Background: Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is a common urological disease, and research on CP/CPPS has increased over the past 50 years. However, few studies have statistically analyzed these publications. In this work, we conducted the knowledge domain and highlighted current research hotspots and emerging trends in CP/CPPS from 1970 to 2020 based on VOSviewer and CiteSpace. Methods: Relevant original articles were obtained from the Web of Science (WoS) database between 1970 and 2020. VOSviewer and CiteSpace software were used to perform the analysis and visualization of scientific productivity and emerging trends. Results: Our results show that the articles related to CP/CPPS have dramatically increased every year from 1 publication in 1970 to 111 publications in 2020. The USA dominated the field in all countries, and Queen's University (Canada) has more extensive cooperating relationships with other institutions. J. Curtis Nickel may have a significant influence on CP/CPPS research with more publications and cocitations. The Journal of Urology is the foremost productive journal and has the most citations of all the journals. A total of 11 major clusters were explored based on the reference cocitation analysis (RCA). Definition, incidence rate or clinical characteristics, etiology or pathogenesis, epidemiological studies (cross-sectional study and cohort study), clinical studies (inflammation, pain, LUTS, α-blockers, antibiotic) and relationships with other diseases [benign prostatic hyperplasia (BPH), prostate cancer, sexual dysfunction] are the knowledge bases for CP/ CPPS research. The treatment mode also changed gradually from anti-inflammatory therapy to symptom improvement, and NIH-CPSI was taken as the evaluation criterion.Conclusions: This scientometric study comprehensively reviewed publications related to CP/CPPS during the past 50 years using quantitative and qualitative methods, and the information provides some references for scholars to conduct further research on CP/CPPS.
Introduction: Cuproptosis seems to promote the progression of diverse diseases. Hence, we explored the cuproptosis regulators in human spermatogenic dysfunction (SD), analyzed the condition of immune cell infiltration, and constructed a predictive model.Methods: Two microarray datasets (GSE4797 and GSE45885) related to male infertility (MI) patients with SD were downloaded from the Gene Expression Omnibus (GEO) database. We utilized the GSE4797 dataset to obtain differentially expressed cuproptosis-related genes (deCRGs) between SD and normal controls. The correlation between deCRGs and immune cell infiltration status was analyzed. We also explored the molecular clusters of CRGs and the status of immune cell infiltration. Notably, weighted gene co-expression network analysis (WGCNA) was used to identify the cluster-specific differentially expressed genes (DEGs). Moreso, gene set variation analysis (GSVA) was performed to annotate the enriched genes. Subsequently, we selected an optimal machine-learning model from four models. Finally, nomograms, calibration curves, decision curve analysis (DCA), and the GSE45885 dataset were utilized to verify the predictions’ accuracy.Results: Among SD and normal controls, we confirmed that there are deCRGs and activated immune responses. Through the GSE4797 dataset, we obtained 11 deCRGs. ATP7A, ATP7B, SLC31A1, FDX1, PDHA1, PDHB, GLS, CDKN2A, DBT, and GCSH were highly expressed in testicular tissues with SD, whereas LIAS was lowly expressed. Additionally, two clusters were identified in SD. Immune-infiltration analysis showed the existing heterogeneity of immunity at these two clusters. Cuproptosis-related molecular Cluster2 was marked by enhanced expressions of ATP7A, SLC31A1, PDHA1, PDHB, CDKN2A, DBT, and higher proportions of resting memory CD4+ T cells. Furthermore, an eXtreme Gradient Boosting (XGB) model based on 5-gene was built, which showed superior performance on the external validation dataset GSE45885 (AUC = 0.812). Therefore, the combined nomogram, calibration curve, and DCA results demonstrated the accuracy of predicting SD.Conclusion: Our study preliminarily illustrates the relationship between SD and cuproptosis. Moreover, a bright predictive model was developed.
Background Thrombophilia is a group of disorders that result in a blood hypercoagulable state and induce thrombosis, which was found widely existed in recurrent pregnancy loss (RPL). More and more research about thrombophilia has been conducted but the association between thrombophilia and RPL remains uncertain. Thus, it’s necessary to combine relevant literature to find the research hotspots and analyze the internal link between different study points, and then predict the development trend in RPL with thrombophilia. Methods Relevant articles between 1970 and 2022 were obtained from the Web of Science (WoS) database. Software VOSviewer and CiteSpace were used to perform the analysis and conduct visualization of scientific productivity and emerging trends. Results Seven hundred twenty-five articles published in recent 30 years by 3205 authors from 1139 organizations and 68 countries were analyzed. 37authors, 38 countries, and 53 organizations published papers ≥5. The United States was the most productive country and Univ Amsterdam was the most productive institution. Journal thrombosis and haemostasis had the most total citations. In keyword and clusters, factor-v-Leiden, inherited thrombophilia, activated protein-c, low-dose aspirin, molecular-weigh heparin, polymorphism had high-frequency focus on its etiology, diagnostics, and therapeutics. The strongest keyword bursts showed the research hotspots changed over time. Conclusions There could be differences in the clinical relevance of different type of thrombophilia, as well as single and multiple thrombophilic factors. Anticoagulation and immunotherapy are currently the main treatment options. More clinical trials and basic research are expected and we should attach more attention to the whole management of in-vitro fertilization in the future.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.