Statement of Retraction: Biochar-based compost: a bibliometric and visualization analysis

BackgroundEpilepsy is a prevalent chronic neurological disease with significant impacts. Traditional diagnostic methods and machine learning face challenges due to the complexity of electroencephalography (EEG). Deep learning (DL) shows potential in epilepsy management through EEG processing and brain imaging analysis. This study aims to fill the gap of missing bibliometric analysis in this field by conducting a visual bibliometric analysis of DL applications in epilepsy, revealing research trends, hotspots, and cutting-edge developments to guide future research directions.MethodsIn this study, a comprehensive search of original research articles and reviews, limited to English-language, published from 2006 to 2025, was conducted by the Web of Science Core Collection database. Bibliometric analyses and visualizations were conducted by CiteSpace, VOSviewer, and Bibliometrix.ResultsThis search retrieved 1266 papers related to DL applied in epilepsy from the Web of Science Core Collection database, showing a consistent upward trend. These papers were from 1957 organizations across 290 countries/regions, primarily from China and the United States. “Biomedical Signal Processing and Control” ranked as the journal with the most published papers. Acharya, U. Rajendra from Ngee Ann Polytechnic, was the most authoritative author. DL-based seizure detection, prediction, and epilepsy management are key research hotspots. Moreover, multimodal data integration approaches are gaining more attention.ConclusionsThis study innovatively employs bibliometric methods to visually analyze research on DL applications in epilepsy, which reveals a rising trend in research within the field and identifies key hotspots, such as DL in seizure detection and prediction. The potential of DL to enhance epilepsy management is highlighted, particularly in improving the accuracy of seizure detection and prediction, thereby enhancing patients’ quality of life. Furthermore, the findings highlight the importance of increasing seizure prediction accuracy, exploring multimodal data integration, and developing more interpretable DL models for future research.

Neutrophils have long been consistently adjudged to hold a dominant position in acute inflammation, which once led people to undervalue their role in chronic malignancy. It is now acknowledged that neutrophils also infiltrate into the tumor microenvironment in substantial quantities and form a highly abundant immune population within the tumor, known as tumor-associated neutrophils (TANs). There has been a surge of interest in researching the eminent heterogeneity and plasticity of TANs in recent years, and scholars increasingly cotton on to the multifaceted functions of TANs so that strenuous endeavors have been devoted to enunciating their potential as therapeutic targets. Yet it remains much left to translate TAN-targeted immunotherapies into clinical practice. Therefore, there is great significance to comprehensively appraise the research status, focal point, and evolution trend of TAN by using bibliometric analysis. Publications related to TAN research from 2000 to 2024 are extracted from the Web of Science Core Collection. Bibliometric analysis and visualization were performed by tools encompassing Microsoft Excel, VOSviewer, CiteSpace, R-bibliometrix, and so on. The bibliometric analysis included a total of 788 publications authored by 5291 scholars affiliated with 1000 institutions across 58 countries/regions, with relevant articles published in 324 journals. Despite China's maximum quantity of publications and top 10 institutions, the United States is the leading country with the most high-quality publications and is also the global cooperation center. FRONTIERS IN IMMUNOLOGY published the most papers, whereas CANCER RESEARCH is the highest co-cited journal. Israeli professor Fridlender, Zvi G. is the founder, pioneer, and cultivator with the highest citation counts and H-index in the TAN area. Our analysis prefigures the future trajectories: TAN heterogeneity, neutrophil extracellular trap, the crosstalk between TANs and immunocytes, and immunotherapy will likely be the focus of future research. A comprehensive bibliometric and visual analysis is first performed to map the current landscape and intellectual structure of TAN, which proffers fresh perspectives for further research. The accurate identification of distinct TAN subpopulations and the precise targeting of key pro-tumor/anti-tumor subpopulations hold immense potential to develop into a TAN-targeted immunotherapy.

In the last few decades, numerous studies pertaining to research groups worldwide have investigated the effects of oral caffeine intake on fat oxidation at rest, during exercise, and after exercise. However, there is no bibliometric analysis to assess the large volume of scientific output associated with this topic. A bibliometric analysis of this topic may be used by researchers to assess the current scientific interest in the application of caffeine as a nutritional strategy to augment fat oxidation, the journals with more interest in this type of publication, and to draw international collaborations between groups working in the same area. For these reasons, the purpose of this study was to assess the research activity regarding oral caffeine intake and fat oxidation rate in the last few decades by conducting a bibliometric and visual analysis. Relevant publications from 1992 to 2022 were retrieved from the Web of Science (WoS) Core Collection database. Quantitative and qualitative variables were collected, including the number of publications and citations, H-indexes, journals of citation reports, co-authorship, co-citation, and the co-occurrence of keywords. There were 182 total publications, while the number of annual publications is saw-shaped with a modest increase of 11.3% from 2000 to 2009 to 2010 to 2019. The United States was the country with the highest number of publications (24.17% of the total number of articles), followed by the Netherlands (17.03%). According to citation analyses, the average number of citations per document is 130, although there are 21 documents that have received more than 100 citations; the most cited document reached 644 citations. These citation data support the overall relevance of this topic in the fields of nutrition and dietetics and sport sciences that when combined harbored 85.71% of all articles published in the WoS. The most productive author was Westerterp-Plantenga with 16 articles (8.79% of the total number of articles). Nutrients was the journal that published the largest number of articles on this topic (6.59% of the total number of articles). Last, there is a tendency to include keywords such as "performance", "carbohydrate", and "ergogenic aid" in the newer articles, while "obesity", "thermogenic", and "tea" are the keywords more commonly included in older documents. Although research into the role of caffeine on fat oxidation has existed since the 1970s, our analysis suggests that the scientific output associated with this topic has progressively increased since 1992, demonstrating that this is a nutritional research area with a strong foundational base of scientific evidence. Based on the findings of this bibliometric analysis, future investigation may consider focusing on the effects of sex and tolerance to caffeine to widen the assessment of the effectiveness of oral caffeine intake as a nutritional strategy to augment the use of fat as a fuel, as these terms rarely appear in the studies included in this analysis. Additionally, more translational research is necessary as the studies that investigate the effect of oral caffeine intake in ecologically valid contexts (i.e., exercise training programs for individuals with excessive adiposity) are only a minor part of the studies on this topic.

Background: Persistent Postural-Perceptual Dizziness (PPPD) is a chronic vestibular disorder that has been receiving more research attention lately. Nonetheless, there is a lack of systematic bibliometric overviews tracing the conceptual evolution, knowledge structure, and emerging research frontiers within this field. The utilization of bibliometric and visualization analyses can enhance the understanding of trends and central themes in PPPD research, offering valuable insights for future studies. Methods: Data were retrieved from the Web of Science Core Collection, yielding a final dataset of 370 bibliographic records ("DATA"). We employed CiteSpace, HistCite, the Alluvial Generator, and R software to conduct multi-dimensional statistical and visualization analyses on publication trends, collaborative networks (countries/institutions/authors), disciplinary distribution, citation bursts, and the evolution of keyword clusters. Results: Starting from 2005, there has been a notable increase in publication volume, reaching its peak in 2024. The United States and Germany are at the forefront of national collaboration, with the University of Munich and the Mayo Clinic being key research institutions. The research focus has transitioned from a primary emphasis on Psychiatry to a broader scope encompassing Neurosciences, Otorhinolaryngology, and General Medicine. Keyword analysis reveals a shift towards standardized terminology, transitioning from "phobic postural vertigo" to "diagnostic criteria" and "consensus documents". Current research trends are centered around comorbidity mechanisms like "vestibular migraine", therapeutic approaches such as "vestibular rehabilitation", and quality of life assessments using the "dizziness handicap inventory". The 2017 consensus document by the Bárány Society is highlighted as a pivotal publication with significant citation impact. Conclusions: The intellectual structure of the field, as revealed by this bibliometric analysis, has transitioned from a phenomenological description to a conceptual unification. The bibliometric analysis indicates that the field is currently in a conceptually stabilized stage characterized by a research focus on refining diagnostic precision and comorbidity exploration, while scholarly attention remains biologically exploratory regarding objective biomarkers and pathophysiological mechanisms.

AimsThis study aims to conduct a bibliometric and visual analysis of published studies on myocarditis and coronavirus disease 2019 (COVID-19) vaccines.BackgroundThe widespread epidemic of COVID-19 has caused millions of deaths and profoundly affected the global medical landscape. Studies on COVID-19 vaccination and related myocarditis have also increased significantly.ObjectiveTo analyze the current status and trends of myocarditis and COVID-19 vaccine research by bibliometric and to elucidate research hotspots and frontiers.MethodsBased on the Web of Science Core Collection SCI-Expanded database, we utilize Excel 2019 and visualization analysis tools VOSviewer, Co-Occurrence13.2 (COOC13.2), Citespace, HistCite, and Scimago Graphica for analysis.ResultsOur study encompassed a total of 389 relevant articles, and we observed a consistent upward trend in the number of publications over time, indicating the growing interest in this subject. Among the countries and regions contributing to this body of literature, the United States emerged as the leading publisher, with Harvard Medical School being the most prominent institution associated with these studies. Notably, Matthew E. Oster from the United States emerged as one of the prominent authors in this field. Hotspot research and frontier areas include myocarditis and the different types of COVID-19 vaccines (e.g., mRNA vaccines, adenovirus vector vaccines, inactivated vaccines), the development of new vaccines in reducing the incidence and sequelae of COVID-19 without an increased incidence of myocarditis, and relief of vaccine hesitancy.ConclusionResearch on myocarditis and the COVID-19 vaccines has grown rapidly. Our research results can help researchers grasp the current status of myocarditis related to the COVID-19 vaccine research and find new research directions in the future.

BackgroundMany studies have shown an association between COVID-19 and autoimmune diseases (ADs). Studies on COVID-19 and ADs have also increased significantly, but there is no bibliometric analysis to summarize the association between COVID-19 and ADs. The purpose of this study was to perform a bibliometric and visual analysis of published studies related to COVID-19 and ADs.MethodsBased on the Web of Science Core Collection SCI-Expanded database, we utilize Excel 2019 and visualization analysis tools Co-Occurrence13.2 (COOC13.2), VOSviewer, CiteSpace, and HistCite for analysis.ResultsA total of 1736 related kinds of papers were included, and the number of papers presented an overall increasing trend. The country/region with the most publications is the USA, the institution is the Harvard Medical School, the author is Yehuda Shoenfeld from Israel, and the journal is Frontiers in Immunology. Research hotspots include immune responses (such as cytokines storm), multisystem ADs (such as systemic lupus erythematosus, rheumatoid arthritis, and multiple sclerosis), treatment modalities (such as hydroxychloroquine, rituximab), vaccination and autoimmune mechanisms (such as autoantibodies, molecular mimicry). The future research direction may be the mechanisms and treatment ideas of the association between ADs and COVID-19 (such as NF-κB, hyperinflammation, antiphospholipid antibodies, neutrophil extracellular traps, granulocyte-macrophage colony-stimulating factor), other cross-diseases of COVID-19 and ADs (such as inflammatory bowel disease, chronic mucocutaneous candidiasis, acute respiratory distress syndrome).ConclusionThe growth rate of publications regarding ADs and COVID-19 has risen sharply. Our research results can help researchers grasp the current status of ADs and COVID-19 research and find new research directions in the future.

Multimodal molecular imaging technologies have been widely used to optimize medical research and clinical practice. Bibliometric analysis was performed to identify global research trends, hot spots, and scientific frontiers of multimodal molecular imaging technology from 2012 to 2021. The articles and reviews related to multimodal molecular imaging were retrieved from the Web of Science Core Collection. A bibliometric study was performed using CiteSpace and VOSviewer. A total of 4169 articles and reviews from 2012 to 2021 were analyzed. An increasing trend in the number of articles on multimodal molecular imaging technology was observed. These publications mainly come from 417 institutions in 92 countries, led by the USA and China. K. Bailey Freund published the most papers amongst the publications, while R.F. Spaide had the most co-citations. A dual map overlay of the literature shows that most publications were specialized in physics/materials/chemistry, and molecular/biology/immunology. Synergistic therapy in cancer, advanced nanotechnology, and multimodal imaging in ophthalmology are new trends and developing areas of interest. A global bibliometric and visualization analysis was used to comprehensively review the published research related to multimodal molecular imaging. This study may help in understanding the dynamic patterns of multimodal molecular imaging technology research and point out the developing areas of this field.

BackgroundType 2 diabetes mellitus (T2DM) is a pathological metabolic disorder induced by the interaction of genetic and environmental factors. Epigenetic modifications, especially DNA and RNA methylation, might be the bridge between hereditary and environmental factors. This study aimed to comprehensively analyze the status and prospective trends of the association between T2DM and DNA/RNA methylation modifications by using bibliometric software.MethodsAll the publications in the Web of Science database for the research of T2DM with DNA and RNA methylation modifications were obtained from the earliest mention to December 2022. CiteSpace software was used to analyze countries, institutions, journals/cited-references, authors/cited-authors, and keywords. Results of the comprehensive visualization and bibliometric analysis were displayed relative to the research hotspots and knowledge structure.ResultsA total of 1,233 publications related to DNA and RNA methylation modifications and T2DM were collected. The number of publications per year and the overall trend consistently and significantly increased during the investigation period. Based on the highest publication counts, the most influential country was the USA, while Lund University was the most productive institution. DIABETES was considered the most popular journal. The most frequent keywords identified in the field of methylation and T2DM were mainly involved in developmental origin, insulin resistance, and metabolism. The study suggested that the study of methylation modifications had an increasingly significant role in understanding the progression of T2DM.ConclusionCiteSpace visualization software was utilized to investigate the status and trends of DNA and RNA methylation modifications in the pathology of T2DM over the past 30 years. Findings from the study provide a guiding perspective for researchers regarding future research directions in this field.

Given the limited availability of bibliometric and visual analysis on the topic of romantic love, the primary objective of the current study is to fill this gap by conducting a comprehensive visual analysis of relevant literature. Through this analysis, the current study aimed to uncover current research trends and identify potential future directions in the field of romantic love. The current study’s search criteria were met by an impressive 6858 publications found in the Web of Science database for the period between 2013 and 2022. A thorough analysis was conducted on the bibliographic visualization of the authors, organizations, countries, references, and keywords. Over time, there has been a remarkable surge in the number of significant publications. Among the authors in the field of romantic love, Emily A. Impett has emerged as the most prolific. The Journal of Social and Personal Relationships is indeed one of the top journals that has published a significant number of articles on the topic of romantic love. During the preceding decade, the University of California System emerged as a prominent producer of publications centered around romantic love, solidifying the United States’ position as a dominant player in this field. In recent times, there has been a significant surge in the popularity of keywords such as “same-sex,” “conflict resolution,” and “social relationships” within academic literature. These topics have experienced a burst of attention, as evidenced by a substantial increase in references and citations. Through the use of visualization maps and analysis of key publications, the current study offers a comprehensive overview of the key concepts and potential avenues for future research in the field of romantic love. Gaining a deep understanding of the complex dynamics and societal implications of romantic love has been instrumental in formulating policies that embody increased compassion and support. As a result, these policies have played a pivotal role in fostering resilient familial ties and contributing to the enduring stability and prosperity of our social fabric.

POEMS syndrome in the 21st century: A bibliometric analysis

BackgroundRheumatoid arthritis (RA) is a chronic autoimmune disease that can lead to joint deformity and loss of function. Recent studies have shown great progress in the research of mesenchymal stem cells (MSCs) in RA. However, thus far, there have been no bibliometric or visualization analyses in this field. This bibliometric analysis provides a comprehensive overview of the general information and research hotspots of MSCs and RA.MethodsArticles relevant to MSCs and RA, published between 2012 and 2021, were searched using the Web of Science Core Collection database. Irrelevant publications were excluded from the analysis. Bibliometric and visualization analyses were conducted using VOSviewer, CiteSpace, and Scimago Graphica.ResultsA total of 577 articles were analyzed. The annual number of publications increased from 2012 to 2017 and plateaued from 2017 to 2021. China and the USA had the largest number of publications. Collaboration among different organizations mainly occurs between institutes of the same country. Stem Cell Research and Therapy and Frontiers in Immunology were the most popular journals in this field. All the top 20 co-cited authors had a positive co-citation relationship. The top references indicate that MSCs can contribute to RA research and treatment mainly via immunomodulation. From 2012 to 2021, “collagen-induced arthritis,” “immunomodulation,” and “therapy” were some of the keywords associated with MSCs and RA, while “extracellular vesicles” showed a strong keyword burst from 2019 to 2021.ConclusionMSCs and RA have been widely studied in different countries and institutions and by different authors over the last ten years. China and the USA had the largest number of publications. Different types of journals provide admirable sources for researchers. Some keywords, including immunomodulation and extracellular vesicles, may be hot spots in the near future. There will be more basic research and clinical translation of MSCs and RA, and substantial new treatments for RA will soon be developed.

Cardiovascular disease remains the leading cause of mortality and disability worldwide. Hypercholesterolemia is a significant causal factor of ischemic heart disease, contributing to half of all cardiovascular fatalities. This study utilized bibliometric tools to offer a comprehensive overview of the current research trends in hypercholesterolemia. The full records and cited references from 18,641 publications (2003-2023) were retrieved from the Web of Science Core Collection, and bibliometric analysis was conducted using VOSviewer. The United States and Harvard University had the most significant influence among the countries/regions and research institutions, respectively. Among the researchers, Kastelein J.J.P. published the highest number of related articles, whereas publications by Sabatine M.S. had the highest average citation. The top 10 keywords were atherosclerosis, familial hypercholesterolemia, cardiovascular disease, risk, risk factors, gene expression, coronary heart disease, low-density lipoprotein, statins, and prevalence. These high-frequency keywords were clustered into groups based on the pathogenic mechanisms, disease prevalence and prevention, drugs and treatments, and familial hypercholesterolemia. These clusters denote distinct study fields and current research hotspots for hypercholesterolemia. Through bibliometric and visual analysis, this study comprehensively assessed global research trends and focal areas within hypercholesterolemia, offering valuable insights into current and future research directions in the field. Further research is needed on the relationship between the intestinal microbiota and cholesterol metabolism and on the advancement of microbiota therapy and precision medicine.

Bibliometric evaluation of global trends and characteristics of RNA methylation during angiogenesis

A high salt diet is a significant risk factor for hypertension, and scholarly investigations into this relationship have garnered considerable attention worldwide. However, bibliometric analyses in this field remain underdeveloped. This study aimed to conduct a bibliometric and visual analysis of research progress on the link between high salt and hypertension from 2011 to 2022 with the goal of identifying future research trends and providing valuable insights for this field. High salt and hypertension data were obtained from the Web of Science Core Collection database. Microsoft Excel, Scimago Graphica, CiteSpace, and VOSviewer software were employed to analyze publication output trends, the most productive countries or regions, journals, authors, co-cited references, and keywords. After screening, 1470 papers met the inclusion criteria. Relevant publications increased annually by 3.66% from 2011 to 2022. The United States led in research productivity, with The Journal of Hypertension publishing the most papers, and David L. Mattson as the most prolific author. Oxidative stress has emerged as a prominent research topic, and extensive investigations have been conducted on related mechanisms. "Oxidative stress," "gut microbiota," and "kidney injury" are recent hotspots that are expected to remain so, and this study carefully characterizes the mechanism of high salt-induced hypertension based on these hotspots. This study utilized bibliometric and visualization analysis to identify the development trends and hotspots of publications related to high salt and hypertension. The findings of this study offer valuable insights into the forefront of emerging trends and future directions in this field.

With the advent of big data, artificial intelligence (AI)is rapidly emerging as a promising avenue for pain management research. Integrating big data analytics, machine learning, and intelligent algorithms within AI can facilitate several significant advancements in healthcare. These include the ability to provide clinical diagnoses of pain, risk prediction, and the development of precision medicine. The number of articles on the application of AI to pain management is on the rise. However, there needs to be more information regarding the quality of the research output in this area, as well as the current hotspots and trends in research. At the same time, no bibliometric metrics have been identified that assess scientific progress in this area. In order to gain an understanding of the current status and potential future directions in the application of AI within the field of pain management, it is first necessary to undertake a visual and analytical study of the relevant research. A bibliometric and visual analysis was conducted to identify research hotspots and trends in the application of AI in pain management over the past 30years. The data information source was the SCI-EXPANDED subset database of the WOS database. A manual search was conducted of all articles and reviews from the database's inception to June 29, 2024. The search was limited to English language sources. A bibliometric analysis was conducted using VOSviewer, CiteSpace, and Bibliometrix (an R-Tool of R-Studio). The analysis encompassed a range of aspects related to the global publication status of papers in the field, including countries and regions, institutions, authors, journals, keywords, and co-cited references. A total of 970 published papers were obtained for this study. The articles were published in 496 journals by 5679 authors affiliated with 2030 academic institutions in 84 countries or regions. From 2014 to 2024, there was a gradual increase in the number of papers published within this field, with 97% of the total published papers. The United States and China contribute the most to this growth. The most prominent research institutions are Harvard University, the University of California system, and Harvard Medical School. At the author level, Mork, Paul Jarle, Bach, and Kerstin of the Norwegian University of Science & Technology (NTNU) were identified as the authors with the highest research output. Breiman, L. of the University of California, Berkeley, emerged as the most influential author, exhibiting the highest co-citation frequency. From the perspective of journals, the Journal of Medical Internet Research, Scientific Reports, PAIN, PLOS ONE, and SPINE are the primary core journals in the field. They have a high number of published papers and co-citation frequency. Furthermore, of the 46,170 co-cited references, Loetsch J's "Machine learning in pain research," published in PAIN in 2018, had the highest number of co-citations, thus making it the most influential article in the study. Combining keywords and co-cited references for analysis leads to the conclusion that using AI for accurate clinical monitoring and risk prediction, clinical diagnosis and classification, and providing personalized treatment plans and care measures for pain has become a current research hotspot and a future trend. Machine learning, deep learning, artificial neural networks, and clinical decision support systems in artificial intelligence are frequently mentioned and commonly used to build predictive models. These are also hot research topics and trends in the field. The field of research on using AI for pain management is experiencing unprecedented growth and development. This study offers a novel perspective on applying AI to pain management, which may inform researchers' selection of potential journals and institutions to collaborate with. Furthermore, this study furnishes researchers with the requisite data to comprehend the present state of research, research focal points, and research tendencies in this field, thereby facilitating the implementation of AI in pain management.