BackgroundWith the development of robotic surgery in the field of oncology, an increasing number of relevant research papers have been published. In order to explore the research hotspots and trends in this field, a bibliometric and visual analysis was performed for the first time.MethodsThe literature records related to oncology robotic surgery were obtained from the Web of Science Core Collection database and imported into the software VOSviewer 1.6.18, CiteSpace 6.1.R3, and the Bibliometric Online Analysis Platform for analysis.ResultsA total of 6,964 publications, including 5,635 articles and 1,329 reviews, were included in this study. Over the past 20 years, annual publications and citations have experienced rapid growth, particularly in the last two years. The United States was the country with the most publications, while Yonsei University in South Korea was the most productive institution. The Journal of Robotic Surgery and the Journal of Urology were the journals with the most publications and citations, respectively. Mottrie A from Belgium and Ficarra V from Italy were the authors with the highest number of publications and citations, respectively. The keywords “robotic surgical procedure”, “laparoscopic surgery”, “prostate cancer”, “colorectal cancer”, “gastric cancer”, “resection”, “complications classification”, “open surgery”, “transoral robotic surgery”, “pathological outcomes”, and “robot-assisted surgery” reflect the research hotspots and trends of oncology robotic surgery.ConclusionThe therapeutic advantages of robotic surgery in oncology are not yet prominent, and further randomized controlled trials with multicenter and large samples are needed to evaluate the advantages of robotic surgery compared with laparoscopic surgery and open surgery in the treatment of tumors from multiple outcome indicators.

The objective of this study is to utilize bibliometric and visual analysis techniques to identify hotspots and frontiers of research in myasthenia gravis (MG) and provide valuable references for future research. The Web of Science Core Collection (WoSCC) database was used to retrieve literature data related to MG research, which was then analyzed using VOSviewer 1.6.18, CiteSpace 6.1.R3, and the Online Platform for Bibliometric Analysis. The analysis revealed 6734 publications distributed across 1612 journals and contributed by as many as 24,024 authors affiliated with 4708 institutions across 107 countries/regions. The number of annual publications and citations for MG research has steadily increased over the past 2 decades, with the last 2 years alone witnessing a remarkable increase in annual publications and citations to over 600 and 17,000, respectively. In terms of productivity, the United States emerged as the top producing country, while the University of Oxford ranked first in terms of research institutions. Vincent A was identified as the top contributor in terms of publications and citations. Muscle & Nerve and Neurology ranked first in publications and citations respectively, with clinical neurology and neurosciences among the main subject categories explored. The study also identified pathogenesis, eculizumab, thymic epithelial cells, immune checkpoint inhibitors, thymectomy, MuSK antibodies, risk, diagnosis, and management as the current hot research topics in MG, while burst keywords like quality of life, immune-related adverse events (irAEs), rituximab, safety, nivolumab, cancer, and classification indicated the frontiers of MG research. This study effectively identifies the hotspots and frontiers of MG research, and offers valuable references for researchers interested in this area.

Background Hepatocellular carcinoma (HCC) is considered to be a malignant tumor with a high incidence and a high mortality. Accurate prognostic models are urgently needed. The present study was aimed at screening the critical genes for prognosis of HCC. Methods The GSE25097, GSE14520, GSE36376 and GSE76427 datasets were obtained from Gene Expression Omnibus (GEO). We used GEO2R to screen differentially expressed genes (DEGs). A protein-protein interaction network of the DEGs was constructed by Cytoscape in order to find hub genes by module analysis. The Metascape was performed to discover biological functions and pathway enrichment of DEGs. MCODE components were calculated to construct a module complex of DEGs. Then, gene set enrichment analysis (GSEA) was used for gene enrichment analysis. ONCOMINE was employed to assess the mRNA expression levels of key genes in HCC, and the survival analysis was conducted using the array from The Cancer Genome Atlas (TCGA) of HCC. Then, the LASSO Cox regression model was performed to establish and identify the prognostic gene signature. We validated the prognostic value of the gene signature in the TCGA cohort. Results We screened out 10 hub genes which were all up-regulated in HCC tissue. They mainly enrich in mitotic cell cycle process. The GSEA results showed that these data sets had good enrichment score and significance in the cell cycle pathway. Each candidate gene may be an indicator of prognostic factors in the development of HCC. However, hub genes expression was weekly associated with overall survival in HCC patients. LASSO Cox regression analysis validated a five-gene signature (including CDC20, CCNB2, NCAPG, ASPM and NUSAP1). These results suggest that five-gene signature model may provide clues for clinical prognostic biomarker of HCC.

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