Search Results (237)

C-reactive protein (CRP) level, platelet-to-lymphocyte ratio (PLR), and neutrophil-to-lymphocyte ratio (NLR) have been proposed as biomarkers that reflect disease severity in canine chronic enteropathies. Their correlation with the Canine Chronic Enteropathy Clinical Activity Index (CCECAI) remains unclear. The objective of the present meta-analysis was to assess the correlation between CCECAI and hematological and immunological markers in dogs with CIE. A meta-analysis was conducted to evaluate the correlation of CRP, PLR, and NLR with CCECAI as a diagnostic marker. The PRISMA guidelines were followed to accomplish this procedure. Pooled correlation coefficients were calculated using Fisher’s Z-transformation under random effects models. Heterogeneity and publication bias were examined using standard procedures for the meta-analysis. Eleven studies were found to be fit: five for CRP, four for NLR, and four for PLR. The pooled correlation for CRP level was 0.229 (95% CI: 0.143–0.311, p < 0.001), with consistent findings across studies (I² = 0%). PLR demonstrated a moderate correlation (pooled r = 0.381, 95% CI: 0.238–0.508, p < 0.001; I² = 41%), while NLR showed a slightly stronger correlation (pooled r = 0.410, 95% CI: 0.286–0.521, p < 0.001) but with substantial heterogeneity (I² = 68%). Publication bias analyses indicated modest asymmetry for CRP and PLR, with Egger’s regression significant for both, whereas the NLR showed no clear evidence of bias. Trim-and-fill adjustments slightly attenuated the pooled estimates but did not alter the statistical significance. In conclusion, the correlation between CCECAI and NLR is the most promising biomarker, followed closely by PLR, whereas CRP has a weaker predictive value. The correlation between CCECAI and each of NLR and PLR may provide rapid and reliable diagnostic information about CIE in dogs. Full article

Noise contamination is a common challenge in the analysis of time series data, where stochastic perturbations can obscure deterministic dynamics and complicate the interpretation of signals from chaotic and physiological systems. Reliable identification of noise regimes and their intensity is therefore essential for robust analysis of dynamical and biomedical signals, where incorrect attribution of stochastic perturbations can lead to misleading interpretations of system behavior. For this reason, the present study examines the role of complexity-based descriptors for identifying stochastic perturbations in time series and analyzes how these metrics respond to different noise regimes across heterogeneous dynamical systems. A supervised learning approach based on complexity descriptors was developed to analyze controlled perturbations in multiple signal types. Gaussian, pink, and low-frequency noise disturbances were injected at predefined intensity levels into the Rössler and Lorenz chaotic systems, the Hénon map, and synthetic electrocardiogram signals, while AR(1) processes were used for validation on inherently stochastic signals. From these systems, eighteen entropy-based, fractal, statistical, and singular value decomposition-based complexity metrics were extracted from either raw signals or reconstructed phase spaces. These features were used to perform three classification tasks that capture different aspects of noise characterization, including detecting the presence of noise, identifying the perturbation type, and discriminating between different noise intensities. In addition to predictive modeling, the study evaluates the complexity profiles and feature relevance of the metrics under varying perturbation regimes. The results show that no single complexity metric consistently discriminates noise regimes across all systems. Instead, system-specific relevance patterns emerge. Under given experimental constraints (data partitioning, machine learning algorithm, etc.), Approximate Entropy provides the strongest discrimination for the Lorenz system and the Hénon map, the Coefficient of Variation, Sample and Permutation Entropy dominate classification for ECG signals, and the Condition Number and Variance of first derivative together with Fisher Information are most informative for the Rössler system. Across all datasets, the proposed framework achieves an average accuracy of 99% for noise presence detection, 98.4% for noise type classification, and 98.5% for noise intensity classification. These findings demonstrate that complexity metrics capture structural and statistical signatures of stochastic perturbations across a diverse set of dynamic systems. Full article

This study presents a systematic comparative benchmark between two distinct paradigms for solving nonlinear partial differential equations (PDEs): the data-driven Physics-Informed Neural Networks (PINNs) and the analytical Homotopy Analysis Method (HAM). We apply both methods to a unified family of canonical PDEs, the Burgers, Huxley, Fisher, Burgers–Huxley, and Burgers–Fisher equations, under identical problem setups, domain discretization, and validation metrics. PINNs incorporate physical laws directly into neural network training by minimizing a loss function that enforces PDE residuals, yielding physically consistent solutions even for strongly nonlinear problems. HAM provides approximate analytical solutions using a unified framework, and the same initial guess, auxiliary linear operator, and auxiliary function across all equations despite their distinct nonlinearities. The controlled, consistent application of both methods enables a fair, reproducible comparison across this equation family. The results provide a quantitative performance map under identical conditions, delineating when PINNs (high accuracy, long-term stability, and generalization capability) are preferable, versus when HAM (computational speed, short-term analytic approximation, and lower memory footprint) offers advantages. While the finite radius of convergence of the truncated HAM series is theoretically expected, our controlled comparison quantifies for the first time how this degradation varies across equation types, revealing that the choice between methods depends on specific problem requirements including error tolerance, available computational resources, and temporal horizon. The novelty lies not in solving each equation individually, but in deriving a performance taxonomy that systematically connects equation features (shocks, stiffness, and reaction–diffusion coupling) to optimal solver choice—providing previously unavailable, evidence-based guidance for the scientific computing community. This study establishes the first rigorous, controlled comparative benchmark between analytic and data-driven PDE solvers across a spectrum of nonlinearities, providing a reproducible baseline for future hybrid scientific machine learning solvers. Full article

Chronic lymphocytic leukemia (CLL) is uncommon in Asia, and longitudinal genomic data from Asian cohorts are limited. We conducted serial whole-exome sequencing (WES) in a multicenter Korean cohort of newly diagnosed, elderly CLL treated with chlorambucil–obinutuzumab to evaluate mutational heterogeneity and clonal hematopoiesis of indeterminate potential (CHIP) during treatment and follow-up. Tumor-only variants were filtered, restricted to nonsynonymous or loss-of-function coding/splice-site mutations, and summarized as a binary patient-by-gene matrix for principal component analysis (PCA), trajectory analysis, and k-means clustering. CHIP was defined as ≥1 qualifying mutation in a prespecified CHIP gene set. Baseline PCA was more compact in patients with complete response at end of treatment, whereas partial response or progressive disease cases were more dispersed. PCA trajectories were compact and directionally consistent in complete responders, more dispersed in partial responders, and highly heterogeneous without a dominant direction in progressive disease. Clustering identified dispersed and compact clusters, and CHIP-associated mutations were enriched in the dispersed cluster (55.6% vs. 8.3%, Fisher’s exact p = 0.0086). In paired samples collected 3–5 months after end of treatment, CHIP status changed in some patients. Serial WES may provide complementary information to treatment response, although these observations require confirmation in larger cohorts. Full article

Rapid and accurate detection of drug-resistant tuberculosis (DR-TB) is critical for effective treatment and containment. The Xpert^® MTB/XDR (GXXDR) assay is designed to detect Mycobacterium tuberculosis complex (MTBC) and resistance to isoniazid and second-line anti-TB drugs directly from clinical specimens. We evaluated the clinical performance of GXXDR using 61 MTBC-positive specimens with available phenotypic drug susceptibility testing results. GXXDR results were compared to a phenotypic drug susceptibility test (pDST) and whole-genome sequencing (WGS) to assess sensitivity, specificity, and concordance. Resistance to isoniazid, fluoroquinolones, amikacin, capreomycin, and ethionamide was analyzed. Sensitivity comparisons between GXXDR, WGS, pDST, and manufacturer data were performed using Fisher’s exact and Tango tests. GXXDR demonstrated a high specificity for most drugs and a strong sensitivity for isoniazid (93.8%) and fluoroquinolone (92.3%), consistent with manufacturer reports. In contrast, the sensitivity for amikacin (58.3%), capreomycin (35.7%), and ethionamide (27.3%) was significantly lower than stated by the manufacturer (91.9%, 84.0% and 64.7%, respectively), likely due to resistance mutations outside the assay’s target regions. Sensitivity concordance of GXXDR with WGS was high for all drugs, except ethionamide. The GXXDR assay enables rapid and reliable detection of isoniazid and fluoroquinolone resistance in clinical settings, though sensitivity for certain second-line drugs may be affected by regional genetic diversity. These findings underscore the importance of integrating local epidemiological data to optimize molecular diagnostics for DR-TB. Full article

Background: Aneurysmal subarachnoid hemorrhage (aSAH) is associated with high early mortality and long-term disability. Prognostic assessment relies mainly on neurological grading scales, which may incompletely capture the systemic metabolic response to acute brain injury. Non-thyroidal illness syndrome (NTIS), particularly low triiodothyronine syndrome (LT3S), is common in critical illness, but its prognostic relevance in aSAH remains unclear. Objectives: To evaluate the prognostic impact of early thyroid hormone alterations on 30-day mortality and early clinical outcomes including delayed cerebral ischemia (DCI) in patients with aSAH, with particular emphasis on the magnitude of triiodothyronine (T3) deficiency. Methods: We conducted a retrospective single-center observational cohort study of 157 consecutive adult patients admitted with confirmed aSAH between 2014 and 2025. Serum free triiodothyronine (fT3), free thyroxine (fT4), and thyroid-stimulating hormone (TSH) were measured within 72 h of admission. Hormone values were normalized to contemporaneous reference intervals to generate continuous reference-adjusted metrics (FT3_level, TSH_level). Associations with 30-day in-hospital mortality were analyzed using logistic regression and Cox proportional hazards models adjusted for admission variables including age, sex, APACHE II score, World Federation of Neurosurgical Societies grade, Fisher grade, and treatment modality. Results: Binary LT3S classification was frequent but not independently associated with 30-day mortality. In contrast, lower FT3_level values were significantly associated with increased mortality and shorter survival time. In logistic regression analyses, each 0.1 increase in FT3_level was associated with an 18% lower odds of death (adjusted OR 0.82, 95% CI 0.69–0.97). This association persisted after adjustment for established clinical severity measures and was concordant with time-to-event analyses. FT3_level was not correlated with TSH_level, consistent with NTIS. Endovascular coiling was associated with more pronounced peripheral fT3 deficiency (p < 0.05) but was not independently associated with mortality. FT3_level was not independently associated with early neurological status or functional outcome at hospital discharge. Conclusions: Lower FT3_level values were independently associated with higher 30-day mortality, indicating that early peripheral T3 reduction reflects clinically relevant metabolic vulnerability in aSAH. Full article

The digitalization of global supply chains and the increasing complexity of international trade have created both opportunities and challenges for customs administrations. The European Union has responded to these dynamics through the new EU customs reform, which aims to achieve full digital transformation and administrative harmonization across Member States. The study analyzes the preconditions for the reform through the lens of customs control, identifying its potential for modernization and the institutional challenges it poses. A quantitative survey was conducted among customs officers and economic operators in Bulgaria to assess their perceptions of the expected effects of the reform on communication, coordination, and control effectiveness. Using statistical methods, including the chi-square (χ²) test, Fisher’s exact test, and Cramér’s V test, the empirical results show statistically significant relationships between communication effectiveness, procedural consistency, and post-clearance control harmonization (p < 0.05). The strongest relationship is found between administrative communication and consistency in control implementation, confirming that harmonization depends not only on digital aggregation but also on institutional coordination mechanisms. The results show that the positive effects of the reform and the accompanying constraints are conditioned by administrative capacity, digital security, and sustainable trust between customs authorities and economic operators. Full article

Background/Objectives: Pediatric shock is a final common pathway of cardiovascular failure across diverse emergencies, yet data from mixed emergency cohorts outside intensive care units remain limited. This study aimed to describe the distribution, etiologic subtypes, and clinical correlates of shock in children presenting within a diagnosis-based emergency cohort. Methods: A retrospective single-centre study was conducted in children aged 0–16 years presenting with selected acute pediatric emergencies, among whom cases with and without shock were compared. Shock was defined using documented diagnoses and compatible hemodynamic features, and multiple etiologic types of shock were analyzed, including hypovolemic, septic, cardiogenic, and anaphylactic shock. Demographic and diagnostic variables—age, length of stay, organ support, age strata, and selected comorbidities—and baseline clinical features were compared between children with and without shock using non-parametric and χ²/Fisher’s exact tests. Results: Within the prespecified diagnosis-based analytic cohort, 36/128 children (28.1%) met the study criteria for shock and occurred across all prespecified acute pediatric emergency groups, with the highest proportional burden in heart failure and meningitis; this proportion should not be interpreted as an emergency-department prevalence estimate. Children with shock were younger, with clustering in infants < 1 year and those aged 5–9 years, and tended to stay longer in hospital. Pre-existing cardiac disease, severe dehydration, and altered mental status/coma were more frequent among children with shock. Septic and cardiogenic shock required the most intensive organ support. Conclusions: In this pediatric emergency cohort, shock emerged as a clinically relevant and etiologically heterogeneous complication across diverse acute presentations, with a distinct age-related vulnerability pattern and consistent associations with readily identifiable bedside clinical features. Simple bedside information—particularly cardiac comorbidity, dehydration, and altered consciousness—may assist the early recognition of children with evolving circulatory failure and support closer monitoring and timely escalation of care. By focusing on a mixed emergency population outside the intensive care unit, this study provides a real-world clinical perspective that may help refine early bedside assessment and improve vigilance for shock in pediatric emergency departments. Full article

Background/Objectives: Chronic lower limb ulcers represent a significant clinical challenge, with conventional therapies achieving healing in only 30–40% of complex cases. This study evaluated the comparative effectiveness of autologous blood clot therapy (ActiGraft, delivering platelet- and leukocyte-derived growth factors) and autologous micrograft therapy (Rigenera, containing viable progenitor cells) versus advanced wound dressings for refractory chronic wounds. Methods: This retrospective analysis of a prospectively collected, non-randomized clinical cohort included 132 patients with chronic lower limb ulcers refractory to prior therapy, who were treated between 2019 and 2024 at a single wound care center. The patients received ActiGraft (n = 32), Rigenera (n = 33), or advanced wound dressings (n = 67) based on their choice after informed discussion. The primary outcome was complete wound closure at 52 weeks. Multivariable Poisson regression with robust variance was performed, adjusting for baseline wound area (log-transformed), chronic renal failure, age, and peripheral vascular disease. Cox proportional hazards was used to model time to closure. Bonferroni correction (threshold p < 0.0167) was applied for three pairwise comparisons. This study was not pre-registered, and the results should be considered hypothesis-generating. Results: Unadjusted wound closure rates were 68.8% (ActiGraft; RR = 1.71, 95% CI: 1.17–2.48, p = 0.015), 60.6% (Rigenera; RR = 1.50, 95% CI: 1.01–2.25, p = 0.089), and 40.3% (advanced dressings). After multivariable adjustment, ActiGraft showed attenuated benefit (adjusted RR = 1.38, 95% CI: 0.86–2.21, p = 0.179), while the beneficial effect of Rigenera became non-significant (adjusted RR = 1.19, 95% CI: 0.73–1.94, p = 0.488). However, the adjusted Cox regression revealed significantly faster healing for ActiGraft (HR = 10.67, 95% CI: 4.17–27.30, p < 0.001) and Rigenera (HR = 4.12, 95% CI: 1.75–9.73, p = 0.001). Sensitivity analyses restricted to comparable wound sizes (≤10 cm²) showed a consistent direction of effect (ActiGraft 71.4% vs. Advanced 37.5%). Infection rates were lower in the autologous therapy groups (0–3.0% vs. 11.9%; Fisher’s exact p = 0.006). Conclusions: ActiGraft autologous blood clot therapy showed trends toward superior wound closure and demonstrated significantly faster healing compared to advanced dressings in patients with refractory chronic lower limb ulcers, with autologous micrograft therapy (Rigenera) showing intermediate results. Significant baseline imbalances in wound size limit causal inference from the closure rate comparisons. These hypothesis-generating findings from a non-randomized cohort warrant confirmation in adequately powered randomized controlled trials with stratification by wound characteristics. Full article

Mediterranean monk seal (Monachus monachus) sightings along the Lebanese coast were recorded between 2020 and 2025. This study aims to provide insights into the consistency of monk seal presence, their habitat use, and their feeding behaviour in the studied area. The research relied on photographic and video materials gathered from social media reports, as well as contributions from local fishers and divers. A total of 43 sightings were recorded, with photo-identification possible for 34 of these. The study confirmed the presence of at least three distinct individuals, including one adult female frequently utilizing marine caves in Amchit and Rawsheh. Video recordings of feeding behaviour revealed prey species such as grey mullet and octopus, which are also targeted by local fisheries, suggesting potential conflicts between the seals and the fishing sector. This study emphasizes the need for a more systematic, long-term monitoring approach, including the use of infrared cameras, to identify suitable habitats and more accurately assess seal presence. The research further recommends a region-wide effort to understand monk seal movements within the Levantine Basin and to support broader conservation initiatives for the species. Full article

Background/Objectives: Early childhood oral health is strongly influenced by parental and caregiver behaviors, yet evidence on the impact of sociodemographic factors remains limited in Eastern European settings. This study evaluated the association between parental and caregiver sociodemographic characteristics (age, educational level, and living environment) and oral health-related behaviors, dental attendance, and caries experience among preschool children in Romania. Methods: A cross-sectional study was conducted among parents or caregivers of children aged 0–6 years (n = 490). Data were collected between September and November 2025 using a structured online questionnaire (24 items). Statistical analyses included Fisher’s exact test, Mann–Whitney U test, Kruskal–Wallis test with post hoc analysis, and Spearman’s correlation (p < 0.05). Results: Higher parental education was consistently associated with favorable oral health behaviors, including earlier initiation of oral hygiene, parent-assisted toothbrushing, use of fluoridated toothpaste, and preventive dental visits (p < 0.01). Children of parents aged 21–30 years were more frequently caries-free (62.7%), whereas caries prevalence was higher among those with parents aged 41–50 years (60.5%) (p < 0.05). Urban residence was associated with twice-daily toothbrushing (49.4% vs. 36.2%) and earlier dental visits compared with rural residence (p < 0.05). Conclusions: Parental education, age, and living environment are significantly associated with early oral health behaviors and caries experience. Preventive programs should prioritize families with lower educational levels and those living in rural areas. Full article

The Atlantic blue crab (Callinectes sapidus) has rapidly expanded across the Mediterranean Sea, forming self-sustaining populations in coastal and transitional ecosystems. Its ecological plasticity, high reproductive potential, and tolerance to wide salinity and temperature ranges have enabled a rapid basin-wide colonization, particularly evident in Italian lagoons and estuaries. This invasion has generated substantial ecological alterations, such as predation on bivalves, competition with native decapods, and disruptions of trophic dynamics, as well as significant economic losses for fisheries and aquaculture sectors, especially in northern Adriatic clam-farming areas. Social perceptions vary widely, and management actions remain fragmented, limiting the effectiveness of control and mitigation efforts. This review analyzes the scientific and gray literature published from its first Mediterranean records to 2025, synthesizing evidence on the species’ distribution, ecological impacts, socio-economic consequences, and existing regulatory responses, with a focus on the Mediterranean basin and Italy. Studies on consumers’ and fishers’ perceptions are examined to identify emerging opportunities for sustainable utilization. By integrating ecological and socio-economic dimensions, the review outlines priority knowledge gaps and management needs, providing a science-based framework to support coordinated monitoring, adaptive control strategies, and potential valorization pathways consistent with the EU Green Deal, the Blue Economy, and Circular Bioeconomy principles. Full article

Marine reserves are areas where fishing mortality is reduced, and their effectiveness in enhancing fisheries depends on the magnitude of this reduction. We evaluated the effectiveness of two marine reserves in the Mediterranean that differed in enforcement levels using a dual approach that combined interviews with fishers and on-board sampling. Only the reserve with stricter fishing restrictions showed measurable stock enhancement. In areas adjacent to this reserve, catches were higher and body sizes were larger for some species. In addition, fishers adjusted their fishing gear when operating near this reserve, thereby targeting larger individuals. In contrast, no distance-related trends were detected around the reserve with weaker fishing restrictions. Both the interviews and on-board sampling produced consistent results regarding the effectiveness of the two reserves. Full article

The density power divergence (DPD) is a well-studied member of the Bregman divergence family and forms the basis of widely used minimum divergence estimators that balance efficiency and robustness. In this paper, we introduce and study a new sub-class of Bregman divergences, termed the exponentially weighted divergence (EWD), designed to generate competitive and practically interpretable inference procedures. The EWD is constructed so that its associated weight function remains bounded within the interval $[0, 1]$, which facilitates a transparent interpretation of robustness through controlled downweighting of low-density observations and avoids excessive influence from high-density points. We develop minimum EWD estimators (MEWDEs) within a general framework accommodating independent but non-homogeneous data, thereby extending classical minimum divergence theory beyond the i.i.d. setting. Under standard regularity conditions, we establish Fisher consistency and asymptotic normality, and we analyze robustness properties through influence function calculations. The EWD framework is further extended to parametric hypothesis testing, for which we derive the asymptotic null distribution of a Bregman divergence-based test statistic. Extensive simulation studies and real-data applications demonstrate that the proposed estimators perform comparably to, and often more robustly than, existing DPD-based procedures, particularly under moderate to heavy contamination, while retaining high efficiency under clean data. Overall, the EWD provides a tractable and interpretable alternative within the Bregman divergence class for robust parametric estimation and testing. Full article

Frustration is an intrinsic feature of molecular complexes, arising when individual constituents must distort from their optimal isolated geometries to achieve collective stabilization. Although energetic frustration can be defined as the average distortion energy associated with complex formation, its quantitative origin and its connection to other molecular descriptors remain insufficiently understood. In this work, we systematically investigate frustration in four representative molecular complexes—two homogeneous clusters, (H₂O)_n and (HF)_n, and two charged clusters, H₃O⁺(H₂O)_n and F⁻(H₂O)_n (n = 1–20)—using three complementary density-based frameworks: (i) total-energy decomposition, (ii) global conceptual DFT (CDFT) descriptors, and (iii) information-theoretic approach (ITA) quantities. Strong linear correlations between the total frustration energy and most energy components, as well as CDFT indices, are revealed, enabling a quantitative interpretation of frustration from energetic and electronic-structure perspectives. Among ITA measures, only a subset, including Shannon entropy, Ghosh–Berkowitz–Parr entropy, Rényi entropy, and the relative Fisher information, exhibits robust and consistent correlations with frustration across all systems, indicating their suitability as ITA-based frustration descriptors. Particularly, the (HF)_n clusters show uniformly excellent correlations for all descriptors due to their structurally simple and homogeneous hydrogen-bonding environment. Overall, this work provides a comprehensive density-based understanding of frustration and clarifies which descriptors reliably track its behavior. These insights establish a foundation for applying ITA and CDFT analyses to frustrated phenomena in broader chemical contexts, which could be applied to other systems, including molecular recognition, conformational dynamics, and catalysis. Full article