Gut microbiota in insulin resistance: a bibliometric analysis.

Tian W ，Liu L ，Wang R ，Quan Y ，Tang B ，Yu D ，Zhang L ，Hua H ，Zhao J ... -  《Journal of Diabetes and Metabolic Disorders》

Research hotspots and trends in diabetes and insulin resistance: a bibliometric analysis.

Many previous studies explored the relationship between diabetes and insulin resistance (IR); however, addressing the research gap where no bibliometric analysis had been conducted to summarize and analyze these publications, we will undertake a comprehensive bibliometric analysis to investigate the current status and emerging trends in publications examining the association between diabetes and IR. We retrieved publications related to the interaction between diabetes and IR from the Web of Science Core Collection (WoSCC). By utilizing software such as CiteSpace, VOSviewer, and Excel 2019, we analyzed and extracted relevant information from the literature to identify and delineate the research hotspots and directions in the study of diabetes and IR. From 1900 to 2024, a total of 2,698 publications were included in the bibliometric analysis, showing a steady annual increase in the number of publications. The USA led in this research field, with the Harvard University being a key research institution. The author Olefsky JM, published the most papers;Defronzo RA was the most cited author. DIABETES was the journal with the highest number of published papers and was also the most cited journal. The main discipline in the field of diabetes and IR research was Endocrinology and Metabolism. The most cited article was "Mechanisms linking obesity to insulin resistance and type 2 diabetes (2006)";"The IDF Diabetes Atlas: Global estimates of diabetes prevalence for 2017 and projections for 2045(2018)" was the most cited reference. "insulin resistance" was the most frequently occurring keyword. The main research hotspots and frontier areas in diabetes and IR research were as follows: (1) The association between IR, diabetes, and obesity was a popular research topic; (2) Cardiovascular diseases secondary to diabetes and IR were another hot topic among researchers; (3) As a core pathological change in diabetes, IR was a major therapeutic target for improving diabetes. This study summarized the research trends and hotspots in the field of diabetes and IR, provided valuable information and insights for scholars who focused on diabetes and IR scientific research, and offered a reference for future research directions.

Zhang S ，Yan H ，Cao D ，Sun W ，Li J ，Xu J ，Song B ，Wu X ... -  《Frontiers in Nutrition》

Research hotspots and frontiers of machine learning in renal medicine: a bibliometric and visual analysis from 2013 to 2024.

The kidney, an essential organ of the human body, can suffer pathological damage that can potentially have serious adverse consequences on the human body and even affect life. Furthermore, the majority of kidney-induced illnesses are frequently not readily identifiable in their early stages. Once they have progressed to a more advanced stage, they impact the individual's quality of life and burden the family and broader society. In recent years, to solve this challenge well, the application of machine learning techniques in renal medicine has received much attention from researchers, and many results have been achieved in disease diagnosis and prediction. Nevertheless, studies that have conducted a comprehensive bibliometric analysis of the field have yet to be identified. This study employs bibliometric and visualization analyses to assess the progress of the application of machine learning in the renal field and to explore research trends and hotspots in the field. A search was conducted using the Web of Science Core Collection database, which yielded articles and review articles published from the database's inception to May 12, 2024. The data extracted from these articles and review articles were then analyzed. A bibliometric and visualization analysis was conducted using the VOSviewer, CiteSpace, and Bibliometric (R-Tool of R-Studio) software. 2,358 papers were retrieved and analyzed for this topic. From 2013 to 2024, the number of publications and the frequency of citations in the relevant research areas have exhibited a consistent and notable increase annually. The data set comprises 3734 institutions in 91 countries and territories, with 799 journals publishing the results. The total number of authors contributing to the data set is 14,396. China and the United States have the highest number of published papers, with 721 and 525 papers, respectively. Harvard University and the University of California System exert the most significant influence at the institutional level. Regarding authors, Cheungpasitporn, Wisit, and Thongprayoon Charat of the Mayo Clinic organization were the most prolific researchers, with 23 publications each. It is noteworthy that researcher Breiman I had the highest co-citation frequency. The journal with the most published papers was "Scientific Reports," while "PLoS One" had the highest co-citation frequency. In this field of machine learning applied to renal medicine, the article "A Clinically Applicable Approach to Continuous Prediction of Future Acute Kidney Injury" by Tomasev N et al., published in NATURE in 2019, emerged as the most influential article with the highest co-citation frequency. A keyword and reference co-occurrence analysis reveals that current research trends and frontiers in nephrology are the management of patients with renal disease, prediction and diagnosis of renal disease, imaging of renal disease, and development of personalized treatment plans for patients with renal disease. "Acute kidney injury," "chronic kidney disease," and "kidney tumors" are the most discussed diseases in medical research. The field of renal medicine is witnessing a surge in the application of machine learning. On one hand, this study offers a novel perspective on applying machine learning techniques to kidney-related diseases based on bibliometric analysis. This analysis provides a comprehensive overview of the current status and emerging research areas in the field, as well as future trends and frontiers. Conversely, this study furnishes data on collaboration and exchange between countries, regions, institutions, journals, authors, keywords, and reference co-citations. This information can facilitate the advancement of future research endeavors, which aim to enhance interdisciplinary collaboration, optimize data sharing and quality, and further advance the application of machine learning in the renal field.

Li F ，Hu C ，Luo X 《-》

Hotspots and research trends of gut microbiome in polycystic ovary syndrome: a bibliometric analysis (2012-2023).

Polycystic ovary syndrome (PCOS) is a common gynecological condition affecting individuals of reproductive age and is linked to the gut microbiome. This study aimed to identify the hotspots and research trends within the domain of the gut microbiome in PCOS through bibliometric analysis. Utilizing bibliometric techniques, we examined the literature on the gut microbiome in PCOS from the Web of Science Core Collection spanning the period from 2012 to 2023. Analytical tools such as CiteSpace, VOSviewer, and Bibliometric R packages were employed to evaluate various metrics, including countries/regions, institutions, authors, co-cited authors, authors' H-index, journals, co-references, and keywords. A total of 191 publications were identified in the field of gut microbiome in PCOS, with an increase in annual publications from 2018 to 2023. People's Republic of China was the most productive country, followed by the United States of America (USA), India. Shanghai Jiao Tong University, Fudan University, and Beijing University of Chinese Medicine were the top three most publications institutions. Thackray VG was identified as the most prolific author, holding the highest H-index, while Liu R received the highest total number of citations. The journal "Frontiers in Endocrinology" published the most articles in this domain. The most frequently co-cited reference was authored by Qi XY. The analysis of keyword burst detection identified "bile acids" (2021-2023) as the leading frontier keyword. Additionally, "gut dysbiosis," "phenotypes," "adolescents," "metabolomics," "metabolites," "fecal microbiota transplantation," and "IL-22" have emerged as the primary keywords reflecting recent research trends. This bibliometric analysis explores how the gut microbiome influences endocrine and metabolic disorders related to PCOS, emphasizing its role in the development of PCOS and treatments targeting the gut microbiome. The findings serve as a valuable resource for researchers, enabling them to identify critical hotspots and emerging areas of investigation in this field.

Wu R ，Mai Z ，Song X ，Zhao W ... -  《-》

Research hotspots and trends in gut microbiota and nonalcoholic fatty liver disease: A bibliometric study.

Recent research indicates that the intestinal microbial community, known as the gut microbiota, may play a crucial role in the pathogenesis of nonalcoholic fatty liver disease (NAFLD). To understand this relationship, this study used a comprehensive bibliometric analysis to explore and analyze the currently little-known connection between gut microbiota and NAFLD, as well as new findings and possible future pathways in this field. To provide an in-depth analysis of the current focus issues and research developments on the interaction between gut microbiota and NAFLD. In this study, all data were collected from the Web of Science Core Collection, and the related searches were completed on one day (February 21, 2024). The data were stored in plain text format to facilitate subsequent analysis. VOSviewer 1.6.20 and CiteSpace 6.1R6 Basic were used for knowledge graph construction and bibliometric analysis. The study included a total of 1256 articles published from 2013 to 2023, and the number of published papers demonstrated an upward trend, reaching a peak in the last two years. The University of California, San Diego held the highest citation count, while Shanghai University of Traditional Chinese Medicine in China led in the number of published works. The journal "Nutrients" had the highest publication count, while "Hepatology" was the most frequently cited. South Korean author Suk Ki Tae was the most prolific researcher. The co-cited keyword cluster labels revealed ten major clusters, namely cortisol, endothelial dysfunction, carbohydrate metabolism, myocardial infarction, non-alcoholic steatohepatitis, lipotoxicity, glucagon-like peptide-1, non-islet dependent, ethnicity, and microRNA. Keyword outbreak analysis highlighted metabolic syndrome, hepatic steatosis, insulin resistance, hepatocellular carcinoma, cardiovascular disease, intestinal permeability, and intestinal bacterial overgrowth as prominent areas of intense research. Through the quantitative analysis of relevant literature, the current research focus and direction of gut microbiota and NAFLD can be more clearly understood, which helps us better understand the pathogenesis of NAFLD, and also opens up innovative solutions and strategies for the treatment of NAFLD.

Huang CY ，Luo ZZ ，Huang WP ，Lin LP ，Yao YT ，Zhuang HX ，Xu QY ，Lai YD ... -  《-》