Search Results (5,573)

Introduction: This study presents the first systematic review and meta-analysis of randomized controlled trials (RCTs) evaluating the efficacy and safety of oral clonidine in spinal surgery to guide clinical practice and inform future research. Methods: RCTs were identified through four databases (PubMed, Scopus, Web of Science, Cochrane Central) up to August 2025. Risk of bias was assessed, and intraoperative and postoperative outcomes were extracted. Data were pooled using mean differences (MD) or risk ratios (RR) with 95% confidence intervals. Results: Eight RCTs with 474 patients (237 clonidine, 237 control) were included. Four studies had a low risk of bias, while two had some concerns, and two had a high risk. Clonidine had no impact on surgery duration but significantly reduced blood loss (MD = −177.76 mL), mean arterial pressure (MD = −11.33 mmHg), and heart rate (MD = −21.18 bpm). Regarding postoperative outcomes, clonidine was associated with improved analgesia, including lower pain scores up to 12 h and a longer time to first analgesic request, with no significant difference in pain scores at 24 h or total postoperative opioid consumption. No significant increase in postoperative complications, including bradycardia, dizziness, headache, or visual disturbances, was observed. Surgeon satisfaction was higher in the clonidine group. Despite high heterogeneity in some outcomes, sensitivity analyses confirmed the robustness of most findings. Conclusions: Prophylactic oral clonidine in spinal surgery significantly reduces blood loss, heart rate, and mean arterial pressure, with added analgesic benefits and good tolerability. Further high-quality RCTs are needed to confirm these results in broader patient populations. Full article

The roughness coefficient is a vital parameter in river dynamics calculations, and its accuracy is crucial for simulating water flow. Various factors contribute to channel roughness, and the underlying mechanisms are quite complex. There is a strong spatiotemporal correlation, which complicates the calculations, particularly when hydrological data is lacking or insufficient. In this study, we solved the two-dimensional shallow-water equations using the Population Simplex Evolution (PSE) with the Finite Volume Method (FVM). This approach allowed us to obtain samples for calibrating channel roughness coefficients. To enhance the analysis, we introduced a Convolutional Neural Network (CNN) to reduce the dimensionality of input parameters and extract the temporal characteristics of the flow series. Notably, we integrated a Transformer to capture the spatial characteristics of the time series. By combining the PSE-FVM with the CNN-Transformer, we effectively calibrated the roughness coefficients. Our findings indicated that the integrated PSE-FVM and CNN-Transformer model achieved high accuracy and efficiency in this calibration process. Specifically, the cross-correlation coefficients exceeded 0.90 for calibration results from September to December 2020. We recorded an average absolute deviation of 7 cm between the calculated and measured maximum water levels, and the average calibration runtime ratio was approximately 0.19% when comparing the CNN-Transformer to the PSE-FVM. Importantly, this approach could be used for rivers with incomplete hydrological data. Our work highlighted spatiotemporal correlations between roughness coefficients and their influencing factors, thereby facilitating the integration of river dynamics models with intelligent algorithms. Therefore, these findings may serve as a valuable reference for river numerical analysis, flood impact assessment, and the development of digital twins and information systems for water-related engineering projects. Full article

Despite recent advancements in solving the Capacitated Vehicle Routing Problem (CVRP), state-of-the-art learning-based methods remain hindered by costly offline training, while classical population solvers rely on implicit mechanisms and rigid parameter tuning. To bridge this methodological gap, this paper introduces the Group Learning Algorithm hybridized with a Multi-Armed Bandit (GLA-MAB), a training-free metaheuristic that transforms evolutionary search into an explicit, controllable learning process. The framework partitions the population into leader-learner groups to extract and inject proven topological structures directly into weaker solutions. Simultaneously, a hierarchical MAB layer oversees the search online, utilizing real-time reward feedback to dynamically manage operator selection and stagnation recovery. Furthermore, a spatial decomposition wrapper ensures strict scalability, extending the framework’s applicability to massive topologies of up to 1200 nodes. Comprehensive evaluations across 117 established CVRP benchmark instances validate the architecture’s efficacy. GLA-MAB achieves near-optimal convergence on classical instances, maintaining mean gaps below 0.03% on Sets A and E, and delivers highly competitive performance on large-scale heterogeneous sets such as Set Li. Ultimately, GLA-MAB provides the dynamic adaptability of modern artificial intelligence while completely eliminating the prohibitive overhead of offline dataset generation. Full article

Purpose: Meningo-ophthalmic and orbitomeningeal arterial communications comprise route-specific relationships between the middle meningeal artery (MMA) and the ophthalmic or orbital arterial system. Their recognition is relevant to middle meningeal artery embolization because orbital or ophthalmic collateral pathways may create routes for non-target embolization. This systematic review aimed to synthesize the prevalence and anatomical patterns of these communications, using quantitative pooling only where the anatomical definition and denominator were sufficiently coherent. Methods: This systematic review and meta-analysis were conducted according to PRISMA 2020 principles and registered in PROSPERO (CRD420261361050). Eligible studies were original human cadaveric anatomical, angiographic, or radiological investigations reporting MMA-ophthalmic or MMA-orbital arterial relationships. After the closure of the full-text retrieval audit, studies and extracted rows were audited by anatomical family, unit of analysis, numerator, denominator, and independence. No global pooled prevalence was calculated across anatomical families. When family-specific pooling was methodologically defensible, proportions were synthesized using logit transformation, restricted maximum likelihood random-effects models, and Hartung-Knapp confidence intervals. Results: Database searches identified 558 records. After removal of 228 duplicates, 330 records were screened, and 285 were excluded by title and abstract. Forty-five reports were sought for retrieval; 10 were not retrieved or were not available as assessable full-text reports after retrieval auditing. Thirty-five full-text reports were assessed; thirteen were excluded for reasons, and three were duplicate reports at the full-text stage. Nineteen studies were included in the qualitative synthesis, and 12 contributed independent data to the final R-ready matrix. MMA arising from the ophthalmic artery was uncommon, with a pooled prevalence of 0.03 (95% CI 0.01 to 0.13; I² = 75.9%). After excluding the clinically selected chronic subdural hematoma subgroup, the estimate was 0.02 (95% CI 0.01 to 0.06; I² = 7.7%). The meningolacrimal/lacrimal-MMA route yielded an exploratory pooled proportion of 0.45 (95% CI 0.09 to 0.86; I² = 95.9%), with substantial anatomical and methodological heterogeneity. Conclusions: The available evidence supports route-specific synthesis rather than a single global prevalence estimate. MMA arising from the ophthalmic artery appears uncommon but procedurally important; however, this estimate should be interpreted as a route-specific estimate across eligible angiographic/anatomical series rather than as a universal anatomical prevalence. Meningolacrimal and lacrimal-MMA routes are frequently described, but their prevalence remains difficult to generalize because detection methods, populations, and denominators differ across studies. Future anatomical and angiographic reports should standardize route definitions, laterality, unit of analysis, and denominator reporting to improve prevalence estimation and procedural safety interpretation. Full article

Background/Objectives: Postoperative atrial fibrillation (POAF) is a frequent complication after cardiac surgery and is associated with increased morbidity, prolonged hospitalization, and higher healthcare costs. Numerous multivariable prediction models have been developed to estimate individual risk; however, their methodological robustness, validation status, and clinical transportability remain uncertain. This systematic review aimed to critically evaluate the methodological quality, validation strategies, and predictive performance of multivariable prediction models developed to estimate the risk of postoperative atrial fibrillation (POAF) after cardiac surgery. Methods: In accordance with PRISMA 2020 guidelines, we conducted a comprehensive search of PubMed, Scopus, Web of Science, and Embase from inception to July 2025. Studies that developed or externally validated multivariable prediction models for POAF in adult patients undergoing cardiac surgery were eligible. Data extraction was performed using the CHARMS checklist, and methodological quality was assessed with PROBAST. Model performance was summarized descriptively, focusing on discrimination (C-statistic/AUC), calibration reporting, and validation strategies. Results: A total of 39 studies were included. Most models were based on logistic regression, whereas a minority employed Cox regression or machine learning techniques. Reported discrimination ranged from 0.60 to 0.98, demonstrating substantial heterogeneity in predictive performance. Calibration was inconsistently reported. Six studies performed external validation. According to PROBAST, 32 of 39 studies (82%) were rated at high risk of bias, predominantly within the analysis domain due to inadequate handling of overfitting, insufficient events-per-variable ratios, and limited validation procedures. Conclusions: Existing prediction models for POAF show variable discrimination but are frequently limited by high risk of bias, inadequate validation, and incomplete calibration assessment, thereby restricting their clinical applicability. Future research should prioritize rigorous external validation, transparent reporting in accordance with TRIPOD recommendations, and methodological strategies that enhance model generalizability and transportability across diverse surgical populations. Full article

The coast redwood forest, populated by the ancient relict species Sequoia sempervirens, provides unique and essential ecological services along the Pacific coast of California. It is a haven for endemism and ecological diversity, offers habitat for threatened species, and is an important global terrestrial carbon sink. However, a long history of resource extraction has significantly impacted this ecosystem. Complex old-growth forests have largely been replaced with managed timber stands, and biological diversity has been reduced through the loss of habitat and basic ecological functions. Under natural conditions, coast redwood is highly resilient to disturbance, due to its propensity for basal and epicormic sprouting. The primarily clonal reproductive strategy of S. sempervirens allows for natural thinning as a stand matures, generally leading to the development of late-seral characteristics without the need for active restoration. The increasingly pervasive use of active silvicultural tools for restoration, such as forest thinning and commercial timber harvest, can create a density-driven cycle that requires periodic re-application of the treatment and hinders natural successional processes. In order to restore forest health and resiliency, natural successional processes inherent to coast redwood can be supported as a restoration alternative. Full article

Background/Objectives: Following the COVID-19 pandemic, pertussis resurged sharply across Europe, with 209,674 cases reported in the EU/EEA in 2024. This study characterises the epidemiology of the 2024 pertussis resurgence across five counties of southeastern Romania, with emphasis on vaccination status, clinical severity, and regional surveillance performance. Methods: A retrospective, population-based analysis was conducted on 452 cases notified between February 2024 and January 2025, extracted from the national surveillance database. A pre-specified reclassification of PCR-positive cases yielded 326 confirmed cases. Categorical, non-parametric, correlation, and multivariate logistic regression analyses were performed. Results: The epidemic peaked in September 2024, with 56.0% of cases occurring between August and October. Children under five years accounted for 63.2% of confirmed cases, and 72.1% were not vaccinated according to age-appropriate schedule, predominantly due to parental refusal (43.0%) and non-attendance (36.6%). Pneumonia affected 36.8% of confirmed cases, ranging from 81.0% in infants under two months to 0% in adolescents. Age-appropriate vaccination was independently protective against pneumonia (adjusted OR = 0.53, 95% CI 0.29 to 0.96, p = 0.035; population attributable risk 37.3%). Significant inter-county heterogeneity was identified in PCR implementation (72 to 100%) and reporting delays. Conclusions: Vaccination gaps were the principal modifiable driver of the resurgence, supporting targeted coverage improvement and the introduction of a national maternal Tdap programme. Full article

Naturally derived psilocybin is widely used, yet its therapeutic potential, pharmacological distinctiveness and regulatory feasibility remain understudied. This review evaluates the potential of naturally derived psilocybin using a six-criterion framework to evaluate: (1) therapeutic benefit, (2) safety and tolerability, (3) pharmacological uniqueness vs. synthetic psilocybin, (4) identity and composition control, (5) dose precision and stability, and (6) ecological sustainability. This paper answers three key questions about naturally derived psilocybin: Does it show therapeutic potential? Does it differ from synthetic psilocybin? Can it meet medicinal standards? Findings suggest perceived therapeutic benefits from naturally derived psilocybin across mental health domains, though evidence of causal efficacy is mixed. Safety profiles are favorable but context-dependent, with risks in vulnerable populations. Some preliminary preclinical evidence indicates possible entourage effects, but human validation is lacking. Dose precision varies, with purified psilocybin being most reliable, followed by standardized extracts, alcoholic, aqueous, and whole biomass preparations. Scalable cultivation is feasible but faces sustainability challenges. Key gaps include a lack of controlled trials, longitudinal safety evaluations, and standardization. We provide a phased research roadmap, which proposes short-term studies to establish safety, mid-term mechanistic and standardization efforts, and long-term integration into therapeutic, cultural, and ecological systems. This review highlights the promise of naturally derived psilocybin but underscores the need for rigorous evidence to support regulatory acceptance and clinical use. Full article

Background: Wrist-hand radiographic skeletal maturation methods are widely used for forensic age estimation of living individuals, remaining among the most widely accepted imaging modalities in forensic practice despite limited evidence supporting their use at the legally relevant 18-year threshold. This systematic review aims to provide a quantitative synthesis of the widely recognized but previously unsynthesized body of evidence regarding their diagnostic accuracy (sensitivity, specificity, AUC-curve, mean absolute error-MAE) for forensic adult age estimation. Methods: Six databases (Scopus, PubMed, Google Scholar, Embase, Cochrane, Clarivate) between 1980 and 2026 were searched. Studies evaluating wrist-hand skeletal maturation for forensic age estimation in individuals ≥16 years with verified chronological age were included. Two reviewers independently screened studies and extracted data. Quality was assessed using QUADAS-2. DerSimonian-Laird random-effects model estimated the sensitivity and specificity of the wrist-hand bones maturation at the age of 18 years, and pooled MAE. GRADE assessed the certainty of evidence. Results: From 747 records, 23 studies (11,425 participants, 15 countries, 2003–2025) were included. Pooled MAE was 0. 537 years (95% CI: 0.387–0.686; 95% PI: 0.33–0.79 years), but obtained from 3 Italian studies conducted on clinical populations, and all characterized by high risk of bias. At the 18-year threshold, pooled sensitivity was 69.5% (95% CI: 61.6–77.3%; 95% PI: 35.3–100%) and specificity 85.56% (95% CI: 83.53–87.60%; 95% PI: 77.2–93.9%). Nevertheless, the heterogeneity was extreme (I² > 98%) for all diagnostic measures, and calculated prediction intervals confirm that individual study results are expected to vary widely. QUADAS-2 assessment revealed 82.6% of studies with high/unclear patient selection bias. GRADE-certainty was VERY LOW for both outcomes due to serious risk of bias, very serious inconsistency, and serious indirectness. Conclusions: Wrist-hand skeletal maturation shows low accuracy and high rates of misclassification for age estimation at the 18-year threshold. The wide prediction intervals (sensitivity 35–100%, specificity 77–94%, MAE 0.33–0.79 years) indicate that performance in a new study population may differ substantially from the pooled estimates. Very low certainty evidence, extreme heterogeneity, and substantial methodological limitations preclude confident application. Results should be interpreted with caution in forensic contexts, preferably combining multiple age indicators, in particular dental evidence. Full article

Background/Objectives: Dietary adherence and physical activity are pivotal yet understudied behavioral components of self-management of type 2 diabetes mellitus (T2DM) in the Middle East and North Africa region. This study aimed to quantify dietary adherence and physical activity levels, examine their association, and identify sociodemographic and clinical factors independently associated with these outcomes among adults with T2DM in southwest Saudi Arabia—a region chronically underrepresented in the literature. Methods: A descriptive cross-sectional study (n = 257; December 2023–March 2024) was conducted at a specialist diabetes center. The Perceived Dietary Adherence Questionnaire (PDAQ; 0–56 after removal of the fat-avoidance item with near-zero item-total correlation) and General Practice Physical Activity Questionnaire (GPPAQ) were administered alongside body mass index (BMI) and glycated hemoglobin (HbA1c) extracted from medical records. Bonferroni-corrected non-parametric bivariate tests, multiple linear regression with variance inflation factor diagnostics, and binary logistic regression were applied. Results: Mean 8-item PDAQ was 20.44 ± 10.04/56 (36.5%); carbohydrate spacing was the critical deficit (16.4%). GPPAQ distribution: 10.1% inactive, 28.0% moderately inactive, 49.0% moderately active, and 12.8% active, with sensitivity analysis ranging 28.0–47.5% in the two lowest categories. PDAQ–GPPAQ correlation was weak (Spearman r = 0.18; 95% CI: 0.06–0.29; r² = 0.032). BMI alone accounted for 81.0% of PDAQ score variance (cross-sectional; direction of association not established; full model Adj. R² = 0.826; LOO-CV R² = 0.820, indicating model stability). Employment type showed the strongest cross-sectional association with GPPAQ-derived inactivity classification (housewife OR = 5.77; retired/seeking OR = 4.98 vs. employed), largely driven by the occupational component of the composite score. Conclusions: Dietary adherence was substantially below the maximum achievable score; BMI was the factor most strongly associated with PDAQ scores in cross-sectional analysis, though the direction of this relationship cannot be established. Physical activity levels were substantially associated with occupational patterns; housewives and retired/other participants faced approximately five-fold greater odds of being classified as inactive or moderately inactive compared with employed individuals. The weak PDAQ–GPPAQ correlation (r² = 0.032) suggests these behaviors are not strongly co-determined and points to the potential value of distinct, hypothesis-generating intervention approaches for dietary quality and leisure-time physical activity in T2DM populations. Full article

Langer’s axillary arch, also known as the axillopectoral muscle, represents a relatively uncommon anatomical variation of the axillary region. Although often asymptomatic, its presence may have important implications in surgical procedures involving the axilla, particularly during breast surgery, axillary lymph node dissection, and reconstructive procedures. Despite numerous anatomical and surgical reports describing this variation, the true prevalence of Langer’s axillary arch remains uncertain due to variability in study design and detection methods. Objective: The aim of this systematic review and meta-analysis was to evaluate the reported prevalence of Langer’s axillary arch and to assess methodological variability among anatomical and surgical studies. Methods: A systematic literature search was conducted in accordance with PRISMA guidelines using electronic databases including PubMed, Scopus, and Web of Science. Studies reporting original data on the presence or prevalence of Langer’s axillary arch in cadaveric or surgical populations were included. Data extraction included study characteristics, sample size, number of detected axillary arches, and reported prevalence. A random-effects meta-analysis was performed to estimate the pooled prevalence and to evaluate heterogeneity between studies. Results: The analysis included studies comprising both cadaveric anatomical investigations and surgical series. Considerable variability in reported prevalence was observed across studies. Cadaveric studies generally reported higher prevalence rates compared with surgical series, reflecting differences in detection methods. Meta-analytic synthesis demonstrated that Langer’s axillary arch represents a relatively uncommon but clinically relevant anatomical variation. Conclusions: Langer’s axillary arch should be recognized as an important anatomical variant of the axillary region. Awareness of this variation is essential for surgeons performing axillary procedures, as its presence may influence surgical exposure and lymph node identification. Further large-scale anatomical and clinical studies are needed to better define its prevalence and surgical implications. Full article

Accurate donor–recipient allograft size matching remains a critical determinant of outcomes in lung transplantation, yet current approaches rely predominantly on predicted total lung capacity (pTLC) and height-based metrics derived from population-based equations. These simplified surrogates fail to capture individual anatomical variability, disease-specific alterations in thoracic geometry, and the spatial relationship between donor lungs and recipient chest cavities. In this review, we examine the limitations of conventional size matching and synthesize emerging evidence supporting imaging-based approaches, including computed tomography (CT) volumetry, radiomics, and machine learning. CT-derived volumetric analysis enables individualized anatomical assessment and has been associated with clinically relevant prediction of primary graft dysfunction and mortality. Advanced computational methods may further support the extraction of imaging-derived features and integration with clinical data, although these approaches remain investigational. Collectively, these developments signal a paradigm shift from crude population-based metrics toward imaging-driven and computational approaches in the modern era. With rigorous validation and careful clinical integration, imaging-based approaches may complement conventional size metrics and support more individualized donor–recipient assessment. Full article

Obesity and metabolic dysregulation are closely associated with chronic low-grade inflammation, in which interleukin-6 (IL-6) plays a key regulatory role. Genetic variation in the IL-6 gene may influence inflammatory responses and metabolic homeostasis. To identify single-nucleotide variants (SNVs) in the IL-6 gene in a cohort of Colombian high-performance athletes and to evaluate their potential functional and structural consequences using bioinformatic prediction and protein-modeling approaches. A descriptive observational study was conducted in a cohort of 23 high-performance Colombian athletes from Valle del Cauca representing cycling, karate, and weightlifting disciplines. Genomic Deoxyribonucleic Acid (DNA) extracted from peripheral blood samples was analyzed using Next-Generation Sequencing (NGS). Identified variants were evaluated using several in silico prediction tools, including Basic Local Alignment Search Tool (BLAST version 2.16.0), Expert Protein Analysis System (ExPASy version 4.0), Open Reading Frame Finder (ORFfinder version 0.4.3), and population databases such as Genome Aggregation Database (gnomAD version 4.0). Structural modeling was used to explore the potential impact of amino-acid substitutions on IL-6 protein stability. Eight single-nucleotide variants were identified in the IL-6 gene. Among them, the rs1524107 variant generated a missense substitution predicted to modify the amino-acid sequence of the IL-6 protein. Structural modeling suggested a potential alteration in protein stability associated with this variant. The rs1524107 variant may influence IL-6 protein structure according to computational predictions. These findings provide preliminary hypothesis-generating evidence regarding the potential role of IL-6 genetic variation in inflammatory regulation; however, functional validation and larger cohort studies are required to determine their biological significance. Full article

Background/Objectives: Cerebrovascular disease (CVD) is the fifth leading cause of death in the U.S. and poses marked health ramifications. Improvements in CVD-related mortality rates have been observed since the 1970s, but incidence remains high. It is imperative to analyze demographic disparities and trends in CVD-related mortality to inform better efforts to reduce the burden of CVD. This study aimed to examine demographic disparities in CVD-related mortality across age groups, biological sex, race/ethnicity, and regions from 1999 to 2024. Methods: This was a retrospective population-based study using the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER). The CDC WONDER was used to extract crude and age-adjusted mortality rates (AAMRs) for CVD-related deaths in the US. Adults aged 25 years and older were included in the study. Joinpoint analysis software was used to calculate the annual percent change (APC) and the average annual percent change (AAPC) for mortality trends. Results: There was a total of 6,541,598 CVD-related deaths from 1999 to 2024 in adults aged 25 years and older. The trend in overall CVD-AAMR steadily declined until 2014, then gradually increased, accelerated, and eventually peaked in 2021 during the COVID-19 pandemic. Male individuals experienced a higher mortality rate and comprised 43% of crude deaths vs. 57% of female individuals across the study period. When stratified by race/ethnicity, non-Hispanic (NH) Black individuals had an AAMR that was nearly 1.5 times that of the next-highest group at 148.37 (146.89 to 149.85) per 100,000 people in 2024. The South had the highest AAMR and experienced 39.4% of deaths out of the four regions. All demographics experienced an increase in mortality during the pandemic, but the Northeast region experienced an earlier peak in 2020 as opposed to all other groups, which saw a peak in 2021. Conclusions: CVD-related mortality declined significantly in adults from 1999 to 2024. Differences across demographic and regional subgroups have narrowed; however, significant disparities persist. These disparities will require comprehensive, concerted efforts to improve cerebrovascular health, outcomes, and equity among the young and middle-aged populations in the US. Full article

Sweet chestnut (Castanea sativa Mill.) coppice forests are important Mediterranean resources, but the genetic structure of local coppice stands remains insufficiently characterized, limiting their use as reference systems for wood provenance studies. This study integrated population genetic analysis, optimization of wood-derived DNA recovery, and reference-based assignment to evaluate Lazio coppice stands and test the declared origin of timber samples. Four Lazio populations were genotyped at 12 SSR loci, screened for Hardy–Weinberg disequilibrium, null alleles, and kin structure, and compared with eight European/Mediterranean populations using five shared loci. DNA extraction from dried wood was optimized through a CTAB-PEG workflow, and 40 timber samples from four sawmills, including two declared from Lazio (MCt and RPt), one from Calabria (CALt) and one from France (FRAt), were assigned using supervised DAPC, STRUCTURE with population information and GDA_NT Bayesian assignment and exclusion testing. Lazio stands retained high SSR diversity but showed heterozygote deficiency and fine-scale family structure; therefore, a conservative post-COLONY dataset was used for downstream analyses. Differentiation was weak among Lazio stands, but they showed a coherent Central Italian affinity within the available European/Mediterranean reference set. The optimized protocol yielded reproducible SSR profiles from all timber samples, with an 80.0% successful wood extraction rate. Within the available reference panel, assignment analyses indicated compatibility of MCt and RPt with a Lazio origin, whereas CALt and FRAt were incompatible with the Lazio references and should be interpreted as extra-regional or insufficiently represented by the current baseline. SSRs provide a practical first-line tool for regional chestnut timber screening, although broader reference panels and complementary high-resolution markers are needed to strengthen fine-scale provenance inference. Full article