Article(id=1277255566963639264, tenantId=1146029695717560320, journalId=1235980609244409860, issueId=1277255461552390652, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1000-2561.2026.03.020, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1761753600000, receivedDateStr=2025-10-30, revisedDate=null, revisedDateStr=null, acceptedDate=1765123200000, acceptedDateStr=2025-12-08, onlineDate=1782451057425, onlineDateStr=2026-06-26, pubDate=1774368000000, pubDateStr=2026-03-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1782451057425, onlineIssueDateStr=2026-06-26, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1782451057425, creator=13701087609, updateTime=1782451057425, updator=13701087609, issue=Issue{id=1277255461552390652, tenantId=1146029695717560320, journalId=1235980609244409860, year='2026', volume='47', issue='3', pageStart='553', pageEnd='823', issueExtLink='null', onlineDate='null', pubDate='1774368000000', pubDateStr='2026-03-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1782451032293, creator='13701087609', updateTime=1782451557265, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1277257664249852732, tenantId=1146029695717560320, journalId=1235980609244409860, issueId=1277255461552390652, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1277257664249852733, tenantId=1146029695717560320, journalId=1235980609244409860, issueId=1277255461552390652, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=763, endPage=776, ext={EN=ArticleExt(id=1277255567240463330, articleId=1277255566963639264, tenantId=1146029695717560320, journalId=1235980609244409860, language=EN, title=Quality Markers Prediction of Blumea balsamifera Based on Fngerprint, Chemical Pattern Recognition and Network Pharmacology, columnId=1236286112713470633, journalTitle=Chinese Journal of Tropical Crops, columnName=Post-harvest Treatment & Quality Safety, runingTitle=null, highlight=null, articleAbstract=

In order to clarify the chemical composition characteristics of Blumea balsamifera, screen anti-inflammatory active components, and identify quality markers (Q-markers), and to provide a scientific basis for the quality control of B. balsamifera, a total of 15 B. balsamifera raw herb and 14 powder herb from Zhenfeng, Ceheng and other regions in Guizhou province were utilized for the research. Gas chromatography-mass spectrometry (GC-MS) was employed to establish fingerprint profiles. Hierarchical cluster analysis (HCA), principal component analysis (PCA), and orthogonal partial least squares-discriminant analysis (OPLS-DA) were applied for data processing. To predict the core anti-inflammatory components, a "component-target-pathway" network was constructed using network pharmacology. This prediction was further supplemented by molecular docking verification. A total of 31 compounds were identified. In the GC-MS analysis, 22 and 16 common peaks were calibrated for the B. balsamifera raw herb and powder herb, with sample similarities ranging from 0.971 to 0.997 and 0.991 to 0.999, respectively. The consistency in chemical profiles indicates that the overall quality of the materials is stable. HCA classified B. balsamifera raw herb into 3 clusters and powder herb into 4 clusters. PCA extracted 4 principal components for each sample type, with cumulative contribution rates of 87.137% and 88.495%, respectively, which could effectively characterize sample quality. OPLS-DA identified 5 differential markers (including L-borneol and camphor) from B. balsamifera raw herb and 6 differential markers (including β-caryophyllene and xanthoxylin) from powder herb. Network pharmacology analysis suggested that palmitic acid, 3-octanol, α-eudesmol, γ-eudesmol and perillaldehyde might be the core anti-inflammatory components of B. balsamifera. The components could act on key targets such as EGFR, PTGS2, ESR1, JAK2 and PPARG, and regulate inflammation-related pathways including arachidonic acid metabolism, Th17 cell differentiation, PPAR signaling pathway and JAK-STAT signaling pathway. Molecular docking results showed that the 5 anti-inflammatory components had good binding affinity with target proteins, with binding energies<0 kcal/mol. L-borneol, camphor and γ-eudesmol were identified as the Q-markers of B. balsamifera. The results would provide support for the quality evaluation, anti-inflammatory mechanism research, and efficient resource utilization of B. balsamifera.

, authors=null, authorsList=Zhengwei ZHANG, Bin CHENG, Changmao GUO, Shi YAO, Kailang MU, Shan SHA, Yuxin PANG, authorCompany=null, correspAuthors=Yuxin PANG, 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, fund=null), CN=ArticleExt(id=1277255567475344356, articleId=1277255566963639264, tenantId=1146029695717560320, journalId=1235980609244409860, language=CN, title=基于指纹图谱、化学模式识别及网络药理学的艾纳香质量标志物预测分析, columnId=1236286112877048492, journalTitle=热带作物学报, columnName=采后处理与质量安全, runingTitle=null, highlight=null, articleAbstract=

为了明确艾纳香药材与艾粉的成分特征，筛选抗炎活性成分，并确定质量标志物，为艾纳香质量控制提供科学依据，本研究以贵州贞丰、册亨等地的15批艾纳香药材及14批艾粉为材料，使用GC-MS建立指纹图谱，运用聚类分析（HCA）、主成分分析（PCA）和正交偏最小二乘法-判别分析（OPLS-DA）法分析数据，通过网络药理学，构建“成分-靶点-通路”网络预测核心抗炎成分，辅以分子对接验证。结果表明：共鉴定出31种化合物，艾纳香药材与艾粉分别标定了共有峰22、16个，样本相似度分别介于0.971~0.997、0.991~0.999之间，成分轮廓一致性良好，整体质量稳定；HCA将艾纳香药材聚为3类、艾粉聚为4类，PCA各提取得到4个主成分，累计贡献率分别达87.137%和88.495%，可有效表征样品质量；OPLS-DA从艾纳香药材中筛选出左旋龙脑、樟脑等5个差异标志物，从艾粉中筛选出β-石竹烯、花椒油素等6个差异标志物。网络药理学表明，棕榈酸、3-辛醇、α-桉叶醇、γ-桉叶醇、紫苏醛可能为艾纳香核心抗炎活性成分，可作用于EGFR、PTGS2、ESR1、JAK2、PPARG等核心靶点，调控花生四烯酸代谢、Th17细胞分化、过氧化物酶体增殖物激活受体信号通路和JAK-STAT信号通路等炎症相关通路；分子对接结果显示，5个抗炎成分与靶点蛋白对接情况良好，结合能均小于0 kcal/mol。本研究确定左旋龙脑、樟脑、γ-桉叶醇为艾纳香质量标志物，本研究结果可为艾纳香药材质量评价、抗炎机制研究及资源高效利用提供支撑。

, authors=, authorsList=张正伟, 程彬, 郭长茂, 姚诗, 穆开朗, 沙姗, 庞玉新, authorCompany=null, correspAuthors=庞玉新, authorNote=null, correspAuthorsNote=, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=29hA168zHslyQfZwb8kpOg==, magXml=UlyYvllO3N6ST/UPrDx6gw==, pdfUrl=null, pdf=fRmj+aQ3dxGv1vXuoMiLtg==, pdfFileSize=4227003, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=QiQICBVxr9G1rD6R6Lzckw==, mapNumber=null, fund=null)}, authors=[Author(id=1277255567747974122, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277255566963639264, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1277255567815082988, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277255566963639264, authorId=1277255567747974122, language=EN, stringName=Zhengwei ZHANG, firstName=Zhengwei, middleName=null, lastName=ZHANG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=Guizhou University of Traditional Chinese Medicine, Guiyang, Guizhou 550025, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1277255567877997549, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277255566963639264, authorId=1277255567747974122, language=CN, stringName=张正伟, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=贵州中医药大学，贵州贵阳　550025, bio={"content":"

张正伟（1998—），男，硕士研究生，研究方向：中药及民族药资源分类鉴定与质量控制。

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张正伟（1998—），男，硕士研究生，研究方向：中药及民族药资源分类鉴定与质量控制。

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