Preoperative smoking and robot-assisted radical cystectomy outcomes & complications in multicenter KORARC database.

To investigate the influence of preoperative smoking history on the survival outcomes and complications in a cohort from a large multicenter database. Many patients who undergo radical cystectomy (RC) have a history of smoking; however, the direct association between preoperative smoking history and survival outcomes and complications in patients with muscle-invasive bladder cancer (MIBC) who undergo robot-assisted radical cystectomy (RARC) remains unexplored. We conducted a retrospective analysis using data from 749 patients in the Korean Robot-Assisted Radical Cystectomy Study Group (KORARC) database, with an average follow-up duration of 30.8 months. The cohort was divided into two groups: smokers (n = 351) and non-smokers (n = 398). Propensity score matching was employed to address differences in sample size and baseline demographics between the two groups (n = 274, each). Comparative analyses included assessments of oncological outcomes and complications. After matching, smoking did not significantly affect the overall complication rate (p = 0.121). Preoperative smoking did not significantly increase the occurrence of complications based on complication type (p = 0.322), nor did it increase the readmission rate (p = 0.076). There were no perioperative death in either group. Furthermore, preoperative smoking history showed no significant impact on overall survival (OS) [hazard ratio (HR) = 0.87, interquartile range (IQR): 0.54-1.42; p = 0.589] and recurrence-free survival (RFS) (HR = 1.12, IQR: 0.83-1.53; p = 0.458) following RARC for MIBC. The extent of preoperative smoking (≤ 10, 10-30, and ≥ 30 pack-years) had no significant influence on OS and RFS in any of the categories (all p > 0.05). Preoperative smoking history did not significantly affect OS, RFS, or complications in patients with MIBC undergoing RARC.

Spatial calibration and uncertainty reduction of the SWAT model using multiple remotely sensed data.

Remotely sensed products are often used in watershed modeling as additional constraints to improve model predictions and reduce model uncertainty. Remotely sensed products also enabled the spatial evaluation of model simulations due to their spatial and temporal coverage. However, their usability is not extensively explored in various regions. This study evaluates the effectiveness of incorporating remotely sensed evapotranspiration (RS-ET) and leaf area index (RS-LAI) products to enhance watershed modeling predictions. The objectives include reducing parameter uncertainty at the watershed scale and refining the model's capability to predict the spatial distribution of ET and LAI at sub-watershed scale. Using the Soil and Water Assessment Tool (SWAT) model, a systematic calibration procedure was applied. Initially, solely streamflow data was employed as a constraint, gradually incorporating RS-ET and RS-LAI thereafter. The results showed that while 14 parameter sets exhibit satisfactory performance for streamflow and RS-ET, this number diminishes to six with the inclusion of RS-LAI as an additional constraint. Furthermore, among these six sets, only three effectively captured the spatial patterns of ET and LAI at the sub-watershed level. Our findings showed that leveraging multiple remotely sensed products has the potential to diminish parameter uncertainty and increase the credibility of intra-watershed process simulations. These results contributed to broadening the applicability of remotely sensed products in watershed modeling, enhancing their usefulness in this field.

Evaluation of histological variants of upper tract urothelial carcinoma as prognostic factor after radical nephroureterectomy.

PURPOSE: To evaluate the impact of variant histology on patients with upper tract urothelial carcinoma (UTUC) survival outcomes. MATERIALS AND METHODS: A total of 519 patients underwent radical nephroureterectomy without neoadjuvant therapy for UTUC at a single institution between May 2003 and December 2019. Multivariate Cox regression analysis evaluated the impact of variant histology on progression-free survival (PFS), cancer-specific survival (CSS), and overall survival (OS). RESULTS: Among 84 patients (16.2%) with variant histology, the most frequent variant type was squamous cell differentiation (64.3%), followed by glandular differentiation (25.0%) and sarcomatoid variant (2.4%). They showed pathologically advanced T stage (for ≥ T3, 59.5% vs 33.3%, p < 0.001), higher tumor grade (96.4% vs 85.7%, p = 0.025), and higher rates of lymph node metastasis (17.9% vs 7.8%, p = 0.015), angiolymphatic invasion (41.7% vs 25.7%, p = 0.003), tumor necrosis (57.1% vs 29.0%, p < 0.001) and positive surgical margin (13.1% vs 5.7%, p = 0.015). On multivariate Cox regression analyses, variant histology was significantly associated with worse PFS (hazard ratio [HR] 2.23; 95% confidence interval [CI] 1.55-3.21; p < 0.001), CSS (HR 2.67; 95% CI 1.35-5.30; p = 0.005) and OS (HR 2.22; 95% CI 1.27-3.88; p = 0.005). In subgroup analysis, no significant survival gains of adjuvant chemotherapy occurred in patients with variant histology. CONCLUSIONS: Variant histology was associated with adverse pathologic features and poor survival outcomes. Our results suggest that patients with variant histology may require a close follow-up schedule and novel adjuvant therapy other than chemotherapy postoperatively.

Bilateral Seminal Vesicle Invasion as a Strong Prognostic Indicator in T3b Prostate Cancer Patients Following Radical Prostatectomy: A Comprehensive, Multi-Center, Long-Term Follow-Up Study.

Purpose: Pathologic T3b (pT3b) prostate cancer, characterized by seminal vesicle invasion (SVI), exhibits variable oncological outcomes post-radical prostatectomy (RP). Identifying prognostic factors is crucial for patient-specific management. This study investigates the impact of bilateral SVI on prognosis in pT3b prostate cancer. Materials and Methods: We evaluated the medical records of a multi-institutional cohort of men who underwent RP for prostate cancer with SVI between 2000 and 2012. Univariate and multivariable analyses were performed using Kaplan-Meier analysis and covariate-adjusted Cox-proportional hazard regression for biochemical recurrence (BCR), clinical progression (CP), and cancer-specific survival (CSS). Results: Among 770 men who underwent RP without neo-adjuvant treatment, median follow-up was 85.7 months. Patients with bilateral SVI had higher preoperative prostate-specific antigen levels and clinical T stage (all p<0.001). Extracapsular extension, tumor volume, lymph node metastasis (p<0.001), pathologic Gleason grade group (p<0.001), and resection margin positivity (p<0.001) were also higher in patients with bilateral SVI. The 5-, 10-, and 15-year BCR-free survival rates were 23.9%, 11.7%, and 8.5%; CP-free survival rates were 82.8%, 62.5%, and 33.4%; and CSS rates were 96.4%, 88.1%, and 69.5%, respectively. The bilateral SVI group demonstrated significantly lower BCR, CP-free survival rates, and CSS rates all (p<0.001). Bilateral SVI was independently associated with BCR (HR 1.197, 95% CI 1p=0.049), CP (p=0.022), and CSS (p=0.038) in covariate-adjusted Cox regression. Conclusion: Bilateral SVI is a robust, independent prognostic factor for poor oncological outcomes in pT3b prostate cancer.

Validation of an algorithm for sound-based voided volume estimation.

A voiding diary is commonly used in clinical practice to monitor urinary tract health. However, manual recording and use of a measuring cup can cause significant inaccuracy and inconvenience. Recently sound-based voided volume estimation algorithms such as proudP have shown potential to accurately measure the voided volumes of patients urination while overcoming these inconveniences. In order to validate the sound-based voided volume estimation algorithm, we chose bodyweight change after urination as a reference value. Total 508 subjects from the United States and Korea were enrolled. 584 data points that have matching bodyweights change data and urination sound data were collected, and fivefold cross validation was performed in order to evaluate the model on all data in the dataset. The mean voided volume estimated by the algorithm was 202.6 mL (SD: ± 114.8) while the mean bodyweight change after urination was 208.0 g (SD: ± 121.5), and there was a strong linear correlation with high statistical significance (Pearson's correlation coefficient = 0.92, p-value < 0.001). Two paired t-test showed the equivalence with bodyweight change data with 10 mL margin. Additionally, a Bland-Altman plot shows a mean difference of - 5.5 mL with LoA (- 98.0, 87.1). The results support high performance of the algorithm across the large population data from multi-site clinical trials.

Modeling lateral carbon fluxes for agroecosystems in the Mid-Atlantic region: Control factors and importance for carbon budget.

Estimating lateral carbon fluxes in agroecosystems presents challenges due to intricate anthropogenic and biophysical interactions. We used a modeling technique to enhance our comprehension of the determinants influencing lateral carbon fluxes and their significance in agroecosystem carbon budgets. The SWAT-C model was refined by incorporating a dynamic dissolved inorganic carbon (DIC) module, enhancing our ability to accurately quantify total lateral carbon fluxes. This improved model was calibrated using observed data on riverine particulate organic carbon (POC) and dissolved organic carbon (DOC) fluxes, as well as net ecosystem exchange (NEE) data monitored by a flux tower situated in a representative agricultural watershed, the Tuckahoe Watershed (TW) of the Chesapeake Bay's coastal plain. We assessed the losses of POC, DOC, and DIC across five primary rotation types: C (continuous carbon), CS (corn-soybean), CSS (corn-soybean-soybean), CWS (corn-wheat-soybean), and CWSCS (corn-wheat-soybean-corn-soybean). Our study revealed notable variations in the average annual fluxes of POC (ranging between 152 and 198 kg ha-1), DOC (74-85 kg ha-1), and DIC (93-156 kg ha-1) across the five rotation types. The primary influencing factor for annual POC fluxes was identified as sediment yield. While both annual DOC and DIC fluxes displayed a marked correlation with surface runoff across all crop rotation schemes, soil respiration also significantly influenced annual DIC fluxes. Total lateral carbon fluxes (POC + DOC+DIC) constituted roughly 11 % of both net ecosystem production (NEP) and NEE, yet they represented a striking 95 % of net biome production (NBP) in the TW's agroecosystem. Grain yield carbon accounted for 80 % of both NEP and NEE and was nearly seven times that of NBP. Our findings suggest that introducing soybeans into cornfields tends to reduce NEP, NEE, and also NBP. Conversely, integrating winter wheat into the corn-soybean rotation significantly boosted NEP, NEE, and NBP values, with NBP even surpassing the levels in continuous corn cultivation.

Clinical value of prostate health index as an indicator for recommending magnetic resonance imaging in patients with gray-zone prostate-specific antigen level.

PURPOSE: To evaluate the usefulness of prostate health index (PHI) as an indicator for recommending magnetic resonance imaging (MRI) in patients with prostate-specific antigen (PSA) gray zone level < 10 ng/mL. METHODS: 443 patients who underwent prostate biopsy (PB) after serum PHI test and MRI between April 2019 and December 2022 were enrolled. For patients with visible lesion on MRI with Prostate Imaging Reporting and Data System Score (PI-RADS) ≥ 3, MRI-targeted PB was performed in addition to systematic 12-core PB. RESULTS: The optimal cutoff value of PHI for predicting PI-RADS ≥ 3 lesions was 39.6, which was significantly associated with overall prostate cancer (OR 3.07, p = 0.018) and clinically significant prostate cancer (csPCa) (OR 4.15, p = 0.006) at MRI-targeted PB cores. When MRI was restricted to patients with PHI ≥ 39.6 alone, 28.7% of unnecessary MRI could be saved at the cost of missing 13.6% of csPCa. When omitting MRI for patients with PHI < 39.6 and PSAD < 0.12 ng/mL2, unnecessary MRI could be reduced by 20.1% with the risk of missing 6.2% of csPCa. With addition of systematic PB, 21.0% of patients with negative MRI-targeted PB were diagnosed as csPCa. CONCLUSIONS: For patients in PSA gray zone, PHI of 39.6 might be an indicator for MRI and further MRI-targeted PB in additional to PSAD of 0.12 ng/mL2, reducing 20.1% of unnecessary MRI with the minimal risk of missing 6.2% of csPCa. To maximize csPCa detection, combining both MRI-targeted and systematic PB should be also considered.

Artificial intelligence-enhanced 12-lead electrocardiography for identifying atrial fibrillation during sinus rhythm (AIAFib) trial: protocol for a multicenter retrospective study.

Introduction: Atrial fibrillation (AF) is the most common arrhythmia, contributing significantly to morbidity and mortality. In a previous study, we developed a deep neural network for predicting paroxysmal atrial fibrillation (PAF) during sinus rhythm (SR) using digital data from standard 12-lead electrocardiography (ECG). The primary aim of this study is to validate an existing artificial intelligence (AI)-enhanced ECG algorithm for predicting PAF in a multicenter tertiary hospital. The secondary objective is to investigate whether the AI-enhanced ECG is associated with AF-related clinical outcomes. Methods and analysis: We will conduct a retrospective cohort study of more than 50,000 12-lead ECGs from November 1, 2012, to December 31, 2021, at 10 Korean University Hospitals. Data will be collected from patient records, including baseline demographics, comorbidities, laboratory findings, echocardiographic findings, hospitalizations, and related procedural outcomes, such as AF ablation and mortality. De-identification of ECG data through data encryption and anonymization will be conducted and the data will be analyzed using the AI algorithm previously developed for AF prediction. An area under the receiver operating characteristic curve will be created to test and validate the datasets and assess the AI-enabled ECGs acquired during the sinus rhythm to determine whether AF is present. Kaplan-Meier survival functions will be used to estimate the time to hospitalization, AF-related procedure outcomes, and mortality, with log-rank tests to compare patients with low and high risk of AF by AI. Multivariate Cox proportional hazards regression will estimate the effect of AI-enhanced ECG multimorbidity on clinical outcomes after stratifying patients by AF probability by AI. Discussion: This study will advance PAF prediction based on AI-enhanced ECGs. This approach is a novel method for risk stratification and emphasizes shared decision-making for early detection and management of patients with newly diagnosed AF. The results may revolutionize PAF management and unveil the wider potential of AI in predicting and managing cardiovascular diseases. Ethics and dissemination: The study findings will be published in peer-reviewed publications and disseminated at national and international conferences and through social media. This study was approved by the institutional review boards of all participating university hospitals. Data extraction, storage, and management were approved by the data review committees of all institutions. Clinical Trial Registration: [cris.nih.go.kr], identifier (KCT0007881).

Detecting causal relationship of non-floodplain wetland hydrologic connectivity using convergent cross mapping.

The hydrologic connectivity of non-floodplain wetlands (NFWs) with downstream water (DW) has gained increased importance, but connectivity via groundwater (GW) is largely unknown owing to the high complexity of hydrological processes and climatic seasonality. In this study, a causal inference method, convergent cross mapping (CCM), was applied to detect the hydrologic causality between upland NFW and DW through GW. CCM is a nonlinear inference method for detecting causal relationships among environmental variables with weak or moderate coupling in nonlinear dynamical systems. We assumed that causation would exist when the following conditions were observed: (1) the presence of two direct causal (NFW → GW and GW → DW) and one indirect causal (NFW → DW) relationship; (2) a nonexistent opposite causal relationship (DW → NFW); (3) the two direct causations with shorter lag times relative to indirect causation; and (4) similar patterns not observed with pseudo DW. The water levels monitored by a well and piezometer represented NFW and GW measurements, respectively, and the DW was indicated by the baseflow at the outlet of the drainage area, including NFW. To elucidate causality, the DW taken at the adjacent drainage area with similar climatic seasonality was also tested as pseudo DW. The CCM results showed that the water flow from NFW to GW and then DW was only present, and any opposite flows did not exist. In addition, direct causations had shorter lag time than indirect causation, and 3-day lag time was shown between NFW and DW. Interestingly, the results with pseudo DW did not show any lagged interactions, indicating non-causation. These results provide the signals for the hydrologic connectivity of NFW and DW with GW. Therefore, this study would support the importance of NFW protection and management.

Partial gland ablation using high-intensity focused ultrasound versus robot-assisted radical prostatectomy: a propensity score-matched study.

Background: We compared the clinical outcomes of robot-assisted radical prostatectomy (RARP) and partial gland ablation (PGA) using high-intensity focused ultrasound (HIFU) in localized prostate cancer. Methods: We analyzed 3,859 patients who had undergone RARP and PGA using HIFU. According to the propensity score for each treatment, 137 patients after PGA were matched to 3,722 patients after RARP at a 1:4 ratio using the nearest neighbor method. Results: The matched cohort comprised 685 subjects (RARP, 548; PGA, 137), with a median follow-up period of 22 months. Treatment failures were identified in 13.9% and 9.1% of patients in the PGA and RARP groups, respectively, after a median follow-up of 36 months postoperatively. Kaplan-Meier analyses revealed significantly longer failure-free (P < 0.001) and salvage-free survival (P = 0.003) in the RARP group than in the PGA group. There was no significant difference in the postoperative urinary symptom score (P = 0.748), but the postoperative erectile function score was significantly higher in the PGA group (P < 0.001). The rate of urinary incontinence (any pad) was significantly lower in the PGA group than that in the RARP group (P < 0.001). Postoperative complications were more frequent in the PGA group (P = 0.003); however, there was no significant difference in high-grade complications (≥3) (P = 0.467). Conclusion: PGA using HIFU showed statistically inferior oncological outcomes compared with RARP for failure-free survival and salvage-free survival. However, functional outcomes regarding postoperative incontinence and erectile dysfunction were more favorable in the PGA group.

Cytoreductive nephrectomy in the age of immunotherapy-based combination treatment.

Renal cell carcinoma (RCC) displays a wide spectrum of oncological prognosis and clinical behavior, and is noted for its generally poor outcome in metastatic settings. However, the introduction of immunotherapy after the cytokine era has changed the landscape of treatment for metastatic RCC, outperforming previous targeted therapy and providing new hope for patients with advanced disease. Cytoreductive nephrectomy (CN) has been the center of controversy, with questionable survival benefit when compared to systemic therapy. Despite discouraging results from the two randomized clinical trials (CARMENA & SURTIME), interest into the role of CN is being rekindled, and contemporary real-world studies provide supporting evidence to suggest that CN may still have a role in well-selected patients treated or expecting treatment with immunotherapy, not only for symptomatic control but also for oncological benefit. In this review article, we attempt to review the modern insight into the role of CN for metastatic RCC in contemporary medicine, with a focus on treatment with immune checkpoint inhibitor combination-based immunotherapy.

Artificial intelligence-enhanced electrocardiography for early assessment of coronavirus disease 2019 severity.

Despite challenges in severity scoring systems, artificial intelligence-enhanced electrocardiography (AI-ECG) could assist in early coronavirus disease 2019 (COVID-19) severity prediction. Between March 2020 and June 2022, we enrolled 1453 COVID-19 patients (mean age: 59.7 ± 20.1 years; 54.2% male) who underwent ECGs at our emergency department before severity classification. The AI-ECG algorithm was evaluated for severity assessment during admission, compared to the Early Warning Scores (EWSs) using the area under the curve (AUC) of the receiver operating characteristic curve, precision, recall, and F1 score. During the internal and external validation, the AI algorithm demonstrated reasonable outcomes in predicting COVID-19 severity with AUCs of 0.735 (95% CI: 0.662-0.807) and 0.734 (95% CI: 0.688-0.781). Combined with EWSs, it showed reliable performance with an AUC of 0.833 (95% CI: 0.830-0.835), precision of 0.764 (95% CI: 0.757-0.771), recall of 0.747 (95% CI: 0.741-0.753), and F1 score of 0.747 (95% CI: 0.741-0.753). In Cox proportional hazards models, the AI-ECG revealed a significantly higher hazard ratio (HR, 2.019; 95% CI: 1.156-3.525, p = 0.014) for mortality, even after adjusting for relevant parameters. Therefore, application of AI-ECG has the potential to assist in early COVID-19 severity prediction, leading to improved patient management.

3D vascularized microphysiological system for investigation of tumor-endothelial crosstalk in anti-cancer drug resistance.

Despite the advantages of microfluidic system in drug screening, vascular systems responsible for the transport of drugs and nutrients have been hardly considered in the microfluidic-based chemotherapeutic screening. Considering the physiological characteristics of highly vascularized urinary tumors, we here investigated the chemotherapeutic response of bladder tumor cells using a vascularized tumor on a chip. The microfluidic chip was designed to have open-top region for tumor sample introduction and hydrophilic rail for spontaneous hydrogel patterning, which contributed to the construction of tumor-hydrogel-endothelium interfaces in a spatiotemporal on-demand manner. Utilizing the chip where intravascularly injected cisplatin diffuse across the endothelium and transport into tumor samples, chemotherapeutic responses of cisplatin-resistant or -susceptible bladder tumor cells were evaluated, showing the preservation of cellular drug resistance even within the chip. The open-top structure also enabled the direct harvest of tumor samples and post analysis in terms of secretome and gene expressions. Comparing the cisplatin efficacy of the cisplatin-resistant tumor cells in the presence or absence of endothelium, we found that the proliferation rates of tumor cells were increased in the vasculature-incorporated chip. These have suggested that our vascularized tumor chip allows the establishment of vascular-gel-tumor interfaces in spatiotemporal manners and further enables investigations of chemotherapeutic screening.

Computer tomography-based shape of tumor contour and texture of tumor heterogeneity are independent prognostic indicators for clinical T1b-T2 renal cell carcinoma.

PURPOSE: To evaluate association between computer tomography (CT)-based features of renal cell carcinoma (RCC) and survival outcomes. METHODS: Data of 958 patients with clinical T1b-T2 RCC who underwent partial/radical nephrectomy from June 2003 to March 2022 were retrospectively evaluated. CT images of patients were reviewed by two radiologists for texture analysis of tumor heterogeneity and shape analysis of tumor contour. Patients were divided into three groups according to patterns of CT-based features: (1) favorable feature group (n = 117); (2) intermediate feature group (n = 606); and (3) unfavorable feature group (n = 235). Kaplan-Meier survival analysis and multivariate Cox regression analysis were performed to evaluate overall survival (OS), cancer-specific survival (CSS), and recurrence-free survival (RFS). RESULTS: RCCs with unfavorable CT-based feature showed larger size on CT, higher nuclear grade, higher rate of histologic necrosis, and higher rate of capsular invasion than those in the other two groups (all p < 0.001). Unfavorable feature was associated with poorer OS (p = 0.001), CSS (p < 0.001), and RFS (p < 0.001) on Kaplan-Meier analysis. In multivariate analysis, intermediate and unfavorable features were independent predictors for recurrence (hazard ratio [HR] 2.51, 95% confidence interval [CI] 1.09-5.79, p = 0.031 and HR 3.71, 95% CI 1.58-8.73, p = 0.003, respectively), but not for overall death or RCC-specific death. CONCLUSIONS: A combination of irregular tumor contour feature with heterogeneous tumor texture feature on CT is associated with poor RFS in clinical T1b-T2 RCC preoperatively.

Hybrid model for daily streamflow and phosphorus load prediction.

Environmental factors, such as climate change and land use changes, affect water quality drastically. To consider these, various predictive models, both process-based and data-driven, have been used. However, each model has distinct limitations. In this study, a hybrid model combining the soil and water assessment tool and the reverse time attention mechanism (SWAT-RETAIN) was proposed for predicting daily streamflow and total phosphorus (TP) load of a watershed. SWAT-RETAIN was applied to Hwangryong River, South Korea. The hybrid model uses the SWAT output as input data for the RETAIN. Spatial, meteorological, and hydrological data were collected to develop the SWAT to generate high temporal resolution data. RETAIN facilitated effective simultaneous prediction. The SWAT-RETAIN exhibited high accuracy in predicting streamflow (Nash-Sutcliffe efficiency (NSE): 0.45, root mean square error (RMSE): 27.74, percent bias (PBIAS): 22.63 for test sets), and TP load (NSE: 0.50, RMSE: 423.93, PBIAS: 22.09 for test sets). This result was evident in the performance evaluation using flow duration and load duration curves. The SWAT-RETAIN provides enhanced temporal resolution and performance, enabling the simultaneous prediction of multiple variables. It can be applied to predict various water quality variables in larger watersheds.

Assessing the impacts of dam/weir operation on streamflow predictions using LSTM across South Korea.

Recently, weather data have been applied to one of deep learning techniques known as "long short-term memory (LSTM)" to predict streamflow in rainfall-runoff relationships. However, this approach may not be suitable for regions with artificial water management structures such as dams and weirs. Therefore, this study aims to evaluate the prediction accuracy of LSTM for streamflow depending on the availability of dam/weir operational data across South Korea. Four scenarios were prepared for 25 streamflow stations. Scenarios #1 and #2 used weather data and weather and dam/weir operational data, respectively, with the same LSTM model conditions for all stations. Scenarios #3 and #4 used weather data and weather and dam/weir operational data, respectively, with the different LSTM models for individual stations. The Nash-Sutcliffe efficiency (NSE) and the root mean squared error (RMSE) were adopted to assess the LSTM's performance. The results indicated that the mean values of NSE and RMSE were 0.277 and 292.6 (Scenario #1), 0.482 and 214.3 (Scenario #2), 0.410 and 260.7 (Scenario #3), and 0.592 and 181.1 (Scenario #4), respectively. Overall, the model performance was improved by the addition of dam/weir operational data, with an increase in NSE values of 0.182-0.206 and a decrease in RMSE values of 78.2-79.6. Surprisingly, the degree of performance improvement varied according to the operational characteristics of the dam/weir, and the performance tended to increase when the dam/weir with high frequency and great amount of water discharge was included. Our findings showed that the overall LSTM prediction of streamflow was improved by the inclusion of dam/weir operational data. When using dam/weir operational data to predict streamflow using LSTM, understanding of their operational characteristics is important to obtain reliable streamflow predictions.

CUDC­907 suppresses epithelial­mesenchymal transition, migration and invasion in a 3D spheroid model of bladder cancer.

CUDC­907 is a novel inhibitor of phosphoinositide 3­kinase and histone deacetylase. It exerts anticancer activities by inducing apoptosis and inhibiting the growth and metastases of various tumors. However, the anticancer effects of CUDC­907 on bladder cancer have not been previously reported. Thus, the present study aimed to examine the anticancer effects of CUDC­907 on 2D monolayer and 3D spheroid models of T24 cells established from highly malignant human grade III urinary bladder carcinoma and cisplatin­resistant T24R2 cells generated by 17 months of exposure to cisplatin, starting at 0.01 µg/ml and increasing stepwise to 2 µg/ml. CUDC­907 treatment significantly reduced the cell viabilities of the monolayer and spheroid cultures in a concentration­dependent manner. The IC50 value of CUDC­907 was higher in the bladder cancer spheroids than in the monolayers. Treatment with CUDC­907 suppressed epithelial­mesenchymal transition via decreasing vimentin and E­cadherin and consequently inhibited the migration and invasion of the bladder cancer spheroids. In addition, it promoted apoptosis and increased the expression of apoptosis­related genes, such as Bax and caspases. In conclusion, CUDC­907 exerted anticancer effects by reducing the viability, migration and invasion, and inducing apoptosis of bladder cancer spheroids. These results suggest that CUDC­907 is a potent agent for the treatment of bladder cancer.

Artificial intelligence-estimated biological heart age using a 12-lead electrocardiogram predicts mortality and cardiovascular outcomes.

Background: There is a paucity of data on artificial intelligence-estimated biological electrocardiography (ECG) heart age (AI ECG-heart age) for predicting cardiovascular outcomes, distinct from the chronological age (CA). We developed a deep learning-based algorithm to estimate the AI ECG-heart age using standard 12-lead ECGs and evaluated whether it predicted mortality and cardiovascular outcomes. Methods: We trained and validated a deep neural network using the raw ECG digital data from 425,051 12-lead ECGs acquired between January 2006 and December 2021. The network performed a holdout test using a separate set of 97,058 ECGs. The deep neural network was trained to estimate the AI ECG-heart age [mean absolute error, 5.8 ± 3.9 years; R-squared, 0.7 (r = 0.84, p < 0.05)]. Findings: In the Cox proportional hazards models, after adjusting for relevant comorbidity factors, the patients with an AI ECG-heart age of 6 years older than the CA had higher all-cause mortality (hazard ratio (HR) 1.60 [1.42-1.79]) and more major adverse cardiovascular events (MACEs) [HR: 1.91 (1.66-2.21)], whereas those under 6 years had an inverse relationship (HR: 0.82 [0.75-0.91] for all-cause mortality; HR: 0.78 [0.68-0.89] for MACEs). Additionally, the analysis of ECG features showed notable alterations in the PR interval, QRS duration, QT interval and corrected QT Interval (QTc) as the AI ECG-heart age increased. Conclusion: Biological heart age estimated by AI had a significant impact on mortality and MACEs, suggesting that the AI ECG-heart age facilitates primary prevention and health care for cardiovascular outcomes.

Machine learning based prediction for oncologic outcomes of renal cell carcinoma after surgery using Korean Renal Cell Carcinoma (KORCC) database.

We developed a novel prediction model for recurrence and survival in patients with localized renal cell carcinoma (RCC) after surgery and a novel statistical method of machine learning (ML) to improve accuracy in predicting outcomes using a large Asian nationwide dataset, updated KOrean Renal Cell Carcinoma (KORCC) database that covered data for a total of 10,068 patients who had received surgery for RCC. After data pre-processing, feature selection was performed with an elastic net. Nine variables for recurrence and 13 variables for survival were extracted from 206 variables. Synthetic minority oversampling technique (SMOTE) was used for the training data set to solve the imbalance problem. We applied the most of existing ML algorithms introduced so far to evaluate the performance. We also performed subgroup analysis according to the histologic type. Diagnostic performances of all prediction models achieved high accuracy (range, 0.77-0.94) and F1-score (range, 0.77-0.97) in all tested metrics. In an external validation set, high accuracy and F1-score were well maintained in both recurrence and survival. In subgroup analysis of both clear and non-clear cell type RCC group, we also found a good prediction performance.

Germline DNA-Repair Genes and HOXB13 Mutations in Korean Men with Metastatic Prostate Cancer: Data from a Large Korean Cohort.

PURPOSE: Germline mutations in DNA damage repair (DDR) genes such as BRCA2 have been associated with prostate cancer (PC) risk but has not been thoroughly evaluated for metastatic prostate cancer (mPC) in Asian men. This study attempts to evaluate frequency of DDR mutations in the largest cohort of Koreans. MATERIALS AND METHODS: We recruited 340 patients with mPC unselected for family history of cancer and compared to 495 controls. Whole genome sequencing was applied to assess germline pathogenic/likely pathogenic variants (PV/LPVs) in 26 DDR genes and HOXB13, including 7 genes (ATM, BRCA1/2, CHEK2, BRIP1, PALB2, and NBN) associated with hereditary PC. Comparisons to published Caucasian and Japanese cohorts were performed. RESULTS: Total of 28 PV/LPVs were identified in 30 (8.8%) patients; mutations were found in 13 genes, including BRCA2 (15 men [4.41%]), ATM (2 men [0.59%]), NBN (2 men [0.59%], and BRIP1 (2 men [0.59%]). Only one patient had HOXB13 mutation (0.29%). A lower rate of overall germline variant frequency was observed in Korean mPC compared to Caucasians (8.8% vs. 11.8%), but individual variants notably differed from Caucasian and geographically similar Japanese cohorts. PV/LPVs in DDR genes tended to increase gradually with higher Gleason scores (GS 7, 7.1%; GS 8, 7.5%; GS 9-10, 9.9%). CONCLUSIONS: BRCA2 was the most frequently mutated gene common to different cohorts supporting its importance, but differences in variant distribution in Korean mPC underscore the need for ethnic-specific genetic models. Future ethnic-specific analyses are warranted to verify our findings.