Search Results (214)

Soluble B-cell maturation antigen (sBCMA), generated by shedding of the plasma-cell receptor BCMA/TNFRSF17, is a circulating marker of plasma-cell burden in multiple myeloma (MM). We investigated whether early sBCMA kinetics capture treatment-induced changes in disease biology and predict subsequent Quality of Response (QoR) beyond free light chain (FLC)-based measures. In this prospective longitudinal study, 100 patients with newly diagnosed or relapsed MM starting treatment were evaluated at baseline, 1 month, and 6 months. sBCMA, involved FLC (iFLC), and involved-to-uninvolved FLC ratio (rFLC) were measured, and a 6-month response was assigned according to International Myeloma Working Group criteria. All biomarkers decreased significantly after treatment initiation (p < 0.0001). Across disease-status cohorts, sBCMA, but not iFLC or rFLC, differed at baseline and showed significantly different 1-month percentage reductions. Larger early decreases in sBCMA, iFLC, and rFLC were associated with deeper 6-month responses. In ordinal logistic regression including the three biomarkers dichotomized by a 50% reduction threshold at 1 month, only sBCMA remained independently associated with QoR; patients with <50% sBCMA reduction had higher odds of worse 6-month response (OR 5.44, 95% CI 1.58–18.76; p = 0.007). These findings support early sBCMA kinetics as a biologically informative marker for short-term response monitoring in MM. Full article

Background: Response to neoadjuvant therapy in locally advanced rectal cancer (LARC) is heterogeneous, and early identification of non-responders may help optimize treatment strategies and reduce unnecessary toxicity. This study aimed to develop and internally validate a machine learning model based on radiomic features extracted from baseline magnetic resonance imaging (MRI) to predict treatment response defined according to MRI tumor regression grade (mrTRG) at restaging MRI. Methods: In this retrospective single-center study, 86 patients with histologically confirmed LARC who underwent baseline and restaging MRI, neoadjuvant therapy, and surgery were included. Primary tumors were manually segmented on oblique axial T2-weighted images. A total of 107 radiomic features were extracted using PyRadiomics (vrs 3.0.1), with and without N4 bias field correction. Feature selection was performed using LASSO, followed by elastic net–regularized logistic regression. Model performance was evaluated using repeated stratified 5-fold cross-validation (20 repetitions). Treatment response was defined according to MRI tumor regression grade (mrTRG) at restaging, dichotomized into responders (mrTRG ≤ 2) and non-responders (mrTRG ≥ 3). Results: The model achieved a mean area under the receiver operating characteristic curve (AUC-ROC) of 0.73, with an accuracy of 72.5%, sensitivity of 79.2%, and specificity of 50%. Conclusions: Baseline MRI-based radiomics shows potential for identifying patients at higher risk of non-response to neoadjuvant therapy in LARC. However, limited specificity and the absence of external validation restrict immediate clinical applicability. Further validation in larger multicenter cohorts and integration with clinical variables are warranted to improve model robustness and generalizability. Full article

We introduce a local phase-field framework for spin-entanglement correlations. In this framework, the relevant hidden variable is an internal scalar phase associated with each fermion and derived from two underlying real fields. The fields are assumed to evolve locally in ordinary spacetime. When a particle pair is produced at a common spacetime event, the pair acquires a shared phase-locking condition at creation; after separation, the two internal phases evolve independently and no nonlocal interaction is introduced. Spin measurements by Stern–Gerlach analyzers are modeled as local filtering operations. Each local response depends only on the internal phase carried by the particle and on the orientation of the local analyzer. The local response function A(α,λ) = cos(λ − 2α) is derived from the spinorial transformation law of the underlying real field pair and the projection geometry of the detector interaction; it is not a phenomenological ansatz. From these deterministic local responses we derive an analog correlator. The raw product moment of the continuous detector outputs evaluates to ⟨AB⟩ = −½ cos 2(α − β), which satisfies classical Clauser-Horne-Shimony-Holt (CHSH) bounds. After Pearson normalization—the operationally appropriate correlation measure for continuous analog detector outputs, justified by channel-contrast physics and scale invariance—the normalized correlator yields E(α,β) = −cos 2(α − β), matching the quantum singlet correlator in functional form. When this normalized correlator is inserted into the CHSH expression, it yields the numerical value 2√2. This result is a structural consequence of the reduced marginal variance of continuous response functions relative to the unit-variance dichotomic observables assumed in Bell’s derivation; it does not constitute a violation of Bell’s inequality. The model does not reproduce quantum singlet statistics at the level of binary detector outcomes, where the correlator takes a triangular rather than cosine form. The contribution is therefore ontological and conceptual rather than predictive. The framework preserves parameter independence and no-signaling throughout. It provides a concrete real-field ontology for spin correlations based on internal phase structure, and it demonstrates that the functional form of the quantum singlet correlation can be obtained from a strictly local deterministic description, provided that the detector responses are treated as continuous analog quantities and normalized accordingly. We compare the model with earlier phase-based approaches and discuss experimental configurations—including time-resolved and multi-stage Stern–Gerlach measurements—that could in principle probe the proposed internal-phase dynamics at the pre-registration level. Full article

Background and Objectives: Tumor-infiltrating lymphocytes (TIL) and the neutrophil-to-lymphocyte ratio (NLR) are each associated with prognosis in melanoma, yet their combined prognostic value remains insufficiently defined. We aimed to assess whether integrating NLR and TILs into a combined immune phenotype improves prediction of recurrence-free survival (RFS) in patients with resected cutaneous melanoma. Materials and Methods: A total of 203 patients were included. Receiver operating characteristic analysis identified an NLR cut-off of 2.75 for RFS, defining low (<2.75) and high (≥2.75) groups. TIL status was dichotomized as present or absent. According to the combined NLR–TIL profile, patients were initially categorized into three immune phenotypes: favorable (low NLR and TIL-positive), intermediate (low NLR and TIL-negative or high NLR and TIL-positive), and unfavorable (high NLR and TIL-negative). For the dichotomized analysis, the intermediate and unfavorable phenotypes were combined and compared with the favorable phenotype. Associations of clinicopathological factors with RFS were evaluated using Kaplan–Meier curves and Cox regression models. Results: The median follow-up was 56 months. In the univariate analysis, stage III disease, greater Breslow thickness, increased mitotic rate, and absence of adjuvant therapy were associated with worse RFS. In addition, patients with an unfavorable immune phenotype had a markedly increased risk of recurrence compared with those in the favorable group (HR 2.86, 95% CI 1.43–5.71; p = 0.004). In multivariate Cox regression analysis, both the unfavorable immune phenotype and stage III disease independently predicted RFS (HR 2.25, 95% CI 1.11–4.54; p = 0.024 and HR 2.13, 95% CI 1.03–4.43; p = 0.041, respectively). Conclusions: Combined assessment of systemic inflammation and tumor-local immune response using NLR and TILs may provide meaningful prognostic stratification in resected cutaneous melanoma. Full article

Background: Autologous stem cell transplantation (ASCT) is a standard treatment for relapsed or high-risk lymphoma. While disease-related factors are well-known, the impact of host-related factors like nutritional status remains less defined. We aimed to evaluate the prognostic value of the prognostic nutritional index (PNI) and other factors in lymphoma patients undergoing ASCT. Methods: We conducted a single-center retrospective cohort study including adult patients with Hodgkin and non-Hodgkin lymphoma who underwent ASCT between January 2015 and December 2023. Pre-transplant clinical, laboratory, and transplant-related variables were analyzed. The prognostic nutritional index (PNI) was calculated using serum albumin and absolute lymphocyte count and dichotomized according to the cohort median. Progression-free survival (PFS) and overall survival (OS) were evaluated using Kaplan–Meier and Cox regression analyses. We conducted a retrospective single-center cohort study including adult patients with Hodgkin and non-Hodgkin lymphoma who underwent ASCT between January 2015 and December 2023. Results: A total of 43 patients were included. Median age was 38 years, and 72.1% were male. Patients transplanted in complete remission (CR) had significantly longer PFS compared with those transplanted in partial remission (PR) (log-rank p = 0.022). Patients with higher pre-ASCT PNI demonstrated significantly improved PFS (median 45 vs. 7 months; log-rank p = 0.021). In multivariable Cox regression analysis, both higher PNI (HR 0.39; 95% CI 0.16–0.97; p = 0.043) and complete remission prior to ASCT (HR 0.41; 95% CI 0.17–0.98; p = 0.046) remained independently associated with improved PFS. Higher infused CD34⁺ (hematopoietic stem cell) dose was associated with shorter hospitalization but showed no statistically significant association with engraftment kinetics or survival. No variable was independently associated with OS, likely due to the limited number of death events. Conclusions: Pre-transplant prognostic nutritional index and disease response independently predict progression-free survival after ASCT in lymphoma. These findings highlight the complementary role of host-related and disease-related factors in transplant outcomes and suggest that PNI may serve as a practical tool for pre-transplant risk stratification and patient optimization. Given the small sample size and limited number of events, these findings should be interpreted with caution. Full article

In intelligence research, the sharing of item response data from cognitive ability assessments is often restricted by privacy concerns, while traditional parametric simulation methods frequently fail to capture complex response dependencies. This study proposes a neural network copula (NNC) framework for generating synthetic dichotomous item response data that preserves essential psychometric properties without revealing sensitive examinee information. By decoupling the modeling of marginal item probabilities from the dependence structure using a deep autoencoder and kernel density estimation, the framework accommodates the discrete nature of binary item response data while minimizing distributional assumptions. Validation against large-scale empirical data demonstrated high correspondence across multiple facets. At the data consistency level, the NNC-based synthetic data reproduced total score distributions and inter-item correlations. Psychometrically, the method yielded consistent item characteristic curve parameter estimates, item fit statistics, and test information functions. Furthermore, Monte Carlo replications demonstrated algorithmic stability and inferential precision. Full article

Comparison of two or multiple groups based on dichotomous items is a central task in item response theory (IRT) linking. This article considers the two-parameter logistic scaling model under sparse differential item functioning (DIF) in item intercepts and DIF-free item discriminations. Robust-mean-geometric-mean (RMGM) and robust Haberman (RHAB) linking are compared across several loss functions and under scaling models with noninvariant or invariant item discriminations. Two simulation studies show that invariant item discriminations improve the precision of estimated group means. In addition, the $L_0$ loss function is generally preferable to the $L_1$ and $L_{0.5}$ loss functions when DIF proportions or sample sizes are large. Several empirical examples illustrate the proposed specifications. Full article

Background: Reliable biomarkers that capture tumor–host interactions and predict treatment resistance in extensive-stage small cell lung cancer (SCLC) remain limited. We evaluated the prognostic and predictive value of the pretreatment lactate dehydrogenase-to-albumin ratio (LAR), an integrative biomarker reflecting metabolic activity, systemic inflammation, and host nutritional status. Methods: This multicenter, retrospective cohort study included patients with extensive-stage SCLC treated at five tertiary centers between 2016 and 2024. Pretreatment LAR was calculated using baseline serum lactate dehydrogenase and albumin levels and dichotomized using a Youden index-derived cut-off at the 12-month overall survival (OS) horizon. Time-dependent receiver operating characteristic (ROC) analyses using inverse probability weighting were performed to assess discriminative performance. Survival outcomes were evaluated using Kaplan–Meier estimates and Cox proportional hazards models. Associations with platinum resistance and lack of objective treatment benefit (defined as progressive disease as best response) were examined using logistic regression models. Results: A total of 223 patients were included. Elevated LAR was associated with inferior OS (median, 15.8 vs. 25.2 months; log-rank p < 0.001) and progression-free survival (7.9 vs. 11.5 months; p < 0.001). In multivariable analysis, LAR remained independently associated with OS (HR, 1.43; 95% CI, 1.04–1.95; p = 0.028). LAR demonstrated modest but consistently superior discriminative performance compared with other inflammatory indices for both 12-month OS (area under the curve [AUC], 0.692) and 6-month progression-free survival (PFS) (AUC, 0.646), with statistically significant differences in DeLong comparisons. Higher LAR was independently associated with increased odds of platinum resistance (adjusted odds ratio [aOR], 2.31; 95% CI, 1.41–3.81; p = 0.001) and lack of objective treatment benefit (adjusted OR, 2.04; 95% CI, 1.33–3.14; p = 0.001). Conclusions: Pretreatment LAR is a clinically accessible and biologically integrative biomarker associated with survival and treatment resistance in extensive-stage SCLC. By capturing tumor–host interactions, LAR may support risk stratification and identify patients at increased risk of early treatment failure. Prospective validation is warranted to define its role in biomarker-driven clinical decision-making. Full article

Given South Korea’s acute land constraints and ambitious renewable energy targets, floating solar farms (FSFs) on multi-purpose dam reservoirs offer a sustainable land-sparing solution for advancing the water-energy nexus and climate adaptation. This study estimates households’ willingness to pay (WTP) for a tariff premium supporting FSFs on multi-purpose dam reservoirs—a bundled sustainability attribute encompassing land-sparing deployment, water-energy nexus synergies (90% evaporation reduction, hydropower complementarity), and avoided land-use conflicts—relative to equivalent electricity from land-based solar farms (LSFs). The valuation scenario explicitly frames FSFs as an integrated policy package, not an isolated engineering characteristic, with balanced disclosure of location-specific trade-offs. The study highlights the sustainability value of land-sparing water-energy nexus solutions in South Korea. The analysis draws on a nationwide contingent valuation survey of 1000 households conducted from mid-April to mid-May 2025. Employing the one-and-one-half-bound dichotomous choice format with a spike model to handle zero WTP responses, we estimate a mean tariff premium of KRW 26.8 (USc 1.9) per kWh—17% of the residential rate. This exceeds the current FSF-LSF levelized cost differential (KRW 19 per kWh), despite 49% zero bids largely from protest responses. Socioeconomic factors (education, income, female gender, metropolitan residence, policy awareness) significantly shape acceptance probabilities. These findings affirm meaningful support for FSF deployment, contributing to long-term sustainability by integrating renewable energy with water resource management and reducing land-use conflicts. They also inform sustainable energy transition policies by showing that consumers are willing to fund multifunctional infrastructure synergies. Full article

The concentration of tourist flows along short urban links caused by cruise stops in medium-sized Mediterranean ports exacerbates traffic and localized environmental externalities. This study evaluates the willingness to pay (WTP) of cruise passengers for an electric tram that would connect the Gaženica Port with Zadar’s historic center, an intervention designed to cut travel time and reduce on-street congestion and emissions. Over the course of two seasons, a two-wave, two-site, in-person survey was conducted at the port and in the city center. The instrument adopts a double-bounded dichotomous choice (DBDC) contingent valuation design with randomized starting bids that were calibrated using a pre-test that benchmarked prevailing transport pricing. Primary WTP estimates are obtained from a binary choice model with socio-demographic and environmental covariates; whereby inference relies on cluster-robust errors. Robustness is assessed through three complementary checks that do not require additional data: (i) a bivariate specification to account for within-respondent correlation between first and follow-up bids; (ii) Turnbull nonparametric bounds for the interval-censored WTP distribution; and (iii) starting-point tests using split-sample estimation and bid-set indicators. A spike adjustment based on “no–no at the lowest bid” responses is explored where appropriate. Beyond its methodological contribution, this research advances the sustainable tourism development discourse by quantifying visitors’ financial support for low-emission urban mobility infrastructure that mitigates environmental stresses while preserving residential life quality. The results integrate cruise tourist management with the more general goals of resilient and sustainable urban destinations by offering a decision-ready value input for port-city mobility planning in historic Mediterranean centers. Full article

Background: Benign paroxysmal positional vertigo (BPPV) is the most common cause of peripheral vertigo and is diagnosed clinically, yet many patients initially present in primary care. Early identification may optimize referral and management. Objective: To perform a pilot Phase 1 validation of the Benign Paroxysmal Positional Vertigo Screening Questionnaire (BPPV-SQ), a brief screening questionnaire designed for future use in general practice (primary care settings where patients are initially evaluated by general practitioners), assessing its ability to identify BPPV, suggest canal involvement, and support progression to Phase 2 validation. Methods: In this prospective observational study, 108 patients with positional vertigo and no neurological signs were evaluated in a specialist setting. The 7-item dichotomous questionnaire (score 0–3 for diagnostic core) was administered prior to bedside examination, which served as the reference standard. Results: Higher questionnaire scores were associated with an increased probability of confirmed BPPV. Among patients with the maximum score of 3, BPPV was confirmed in 73.5% of cases, with a lateralization concordance of 69.4% between questionnaire responses and specialist diagnosis. In contrast, lower scores (0–1) were associated with a markedly lower rate of confirmed BPPV (14.3%). Conclusions: In this pilot Phase 1 validation, the BPPV-SQ demonstrated score-dependent diagnostic reliability and acceptable lateralization agreement in high-score patients, supporting progression to Phase 2 validation in primary care. Full article

Episodic future thinking (EFT) has been confirmed as a promising cognitive intervention for enhancing prospective memory (PM), yet emerging evidence suggests its effects may depend on the specificity of induction. The current study investigated this issue by dichotomizing EFT into two distinct methods: specific (researcher-guided detailed mental simulations) versus non-specific (participants’ self-guided imagination), implemented through differentially structured future thinking instructions. We also analyzed the distinct cognitive strategies mainly employed under each EFT condition based on the Dynamic Multiprocess Framework. The latent profile analysis (LPA) was further conducted to characterize individual variability in responsiveness to EFT manipulations. Behavioral results revealed comparable PM accuracy improvements across both EFT methods relative to the control group; moreover, specific EFT uniquely accelerated response times for both PM and ongoing task execution. The LPA further identified three distinct EFT response patterns—self-competent, proactive, and reactive—each exhibiting unique state-dependent cognitive characteristics. These findings provide a refined understanding of the EFT-PM relationship: (1) specific EFT facilitates more automatic retrieval of PM intentions, whereas non-specific EFT predominantly engages strategic monitoring; (2) individual differences in baseline mental images influence the effectiveness of EFT methods, suggesting the potential benefits of personalized intervention approaches for PM enhancement. Full article

Small-scale (e.g., classroom) assessment represents the most common and needed scenario for cognitive diagnostic testing. In such settings, polytomously scored items (e.g., constructed-response tasks) are widely used, as they provide more fine-grained measurement of students’ skills and cognitive processes. However, a significant gap remains between the current methods and pressing practical needs. On one hand, parametric cognitive diagnosis models capable of handling polytomous response data require large samples for stable estimation, making them unsuitable for small-scale classroom use. On the other hand, existing nonparametric classification methods, while robust in small samples, are largely confined to dichotomous (0/1) response data. There is a lack of dedicated nonparametric methods for polytomous responses, creating a disconnect between practical testing and diagnostic tools. To address this real-world necessity, this study proposes the seq-GNPED method. It extends the generalized nonparametric classification framework to polytomous data by introducing weighted ideal category response and a collapsed class iterative algorithm. Simulations and empirical applications confirm that seq-GNPED achieves robust and accurate diagnosis under small sample conditions where parametric models falter, effectively leveraging the informational richness of polytomous items. This work bridges a critical gap by providing a practical, nonparametric tool tailored for fine-grained, classroom-ready cognitive diagnosis. Full article

Background: Screening patients admitted to internal medicine for hyperferritinemia might reveal a dichotomy between normoferritinemic inflammation and hyperferritinemic inflammation phenotypes, opening new research into innate immunity activation during acute inflammation. Methods: We identified 4514 consecutive patients screened for CRP and ferritin on admission. Patients with CRP ≤ 150 mg/L were excluded. We selected 100 patients with the lowest (normoferritinemic inflammation) and 100 with the highest (hyperferritinemic inflammation) ferritin concentrations. Sub-analysis of 39 CRP-matched pairs (±15 mg/L) and multivariable logistic regression—adjusting for age, sex, sepsis, malignancy, CRP, and comorbidities—were performed. Results: Groups did not differ significantly by age (p = 0.068) or sex (p = 0.319). Mortality was significantly higher in the hyperferritinemic inflammation group (41% vs. 7%, p < 0.001), a trend maintained in non-malignant (31.1% vs. 6.5%, p < 0.001) and CRP-matched (25.6% vs. 2.6%, p = 0.012) subgroups. Multivariable regression confirmed hyperferritinemic inflammation as a significant independent predictor of mortality (OR 3.726; 95% CI 1.304–10.647; p = 0.014), even after adjusting for the Charlson Comorbidity Index. Conclusions: Significant inflammation accompanied by hyperferritinemic inflammation is associated with elevated mortality compared to normoferritinemic inflammation, suggesting a dichotomous divergence of the inflammatory response. Full article

Background: Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection and remains a leading cause of mortality in intensive care units (ICUs). Although the Sequential Organ Failure Assessment (SOFA) score is widely used for prognostic stratification, organ dysfunction represents a downstream manifestation of sepsis, whereas immune and inflammatory dysregulation may precede overt organ failure. Monocyte distribution width (MDW) is a novel hematological parameter reflecting monocyte activation and is approved for the diagnosis of sepsis; however, its prognostic value and potential role within composite biomarker models in critically ill surgical patients with sepsis remain incompletely defined. Methods: We conducted a prospective, observational, single-center pilot study in two surgical intensive care units between November 2022 and December 2023. Adult patients with sepsis defined according to Sepsis-3 criteria were enrolled. Laboratory and clinical variables—including MDW, neutrophil-to-lymphocyte ratio (NLR), C-reactive protein (CRP), procalcitonin (PCT), and SOFA score—were measured on admission and during the first five days of ICU stay. Patient-level median values across five days were used for analysis. The primary outcome was in-hospital mortality. Prognostic performance was assessed using receiver operating characteristic (ROC) curve analysis and logistic regression. A composite bioscore was constructed by combining dichotomized MDW, NLR, CRP, and PCT values. Results: Sixty patients were included; 24 (40%) died during hospitalization. Non-survivors were older and had significantly higher SOFA scores. MDW, NLR, CRP, and PCT were significantly higher in non-survivors. SOFA demonstrated the strongest discriminative ability for mortality prediction (AUC 0.839, 95% CI 0.730–0.948). Among biomarkers, NLR (AUC 0.741) and PCT (AUC 0.714) showed good discriminative performance, while MDW (AUC 0.690) and CRP (AUC 0.662) showed moderate discrimination; MDW exhibited the highest specificity (80.6%). In multivariable analysis with individual biomarkers, only SOFA remained an independent predictor of mortality. The composite bioscore demonstrated good discriminative ability (AUC 0.805) and, when evaluated alongside SOFA, remained independently associated with fatal outcome (OR 11.92, 95% CI 1.76–80.75); however, given the modest sample size and wide confidence intervals, this finding should be interpreted with caution. Repeated-measures correlation analysis revealed no strong collinearity among biomarkers. Conclusions: A composite bioscore incorporating MDW, NLR, CRP, and PCT provides prognostic information comparable to SOFA and remains independently associated with mortality. This approach may complement organ dysfunction-based assessment and support early risk stratification in sepsis. Full article