| 申军凯,张酉秋,李浩娜,于培明.基于科学计量学与可视化的我国中药及天然药物研究热点分析[J].中国药事,2022,36(1):92-104 |
| 基于科学计量学与可视化的我国中药及天然药物研究热点分析 |
| Research Hotspots of Traditional Chinese Medicine and Natural Medicine in China Based on Scientometrics and Visualization |
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| DOI：10.16153/j.1002-7777.2022.01.012 |
| 中文关键词: 中药 天然药物 科学计量学 CiteSpace可视化 知识图谱 研究热点 |
| 英文关键词: traditional Chinese medicine natural medicine scientometrics CiteSpace visualization knowledge graph research hotspots |
| 基金项目:河南省高等学校重点科研项目(编号 22A330002)；河南省医学教育研究项目(编号 Wjlx2021043)； 开封市科技攻关项目(编号 2103006)；河南大学本科教学改革研究与实践项目重点项目(编号 HDXJJG2020-20) |
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| 中文摘要: |
| 目的：对当前我国中药和天然药物领域研究热点进行探测，为学者了解该领域研究现状提供一个全面直观的视角。方法：检索Web of Science核心集中我国学者发表的中药及天然药物相关学术论文，对文献关键词进行共现分析、聚类分析与突发性探测，对施引文献进行共被引分析和突发性探测，并以网络知识图谱的形式进行可视化。结果：最终筛选得到18689篇文献， “Chemistry”“Pharmacology & Pharmacy”“Integrative & Complementary Medicine”和“Biochemistry & Molecular Biology”在学科共现网络中具有较高频次和中介中心性；“Expression”“Apoptosis” “Activation”“Cell”“Mechanism”“Identification”和“Oxidative Stress”等关键词在共现网络中具有较高共现频次和中介中心性；“Expression”“Oxidative Stress”“Identification”“Mechanism” “Apoptosis”“Traditional Chinese Medicine”“Cell”和“Mass Spectrometry”为主要关键词聚类类团； “Cancer Cell”“Root”“Performance Liquid Chromatography”“In Vivo”“Plasma”及“Inhibitor” 等为突发性关键词；共被引文献主要分布在“Panax Species”“Network Pharmacology”“Chloroplast Genome”“Quality Control”“Apoptosis”“Metabolomics”“Chronic Kidney Disease”“Molecular Docking”“Biosynthesis”“Proteomics”“Chemical Profiling”和“Lung Cancer”研究主题。结论：遗传表达、鉴定、反应机理、氧化应激、细胞凋亡与质谱分析为热点研究对象；中药网络药理学、生物遗传与基因测序、肺癌等癌症诊疗、计算机与大数据在中药药理和分子水平诊断机制领域的应用、关于癌症治疗方面自然产物作用机制、传统中医在心脑血管疾病系统水平的药物靶点的关联特征、药对在中药配伍中的作用等方向或成为前沿性学术问题。 |
| 英文摘要: |
| Objective: To explore the current research hotspots of traditional Chinese medicine and natural medicine in China and provide a comprehensive and intuitive perspective for scholars to understand theresearch status in this field. Methods: To retrieve the academic papers related to traditional Chinese medicine and natural medicine published by Chinese scholars in the core collection of Web of Science. Co-occurrence analysis, cluster analysis and emergent detection were carried out for the keywords in the literature, cocitation analysis and emergent detection were carried out for the cited literature, and visualization was carried out in the form of network knowledge graph. Results: A total of 18689 pieces of literature were eventually screened. “Chemistry”, “Pharmacology & Pharmacy”, “Integrative & Complementary Medicine” and “Biochemistry & Molecular Biology” have high frequency and intermediate centrality in the discipline co-occurrence network; “Expression”, “Apoptosis”, “Activation”, “Cell” “Mechanism”, “Identification” and “Oxidative Stress” show higher co-occurrence frequency and mediating centrality in the keyword co-occurrence network; “Expression”, “Oxidative Stress”, “Identification”, “Mechanism” “Apoptosis”, “Traditional Chinese Medicine”, “Cell” and “Mass Spectrometry” form main keyword clusters; “Cancer Cell”, “Root” “Performance Liquid Chromatography”, “In Vivo”, “Plasma”and“Inhibitor” were the keywords with the strongest citation bursts; Co-cited literature was mainly distributed in such research topics as “Panax Species”, “Network Pharmacology” “Chloroplast Genome", “Quality Control”, “Apoptosis” “Metabolomics”, “Chronic Kidney Disease”, “Molecular Docking” “Biosynthesis”“Proteomics”, “Chemical Profiling” and “Lung Cancer”. Conclusion: Genetic expression, identification, reaction mechanism, oxidative stress, apoptosis and mass spectrometry analysis are the hot research objects. Traditional Chinese medicine network pharmacology, biological genetics and gene sequencing, lung cancer diagnosis and treatment, the application of computer and big data in the field of Traditional Chinese medicine pharmacology and molecular diagnosis mechanism, function mechanism of natural products in cancer treatment, traditional Chinese medicine’s characteristics related to drug targets in the system level of heart cerebrovascular disease, and the role of compatibility of medicine in traditional Chinese medicine might become frontier academic problems. |
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