Our experiments revealed that the therapeutic effects of allicin against E. coli induced urinary inflammation were characterized by the restoration of the highly expressed MALT1, the activated AKT/NF-κB pathway, and excessive release of cytokines.

Background. Renal transplantation can significantly improve the survival rate and quality of life of patients with end-stage renal disease, but the probability of acute rejection (AR) in adult renal transplant recipients is still approximately 12.2. Machine learning (ML) is superior to traditional statistical methods in various clinical scenarios. However, the current AR model is constructed only through simple difference analysis or a single queue, which cannot guarantee the accuracy of prediction. Therefore, this study identified and validated new gene sets that contribute to the early prediction of AR and the prognosis prediction of patients after renal transplantation by constructing a more accurate AR gene signature through ML technology. Methods. Based on the Gene Expression Omnibus (GEO) database and multiple bioinformatic analyses, we identified differentially expressed genes (DEGs) and built a gene signature via LASSO regression and SVM analysis. Immune cell infiltration and immunocyte association analyses were also conducted. Furthermore, we investigated the relationship between AR genes and graft survival status. Results. Twenty-four DEGs were identified. A 5 gene signature (CPA6, EFNA1, HBM, THEM5, and ZNF683) were obtained by LASSO analysis and SVM analysis, which had a satisfied ability to differentiate AR and NAR in the training cohort, internal validation cohort and external validation cohort. Additionally, ZNF683 was associated with graft survival. Conclusion. A 5 gene signature, particularly ZNF683, provided insight into a precise therapeutic schedule and clinical applications for AR patients.

Objective. Bladder cancer (BC) is the most common malignancy in the urinary system and is prone to recurrence and metastasis. Pyroptosis is a kind of cell necrosis that is triggered by the gasdermin protein family. lncRNAs are noncoding RNAs that are more than 200 nucleotides long. Both pyroptosis and lncRNAs are associated with tumor development and progression. This study is aimed at exploring and establishing a prognostic signature of BC based on pyroptosis-related lncRNAs. Methods. In this study, The Cancer Genome Atlas (TCGA) database provided us with the RNA sequencing transcriptome data of bladder cancer patients, and we identified differentially expressed pyroptosis-related lncRNAs in bladder cancer. Then, the prognostic significance of these lncRNAs was assessed using univariate Cox regression analysis and LASSO regression analysis. Subsequently, 4 pyroptosis-related lncRNAs, namely, AL121652.1, AL161729.4, AC007128.1, and AC124312.3, were identified by multivariate Cox regression analysis, thus constructing the prognostic risk model. Then, we compared the levels of immune infiltration, differences in cell function, immune checkpoints, and m6A-related gene expression levels between the high- and low-risk groups. Result. Patients were divided into low-risk or high-risk groups based on the median risk score. Kaplan–Meier survival analysis indicated that the overall survival of bladder cancer patients in the low-risk group was substantially superior to that in the high-risk group ( ). The receiver operating characteristic (ROC) curve further confirmed the credibility of our model. Moreover, gene set enrichment analysis (GSEA) indicated that these were different signal pathways significantly enriched between the two groups. Immune infiltration, immune checkpoint, and N6-methyladenosine-related gene analysis also reflected that there were notable differences between the two groups. Conclusion. Therefore, this prognostic risk model is based on the level of pyroptotic lncRNAs, which is conducive to individualized assessment of the risk of patients and provides a reference for clinical treatment. This will also help provide insights into the prognosis and treatment of bladder cancer.