Biomarkers are molecules such as proteins, genes, or other substances that may be tested to determine the stage of the tumor in a patient. The role of prostate cancer biomarkers is pivotal and the combination of prostate cancer immunotherapy with efficient biomarkers has emerged as a beneficial treatment strategy and its use has increased rapidly. The two primary objectives of this current prostate cancer early detection programs were recognizing non-symptomatic individuals with prostate cancer requiring prostatic core biopsy and identifying men with prostate cancer who might benefit from definitive medical treatment. The progress that has been made so far in the identification of the biomarkers that can be used for the classification, prediction and prognostication of prostate cancer, and as major targets for its clinical intervention has been well summarized in this review.

Purpose: This study aimed to analyze the sleep patterns of patients with nocturnal enuresis (NE) using a wearable brain-wave-sensing device. Materials and Methods: We prospectively analyzed 10 of the 14 patients who visited the hospital for NE between August 2023 and July 2024 and agreed to participate in the study. Four patients were excluded owing to pairing errors and loss to follow-up.Participants were instructed to maintain a frequency volume chart for 1 week and sleep while wearing MUSE-STM , a wearable brainwave detection device. We monitored the arousal threshold state based on sleep patterns when NE occurred in all patients. Results: The median age of the patients was 8.7 years (interquartile range, 7.0–10.6), and 4 patients (40.0%) were male. In all participants, non-rapid eye movement (NREM) deep sleep was the dominant stage in the early part of sleep, whereas NREM light sleep was dominant in the middle part. The arousal threshold was high in the early part of sleep and decreased toward the end.A poor response to enuretic alarms was observed when NE occurred during the NREM deep-dominant period. In contrast, a good response was observed when NE occurred during the NREM light-dominant period. Conclusions Differences in sleep stages influence the arousal threshold more than individual characteristics. To effectively manage the NE, focusing on the timing of urination is important in the latter part of the sleep period.

Purpose: Bladder cancer is a common genitourinary malignant disease worldwide. Dasatinib is a small molecule inhibitor of Src family kinases. We investigated the anticancer effect and putative molecular mechanisms of dasatinib on T24 and cisplatin-resistant T24R2 human bladder cancer cells. Materials and Methods: Cell proliferation was measured using Cell Counting Kit-8 (CCK-8) and colony formation in dasatinib treated bladder cancer cells. Flow cytometry was used to determined cell cycle arrest and apoptosis. The expression of apoptosis and autophagy related proteins were detected by western blot analysis. Results: In bladder cancer cells, dasatinib significantly reduced cell proliferation, colony formation, and induced G1-phase arrest.Dasatinib triggered apoptosis along with an increased expression of apoptosis-related genes (caspases, PARP, and cytochrome c).Down-regulation of Bcl-2 and up-regulation of Bad, which are hallmarks of apoptosis, were found to play a dominant role in mediating the effects of dasatinib treatment. We further showed that dasatinib inhibits p-Src, p-PI3K, p-Akt, and p-mTOR in bladder cancer cells. Dasatinib also increased the expression of markers of autophagy flux such as LC3-II and p62. Conclusions These results confirmed that dasatinib is a potent chemotherapeutic drug which induces apoptosis and autophagy by suppressing the PI3K/Akt/mTOR pathway in bladder cancer cells.

Purpose: To investigate the prevalence of anogenital warts (AGW) caused by human papillomavirus in men and the characteristics and changes of the disease in Korea. Materials and Methods: From 2007 to 2018, male AGW corresponding to the International Classification of Disease-10 A63.0 were targeted. Through a big data analysis of the Health Insurance Review & Assessment Service, data of patients diagnosed with AGW as either the main or secondary diagnosis were extracted. The overall prevalence and prevalence by age were calculated through the population by year and the population by 5-year-old unit of the National Statistical Office. Additionally, the amount accrued through the disease code was confirmed and compared as AGW-related medical expenses. Results: The annual number of patients increased by 3.5 times from 32,709 in 2007 to 114,734 in 2018. Additionally, the annual prevalence increased by 3.34 times from 132.83 per 100,000 to 443.57. The age-specific prevalence was the highest among the 25-to 29-year age group. The highest prevalence was observed in the 25- to 29-year age group in 2018 (1,492.15 per 100,000), and the lowest was noted in the 10- to 14-year age group in 2014 (7.28 per 100,000). AGW-related medical expenses increased by approximately 9.76 times from US$ 2,789,215.1 in 2007 to US$ 27,227,254.9 in 2018. Conclusions In Korea, cases of male AGW are increasing yearly, with the 25- to 29-year age group having the highest prevalence.Medical costs related to AGW are also increasing tenfold. For male AGW, further studies and national interventions are needed.

Purpose: Semantic segmentation is a fundamental part of the surgical application of deep learning. Traditionally, segmentation in vision tasks has been performed using convolutional neural networks (CNNs), but the transformer architecture has recently been introduced and widely investigated. We aimed to investigate the performance of deep learning models in segmentation in robot-assisted radical prostatectomy (RARP) and identify which of the architectures is superior for segmentation in robotic surgery. Materials and Methods: Intraoperative images during RARP were obtained. The dataset was randomly split into training and validation data. Segmentation of the surgical instruments, bladder, prostate, vas and seminal vesicle was performed using three CNN models (DeepLabv3, MANet, and U-Net++) and three transformers (SegFormer, BEiT, and DPT), and their performances were analyzed. Results: The overall segmentation performance during RARP varied across different model architectures. For the CNN models, DeepLabV3 achieved a mean Dice score of 0.938, MANet scored 0.944, and U-Net++ reached 0.930. For the transformer architectures, SegFormer attained a mean Dice score of 0.919, BEiT scored 0.916, and DPT achieved 0.940. The performance of CNN models was superior to that of transformer models in segmenting the prostate, vas, and seminal vesicle. Conclusions Deep learning models provided accurate segmentation of the surgical instruments and anatomical structures observed during RARP. Both CNN and transformer models showed reliable predictions in the segmentation task; however, CNN models may be more suitable than transformer models for organ segmentation and may be more applicable in unusual cases. Further research with large datasets is needed.

Purpose: To intelligently diagnose whether there is bladder outlet obstruction (BOO) in female with decent detrusor contraction ability by focusing on urodynamic study (UDS) data. Materials and Methods: We retrospectively reviewed the UDS data of female patients during urination. Eleven easily accessible urinary flow indicators were calculated according to the UDS data of each patient during voiding period. Eight diagnosis models based on back propagation neural network with different input feature combination were constructed by analyzing the correlations between indicators and lower urinary tract dysfunction labels. Subsequently, the stability of diagnostic models was evaluated by five-fold cross-validation based on training data, while the performance was compared on test dataset. Results: UDS data from 134 female patients with a median age of 51 years (range, 27–78 years) were selected for our study.Among them, 66 patients suffered BOO and the remaining were normal. Applying the 5-fold cross-validation method, the model with the best performance achieved an area under the receiver operating characteristic curve (AUC) value of 0.949±0.060 using 9 UDS input features. The accuracy, sensitivity, and specificity for BOO diagnosis model in the testing process are 94.4%, 100%, and 89.3%, respectively. Conclusions The 9 significant indicators in UDS were employed to construct a diagnostic model of female BOO based on machine learning algorithm, which performs preferable classification accuracy and stability.

Purpose: This study evaluated the effectiveness of chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) treatments using multiple pharmaceutical agents that could simultaneously preserve or enhance fertility capability. Materials and Methods: This was a single-center-based, randomized controlled study, whereas the final analysis evaluated a total 350 CP/CPPS patients (age range, 28–40 years) and 50 patients were randomly allocated to each therapeutic group, with a 1:1 ratio. The therapeutic groups consist of tadalafil (group 1, 5 mg daily), L-carnitine (group 2, 2 g daily), Serenoa repens extract (group 3, 320 mg daily), group 4 (tadalafil+L-carnitine), group 5 (tadalafil+S. repens), group 6 (L-carnitine+S. repens), and group 7 (tadalafil+L-carnitine+S. repens). The treatment outcomes at 3 months post-therapy were analyzed. Results: At 3 months post-therapy, the mean total sperm motility was significantly improved in all groups. A normal morphology improvement was observed in L-carnitine receiving groups. The mean total score on the National Institutes of Health Chronic Prostatitis Symptom Index (NIH-CPSI) and the mean International Prostate Symptom Score (IPSS) showed the greatest reduction in intensity in group 7. Logistic regression analyses showed that group 5 and group 7 were significantly associated with improvements in total IPSS and total NIH-CPSI scores at 3 months post-therapy. Group 7 was a significant predictor for improving total sperm motility, leukocytospermia and normal form of sperm. Conclusions Tadalafil, carnitine, and S. repens combination therapy could be considered a feasible treatment option for CP/CPPS males with subfertility.

Purpose: The effect of soy products on prostate cancer (PCA) remains a topic of debate. This study aimed to investigate the association between soy products consumption and the incidence of PCA. Materials and Methods: A search was conducted in the PubMed, EBSCO, Web of Science, and Cochrane Library databases up to December 2023. The adjusted odds ratio (OR) and corresponding 95% confidence interval (CI) were used to assess the association. Results: A total of 22 articles, comprising 1,409,213 participants, were included for this meta-analysis. The results indicate that soy products reduce the risk of PCA (OR=0.94, 95% CI=0.91–0.97, p<0.001), especially in cases of localized or low-grade PCA (OR=0.94, 95% CI=0.90–0.97, p<0.001), but exhibit no effect on non-localized or high-grade PCA (OR=0.96, 95% CI=0.91–1.01, p=0.085).Furthermore, increased consumption frequency was negatively associated with PCA risk. Specifically, soy products can reduce the risk of PCA in African Americans (OR=0.89, p=0.006) and Latinos (OR=0.93, p=0.036), but have no impact on Japanese (OR=0.99, p=0.655), Chinese (OR=0.90, p=0.155), and Whites (OR=0.96, p=0.133). Non-fermented soy products were associated with a reduction in the incidence rate of PCA (OR=0.93, 95% CI=0.90–0.96, p<0.001), while fermented soy products had no effect on the incidence rate of PCA (OR=1.10, 95% CI=0.98–1.22, p=0.096). Conclusions The consumption of soy products can reduce the overall risk of PCA among men. Various factors, including soy products-related factors (e.g., consumption, frequency), population-related factors (e.g., race), and PCA-related factors (e.g., PCA stage) collectively influence the effect of soy products on PCA.