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Abstract Background Urolithiasis is a prevalent urological ailment characterized by increasing prevalence and recurrence rates, resulting in substantial social and economic burden. While men exhibit an incidence rate nearly twice that of women, this gender disparity is gradually diminishing. Nevertheless, the mechanisms underlying this condition remain incompletely elucidated. The identification of the urinary microbiome (urobiome) has provided a fresh perspective on urolithiasis. This study aimed to analyze the urobiome of unilateral stone formers in the renal pelvis and evaluate the variations in microbial diversity and community composition between males and females. Methods Renal pelvis urine samples were obtained from a cohort of 21 male and 9 female patients and subsequently subjected to taxonomic and functional analysis using 2bRAD sequencing for Microbiome (2bRAD-M). The collected samples were categorized into four distinct groups, namely the stone side of males (SM), stone side of females (SF), non-stone side of males (NSM), and non-stone side of females (NSF). Results Through the application of beta diversity analysis, dissimilarity was observed between NSM and NSF. Additionally, NSF exhibited a higher abundance of microbial populations, and a total of 29 distinct species were identified as differentially present between NSM and NSF using LEfSe. Lactobacillus iners, Atopobium deltae, Lawsonella clevelandensis, and Meyerozyma guilliermondii exhibited enrichment in the SF group compared to the SM group. Furthermore, we identified distinct species that differed between the SM and NSM groups, as well as the SF and NSF groups. Besides, we conducted COG annotation and KEGG pathway predictions, revealing significant differences in urobiome function across the different groups. Conclusion Variations in microbial community composition and predicted functions were observed among the various groups. Future research could potentially leverage the urobiome to personalize urolithiasis treatment based on individual microbial characteristics, taking into account gender-specific differences.

Our study aimed to apply a proteomic approach to investigate the molecular mechanisms underlying the effects of oxalate on rat renal tubular epithelial cells. NRK-52E cells were treated with or without oxalate and subjected to quantitative proteomics to identify key proteins and key pathological changes under high oxalate stimulation. A total of 268 differentially expressed proteins (DEPs) between oxalate-treated and control groups were identified, with 132 up-regulated and 136 down-regulated proteins. Functional enrichment analysis revealed that DEPs are associated with oxidative stress, apoptosis, ferroptosis, pro-inflammatory cytokines, vitamin D, and biomineralization. SPP1, MFGE8, ANKS1A, and NAP1L1 were up-regulated in the oxalate-treated cells and the hyperoxaluric stone-forming rats, while SUB1, RNPS1, and DGLUCY were down-regulated in both cases. This altered proteomic landscape sheds light on the pathological processes involved in oxalate-induced renal damage and identifies potential biomarkers and therapeutic targets to mitigate the effects of hyperoxaluria and reduce the risk of CaOx stone formation.

Our study aimed to elucidate the mechanisms behind the interaction between calcium oxalate (CaOx) crystals and renal tubular epithelial cells through transcriptome sequencing analysis. HK-2 cells were stimulated with or without CaOx monohydrate crystals and subjected to RNA-seq to assess the effects of CaOx crystals on gene expression changes, key pathways, and molecular players during this interaction. A total of 629 differentially expressed genes (DEGs) were identified between the control group and experimental group, with 491 genes up-regulated and 138 down-regulated. Functional enrichment analysis indicated that the DEGs were significantly associated with endoplasmic reticulum stress (ERS) and unfolded protein response. To validate our findings, we compared our results with the public dataset GSE73680 and confirmed the increased expression of two ERS-related DEGs, CHAC1 and FGF21, in renal papillary tissues from patients with CaOx stones. Collectively, these findings suggest that ERS plays a crucial role in the crystal–cell interaction and highlight the potential for developing therapeutic strategies aimed at reducing CaOx stone formation by targeting ERS-related molecules and pathways.

This review discusses recent advances in robotic surgery for urologic tumors, focusing on three key areas: robotic systems, assistive technologies, and artificial intelligence. The Da Vinci SP system has enhanced the minimally invasive nature of robotic surgeries, while the Senhance system offers advantages such as tactile feedback and eye-tracking capabilities. Technologies like 3D reconstruction combined with augmented reality and fluorescence imaging aid surgeons in precisely identifying the anatomical relationships between tumors and surrounding structures, improving surgical efficiency and outcomes. Additionally, the development of artificial intelligence lays the groundwork for automated robotics. As these technologies continue to evolve, we are entering an era of minimally invasive, precise, and intelligent robotic surgery.

Abstract Background The pathogenesis of kidney stone disease (KSD) is not fully understood, and potential contributing factors remain to be explored. Several studies have revealed that the urinary microbiome (urobiome) of stone formers was distinct from that of healthy individuals using 16S rRNA gene sequencing, most of which only provided microbial identification at the genus level. 2bRAD sequencing for Microbiome (2bRAD-M) is a novel sequencing technique that enables accurate characterization of the low-biomass microbiome at the species resolution. We aimed to apply 2bRAD-M to profile the renal pelvis urobiome of unilateral kidney stone patients and compared the urobiome with and without stone(s). Method A total of 30 patients with unilateral stones were recruited, and their renal pelvis urine from both sides was collected. A ureteroscope was inserted into the renal pelvis with stone(s) and a ureteral catheter was placed into the ureteroscope to collect renal pelvis urine. This procedure was repeated again with new devices to collect the urine of the other side. 2bRAD-M was performed to characterize the renal pelvis urobiome of unilateral stone formers to explore whether microbial differences existed between the stone side and the non-stone side. Results The microbial community composition of the stone side was similar to that of the non-stone side. Paired comparison showed that Corynebacterium was increased and Prevotella and Lactobacillus were decreased in the stone side. Four species (Prevotella bivia, Lactobacillus iners, Corynebacterium aurimucosum, and Pseudomonas sp_286) were overrepresented in the non-stone side. 24 differential taxa were also identified between two groups by linear discriminant analysis effect size (LEfSe). Extensive and close connections among genera and species were observed in the correlation analysis. Moreover, a random forest classifier was constructed using specific enriched species, which can distinguish the stone side from the non-stone side with an accuracy of 71.2%. Conclusion This first 2bRAD-M microbiome survey gave an important hint towards the potential role of urinary dysbiosis in KSD and provided a better understanding of mechanism of stone formation.

BackgroundThe pathogenesis of urolithiasis remains unclear, making the development of medications for treatment and prevention stagnant. Randall’s plaques (RPs) begin as interstitial calcium phosphate crystal deposits, grow outward and breach the renal papillary surface, acting as attachment for CaOx stones. Since matrix metalloproteinases (MMPs) can degrade all components of extracellular matrix (ECM), they might participate in the breach of RPs. Besides, MMPs can modulate the immune response and inflammation, which were confirmed to be involved in urolithiasis. We aimed to investigate the role of MMPs in the development of RPs and stone formation.MethodsThe public dataset GSE73680 was mined to identify differentially expressed MMPs (DEMMPs) between normal tissues and RPs. WGCNA and three machine learning algorithms were performed to screen the hub DEMMPs. In vitro experiments were conducted for validation. Afterwards, RPs samples were classified into clusters based on the hub DEMMPs expression. Differentially expressed genes (DEGs) between clusters were identified and functional enrichment analysis and GSEA were applied to explore the biological role of DEGs. Moreover, the immune infiltration levels between clusters were evaluated by CIBERSORT and ssGSEA.ResultsFive DEMMPs, including MMP1, MMP3, MMP9, MMP10, and MMP12, were identified between normal tissues and RPs, and all of them were elevated in RPs. Based on WGCNA and three machine learning algorithms, all of five DEMMPs were regarded as hub DEMMPs. In vitro validation found the expression of hub DEMMPs also increased in renal tubular epithelial cells under lithogenic environment. RPs samples were divided into two clusters and cluster A exhibited higher expression of hub DEMMPs compared to cluster B. Functional enrichment analysis and GSEA found DEGs were enriched in immune-related functions and pathways. Moreover, increased infiltration of M1 macrophages and enhanced levels of inflammation were observed in cluster A by immune infiltration analysis.ConclusionWe assumed that MMPs might participate in RPs and stone formation through ECM degradation and macrophages-mediated immune response and inflammation. Our findings offer a novel perspective on the role of MMPs in immunity and urolithiasis for the first time, and provide potential biomarkers to develop targets for treatment and prevention.

Abstract Background Kidney stone disease (KSD) is a multifactorial disease involving both environmental and genetic factors, whose pathogenesis remains unclear. This study aims to explore the hub genes related to stone formation that could serve as potential therapeutic targets. Methods Based on the GSE73680 dataset with 62 samples, differentially expressed genes (DEGs) between Randall’s plaque (RP) tissues and normal tissues were screened and weighted gene co-expression network analysis (WGCNA) was applied to identify key modules associated with KSD. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed to explore the biological functions. The protein–protein interaction (PPI) network was constructed to identify hub genes. Meanwhile, CIBERSORT and ssGSEA analysis were used to estimate the infiltration level of the immune cells. The correlations between hub genes and immune infiltration levels were also investigated. Finally, the top hub gene was selected for further GSEA analysis. Results A total of 116 DEGs, including 73 up-regulated and 43 down-regulated genes, were screened in the dataset. The red module was identified as the key module correlated with KSD. 53 genes were obtained for functional enrichment analysis by taking the intersection of DEGs and genes in the red module. GO analysis showed that these genes were mainly involved in extracellular matrix organization (ECM) and extracellular structure organization, and others. KEGG analysis revealed that the pathways of aldosterone-regulated sodium reabsorption, cell adhesion molecules, arachidonic acid (AA) metabolism, and ECM-receptor interaction were enriched. Through PPI network construction, 30 hub genes were identified. CIBERSORT analysis revealed a significantly increased proportion of M0 macrophages, while ssGSEA revealed no significant differences. Among these hub genes, SPP1, LCN2, MMP7, MUC1, SCNN1A, CLU, SLP1, LAMC2, and CYSLTR2 were positively correlated with macrophages infiltration. GSEA analysis found that positive regulation of JNK activity was enriched in RP tissues with high SPP1 expression, while negative regulation of IL-1β production was enriched in the low-SPP1 subgroup. Conclusions There are 30 hub genes associated with KSD, among which SPP1 is the top hub gene with the most extensive links with other hub genes. SPP1 might play a pivotal role in the pathogenesis of KSD, which is expected to become a potential therapeutic target, while its interaction with macrophages in KSD needs further investigation.

Urolithiasis is a common urological disease with increasing incidence and a high recurrence rate, whose etiology is not fully understood. The application of sequencing and culturomics has revealed that urolithiasis is closely related to the urinary microbiome (urobiome), shedding new light on the pathogenesis of stone formation. In this study, we recruited 30 patients with unilateral stones and collected their renal pelvis urine from both sides. Then, we performed 2bRAD-M, a novel sequencing technique that provides precise microbial identification at the species level, to characterize the renal pelvis urobiome of unilateral stone formers in the both sides. We first found that the urobiome in the stone side could be divided into two clusters (Stone1 and Stone2) based on distance algorithms. Stone2 harbored higher microbial richness and diversity compared to Stone1. The genera Cupriavidus and Sphingomonas were overrepresented in Stone1, whereas Acinetobacter and Pseudomonas were overrepresented in Stone2. Meanwhile, differential species were identified between Stone1 and Stone2. We further constructed a random forest model to discriminate two clusters which achieved a powerful diagnostic potential. Moreover, the urobiome of the non-stone side (Control1/2) was compared with that of the stone side (Stone1/2). Stone1 and Control1 showed different microbial community distributions, while Stone2 was similar to Control2 based on diversity analysis. We also identified differentially abundant species among all groups. We assumed that there might be different mechanisms of how microbiota contribute to stone formation in two clusters. Our findings might assist in the selection of suitable medical treatments for urolithiasis.

Background: The incidence rate and mortality of bladder cancer are increasing year by year. Interestingly, the commonly used metabolic regulatory drug metformin has been reported to have anti-tumor effect in recent years. Nevertheless, it keeps unclear whether the usage of metformin is beneficial or unbeneficial in treating bladder cancer. Thus, a meta-analysis was conducted to explore the long-term effect of metformin on the incidence of bladder cancer and OS, PFS, DSS and RFS in bladder cancer patients with T2DM.Method: We aim to collect evidence of the association between the usage of metformin and the incidence and treatment outcome of bladder cancer. We searched PubMed, Embase, Ovid Medline and Cochrane Library up to February 2021 to get effective literature reporting the effects of metformin in bladder cancer. The main outcomes were the protective effects of metformin on the incidence, overall survival (OS), recurrence-free survival (RFS), progression-free survival (PFS), and disease-specific survival (DSS) of bladder cancer. And OR (odds ratio) and HR (hazard ratio) with their 95%CI were pooled. Two independent researchers assessed the quality of included studies using the Newcastle-Ottawa Scale (NOS).Results: We involved 12 studies meeting the inclusion criteria, including a total of 1,552,773 patients. The meta-analysis showed that use of metformin could decrease the incidence (OR = 0.45, 95%CI = 0.37–0.56; p < 0.01) and prolong recurrence-free-survival (HR = 0.56, 95%CI = 0.41–0.76; p = 0.91) of bladder cancer. However, there were no significant protective effects in the overall survival (HR = 0.93, 95%CI = 0.67–1.28, p = 0.05), disease-specific-survival (HR = 0.73, 95%CI = 0.47–1.16; p = 0.01), and progression-free-survival (HR = 0.78, 95%CI = 0.53–1.15, p = 0.34).Conclusion: The results revealed that the usage of metformin could reduce the incidence of bladder cancer and prolong the prognosis of bladder cancer in T2DM patients, respectively. More prospective studies are needed to prove the protective role of metformin on bladder cancer.

Background and AimsUrolithiasis is characterized by high rates of prevalence and recurrence. Hyperuricemia is related to various diseases. We hope to determine the association between serum uric acid (UA) level and kidney stone (KS).MethodsIn this population-based cross-sectional study, a total of 82,017 Chinese individuals who underwent a comprehensive examination in 2017 were included. The KS was diagnosed based on ultrasonography examination outcomes. Fully adjusted odds ratio (OR) for KS, and mean difference between the two groups were applied to determine the association of UA level with KS.ResultsAmong the 82,017 participants included in this study (aged 18~99 years), 9,435 participants (11.5%) are diagnosed with KS. A proportion of 56.3% of individuals is male. The mean UA level of overall participants is 341.77 μmol/L. The participants with KS report higher UA level than the participants without KS [mean UA level 369.91 vs. 338.11 μmol/L; mean difference (MD), 31.96 (95% CI, 29.61~34.28) μmol/L]. In men, the OR for KS significantly increases from 330 μmol/L UA level. Every 50 μmol/L elevation of UA level increases the risk of KS formation by about 10.7% above the UA level of 330 μmol/L in men. The subgroup analysis for male is consistent with the overall result except for the participants presenting underweight [adjusted OR, 1.035 (0.875~1.217); MD, −5.57 (−16.45~11.37)], low cholesterol [adjusted OR, 1.088 (0.938~1.261); MD, 8.18 (−7.93~24.68)] or high estimated glomerular filtration rate (eGFR) [adjusted OR, 1.044 (0.983~1.108); MD, 5.61 (−1.84~13.36)]. However, no significant association is observed in women between UA and KS either in all female participants or in female subgroups.ConclusionAmong Chinese adults, UA level is associated with KS in a dose-response manner in men but not in women. However, the association becomes considerably weak in male participants with malnutrition status.