GLIDR promotes the aggressiveness progression of prostate cancer cells by sponging miR-128-3p.

Glioblastoma downregulated RNA (GLIDR) is a newly discovered long non-coding RNA (lncRNA) that its increased expression indicates a poor prognosis of prostate cancer (PCa). However, the effect of GLIDR on PCa cells is not clear. Our study investigated the role and molecular mechanism of GLIDR in PCa cells. The results showed that GLIDR expression levels were higher in PCa samples and cells than in control. GLIDR could regulate the invasive potential, epithelial-to-mesenchymal transition (EMT) and proliferation in PC-3 and LnCaP cells. Besides, GLIDR could weaken the inhibitory effects of miR-128-3p on invasion, EMT and proliferation in PCa cells. Western blotting proved that miR-128-3p affected the expression of EMT markers, such as E-cadherin, Snail and N-cadherin, and GLIDR could reversed the effects of miR-128-3p on the expression levels of EMT markers in PCa cells. In addition, knockdown of miR-128-3p stimulated the invasion, EMT, and proliferation in PCa cells, whereas these effects were reversed when GLIDR expression was knocked down. GLIDR knockdown inhibited the invasion, EMT, and proliferation in PCa cells, and GLIDR was shown to sponge miR-128-3p. Together, these results highlight GLIDR as a potential therapeutic target for the PCa treatment.

Create a predictive model for neurogenic bladder patients: upper urinary tract damage predictive nomogram.

Objective: To create a nomogram to evaluate the risk of upper urinary tract damage (UUTD) in patients with neurogenic bladder (NGB) Methods: A retrospective analysis was conducted on 301 patients with NGB who were admitted to certain hospitals. Data collected included clinical symptoms, patients' characteristics, laboratory parameters, imaging findings, and urodynamic parameters. The least absolute shrinkage and selection operator（LASSO）regression model was used to optimise the selection of predictors. Multivariate logistic regression analysis was performed to develop a UUTD risk predictive model. Validation was performed by bootstrap. Results: The predictors included in the nomogram included sex, duration of disease, history of UTI, bladder compliance, and fecal incontinence. The model presented good discrimination with a C-index value of 0.796 (95% confidence interval: 0.74896-0.84304) and good calibration. The C-index value of the interval validation was 0.7872112. The results of decision curve analysis (DCA) demonstrated that the UUTD-risk predictive nomogram was clinically useful. Conclusion: The nomogram incorporating the sex, duration of disease, history of UTI, bladder compliance, and fecal incontinence could be an important tool of UUTD risk prediction in NGB patients.