An automatic diagnostic system for the urodynamic study applying in lower urinary tract dysfunction.

OBJECTIVE: To establish an automatic diagnostic system based on machine learning for preliminarily analysis of urodynamic study applying in lower urinary tract dysfunction (LUTD). METHODS: The eight most common conditions of LUTDs were included in the present study. A total of 527 eligible patients with complete data, from the year of 2015 to 2020, were enrolled in this study. In total, two global parameters (patients' age and sex) and 13 urodynamic parameters were considered to be the input for machine learning algorithms. Three machine learning approaches were applied and evaluated in this study, including Decision Tree (DT), Logistic Regression (LR), and Support Vector Machine (SVM). RESULTS: By applying machine learning algorithms into the 8 common LUTDs, the DT models achieved the AUC of 0.63-0.98, the LR models achieved the AUC of 0.73-0.99, and the SVM models achieved the AUC of 0.64-1.00. For mutually exclusive diagnoses of underactive detrusor and acontractile detrusor, we developed a classification model that classifies the patients into either of these two diseases or double-negative class. For this classification method, the DT models achieved the AUC of 0.82-0.85 and the SVM models achieved the AUC of 0.86-0.90. Among all these models, the LR and the SVM models showed better performance. The best model of these diagnostic tasks achieved an average AUC of 0.90 (0.90 ± 0.08). CONCLUSIONS: An automatic diagnostic system was developed using three machine learning models in urodynamic studies. This automated machine learning process could lead to promising assistance and enhancements of diagnosis and provide more useful reference for LUTD treatment.

Letter to the editor: Aggressive variant prostate cancer: An exemplary case study and comprehensive literature survey.

This article enthusiastically explores the study of highly aggressive variant prostate cancer (AVPC), acknowledging its relatively rare yet highly menacing presence within the realm of prostate cancer. The paper delves into the pathological characteristics of AVPC, diagnostic and therapeutic challenges, and the potential applications of precision medicine and molecular imaging in the future.

Neutrophil-to-lymphocyte ratio as a promising non-invasive biomarker for symptom assessment and diagnosis of interstitial cystitis/bladder pain syndrome.

BACKGROUND: Our study aims to investigate the association between the serum neutrophil-to-lymphocyte ratio (NLR) and interstitial cystitis (IC), as well as to explore whether NLR can serve as a diagnostic marker to distinguish IC from overactive bladder (OAB). We postulate that elevated NLR levels are intricately linked to the onset and clinical presentation of IC, and that the NLR profiles in OAB patients exhibit discernible disparities from those of IC patients. METHODS: In a retrospective analysis, we scrutinized the medical records of 70 women diagnosed with IC/BPS, 20 women diagnosed with OAB, and a randomly selected cohort of 150 healthy women who underwent physical examinations during the same temporal frame. A comprehensive panel of blood tests was administered to all participants, and NLR was determined through the calculation of the neutrophil-to-lymphocyte proportion. Additionally, symptom assessment questionnaires and urination diaries were collected from IC/BPS patients. RESULTS: NLR levels exhibited significant distinctions among the IC/BPS, Normal, and OAB groups (P < 0.001). Within the IC/BPS group, Hunner type interstitial cystitis (HIC) demonstrated notably divergent NLR levels in comparison to non-Hunner type interstitial cystitis (NHIC) (p = 0.001). Additionally, we observed positive correlations between NLR and Nighttime voids (r = 0.268, p = 0.029), ICPI (r = 0.327, p = 0.007), ICSI (r = 0.369, p = 0.002), PUF Symptom Scale (r = 0.263, p = 0.032), and PUF (r = 0.297, p = 0.015). The receiver operating characteristic (ROC) analysis yielded an area under the curve (AUC) of 0.765 for NLR in distinguishing IC/BPS from the Normal group, and an AUC of 0.707 in discerning IC from OAB. Furthermore, the AUC of NLR was 0.723 for identifying HIC and NHIC patients. CONCLUSIONS: Our study unveils the prospective utility of serum NLR as a promising biomarker for both diagnostic and symptom evaluation purposes in IC/BPS patients. It effectively demarcates this condition from OAB, which presents with similar clinical features. Consequently, NLR demonstrates potential as a non-invasive diagnostic instrument to distinguish between the subtypes of IC, particularly HIC and NHIC, which manifest similar symptoms within the IC/BPS spectrum.

SEMA3G functions as a novel prognostic biomarker associated with Wnt pathway in clear cell renal cell carcinoma.

Renal cell cancer (RCC) is one of the most common cancer, and the incidence of clear cell renal cell cancer rank at the first among multiple subtypes of RCC. Tumor heterogeneity and limited therapies expedite researches and studies on prognostic biomarkers and molecular mechanism. SEMA3G mediates various bimolecular processes but few studies have assessed the influence of SEMA3G on ccRCC. The expression of SEMA3G at mRNA level in ccRCC was analyzed using 4 TCGA datasets. The expression at protein level was verified by immunohistochemistry and western blot. Biological pathway was explored by GSEA and western blot. At both mRNA and protein level, SEMA3G expressed significantly lower in ccRCC tissues compared with normal renal tissues, and the expression was highly associated with clinical stage and pathological grade. Low expression of SEMA3G indicated a poorer overall survival and disease specific survival. Transwell and wound-healing assays showed that overexpressed SEMA3G inhibited the cell motility of renal cancer cells. Upregulated SEMA3G suppressed the invasion and proliferation of both 769-P and 786-O cells. Wnt signaling pathway was tested to work in the interfering of SEMA3G on tumorigenesis and progression of ccRCC. The results provide novel insight into the role of SEMA3G in ccRCC, suggesting the prognostic value and potential suppressor role of SEMA3G.

Cystoscopy, an indispensable tool for the diagnosis and prognosis of bladder pain syndrome, takes nomograms for predicting recurrence.

PURPOSE: We aimed to illustrate the importance of cystoscopy for the diagnosis and prognosis of bladder pain syndrome (BPS) or interstitial cystitis (IC). METHODS AND MATERIALS: We designed a 4-year prospective follow-up study. Patients who underwent cystoscopy between May 2011 and July 2021 with a diagnosis of BPS/IC before surgery or positive cystoscopic findings during initial surgery at Peking University People's Hospital were enrolled. Data related to symptom recurrence were obtained through clinic visits and telephone follow-up. We compared the differences in clinical features of BPS/IC subtypes differentiated by cystoscopy and first created clinical predictive nomograms for BPS/IC. RESULTS: A total of 141 patients were included. There was an 8.51% chance of BPS/IC being misdiagnosed as other diseases or other diseases being misdiagnosed as BPS/IC without cystoscopy. Patients with HIC had higher pain scores and ICPI, higher residual urine volume, lower first-sense-to-void, and maximum cystometric bladder capacities than NHIC. Nomogram Models showed that patients who with higher ICPI, ICSI and lower AMBC have a greater recurrence probability, and lesions in the trigone may indicate a greater likelihood of recurrence than lesions in other bladder walls. CONCLUSIONS: Timely detection of bladder cancer and other diseases using cystoscopy can avoid poor treatment effects. BPS/IC subtypes can be classified according to mucosal changes under cystoscopy. Lesions in the bladder triangle can indicate a higher recurrence risk, which is important in follow-up treatment. We strongly recommend that cystoscopy should be included in the international BPS/IC diagnostic criteria.