Basal metabolic rate and the risk of urolithiasis: a two-sample Mendelian randomization study.

OBJECTIVE: Few studies have investigated the impact of basal metabolic rate (BMR) on the development of urolithiasis, and the causal relationship is yet to be established. In this study, a two-sample Mendelian randomization (MR) analysis was utilized to identify the causal relationship between BMR and risk of urolithiasis. METHOD: Genetic instruments for BMR were drawn from a public genome-wide association study (GWAS). Summary dates on BMR and urolithiasis were obtained from a GWAS meta-analysis with sample sizes of 454,874 and 212,453, respectively. The inverse-variance weighted (IVW) method was provided as the main approach to estimate the causal relationship. The weighted-median method and the MR-Egger method were used as supplements to the IVW method. In addition, we conducted sensitivity analyses, including heterogeneity tests, pleiotropy tests and leave-one-out analysis, to assess the robustness of the outcomes. Furthermore, the funnel plot asymmetry was visually inspected to evaluate possible bias. RESULTS: The inverse-variance weighted data revealed that genetically predicted BMR significantly decreased the risk of urolithiasis [beta coefficient (beta): - 0.2366, odds ratio (OR): 0.7893, 95% confidence interval (CI) 0.6504-0.9579, p = 0.0166]. CONCLUSIONS: BMR has causal effects on urolithiasis in an MR study, and the risk of urolithiasis in patients with lower levels of BMR is higher.

The Association between Dietary Sugar Intake and Nephrolithiasis: Results from National Health and Nutrition Examination Survey 2007-2018.

BACKGROUND: Dietary sugar intake is gradually considered a risk factor for many diseases. A sugary diet was positively associated with risk of nephrolithiasis, but the specific relationships remain undefined. OBJECTIVES: To determine associations between risk of nephrolithiasis and dietary sugar intake. METHODS: This cross-sectional study involved 21,590 participants based on the National Health and Nutrition Examination Survey from 2007 to 2018. Amounts of dietary sugar intake (g/d) were the main exposure, including total sugar intake, added sugar intake, and food sources. Associations were analyzed by logistic regression models and restricted cubic splines using complex weighted designs. RESULTS: Weighted mean intake [standard error] of total sugar and added sugar were 111.2 [2.0] g/d and 73.7 [1.9] g/d in participants with nephrolithiasis, respectively. In the fully adjusted regression model, compared to those in quartile 1, the population in quartile 4 of total sugar intake showed a significant risk of nephrolithiasis [odds ratio (OR): 1.23; 95% confidence interval (CI): 1.00-1.51]; OR for added sugar intake was 1.56 (95% CI: 1.25-1.94). The risks of nephrolithiasis increased steadily when total sugar and added sugar intake exceeded ∼150 g/d and 63 g/d in restricted cubic spline analyses, respectively. The highest sugar intake from beverages was associated with an increased risk of nephrolithiasis (OR for total sugar: 1.36; 95% CI: 1.07-1.72; OR for added sugar: 1.37; 95% CI: 1.09-1.73). Added sugar intake from meat, egg, and oil was significantly associated with risk of nephrolithiasis (quartile 4, OR: 1.22; 95% CI: 1.02-1.47), whereas total sugar intake from dairy products was in reverse (quartile 4, OR: 0.67; 95% CI: 0.54-0.82). CONCLUSIONS: Total and added sugar intake, sugar intake from beverages, and added sugar intake from meat, egg, and oil were associated with an increased risk of nephrolithiasis, whereas total sugar intake from dairy products was negatively associated.

METTL3-dependent m6A modification mediates bladder remodeling after partial bladder outlet obstruction through CCN2 activation.

AIMS: N6-methyladenosine (m6A) modification is a critical posttranscriptional event in gene regulation. Thus, identifying methyltransferase, demethylase, or m6A binding protein-mediated m6A modifications in cancer or noncancer transcriptomes has become a promising novel strategy for disease therapy development. However, novel insights into m6A modification in partial bladder outlet obstruction (pBOO) and detailed information about the drivers of bladder remodeling remain to be elucidated. Here, we first characterized the m6A modification landscape in pBOO and investigated potential actionable pharmaceutical targets for future therapies. METHODS: We generated an improved animal model of pBOO in SD rats with urethral meatus stricture induced by suturing. Urodynamic investigations and cystometry were carried out to evaluate the physiologic changes elicited by pBOO. Whole-transcriptome sequencing (RNA-seq) and m6A-modified RNA immunoprecipitation sequencing (MeRIP-seq) were subsequently performed to analyze the expression pattern associated with bladder remodeling in pBOO. RESULTS: The cystometric evaluation of bladder function demonstrated obvious increases in pressure-related parameters in the pBOO group. Hematoxylin and eosin staining and Masson's trichrome staining validated the occurrence of bladder remodeling. A global elevation in m6A RNA methylation levels was observed in parallel to a increased expression of METTL3 in the pBOO group. High-throughput sequencing revealed the differences in expression patterns between the pBOO and sham-operated groups. Furthermore, potential m6A-modified genes, including CCN2, may serve as new pharmaceutical targets to reverse bladder remodeling. CONCLUSIONS: Exploring the roles of m6A-modified genes identified as associated with bladder remodeling by integrating RNA-seq and MeRIP-seq data can offer new insights for developing promising treatments for pBOO patients.

Associations between overactive bladder and sleep patterns: a cross-sectional study based on 2007-2014 NHANES.

OBJECTIVES: To determine whether relationship exists between overactive bladder (OAB) and sleep patterns through the cross-sectional study. PATIENTS AND METHODS: Patients from the National Health and Nutrition Examination Survey (NHANES) 2007-2014 were included in this study. Data were extracted through questionnaires, including demographics, dietary and health-related behaviors, body measurements and disease information. Three sleep factors were included to aggregate overall sleep scores, ranging from 0 to 3. A sleep score of 0 to 1, 2 or 3 was expressed as a bad, intermediate or healthy sleep pattern, respectively. The Overactive Bladder Symptom Score (OABSS) scale was applied to quantify the severity of OAB for each participant. Weighted logistic regression models were used to investigate the associations between sleep and OAB. RESULTS: A total of 16,978 participants were enrolled in this study. The relationship between OAB and sleep patterns was statistically significant. After fully adjusting for confounding factors, the OAB risk of patients with intermediate and poor sleep patterns obviously increased by 26% and 38%, respectively, and mild (OR = 1.21, 95% CI [1.03,1.42]), moderate (OR = 1.45, 95% CI [1.27,1.66]) and severe (OR = 1.57, 95% CI [1.18,2.09]) OAB were significantly associated with sleep pattern grouping. The prevalence of OAB is significantly higher in patients with bad sleep patterns, and vice versa. CONCLUSION: This study indicated that there is a positive relationship between OAB and worse sleep-related issues.

Multi-Source Soil Moisture Data Fusion Based on Spherical Cap Harmonic Analysis and Helmert Variance Component Estimation in the Western U.S.

Soil moisture (SM) is a vital climate variable in the interaction process between the Earth's atmosphere and land. However, global soil moisture products from various satellite missions and land surface models are affected by inherently discontinuous observations and coarse spatial resolution, which limits their application at fine spatial scales. To address this problem, this paper integrates three diverse types of datasets from in situ, satellites, and models through Spherical cap harmonic analysis (SCHA) and Helmert variance component estimation (HVCE) to produce 1 km of spatio-temporally continuous SM products with high accuracy. First, this paper eliminates the bias between different datasets and in situ sites and resamples the datasets before data fusion. Then, multi-source SM data fusion is performed based on the SCHA and HVCE methods. Finally, this paper evaluates the fused products from three aspects, including the performance of representative sites under different climate types, the overall performance of validation sites, and the comparison with other products. The results show that the fused products have better performance than other SM products. In the representative sites, the minimal correlation coefficient (R) of the fused products is above 0.85, and the largest root mean square error (RMSE) is below 0.040 m3 m-3. For all validation sites, the R and RMSE of the fused products are 0.889 and 0.036 m3 m-3, respectively, while the R for other products is below 0.75 and the RMSE is above 0.06 m3 m-3. In comparison to other SM products, the fused products exhibit superior performance, generally align more closely with in situ measurements, and possess the ability to accurately and finely capture the spatial and temporal variability of surface SM.

A Dual-Threshold Algorithm for Ice-Covered Lake Water Level Retrieval Using Sentinel-3 SAR Altimetry Waveforms.

Satellite altimetry has been proven to measure water levels in lakes and rivers effectively. The Sentinel-3A satellite is equipped with a dual-frequency synthetic aperture radar altimeter (SRAL), which allows for inland water levels to be measured with higher precision and improved spatial resolution. However, in regions at middle and high latitudes, where many lakes are covered by ice during the winter, the non-uniformity of the altimeter footprint can substantially impact the accuracy of water level estimates, resulting in abnormal readings when applying standard SRAL synthetic aperture radar (SAR) waveform retracking algorithms (retrackers). In this study, a modified method is proposed to determine the current surface type of lakes, analyzing changes in backscattering coefficients and brightness temperature. This method aligns with ground station observations and ensures consistent surface type classification. Additionally, a dual-threshold algorithm that addresses the limitations of the original bimodal algorithm by identifying multiple peaks without needing elevation correction is introduced. This innovative approach significantly enhances the precision of equivalent water level measurements for ice-covered lakes. The study retrieves and compares the water level data of nine North American lakes covered by ice from 2016-2019 using the dual-threshold and the SAMOSA-3 algorithm with in situ data. For Lake Athabasca, Cedar Lake, Great Slave Lake, Lake Winnipeg, and Lake Erie, the root mean square error (RMSE) of SAMOSA-3 is 39.58 cm, 46.18 cm, 45.75 cm, 42.64 cm, and 6.89 cm, respectively. However, the dual-threshold algorithm achieves an RMSE of 6.75 cm, 9.47 cm, 5.90 cm, 7.67 cm, and 5.01 cm, respectively, representing a decrease of 75%, 79%, 87%, 82%, and 27%, respectively, compared to SAMOSA-3. The dual-threshold algorithm can accurately estimate water levels in ice-covered lakes during winter. It offers a promising prospect for achieving long-term, continuous, and high-precision water level measurements for middle- and high-latitude lakes.

An Interferometric Synthetic Aperture Radar Tropospheric Delay Correction Method Based on a Global Navigation Satellite System and a Backpropagation Neural Network: More Suitable for Areas with Obvious Terrain Changes.

Atmospheric delay correction remains a major challenge for interferometric synthetic aperture radar (InSAR) technology. In this paper, we first reviewed several commonly used methods for tropospheric delay correction in InSAR. Subsequently, considering the large volume and high temporal resolution of global navigation satellite system (GNSS) station measurement data, we proposed a method for spatial prediction of the InSAR tropospheric delay phase based on the backpropagation (BP) neural network and GNSS zenith total delay (ZTD). Using 42 Sentinel-1 interferograms over the Los Angeles area in 2021 as an example, we validated the accuracy of the BP + GNSS method in spatially predicting ZTD and compared the correction effects of BP + GNSS and five other methods on interferograms using the standard deviation (StaD) and structural similarity (SSIM). The results demonstrated that the BP + GNSS method reduced the root-mean-square error (RMSE) in spatial prediction by approximately 95.50% compared to the conventional interpolation method. After correction using the BP + GNSS method, StaD decreased in 92.86% of interferograms, with an average decrease of 52.03%, indicating significantly better correction effects than other methods. The SSIM of the BP + GNSS method was lower in mountainous and high-altitude areas with obvious terrain changes in the east and north, exhibiting excellent and stable correction performance in different seasons, particularly outperforming the GACOS method in autumn and winter. The BP + GNSS method can be employed to generate InSAR tropospheric delay maps with high temporal and spatial resolution, effectively addressing the challenge of removing InSAR tropospheric delay signals in areas with significant terrain variations.

A 7-gene signature predicts the prognosis of patients with bladder cancer.

The biomarkers have an important guiding role in prognosis and treatment of patients with bladder cancer (BC). The aim of the present study was to identify and evaluate a prognostic gene signature in BC patients. The gene expression profiles of BC samples and the corresponding clinicopathological data were downloaded from GEO and TCGA. The differentially expressed genes (DEGs) were identified by R software. Univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) Cox regression were applied to construct the prognostic score model. A nomogram was established with the identified prognostic factors to predict the overall survival rates of BC patients. The discriminatory and predictive capacity of the nomogram was evaluated based on the concordance index (C-index), calibration curves and decision curve analysis (DCA). A 7-gene signature (KLRB1, PLAC9, SETBP1, NR2F1, GRHL2, ANXA1 and APOL1) was identified from 285 DEGs by univariate and LASSO Cox regression analyses. Univariate and multivariate Cox regression analyses showed that age, lymphovascular invasion, lymphatic metastasis, metastasis and the 7-gene signature risk score was an independent predictor of BC patient prognosis. A nomogram that integrated these independent prognostic factors was constructed. The C-index (0.73, CI 95%, 0.693-0.767) and calibration curve demonstrated the good performance of the nomogram. DCA of the nomogram further showed that this model exhibited good net benefit. The combined 7-gene signature could serve as a biomarker for predicting BC prognosis. The nomogram built by risk score and other clinical factors could be an effective tool for predicting the prognosis of patients with BC.

A novel autophagy-related long non-coding RNAs prognostic risk score for clear cell renal cell carcinoma.

BACKGROUND: As the main histological subtype of renal cell carcinoma, clear cell renal cell carcinoma (ccRCC) places a heavy burden on health worldwide. Autophagy-related long non-coding RNAs (ARlncRs) have shown tremendous potential as prognostic signatures in several studies, but the relationship between them and ccRCC still has to be demonstrated. METHODS: The RNA-sequencing and clinical characteristics of 483 ccRCC patients were downloaded download from the Cancer Genome Atlas and International Cancer Genome Consortium. ARlncRs were determined by Pearson correlation analysis. Univariate and multivariate Cox regression analyses were applied to establish a risk score model. A nomogram was constructed considering independent prognostic factors. The Harrell concordance index calibration curve and the receiver operating characteristic analysis were utilized to evaluate the nomogram. Furthermore, functional enrichment analysis was used for differentially expressed genes between the two groups of high- and low-risk scores. RESULTS: A total of 9 SARlncRs were established as a risk score model. The Kaplan-Meier survival curve, principal component analysis, and subgroup analysis showed that low overall survival of patients was associated with high-risk scores. Age, M stage, and risk score were identified as independent prognostic factors to establish a nomogram, whose concordance index in the training cohort, internal validation, and external ICGC cohort was 0.793, 0.671, and 0.668 respectively. The area under the curve for 5-year OS prediction in the training cohort, internal validation, and external ICGC cohort was 0.840, 0.706, and 0.708, respectively. GO analysis and KEGG analysis of DEGs demonstrated that immune- and inflammatory-related pathways are likely to be critically involved in the progress of ccRCC. CONCLUSIONS: We established and validated a novel ARlncRs prognostic risk model which is valuable as a potential therapeutic target and prognosis indicator for ccRCC. A nomogram including the risk model is a promising clinical tool for outcomes prediction of ccRCC patients and further formulation of individualized strategy.

A novel molecular subtypes and risk model based on inflammatory response-related lncrnas for bladder cancer.

BACKGROUND: Inflammation and long noncoding RNAs (lncRNAs) are gradually becoming important in the development of bladder cancer (BC). Nevertheless, the potential of inflammatory response-related lncRNAs (IRRlncRNAs) as a prognostic signature remains unexplored in BC. METHODS: The Cancer Genome Atlas (TCGA) provided RNA expression profiles and clinical information of BC samples, and GSEA Molecular Signatures database provided 1171 inflammation-related genes. IRRlncRNAs were identified using Pearson correlation analysis. After that, consensus clustering was performed to form molecular subtypes. After performing least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses, a risk model constructed based on the prognostic IRRlncRNAs was validated in an independent cohort. Kaplan-Meier (KM) analysis, univariate and multivariate Cox regression, clinical stratification analysis, and time-dependent receiver operating characteristic (ROC) curves were utilized to assess clinical effectiveness and accuracy of the risk model. In clusters and risk model, functional enrichment was investigated using GSEA and GSVA, and immune cell infiltration analysis was demonstrated by ESTIMATE and CIBERSORT analysis. RESULTS: A total of 174 prognostic IRRlncRNAs were confirmed, and 406 samples were divided into 2 clusters, with cluster 2 having a significantly inferior prognosis. Moreover, cluster 2 exhibited a higher ESTIMATE score, immune infiltration, and PD-L1 expression, with close relationships with the inflammatory response. Further, 12 IRRlncRNAs were identified and applied to construct the risk model and divide BC samples into low-risk and high-risk groups successfully. KM, ROC, and clinical stratification analysis demonstrated that the risk model performed well in predicting prognosis. The risk score was identified as an independently significant indicator, enriched in immune, cell cycle, and apoptosis-related pathways, and correlated with 9 immune cells. CONCLUSION: We developed an inflammatory response-related subtypes and steady prognostic risk model based on 12 IRRlncRNAs, which was valuable for individual prognostic prediction and stratification and outfitted new insight into inflammatory response in BC.

Evaluating the Performance of Seven Ongoing Satellite Altimetry Missions for Measuring Inland Water Levels of the Great Lakes.

Satellite altimetry can provide long-term water level time series for water bodies lacking hydrological stations. Few studies have evaluated the performance of HY-2C and Sentinel-6 satellites in inland water bodies, as they have operated for less than 1 and 2 years, respectively. This study evaluated the measured water level accuracy of CryoSat-2, HY-2B, HY-2C, ICESat-2, Jason-3, Sentinel-3A, and Sentinel-6 in the Great Lakes by in-situ data of 12 hydrological stations from 1 January 2021 to 1 April 2022. Jason-3 and Sentinel-6 have the lowest mean root-mean-square-error (RMSE) of measured water level, which is 0.07 m. The measured water level of Sentinel-6 satellite shows a high correlation at all passing stations, and the average value of all correlation coefficients (R) is also the highest among all satellites, reaching 0.94. The mean RMSE of ICESat-2 satellite is slightly lower than Jason-3 and Sentinel-6, which is 0.09 m. The stability of the average deviation (bias) of the ICESat-2 is the best, with the maximum bias only 0.07 m larger than the minimum bias. ICESat-2 satellite has an exceptionally high spatial resolution. It is the only satellite among the seven satellites that has retrieved water levels around twelve stations. HY-2C satellite has the highest temporal resolution, with a temporal resolution of 7.5 days at station 9075014 in Huron Lake and an average of 10 days in the Great Lakes region. The results show that the seven altimetry satellites currently in operation have their own advantages and disadvantages, Jason-3 and Sentinel-6 have the highest accuracy, ICESat-2 has higher accuracy and the highest spatial resolution, and HY-2C has the highest temporal resolution, although it is less accurate. In summary, with full consideration of accuracy and space-time resolution, the ICESat-2 satellite can be used as the benchmark to achieve the unification of multi-source data and establish water level time series.

The tumour microenvironment and metabolism in renal cell carcinoma targeted or immune therapy.

Renal cell carcinoma (RCC) is one of the most common tumours of the urinary system, and is insidious and not susceptible to chemoradiotherapy. As the most common subtype of RCC (70-80% of cases), clear cell renal cell carcinoma (ccRCC) is characterized by the loss of von Hippel-Lindau and the accumulation of robust lipid and glycogen. For advanced RCC, molecular-targeted drugs, tyrosine kinase inhibitors (TKIs) and the immune checkpoint inhibitors (ICIs) have been increasingly recommended and investigated. Due to the existence of a highly dynamic, adaptive and heterogeneous tumour microenvironment (TME), and due to the glucose and lipid metabolism in RCC, this cancer may be accompanied by various types of resistance to TKIs and ICIs. With the increased production of lactate, nitric oxide, and other new by-products of metabolism, novel findings of the TME and key metabolic enzymes drived by HIF and other factors have been increasingly clarified in RCC carcinogenesis and therapy. However, there are few summaries of the TME and tumour metabolism for RCC progression and therapy. Here, we summarize and discuss the relationship of the important implicated characteristics of the TME as well as metabolic molecules and RCC carcinogenesis to provide prospects for future treatment strategies to overcome TME-related resistance in RCC.

53 years old is a reasonable cut-off value to define young and old patients in clear cell renal cell carcinoma: a study based on TCGA and SEER database.

BACKGROUND: The objectives of this study were to screen out cut-off age value and age-related differentially expressed genes (DEGs) in clear cell renal cell carcinoma (CCRCC) from Surveillance Epidemiology and End Results (SEER) database and The Cancer Genome Atlas (TCGA) database. METHODS: We selected 45,974 CCRCC patients from SEER and 530 RNA-seq data from TCGA database. The age cut-off value was defined using the X-tile program. Propensity score matching (PSM) was used to balance the differences between young and old groups. Hazard ratio (HR) was applied to evaluate prognostic risk of age in different subgroups. Age-related DEGs were identified via RNA-seq data. Survival analysis was used to assess the relationship between DEGs and prognosis. RESULTS: In this study, we divided the patients into young (n = 14,276) and old (n = 31,698) subgroups according to cut-off value (age = 53). Age > 53 years was indicated as independent risk factor for overall survival (OS) and cancer specific survival (CSS) of CCRCC before and after PSM. The prognosis of old group was worse than that in young group. Eleven gene were differential expression between the younger and older groups in CCRCC. The expression levels of PLA2G2A and SIX2 were related to prognosis of the elderly. CONCLUSION: Fifty-three years old was cut-off value in CCRCC. The prognosis of the elderly was worse than young people. It remind clinicians that more attention and better treatment should be given to CCRCC patients who are over 53 years old. PLA2G2A and SIX2 were age-related differential genes which might play an important role in the poor prognosis of elderly CCRCC patients.

Serum Neuroendocrine Markers Predict Therapy Outcome of Patients with Metastatic Castration-Resistant Prostate Cancer: A Meta-Analysis.

PURPOSE: To evaluate whether serum neuroendocrine markers could effectively predict treatment outcomes in patients with metastatic castration-resistant prostate cancer (mCRPC). METHODS: The PubMed, Cochrane Library and Embase databases were sought to identify eligible studies concerning serum neuroendocrine markers and the prognosis of post-treatment mCRPC from inception to April 2018. The association between serum neuroendocrine markers, that is, chromogranin A (CgA) and neurone-specific enolase (NSE), levels and the prognosis of post-treatment mCRPC were summarized using a random-effects model and hazard ratio (HR) with 95% CI Sensitivity analyses were conducted to assess potential bias. RESULTS: A total of 234 participants are included in this meta-analysis (mean age = 71.3 years) from 6 studies. The pooled results show that higher markers' levels at baseline in patients were associated with unfavorable overall survival (OS; univariate analysis: HR 3.775, 95% CI 1.469-9.698, p = 0.006; multivariate analysis: HR 3.838, 95% CI 1.774-8.304, p = 0.001), and a similar situation was observed in progression-free survival (PFS; univariate analysis: HR 2.785, 95% CI 1.315-5.898, p = 0.007; multivariate analysis: HR 1.266, 95% CI 1.017-1.577, p = 0.035). Estimates of the total effects were generally consistent in the sensitivity analysis. Publication bias was observed when performing the univariate analysis of PFS, and we have the explanation accordingly. CONCLUSIONS: The results of this pooled analysis confirm serum neuroendocrine markers could be the effective predictor of treatment outcome in patients with mCRPC. In addition, a combination of CgA and NSE is more valuable to predict worse OS. Further randomized case-control trials are required to validate this relationship.

Endourologic strategies for a minimally invasive management of urinary tract stones in patients with urinary diversion.

OBJECTIVE: To present our experience in minimally invasive management of urinary tract stones in patients with urinary diversion. MATERIALS AND METHODS: We retrospectively reviewed 26 patients with urinary tract stones after cystectomy and urinary diversion. The types of urinary diversion were ileal conduit, colon conduit, ileal orthotopic neobladder in 19, 4, and 3 patients, respectively. At postoperative days 2, a plain KUB and urinary ultrasonography were performed in order to assess stone fragmentation or hydronephrosis. According to postoperative imaging, stone free rate (SFR) was defined as complete absence of fragments or residual stones less than 4mm. RESULTS: 19 patients were treated with minimally invasive percutaneous lithotripsy (MPCNL) and 2 patients required second-look MPCNL. Anterograde flexible ureteroscopy was performed in 2 patients, while in 2 patients a combined anterograde and retrograde approach was required. Three reservoir stones were treated by transurethral neo-bladder lithotripsy. Postoperative significant complications occurred in 2 patients (7.7%). The highest percentage of stone composition was struvite, as a result of chronic urinary tract infection (UTI). SFR was 88.5% (23 of 26). CONCLUSIONS: Our experience showed that MPCNL is a safe and effective treatment modality with little morbidity for renal and upper ureteral stones in patients with urinary diversion. For middle and lower ureteral stones, an anterograde approach could be also considered as a first line treatment, but a combined anterograde and retrograde approach was required when the anterograde access alone cannot provide acceptable results.

CyPA-CD147-ERK1/2-cyclin D2 signaling pathway is upregulated during rat left ventricular hypertrophy.

The changes of serum cyclophilin A (CyPA), its receptor CD147 and the downstream signaling pathway during the process of cardiac hypertrophy remain unknown. The present study aims to investigate the relationships between CyPA-CD147-ERK1/2-cyclin D2 signaling pathway and the development of cardiac hypertrophy. Left ventricular hypertrophy was prepared by 2-kidney, 2-clip in Sprague-Dawley rats and observed for 1 week, 4 and 8 weeks. Left ventricular hypertrophy was evaluated by ratio of left ventricular heart weight to body weight (LVW/BW) and cardiomyocyte cross sectional area (CSA). CyPA levels in serum were determined with a rat CyPA ELISA kit. Expressions of CyPA, CD147, phospho-ERK1/2 and cyclin D2 in left ventricular myocytes were determined by Western blot and immunostaining. Compared with sham groups, systolic blood pressure reached hypertensive levels at 4 weeks in 2K2C groups. LVW/BW and CSA in 2K2C groups were significantly increased at 4 and 8 weeks after clipping. ELISA results indicated a prominent increase in serum CyPA level associated with the degree of left ventricular hypertrophy. Western blot revealed that the expressions of CyPA, CD147, phospho-ERK1/2 and cyclin D2 in left ventricular tissues were also remarkably increased as the cardiac hypertrophy developed. The results of the present study demonstrates that serum CyPA and CyPA-CD147-ERK1/2-cyclin D2 signaling pathway in ventricular tissues are time-dependently upregulated and activated with the process of left ventricular hypertrophy. These data suggest that CyPA-CD147 signaling cascade might play a role in the pathogenesis of left ventricular hypertrophy, and CyPA might be a prognosticator of the degree of left ventricular hypertrophy.

The association between wet overactive bladder and consumption of tea, coffee, and caffeine: Results from 2005-2018 National Health and Nutrition Examination Survey.

BACKGROUND & AIMS: Previous studies have reported an inconsistent relationship between overactive bladder (OAB) and the consumption of tea, coffee, and caffeine. Our study aims to determine these associations in a large and nationally representative adult sample. METHODS: This cross-sectional study included 15,379 participants from the 2005-2018 US National Health and Nutrition Examination Survey (NHANES) database. The outcome was the risk of wet OAB that was diagnosed when the OAB symptom score was ≥3 with urgent urinary incontinence and excluded other diseases affecting diagnosis. The exposures were the consumption of tea, coffee, and caffeine. Weighted logistic regression models were established to explore these associations by calculating odds ratios (OR) and 95% confidence intervals (CI), as did restricted cubic splines (RCS) used to analyze the nonlinear associations. RESULT: Of all the participants (n = 15,379), 2207 had wet OAB. Mean [SE] consumption of tea, total coffee, caffeinated coffee, decaffeinated coffee, and caffeine was 233.6 [15.7] g/day, 364.3 [15.5] g/day, 301.6 [14.9] g/day, 62.7 [7.9] g/day, 175.5 [6.6] mg/day in participants with wet OAB, respectively. In the fully adjusted model, compared to those without tea consumption, the high consumption of tea (>481 g/day) was associated with an increased risk of wet OAB (OR: 1.29; 95%CI: 1.01-1.64). Low decaffeinated coffee (0.001-177.6 g/day) had a negative association with the risk (OR: 0.66; 95%CI: 0.49-0.90). In the RCS analysis, tea consumption showed a positive linear association with the risk of wet OAB, and decaffeinated coffee showed a nonlinear relationship with the risk and had a turning point of 78 g/day in the U-shaped curve between 0 and 285 g/day. Besides, total coffee, caffeinated coffee, and caffeine consumption had no significant association with the risk. Interestingly, in the high tea consumption, participants with high total coffee consumption [>527.35 g/day, OR and 95%CI: 2.14(1.16-3.94)] and low caffeine consumption [0.1-74.0 mg/day, OR and 95%CI: 1.50(1.03-2.17)] were positively associated with the risk of wet OAB. CONCLUSION: High tea consumption was associated with the increased risk of wet OAB, especially intake together with high total coffee and low caffeine consumption, but no significant association with the single consumption of total coffee and caffeine. Low decaffeinated coffee was associated with a decreased risk of wet OAB. It is necessary to control tea intake when managing the liquid intake of wet OAB patients.

Unveiling the Etiology of Urological Tumors: A Systematic Review of Mendelian Randomization Applications in Renal Cell Carcinoma, Bladder Cancer, and Prostate Cancer.

BACKGROUND: Our study aims to address two pivotal questions: "What are the recent advancements in understanding the etiology of urological tumors through Mendelian Randomization?" and "How can Mendelian Randomization be more effectively applied in clinical settings to enhance patient health outcomes in the future?" METHODS: In our systematic review conducted in April 2023, we utilized databases like PubMed and Web of Science to explore the influence of Mendelian Randomization in urological oncological diseases. We focused on studies published from January 2018, employing keywords related to urological tumors and Mendelian Randomization, supplemented with MeSH terms and manual reference checks. Our inclusion criteria targeted original research studies, while we excluded reports and non-relevant articles.  Data extraction followed a PICO-based approach, and bias risk was independently evaluated, with discrepancies resolved through discussion. This systematic approach adhered to PRISMA guidelines for accuracy and thoroughness in reporting. RESULTS: From the initial 457 publications, we narrowed down to 43 full-text articles after screening and quality assessments.A deeper understanding of Mendelian Randomization can help us explore risk factors with a clear causal relationship to urological tumors.This insight may pave the way for future research in early diagnosis, treatment, and management of associated diseases. CONCLUSION: Our review underscores the value of MR in urogenital tumor research, highlighting its efficacy in establishing causality and its potential to clarify disease mechanisms. Despite challenges like large sample sizes and variant identification, MR offers new perspectives for understanding and managing these tumors, suggesting a trend towards more inclusive and diverse research approaches.

Identification of signature genes for renal ischemia‒reperfusion injury based on machine learning and WGCNA.

Background: As an inevitable event after kidney transplantation, ischemia‒reperfusion injury (IRI) can lead to a decrease in kidney transplant success. The search for signature genes of renal ischemia‒reperfusion injury (RIRI) is helpful in improving the diagnosis and guiding clinical treatment. Methods: We first downloaded 3 datasets from the GEO database. Then, differentially expressed genes (DEGs) were identified and applied for functional enrichment analysis. After that, we performed three machine learning methods, including random forest (RF), Lasso regression analysis, and support vector machine recursive feature elimination (SVM-RFE), to further predict candidate genes. WGCNA was also executed to screen candidate genes from DEGs. Then, we took the intersection of candidate genes to obtain the signature genes of RIRI. Receiver operating characteristic (ROC) analysis was conducted to measure the predictive ability of the signature genes. Kaplan‒Meier analysis was used for association analysis between signature genes and graft survival. Verifying the expression of signature genes in the ischemia cell model. Results: A total of 117 DEGs were screened out. Subsequently, RF, Lasso regression analysis, SVM-RFE and WGCNA identified 17, 25, 18 and 74 candidate genes, respectively. Finally, 3 signature genes (DUSP1, FOS, JUN) were screened out through the intersection of candidate genes. ROC analysis suggested that the 3 signature genes could well diagnose and predict RIRI. Kaplan‒Meier analysis indicated that patients with low FOS or JUN expression had a longer OS than those with high FOS or JUN expression. Finally, we validated using the ischemia cell model that compared to the control group, the expression level of JUN increased under hypoxic conditions. Conclusions: Three signature genes (DUSP1, FOS, JUN) offer a good prediction for RIRI outcome and may serve as potential therapeutic targets for RIRI intervention, especially JUN. The prediction of graft survival by FOS and JUN may improve graft survival in patients with RIRI.