Project description:Purpose Resistance training (RT) can intervene in aging, which can effectively improve trainees’ life. However, unhealthy living habits such as irregular life, obesity and hyperlipidemia, and chronic diseases lead to a significant decline in the energy level of the population, seriously affecting the health of the population. Our research identifies the research hotspots of RT to intervene in aging from the perspective of bibliometrics, predicts research frontiers and development trends, and provides more perspectives for research on aging populations. Methods In this study, we used CiteSpace and VOSviewer visualization software to draw the scientific knowledge map of countries/regions, institutions, authors, co-occurrence keywords, and co-cited references of published articles, and explore the Web of Science core collection database all about the RT intervention aging research status, hotspots, frontiers, and development trends of articles on aging. Results Among the 760 articles that meet the inclusion criteria, the number of articles published and the frequency of citations have increased steadily in the past 5 years. Judging from the countries/regions, institutions, scholars, and journals that published articles, the ones with the largest numbers are the USA, Univ Estadual Londrina, Cyrino ES, and Exp Gerontol. The ones with the highest influence are England, Univ Arkansas Med Sci, Frontera WR, and Biochem Biophys Rep Co. The top five co-occurrence keywords of include exercise, strength, resistance training, skeletal muscle, and muscle strength. The research frontier is physical function. Conclusion In the field of RT intervention aging research, relevant scholars deserve further in-depth research and exploration. The United States, Brazil, Canada, and other economically developed countries/regions, institutions, and authors have greater influence and productivity. These quantitative research results can provide references for relevant scholars’ follow-up research and government departments to formulate and modify health policies or measures.

Project description:ObjectiveUsing visual bibliometric analysis, the application and development of artificial intelligence in clinical esophageal cancer are summarized, and the research progress, hotspots, and emerging trends of artificial intelligence are elucidated.MethodsOn April 7th, 2022, articles and reviews regarding the application of AI in esophageal cancer, published between 2000 and 2022 were chosen from the Web of Science Core Collection. To conduct co-authorship, co-citation, and co-occurrence analysis of countries, institutions, authors, references, and keywords in this field, VOSviewer (version 1.6.18), CiteSpace (version 5.8.R3), Microsoft Excel 2019, R 4.2, an online bibliometric platform (http://bibliometric.com/) and an online browser plugin (https://www.altmetric.com/) were used.ResultsA total of 918 papers were included, with 23,490 citations. 5,979 authors, 39,962 co-cited authors, and 42,992 co-cited papers were identified in the study. Most publications were from China (317). In terms of the H-index (45) and citations (9925), the United States topped the list. The journal "New England Journal of Medicine" of Medicine, General & Internal (IF = 91.25) published the most studies on this topic. The University of Amsterdam had the largest number of publications among all institutions. The past 22 years of research can be broadly divided into two periods. The 2000 to 2016 research period focused on the classification, identification and comparison of esophageal cancer. Recently (2017-2022), the application of artificial intelligence lies in endoscopy, diagnosis, and precision therapy, which have become the frontiers of this field. It is expected that closely esophageal cancer clinical measures based on big data analysis and related to precision will become the research hotspot in the future.ConclusionsAn increasing number of scholars are devoted to artificial intelligence-related esophageal cancer research. The research field of artificial intelligence in esophageal cancer has entered a new stage. In the future, there is a need to continue to strengthen cooperation between countries and institutions. Improving the diagnostic accuracy of esophageal imaging, big data-based treatment and prognosis prediction through deep learning technology will be the continuing focus of research. The application of AI in esophageal cancer still has many challenges to overcome before it can be utilized.

Project description:BackgroundGlioblastoma (GBM) is one of the common malignant tumors of the central nervous system (CNS), characterized by rapid proliferation, heterogeneity, aggressiveness, proneness to recurrence after surgery, and poor prognosis. There is increasing evidence that tumorigenesis is inextricably linked to immune escape, and immunotherapy is undoubtedly an important complement to clinical treatment options for GBM, and will be a focus and hot topic in GBM treatment research. The purpose of this study was to visualize and analyze the scientific results and research trends of immunotherapy for GBM.MethodsPublications concerning immunotherapy for GBM were retrieved from the Web of Science Core Collection (WOScc) database. Bibliometric and visual analysis was performed mainly using CiteSpace and R software, and the Online Analysis Platform of Literature Metrology (https://bibliometric.com/app) for countries/regions, authors, journals, references and keywords related to publications in the field.ResultsAmong totally 3491 publications retrieved in this field, 1613 publications were finally obtained according to the screening criteria, including 1007 articles (62.43%) and 606 reviews (37.57%). The number of publications increased year by year, with an average growth rate (AGR) of 17.41%. Such a number was the largest in the USA (717, 44.45%), followed by China (283, 17.55%), and the USA showed the strongest international collaboration. Among the research institutions, Duke Univ (94, 5.83%) was the largest publisher in the field, followed by Harvard Med Sch (70, 4.34%). In addition, the most prolific authors in this field were OHN H SAMPSON (51) and MICHAEL LIM (43), and the degree of collaboration (DC) between authors was 98.26%. Among the co-cited authors, STUPP R (805) was the most cited author, followed by REARDON DA (448). The journal with the most published publications was FRONTIERS IN IMMUNOLOGY (75), and the most cited journal in terms of co-citation was CLIN CANCER RES (1322), followed by CANCER RES (1230). The high-frequency keyword included glioblastoma (672) and immunotherapy (377). Cluster analysis was performed on the basis of keyword co-occurrence analysis, yielding 17 clusters, based on which the current research status and future trends in the field of immunotherapy for GBM were identified.ConclusionImmunotherapy is currently a novel treatment strategy for GBM that has attracted much attention. In the future, it is necessary to strengthen cooperation and exchanges between countries and institutions towards relevant research to promote the development of this field. Immunotherapy is expected to be an important part of the future treatment strategy for GBM, and it has already become a hot spot of current research and will be the key focus of future research.

Project description:BackgroundPrimary thyroid lymphoma (PTL) is a rare malignancy of the thyroid gland that poses significant clinical challenges due to its rarity and the varied therapeutic approaches it demands. Although recent years have seen an increasing focus on PTL, there is a notable lack of bibliometric analyses that consolidate the evolving research within this field. This study aims to analyze and highlight the research hotspots and trend changes in PTL, elucidating their clinical implications and guiding future research.MethodsWe conducted a systematic bibliometric analysis of literature on PTL published from 2000 to 2023. This involved a structured search in the Web of Science Core Collection, using medical subject headings (MeSH) from the MeSH database to refine and eliminate duplicates, forming a precise search formula. Relevant publications were limited to English-language articles and reviews, which were then processed and analyzed using CiteSpace (6.2.R4) for visualization. The analysis, performed with CiteSpace software, facilitated the visualization of trends and hotspots in PTL research by mapping citation networks and identifying key themes and influential works.ResultsOur search yielded 281 literature records on PTL, demonstrating a curvilinear upward trend in publications over the years. The majority of publications originated from China, with the most influential contributions coming from the United States. Hirokawa Mitsuyoshi and Derringer Ga were identified as the most prolific and most co-cited authors, respectively. Keyword and co-citation analyses indicated a growing interest in clinicopathological features, treatment modalities, survival outcomes of different PTL subtypes, risk factors, complementary diagnostic techniques, and immunotherapeutic approaches.ConclusionsThis bibliometric analysis underscores the significant clinical relevance of understanding the pathologies, diagnostic challenges, and treatment strategies for PTL. The identified research hotspots, particularly in pathological typing, diagnosis and treatment modalities, gene expression profiles, targeted therapies, clinical trials, and survival rates, highlight critical areas requiring continued research focus. These insights have pivotal implications for improving patient outcomes and advancing the clinical management of PTL.

Project description:ObjectiveThis study aimed to analyze and visualize the current research focus, research frontiers, evolutionary processes, and trends of artificial intelligence (AI) in the field of gastric cancer using a bibliometric analysis.MethodsThe Web of Science Core Collection database was selected as the data source for this study to retrieve and obtain articles and reviews related to AI in gastric cancer. All the information extracted from the articles was imported to CiteSpace to conduct the bibliometric and knowledge map analysis, allowing us to clearly visualize the research hotspots and trends in this field.ResultsA total of 183 articles published between 2017 and 2022 were included, contributed by 201 authors from 33 countries/regions. Among them, China (47.54%), Japan (21.86%), and the USA (13.11%) have made outstanding contributions in this field, accounting fsor 82.51% of the total publications. The primary research institutions were Wuhan University, Tokyo University, and Tada Tomohiro Inst Gastroenterol and Proctol. Tada (n = 12) and Hirasawa (n = 90) were ranked first in the top 10 authors and co-cited authors, respectively. Gastrointestinal Endoscopy (21 publications; IF 2022, 9.189; Q1) was the most published journal, while Gastric Cancer (133 citations; IF 2022, 8.171; Q1) was the most co-cited journal. Nevertheless, the cooperation between different countries and institutions should be further strengthened. The most common keywords were AI, gastric cancer, and convolutional neural network. The "deep-learning algorithm" started to burst in 2020 and continues till now, which indicated that this research topic has attracted continuous attention in recent years and would be the trend of research on AI application in GC.ConclusionsResearch related to AI in gastric cancer is increasing exponentially. Current research hotspots focus on the application of AI in gastric cancer, represented by convolutional neural networks and deep learning, in diagnosis and differential diagnosis and staging. Considering the great potential and clinical application prospects, the related area of AI applications in gastric cancer will remain a research hotspot in the future.

Project description:BackgroundThe etiology of idiopathic scoliosis (IS) remains unclear. Gene-based studies on genetic etiology and molecular mechanisms have improved our understanding of IS and guided treatment and diagnosis. Therefore, it is imperative to explicate and demarcate the preponderant areas of inquiry, key scholars, and their aggregate scholarly output, in addition to the collaborative associations amongst publications or researchers.MethodsDocuments were retrieved from the Web of Science Core Collection (WoSCC) with the following criteria: TS = ("idiopathic scoliosis" AND gene) refined by search operators (genomic OR "hereditary substance" OR "germ plasm" OR Cistrons OR genetics OR genetic OR genes OR Polygenic OR genotype OR genome OR allele OR polygenes OR Polygene) AND DOCUMENT TYPES (ARTICLE OR REVIEW), and the timespan of 2002-01-01 to 2022-11-26. The online bibliometric analysis platform (bibliometric), bibliographic item co-occurrence matrix builder (BICOMB), CiteSpace 6.1. R6 and VOS viewer were used to evaluate articles for publications, nations, institutions, journals, references, knowledge bases, keywords, and research hotspots.ResultsA total of 479 documents were retrieved from WoSCC. Fourty-four countries published relevant articles. The country with the most significant number of articles was China, and the institution with the most significant number of articles was Nanjing University. Citation analysis formed eight meaningful clusters and 16 high-frequency keywords. (2) The citation knowledge map included single nucleotide polymorphisms, whole exome sequencing, axonal dynamin, drug development, mesenchymal stem cells, dietary intake, curve progression, zebrafish development model, extracellular matrix, and rare variants were the current research hotspots and frontiers.ConclusionsRecent research has focused on IS-related genes, whereas the extracellular matrix and unusual variants are research frontiers and hotspots. Functional analysis of susceptibility genes will prove to be valuable for identifying this disease.

Project description:BackgroundBuyang huanwu decoction (BYHWD) has shown significant clinical efficacy in the treatment of several diseases, particularly stroke. However, bibliometric research has not been comprehensive.MethodsBYHWD articles were collected from literature databases published from January 1, 1915, to March 31, 2024, including the China National Knowledge Infrastructure, Weipu, Wanfang, Pubmed, Scopus, and Web of Science Core Collection. Knowledge network graphs of annual publication volume, authors, institutions, countries, keywords, and references were constructed.ResultsNine thousand two hundred thirty-eight Chinese literature and 559 English articles published between 1915 and 2024 showed an overall upward trend. The countries, institutions, journals, and authors with the highest output were China, Hunan University of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangxian Cai, and Changqing Deng, respectively. Research teams outside China were located at Daejeon University, Gachon University, Aga Khan University, Yale University, etc. The results of keyword co-occurrence and burst analysis included clinical applications, animal experiments, action mechanisms, clinical efficacy, and safety evaluations based on systematic reviews and meta-analyses. Literature co-citation analysis revealed that BYHWD was highly correlated with neuroprotection and reduction of cerebral ischemia/reperfusion injury.ConclusionBoth Chinese and English literature have shown overall growth trend since 1984 and 1989, respectively. Clinical applications, pharmacological effects, mechanisms, active ingredients, evaluation of clinical efficacy and safety, modified BYHWD, methods, and biological techniques may be hotspots and focus of future research on BYHWD. Hotspot analytical methods and biological techniques include systematic reviews, meta-analyses, data mining, network pharmacology, and molecular docking. Future valuable research fields may include studies on neuroprotection, anti-inflammatory activity, ischemic stroke, bioactive compounds, and their underlying mechanisms.

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Research hotspots for pediatric fractures from 2017 to 2022: A bibliometric and visual analysis via Citespace

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