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Aims: Pathology education is a core component of medical training, and its literature is critical for refining educational modalities. We performed a cross-sectional bibliometric analysis to explore publications on pathology education, focusing on new medical education technologies.
Methods: The analysis identified 64 pathology journals and 53 keywords. Relevant articles were collected using a web application, PaperScraper, developed to accelerate literature search. Citation data were collected from multiple sources. Descriptive statistics, with time period analysis, were performed using Microsoft Excel and visualised with Flourish Studio. Two article groups were further investigated with a bibliometric software, VOSViewer, to establish co-authorship and keyword relationships.
Results: 8946 citations were retrieved from 905 selected articles. Most articles were published in the last decade (447, 49.4%). The top journals were (184), (122) and the (117). The highest number of citations was found for (2120), followed by (2098) and (1142). Authors with different backgrounds had the greatest number of articles and citations. 12 co-authorship, 3 keyword and 8 co-citation clusters were found for the social media/online resources group, 8 co-authorship, 4 keyword and 7 co-citation clusters for the digital pathology/virtual microscopy/mobile technologies group.
Conclusions: The analysis revealed a significant increase in publications over time. The emergence of digital teaching and learning resources played a major role in this growth. Overall, these findings underscore the transformative potential of technology in pathology education.
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http://dx.doi.org/10.1136/jcp-2023-209203 | DOI Listing |
Cell Mol Biol (Noisy-le-grand)
September 2025
Assistant Professor of General Surgery, Department of Surgery, College of Medicine, University of Duhok, Kurdistan Region, Iraq.
Hormonal status and lymphatic invasion are two important prognostic factors among cases of breast cancer. This study aims to assess and evaluate the hormonal receptor status and lymph node involvement among female breast cancer patients in Duhok city, Kurdistan region, Iraq. A retrospective cross-sectional study was conducted, involving 156 diagnosed cases of breast cancer who had undergone surgical treatment and laboratory investigations at Azadi Teaching Hospital and Duhok Private Hospital for 30 months.
View Article and Find Full Text PDFCell Mol Biol (Noisy-le-grand)
September 2025
Department of Biology, College of Education for Pure Sciences, University of Kerbala, Kerbala, Iraq.
Gastric cancer is one of the causes of deaths related to cancer across the globe and both genetic and environmental factors are the most prominent. Causes of its pathogenesis. This paper researches the expression of the C-FOS gene.
View Article and Find Full Text PDFJ Thorac Oncol
July 2025
Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York.
Introduction: TNM staging systems create prognostic categories by anatomic extent of disease. Whether therapeutically important molecular alterations in NSCLC augment the prognostic information of TNM staging is unclear. To study this, we analyzed molecular data from the ninth edition of the lung cancer staging system.
View Article and Find Full Text PDFElife
September 2025
State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China.
Innate immune cells can acquire a memory phenotype, termed trained immunity, but the mechanism underlying the regulation of trained immunity remains largely elusive. Here, we demonstrate that inhibition of Aurora kinase A (AurA) dampens trained immunity induced by β-glucan. ATAC-seq and RNA-seq analysis reveal that AurA inhibition restricts chromatin accessibility of genes associated with inflammatory pathways such as JAK-STAT, TNF, and NF-κB pathways.
View Article and Find Full Text PDFBrief Bioinform
August 2025
College of Pharmacy, Chongqing Medical University, No. 1 Yixueyuan Road, Yuzhong District, Chongqing 400016, P. R. China.
Drug-induced hepatotoxicity (DIH), characterized by diverse phenotypes and complex mechanisms, remains a critical challenge in drug discovery. To systematically decode this diversity and complexity, we propose a multi-dimensional computational framework integrating molecular structure analysis with disease pathogenesis exploration, focusing on drug-induced intrahepatic cholestasis (DIIC) as a representative DIH subtype. First, a graph-based modularity maximization algorithm identified DIIC risk genes, forming a DIIC module and eight disease pathogenesis clusters.
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