Search Results (69)

Background/Objectives: Neoadjuvant cisplatin-based chemotherapy (NAC) followed by radical cystectomy (RC) is a standard treatment for cisplatin-eligible patients with muscle-invasive bladder cancer (MIBC), yet baseline tools to refine prognostic stratification remain limited. We aimed to develop and internally validate a clinicopathological nomogram integrating the neutrophil-to-lymphocyte ratio (NLR) to estimate event-free survival (EFS) in patients with MIBC treated with NAC. Methods: We retrospectively analyzed 210 patients with cT2–T4aN0–1M0 MIBC treated with cisplatin-based NAC at two Spanish institutions between 2010 and 2021. Candidate predictors included demographic, clinicopathological, and routine laboratory variables. A multivariable Cox model with backward selection based on the Akaike information criterion (AIC) was used to derive the final model, and internal validation was performed using 1000 bootstrap resamples. Results: Sex, age, prior non–muscle-invasive bladder cancer (NMIBC), and NLR were retained in the final nomogram. The model showed moderate discrimination, with a Harrell’s c-index of 0.60 and an optimism-corrected c-index of 0.58. The nomogram stratified patients into low-, intermediate-, and high-risk groups, with median EFS not reached, 47.5 months, and 18.0 months, respectively. High-risk patients also showed lower pathological complete response (pCR) rates. Conclusions: This exploratory nomogram integrates an accessible systemic inflammatory marker with baseline clinical variables to identify patients with poorer outcomes despite NAC. External validation in contemporary cohorts is warranted before clinical implementation. Full article

Background: Medication adherence is essential for effective management of chronic conditions, particularly among older adults with complex chronic conditions (CCCs). The Simplified Medication Adherence Questionnaire (SMAQ) is a brief self-report instrument widely used to assess adherence; however, its psychometric properties have not been evaluated in Albanian older populations. Objective: To assess the psychometric properties of the SMAQ in Albanian older adults with CCCs. Methods: A multicenter, cross-sectional study was conducted among 727 adults aged ≥65 years with two or more chronic conditions recruited from primary healthcare centers in southern Albania. Internal consistency was assessed using Cronbach’s alpha and McDonald’s ω. Construct validity was evaluated through exploratory and confirmatory factor analyses and correlations with clinical and behavioral variables. Discriminative validity was examined using known-group approach and independent samples t-tests, and criterion validity was assessed using Spearman correlations. Results: The SMAQ demonstrated good internal consistency (α = 0.799, ω = 0.821). Factor analyses supported a unidimensional structure, with all items loading significantly onto a single factor. Model fit indices indicated acceptable fit (CFI = 0.921; SRMR = 0.051), although RMSEA suggested some misfit (0.116). Non-adherent participants had significantly higher SMAQ scores than adherent participants (p < 0.001), indicating strong discriminative validity. Conclusions: The SMAQ is a reliable and valid tool for assessing medication adherence among Albanian older adults with CCCs, supporting its use in primary healthcare and research settings. Full article

The middle and lower reaches of the Yangtze River Basin occupy a strategically pivotal position in regional development; yet extreme drought-runoff events pose severe threats to water supply and ecological security. Despite this, systematic research gaps persist, including the lack of a unified definition, standardized identification criteria, and clear understanding of formation mechanisms for extreme drought-runoff. To address these limitations, this study focused on extreme drought-runoff in the basin, utilizing 1956–2024 discharge data from four mainstream hydrological stations and meteorological data from 171 stations. Quantitative discrimination criteria were established via Pearson-III frequency analysis; meteorological characteristics were analyzed using the Meteorological Drought Comprehensive Index; and formation mechanisms were explored through partial correlation analysis and multiple linear regression. This study innovatively proposed a basin-wide three-level quantitative discrimination criterion for drought-runoff based on the June–November flow frequency of key mainstream stations, which is distinguished from single-indicator drought identification methods (SPI/SPEI/SSI) by integrating basin-scale hydrological coherence and seasonal drought characteristics. The results revealed basin-wide extreme drought-runoff in 2006 and 2022, severe drought-runoff in 1972 and 2011, and relatively severe drought-runoff in 1959, 1992, and 2024. Typical extreme drought-runoff events were characterized by sustained low precipitation and high temperatures. Meteorological factors emerged as the primary driver during June–September, while reservoir operation and riverine water intake played secondary roles. Notably, the large-scale reservoir group in the Yangtze River Basin (53 key control reservoirs) helped alleviate drought-runoff impacts from December to May (non-flood season) via water supplementation. These findings provide a robust scientific basis for precise drought-runoff prediction and the development of targeted adaptation strategies in the Yangtze River Basin. Full article

Filtering constitutes a critical step in the post-processing of airborne Light Detection And Ranging (LiDAR) data. Over the past decade, machine learning has emerged as a prominent methodological paradigm across numerous disciplines, attracting significant research interest in its application to LiDAR filtering. From a machine learning perspective, filtering is essentially a binary classification task that aims to discriminate between ground and non-ground points. However, the limited information inherent in point clouds often leads to the generation of highly correlated features, particularly those derived from height data, which can compromise filtering accuracy. To address this issue, feature selection becomes imperative. In this study, we employed height-based mutual information as a criterion to identify and eliminate less discriminative features for filtering. The AdaBoost (Adaptive Boosting) algorithm was adopted as the classifier for point cloud filtering. For each point, nineteen features were derived from the raw LiDAR point cloud based on height and other geometric attributes within a defined neighborhood. The performance of the proposed feature selection approach was evaluated using benchmark datasets provided by the International Society for Photogrammetry and Remote Sensing (ISPRS). Experimental results demonstrate that the method is effective and reliable. After removing three selected features, the average kappa coefficient improved, along with a reduction in three categories of error, although a slight increase in Type II error (0.15%) was observed. Full article

Background and Objectives: Anatomical staging alone insufficiently explains survival heterogeneity in patients with resected non-small cell lung cancer (NSCLC). Although inflammation-based biomarkers have demonstrated prognostic value, the clinical relevance of erythrocyte-derived indices—particularly mean corpuscular volume (MCV)—remains poorly characterized in this setting. This study evaluated the prognostic significance of preoperative MCV and examined whether its integration with the Noble and Underwood (NUn) score improves survival prediction. Methods: We retrospectively analyzed patients with stage I–IIIA NSCLC who underwent complete surgical resection. Associations between clinicopathological variables and overall survival (OS) were assessed using Cox proportional hazards models. Prognostic performance was evaluated using the concordance index and the integrated time-dependent area under the curve. Continuous variables were modeled on their original scale without dichotomization. Results: Model comparison using the Akaike Information Criterion indicated that incorporation of the composite NUn–MCV index into the intermediate model—comprising age, basal metabolic rate, American Society of Anesthesiologists physical status, pleural invasion, and pathological stage—provided a superior model fit compared with inclusion of the NUn score and MCV as separate covariates. On this basis, the composite NUn–MCV model was selected as the full model. Across all evaluations, the full model demonstrated consistently greater discriminative ability for survival prediction than both the intermediate model and the baseline model based solely on pathological stage. Conclusions: Preoperative MCV independently predicts OS in patients with resected stage I–IIIA NSCLC. Integration of MCV with the NUn score into a composite index provides incremental prognostic value beyond anatomical staging and established clinical factors, supporting its use as a complementary tool for postoperative risk stratification. Full article

Trees play a critical role in urban ecological protection and wind disaster mitigation, yet conventional Gaussian-based wind engineering models often underestimate extreme tree motions under turbulent flows. This study aims to clarify the statistical characteristics of tree wind-induced responses and develop a quantitative framework to distinguish Gaussian and non-Gaussian behaviors. Scaled aeroelastic tree models were tested in a boundary-layer wind tunnel under controlled turbulence intensity (0.05–0.19), mean wind speeds of 3.9–9.3 m/s, and leaf area index (LAI) of 0–2.46. Acceleration and displacement time histories of branches, crown center, and trunk were recorded. A Gaussian discrimination criterion was established using cumulative probability thresholds of skewness and kurtosis, supplemented by time-history and probability density verification. Results reveal that branch accelerations exhibit strong non-Gaussianity with heavy-tailed and asymmetric distributions, crown displacements show moderate non-Gaussianity, while trunk responses remain near-Gaussian due to higher stiffness. Under weak turbulence, Gamma and Lognormal distributions fit best; under strong turbulence, the Generalized Extreme Value (GEV) distribution prevails. A high-quantile GEV-based framework markedly reduces extreme response prediction bias compared with Gaussian assumptions. These findings provide a probabilistic basis for more accurate assessment of tree wind stability and the design of wind-resistant urban vegetation and shelterbelts. Full article

Background: Bladder cancer exhibits substantial heterogeneity, and accurate discrimination between non-muscle-invasive (NMIBC) and muscle-invasive disease (MIBC), as well as between low-grade (LG) and high-grade (HG) tumors, remains essential for appropriate clinical management. Established immunohistochemical (IHC) markers, such as p53, Ki-67, and E-cadherin, could be used in a new setting, but standardized cut-off values and their combined predictive value remain unclear. This study aimed to identify optimal cut-offs for these markers and to evaluate whether biomarker combinations enhance the discrimination of tumor grade and stage. Methods: A retrospective dataset of 568 cases of bladder cancer was analyzed. For each case, the expression of p53, Ki-67, and E-cadherin was quantified, and tumors were classified as NMIBC or MIBC, and as LG or HG. ROC-based cut-off selection was performed using Youden’s J criterion with 10-fold stratified cross-validation. E-cadherin was modelled using an inverted scale to reflect biological loss. Logistic regression models were used to evaluate the discriminatory performance of single markers, two-marker combinations, and a three-marker model. Cross-validated AUC values and optimal thresholds were reported. Results: Ki-67 showed the strongest single-marker performance for predicting both MIBC (AUC 0.842) and HG disease (AUC 0.813), with optimal cut-offs of ≥40% and ≥30%, respectively. p53 demonstrated moderate discrimination (AUC 0.778 for MIBC and 0.776 for HG), while E-cadherin, evaluated on an inverted scale, showed acceptable performance (AUC 0.746 for MIBC; 0.780 for HG). Combining markers yielded modest improvements, with the best performance observed for Ki-67 + E-cadherin (AUCs of 0.851 for MIBC and 0.838 for HG). Conclusions: Ki-67 is the most effective single biomarker for distinguishing invasive and HG bladder cancer, while E-cadherin provides complementary value. A two-marker panel combining Ki-67 and E-cadherin, using appropriate cut-offs, offers the highest overall performance and may serve as a practical tool for enhanced pathological stratification. Full article

Background: Endoscopic retrograde cholangiopancreatography (ERCP) is the primary treatment option for choledocholithiasis. However, this procedure carries an inherent non-negligible risk of complications, requiring precise indications and careful patient selection. Endoscopic ultrasonography (EUS) can verify the presence of bile duct stones prior to ERCP. The current ESGE recommendations permit ERCP in high-risk patients without confirmation; however, several individuals undergo ERCP without evident advantage, indicating a necessity for enhanced stratification. Objectives: We aim to evaluate the rate of EUS-validated choledocholithiasis in patients with suspected common bile duct (CBD) stones and to determine the predictors of residual stones. A secondary objective was to create and internally validate a streamlined scoring system to enhance risk assessment in ESGE high-risk patients. Methods: We conducted a retrospective analysis of patients who had endoscopic ultrasound for suspected choledocholithiasis from January 2023 to December 2024 at a tertiary center. Multivariate logistic regression determined independent predictors of retained calculi. A simplified score was derived from model coefficients and internally validated. Results: Among 438 examined patients, 186 were included and 87 had choledocholithiasis confirmed via EUS. ERCP was conducted in 81 patients and postponed for 6 patients due to contraindications. According to the ESGE criteria, 10 patients (5.4%) were classified as low risk, 92 (49.5%) as intermediate risk, and 84 (45.2%) as high risk for choledocholithiasis. For high-risk individuals, EUS identified stones in 45 (53.5%), while 39 (46.4%) experienced spontaneous clearance. Acute pancreatitis (aOR 0.075), cholangitis (aOR 6.939), and EUS CBD diameter (aOR 1.220 per mm) were independent predictors of stones. The resultant three-component score (−2 to +4 points) demonstrated effective discrimination (AUROC 0.788). A criterion of ≥2 resulted in 85.7% sensitivity and 59.0% specificity. Conclusions: Almost fifty percent of ESGE high-risk patients were not found to have CBD stones during EUS. Integrating EUS data with a straightforward predictive score may enhance risk classification and avert superfluous ERCP procedures. Full article

Early identification of cognitive precursors to literacy and numeracy is essential for promoting school readiness and preventing later learning difficulties. Digital assessment tools using touchscreen technology offer advantages of engagement, standardization, and efficiency. This study reports preliminary findings on the Digital Assessment for Preschoolers—Tool (DAP-T), a touchscreen-based battery for preschool children. A sample of 105 children (M = 61.43 months, SD = 10.38; age range = 38–72) completed eight tasks assessing visuomotor integration, literacy (letter knowledge, phonological awareness, notational awareness, Rapid Automatized Naming), and numeracy (non-symbolic quantity comparison, quantity recognition, counting, cardinality). A subsample (n = 47–61, depending on the measure) also completed the paper-based criterion tasks used for concurrent validity analyses. Item difficulty and discrimination, internal consistency (McDonald’s ω), concurrent validity, and factorial structure (SEM) were assessed. Results showed medium-to-low difficulty, age-related performance increases, and good discrimination in most tasks. Reliability was high (ω = 0.713–0.966), and correlations with criterion measures ranged from ρ = 0.52 to 0.95. The DAP-T showed promising psychometric properties as a rapid, standardized tool to detect early difficulties and guide targeted interventions. Full article

Background: Autism Spectrum Disorder (ASD) encompasses a range of neurodevelopmental conditions characterized by impairments in social communication, restricted and repetitive behaviors, and sensory sensitivities. Despite increased awareness, timely diagnosis in Türkiye remains limited due to the lack of culturally appropriate, psychometrically robust assessment tools. Objective: This study aimed to develop, validate, and standardize the Autism Behavior Assessment Scale (ABAS) as a reliable and culturally adapted tool for assessing ASD-related behaviors in individuals aged 3–24 years in Türkiye. Methods: Employing a three-phase, nine-step scale development framework, data were gathered from 1275 informants (parents and professionals) across 14 provinces. The ABAS comprises 36 items rated on a three-point Likert scale, spanning four subscales: Restricted Repetitive Behaviors & Sensory Sensitivity (RRBSS), Social Interaction (SI), Social Communication (SC), and Non-Developmental Speech (NDS). Psychometric analyses included exploratory and confirmatory factor analysis, reliability testing, and validation against established instruments. Results: The four-factor structure was confirmed via EFA and CFA with excellent model fit. The ABAS demonstrated strong internal consistency (α = 0.91–0.96), test–retest reliability (r = 0.83), and criterion validity (r = 0.93 with GARS-2-TV; r = 0.84 with U-ODKL). Discriminant validity analyses showed that the ABAS accurately differentiated individuals with ASD from individuals with intellectual disabilities (ID) and individuals with hearing impairments (AUC = 0.99). Conclusions: The ABAS is a psychometrically sound, developmentally sensitive, and culturally grounded instrument for identifying and monitoring ASD-related behaviors in Türkiye. It holds promise for improving early detection and guiding educational and clinical interventions. Full article

Quantum state discrimination (QSD) is a fundamental task in quantum information processing, improving the computation efficiency and communication security. Non-Hermitian (NH) PT-symmetric systems were found to be able to discriminate two quantum states better than the Hermitian strategy. In this work, we propose a QSD approach based on P-pseudo-Hermitian systems with real spectra. We theoretically prove the feasibility of realizing QSD in the real-spectrum phase of a P-pseudo-Hermitian system, i.e., two arbitrary non-orthogonal quantum states can be discriminated by a suitable P-pseudo-Hermitian Hamiltonian. In detail, we decide the minimal angular separation between two non-orthogonal quantum states for a fixed P-pseudo-Hermitian Hamiltonian, and we find the orthogonal evolution time is able to approach zero under suitable conditions, while both the trace distance and the quantum relative entropy are employed to judge their orthogonality. We give a criterion to choose the parameters of a P-pseudo-Hermitian Hamiltonian that evolves the two initial orthogonal states faster than a fixed arbitrary PT-symmetric one with an identical energy difference. Our work expands the NH family for QSD, and can be used to explore real quantum systems in the future. Full article

The article investigates the accuracy of nonparametric univariate density estimation methods applied to various Gaussian mixture models. A comprehensive comparative analysis is performed for four popular estimation approaches: adaptive kernel density estimation, projection pursuit, log-spline estimation, and wavelet-based estimation. The study is extended with modified versions of these methods, where the sample is first clustered using the EM algorithm based on Gaussian mixture components prior to density estimation. Estimation accuracy is quantitatively evaluated using MAE and MAPE criteria, with simulation experiments conducted over 100,000 replications for various sample sizes. The results show that estimation accuracy strongly depends on the density structure, sample size, and degree of component overlap. Clustering before density estimation significantly improves accuracy for multimodal and asymmetric densities. Although no formal statistical tests are conducted, the performance improvement is validated through non-overlapping confidence intervals obtained from 100,000 simulation replications. In addition, several decision-making systems are compared for automatically selecting the most appropriate estimation method based on the sample’s statistical features. Among the tested systems, kernel discriminant analysis yielded the lowest error rates, while neural networks and hybrid methods showed competitive but more variable performance depending on the evaluation criterion. The findings highlight the importance of using structurally adaptive estimators and automation of method selection in nonparametric statistics. The article concludes with recommendations for method selection based on sample characteristics and outlines future research directions, including extensions to multivariate settings and real-time decision-making systems. Full article

Roof water inrush accidents in coal mine driving roadways occur frequently in China, accounting for a high proportion of major coal mine water hazard accidents and causing serious losses. Aiming at the lack of research on the mechanism of roof water inrush in driving roadways and the difficulty of predicting water inrush accidents, this paper constructs a local damage criterion for coal–rock mass and a seepage–fracture coupling model based on peridynamics (PD) bond theory. It identifies three zones of water-conducting channels in roadway surrounding rock, the water fracture zone, the driving fracture zone, and the water-resisting zone, revealing that the damage degree of the water-resisting zone dominates the transformation mechanism between delayed and instantaneous water inrush. A discriminant function for the effectiveness of water-conducting channels is established, and a single-index prediction and evaluation system based on damage critical values is proposed. A “geometry damage” dual-control water inrush prediction model within the PD framework is constructed, along with a non-local action mechanism model and quantitative prediction method for water inrush. Case studies verify the threshold for delayed water inrush and criteria for instantaneous water inrush. The research results provide theoretical tools for roadway water exploration design and water hazard prevention and control. Full article

Background: Prevention and clinical management of musculoskeletal injuries have historically focused on the assessment and training of modifiable physical factors, but perceptual decision-making has only recently been recognized as a potentially important capability. Immersive virtual reality (VR) systems can measure the speed, accuracy, and consistency of body movements corresponding to stimulus–response instructions for the completion of a forced-choice task. Methods: A cohort of 26 female college soccer players (age 19.5 ± 1.3 years) included 10 players who participated in a baseline assessment, 10 perceptual-response training (PRT) sessions, a post-training assessment that preceded the first soccer practice, and a post-season assessment. The remaining 16 players completed an assessment prior to the team’s first pre-season practice session, and a post-season assessment. The assessments and training sessions involved left- or right-directed neck rotation, arm reach, and step-lunge reactions to 40 presentations of different types of horizontally moving visual stimuli. The PRT program included 4 levels of difficulty created by changes in initial stimulus location, addition of distractor stimuli, and increased movement speed, with ≥90% response accuracy used as the criterion for training progression. Perceptual latency (PL) was defined as the time elapsed from stimulus appearance to initiation of neck rotation toward a peripheral virtual target. The speed–accuracy tradeoff was represented by Rate Correct per Second (RCS) of PL, and inconsistency across trials derived from their standard deviation for PL was represented by intra-individual variability (IIV). Perceptual Decision Efficiency (PDE) represented the ratio of RCS to IIV, which provided a single value representing speed, accuracy, and consistency. Statistical procedures included the bivariate correlation between RCS and IIV, dependent t-test comparisons of pre- and post-training metrics, repeated measures analysis of variance for group X session pre- to post-season comparisons, receiver operating characteristic analysis, and Kaplan–Meier time to injury event analysis. Results: Statistically significant (p < 0.05) results were found for pre- to post-training change, and pre-season to post-season group differences, for RCS, IIV, and PDE. An inverse logarithmic relationship was found between RCS and IIV (Spearman’s Rho = −0.795). The best discriminator between injured and non-injured statuses was PDE ≤ 21.6 (93% Sensitivity; 42% Specificity; OR = 9.29). Conclusions: The 10-session PRT program produced significant improvement in perceptual decision-making that appears to provide a transfer benefit, as the PDE metric provided good prospective prediction of musculoskeletal injury. Full article

Background: Locally acting gastrointestinal (GI) drugs present challenges for generic drug development because traditional bioequivalence measures, which rely on systemic drug levels, do not reflect local efficacy. This review examines regulatory guidelines for establishing therapeutic equivalence for such drugs, using rifaximin—a minimally absorbed, gut-localized antibiotic—as a case study. Methods: We reviewed bioequivalence guidelines from the United States Food and Drug Administration (FDA) and European Medicines Agency (EMA), along with the literature on rifaximin’s biopharmaceutical and clinical properties, to identify strategies and challenges for establishing equivalence for locally acting GI drugs. Results: Rifaximin exemplifies the limitations of standard bioequivalence methods: as a Biopharmaceutics Classification System (BCS) class IV drug with minimal absorption and low solubility, in vitro dissolution may not predict local drug availability. Clinical endpoint trials (e.g., traveler’s diarrhea, hepatic encephalopathy, IBS-D) are resource-intensive and insensitive to formulation differences. Pharmacokinetic (PK) studies in healthy volunteers show low, variable plasma levels, which may inaccurately discriminate between formulations. The EMA requires evidence of non-saturable absorption to accept PK data, a difficult-to-establish but potentially irrelevant criterion. Differences between FDA and EMA approaches highlight a lack of harmonization, complicating global generic development. Conclusions: A tailored, multifaceted approach is needed to demonstrate bioequivalence for GI-localized drugs like rifaximin. This case underscores the need for more sensitive surrogate methods (e.g. advanced in vitro or pharmacodynamic models) and flexible regulatory criteria. Harmonization across international guidelines and innovative bioequivalence study designs are key to facilitating the approval of safe and effective generic alternatives in this drug class. Full article