Search PubMedSearch

SEARCH · Search PubMed

Results for “VOSviewer”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

6 recordsLinked to original sources

A Bibliometric Analysis of Systematic Reviews in the Field of Ankylosing Spondylitis from 2007 to 2025.

BACKGROUND: Ankylosing spondylitis (AS) is an inflammatory autoimmune disease and the most common clinical form of spinal arthritis. Over the past decades, tremendous progress has been made in systematic reviews on AS. This study aimed to conduct a bibliometric analysis of AS-related meta-analyses to visualize the hotspots and trends in the field. METHODS: A comprehensive search was conducted for publications of AS meta-analysis from 2007 to 2025 using the Web of Science Core Collection database. Bibliometric analysis was performed using the Bibliometrix software package, VOSviewer, and CiteSpace. RESULTS: In total, 1073 articles were identified, and the number of relevant publications showed annual growth. China, the USA, and England were the most productive countries. Annals of the Rheumatic Diseases was the most productive journal (54, 10.65%), Pan Faming was the most productive author (23, 4.54%), and Anhui Medical University (45, 8.88%) was the most productive institution. High-frequency keywords were mainly grouped into five themes: complications, biologics, physical therapy exercises, gut microbiota, and analytical methods. DISCUSSION: This first bibliometric analysis of AS-related EBM research showed a 20-year upward trend in AS meta-analyses, consistent with prior studies. CiteSpace revealed that China (top since 2014) and the USA led in publications (53 countries) but had limited collaboration. Pan Faming (23 articles) was the most active author, and Annals of the Rheumatic Diseases published the most articles. Keyword analysis identified five themes (e.g., AS complications, biologics) and research frontiers: pre-2012 genome-AS links, post-2012 multi-center RCTs, and the recent focus on AS patients' HRQoL. Limitations included database and English-language bias; future meta-analyses should adopt standardized outcomes. CONCLUSION: In recent years, there has been a remarkable surge in the number of meta-analyses on AS. This significant increase underscores the importance of this research area. Studies in this field have mainly focused on several key aspects: risk factors, network meta-analysis, and quality- of-life studies. These findings are highly valuable for understanding advancements in ASrelated research and can also encourage researchers and clinicians to focus on both effective medical treatments and the well-being of AS patients.

Spondylitis, Ankylosing

Molecular Diagnostics for WHO Priority Bacterial Pathogens: A Bibliometric Mapping of Diagnostic Platforms, Resistance Markers, and Antimicrobial Resistance Research Trends.

Antimicrobial resistance (AMR) constrains effective treatment and carries implications for infection control, surveillance, and public health. The World Health Organization (WHO) priority bacterial pathogen framework has intensified the need for diagnostic innovation by redefining research priorities around organisms combining high disease burden with complex resistance profiles. Molecular diagnostics have accordingly moved beyond culture-based workflows, integrating rapid pathogen identification, resistance-marker detection, genomic surveillance, and clinical decision support. The present study conducted a bibliometric mapping of the literature on WHO priority pathogens. Rather than addressing resistance at a general level or a single pathogen or technology, it integrates priority pathogens, molecular platforms, and resistance markers within a single framework, tracing their joint thematic and temporal evolution along an explicit pathogen-platform-marker axis. Scopus-indexed articles and reviews (2000-2025) were retrieved, yielding 1746 publications after screening adapted from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Analyses used Bibliometrix/Biblioshiny, R, and VOSviewer. The literature expanded markedly after 2018, led by China and the United States. Methicillin-resistant Staphylococcus aureus (MRSA), Mycobacterium tuberculosis, Enterococcus faecium, and the Enterobacterales-carbapenemase axis constituted the principal thematic cores, whereas conventional polymerase chain reaction (PCR)/nucleic acid amplification testing (NAAT) and whole-genome sequencing were the dominant platforms. Overall, the field has evolved from pathogen detection into an AMR-centered translational domain encompassing resistance prediction, genomic epidemiology, surveillance, and clinical decision support. Diagnostic development, stewardship, and surveillance depend on hybrid workflows coupling rapid marker-targeted assays with genome-based characterization, delivering actionable resistance within clinically meaningful timeframes, and extending coverage to underrepresented pathogens and platforms.

Humans

Effectiveness of artificial intelligence in nursing simulation education: A systematic review, meta-analysis and bibliometric visualization analysis.

OBJECTIVES: To synthesize the roles and core functions of AI in nursing simulation education for nursing students via systematic review, quantitatively evaluate its effects on students' knowledge and skill outcomes through meta-analysis, and map the research landscape and development trends of this field through bibliometric visualization analysis. DESIGN: Systematic review, meta-analysis and bibliometric visualization analysis. DATA SOURCES: Eight electronic databases: PubMed, Web of Science, MEDLINE, ERIC, Academic Search Complete, China National Knowledge Infrastructure (CNKI), Wanfang Database, VIP Chinese Science and Technology Journal Database (VIP) were employed to search studies from the time of construction to 16 December 2025. REVIEW METHODS: Studies meeting the inclusion criteria were screened. The revised Cochrane Risk of Bias tool (ROB 2) and Joanna Briggs Institute (JBI) critical appraisal checklists were used for quality assessment. Meta-analysis was performed with Review Manager 5.4, and bibliometric visualization analysis was conducted using VOSviewer 1.6.20 and Bibliometrix (based on R4.4.3). RESULTS: A total of 61 studies were included. AI primarily played two roles in nursing simulation education: peer-type new subject (n = 24) and direct mediator (n = 22). Meta-analysis showed that AI interventions significantly improved nursing students' knowledge (SMD = 1.49, 95% CI [0.55,2.43], p = 0.002) and skills (SMD = 0.66, 95% CI [0.02,1.31], p = 0.04). Bibliometric analysis identified that the United States of America and China were the two main contributing countries in this field, and the key motor themes included generative artificial intelligence, virtual patients, and geriatric care. CONCLUSIONS: AI exerts positive effects on nursing students' knowledge acquisition and skill enhancement in simulation education, with peer-type new subject and direct mediator as the dominant roles. Future research should focus on expanding AI applications in multi-specialty simulation scenarios, activating the data-driven value of machine learning, and strengthening international collaboration and standardization construction, so as to promote the sustainable development of AI-integrated nursing simulation education.

Humans

Bibliometric analysis of retinoblastoma research over the past decade.

BACKGROUND: Retinoblastoma (RB), the most prevalent primary intraocular malignancy in children, has emerged as a model disease for exploring the molecular underpinnings of pediatric cancer. Over the past decade, research in this field has accelerated, propelled by advances in genomics, diagnostic imaging, targeted therapies, and global scientific collaboration. METHODS: This study systematically retrieved RB-related publications from 2015 to 2024 using the Web of Science Core Collection. A total of 4990 articles were included. CiteSpace and VOSviewer were employed to perform bibliometric and visual analyses across multiple dimensions, including countries, institutions, authors, journals, and thematic evolution. RESULTS: The United States and China were identified as the leading contributors, jointly accounting for over 40.55% of all publications. US-based journals led in both publication volume and citation impact, underscoring their global influence. Cluster analysis revealed 4 major research domains: clinical diagnosis, treatment, and prognosis; molecular mechanisms and signaling pathways; gene and protein function studies; and research methodologies and experimental models. CONCLUSION: RB research is transitioning into an era of precision oncology, characterized by molecular subtyping, novel therapeutic targets, and individualized treatment approaches. While diagnostic and therapeutic outcomes have markedly improved in high-income countries, significant disparities persist in low- and middle-income regions due to limited access to early detection and comprehensive care. Future priorities should include the refinement of preclinical models, investigation of drug resistance mechanisms, and promotion of international collaboration to standardize diagnostic and therapeutic strategies. These efforts are critical to improving global outcomes for children with RB.

Retinoblastoma

From transcriptomic profiling to precision oncology: a bibliometric analysis of RNA sequencing in acute myeloid leukemia.

BACKGROUND: RNA sequencing (RNA-seq) has become an important tool for investigating the molecular heterogeneity of acute myeloid leukemia (AML); however, the global development and thematic evolution of this field remain inadequately characterized. OBJECTIVE: To map the global landscape of AML RNA-seq research and identify major knowledge domains, emerging themes, and temporal changes in research priorities. METHODS: Publications indexed in the Web of Science Core Collection and Scopus between January 1, 2007, and August 18, 2025, were retrieved. After database filtering, merging, and deduplication, 3,460 articles and reviews were included. CiteSpace, VOSviewer, the bibliometrix R package, and Microsoft Excel were used to analyze publication trends, collaboration networks, co-citation structures, keyword evolution, and citation bursts. RESULTS: Publication output increased steadily, accelerating after 2014. China contributed the largest number of publications (n = 547, 15.8%), whereas the United States had the highest total citation count. Major publication outlets spanned hematology, oncology, genomics, and molecular biology. Co-citation analysis identified prominent themes involving next-generation sequencing, gene mutations, KMT2A rearrangements, epigenetic dysregulation, leukemia-initiating cells, drug resistance, biomarkers, T-cell biology, and single-cell sequencing. Earlier literature emphasized sequencing technologies, gene expression profiling, and molecular alterations, whereas recent publications show increasing representation of cellular heterogeneity, single-cell transcriptomics, drug resistance, biomarker applications, immune-related research, and computational interpretation. CONCLUSION: While molecular characterization remains foundational, AML RNA-seq research has broadened to encompass increasingly prominent cellular, functional, computational, and translational dimensions. This study provides a structured overview of the field; nevertheless, bibliometric prominence should not be interpreted as direct evidence of clinical utility.

RNA sequencing

Microplastics and nanoplastics-related genes signature predicts prognosis in pancreatic ductal adenocarcinoma and functional validation of interleukin 1 alpha.

BACKGROUND: Microplastics and nanoplastics (MNPs), as emerging environmental pollutants, have garnered significant attention from the global scientific community due to their potential threats to human health, particularly their association with the occurrence and development of cancer. The goal of our study is to create a predictive marker for pancreatic ductal adenocarcinoma (PAAD) based on MNPs-related genes, with the purposes of predicting survival outcomes and assessing the tumor immune microenvironment. METHODS: Using multi-cohort data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and International Cancer Genome Consortium (ICGC), we assessed the association between MNPs and PAAD prognosis through the Xiantao Academic (https://www.xiantao.love/). The development of a prognostic signature was followed by an assessment of its significance through the Kaplan-Meier method, time-dependent receiver operating characteristic (ROC), and decision curve analysis (DCA). The validity of the risk model was confirmed through the ICGC and GSE71729 cohorts. The model was then assessed for levels of tumor immune infiltration. To explore MNPs-related genes expression characteristics within immune cells in PAAD, we performed single-cell RNA sequencing and spatial transcriptomics analysis through the Sparkle Platform (https://grswsci.top/). Finally, in vitro experiments were conducted to investigate the biological function of interleukin 1 alpha (IL1A). RESULTS: A four-gene signature comprising XDH, IL1A, KIF20A, and ASPM, based on MNPs, was developed to stratify PAAD patients into two distinct risk groups. The high-risk group showed a significantly poorer prognosis. A similar trend was verified in the external cohorts ICGC and GSE71729. The signature risk score affected immune cell infiltration in the PAAD microenvironment. The infiltration of B cells, CD8+ T cells, cytotoxic cells, immature dendritic cells (iDCs), mast cells, plasmacytoid dendritic cell (pDC), T cells, Tem cells, T follicular helper (TFH) cells, and T helper 17 (Th17) cells had a positive correlation with the low-risk group. In contrast, high-risk patients tended to have increased number of T helper (Th2) cells and higher expression of SIGLEC15, CD274, IGSF8. Knockdown of IL1A in PAAD cells inhibited their tumor proliferation ability in vitro. CONCLUSIONS: Using MNPs-related genes, we built a prognostic model for PAAD, revealing that patients with high-risk scores are likely to have a worse prognosis. This model is designed to develop personalized treatment strategies tailored to the specific needs of each patient, thereby improving clinical outcomes for PAAD patients. Furthermore, IL1A could be a promising therapeutic candidate for PAAD.

Microplastics