Search Results (2,228)

Obstructive sleep apnea (OSA) is a prevalent disorder linked to metabolic complications such as diabetes and cardiovascular disease. By fragmenting normal sleep architecture, OSA perturbs the growth hormone/insulin-like growth factor (GH/IGF) axis and alters circulating levels of IGF-binding proteins (IGFBPs). A prior clinical observation of elevated IGFBP4 in OSA patients motivated the present investigation in a controlled animal model. Building on the previously reported protocol, OSA was induced in male C57BL/6 mice (9–12 weeks old) through intralingual injection of polytetrafluoroethylene (PTFE), producing tongue hypertrophy, intermittent airway obstruction, and hypoxemia. After 8–10 weeks, the study assessed (1) hypoxia biomarkers—including HIF-1α and VEGF expression—and (2) neurobehavioral outcomes in anxiety and cognition using the open-field and novel object recognition tests. PTFE-treated mice exhibited a significant increase in circulating IGFBP4 versus both baseline and control groups. Hepatic Igfbp4 mRNA was also upregulated. Behaviorally, PTFE mice displayed heightened anxiety-like behavior and impaired novel object recognition, paralleling cognitive deficits reported in human OSA. These findings validate the PTFE-induced model as a tool for studying OSA-related hypoxia and neurocognitive dysfunction, and they underscore IGFBP4 as a promising biomarker and potential mediator of OSA’s systemic effects. Full article

Invasive infections with rare yeasts are increasing worldwide and are associated with higher mortality rates due to their resistance to antifungal drugs. Accurate antifungal susceptibility testing (AFST) is crucial for proper management of rare yeast infections. We performed AFST of 74 Candida kefyr isolates by Etest, EUCAST-based MICRONAUT-AM assay (MCN-AM) and reference Clinical and Laboratory Standards Institute broth microdilution method (CLSI). Essential agreement (EA, ±1 two-fold dilution), categorical agreement (CA), major errors (MEs) and very-major errors (VmEs) were determined using epidemiological cut-off values of ≤1.0 µg/mL, ≤0.03 µg/mL, ≤0.5 µg/mL and ≤1 µg/mL, defining wild-type isolates for fluconazole, voriconazole, micafungin and amphotericin B (AMB), respectively. Results for AMB susceptibility were correlated with ERG2/ERG3 mutations and total-cell sterols. CA of ≥97% was recorded between any two methods while EA varied between 72 and 82%, 87 and 92%, and 49 and 76% for fluconazole, voriconazole and micafungin, respectively. For AMB, CAs between CLSI and Etest; CLSI and MCN-AM; MCN-AM and Etest were 95% (4 ME, 0 VmE), 96% (3 ME, 0 VmE) and 99%, respectively, while EA varied from 32% to 69%. Non-synonymous ERG2/ERG3 mutations and no ergosterol were found in seven of eight isolates of non-wild types for AMB by Etest. Our data show that Etest, CLSI and MCN-AM methods are suitable for AFST of C. kefyr for fluconazole, voriconazole and micafungin. Excellent CAs for AMB between Etest and MCN-AM with concordant sterol profiles but not with CLSI suggest that Etest is also an excellent alternative for the detection of C. kefyr isolates with reduced susceptibility to AMB. Full article

Evaporative cooling (EC) offers an energy-efficient alternative to direct expansion (DX) cooling but suffers from high water consumption. This limitation can be mitigated by pre-cooling incoming fresh air using cooler exhaust air via energy recovery. This study presents and optimizes a solar-driven EC system integrated with underfloor air distribution (UFAD) to enhance thermal comfort and minimize water use in a temporary office in Riyadh’s arid climate. A 3D CFD model was developed and validated against published data to simulate indoor airflow, providing data for thermal comfort evaluation using the predicted mean vote model in cases with and without energy recovery. A year-round hourly energy analysis revealed that the solar-driven EC-UFAD system reduces grid power consumption by 93.5% compared to DX-based UFAD under identical conditions. Energy recovery further cuts annual EC water usage by up to 31.3%. Operational costs decreased by 84% without recovery and 87% with recovery versus DX-UFAD. Full article

Short sleep has been linked to overweight, possibly via alterations in appetite-regulating hormones, but findings are inconsistent. Sex differences may contribute to this variability. This systematic review examines whether sex modifies the hormonal response to sleep curtailment. PubMed, Embase, Cochrane, CINAHL, and PsycINFO were searched for English-language experimental studies published before December 2024. Included studies assessed at least one appetite-regulating hormone and presented sex-specific analyses. Studies involving health conditions affecting sleep, circadian misalignment, or additional interventions were excluded. Risk of bias was assessed using the Revised Cochrane Risk-of-Bias tool (RoB 2). Eight studies (n = 302 participants) met inclusion criteria. A narrative synthesis of the findings was conducted for each hormone separately to explore potential differences in their response to sleep restriction. Some sex-related variations in hormonal response to sleep restriction have been observed for leptin (four studies, n = 232), insulin (three studies, n = 56), glucagon-like peptide-1 (one study, n = 27), ghrelin (three studies, n = 87), adiponectin (two studies, n = 71) and thyroxine (two studies, n = 41). However, findings were inconsistent with no clear patterns. No sex-related differences were found for glucagon or PYY, though data were limited. Findings suggest sex may influence hormonal responses to sleep restriction, but inconsistencies highlight the need to consider factors such as BMI and energy balance. Well-controlled, adequately powered studies are needed to clarify these effects. Full article

A simple and inexpensive thermal oxidation process is used to grow β-Ga₂O₃ oxide (β-Ga₂O₃) thin films/nanorods on a c-plane (0001) sapphire substrate using Ag/Au catalysts. The effect of these catalysts on the growth mechanism of Ga₂O₃ was studied by different characterization techniques, including X-ray diffraction analysis (XRD), Scanning Electron Microscopy (SEM), and Energy Dispersive X-ray analysis (EDX). The XRD results of the grown Ga₂O₃ on a sapphire substrate show three sharp diffraction peaks located at 19.31°, 38.70° and 59.38° corresponding to the $\left(\overline{2}01\right), \left(\overline{4}02\right)$ and $\left(\overline{6}03\right)$ planes of β-Ga₂O₃. Field Emission Scanning Electron Microscope (FESEM) analysis showed the formation of longer and denser Ga₂O₃ nanowires at higher temperatures, especially in the presence of silver nanoparticles as catalysts. Full article

Cystinosis is a rare systemic disease characterized by the accumulation of cystine in tissues, leading to multi-organ damage. Infantile nephropathic cystinosis is the dominant and severe form of cystinosis with critical renal manifestations that require kidney transplantation at an early age if left untreated. Cysteamine, the lifelong cystine-depleting therapy, is the mainstay treatment of nephropathic cystinosis. Cysteamine prevents cystine crystal formation and delays disease progression. While the initially introduced cysteamine consists of an immediate-release (IR) formulation, a delayed-release (DR) formulation has been developed with a simplified dosing regimen (Q12H instead of Q6H) and an improved quality of life while maintaining comparable efficacy. Due to the rare incidence of the disease and lack of international guidelines, diagnosis and treatment initiation are oftentimes delayed, leading to a poor prognosis. Pediatric and adult nephrologists from Kuwait, Saudi Arabia, the United Arab Emirates (UAE), and Qatar, in addition to one international expert from Amsterdam, convened to share their clinical experience, reflecting on the challenges encountered and therapeutic approaches followed in the management of nephropathic cystinosis in the Gulf Cooperation Council (GCC) region. Experts completed a multiple-choice questionnaire and engaged in structured discussions, where they shed light on gaps and limitations with regard to diagnostic tests and criteria to ensure early diagnosis and timely treatment initiation. Based on available literature, experts suggested an algorithm to help guide nephropathic cystinosis management in the GCC. It is highly recommended for patients who do not tolerate IR-cysteamine and do not adhere to IR-cysteamine treatment to switch to DR-cysteamine. Given the systemic nature of the disease, a multi-disciplinary approach is required for optimal disease management. Full article

Several single-nucleotide polymorphisms (SNPs) across the lipoprotein lipase (LPL) gene have been found to be associated with dyslipidemia and obesity. Several InDels and SNPs in exon 1, intron 2, and intron 7 have been reported; however, their association with lipid parameters and body mass index (BMI) remains unclear. Here, we aimed to investigate the relationship among LPL variants, lipid levels, and BMI in a Kuwaiti population. Sanger sequencing was performed on three targeted regions of the LPL gene. Based on the minor allele frequency, Hardy–Weinberg equilibrium, and linkage disequilibrium, five SNPs were selected and genotyped in a cohort of 688 Kuwaiti samples to investigate their association with lipid levels and BMI. A total of 30 variants (6 InDels and 24 SNPs) were identified; of them, 5 SNPs (rs1800590, rs74377536, rs8176337, rs303, and rs304) were selected for their association with BMI and lipid levels. The G-allele of rs8176337 was found to be associated with increased BMI (β = 1.41; 95% confidence interval = 0.22–2.60; p = 0.02). In addition, an association was observed for rs303 and rs304 with both cholesterol and LDL (p < 0.05). Overall, our results demonstrate an association between LPL variants and lipid levels, and the observed association between rs8176337 and BMI was novel. Full article

Photovoltaic panels have become a promising solution for generating renewable energy and reducing our reliance on fossil fuels by capturing solar energy and converting it into electricity. The effectiveness of this conversion depends on several factors, such as the quality of the solar panels and the amount of solar radiation received in a specific region. This makes accurate solar irradiance forecasting essential for planning and managing efficient solar power systems. This study examines the application of machine learning (ML) models for accurately predicting global horizontal irradiance (GHI) using a three-year dataset from six distinct photovoltaic stations: NELHA, ULL, HSU, RaZON+, UNLV, and NWTC. The primary aim is to identify optimal shared features for GHI prediction across multiple sites using a 30 min time shift based on autocorrelation analysis. Key features identified for accurate GHI prediction include direct normal irradiance (DNI), diffuse horizontal irradiance (DHI), and solar panel temperatures. The predictions were performed using tree-based algorithms and ensemble learners, achieving $R^2$ values exceeding 95% at most stations, with NWTC reaching 99%. Gradient Boosting Regression (GBR) performed best at NELHA, NWTC, and RaZON, while Multi-Layer Perceptron (MLP) excelled at ULL and UNLV. CatBoost was optimal for HSU. The impact of time-shifting values on performance was also examined, revealing that larger shifts led to performance deterioration, though MLP performed well under these conditions. The study further proposes a stacking ensemble approach to enhance model generalizability, integrating the strengths of various models for more robust GHI prediction. Full article

Cardiovascular diseases (CVDs) remain the leading cause of death globally, underscoring the urgent need for data-driven early diagnostic tools. This study proposes a multilayer artificial neural network (ANN) model for heart disease prediction, developed using a real-world clinical dataset comprising 13,981 patient records. Implemented on the Orange data mining platform, the ANN was trained using backpropagation and validated through 10-fold cross-validation. Dimensionality reduction via principal component analysis (PCA) enhanced computational efficiency, while Shapley additive explanations (SHAP) were used to interpret model outputs. Despite achieving 83.4% accuracy and high specificity, the model exhibited poor sensitivity to disease cases, identifying only 76 of 2233 positive samples, with a Matthews correlation coefficient (MCC) of 0.058. Comparative benchmarks showed that random forest and support vector machines significantly outperformed the ANN in terms of discrimination (AUC up to 91.6%). SHAP analysis revealed serum creatinine, diabetes, and hemoglobin levels to be the dominant predictors. To address the current study’s limitations, future work will explore LIME, Grad-CAM, and ensemble techniques like XGBoost to improve interpretability and balance. This research emphasizes the importance of explainability, data representativeness, and robust evaluation in the development of clinically reliable AI tools for heart disease detection. Full article

Root caries is a form of decay affecting root surfaces of teeth, often exacerbated by periodontal disease, reduced salivary flow, and compromised mucosal health, all factors strongly influenced by nutrition. Despite this connection, few studies have addressed the role of vitamins in oral health. This study examines the association between serum levels of alpha-carotene (α-carotene), a potent antioxidant and proxy for vitamin A, and the experience of root caries. Using data from the 2017–2018 National Health and Nutrition Examination Survey (NHANES), we conducted a cross-sectional analysis and applied a weighted multiple logistic regression model, adjusting for potential confounders including age, sex, education level, race, income-to-poverty ratio, and presence of gum disease. Higher serum α-carotene levels were inversely associated with root caries. Each unit increase in serum α-carotene was associated with a 9% decrease in the odds of having root caries (OR = 0.91; 95% CI: 0.86–0.97; p = 0.004). In this nationally representative sample of U.S. adults, lower serum α-carotene levels were associated with a higher prevalence of root caries. These findings highlight the potential role of nutritional assessment and integration in oral health. Longitudinal and mechanistic studies are needed to confirm and further explore α-carotene’s effects on oral health. Full article

A new, simple machine was developed to address a long-standing challenge in biomedical and mechanical engineering: how to enhance the primary stability and long-term integration of screws and implants in low-density or heterogeneous materials, such as bone or composite substrates. Traditional screws often rely solely on external threading for fixation, leading to limited cohesion, poor integration, or early loosening under cyclic loading. In response to this problem, we designed and built a novel device that leverages a unique mechanical principle to simultaneously perforate, collect, and compact the substrate material during insertion. This mechanism results in an internal material interlock, enhancing cohesion and stability. Drawing upon principles from physics, chemistry, engineering, and biology, we evaluated its biomechanical behavior in synthetic bone analogs. The maximum insertion (MIT) and removal torques (MRT) were measured on synthetic osteoporotic bones using a digital torquemeter, and the values were compared directly. Experimental results demonstrated that removal torque (mean of 21.2 Ncm) consistently exceeded insertion torque (mean of 20.2 Ncm), indicating effective material interlocking and cohesive stabilization. This paper reviews the relevant literature, presents new data, and discusses potential applications in civil infrastructure, aerospace, and energy systems where substrate cohesion is critical. The findings suggest that this new simple machine offers a transformative approach to improving fixation and integration across multiple domains. Full article

The present study investigated the impact of a disability awareness program on the attitudes of university students at Al-Ahliyya Amman University towards people with disabilities. The study employed a randomized, two-group, pre- and post-test design. A total of 60 university students were randomly allocated to either the experimental or control group. The results of a survey showed that those in the experimental group, in comparison with the control group, exhibited a statistically significant increase in the favorability of their attitudes towards people with disabilities following the implementation of the program. Based on the results of this study, we recommend implementing disability awareness programs inside universities and subsequently evaluating their effectiveness in enhancing student attitudes and interactions with people with disabilities, which in turn could lead to a more inclusive society and improve the quality of life for people with disabilities by reducing social barriers and fostering greater understanding and acceptance. The limitations of this study include its restriction to a single university setting and its utilization of a rather small sample size. The study did not assess the long-term effects of the disability awareness program. Full article

Fast charging accelerates lithium-ion battery operation but increases the risk of lithium (Li) plating—a process that undermines efficiency, longevity, and safety. Here, we introduce a predictive modeling framework that captures the onset and severity of Li plating under practical fast-charging conditions. By integrating an empirically parameterized SOC threshold model with time-dependent kinetic simulations and Arrhenius based thermal analysis, we delineate operating regimes prone to irreversible Li accumulation. The framework distinguishes reversible and irreversible plating fractions, quantifies energy losses, and identifies a critical activation energy (0.25 eV) associated with surface-limited deposition. Visualizations in the form of severity maps and voltage-zone risk classifications enable direct application to battery management systems. This approach bridges electrochemical degradation modeling with real-time charge protocol design, offering a practical tool for safe, high-performance battery operation. Full article

The evolution of electrical power systems into smart grids has brought about significant advancements in electricity generation, transmission, and utilization. These cutting-edge grids have shown potential as an effective way to maximize energy efficiency, manage resources effectively, and enhance overall reliability and sustainability. However, with the integration of complex technologies and interconnected systems inherent to smart grids comes a new set of safety and security challenges that must be addressed. First, this paper provides an in-depth review of the key considerations surrounding safety and security in smart grid environments, identifying potential risks, vulnerabilities, and challenges associated with deploying smart grid infrastructure within the context of the Internet of Things (IoT). In response, we explore both cryptographic and non-cryptographic countermeasures, emphasizing the need for adaptive, lightweight, and proactive security mechanisms. As a key contribution, we introduce a layered classification framework that maps smart grid attacks to affected components and defense types, providing a clearer structure for analyzing the impact of threats and responses. In addition, we identify current gaps in the literature, particularly in real-time anomaly detection, interoperability, and post-quantum cryptographic protocols, thus offering forward-looking recommendations to guide future research. Finally, we present the Multi-Layer Threat-Defense Alignment Framework, a unique addition that provides a methodical and strategic approach to cybersecurity planning by aligning smart grid threats and defenses across architectural layers. Full article

Background and Objectives: Caring for an individual with dementia encompasses many challenges. This can lead to increased burden, anxiety, and mental health issues among those taking care of them. Limited research exists investigating the care of people with dementia in Kuwait, particularly regarding the mental health of caregivers. There is a need to understand the impact of caregiver burden in this population. This study aimed to assess the level of burden of care, depression, anxiety, and well-being among caregivers of the elderly with dementia in Kuwait. Methods: This study used a descriptive and cross-sectional design. To measure the burden of care, depression, anxiety, and well-being of the caregivers, we utilized the Zarit Burden Interview, the Hospital Anxiety and Depression Scale, and the World Health Organization-Five Well-Being Index. A sensitivity analysis was conducted to compare the results of the parametric and non-parametric methods. Results: This study included 180 (65%) caregivers for the elderly with dementia and 98 (35%) without dementia. The descriptive statistics showed that caregivers for the elderly with dementia and caregivers for the elderly without dementia experienced moderate burden (17.21 ± 9.09 and 14.51 ± 8.08, respectively), borderline abnormal anxiety (9.92 ± 5.15 and 8.61 ± 4.79, respectively), borderline abnormal depression (8.69 ± 4.35 and 8.06 ± 4.24, respectively), and low mental health well-being (54.40 ± 25.10 and 58.90 ± 23.42, respectively). The t-test of independent samples and Mann–Whitney U test results showed that the burden and anxiety in the caregivers for the elderly with dementia group were statistically significantly higher than those in the caregivers for the elderly without dementia group (p = 0.015 and p = 0.039; p = 0.026 and p = 0.027, respectively). The ANOVA test and Kruskal–Wallis test revealed that the caregivers for the elderly with dementia group had statistically significant differences in burden (p < 0.001; p < 0.001), anxiety (p = 0.048; p = 0.043), depression (p = 0.017; p = 0.009), and mental health well-being (p = 0.001; p = 0.002) scores across various durations of care. The multiple linear regression showed that caregiving was a significant predictor of burden of care and anxiety, indicating that caregivers of the elderly with dementia experienced a higher burden of care than those caring for the elderly without dementia. In addition, confounders with significant influence were duration of care (p < 0.001), education level (p = 0.002), employment status (p = 0.008), and gender (p = 0.02). Conclusions: Family caregivers experienced significant levels of burden of care and anxiety when caring for the elderly with dementia. A multidimensional holistic approach is needed to provide family caregivers of the elderly with dementia with valuable interventions. Full article