Background The relationship between erectile dysfunction (ED) and physical activity has been established in several previous studies, but there is little information on the specific forms of activity that affect ED. Aim The objective of this study was to evaluate the relationship of 4 exercise categories and 2 activity intensities with ED in US men. Methods We used data sets from the National Health and Nutrition Examination Survey, 2001-2004. We used odds ratios (ORs) and multivariate logistic regression models to investigate the relationship between physical activity and ED. We also conducted subgroup analyses by age and controlled for potential confounder variables using propensity score matching analyses. Outcomes The primary outcome was ED as assessed through self-reporting. Results An overall 4094 adult men were included in the study. Adjusted multivariate regression models indicated that men who participated in monthly muscle-strengthening activities (OR = 0.75, P = .031), leisure activities (OR = 0.76, P = .024), or vigorous activities (OR = 0.64, P = .001) had a lower risk of ED. The subgroup analysis showed that among those ≥40 years old, muscle-strengthening activity (OR = 0.67, P = .005), leisure activity (OR = 0.72, P = .006), and vigorous activity (OR = 0.50, P < .001) were negatively associated with ED. After adjustment of propensity score matching, leisure activity and vigorous activity were also associated with a lower risk of ED, and muscle-strengthening activity was not significantly associated with ED. Clinical Implications Our findings could provide guidance to clinicians in helping patients with ED develop exercise programs. Strengths and Limitations We explored the relationship of 4 types and 2 intensities of exercise with ED, using a large sample size and sampling weights to produce representative data. However, this is only a cross-sectional study. Conclusion Active monthly participation in leisure and vigorous activity is associated with the maintenance of erectile function, while the relevance of muscle-strengthening activities needs further study.
BackgroundCOVID-19, a serious respiratory disease that has the potential to affect numerous organs, is a serious threat to the health of people around the world. The objective of this article is to investigate the potential biological targets and mechanisms by which SARS-CoV-2 affects benign prostatic hyperplasia (BPH) and related symptoms.MethodsWe downloaded the COVID-19 datasets (GSE157103 and GSE166253) and the BPH datasets (GSE7307 and GSE132714) from the Gene Expression Omnibus (GEO) database. In GSE157103 and GSE7307, differentially expressed genes (DEGs) were found using the “Limma” package, and the intersection was utilized to obtain common DEGs. Further analyses followed, including those using Protein-Protein Interaction (PPI), Gene Ontology (GO) function enrichment analysis, and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Potential hub genes were screened using three machine learning methods, and they were later verified using GSE132714 and GSE166253. The CIBERSORT analysis and the identification of transcription factors, miRNAs, and drugs as candidates were among the subsequent analyses.ResultsWe identified 97 common DEGs from GSE157103 and GSE7307. According to the GO and KEGG analyses, the primary gene enrichment pathways were immune-related pathways. Machine learning methods were used to identify five hub genes (BIRC5, DNAJC4, DTL, LILRB2, and NDC80). They had good diagnostic properties in the training sets and were validated in the validation sets. According to CIBERSORT analysis, hub genes were closely related to CD4 memory activated of T cells, T cells regulatory and NK cells activated. The top 10 drug candidates (lucanthone, phytoestrogens, etoposide, dasatinib, piroxicam, pyrvinium, rapamycin, niclosamide, genistein, and testosterone) will also be evaluated by the P value, which is expected to be helpful for the treatment of COVID-19-infected patients with BPH.ConclusionOur findings reveal common signaling pathways, possible biological targets, and promising small molecule drugs for BPH and COVID-19. This is crucial to understand the potential common pathogenic and susceptibility pathways between them.
BackgroundThe prostate, as an endocrine and reproductive organ, undergoes complex hormonal and metabolic changes. Recent studies have shown a potential relationship between metabolic syndrome and the progression and recurrence of prostate cancer (PCa). This study aimed to construct a metabolic syndrome-related prognostic index (MSRPI) to predict biochemical recurrence-free survival (BFS) in patients with PCa and to identify cold and hot tumors to improve individualized treatment for patients with PCa.MethodsThe Cancer Genome Atlas database provided training and test data, and the Gene Expression Omnibus database provided validation data. We extracted prognostic differentially expressed metabolic syndrome-related genes (DEMSRGs) related to BFS using univariate Cox analysis and identified potential tumor subtypes by consensus clustering. The least absolute shrinkage and selection operator (LASSO) algorithm and multivariate Cox regression were used to construct the MSRPI. We further validated the predictive power of the MSRPI using KaplanMeier survival analysis and receiver operating characteristic (ROC) curves, both internally and externally. Drug sensitivity was predicted using the half-maximal inhibitory concentration (IC50). Finally, we explored the landscape of somatic mutations in the risk groups.ResultsForty-six prognostic DEMSRGs and two metabolic syndrome-associated molecular clusters were identified. Cluster 2 was more immunogenic. Seven metabolic syndrome-related genes (CSF3R, TMEM132A, STAB1, VIM, DUOXA1, PILRB, and SLC2A4) were used to construct risk equations. The high-risk index was significantly associated with a poor BFS, which was also validated in the validation cohort. The area under the ROC curve (AUC) for BFS at 1-, 3-, and 5- year in the entire cohort was 0.819, 0.785, and 0.772, respectively, demonstrating the excellent predictive power of the MSRPI. Additionally, the MSRPI was found to be an independent prognostic factor for BFS in PCa. More importantly, MSRPI helped differentiate between cold and hot tumors. Hot tumors were associated with the high-risk group. Multiple drugs demonstrated significantly lower IC50 values in the high-risk group, offering the prospect of precision therapy for patients with PCa.ConclusionThe MSRPI developed in this study was able to predict biochemical recurrence in patients with PCa and identify cold and hot tumors. MSRPI has the potential to improve personalized precision treatment.
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