Urinary tract infections (UTIs) remain among the most common bacterial infections worldwide, affecting millions every year. While Escherichia coli (E. coli) is the predominant pathogen, a broad range of Gram-negative and Gram-positive organisms can be implicated. Treating UTIs, particularly complicated or severe infections, frequently relies on broad-spectrum antibiotics, often started empirically before identifying the causative pathogen. However, despite their ability to cover a wide spectrum of pathogens, they have become a growing threat to public health, mainly due to the rise of antimicrobial resistance, but also due to the many other adverse effects they can potentially cause. Neurotoxicity represents one of the most consequential yet underrecognized complications of antibiotic therapy. Broad-spectrum agents commonly used for UTIs, including fosfomycin, fluoroquinolones, carbapenems, and cephalosporins, have been associated with a wide range of neurologic manifestations such as epileptic seizures, encephalopathy, movement disorders, delirium, and psychosis, varying in onset, duration, severity, and reversibility. To induce such reactions, antibiotics interact with the central nervous system (CNS) in several ways that can threaten its integrity and disrupt homeostatic control of its components. This review provides a synopsis of the known neurological adverse reactions linked to four major antibiotic classes routinely used in UTI management and the mechanistic pathways underlying CNS toxicity. An overall clearer understanding of these risks may help clinicians balance therapeutic benefit against potential harm, optimize antimicrobial selection, and improve prevention and management strategies for antibiotic-associated neurotoxicity.
Fish swim bladder (FSB)–derived biomaterials have recently emerged as a promising marine-based extracellular matrix (ECM) platform with potential applications in urological tissue engineering and regenerative medicine. This narrative review synthesizes current evidence regarding the structural, biological, and functional properties of FSB and evaluates its potential role in urological reconstruction. This narrative review was conducted using the PubMed, Google Scholar, and ScienceDirect databases with predefined keywords related to FSB-derived biomaterials. Articles published from January 1, 2000, to December 31, 2025, were included. Eligible studies comprised original research, in vitro and in vivo experimental studies, and review articles. FSB is characterized by a high content of type I collagen, elastin, and glycosaminoglycans (GAGs), forming a well-organized, hydrated, and mechanically resilient matrix that closely resembles native mammalian ECM. These properties support cellular adhesion, proliferation, and tissue regeneration, while also modulating inflammatory responses during wound healing. Preclinical studies demonstrate that decellularized FSB scaffolds exhibit favorable mechanical properties, biocompatibility, and the ability to promote constructive tissue remodeling. In addition, hydrolyzed derivatives, such as gelatin and collagen peptides, have demonstrated antioxidant and regenerative properties. However, intrinsic antimicrobial activity remains limited, often requiring additional functionalization to achieve clinically relevant antibacterial effects. Safety considerations, including potential allergenicity, variability in raw materials, and the risk of microbial contamination, underscore the importance of standardized processing and rigorous sterilization protocols. Composition, thermal stability, and gelation behavior vary substantially across fish species, indicating that species selection is a critical determinant of scaffold performance. Despite encouraging findings in experimental models, clinical translation in urological applications remains limited. Further research focusing on organ-specific applications, long-term safety, and optimized scaffold design is essential. Overall, FSB-derived biomaterials represent a sustainable and versatile platform with significant potential to advance regenerative strategies in urological care.
Objective:To explore the relationship between atrial fibrillation and the Klotho G-395A polymorphism in patients on maintenance hemodialysis (MHD). Methods:The study included 120 MHD patients (persistent atrial fibrillation, n = 30; paroxysmal atrial fibrillation, n = 30; normal sinus rhythm, n = 60) and 120 control individuals. Klotho G-395A mutations were detected by the fluorescence quantitative polymerase chain reaction. ELISA was used to detect serum soluble Klotho (sKl) and intact fibroblast growth factor 23 (iFGF23) levels, and left atrium diameters were measured by echocardiography. Correlation analysis between Klotho G-395A genotypes, clinical parameters, and biochemical indexes was performed, along with logistic regression analysis to determine the risk factors for atrial fibrillation. Results:Three genotypes of Klotho G-395A, namely, GG, GA, and AA, were detected. The frequencies of the GA/AA genotypes and A allelic genes were significantly higher in the MHD patients than in the healthy controls, and these genotypes were associated with both atrial fibrillation and persistent atrial fibrillation. Furthermore, serum sKl, serum iFGF23, and left artery diameter were significantly associated with atrial fibrillation and also showed significant differences between the persistent and paroxysmal atrial fibrillation groups. The serum sKl level was negatively correlated with serum FGF23 level and the left atrium diameter, while the serum FGF23 level was positively correlated with the left atrium diameter. The incidence of atrial fibrillation and left atrium diameter was significantly higher in those with the GA/AA genotype than in those with the GG genotype, while the serum sKl levels were significantly lower. The GA/AA genotype was associated with a 5.444 times higher likelihood of atrial fibrillation than the GG genotype. Conclusions:The A allele of Klotho G-395A may be a risk marker of atrial fibrillation in MHD patients. Moreover, sKl deficiency may contribute to the early development of atrial fibrillation in MHD patients.
Objective:To evaluate the association between prostate morphology and intraoperative blood loss during TURP. Materials and Methods:This prospective observational study included 1120 patients undergoing TURP. Intraoperative blood loss was quantitatively assessed using an endoscopic surgical monitoring system. The transverse and longitudinal diameters of the prostate were measured preoperatively by ultrasonography, and the W/L ratio was defined as the transverse-to-longitudinal diameter ratio. Univariable and multivariable linear regression analyses, nested regression models, and ROC analysis were used to evaluate the association between the W/L ratio and intraoperative blood loss. Results:The median intraoperative blood loss was 104 mL (IQR 36-214), and the median W/L ratio was 1.06 (IQR 1.02-1.18). Univariable analysis showed that the W/L ratio was negatively associated with intraoperative blood loss. In the multivariable analysis, after adjustment for age, BMI, prostate volume, operative time, Q max, 5-ARI use, and surgeon experience category, the W/L ratio remained independently associated with intraoperative blood loss (B = - 45.957, 95% CI: -89.229 to -2.684, p = 0.037). Nested regression models showed that the addition of the W/L ratio increased the model R 2 from 0.444 to 0.446, indicating statistically significant but limited incremental information. Exploratory ROC analyses yielded AUCs of 0.816 and 0.791 for intraoperative blood loss thresholds of ≥ 300 mL and ≥ 400 mL. Conclusions:A lower prostate W/L ratio was independently associated with greater intraoperative blood loss during TURP. Although its effect size was smaller than those of operative time and prostate volume, the W/L ratio may serve as an adjunctive morphometric marker that is readily available from preoperative imaging. Trial Registration: Chinese Registry of Clinical Trial: ChiCTR2400088743.
Background and Aims:Computed tomography texture analysis, powered by machine learning techniques, may differentiate clear cell renal cell carcinoma (ccRCC) from other renal tumor subtypes, such as papillary and chromophobe variants, or benign renal masses such as oncocytomas, as demonstrated here using the KiTS23 dataset. Methods:After excluding multifocal cases to avoid lesion-level labeling ambiguity and intrapatient lesion heterogeneity, 396 cases were included. Using PyRadiomics, 386 radiomics features were initially extracted from preprocessed computed tomography volumes and tumor segmentation masks. Subsequent multistage feature selection reduced the candidate feature set to 73 radiomics descriptors, and LASSO further selected six features for the primary classifier. Candidate machine-learning models were evaluated, with class-weighted Logistic Regression selected as the primary model. Threshold adjustment using the Youden index and bootstrap feature-selection stability analysis were performed. Results:The LASSO-selected class-weighted Logistic Regression model showed the best overall performance. Using the default probability threshold of 0.5, it achieved an accuracy of 76.5%, an area under the receiver operating characteristic curve of 80.4%, a precision of 91.2%, a sensitivity of 73.8%, and a specificity of 82.9% on the held-out test set. Youden-index thresholding increased sensitivity but reduced specificity; therefore, the fixed threshold of 0.5 was retained as the primary operating threshold. Bootstrap stability analysis showed that several LASSO-selected radiomics descriptors were repeatedly selected across resampled training cohorts. Conclusions:Radiomics-based machine learning shows promise for discriminating ccRCC from non-ccRCC renal tumors, but the results remain preliminary and have been evaluated internally. Given the moderate discrimination and lack of external validation, further studies using larger, multicenter datasets with standardized radiomics workflows are necessary.
