Sigma-1 receptor exerts protective effects on ameliorating nephrolithiasis by modulating endoplasmic reticulum-mitochondrion association and inhibiting endoplasmic reticulum stress-induced apoptosis in renal tubular epithelial cells.

Oxalate-induced damage to renal tubular epithelial cells (RTECs) is an essential factor in the incident kidney stone, but the specific mechanism is unclear. Recent research has pinpointed interacting areas within the endoplasmic reticulum and mitochondria, called mitochondria-associated membranes (MAMs). These studies have linked endoplasmic reticulum stress (ERS) and oxidative imbalance to kidney disease development. The sigma-1 receptor (S1R), a specific protein found in MAMs, is involved in various physiological processes, but its role in oxalate-induced kidney stone formation remains unclear. In this study, we established cellular and rat models of oxalate-induced kidney stone formation to elucidate the S1R's effects against ERS and apoptosis and its mechanism in oxalate-induced RTEC injury. We found that oxalate downregulated S1R expression in RTECs and escalated oxidative stress and ERS, culminating in increased apoptosis. The S1R agonist dimemorfan up-regulated S1R expression and mitigated ERS and oxidative stress, thereby reducing apoptosis. This protective effect was mediated through S1R inhibition of the CHOP pathway. Animal experiments demonstrated that S1R's activation attenuated oxalate-induced kidney injury and alleviated kidney stone formation. This is the first study to establish the connection between S1R and kidney stones, suggesting S1R's protective role in inhibiting ERS-mediated apoptosis to ameliorate kidney stone formation.

Understanding formation processes of calcareous nephrolithiasis in renal interstitium and tubule lumen.

Kidney stone, one of the oldest known diseases, has plagued humans for centuries, consistently imposing a heavy burden on patients and healthcare systems worldwide due to their high incidence and recurrence rates. Advancements in endoscopy, imaging, genetics, molecular biology and bioinformatics have led to a deeper and more comprehensive understanding of the mechanism behind nephrolithiasis. Kidney stone formation is a complex, multi-step and long-term process involving the transformation of stone-forming salts from free ions into asymptomatic or symptomatic stones influenced by physical, chemical and biological factors. Among the various types of kidney stones observed in clinical practice, calcareous nephrolithiasis is currently the most common and exhibits the most intricate formation mechanism. Extensive research suggests that calcareous nephrolithiasis primarily originates from interstitial subepithelial calcified plaques and/or calcified blockages in the openings of collecting ducts. These calcified plaques and blockages eventually come into contact with urine in the renal pelvis, serving as a nidus for crystal formation and subsequent stone growth. Both pathways of stone formation share similar mechanisms, such as the drive of abnormal urine composition, involvement of oxidative stress and inflammation, and an imbalance of stone inhibitors and promoters. However, they also possess unique characteristics. Hence, this review aims to provide detailed description and present recent discoveries regarding the formation processes of calcareous nephrolithiasis from two distinct birthplaces: renal interstitium and tubule lumen.

Exploration of the prognostic effect of costimulatory genes in bladder cancer.

BACKGROUND: A prognostic model of bladder cancer was constructed based on costimulatory molecules, and its stability and accuracy were verified in different datasets. METHOD: The expression profile of bladder cancer RNA and the corresponding clinical data in The Cancer Genome Atlas (TCGA) database were analyzed employing computational biology, and a prognostic model was constructed for costimulating molecule-related genes. The model was applied in GSE160693, GSE176307, Xiangya_Cohort, GSE13507, GSE19423, GSE31684, GSE32894, GSE48075, GSE69795 and GSE70691 in TCGA dataset and Gene Expression Omnibus database. The role of costimulating molecules in bladder cancer tumor subtypes was also explored. By consistent cluster analysis, bladder cancer in the TCGA dataset was categorized into two subtypes: C1 and C2. The C1 subtype exhibited a poor prognosis, high levels of immune cell infiltration and significant enrichment of natural killer cells, T cells and dendritic cells in the C1 subtype. In addition, the ImmuneScore calculated by the ESTIMATE algorithm differed greatly between the two subtypes, and the ImmuneScore of the C1 subtype was greater than the C2 subtype in a significant manner. RESULTS: This study also assessed the relationship between costimulating molecules and immunotherapy response. The high-risk group responded poorly to immunotherapy, with significant differences in the amount of most immune cells between the two groups. Further, three indices of the ESTIMATE algorithm and 22 immune cells of the CIBERSORT algorithm were significantly correlated with risk values. These findings suggest the potential value of costimulating molecules in predicting immunotherapy response. CONCLUSION: A costimulatory molecule-based prognostic model for bladder cancer was established and validated across multiple datasets. This model introduces a novel mode for tailoring treatments to each individual with bladder cancer, and offers valuable insights for informed clinical choices. Simultaneously, this research also delved into the significance of costimulating molecules within distinct bladder cancer subtypes, shedding novel insights into improving immunotherapy strategies for the treatment of bladder cancer.

Oncological effectiveness of bladder-preserving trimodal therapy versus radical cystectomy for the treatment of muscle-invasive bladder cancer: a system review and meta-analysis.

OBJECTIVE: Radical cystectomy (RC) is the gold standard treatment for muscle-invasive bladder cancer (MIBC). As a bladder-preservation option recommended in guidelines, trimodal therapy (TMT) has become increasingly popular in recent years. However, it is still uncertain whether TMT can provide comparable oncologic outcomes to RC. Therefore, it is imperative to evaluate whether TMT yields comparable outcomes to RC. METHODS: We conducted a systematic search of Web of Science, MEDLINE, the Cochrane Library, and EMBASE databases up to June 2023 to identify studies that met our inclusion criteria. The primary outcome measures evaluated in this study were overall survival (OS) and cancer-specific survival (CSS). The study quality was evaluated independently by two authors, and data were extracted accordingly. RESULTS: After excluding duplicates and ineligible articles, our meta-analysis included seven studies involving 3,489 and 13,877 patients in the TMT and RC groups, respectively. Short-term overall survival rates were comparable between the groups, but beyond 5 and > 10-years, the RC group had significantly higher overall survival rates compared to the TMT group. In terms of cancer-specific survival, there was no significant difference between the groups at 1-year follow-up, but from the second year onwards, including the 5-year and > 10-year nodes, the RC group had significantly better outcomes compared to the TMT group. CONCLUSION: The treatment effect of RC is better than that of TMT. Unless the patient can't tolerate RC or has a strong desire to preserve the bladder, RC should be chosen over TMT in treatment, and patients undergoing TMT should be closely followed up.

Building a nomogram plot based on the nanopore targeted sequencing for predicting urinary tract pathogens and differentiating from colonizing bacteria.

Background: The identification of uropathogens (UPBs) and urinary tract colonizing bacteria (UCB) conduces to guide the antimicrobial therapy to reduce resistant bacterial strains and study urinary microbiota. This study established a nomogram based on the nanopore-targeted sequencing (NTS) and other infectious risk factors to distinguish UPB from UCB. Methods: Basic information, medical history, and multiple urine test results were continuously collected and analyzed by least absolute shrinkage and selection operator (LASSO) regression, and multivariate logistic regression was used to determine the independent predictors and construct nomogram. Receiver operating characteristics, area under the curve, decision curve analysis, and calibration curves were used to evaluate the performance of the nomogram. Results: In this study, the UPB detected by NTS accounted for 74.1% (401/541) of all urinary tract microorganisms. The distribution of ln(reads) between UPB and UCB groups showed significant difference (OR = 1.39; 95% CI, 1.246-1.551, p < 0.001); the reads number in NTS reports could be used for the preliminary determination of UPB (AUC=0.668) with corresponding cutoff values being 7.042. Regression analysis was performed to determine independent predictors and construct a nomogram, with variables ranked by importance as ln(reads) and the number of microbial species in the urinary tract of NTS, urine culture, age, urological neoplasms, nitrite, and glycosuria. The calibration curve showed an agreement between the predicted and observed probabilities of the nomogram. The decision curve analysis represented that the nomogram would benefit clinical interventions. The performance of nomogram with ln(reads) (AUC = 0.767; 95% CI, 0.726-0.807) was significantly better (Z = 2.304, p-value = 0.021) than that without ln(reads) (AUC = 0.727; 95% CI, 0.681-0.772). The rate of UPB identification of nomogram was significantly higher than that of ln(reads) only (χ2 = 7.36, p-value = 0.009). Conclusions: NTS is conducive to distinguish uropathogens from colonizing bacteria, and the nomogram based on NTS and multiple independent predictors has better prediction performance of uropathogens.

Clinical features and prognostic factors in patients diagnosed with lymphovascular invasion of testicular germ-cell tumors: Analysis based on the SEER database.

Background: Lymphovascular invasion (LVI) is a high-risk factor for testicular germ-cell tumors (TGCT), but a prognostic model for TGCT-LVI patients is lacking. This study aimed to develop a nomogram for predicting the overall survival (OS) of TGCT-LVI patients. Methods: A complete cohort of 3288 eligible TGCG-LVI patients (training cohort, 2300 cases; validation cohort, 988 cases) were obtained from the Surveillance, Epidemiology, and End Results database. Variables screened by multivariate Cox regression analysis were used to construct a nomogram, which was subsequently evaluated using the consistency index (C-index), time-dependent receiver operating characteristic curve (ROC), and calibration plots. The advantages and disadvantages of the American Joint Committee on Cancer (AJCC) staging system and the nomogram were assessed by integrated discrimination improvement (IDI) and net reclassification improvement (NRI). Decision-analysis curve (DCA) was used to measure the net clinical benefit of the nomogram versus the AJCC staging system. Finally, Kaplan-Meier curves were used to evaluate the ability to identify different risk groups between the traditional AJCC staging system and the new risk-stratification system built on the nomogram. Results: Nine variables were screened by multivariate Cox regression analysis to construct the nomogram. The C-index (training cohort, 0.821; validation cohort, 0.819) and time-dependent ROC of 3-, 5-, and 9-year OS between the two cohorts suggested that the nomogram had good discriminatory ability. Calibration curves showed good consistency of the nomogram. The NRI values of 3-, 5-, and 9-year OS were 0.308, 0.274, and 0.295, respectively, and the corresponding values for the validation cohort were 0.093, 0.093, and 0.099, respectively (P<0.01). Additionally, the nomogram had more net clinical benefit as shown by the DCA curves, and the new risk-stratification system provided better differentiation than the AJCC staging system. Conclusions: A prognostic nomogram and new risk-stratification system were developed and validated to assist clinicians in assessing TGCT-LVI patients.

Competitive Risk Model for Specific Mortality Prediction in Patients with Bladder Cancer: A Population-Based Cohort Study with Machine Learning.

Background: Noncancer death accounts for a high proportion of all patients with bladder cancer, while these patients are often excluded from the survival analysis, which increases the selection bias of the study subjects in the prediction model. Methods: Clinicopathological information of bladder cancer patients was retrieved from the Surveillance, Epidemiology, and End Results (SEER) database, and the patients were categorized at random into the training and validation cohorts. The random forest method was used to calculate the importance of clinical variables in the training cohort. Multivariate and univariate analyses were undertaken to assess the risk indicators, and the prediction nomogram based on the competitive risk model was constructed. The model's performance was evaluated utilizing the calibration curve, consistency index (C index), and the area under the receiver operator characteristic curve (AUC). Results: In total, we enrolled 39285 bladder cancer patients in the study (27500 patients were allotted to the training cohort, whereas 11785 were allotted to the validation cohort). A competitive risk model was constructed to predict bladder cancer-specific mortality. The overall C index of patients in the training cohort was 0.876, and the AUC values were 0.891, 0.871, and 0.853, correspondingly, for 1-, 3-, and 5-year cancer-specific mortality. On the other hand, the overall C index of patients in the validation cohort was 0.877, and the AUC values were 0.894, 0.870, and 0.847 for 1-, 3-, and 5-year correspondingly, suggesting a remarkable predictive performance of the model. Conclusions: The competitive risk model proved to be of great accuracy and reliability and could help clinical decision-makers improve their management and approaches for managing bladder cancer patients.

Dihydroartemisinin Promoted Bone Marrow Mesenchymal Stem Cell Homing and Suppressed Inflammation and Oxidative Stress against Prostate Injury in Chronic Bacterial Prostatitis Mice Model.

Although bone marrow mesenchymal stem cells (BMMSCs) are effective in treating chronic bacterial prostatitis (CBP), the homing of BMMSCs seems to require ultrasound induction. Dihydroartemisinin (DHA) is an important derivative of artemisinin (ART) and has been previously reported to alleviate inflammation and autoimmune diseases. But the effect of DHA on chronic prostatitis (CP) is still unclear. This study aims to clarify the efficacy and mechanism of DHA in the treatment of CBP and its effect on the accumulation of BMMSCs. The experimental CBP was produced in C57BL/6 male mice via intraurethrally administered E. coli solution. Results showed that DHA treatment concentration-dependently promoted the accumulation of BMMSCs in prostate tissue of CBP mice. In addition, DHA and BMMSCs cotreatment significantly alleviated inflammation and improved prostate damage by decreasing the expression of proinflammatory factors such as TNF-α, IL-1ß, and chemokines CXCL2, CXCL9, CXCL10, and CXCL11 in prostate tissue of CBP mice. Moreover, DHA and BMMSCs cotreatment displayed antioxidation property by increasing the production of glutathione peroxidase (GSH-Px), SOD, and decreasing malondialdehyde (MDA) expression. Mechanically, DHA and BMMSCs cotreatment significantly inhibited the expression of TGFß-RI, TGFß-RII, phosphor (p)-Smad2/3, and Smad4 in a dose-dependent manner while stimulated Smad7 expression in the same manner. In conclusion, our findings provided evidence that DHA effectively eliminated inflammatory and oxidative stress against prostate injury, and this effect involved the TGF-ß/Smad signaling pathway in CBP.

Efficient near-infrared anionic conjugated polyelectrolyte for photothermal therapy.

In this work, an anionic conjugated polyelectrolyte (PCP-SO3K), in which the backbone contains alternating 4,4-bis-alkyl-4H-cyclopenta-[2,1-b;3,4-b']-dithiophene and benzene structural units and the charges are provided by pendant sulfonate groups, was synthesized. The ionic nature of PCP-SO3K renders it soluble in water, and PCP-SO3K aqueous solution exhibits good photostability, with two main absorbance bands centered at 490 nm and 837 nm before and after laser irradiation. Its NIR absorption in water, negligible photoluminescence and insignificant intersystem crossing endow PCP-SO3K with efficient photothermal therapy performance, and an effective photothermal conversion efficiency of 56.7% was realized. Thus, PCP-SO3K aqueous solution can be used as an effective photothermal agent for in vivo applications as its photoactivity can be triggered by NIR light and can convert laser energy into thermal energy in a water environment. Of particular importance is the fact that complete tumor remission without recurrence in 4T1 tumor-bearing mice was realized after intravenous injection of PCP-SO3K aqueous solution and laser irradiation (2.0 W cm-2, 808 nm). The results indicate that the application of anionic conjugated polyelectrolytes as photothermal agents in photothermal therapy provides a new platform for the design of photothermal agents for clinical cancer treatment.