Article(id=1304414830610375518, tenantId=1146029695717560320, journalId=1302319053441957962, issueId=1304414798482010221, articleNumber=null, orderNo=null, doi=10.7501/j.issn.0253-2670.2026.05.034, pmid=null, cstr=null, oa=null, hot=0, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1759420800000, receivedDateStr=2025-10-03, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1788926330472, onlineDateStr=2026-09-09, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1788926330472, onlineIssueDateStr=2026-09-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1788926330472, creator=13701087609, updateTime=1788926330472, updator=13701087609, issue=Issue{id=1304414798482010221, tenantId=1146029695717560320, journalId=1302319053441957962, year='2026', volume='57', issue='5', pageStart='1597', pageEnd='2008', issueExtLink='null', onlineDate='null', pubDate='1773244800000', pubDateStr='2026-03-12', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1788926322813, creator='13701087609', updateTime=1788926625459, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1304416067925864795, tenantId=1146029695717560320, journalId=1302319053441957962, issueId=1304414798482010221, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1304416067925864796, tenantId=1146029695717560320, journalId=1302319053441957962, issueId=1304414798482010221, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1995, endPage=2008, ext={EN=ArticleExt(id=1304414830920754016, articleId=1304414830610375518, tenantId=1146029695717560320, journalId=1302319053441957962, language=EN, title=Tensor technology promotes the modernization of quality standards of Chinese medicine, columnId=null, journalTitle=Chinese Traditional and Herbal Drugs, columnName=null, runingTitle=null, highlight=null, articleAbstract=The controllability and scientific rigor of traditional Chinese medicine (TCM) quality standards are fundamental to ensuring their clinical efficacy. The core limitation of current TCM quality standards lies in the inherent conflict between holistic and reductionist approaches, which hinders their international recognition under reductionist frameworks and significantly impedes TCM’s globalization. As a mathematical tool for processing complex high-dimensional data, tensor theory demonstrates exceptional computational efficiency when applied in artificial intelligence (AI) and big data technologies, thereby accelerating the development of sophisticated AI models and applications. Furthermore, tensor-based theoretical and algorithmic research in high-dimensional data modeling provides essential mathematical tools for practical problem-solving. By applying the second-order tensor correction method and the third-order tensor correction method, we can accurately analyze the components of TCM, thus establishing the logical relationship between the macro-quality of TCM and the micro-components, and effectively solving the contradiction between the integrity and reducibility of TCM quality. Therefore, tensor technology is expected to provide new theoretical support and technical means for the modernization of quality standards of TCM., authors=GENG Puyu, JIANG Xingming, SHEN Lei, WANG Shuqi, QIU Ningning, LIU Wenlong, ZHANG Xili, authorsList=GENG Puyu, JIANG Xingming, SHEN Lei, WANG Shuqi, QIU Ningning, LIU Wenlong, ZHANG Xili, authorCompany=null, correspAuthors=null, 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=1304414830853645151, articleId=1304414830610375518, tenantId=1146029695717560320, journalId=1302319053441957962, language=CN, title=张量技术推动中药质量标准现代化, columnId=1304140194685415572, journalTitle=中草药, columnName=综述, runingTitle=null, highlight=null, articleAbstract=中药质量标准的可控性与科学性是保障中药临床疗效的核心要素，现阶段传统质量标准的核心局限在于中药整体性与还原性之间的矛盾，这使得中药质量标准难以获得以还原论为主导的国际认可，进而严重阻碍了中药的国际化进程。而张量作为一种可处理复杂高维数据的数理工具，其在人工智能和大数据技术领域的应用，能够显著提升计算效率，推动复杂AI模型与应用的实现。此外，张量在高维数据建模方面的理论和算法研究，为解决实际问题提供了关键的数学工具。通过应用2阶张量校正法和3阶张量校正法，可以对中药成分进行精确的分析，从而建立宏观中药质量与微观成分之间的逻辑关联，有效解决中药质量整体性与还原性之间的矛盾。因此张量技术有望为中药质量标准现代化提供新的理论支持和技术手段。, authors=耿朴玉1,2 , 江星明1 , 申蕾1,2 , 汪舒琦1,2 , 邱宁宁1,2 , 刘文龙1,2,3 , 张喜利1,2 , authorsList=耿朴玉, 江星明, 申蕾, 汪舒琦, 邱宁宁, 刘文龙, 张喜利, authorCompany=1 湖南中医药大学药学院, 湖南 长沙 410208; et al . Chemical profiling and quality evaluation of Liuweizhiji Gegen-Sangshen oral liquid by UPLC-Q-TOF-MS and HPLC-diode array detector fingerprinting[J]. Phytochem Anal , 2024, 35(4): 860-872.et al . Application of a new validated HPLC-DAD method for simultaneous determination of ten active components in xiedusan[J]. Pakistan J Pharm Sci , 2022, 34(6): 2235-2245.et al . Integrated chemometric fingerprints of antioxidant activities and HPLC-DAD-CL for assessing the quality of the processed roots of Polygonum multiflorum Thunb. (Heshouwu)[J]. Chin Med , 2016, 11: 18.Chemom Intell Lab Syst , 2025, 257: 105290.et al . Tensor decomposition for signal processing and machine learning[J]. IEEE Trans Signal Process , 2017, 65(13): 3551-3582.et al . TPpred-ATMV: Therapeutic peptide prediction by adaptive multi-view tensor learning model[J]. Bioinformatics , 2022, 38(10): 2712-2718.et al . Generative tensor network classification model for supervised machine learning[J]. Phys Rev B , 2020, 101(7): 075135.IEEE Trans Signal Inf Process Netw , 2021, 7: 539-550.et al . Tensor methods in data analysis of chromatography/mass spectroscopy-based plant metabolomics[J]. Plant Meth , 2023, 19(1): 130.et al . Triple decomposition and tensor recovery of third order tensors[J]. 2021, 42(1): 299-329.IEEE Access , 2024, 12: 157901-157923.et al . Synergistic hematopoietic effect of Astragaloside IV and Ferulic acid from Danggui Buxue Decoction: Role of Nrf2-mediatedoxidativestressresponse[J]. J Ethnopharmacol , 2018, 226: 101-110.et al . Donkey-hide gelatin (Ejiao) activatesEPO synthesis via amino acid-mediated HlF signaling in chronic anemia model[J]. Phytomedicine , 2024, 128: 155432.et al . Astragaloside IV promotes hematopoiesis by enhancing transferrin receptor expressionand activating stem cell factor/c-Kit signaling[J]. Phytother Res , 2024, 38(5): 1145-1153.et al . Ferulicacid enhances the anti-fbrotic effects of astragaloside IV on pulmonary fibrosis via TGF-β1/Smad3 signaling[J]. J Cell Physiol , 2024, 239(3): e31245.Trac Trends Anal Chem , 2020, 130: 115954.et al . Recent applications of multiway calibration methods in environmental analytical chemistry: A review[J]. Microchem J , 2020, 159: 105575.Comput Optim Appl , 2024, 88(3): 923-962.et al . Tensorfusion of evaporative light scattering detectionand mass spectrometry for comprehensive profiling of UV-silent triterpenoids incomplex herbal extracts[J]. J Chromatogr A, 2024, 1725: e202400163.et al . Multi-modaldata fusion in analytical chemistry: Atensor-based approach for enhanced detectionof low-abundance compounds[J]. Anal Chim Acta , 2024, 1305: e202400345.et al . Tensor-augmented chromatographic analysisof Astragali Radix : Resolving coeluted peaks for comprehensive saponin profiling.[J]. Pharm Biomed Anal , 2024, 245: e202400567.et al . Challenges in quality control of Astragali Radix : Overlapping peaks and structuralanalogs in HPLC profiling[J]. Phytochem Anal , 2024, 35(4): e202400789.et al . Tensor decomposition versus integrative analysis of multi-batch LC-MS data: Overcoming dimensionality constraints in metabolomics[J]. TrAC Trends Anal Chem , 2024, 173: e202400912.Clin Chem , 2003, 49(7): 1041-1044.et al . Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking[J]. Nat Biotechnol , 2016, 34(8): 828-837.et al . Artifacts in herbal metabolomics: The impact of sample purification on LC-MS data integrity[J]. J Chromatography A , 2023, 1692: 463842.Analytical Chemistry , 2025, 96(15): 5897-5905.et al . Structure-revealing data fusion model with applications in metabolomics[J]. IEEE TransPattern Anal Mach Intell , 2015, 37(1): 1-14.Analyt Chemistry , 2023, 95(32): 12021-12030.m /z , retention time, collision energy, and ionization mode[J]. Anal Chem , 2023, 95(18): 7123-7132.et al . Low-rank sensor completion for recovering missing values in mass spectrometry data via convex optimization[J]. IEEE Transactionson Computational Biologyand Bioinformatics , 2022, 19(5): 2890-2901.Nature Methods , 2024, 21(3): 401-410.
中草药
|综述
2026
, 57
(5) :
1995
-2008
张量技术推动中药质量标准现代化
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耿朴玉, 江星明, 申蕾, 汪舒琦, 邱宁宁, 刘文龙, 张喜利
作者信息
通讯作者:
刘文龙
作者简介:
耿朴玉: 耿朴玉,硕士研究生,从事中药质量研究。E-mail:winwin10011123@163.com
江星明: 江星明,硕士,高级实验师,从事中药制剂质量及药物分析研究。E-mail:jxm519@hnucm.edu.cn
Tensor technology promotes the modernization of quality standards of Chinese medicine
GENG Puyu, JIANG Xingming, SHEN Lei, WANG Shuqi, QIU Ningning, LIU Wenlong, ZHANG Xili
Affiliations
doi: 10.7501/j.issn.0253-2670.2026.05.034
文章导航
中药质量标准的可控性与科学性是保障中药临床疗效的核心要素，现阶段传统质量标准的核心局限在于中药整体性与还原性之间的矛盾，这使得中药质量标准难以获得以还原论为主导的国际认可，进而严重阻碍了中药的国际化进程。而张量作为一种可处理复杂高维数据的数理工具，其在人工智能和大数据技术领域的应用，能够显著提升计算效率，推动复杂AI模型与应用的实现。此外，张量在高维数据建模方面的理论和算法研究，为解决实际问题提供了关键的数学工具。通过应用2阶张量校正法和3阶张量校正法，可以对中药成分进行精确的分析，从而建立宏观中药质量与微观成分之间的逻辑关联，有效解决中药质量整体性与还原性之间的矛盾。因此张量技术有望为中药质量标准现代化提供新的理论支持和技术手段。
张量
/
整体性与还原性
/
宏观药效
/
微观成分
/
质量标准
The controllability and scientific rigor of traditional Chinese medicine (TCM) quality standards are fundamental to ensuring their clinical efficacy. The core limitation of current TCM quality standards lies in the inherent conflict between holistic and reductionist approaches, which hinders their international recognition under reductionist frameworks and significantly impedes TCM’s globalization. As a mathematical tool for processing complex high-dimensional data, tensor theory demonstrates exceptional computational efficiency when applied in artificial intelligence (AI) and big data technologies, thereby accelerating the development of sophisticated AI models and applications. Furthermore, tensor-based theoretical and algorithmic research in high-dimensional data modeling provides essential mathematical tools for practical problem-solving. By applying the second-order tensor correction method and the third-order tensor correction method, we can accurately analyze the components of TCM, thus establishing the logical relationship between the macro-quality of TCM and the micro-components, and effectively solving the contradiction between the integrity and reducibility of TCM quality. Therefore, tensor technology is expected to provide new theoretical support and technical means for the modernization of quality standards of TCM.
tensor
/
holism and reductionism
/
macroscopic pharmacological effects
/
microscopic components
/
quality standards
耿朴玉, 江星明, 申蕾, 汪舒琦, 邱宁宁, 刘文龙, 张喜利.
张量技术推动中药质量标准现代化.
中草药,
2026
, 57
(5)
: 1995
-2008
.
DOI: 10.7501/j.issn.0253-2670.2026.05.034
GENG Puyu, JIANG Xingming, SHEN Lei, WANG Shuqi, QIU Ningning, LIU Wenlong, ZHANG Xili.
Tensor technology promotes the modernization of quality standards of Chinese medicine[J].
Chinese Traditional and Herbal Drugs ,
2026
, 57
(5)
: 1995
-2008
.
DOI: 10.7501/j.issn.0253-2670.2026.05.034
国家自然科学基金项目 (81874344); 湖南省卫生健康高层次人才重大科研专项 (R2023139); 湖南省自然科学基金项目 (2023JJ60474); 长沙市自然科学基金项目 (kq2208191); 湖南创新型省份建设专项 (2024RC8110)
参考文献
引证文献
钟南山. 用现代科技实现中医从经验向循证转化[J]. 中医临床研究, 2024, 16(18): 7.et al . Chemical profiling and quality evaluation of Liuweizhiji Gegen-Sangshen oral liquid by UPLC-Q-TOF-MS and HPLC-diode array detector fingerprinting[J]. Phytochem Anal , 2024, 35(4): 860-872.et al . Application of a new validated HPLC-DAD method for simultaneous determination of ten active components in xiedusan[J]. Pakistan J Pharm Sci , 2022, 34(6): 2235-2245.et al . Integrated chemometric fingerprints of antioxidant activities and HPLC-DAD-CL for assessing the quality of the processed roots of Polygonum multiflorum Thunb. (Heshouwu)[J]. Chin Med , 2016, 11: 18.Chemom Intell Lab Syst , 2025, 257: 105290.et al . Tensor decomposition for signal processing and machine learning[J]. IEEE Trans Signal Process , 2017, 65(13): 3551-3582.et al . TPpred-ATMV: Therapeutic peptide prediction by adaptive multi-view tensor learning model[J]. Bioinformatics , 2022, 38(10): 2712-2718.et al . Generative tensor network classification model for supervised machine learning[J]. Phys Rev B , 2020, 101(7): 075135.IEEE Trans Signal Inf Process Netw , 2021, 7: 539-550.et al . Tensor methods in data analysis of chromatography/mass spectroscopy-based plant metabolomics[J]. Plant Meth , 2023, 19(1): 130.et al . Triple decomposition and tensor recovery of third order tensors[J]. 2021, 42(1): 299-329.IEEE Access , 2024, 12: 157901-157923.et al . Synergistic hematopoietic effect of Astragaloside IV and Ferulic acid from Danggui Buxue Decoction: Role of Nrf2-mediatedoxidativestressresponse[J]. J Ethnopharmacol , 2018, 226: 101-110.et al . Donkey-hide gelatin (Ejiao) activatesEPO synthesis via amino acid-mediated HlF signaling in chronic anemia model[J]. Phytomedicine , 2024, 128: 155432.et al . Astragaloside IV promotes hematopoiesis by enhancing transferrin receptor expressionand activating stem cell factor/c-Kit signaling[J]. Phytother Res , 2024, 38(5): 1145-1153.et al . Ferulicacid enhances the anti-fbrotic effects of astragaloside IV on pulmonary fibrosis via TGF-β1/Smad3 signaling[J]. J Cell Physiol , 2024, 239(3): e31245.Trac Trends Anal Chem , 2020, 130: 115954.et al . Recent applications of multiway calibration methods in environmental analytical chemistry: A review[J]. Microchem J , 2020, 159: 105575.Comput Optim Appl , 2024, 88(3): 923-962.et al . Tensorfusion of evaporative light scattering detectionand mass spectrometry for comprehensive profiling of UV-silent triterpenoids incomplex herbal extracts[J]. J Chromatogr A, 2024, 1725: e202400163.et al . Multi-modaldata fusion in analytical chemistry: Atensor-based approach for enhanced detectionof low-abundance compounds[J]. Anal Chim Acta , 2024, 1305: e202400345.et al . Tensor-augmented chromatographic analysisof Astragali Radix : Resolving coeluted peaks for comprehensive saponin profiling.[J]. Pharm Biomed Anal , 2024, 245: e202400567.et al . Challenges in quality control of Astragali Radix : Overlapping peaks and structuralanalogs in HPLC profiling[J]. Phytochem Anal , 2024, 35(4): e202400789.et al . Tensor decomposition versus integrative analysis of multi-batch LC-MS data: Overcoming dimensionality constraints in metabolomics[J]. TrAC Trends Anal Chem , 2024, 173: e202400912.Clin Chem , 2003, 49(7): 1041-1044.et al . Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking[J]. Nat Biotechnol , 2016, 34(8): 828-837.et al . Artifacts in herbal metabolomics: The impact of sample purification on LC-MS data integrity[J]. J Chromatography A , 2023, 1692: 463842.Analytical Chemistry , 2025, 96(15): 5897-5905.et al . Structure-revealing data fusion model with applications in metabolomics[J]. IEEE TransPattern Anal Mach Intell , 2015, 37(1): 1-14.Analyt Chemistry , 2023, 95(32): 12021-12030.m /z , retention time, collision energy, and ionization mode[J]. Anal Chem , 2023, 95(18): 7123-7132.et al . Low-rank sensor completion for recovering missing values in mass spectrometry data via convex optimization[J]. IEEE Transactionson Computational Biologyand Bioinformatics , 2022, 19(5): 2890-2901.Nature Methods , 2024, 21(3): 401-410.
2026年第57卷第5期
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doi: 10.7501/j.issn.0253-2670.2026.05.034
接收时间：2025-10-03
首发时间：2026-09-09
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2种不同金属材料的力学参数
科 属数 种数 占总种数比例 属 种数 占总种数比例 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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