Search Results (1,205)

Background/Objectives: Type 2 diabetes mellitus (T2DM) is characterized by chronic hyperglycemia and insulin resistance, leading to progressive metabolic dysfunction. Flavonoids, such as astragalin, have reported antidiabetic potential; however, their direct effects on pancreatic β-cell ionic mechanisms and insulin secretion remain unclear. This study aimed to investigate the effects of astragalin on glucose uptake, insulin secretion, and membrane ionic currents in pancreatic β-cell lines. Methods: Murine MIN6 and rat INS-1 pancreatic β-cells were used as experimental models. Following astragalin treatment, glucose uptake was quantified by bioluminescence, and insulin secretion was measured by ELISA. Ionic currents were analyzed using the whole-cell patch-clamp technique. Selective pharmacological blockers targeting ATP-sensitive K⁺ channels (KATP), voltage-dependent K⁺ channels (K_v), and L-type voltage-dependent Ca²⁺ channels were applied to elucidate the underlying mechanisms. Results: Astragalin increased glucose uptake in a time-dependent manner, reaching a plateau between 3 and 5 h. Insulin secretion was significantly enhanced after 1 h of exposure to 100 µM astragalin. Patch-clamp recordings demonstrated that astragalin reduced potassium channel currents in pancreatic β-cells. Pharmacological modulation confirmed the involvement of KATP, K_v, and L-type Ca²⁺ channels. Verapamil attenuated the insulinotropic effect, supporting the role of calcium influx in astragalin-induced insulin exocytosis. Conclusions: Astragalin enhances glucose uptake and stimulates insulin secretion in pancreatic β-cells through modulation of potassium and calcium channels, promoting calcium-dependent exocytosis. These findings support its potential as a candidate for antidiabetic therapeutic strategies. Full article

Background: Traumatic spinal injuries (TSI) are often associated with substantial physical burden and potential psychological consequences. Early detection of depressive symptoms may be important for improving quality of life during recovery. Despite the high prevalence of injury, unique sociocultural factors affecting mental health, and the need to optimize long-term rehabilitation outcomes, there is a lack of longitudinal assessments of depression in TSI patients in this region of the MENA (Middle East and North Africa). This study aimed to examine the occurrence of depressive symptoms following TSI over a 3-month period. Methods: A prospective cohort study was conducted to assess the occurrence of depression in TSI patients admitted between 2019 and 2022 at the Hamad Trauma Center. Conscious patients aged 18–65 years diagnosed with TSI were included. Perceived social support was assessed using the RAND Social Support Survey (Medical Outcomes Study Social Support Survey), a validated instrument measuring multiple dimensions of social support. Patient Health Questionnaire-9 (PHQ-9), a widely validated self-administered screening tool for depressive symptoms, was utilized twice: at 2 weeks and at 3 months post-trauma to evaluate early-onset depressive symptoms and their persistence or resolution over time. Results: A total of 189 TSI were included. The cohort was predominantly young individuals. The most common mechanisms of injury included falls (42.1%) and motor vehicle crashes (31.1%). The mean Injury Severity Score was 16.5 ± 8.2 and the spine Abbreviated Injury Scale score was 2.4 ± 0.7. Injuries involved cervical (32.8%), thoracic (38.1%), and lumbo-sacral (6.9%) regions. A total of 32.6% underwent spinal surgery, and 9.0% experienced neurological deficits. Most patients reported emotional and informational support (69%), and 62% reported caregiving support. At 2 weeks post-trauma, patients demonstrated mild depressive symptoms, with a mean PHQ-9 score of 4.6 ± 5.1, which decreased to 2.5 ± 4.2 at 3 months. The proportion of patients screening positive for depressive symptoms (PHQ-9 ≥ 5) decreased from 39.1% (52/133) at 2 weeks to 19.5% (26/133) at 3 months, corresponding to a 19.6% absolute reduction over the follow-up period. A subset of patients reported increased feelings of depression or hopelessness and sleep disturbances at three months compared with two weeks post-trauma. Conclusions: Patients with TSIs experience psychological distress in the early post-injury period, with a subset screening positive for depressive symptoms. Although depressive symptom scores declined over 3 months, continued psychological screening and follow-up care remain important components of comprehensive TSI management during recovery and rehabilitation. Our results should be considered cautiously because of gender-biased findings, single center data and potential attrition bias. Full article

The 2x2 Demonstrator, a prototype for the Deep Underground Neutrino Experiment (DUNE) liquid argon (LAr) Near Detector, was exposed to the Neutrinos from the Main Injector (NuMI) neutrino beam at Fermi National Accelerator Laboratory (Fermilab). This detector is a prototype of a new modular design for a liquid argon time-projection chamber (LArTPC), comprising a two-by-two array of four modules, each further segmented into two optically isolated LArTPCs. The 2x2 Demonstrator features a number of pioneering technologies, including a low-profile resistive field shell to establish drift fields, native 3D ionization pixelated imaging, and a high-coverage dielectric light readout system. The 2.4-tonne active mass detector is flanked upstream and downstream by supplemental solid-scintillator tracking planes, repurposed from the MINERvA experiment, which track ionizing particles exiting the argon volume. The antineutrino beam data collected by the detector over a 4.5 day period in 2024 include over 30,000 neutrino interactions in the LAr active volume—the first neutrino interactions reported by a DUNE detector prototype. During its physics-quality run, the 2x2 Demonstrator operated at a nominal drift field of 500 V/cm and maintained good LAr purity, with a stable electron lifetime of approximately 1.25 ms. This paper describes the detector and supporting systems, summarizes the installation and commissioning, and presents the initial validation of collected NuMI beam and off-beam self-triggers. In addition, it highlights observed interactions in the detector volume, including candidate muon antineutrino events. Full article

Exchange rate volatility creates uncertainty for firms in open economies, especially in emerging markets with structural vulnerability and shallow financial markets. This work examines the impact of exchange rate volatility on the cash-flow performance of non-financial firms in the Middle East and North Africa (MENA) region of 292 firms across 11 countries from 2014 to 2023. Heteroskedasticity, serial correlation and cross-sectional dependence were estimated using fixed effects, random effects and robustness estimation using Driscoll–Kraay standard errors and Feasible Generalized Least Squares (FGLS). Exchange rate volatility has no statistically significant impact on corporate cash flows across all specifications, confirming the existence of an exchange rate exposure puzzle in emerging markets. Firm size always appears to be the strongest and most robust predictor of liquidity performance. The macroeconomic growth effect is weaker and context dependent: It is insignificant with baseline panel estimations, is negative with Driscoll–Kraay corrections and is marginally positive with FGLS structural controls. Profitability and inflation are virtually nonexistent. These insights inform both financial risk management and policy actions aimed at enhancing corporate stability and supporting sustainable development in emerging markets. Full article

Climate change is reshaping global hydrological cycles, intensifying scarcity and heightening health risks in vulnerable regions. This study examines the health impacts of climate-driven water scarcity across the Middle East, South Asia, and Sub-Saharan Africa using data on water availability, climate variability, and health outcomes. The study uses a multi-regional mixed methods approach that brings together climate, hydrology, governance, and health data to explore how climate-driven water scarcity affects public health in South Asia, Sub-Saharan Africa, and the MENA region. It combines quantitative climate and health indicators with qualitative evaluations of water system vulnerability to compare exposure pathways and health outcomes across regions. Findings show that rising temperatures, altered rainfall, declining groundwater, and recurrent droughts undermine water security, leading to increased disease burdens through four pathways: (1) waterborne illnesses from unsafe or insufficient supplies; (2) reduced hygiene due to limited access; (3) food insecurity from crop failures; and (4) mental health stress, conflict, and displacement from water competition. Women, children, and low-income households face disproportionate impacts. Current adaptation measures are fragmented, highlighting the need for integrated water governance to build climate resilience. Recommended strategies include community-based water safety planning, digital water monitoring, and embedding health metrics in climate–water policies. This cross-regional analysis supports equitable, climate-resilient health systems and informs interventions to mitigate water scarcity under accelerating climate change. This study directly supports global policy agendas by providing evidence that advances the objectives of the Sustainable Development Goals and international frameworks on climate resilience, water security, and food and health protection. Full article

This study investigates two graphene oxide (GO)-based coating architectures on urinary catheter substrates—layered (PEI+GO) and embedded (PEI/GO)—loaded with antimicrobial peptides (E14LKK and fLFB), with the aim of elucidating how coating structure governs peptide retention and release. Physicochemical and morphological characterization confirmed distinct coating architectures and thicknesses. Molecular dynamics simulations were employed to probe GO–peptide and PEI–peptide interactions, revealing weaker binding of fLFB to GO relative to PEI, consistent with enhanced peptide mobility. Antibacterial performance against Escherichia coli and Enterococcus faecalis was evaluated using agar diffusion assays as a comparative indicator of peptide release from surface-bound coatings. The layered PEI+GO–fLFB system exhibited the highest antibacterial activity, in agreement with simulation-predicted interaction energetics and structural fluctuations. Rather than targeting immediate clinical translation, this work provides mechanistic insight into how GO–polymer architecture modulates antimicrobial peptide availability, offering a molecular dynamics simulation-guided framework for the rational design of peptide-releasing antimicrobial coatings. Full article

The convergence of climate change, migration, and health represents a critical global challenge, with the Middle East and North Africa (MENA) region illustrating acute vulnerabilities while offering insight relevant beyond the region. Increasing exposure to extreme heat, droughts, and floods drives displacement, constrained mobility, and adaptive migration, placing additional pressure on already stretched health systems. This paper proposes an integrated Nexus Action Framework for Climate Change, Migration, and Health (NAF-CMH) to address these interlinked dynamics and move beyond fragmented, sector-specific responses. The framework conceptualizes human mobility both as a potential resilience strategy and as a determinant of health, encompassing climate-affected migrants, displaced populations, and those experiencing involuntary immobility across diverse pathways and settings. It promotes systematic integration of health considerations into climate adaptation and migration governance and situates these interventions within the broader agenda of climate-resilient health systems. Drawing on a non-systematic narrative review of peer-reviewed and grey literature, complemented by the authors’ expertise, the paper identifies seven interrelated pillars for coordinated policy and operational action. While grounded in MENA-specific vulnerabilities, the framework is flexible and adaptable to other regions facing climate-driven mobility challenges. By providing an operational architecture for multisector collaboration, the NAF-CMH supports policymakers, public health authorities, and migration actors in strengthening resilience, reducing vulnerability and safeguarding health amid accelerating climate impacts and evolving mobility patterns. Full article

Magnetic nanomaterials (MNMs) have been adopted as effective platforms for water remediation owing to their excellent surface-area-to-volume ratios, tunable surface chemistry, and magnetic separability. This review highlights the recent progress made in the synthesis, properties, and environmental applications in the removal of organic and inorganic contaminants using magnetic nanoparticles (MNPs) and one-dimensional magnetic nanofibers. Demonstrated removal rates of organic contaminants such as dyes, pharmaceuticals, and pesticides are often up to 85–100% under laboratory conditions, with adsorption capacities of 580 mg·g⁻¹ for melanoidin, 397.43 mg·g⁻¹ for Congo Red, and 392.64 mg·g⁻¹ for tetracycline. For heavy metals such as As(V), Cd(II), Cr(VI) and Pb(II), efficiencies are generally between 90–99% with maximum adsorption capacities of 909.1 mg·g⁻¹ for Pb(II). In particular, the review compares major synthesis routes such as coprecipitation, hydrothermal, solvothermal, thermal decomposition, sol–gel, microwave, and green methods by evaluating their effect on particle size (6–50 nm), magnetic properties (saturation magnetization up to ~101 emu·g⁻¹), and removal performance. The four principal mechanisms are described in this paper—adsorption, filtration, transformation, and photocatalysis—giving special emphasis to the advantages of magnetic recovery and advanced oxidation processes. Although most studies remain at the laboratory scale, MNMs demonstrate strong potential for scalable wastewater treatment, provided that toxicity, life-cycle impacts, and matrix effects are carefully evaluated. Full article

As climate change increasingly impacts the water cycle across the Alpine region, monitoring surface soil moisture is essential for hydrological models and drought early warning. Yet operational products either mask steep terrain, or lack the spatial resolution to capture the surface soil moisture (SSM) spatial variability of the Alpine catchments. This study presents a novel retrieval approach aggregating Sentinel-1 radiometric terrain-corrected backscatter (${\gamma }^0$) into 100 m elevation bands per sub-basin and aspect across the Austrian Alps. The resulting Alpine backscatter product is processed through an orbit-wise change detection to derive over 34,000 SSM timeseries, evaluated using ERA5-Land and compared to 264 precipitation stations from Geosphere for the period from 2016 to 2024. The results show satisfactory agreement with ERA5-Land (Pearson correlation > 0.46 below 400 m) and capture in situ precipitation-driven anomalies with the strongest performance below 400 m (Spearman correlation > 0.47), particularly over grasslands and south-facing slopes. Despite its limitations at high elevation and over dense vegetation, Sentinel-1 provides consistent and elevation-stratified information across more than 80% of the Austrian Alps, typically excluded from operational products. The new Alpine SSM product highlights Sentinel-1’s potential to support hydrological modeling, drought monitoring, and water resource management across complex topography such as the Alps. Full article

Background: Amid rising trade, urbanization, and carbon emissions in MENA countries, sustainable logistics faces major constraints. This study develops an enhanced Green Logistics Performance Index (GLPI) using min-max normalization and Principal Component Analysis (PCA) to integrate the World Bank’s Logistics Performance Index (LPI) and Yale’s Environmental Performance Index (EPI). The study uses fixed-effects panel regression on data from 20 MENA countries (2018–2024), identifies key drivers, and applies ARIMA and LSTM models for 2030 projections. The prior ratio-based GLPI suffered from scale sensitivity and volatility; this refined version provides improved stability and predictive utility for Green Supply Chain Management (GSCM). Methods: Panel data from 20 MENA countries (2018–2024) were analyzed. The enhanced GLPI normalizes and weights LPI and EPI scores via PCA. Fixed-effects regression identifies drivers, while ARIMA and LSTM enable scenario-based forecasting (baseline, optimistic, and pessimistic). Results: Renewable energy share positively influences GLPI, while trade openness has a negative effect. Projections indicate the regional GLPI will reach about 0.65 by 2030, with Saudi Arabia potentially achieving 25% higher under optimistic conditions. Conclusions: The refined GLPI advances GSCM theory by operationalizing triple bottom line trade-offs through a robust, predictive metric. It bridges descriptive limitations in prior literature, enabling forward-looking insights into sustainable logistics in emerging economies, with potential applicability beyond MENA. Full article

Scientific collaboration is increasingly needed to address complex research challenges, yet identifying promising partners in the absence of prior co-authorship remains difficult. We present a decision-support pipeline for discovering researchers who have not previously worked together and whose collaboration is unlikely to emerge without deliberate intervention or institutional incentives. The approach leverages document-level semantic representations to estimate proximity between publications, aggregates these similarities at the author level, and surfaces collaboration opportunities that are not evident from the co-authorship graph. To support interpretation by decision makers, a separate LLM module proposes potential joint research directions, which are subsequently annotated with multi-label fields of study. We evaluate the pipeline through an institutional case study, analyzing 7531 publications from 2009 to 2024 using retrospective, temporally shifted windows. While only a small fraction of suggested pairs materialized spontaneously in subsequent periods, the collaborations that do emerge exhibit strong semantic alignment with the computed recommendations (high cosine similarity) and substantial thematic overlap. These results indicate that semantic proximity can act as an early indicator of latent complementarity between researchers without prior ties, supporting intentional institutional mediation and complementing topology-driven approaches that predict links under passive evolution. Full article

Background: This study revisits whether oil revenue windfalls translate into higher socio-economic welfare in oil-exporting economies and explains why oil price booms often fail to generate sustained gains in real GDP per capita. Methods: Using annual data for ten oil-exporting countries over 1990–2024, we estimate country-specific ARDL/ECM models under a unified specification. The dependent variable is log real GDP per capita, explained by log real oil prices, the log share of government expenditure in GDP, population growth, and world GDP growth, with political and devaluation dummies where relevant. Results: Cointegration and significant error correction terms hold for most exporters, but adjustment speeds differ sharply. Long-run oil price elasticities are heterogeneous: strongly positive in Qatar, weak or insignificant in several cases (including Azerbaijan), and negative in a post-rentier pattern (UAE/Oman). Fiscal and demographic channels emerge as systematic constraints: government expenditure shares are often negatively associated with long-run welfare, and population growth typically reduces GDP per capita. World GDP growth is generally positive but uneven in significance. Conclusions: Resource use is conditional: welfare outcomes depend on fiscal regimes, demographic pressures, and structural transformation rather than windfall size alone. Full article

Enteric diseases are a significant challenge for the poultry industry, causing substantial economic losses and affecting productivity. Turkey astrovirus (TAstV) types 1 and 2 and avian nephritis virus (ANV) are recognized as viral pathogens contributing with enteric diseases in turkeys, particularly in young poults. These viruses, part of the Astroviridae family, are small, round, non-enveloped, positive-sense RNA viruses with high prevalence in turkey flocks. Despite their importance, they had not been identified in Ecuador until now. This study presents the first detection and molecular characterization of TAstV-1, TAstV-2, and ANV in Ecuadorian turkeys using RT-qPCR assays based on SYBR Green, developed and optimized for high sensitivity and specificity. Two hundred intestinal samples were collected from turkeys with enteric disorders, along with fifty cloacal swabs from apparently healthy turkeys in Pichincha Province. The RT-qPCR assays developed demonstrated a limit of detection of one copy of viral genetic material and high repeatability, with inter and intra-assay coefficients of variation below 1%. Based on these tests, TAstV was detected in 93% of turkey samples with gastroenteritis, and none of the samples of the healthy group tested positive, with ANV being the most prevalent, followed by TAstV-2 and TAstV-1. Phylogenetic analysis of the partial ORF1b gene confirmed the genetic relationships between Ecuadorian strains and those from other countries, highlighting possible routes of introduction and evolution of the virus. Co-infections with TAstV-2 and ANV were common, while single infections were predominantly caused by ANV. These findings underscore the critical need for surveillance and biosecurity measures to control the spread of these viruses within Ecuador’s poultry industry. This study provides valuable insights on astrovirus presence in Ecuadorian turkey flocks and establishes robust diagnostic tools for monitoring and managing turkey astrovirus infections. Full article