A nomogram clinical prediction model for predicting urinary infection stones: development and validation in a retrospective study.

PURPOSE: This study aimed to develop a nomogram prediction model to predict the exact probability of urinary infection stones before surgery in order to better deal with the clinical problems caused by infection stones and take effective treatment measures. METHODS: We retrospectively collected the clinical data of 390 patients who were diagnosed with urinary calculi by imaging examination and underwent postoperative stone analysis between August 2018 and August 2023. The patients were randomly divided into training group (n = 312) and validation group (n = 78) using the "caret" R package. The clinical data of the patients were evaluated. Univariate and multivariate logistic regression analysis were used to screen out the independent influencing factors and construct a nomogram prediction model. The receiver operating characteristic curve (ROC), calibration curves, and decision curve analysis (DCA) and clinical impact curves were used to evaluate the discrimination, accuracy, and clinical application efficacy of the prediction model. RESULTS: Gender, recurrence stones, blood uric acid value, urine pH, and urine bacterial culture (P < 0.05) were independent predictors of infection stones, and a nomogram prediction model ( https://zhaoyshenjh.shinyapps.io/DynNomInfectionStone/ ) was constructed using these five parameters. The area under the ROC curve of the training group was 0.901, 95% confidence interval (CI) (0.865-0.936), and the area under the ROC curve of the validation group was 0.960, 95% CI (0.921-0.998). The results of the calibration curve for the training group showed a mean absolute error of 0.015 and the Hosmer-Lemeshow test P > 0.05. DCA and clinical impact curves showed that when the threshold probability value of the model was between 0.01 and 0.85, it had the maximum net clinical benefit. CONCLUSIONS: The nomogram developed in this study has good clinical predictive value and clinical application efficiency can help with risk assessment and decision-making for infection stones in diagnosing and treating urolithiasis.

Tumor Necrosis Factor Receptor-Associated Factor 6 and Human Cancer: A Systematic Review of Mechanistic Insights, Functional Roles, and Therapeutic Potential.

Cancer imposes a substantial burden and its incidence is persistently increasing in recent years. Cancer treatment has been difficult due to its inherently complex nature. The tumor microenvironment (TME) includes a complex interplay of cellular and noncellular constituents surrounding neoplastic cells, intricately contributing to the tumor initiation and progression. This critical aspect of tumors involves a complex interplay among cancer, stromal, and inflammatory cells, forming an inflammatory TME that promotes tumorigenesis across all stages. Tumor necrosis factor receptor-associated factor 6 (TRAF6) is implicated in modulating various critical processes linked to tumor pathogenesis, including but not limited to the regulation of tumor cell proliferation, invasion, migration, and survival. Furthermore, TRAF6 prominently contributes to various immune and inflammatory pathways. The TRAF6-mediated activation of nuclear factor (NF)-κB in immune cells governs the production of proinflammatory cytokines. These cytokines sustain inflammation and stimulate tumor growth by activating NF-κB in tumor cells. In this review, we discuss various types of tumors, including gastrointestinal cancers, urogenital cancers, breast cancer, lung cancer, head and neck squamous cell carcinoma, uterine fibroids, and glioma. Employing a rigorous and systematic approach, we comprehensively evaluate the functional repertoire and potential roles of TRAF6 in various cancer types, thus highlighting TRAF6 as a compelling and emerging therapeutic target worthy of further investigation and development.

Gp130 degradation induced by epirubicin contributes to chemotherapy efficacy.

Two anthracyclines, doxorubicin and epirubicin have been widely used alone or in combination with other antitumor reagents in the chemotherapeutic treatment of various malignancies. Although therapeutic efficacy of anthracyclines has been studied extensively, precise cytotoxic mechanism of these drugs is not been completely elucidated. Here we show that epirubicin-induced degradation of transmembrane protein gp130 contributes to antitumor effect of epirubicin. gp130 is degraded by epirubicin in a proteasome- and autophagy-dependent manner. Epirubicin induces activation of p38-MK2 signaling pathway to phosphorylate gp130 at Ser 782, which results in gp130 internalization and degradation by lysosome. Although mutation of Ser 782 to Ala or Cys in gp130 upregulates global epirubicin-induced autophagy, reduced degradation of gp130 accompanied with enhanced Stat3 phosphorylation at tyrosine 705 is observed. We also show that epirubicin-resistant tumor cells express higher level of gp130. Altogether, our results indicate that degradation of gp130 and subsequent reduction of gp130-Stat3 signaling contributes to epirubicin-induced tumor cell death.