContent=
指标(indicator) e k w k(ρ)指标(indicator) e k w k(ρ)指标(indicator) e k w k(ρ)
10.8460.042120.9360.042230.8770.042
20.8640.037130.8980.037240.8440.037
30.9430.015140.9440.015250.8910.015
40.9140.023150.9190.023260.8310.023
50.8850.031160.9220.031270.8880.031
60.8860.031170.8880.031280.8540.031
70.9220.021180.8940.021290.9230.021
80.9000.027190.8630.027300.9050.027
90.8950.029200.8650.029310.9100.029
100.9320.018210.8840.018320.8860.018
110.8720.035220.8020.035330.8380.035
), ArticleFig(id=1240722376430768743, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, language=CN, label=表3, caption=

炎可宁片中33个指标的信息熵、熵权系数计算结果

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指标(indicator) e k w k(ρ)指标(indicator) e k w k(ρ)指标(indicator) e k w k(ρ)
10.8460.042120.9360.042230.8770.042
20.8640.037130.8980.037240.8440.037
30.9430.015140.9440.015250.8910.015
40.9140.023150.9190.023260.8310.023
50.8850.031160.9220.031270.8880.031
60.8860.031170.8880.031280.8540.031
70.9220.021180.8940.021290.9230.021
80.9000.027190.8630.027300.9050.027
90.8950.029200.8650.029310.9100.029
100.9320.018210.8840.018320.8860.018
110.8720.035220.8020.035330.8380.035
), ArticleFig(id=1240722376535626349, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, language=EN, label=Tab. 4, caption=

Evaluation results of entropy weight TOPSIS method for Yankening tablets

, figureFileSmall=null, figureFileBig=null, tableContent=
厂家及批号(manufacturer and batch number) Dj排序(rank)
D 2201070.1020.1150.5301
C 2107050.1160.1230.5162
D 2205120.1140.1150.5023
D 2207050.1080.1000.4804
A 2204110.1170.0860.4235
A 2109230.1220.0890.4226
A 2107160.1270.0840.3987
D 170608*0.1290.0810.3858
A 200925*0.1330.0720.3499
C 2011010.1390.0720.34110
C 2211020.1380.0690.33311
C 2212020.1340.0670.33212
D 180404*0.1390.0560.28513
B 2209090.1480.0560.27414
B 2206090.1490.0520.26015
B 2111110.1560.0450.22316
C 190501*0.1530.0430.22117
), ArticleFig(id=1240722376623706739, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, language=CN, label=表4, caption=

炎可宁片熵权TOPSIS法评价结果

, figureFileSmall=null, figureFileBig=null, tableContent=
厂家及批号(manufacturer and batch number) Dj排序(rank)
D 2201070.1020.1150.5301
C 2107050.1160.1230.5162
D 2205120.1140.1150.5023
D 2207050.1080.1000.4804
A 2204110.1170.0860.4235
A 2109230.1220.0890.4226
A 2107160.1270.0840.3987
D 170608*0.1290.0810.3858
A 200925*0.1330.0720.3499
C 2011010.1390.0720.34110
C 2211020.1380.0690.33311
C 2212020.1340.0670.33212
D 180404*0.1390.0560.28513
B 2209090.1480.0560.27414
B 2206090.1490.0520.26015
B 2111110.1560.0450.22316
C 190501*0.1530.0430.22117
), ArticleFig(id=1240722376715981432, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, language=EN, label=Tab. 5, caption=

Evaluation results of entropy weight grey correlation method for Yankening tablets

, figureFileSmall=null, figureFileBig=null, tableContent=
厂家及批号
(manufacturer and batch number)
R j( s) R j( t) R j排序
(rank)
D 2201070.2680.0710.7901
D 2205120.3050.1620.6532
C 2107050.3300.2120.6093
A 2109230.1310.1070.5514
A 2204110.0950.0820.5375
A 2107160.1260.1160.5226
D 2207050.1100.1070.5077
D 170608*0.1110.1370.4478
C 2212020.0730.1360.3499
A 200925*0.0620.1300.32310
C 2211020.0740.1770.29511
B 2209090.0800.2210.26712
D 180404*0.0410.2090.16513
C 2011010.0560.3380.14314
B 2206090.0420.3060.12215
B 2111110.0450.3390.11716
C 190501*0.0370.4260.08017
), ArticleFig(id=1240722376850199164, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, language=CN, label=表5, caption=

炎可宁片商权灰色关联度法评价结果

, figureFileSmall=null, figureFileBig=null, tableContent=
厂家及批号
(manufacturer and batch number)
R j( s) R j( t) R j排序
(rank)
D 2201070.2680.0710.7901
D 2205120.3050.1620.6532
C 2107050.3300.2120.6093
A 2109230.1310.1070.5514
A 2204110.0950.0820.5375
A 2107160.1260.1160.5226
D 2207050.1100.1070.5077
D 170608*0.1110.1370.4478
C 2212020.0730.1360.3499
A 200925*0.0620.1300.32310
C 2211020.0740.1770.29511
B 2209090.0800.2210.26712
D 180404*0.0410.2090.16513
C 2011010.0560.3380.14314
B 2206090.0420.3060.12215
B 2111110.0450.3390.11716
C 190501*0.0370.4260.08017
), ArticleFig(id=1240722376959251074, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, language=EN, label=Tab. 6, caption=

Comprehensive evaluation results of Yankening tablets

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厂家及批号
(manufacturer and batch number)
综合贴近度
(comprehensive closeness)
综合排名
(comprehensive rank)
D 2201070.6601
D 2205120.5782
C 2107050.5623
D 2207050.4944
A 2109230.4865
A 2204110.4806
A 2107160.4607
D 170608*0.4168
C 2212020.3409
A 200925*0.33610
C 2211020.31411
B 2209090.27012
C 2011010.24213
D 180404*0.22514
B 2206090.19115
B 2111110.17016
C 190501*0.15017
), ArticleFig(id=1240722377122828934, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, language=CN, label=表6, caption=

炎可宁片综合评价结果

, figureFileSmall=null, figureFileBig=null, tableContent=
厂家及批号
(manufacturer and batch number)
综合贴近度
(comprehensive closeness)
综合排名
(comprehensive rank)
D 2201070.6601
D 2205120.5782
C 2107050.5623
D 2207050.4944
A 2109230.4865
A 2204110.4806
A 2107160.4607
D 170608*0.4168
C 2212020.3409
A 200925*0.33610
C 2211020.31411
B 2209090.27012
C 2011010.24213
D 180404*0.22514
B 2206090.19115
B 2111110.17016
C 190501*0.15017
), ArticleFig(id=1240722377210909323, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, language=EN, label=Tab. 7, caption=

Determination results of the content of 10 components in Yankening tablets

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厂家及批号
(manufacturer and batch number)
含量
(content)/(mg·g-1
盐酸小檗碱
(berberine hydrochloride)
黄芩苷
(baicalin)
汉黄芩苷
(wogonoside)
黄芩素
(baicalein)
汉黄芩素
(wogonin)
A 200925*10.4926.044.992.251.11
A 21071613.0426.135.022.591.45
A 21092313.1829.395.652.671.57
A 22041112.0827.885.303.151.50
B 2111112.9814.473.271.640.83
B 2206092.6917.954.812.691.03
B 2209093.6519.865.191.810.94
C 190501*4.924.220.743.561.45
C 2011014.575.280.697.662.93
C 2107057.486.900.8713.314.72
C 2211024.5917.643.772.251.05
C 2212027.2422.244.182.861.22
D 170608*5.5813.092.763.501.50
D 180404*7.417.531.215.742.42
D 22010712.5241.878.143.641.46
D 22051211.2844.189.092.211.11
D 2207059.1239.938.554.531.95
厂家及批号
(manufacturer and batch number)
含量(content)/(mg·g-1
芦荟大黄素
(aloe emodin)
大黄酸
(rhein)
大黄素
(emodin)
大黄酚
(chrysophanol)
大黄素甲醚
(emodin methyl ether)
A 200925*0.180.270.280.660.27
A 2107160.140.280.280.580.25
A 2109230.160.260.250.590.25
A 2204110.220.350.370.770.35
B 2111110.200.330.330.910.33
B 2206090.190.270.321.240.42
B 2209090.180.250.301.110.38
C 190501*0.210.180.241.160.43
C 2011010.120.140.301.300.44
C 2107050.160.190.481.940.70
C 2211020.120.140.210.740.27
C 2212020.110.110.210.720.25
D 170608*0.220.130.181.100.44
D 180404*0.100.180.260.520.24
D 2201070.110.140.210.800.30
D 2205120.130.080.140.960.34
D 2207050.090.080.130.700.24
), ArticleFig(id=1240722377324155535, tenantId=1146029695717560320, journalId=1205117023404326918, articleId=1240709666213261914, language=CN, label=表7, caption=

炎可宁片10个成分含量测定结果

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厂家及批号
(manufacturer and batch number)
含量
(content)/(mg·g-1
盐酸小檗碱
(berberine hydrochloride)
黄芩苷
(baicalin)
汉黄芩苷
(wogonoside)
黄芩素
(baicalein)
汉黄芩素
(wogonin)
A 200925*10.4926.044.992.251.11
A 21071613.0426.135.022.591.45
A 21092313.1829.395.652.671.57
A 22041112.0827.885.303.151.50
B 2111112.9814.473.271.640.83
B 2206092.6917.954.812.691.03
B 2209093.6519.865.191.810.94
C 190501*4.924.220.743.561.45
C 2011014.575.280.697.662.93
C 2107057.486.900.8713.314.72
C 2211024.5917.643.772.251.05
C 2212027.2422.244.182.861.22
D 170608*5.5813.092.763.501.50
D 180404*7.417.531.215.742.42
D 22010712.5241.878.143.641.46
D 22051211.2844.189.092.211.11
D 2207059.1239.938.554.531.95
厂家及批号
(manufacturer and batch number)
含量(content)/(mg·g-1
芦荟大黄素
(aloe emodin)
大黄酸
(rhein)
大黄素
(emodin)
大黄酚
(chrysophanol)
大黄素甲醚
(emodin methyl ether)
A 200925*0.180.270.280.660.27
A 2107160.140.280.280.580.25
A 2109230.160.260.250.590.25
A 2204110.220.350.370.770.35
B 2111110.200.330.330.910.33
B 2206090.190.270.321.240.42
B 2209090.180.250.301.110.38
C 190501*0.210.180.241.160.43
C 2011010.120.140.301.300.44
C 2107050.160.190.481.940.70
C 2211020.120.140.210.740.27
C 2212020.110.110.210.720.25
D 170608*0.220.130.181.100.44
D 180404*0.100.180.260.520.24
D 2201070.110.140.210.800.30
D 2205120.130.080.140.960.34
D 2207050.090.080.130.700.24
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基于指纹图谱结合多元统计分析及多指标定量的炎可宁片质量评价研究
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王洪明 1 , 王小兵 2 , 许学丽 1, * , 梁秀坤 1
药物分析杂志 | 质量分析 2025,45(3): 504-513
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药物分析杂志 | 质量分析 2025, 45(3): 504-513
基于指纹图谱结合多元统计分析及多指标定量的炎可宁片质量评价研究
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王洪明1 , 王小兵2, 许学丽1, * , 梁秀坤1
作者信息
  • 1.滨州市检验检测中心,滨州 256600
  • 2.山东省食品药品检验研究院,济南 250000
  • Tel:(0543)8176977;E-mail:

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*Tel:(0543)8610062;E-mail:
Study on quality evaluation of Yankening tablets based on fingerprint combined with multivariate statistical analysis and multi-component quantification
Hong-ming WANG1 , Xiao-bing WANG2, Xue-li XU1, * , Xiu-kun LIANG1
Affiliations
  • 1. Binzhou Inspection and Testing Center, Binzhou 256600, China
  • 2. Shandong Institute for Food and Drug Control, Jinan 250000, China
出版时间: 2025-03-31 doi: 10.16155/j.0254-1793.2024-0450
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目的:建立测定炎可宁片指纹图谱的方法,结合多元统计分析及多指标定量评价炎可宁片质量。方法:采用InertSustain C18(250 mm×4.6 mm,5 μm)色谱柱,以甲醇-乙腈-0.2%磷酸溶液为流动相,梯度洗脱,体积流量1.0 mL · min-1,柱温30 ℃,检测波长254 nm,建立炎可宁片的HPLC指纹图谱,对17批炎可宁片中的10个成分(盐酸小檗碱、黄芩苷、汉黄芩苷、黄芩素、芦荟大黄素、汉黄芩素、大黄酸、大黄素、大黄酚、大黄素甲醚)进行含量测定,并结合相似度评价、聚类分析、熵权TOPSIS法、熵权-灰色关联度分析法对炎可宁片质量进行综合评价。结果:目前市场上的炎可宁片质量差异较大,17批样品指纹图谱共匹配得到33个共有峰,相似度评价、聚类分析结果均显示不同样品之间存在差异,综合质量排名及多指标含量测定结果,揭示了影响药品质量重要因素是黄柏、黄连、黄芩3味药材的质量及工艺控制水平。结论:本法建立的炎可宁片的指纹图谱结合多元统计模型,可为炎可宁片的质量评价研究及产品质量提高提供参考。

炎可宁片  /  指纹图谱  /  聚类分析  /  熵权TOPSIS法  /  灰色关联度分析

Objective: To establish a method for determining the fingerprint of Yankening tablets and evaluate their quality combined with multivariate statistical analysis and multi-component quantification. Methods: The seperation was performed on a 30 ℃ thermostatic InertSustain C18(250 mm×4.6 mm, 5 μm) column,with the mobile phase comprising of methanol-acetonitrile-0.2% phosphoric acid flowing at 1.0 mL · min-1 in a gradient elution manner, and the detection wavelength was set at 254 nm to establish HPLC fingerprint of Yankening tablets,contents of 10 components (berberine hydrochloride, baicalin, wogonoside, baicalein, aloe emodin, wogonin, rhein,emodin, chrysophanol, emodin methyl ether) in 17 batches of Yankening tablets were determined, and similarity evaluation, cluster analysis, entropy weight TOPSIS method, and entropy weight grey correlation analysis were used to comprehensively evaluate the quality of Yankening tablets. Results: There were significant differences in the quality of Yankening tablets of the current market. 33 common peaks were obtained by matching in the fingerprints of 17 batches of samples, and the similarity evaluation and cluster analysis results showed differences among different samples. The comprehensive quality ranking and multi-component content determination revealed that the important factors affecting drug quality were the quality and process control level of the three medicinal herbs,Phellodendri Chinensis Cortex, Coptidis Rhizoma and Scutellariae Radix. Conclusion: The fingerprint established by this method, combined with a multivariate statistical model, can provide reference for the quality evaluation research and products quality improvement of Yankening tablets.

Yankening tablets  /  fingerprint  /  cluster analysis  /  entropy weight TOPSIS method  /  entropy weight grey correlation analysis
王洪明, 王小兵, 许学丽, 梁秀坤. 基于指纹图谱结合多元统计分析及多指标定量的炎可宁片质量评价研究. 药物分析杂志, 2025 , 45 (3) : 504 -513 . DOI: 10.16155/j.0254-1793.2024-0450
Hong-ming WANG, Xiao-bing WANG, Xue-li XU, Xiu-kun LIANG. Study on quality evaluation of Yankening tablets based on fingerprint combined with multivariate statistical analysis and multi-component quantification[J]. Chinese Journal of Pharmaceutical Analysis, 2025 , 45 (3) : 504 -513 . DOI: 10.16155/j.0254-1793.2024-0450
炎可宁片由黄柏、大黄、黄连、黄芩、板蓝根5味中药组成,具有清热泻火、消炎止痢的功效。目前炎可宁片的质量标准多达30余个[1-3],均非《中华人民共和国药典》标准,标准规定的检测项目不一致,含量测定限度规定差异大,难以从整体上反映有效成分信息,不能全面有效地控制其质量。
指纹图谱作为一种质量控制方法,建立在中药化学成分系统研究的基础上,较为全面地表征中药的质量特征[4]。熵权法与TOPSIS法、灰色关联度法相结合,建立评价模型,应用于药品质量评价,科学客观地反映药品质量[5-6]。本文对炎可宁片的高效液相色谱(HPLC)指纹图谱方法进行研究,对其部分化学成分进行指认。通过不同家产品指纹图谱的相似度分析,结合多元统计分析方法,对不同厂家产品质量进行评价,揭示引起质量差异的指标性成分。
岛津LC-20AT型HPLC仪(Shimadzu公司),KQ-300VDV型超声波清洗器(昆山市超声仪器有限公司),CP225D电子分析天平(Sartorius公司,十万分之一精度),《中药色谱指纹图谱相似度评价系统》(2004年A版),TBtools软件。
对照品盐酸小檗碱(批号110713-201814,含量86.7%)、黄芩苷(批号110715-201821,含量95.4%)、汉黄芩苷(批号112002-201702,含量98.5%)、黄芩素(批号111595-201808,含量97.9%)、芦荟大黄素(批号110795-201710,含量98.3%)、汉黄芩素(批号111514-201716,含量100.0%)、大黄酸(批号110757-200206,含量99.3%)、大黄素(批号110756-201913,96%)、大黄酚(批号110796-201922,含量99.4%)、大黄素甲醚(批号110758-201616,含量99%)购于中国食品药品检定研究院;甲醇、乙腈、磷酸等试剂均为色谱纯,购自天津科密欧化学试剂有限公司;水为超纯水。共收集了4家17批样品,A厂批号分别为200925*、210716、210923、220411;B厂批号分别为211111、220609、220909;C厂批号分别为190507*、201101、210705、221102、221202;D厂批号分别为170608*、180404*、220107、220512、220705,其中标*的4批为过期样品。
采用InertSustain C18(250 mm×4.6 mm,5 μm)色谱柱,流动相为甲醇(A)-乙腈(B)-0.2%磷酸溶液(C),梯度洗脱程序见表1,流速为1.0 mL · min-1,检测波长为254 nm,柱温为30 ℃,进样量为5 μL。
分别取盐酸小檗碱、黄芩苷、汉黄芩苷、黄芩素、芦荟大黄素、汉黄芩素、大黄酸、大黄素、大黄酚、大黄素甲醚的对照品适量,精密称定,制成含盐酸小檗碱56.70 μg · mL-1、黄芩苷161.3 μg · mL-1、汉黄芩苷45.16 μg · mL-1、黄芩素24.20 μg · mL-1、芦荟大黄素0.875 9 μg · mL-1、汉黄芩素9.560 μg · mL-1、大黄酸1.248 μg · mL-1、大黄素1.470 0 μg · mL-1、大黄酚6.626 μg · mL-1、大黄素甲醚3.181 μg · mL-1的混合溶液,即得。
取炎可宁片样品20片,置研钵中研细,取粉末约0.3 g,精密称定,置具塞锥形瓶中,精密加入甲醇50 mL,称定质量,超声(功率300 W,频率45 kHz)处理30 min,取出,放冷至室温后,再次称定质量,用甲醇补足减失的质量,摇匀,经0.22 μm微孔滤膜滤过,取续滤液,即得。
炎可宁片的指纹图谱精密度试验、重复性试验、稳定性试验单峰面积占总峰面积>5%的各色谱峰的相对保留时间和相对峰面积的RSD均小于2%[7],方法学考察结果均满足2020年版《中华人民共和国药典》标准要求。
测定17批炎可宁片样品的指纹图谱,将色谱图导入《中药色谱指纹图谱相似度评价系统》 (2004年A版),匹配色谱图,确定了33个共有峰,并生成对照色谱指纹图谱,见图1
测定混合对照品溶液的色谱图,见图2,与对照指纹图谱进行比对。根据保留时间相近原则[8],9号峰为盐酸小檗碱,13号峰为黄芩苷,18号峰为汉黄芩苷,22号峰为黄芩素,25号峰为芦荟大黄素,26号峰为汉黄芩素,29号峰为大黄酸,31号峰为大黄素,32号峰为大黄酚,33号峰为大黄素甲醚。
将17批炎可宁片样品的指纹图谱与对照指纹图谱进行相似度计算,结果见表2。C厂190501*、201101、210705及D厂180404* 4批样品相似度低于0.900,其余样品结果均高于0.900。其中,C厂190501*、D厂180404*为过期样品,说明部分过期样品与未过期样品之间相似度较低;不同厂家样品的相似度结果也有不同,如B厂样品、C厂部分样品与其他厂家样品相似度差异较大,表明不同厂家样品之间存在差异。
聚类热图可通过横向与纵向聚类来反映样本的批间差异及成分间的相关性,热图中色块的深度可以直观地反映成分的含量[9]
以17批次样品的共有峰峰面积为变量,导入TBtools软件[10],数据经过标准化,行列距离度量为euclidean,选择complete连接法,对4个厂家样品进行系统聚类热图分析,见图3
结果显示17批样品分为4类,峰9(盐酸小檗碱)、峰13(黄芩苷)在4批样品中颜色偏暖,表明这些成分在样品中含量较高,Ⅰ类与其他3类样品相比,峰22(黄芩素)颜色更暖,表明峰22(黄芩素)在Ⅰ类与其他3类样品中含量差异较大。样品的聚类热图直观地反映了不同家之间的样品存在类别差异,D厂过期样品与未过期样品划分为不同类别,说明样品之间存在较大差异,而A厂过期样品与未过期样品聚为一类,说明两者之间差异不大,可能与此批样品过期时间较短有关。
将17批炎可宁片样品中的33个共有峰峰面积按“峰面积/称样量”计算其比值,构建原始数据矩阵A=(Ajk)n×m。其中n为样品批次(n=17),m为评价指标(m=33)。
对原始数据矩阵进行归一化处理,为保证数值有效,在归一化后对每个数值再加上0.000 1的有效值,将原始数据转化成标准化数据矩阵B=(Bjk)n×m。本研究中,炎可宁片的33项指标均为正向性指标,标准化公式如下:
将矩阵B转化为标准化数据概率矩阵P=(Pjk)n×m,进而计算得各项指标的信息熵ek,熵权系数wk,见表3。熵值可以用来判断某个指标的离散程度,其信息熵值越小,指标的离散程度越大,该指标对综合评价的影响(权重)就越大[11]
按公式(5)将标准化数据矩阵B熵权化,即得到加权矩阵C=(Cjk)n×m
计算每个待评价对象到正理想解和负理想解的距离Dj+Dj-及每个待评价对象的相对贴近度D,得到各评价对象的优先序。见表4
将“3.1”项中原始数据,采用各指标“原始数据/指标均值”对数据进行均质化处理,即组成标准化矩阵E=(Ejk)n×m。其中最优参考序列为{Esk}=max{1≤jn}{Ejk},最差参考序列为{Etk}=min{1≤jn}{Ejk[12]
经标准化处理后的评价单元序列相对于最优参考序列的相关系数按公式(9)计算。
式中∆min=min|Ejk-Esk|,∆max=max|Ejk-Esk|(j=1,2……nk=1,2……mρ值见表2)。
经标准化处理后的评价单元序列相对于最差参考序列的相关系数按公式(10)计算。
式中∆min′=min|EjkEtk|,∆max′=max|EjkEtk|(j=1,2……nk=1,2……mρ值见表2)。
按公式(11)计算各评价单元相对于最优参考序列的关联度。
按公式(12)计算各评价单元相对于最差参考序列的关联度
R j( s)值愈大,Rj(t)愈小,评价单元愈佳[13],按公式(13)计算各评价单元相对于最优参考序列和最差参考序列关联度,进行排序,确定不同批次炎可宁片质量排序,结果见表5
2种方法的评价结果较为一致,排名第一的均为D厂220107样品,排名最后3位的均为C厂190501及B厂211111、B厂220609样品,其他批次产品2种方法排序略有不同。参照公式(14)[14]对二者进行加权计算综合贴近度Tj,综合贴近度越大,表明质量越优,得到17批样品的质量排序,见表6。结果显示,质量较优的是D、A厂未过期样品及C厂210705样品,C、D厂的部分过期样品及B厂样品排名较差,各厂的过期样品排名均比未过期样品排名靠后,说明不同厂家的产品质量存在差异,过期样品的质量劣于未过期样品。
变量重要性投影(variable importance in projection,VIP)值是筛选差异性组分的重要指标,VIP值越高,表示对应组分对组间质量差异的影响越大,一般以VIP值>1为标准筛选差异标志成分[15]。由VIP值结果[7],5、22、3、26、9、18、29、12、10、21、15、6、31、2号峰对应成分可以作为炎可宁片不同厂家产品相互区分的差异性指标。其中9号峰为盐酸小檗碱,18号峰为汉黄芩苷,22号峰为黄芩素,26号峰为汉黄芩素,29号峰为大黄酸。
测定盐酸小檗碱、黄芩苷、汉黄芩苷、黄芩素、汉黄芩素、芦荟大黄素、大黄酸、大黄素、大黄酚、大黄素甲醚10个成分的含量[7],结果见表7,并将10个成分分为生物碱类(盐酸小檗碱)、黄酮类(黄芩苷、汉黄芩苷、黄芩素、汉黄芩素)、大黄蒽醌类(芦荟大黄素、大黄酸、大黄素、大黄酚、大黄素甲醚),分别计算总量,3类成分含量柱状图见图4。D、A厂未过期样品黄酮类总量及盐酸小檗碱总量均较高,且批次间差异较小,综合贴近度排名靠前,质量较优;B、C厂产品上述2类成分总量较低,且批次间差异较大,综合排名靠后,质量较差;各厂过期样品上述2类成分均比未过期样品低,排名均低于同厂未过期样品;大黄蒽醌类成分在各批次间差异较小。
灰色关联度法是根据数列之间发展趋势的相似或相异程度,衡量因素间关联程度的1种方法,TOPSIS法是评价对象逼近于理想解的排序方法。运用熵权法赋权,对2个模型数据进行校正,突出重要指标在评价模型中的作用,使评价模型更为真实客观,可信度更高。
盐酸小檗碱、黄芩苷、黄芩素、汉黄芩素等参与多种炎症反应,对胃肠炎、细菌性痢疾、急性扁桃体炎、呼吸道感染等均有一定疗效[16-18]。结合中药Q-marker确定“五原则”[19]基本研究前期OPLS-DA分析[7],筛选盐酸小檗碱、黄芩素、汉黄芩素、黄芩苷、汉黄芩苷为炎可宁片质量标志物。综合质量排序靠前的批次中盐酸小檗碱及黄酮类含量更高,盐酸小檗碱来自黄柏及黄连药材,黄酮类成分可反映黄芩质量,说明黄柏、黄连、黄芩的药材质量及企业的工艺水平是影响药品最终质量的重要因素。
本研究建立了测定炎可宁片指纹图谱的方法,17批炎可宁片样品指纹图谱共匹配得到33个共有峰,指纹图谱相似度评价结果与聚类分析结果均表明不同厂家样品相似度存在差异,过期样品与不过期样品相似度差异较大。结合熵权-灰色关联度法及熵权TOPSIS法得到了样品的综合质量排名,指标成分含量测定结果印证了样品综合排名结果,揭示了影响炎可宁片质量的关键因素是其中黄柏、黄连、黄芩3味药材的质量及工艺控制水平。本研究通过指纹图谱结合多元统计分析及多指标定量分析,较为客观地评价了不同厂家、不同批次的炎可宁片的质量,分析了不同样品之间一致性差异及引起差异的主要原因,为产品标准提高、厂家工艺改进提供数据参考。
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doi: 10.16155/j.0254-1793.2024-0450
  • 接收时间:2024-07-11
  • 首发时间:2026-03-17
  • 出版时间:2025-03-31
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  • 收稿日期:2024-07-11
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    1.滨州市检验检测中心,滨州 256600
    2.山东省食品药品检验研究院,济南 250000

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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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