Search Results (6,202)

Background/Objectives: Central nervous system (CNS) infections remain a significant public health challenge and require rapid and accurate diagnosis to guide clinical management. Although the incidence of bacterial meningitis has declined owing to widespread vaccination, viral etiologies continue to dominate CNS infections. The aim of this study was to assess the epidemiological trends, age distribution, and seasonality of CNS infections using multiplex PCR. Methods: A retrospective analysis was conducted on cerebrospinal fluid (CSF) samples collected between January 2021 and December 2022 from patients with CNS infections at King Abdulaziz Medical City. A BioFire FilmArray Meningitis/Encephalitis (ME) panel was used to detect pathogens. Patient demographics, pathogen distribution, and seasonal trends were analyzed. Results: A total of 2,460 CSF samples were tested, of which 130 (5%) were positive for at least one pathogen. Viral pathogens accounted for 82.3% of the infections, with human herpesvirus-6 (HHV-6) (31%) and enterovirus (EV) (20%) being the most common. Bacterial pathogens represented 17.7% of the cases, with Streptococcus pneumoniae (6%) and Escherichia coli K1 (5%) being the predominant bacterial agents. The highest infection burden was observed in infants aged 0–6 months, with a marked male predominance. Seasonal analysis revealed multiple peaks in viral infections, particularly of HHV-6 and EVs, whereas bacterial infections were sporadic, with Streptococcus agalactiae and Streptococcus pneumoniae peaking in October and November. Conclusions: Viral infections, particularly HHV-6 and EVs, dominated CNS infections, with distinct seasonal and age-related variations. These findings underscore the value of multiplex PCR in improving the rapid diagnosis of CNS infections and aiding in timely treatment and antimicrobial stewardship. Full article

Background/Objectives: This study aimed to develop and validate a Dietary Practices and Food Safety Literacy Scale comprehensively assessing competencies among Korean older adults in healthy dietary practices, hygiene, and food safety. Methods: Item development was informed by a literature review, national dietary guidelines, and existing literacy frameworks. Content validity was reviewed by a 10-member expert panel using the Delphi method. Construct validity was tested using exploratory factor analyses (EFA) and confirmatory factor analyses (CFA), and reliability was assessed through Cronbach’s α, composite reliability (CR), and average variance extracted (AVE). Results: EFA identified three factors—management, decision-making, and moderation competencies—comprising 13 items. Internal consistency was acceptable (α = 0.69–0.83), and CFA supported the three-factor structure (CFI = 0.919, RMSEA = 0.087). CR values exceeded 0.70, and AVE were close to or exceeded the recommended threshold. Conclusions: The scale demonstrates sound psychometric properties and provides a practical tool for identifying competency gaps in Dietary Practices and Food Safety Literacy. Its application may guide tailored health education and community-based interventions to promote healthy aging and support public health strategies in aging societies. By translating health information literacy into measurable, behavior-oriented domains, this tool bridges the gap between theoretical constructs and practical assessment. It can be incorporated into routine health monitoring, enabling policymakers and practitioners to design evidence-based interventions that enhance older adults’ dietary self-management and food safety awareness. Full article

Background/Objectives: The factors contributing to residual atherosclerotic cardiovascular disease (ASCVD) risk in individuals are not fully understood, but knowledge of the specific type of dyslipoproteinemia may help further refine risk assessment. We developed a novel phenotyping and risk assessment system that may be applied automatically using standard lipid panel parameters. Methods: NHANES data collected from 37,056 individuals during 1999–2018 were used to develop a three-dimensional dyslipidemia phenotype classification system. ARIC data from 14,632 individuals were used to train and validate the risk model. Three-dimensional Cartesian coordinates were converted to spherical coordinates, which were used as features in a logistic regression model that provides a probability of ASCVD. UK Biobank data from 354,344 individuals were used to further validate and test the model. Results: Nine lipidemia phenotypes were defined based on the concentrations of HDLC, non-HDLC and TG. These phenotypes were related to the prevalence of metabolic syndrome, pooled cohort equation (PCE) score and ASCVD-free survival. A logistic regression model including age, sex and the spherical coordinates of the phenotype provided a composite risk score with predictive accuracy comparable to that of the PCEs. Conclusions: We provided an example of how a multidimensional coordinate system may be used to define a novel lipoprotein phenotyping system to examine disease associations. When applied to an ASCVD risk model, the composite spherical coordinate risk marker, which can be fully automated, provided an F1 performance score almost as good as the PCEs, which requires other risk factors besides lipids. Full article

Photovoltaic/Thermal (PV/T) systems are a technology designed to simultaneously convert solar energy into both electrical and thermal energy. The overall conversion efficiency of these systems can be significantly enhanced by effectively cooling the photovoltaic (PV) module. To this end, this paper presents a comparative experimental study of a PV panel under three distinct configurations: operating with a no cold plate, with an ordinary cold plate, and with a spiral coil cold plate. The system’s photo-thermoelectric efficiency was evaluated by measuring key parameters, including the PV panel’s surface temperature, electrical power output, and the water tank temperature. The results indicate that the spiral coil configuration demonstrated a marked superiority in temperature regulation over the baseline case, achieving a maximum temperature reduction of 13.8 °C and an average reduction of 10.74 °C. Furthermore, a stable temperature drop exceeding 10 °C was maintained for 74.07% of the experimental duration. When compared to the ordinary cold plate, the spiral coil configuration continued to exhibit superior performance, delivering maximum and average temperature drops of 3.6 °C and 2.16 °C, respectively, while sustaining a cooling advantage of over 2 °C for 66.67% of the test period. These findings conclusively demonstrate that the spiral coil cold plate is the most effective configuration for enhancing the system’s overall performance. Full article

This study, via a combination of experiments and numerical simulations, investigates the structural tensile failure mechanisms of battle-damaged aluminum alloy flat panels and stiffened panels, the variation in their residual strength with hole characteristics, and modifies the calculation formula of the net-section failure criterion for evaluating damaged panels’ residual strength. Experimental and simulation results demonstrate that hole size and position exert a significant influence on panels’ residual strength: larger hole size and greater eccentricity both diminish load-bearing capacity, stiffened panels with web damage exhibit lower load-bearing capacity than those with flange damage. Different hole positions induce edge effects that alter stress distribution at the hole cross-section. Introducing a stress averaging coefficient modifies the residual strength evaluation of flat panels, which is further extended to stiffened panels with high result accuracy. This study presents a rapid method for evaluating damaged panels’ residual strength and serves as a reference for aircraft battle damage repair (ABDR) design. Full article

High-quality corporate innovation serves as a critical driver for achieving corporate sustainable development. This study bridges the gap between macroeconomic fiscal sustainability and microeconomic innovation quality. Specifically, this paper investigates the influence of local fiscal sustainability on high-quality corporate innovation, examining the underlying mechanisms and heterogeneous effects. Methodologically, data were collected using Python-based retrieval and web-scraping techniques. A multi-dimensional index of local fiscal sustainability was constructed, comprising five key dimensions to quantitatively map provincial fiscal sustainability across China. Corporate innovation quality was measured using patent citation metrics. Employing panel data from A-share listed companies over the 2015–2023 period, we implemented a two-way fixed-effects model for rigorous empirical econometric analysis. The findings indicate a significant positive relationship between local fiscal sustainability and high-quality corporate innovation. This result remains robust after a battery of robustness tests, including the use of instrumental variable (IV) methods. Mechanism analysis reveals that the resource compensation effect is the primary channel. Furthermore, our analysis identifies heterogeneity across varying innovation environments, economic regions, and industry characteristics. The positive influence is particularly pronounced in provinces with stronger intellectual property protection, firms located in the eastern regions, and High-Tech Enterprises. Collectively, the conclusions drawn from this research offer valuable policy implications for strengthening local fiscal sustainability and enhancing high-quality corporate innovation. Full article

Achieving gender diversity and women’s empowerment (SDG 5) is not only a social priority but also a key driver of sustainable financial resilience. This study investigates whether the presence of women on bank boards strengthens the stability of financial institutions in the Middle East and North Africa (MENA), where gender diversity remains limited yet is steadily growing. Using a balanced panel of 61 commercial banks across nine MENA countries from 2012 to 2020, we assess whether board gender diversity enhances the predictive performance of Early Warning Systems (EWSs) for bank distress. Applying a logit random-effects model, our results show that a higher proportion of female directors significantly lowers the probability of bank failure and improves EWS accuracy. Further analyses reveal that gender-diverse boards foster stronger governance by reducing operating costs, boosting profitability, and supporting higher capitalization and liquidity, indicating more prudent and risk-averse oversight. Robust tests using the Z-score and System Generalized Method of Moments (System-GMM) confirm these outcomes. Moreover, a non-linear pattern emerges: the stabilizing influence of women directors is most pronounced during financial crises but less evident in stable periods. These findings underscore the strategic value of women’s leadership in banking, offering insights for policymakers and regulators aiming to advance SDG 5 and promote resilient, inclusive financial systems. Full article

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by motor and non-motor symptoms. The absence of reliable fluid biomarkers continues to hinder early diagnosis and effective monitoring of disease progression. Circulating microRNAs (cmiRNAs) are potential candidates, given their stability in biofluids and their ability to mirror pathological processes. We conducted a longitudinal study in 30 early-stage levodopa-naive PD patients (22 men, 8 women). Serum samples were collected at baseline (T0) and at a follow-up time point two years later (T2). A panel of MicroRNAs (miRNAs) (miR-146a-5p, miR-34a-5p, miR-155-5p, miR-29a-3p, miR-106a-5p) were quantified by quantitative real-time PCR. Data were expressed as relative expression (2^−ΔCt), and statistical analyses included sex-stratified comparisons and paired tests for longitudinal changes. At baseline, no significant differences were found in the expression of the miRNAs between male and female PD patients. In contrast, longitudinal within-subject analysis revealed a highly significant upregulation in miR-146a-5p expression from T0 to T2 in both sexes (p < 0.0001). No other miRNAs in the panel exhibited significant changes over time. CmiR-146a-5p levels rise markedly over time in PD patients, independent of sex, suggesting that this miRNA could be a dynamic biomarker of disease progression. Full article

This study investigates the relationship between economic growth and environmental performance in selected Middle East and North Africa (MENA) countries through the lens of the Environmental Kuznets Curve (EKC) hypothesis. Due to data availability constraints, our sample includes Algeria, Egypt, Lebanon, Mauritius, Morocco, and Oman, covering the period 1990–2022. Using annual panel data, we apply panel cointegration techniques alongside Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) estimators, complemented by Granger causality tests, to examine the interaction among GDP per capita, renewable energy consumption, and transport service exports in determining CO₂ emissions per unit of GDP. The empirical findings provide only partial support for the EKC: while the DOLS results confirm an inverted U-shaped income–emissions relationship, the FMOLS estimations contradict it, suggesting a more complex and nonlinear pattern. Beyond testing the EKC, this study contributes two novel dimensions to the literature. First, it shows that renewable energy exerts a statistically significant negative effect on carbon intensity in the long run, despite weak short-run causality, highlighting the delayed but durable environmental benefits of clean energy adoption. Second, it introduces transport service exports as a proxy for structural economic transformation, capturing the role of trade-driven diversification in reducing emissions. By embedding renewable energy deployment and service-based trade dynamics into the EKC framework, the study advances a more policy-relevant and region-specific understanding of the growth–environment nexus in the selected MENA economies. The results underscore the importance of scaling renewable energy, promoting low-carbon service sectors, and aligning trade and environmental policies to ensure that economic growth supports long-term climate objectives. Full article

This article examines the growth threshold effect on renewable energy transition in eight Southeast Asian countries from 2000 to 2023. Utilizing panel data and threshold regression analysis, the study confirms the following established findings: (1) There is evidence of a significant impact of the moderating effect of growth/FDI on the nexus between access to clean energy and the renewable energy transition in Southeast Asian countries. (2) There is evidence of a significant impact of the moderating effect of growth/trade on the nexus between access to clean energy and the renewable energy transition in Southeast Asian countries. (3) There is evidence of a significant effect of the moderating effect of growth/R&D on the nexus between access to clean energy and the renewable energy transition in Southeast Asian countries. (4) Lastly, the complementary growth threshold of 1.68% is to be checked for access to clean energy and technologies and the renewable energy transition in Southeast Asian countries. Therefore, policies should promote sustained growth while ensuring investments in research and development, trade, and foreign direct investment (FDI), which are expected to benefit the region in the long term. In the short term, it may be necessary to reassess current policies to prevent misallocation of resources, ensuring progress towards SDG-7 before the 2030 deadline. Future research should investigate additional factors that could facilitate a sustained transition to renewable energy and examine the complex relationship between economic growth, access to clean energy, and renewable energy transition in Southeast Asian countries. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a multifactorial condition requiring multi-target therapeutic strategies beyond traditional single-marker approaches. In this work, we present a fully in silico nutraceutical screening pipeline that integrates molecular prediction, systemic aggregation, and technological design. A curated panel of ten MASLD-relevant targets, spanning nuclear receptors (FXR, PPAR-α/γ, THR-β), lipogenic and cholesterogenic enzymes (ACC1, FASN, DGAT2, HMGCR), and transport/regulatory proteins (LIPG, FABP4), was assembled from proteomic evidence. Bioactivity records were extracted from ChEMBL, structurally standardized, and converted into RDKit descriptors. Predictive modeling employed a stacked ensemble of Random Forest, XGBoost, and CatBoost with isotonic calibration, yielding robust performance (mean cross-validated ROC-AUC 0.834; independent test ROC-AUC 0.840). Calibrated probabilities were aggregated into total activity (TA) and weighted TA metrics, combined with structural clustering (six structural clusters, twelve MOA clusters) to ensure chemical diversity. We used physiologically based pharmacokinetic (PBPK) modeling to translate probabilistic profiles into minimum simulated doses (MSDs) and chrono-specific exposure (%T>IC50) for three prototype concepts: HepatoBlend (morning powder), LiverGuard Tea (evening aqueous form), and HDL-Chews (postprandial chew). Integration of physicochemical descriptors (MW, logP, TPSA) guided carrier and encapsulation choices, addressing stability and sensory constraints. The results demonstrate that a computationally integrated pipeline can rationally generate multi-target nutraceutical formulations, linking molecular predictions with systemic coverage and practical formulation specifications, and thus provides a transferable framework for MASLD and related metabolic conditions. Full article

As a systematic project, corporate green innovation involves technological, organizational, and environmental dimensions. Therefore, its effective functioning is contingent on guidance from internal leadership. STEM represents an integration of science, technology, engineering, and mathematics education. A STEM CEO is a chief executive officer holding a degree in science, engineering, agriculture, or medicine. However, research on the impact of STEM CEOs on green innovation is limited. Using data from Chinese listed manufacturing firms from 2010 to 2023, panel fixed effects models reveal that STEM CEOs positively influence corporate green innovation. Further analysis indicates that alleviating financing constraints, fostering external collaboration, increasing R&D investment, and improving the efficiency of innovation resource allocation are key pathways through which STEM CEOs enhance green innovation output. Furthermore, this impact is positively moderated by the level of green finance development and the intensity of market competition. Finally, heterogeneity tests demonstrate that these positive effects are more pronounced for firms with high public environmental concern, in non-heavily polluting industries, with strong ESG performance, and in highly competitive industries. These findings underscore the role of STEM leaders in enhancing the output of green innovation systems, offering actionable insights into the interaction between STEM CEOs and the external environment. Full article

This study developed sustainable foam-type composites from recycled paper (P), corrugated cardboard (C), and their 1:1 mixture (PC) for use in thermal and acoustic insulation. The materials were produced by water-assisted defibration, gas foaming with sodium bicarbonate and yeast, and oven curing, resulting in lightweight porous panels without synthetic binders. The composites exhibited distinct density and porosity profiles that influenced moisture behavior and stability. Cardboard-based panels absorbed the most water and swelled the most, while paper-based panels were more resistant. Despite these differences, all materials showed uniformly low thermal conductivity, confirming their strong insulation capability. Acoustic performance was enhanced by perforation and multilayer assembly. Cardboard panels with a triple-layer perforated design achieved the highest sound absorption, while mixed paper–cardboard composites provided balanced broadband performance. Microscopy revealed that fiber morphology—coarse in cardboard, fine in paper, and interlaced in mixtures—shaped the porous structure and bonding. Mechanical tests indicated comparable stiffness and strength across all types, with cardboard showing the strongest internal bonding. Overall, the results demonstrate that fiber structure and porosity govern material performance. These foam composites combine effective thermal insulation, competitive sound absorption, and sufficient mechanical strength, positioning them as biodegradable, low-cost alternatives for sustainable construction and acoustic applications. Full article

Background: Autosomal recessive polycystic kidney disease (ARPKD) is a rare form of PKD that leads to the development of multiple renal cysts and hepatic fibrosis. Aim: The first documented case of large hepatic cyst associated with dual PKHD1-PKD1 variants. Case report: We present the case of a 5-year-old boy with a kidney US image typical of ARPKD and numerous large cysts in the liver not typical for this disease. Genetic analysis revealed heterozygous missense mutations in the PKHD1 gene (maternally, c.107C>T/p.Thr36Met in exon 3; paternally, c.4870C>T/p.Arg1624Rrp in exon 32) and an additional new variant in PKD1 (maternally, c.5323G>A/p.Gly1775Ser in exon 32). Genetic tests excluded mutations in genes responsible for polycystic liver disease (PCLD). However, the presence of the PKD1 mutation is clinically not clear due to the normal abdominal US image in the mother; it seems to be the most likely explanation for unusual phenotype in our patient. Conclusions: This case may contribute to the understanding of the phenotypic variability in ARPKD and the potential modifying role of mutations in other PKD-related genes. Comprehensive genetic panels are crucial for explaining atypical phenotypes and prognosis in patients with PKD. Full article

To investigate the initial rotational stiffness and ultimate moment of fully bolted connections in panelized steel modular structures, a finite element analysis was carried out on 20 joint models. High-fidelity models were developed using ABAQUS, and their accuracy was confirmed through comparison with experimental tests. A parametric study was performed to systematically evaluate the effects of the column wall thickness in the core zone, internal diaphragm configurations, angle steel thickness, and stiffener layouts on the joint stiffness and ultimate strength, leading to practical optimization suggestions. Additionally, a mechanical model and a corresponding formula for predicting the initial rotational stiffness of the joints were proposed based on the component method in Eurocode EC3. The model was validated against the finite element results, showing good reliability. Three failure modes were identified as follows: buckling deformation of the beam flange, buckling deformation of the column flange, and deformation of the joint panel zone. In joints with a weak core zone, both the use of internal diaphragms and increased column wall thickness effectively improved the initial rotational stiffness and ultimate bearing capacity. For joints with weak angle steel connections, adding stiffeners or increasing the limb thickness significantly enhanced both the stiffness and capacity. The diameter of bolts in the endplate-to-column flange connection was found to have a considerable effect on the initial rotational stiffness, but minimal impact on the ultimate strength. This study offers a theoretical foundation for the engineering application of panelized steel modular structural joints. Full article