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BackgroundRecent studies have shown that obesity may contribute to the pathogenesis of benign prostatic hyperplasia (BPH). However, the mechanism of this pathogenesis is not fully understood.MethodsA prospective case-control study was conducted with 30 obese and 30 nonobese patients with BPH. Prostate tissues were collected and analyzed using ultra performance liquid chromatography ion mobility coupled with quadrupole time-of-flight mass spectrometry (UPLC-IMS-Q-TOF).ResultsA total of 17 differential metabolites (3 upregulated and 14 downregulated) were identified between the obese and nonobese patients with BPH. Topological pathway analysis indicated that glycerophospholipid (GP) metabolism was the most important metabolic pathway involved in BPH pathogenesis. Seven metabolites were enriched in the GP metabolic pathway. lysoPC (P16:0/0:0), PE (20:0/20:0), PE (24:1(15Z)/18:0), PC (24:1(15Z)/14:0), PC (15:0/24:0), PE (24:0/18:0), and PC (16:0/18:3(9Z,12Z,15Z)) were all significantly downregulated in the obesity group, and the area under the curve (AUC) of LysoPC (P-16:0/0/0:0) was 0.9922. The inclusion of the seven differential metabolites in a joint prediction model had an AUC of 0.9956. Thus, both LysoPC (P-16:0/0/0:0) alone and the joint prediction model demonstrated good predictive ability for obesity-induced BPH mechanisms.ConclusionsIn conclusion, obese patients with BPH had a unique metabolic profile, and alterations in PE and PC in these patients be associated with the development and progression of BPH.

Background: Bladder cancer ranks among the top three in the urology field for both morbidity and mortality. Telomere maintenance-related genes are closely related to the development and progression of bladder cancer, and approximately 60%–80% of mutated telomere maintenance genes can usually be found in patients with bladder cancer.Methods: Telomere maintenance-related gene expression profiles were obtained through limma R packages. Of the 359 differential genes screened, 17 prognostically relevant ones were obtained by univariate independent prognostic analysis, and then analysed by LASSO regression. The best result was selected to output the model formula, and 11 model-related genes were obtained. The TCGA cohort was used as the internal group and the GEO dataset as the external group, to externally validate the model. Then, the HPA database was used to query the immunohistochemistry of the 11 model genes. Integrating model scoring with clinical information, we drew a nomogram. Concomitantly, we conducted an in-depth analysis of the immune profile and drug sensitivity of the bladder cancer. Referring to the matrix heatmap, delta area plot, consistency cumulative distribution function plot, and tracking plot, we further divided the sample into two subtypes and delved into both.Results: Using bioinformatics, we obtained a prognostic model of telomere maintenance-related genes. Through verification with the internal and the external groups, we believe that the model can steadily predict the survival of patients with bladder cancer. Through the HPA database, we found that three genes, namely ABCC9, AHNAK, and DIP2C, had low expression in patients with tumours, and eight other genes—PLOD1, SLC3A2, RUNX2, RAD9A, CHMP4C, DARS2, CLIC3, and POU5F1—were highly expressed in patients with tumours. The model had accurate predictive power for populations with different clinicopathological features. Through the nomogram, we could easily assess the survival rate of patients. Clinicians can formulate targeted diagnosis and treatment plans for patients based on the prediction results of patient survival, immunoassays, and drug susceptibility analysis. Different subtypes help to further subdivide patients for better treatment purposes.Conclusion: According to the results obtained by the nomogram in this study, combined with the results of patient immune-analysis and drug susceptibility analysis, clinicians can formulate diagnosis and personalized treatment plans for patients. Different subtypes can be used to further subdivide the patient for a more precise treatment plan.

Danshen (DS) is used for treatment of various ischemic events in the traditional Chinese medicine. Hence, this study was designed to investigate its effect on ischemia/reperfusion injury (IRI) after experimental kidney transplantation (eKTx). Nephrectomized Sprague–Dawley rats underwent eKTx. Some animals were infused with 1.5 ml DS 10 min before surgery. Kidney grafts were transplanted after cold storage for 20 h in Histidine–Tryptophane–Ketoglutarate solution. After reperfusion blood samples were collected for blood urinary nitrogen (BUN), creatinine, lactate dehydrogenase (LDH), and alanine transaminase. Further, tissue was assessed for morphologic and pathophysiologic changes. Donor preconditioning with DS (DS-d) significantly decreased BUN, creatinine, LDH, and aspartate aminotransferase to 65–97% of controls while preconditioning of the recipient (DS-r) decreased values to 58–82% ( P < 0.05). Tubular damage and caspase-3 decreased significantly in both DS-d and DS-r (DS-d: 96% and 67%, DS-r: 83% and 75% of controls) while heat shock protein 72 and superoxide dismutase increased significantly (DS-d: 143% and 173%, DS-r: 166% and 194% of controls). Further, inducible nitric oxide synthase and tumor necrosis factor-α decreased (DS-d: 84% and 61%, DS-r: 79% and 67% of controls) after DS. Preconditioning of both donors and recipients with DS significantly reduces IRI and thus improves graft function after eKTx. [ABSTRACT FROM AUTHOR]