DriverDBv4: a multi-omics integration database for cancer driver gene research.

Advancements in high-throughput technology offer researchers an extensive range of multi-omics data that provide deep insights into the complex landscape of cancer biology. However, traditional statistical models and databases are inadequate to interpret these high-dimensional data within a multi-omics framework. To address this limitation, we introduce DriverDBv4, an updated iteration of the DriverDB cancer driver gene database (http://driverdb.bioinfomics.org/). This updated version offers several significant enhancements: (i) an increase in the number of cohorts from 33 to 70, encompassing approximately 24 000 samples; (ii) inclusion of proteomics data, augmenting the existing types of omics data and thus expanding the analytical scope; (iii) implementation of multiple multi-omics algorithms for identification of cancer drivers; (iv) new visualization features designed to succinctly summarize high-context data and redesigned existing sections to accommodate the increased volume of datasets and (v) two new functions in Customized Analysis, specifically designed for multi-omics driver identification and subgroup expression analysis. DriverDBv4 facilitates comprehensive interpretation of multi-omics data across diverse cancer types, thereby enriching the understanding of cancer heterogeneity and aiding in the development of personalized clinical approaches. The database is designed to foster a more nuanced understanding of the multi-faceted nature of cancer.

LipidSig 2.0: integrating lipid characteristic insights into advanced lipidomics data analysis.

In the field of lipidomics, where the complexity of lipid structures and functions presents significant analytical challenges, LipidSig stands out as the first web-based platform providing integrated, comprehensive analysis for efficient data mining of lipidomic datasets. The upgraded LipidSig 2.0 (https://lipidsig.bioinfomics.org/) simplifies the process and empowers researchers to decipher the complex nature of lipids and link lipidomic data to specific characteristics and biological contexts. This tool markedly enhances the efficiency and depth of lipidomic research by autonomously identifying lipid species and assigning 29 comprehensive characteristics upon data entry. LipidSig 2.0 accommodates 24 data processing methods, streamlining diverse lipidomic datasets. The tool's expertise in automating intricate analytical processes, including data preprocessing, lipid ID annotation, differential expression, enrichment analysis, and network analysis, allows researchers to profoundly investigate lipid properties and their biological implications. Additional innovative features, such as the 'Network' function, offer a system biology perspective on lipid interactions, and the 'Multiple Group' analysis aids in examining complex experimental designs. With its comprehensive suite of features for analyzing and visualizing lipid properties, LipidSig 2.0 positions itself as an indispensable tool for advanced lipidomics research, paving the way for new insights into the role of lipids in cellular processes and disease development.

A comparative study of transperineal software-assisted magnetic resonance/ultrasound fusion biopsy and transrectal cognitive fusion biopsy of the prostate.

BACKGROUND: The advantages and disadvantages of transperineal and transrectal biopsies remain controversial in the era of prostate targeted biopsy. In this study, we compared the cancer detection and complication rates of transperineal magnetic resonance/ultrasound (MR/US) fusion biopsy and transrectal cognitive fusion biopsy of the prostate. METHODS: This was a comparative study of two prospectively collected cohorts. Men with clinically suspected prostate cancer and prostate imaging reporting and data system (PI-RADS) score ≥ 3 lesions on multi-parametric magnetic resonance imaging (mpMRI) were enrolled. They underwent either transperineal software fusion biopsy or transrectal cognitive fusion biopsy and systematic biopsy. The detection rates of any prostate cancer and clinically significant prostate cancer (csPC, defined as Gleason score ≥ 3 + 4) and the complication rates between both groups were analysed. RESULTS: Ninety-two and 85 patients underwent transperineal software fusion and transrectal cognitive fusion biopsies, respectively. The detection rate for any prostate cancer was similar between both groups (60.8% vs. 56.4%, p = 0.659). In terms of csPC detection, transperineal fusion biopsy outperformed transrectal fusion biopsy (52.2% vs. 36.5%, p = 0.036). In multivariate regression analysis, age, PI-RADS score > 3, and transperineal route were significant predictors of csPC. Meanwhile, transperineal biopsy resulted in a higher rate of urinary retention than transrectal biopsy (18.5% vs. 4.7%, p = 0.009). No serious infectious complications were noted, although a patient developed sepsis after transrectal biopsy. CONCLUSIONS: Transperineal software fusion biopsy provided a higher csPC detection rate than transrectal cognitive fusion biopsy and carried minimal risk for infectious complications in patients with MRI-visible prostate lesions.

External validation of the Simplified PADUA REnal (SPARE) nephrometry system in predicting surgical outcomes after partial nephrectomy.

BACKGROUND: Pentafecta is a major goal in the era of partial nephrectomy (PN). Simplified PADUA REnal (SPARE) nephrometry system was developed to evaluate the complexity of tumor. However, the predictive ability in pentafecta of SPARE system is yet to be determined. The aim of this study was to externally validate the applicability of SPARE nephrometry system in predicting pentafecta achievement after partial nephrectomy, and to examine inter-observer concordance. METHODS: We retrospectively reviewed data of 207 consecutive patients who underwent PN between January 2012 and August 2018 at a tertiary referral center. We obtained SPARE, R.E.N.A.L., and PADUA scores and evaluated correlations among the nephrometries and surgical outcomes including pentafecta by Spearman test. Logistic regression analysis was used to identify independent predictors of pentafecta outcomes. We compared the nephrometries to determine the predictive ability of achieving pentafecta using receiver operating characteristic curve analysis. Fleiss' generalized kappa was used to assessed interobserver variation in the SPARE system. RESULTS: Based on the SPARE system, 120, 74, and 13 patients were stratified into low-risk, intermediate-risk, and high-risk groups, respectively. Regarding the individual components of pentafecta, there were significant differences in the complication rate (p = 0.03), ischemia time (p < 0.001), and percent change of eGFR (p < 0.001) among the three risk groups. In addition, higher tumor complexity was significantly associated with a lower achievement rate of pentafecta (p = 0.01). In Spearman correlation tests, SPARE nephrometry was correlated with ischemia time (ρ:0.37, p < 0.001), operative time (ρ:0.28, p < 0.001), complication rate (ρ:0.34, p < 0.001), percent change of eGFR (ρ:0.34, p < 0.001), and progression of chronic kidney disease stage (ρ:0.17, p = 0.02). Multivariate analysis revealed that SPARE significantly affected pentafecta (OR: 0.67, p < 0.001). In ROC curve analysis, SPARE showed fair predictive ability in the achievement pentafecta (AUC: 0.71). The predictive ability of pentafecta was similar between nephrometries (SPARE vs. R.E.N.A.L., p = 0.78; SPARE vs. PADUA, p = 0.66). The interobserver concordance of SPARE was excellent (Kappa: 0.82, p = 0.03). CONCLUSIONS: SPARE system was a predictive factor of surgical outcomes after PN. This refined nephrometry had similar predictive abilities for pentafecta achievement compared with R.E.N.A.L. and PADUA.

The role of RENAL, PADUA, C-index, CSA nephrometry systems in predicting ipsilateral renal function after partial nephrectomy.

BACKGROUND: Functional outcome is an important issue in nephron-sparing surgery. Various nephrometries have been developed to predict renal function preservation. The aim of this study was to examine the applicability of R.E.N.A.L., PADUA, C-index, and mathematical tumor contact surface area (CSA) in predicting ipsilateral renal function after partial nephrectomy using radio-isotope scans. METHODS: We performed this retrospective study in patients who underwent partial nephrectomy between May 2013 and April 2017, and used abdominopelvic computerized tomography or magnetic resonance imaging to obtain R.E.N.A.L., C-index, and CSA. Renal function was measured by 99mTc mercaptoacetyltriglycine (MAG3). We evaluated correlations between nephrometries and perioperative parameters, and comparatively analyzed different nephrometries to determine the predictive ability in the percent change of effective renal plasma flow of the affected kidney. RESULTS: Three, two, and 35 patients received partial nephrectomy in open, laparoscopic, and robotic approaches, respectively. The median (IQR) tumor size was 3.13 (2.4) cm. The median (IQR) R.E.N.A.L., PADUA, C-index, and CSA scores were 7 (3), 8 (2), 2.01 (1.87), and 14.14 (19.25) cm2, respectively. Spearman correlation analysis showed that four nephrometries were correlated with each other. The strongest correlations were between CSA and C-index (coefficient: - 0.885, p < 0.001), followed by R.E.N.A.L. and PADUA (coefficient: 0.778, p < 0.001). Ischemia time was significantly correlated with R.EN.A.L. (coefficient: 0.35, p = 0.025), PADUA (coefficient: 0.42, p = 0.007), C-index (coefficient: - 0.45, p = 0.004), and CSA (coefficient: 0.41, p = 0.009). In multivariate analysis, PADUA significantly affected ischemia time (p = 0.04). The percent change in effective renal plasma flow (PCE) of the operated kidney was correlated with PADUA (coefficient: 0.48 p = 0.002), C-index (coefficient: - 0.74, p < 0.001), and CSA (coefficient: 0.75, p < 0.001). Only CSA and C-index independently affected PCE (both p < 0.05) in multivariate analysis. In ROC curve analysis, both C-index and CSA could predict 20% change in effective renal plasma flow (AUC: 0.91 vs 0.86, p = 0.2) of the affected kidney. CONCLUSIONS: We suggest using PADUA to evaluate surgical complexity and ischemia time. Regarding the accuracy of the prediction of post-operative ipsilateral renal function, both CSA and C-index outperformed R.E.N.A.L. and PADUA nephrometries.

A Mathematical Method to Calculate Tumor Contact Surface Area: An Effective Parameter to Predict Renal Function after Partial Nephrectomy.

PURPOSE: We proposed a mathematical formula to calculate contact surface area between a tumor and renal parenchyma. We examined the applicability of using contact surface area to predict renal function after partial nephrectomy. MATERIALS AND METHODS: We performed this retrospective study in patients who underwent partial nephrectomy between January 2012 and December 2014. Based on abdominopelvic computerized tomography or magnetic resonance imaging, we calculated the contact surface area using the formula (2*π*radius*depth) developed by integral calculus. We then evaluated the correlation between contact surface area and perioperative parameters, and compared contact surface area and R.E.N.A.L. (Radius/Exophytic/endophytic/Nearness to collecting system/Anterior/Location) score in predicting a reduction in renal function. RESULTS: Overall 35, 26 and 45 patients underwent partial nephrectomy with open, laparoscopic and robotic approaches, respectively. Mean ± SD contact surface area was 30.7±26.1 cm(2) and median (IQR) R.E.N.A.L. score was 7 (2.25). Spearman correlation analysis showed that contact surface area was significantly associated with estimated blood loss (p=0.04), operative time (p=0.04) and percent change in estimated glomerular filtration rate (p <0.001). On multivariate analysis contact surface area and R.E.N.A.L. score independently affected percent change in estimated glomerular filtration rate (p <0.001 and p=0.03, respectively). On ROC curve analysis contact surface area was a better independent predictor of a greater than 10% change in estimated glomerular filtration rate compared to R.E.N.A.L. score (AUC 0.86 vs 0.69). CONCLUSIONS: Using this simple mathematical method, contact surface area was associated with surgical outcomes. Compared to R.E.N.A.L. score, contact surface area was a better predictor of functional change after partial nephrectomy.

The complete mitochondrial genome of Triplophysa erythraea (Huang et al. 2019) (Cypriniformes, Nemacheilidae).

In this study, the complete mitochondrial genome of Triplophysa erythraea was determined for the first time. Results showed the mitogenome was 16 565 bp, including 2 ribosomal RNA genes, 22 transfer RNA genes, 13 protein-coding genes and 2 non-coding regions. The overall base composition of its mitochondrial genome was 28.9% A, 25.2% T, 28.7% C and 17.2% G. Phylogenetic tree revealed that Triplophysa erythraea had the closest relationship with Triplophysa xiangxiensis, which was also found in Xiangxi Tujia and Miao Nationality Autonomous Prefecture, Hunan province. In general, this study provided valuable information for conservation genetics analyses of Triplophysa erythraea and further displayed the evolution of species within the genus Triplophysa.

Learning Curve of Transperineal MRI/US Fusion Prostate Biopsy: 4-Year Experience.

This study aimed to evaluate the learning curve of transperineal magnetic resonance imaging (MRI)/ultrasound (US) fusion biopsy in a team composed of a single surgeon, a single radiologist, and a single pathologist. We prospectively enrolled 206 patients undergoing MRI/US fusion prostate biopsy and divided them into four cohorts by the year of biopsy. We analyzed temporal changes in clinically significant prostate cancer (csPC) detection rate, percentage of positive cores on biopsy, and Gleason upgrading rate after radical prostatectomy. The csPC detection rate by MRI/US fusion targeted biopsy (TB) increased significantly (from 35.3% to 60.0%, p = 0.01). With increased experience, the csPC detection rates for small (≤1 cm) and anterior target lesions gradually increased (from 41.2% to 51.6%, p = 0.5; from 54.5% to 88.2%, p = 0.8, respectively). The percentage of positive cores on TB increased significantly (from 18.4% to 44.2%, p = 0.001). The Gleason upgrading rate gradually decreased (from 22.2% to 11.1%, p = 0.4). In conclusion, with accumulated experience and teamwork, the csPC detection rate by TB significantly increased. Multidisciplinary team meetings and a free-hand biopsy technique were the key factors for overcoming the learning curve.

Machine Learning and Radiomics of Bone Scintigraphy: Their Role in Predicting Recurrence of Localized or Locally Advanced Prostate Cancer.

BACKGROUND: Machine-learning (ML) and radiomics features have been utilized for survival outcome analysis in various cancers. This study aims to investigate the application of ML based on patients' clinical features and radiomics features derived from bone scintigraphy (BS) and to evaluate recurrence-free survival in local or locally advanced prostate cancer (PCa) patients after the initial treatment. METHODS: A total of 354 patients who met the eligibility criteria were analyzed and used to train the model. Clinical information and radiomics features of BS were obtained. Survival-related clinical features and radiomics features were included in the ML model training. Using the pyradiomics software, 128 radiomics features from each BS image's region of interest, validated by experts, were extracted. Four textural matrices were also calculated: GLCM, NGLDM, GLRLM, and GLSZM. Five training models (Logistic Regression, Naive Bayes, Random Forest, Support Vector Classification, and XGBoost) were applied using K-fold cross-validation. Recurrence was defined as either a rise in PSA levels, radiographic progression, or death. To assess the classifier's effectiveness, the ROC curve area and confusion matrix were employed. RESULTS: Of the 354 patients, 101 patients were categorized into the recurrence group with more advanced disease status compared to the non-recurrence group. Key clinical features including tumor stage, radical prostatectomy, initial PSA, Gleason Score primary pattern, and radiotherapy were used for model training. Random Forest (RF) was the best-performing model, with a sensitivity of 0.81, specificity of 0.87, and accuracy of 0.85. The ROC curve analysis showed that predictions from RF outperformed predictions from other ML models with a final AUC of 0.94 and a p-value of <0.001. The other models had accuracy ranges from 0.52 to 0.78 and AUC ranges from 0.67 to 0.84. CONCLUSIONS: The study showed that ML based on clinical features and radiomics features of BS improves the prediction of PCa recurrence after initial treatment. These findings highlight the added value of ML techniques for risk classification in PCa based on clinical features and radiomics features of BS.

QSOFA and SOFA scores are valuable tools for predicting postoperative sepsis resulting from ureteroscopic lithotripsy (URSL).

The sequential organ failure assessment (SOFA) and quick sequential organ failure assessment (qSOFA) scores are new tools which are used to assess sepsis based on the Third International Consensus Definitions for Sepsis and Septic Shock Task Force. This study aimed to evaluate the feasibility of using the SOFA and qSOFA to predict post-ureteroscopic lithotripsy (URSL) sepsis. Patients who underwent URSL due to ureteral stone obstruction were retrospectively reviewed using SOFA and qSOFA scores. Patient characteristics including age, gender, comorbidities, American Society of Anesthesiologists Classification, stone burden, stone location, hydronephrosis status, infectious status, preoperative SOFA and qSOFA score were collected. Preoperative factors were analyzed to determine if they were correlated with postoperative sepsis. A total of 830 patients were included in this study, of whom 32 (3.9%) had postoperative sepsis. Multivariate analysis revealed that older age, proximal ureteral stones, severe hydronephrosis, and high preoperative qSOFA or SOFA score were significantly associated with postoperative sepsis. The areas under the curves of a qSOFA score ≥ 1 and SOFA score ≥ 2 for predicting postoperative sepsis were 0.754 and 0.823, respectively. Preoperative qSOFA and SOFA scores are convenient and effective for predicting post-URSL sepsis. Further preventive strategies should be performed in these high-risk patients.

The Role of Annexin A4 in Triple-Negative Breast Cancer Progression and Its Clinical Application.

BACKGROUND: The expression of annexin A4 in triple-negative breast cancer (TNBC) remains unclear. In the present study, we investigated the expression of annexin A4 in TNBC tissues, as well as its relationship with clinicopathological and prognostic indicators, with an aim to assess its application value. METHODS: We adopted immunohistochemical and western blot to detect annexin A4 expression in TNBC and para-carcinoma tissues, and to explore the relationship between abnormal expression of annexin A4 and clinicopathological features of TNBC patients. RESULTS: The annexin A4 expression was significantly higher in TNBC tissues than in adjacent tissues. We analyzed the relationship between annexin A4 expression level and clinicopathological characteristics of TNBC patients. The results suggested that annexin A4 expression level was closely related to TNM stage, vascular involvement, lymphovascular invasion, and lymph node status of TNBC patients. The results survival analysis suggested upregulated expression of annexin A4 in TNBC patients with a shorter survival time. The results of a multifactor analysis showed that high annexin A4 expression rate was an independent predictive factor of the prognosis of the TNBC patients. CONCLUSIONS: The high annexin A4 expression indicates the poor prognosis of TNBC patients; thus, annexin A4 can be regarded as an important molecular marker in TNBC prognosis.

Mesostructured tin oxide as sensitive material for C(2)H(5)OH sensor.

Mesostructured tin oxide with high specific surface area was synthesized using cationic surfactant (cetyltrimethylammonium bromide, CTAB: CH(3)(CH(2))(15)N(+)(CH(3))(3)Br(-)) as the organic template and hydrous tin chloride (SnCl(4).5H(2)O) and NH(4)OH as the inorganic precursors under acidic conditions at ambient temperature. Thermogravimetric analysis (TGA), Fourier transformed infrared (FTIR), X-ray diffraction analysis (XRD), X-ray photoelectron spectrum (XPS) and N(2)-sorption isotherms were used to characterize the mesostructured tin oxide that was formed at room temperature as well as calcined at different temperature. The surface area of mesostructured tin oxide calcined at 400 degrees C is 136 m(2) g(-1). The indirect heating sensor using this material as sensitive body was fabricated on an alumna tube with Au electrodes and platinum wires. Electrical and sensing properties of such a sensor were investigated. It was found that the mesostructured tin oxide with high surface area had higher sensitivity to C(2)H(5)OH and selectivity to gasoline than commercial sample of polycrystalline tin(IV) oxide.