Effects of apigenin on the function of human α7-nicotinic acetylcholine receptors expressed in oocytes.

The effects of apigenin, a plant flavonoid, were investigated using the two-electrode voltage-clamp technique on the function of the cloned α7 subunit of the human nicotinic acetylcholine (α7-nACh) receptor expressed in oocytes. Currents induced by ACh (100 μM) were reversibly potentiated by apigenin with an EC value of 5.4 µM in a voltage-independent manner.

Causal evidence for the primordiality of colours in trans-Neptunian objects.

The origins of the colours of trans-Neptunian objects (TNOs) represent a crucial unresolved question, central to understanding the history of our Solar system. Recent observational surveys revealed correlations between the eccentricity and inclination of TNOs, and their colours. This rekindled the long-standing debate on whether these colours reflect the conditions of TNO formation or their subsequent evolution.

A network analysis of gender differences in unresolved attachment, post-traumatic stress following COVID-19, psychiatric comorbidity, and contamination fear in adolescents: Implications for psychotherapy.

Objectives: This study used a network approach to examine gender differences in adolescents regarding unresolved attachment styles, COVID-19 PTSD symptoms, comorbid psychiatric symptoms, and contamination fear. The rationale for the study stems from the suggestion that parents' relationships with adolescents (i.e.

Raw event-based adversarial attacks for Spiking Neural Networks with configurable latencies.

Spiking Neural Networks (SNNs) and data from Dynamic Vision Sensors (DVSs) offer energy-efficient solutions for edge devices with limited battery life. The input latencies of event data to SNNs are critical for energy savings, and reducing these latencies through configurable parameters is essential. However, security concerns, particularly adversarial attacks on SNNs, are increasingly significant.

Multivariable optimal control for hemodialysis: A physiologically-grounded simulation study.

This study introduces a novel multivariable optimal control framework for hemodialysis, which uniquely integrates five physiological states (blood urea concentration, fluid volume, blood pressure, electrolytes, and hemoglobin) with three clinically adjustable inputs (ultrafiltration rate, blood flow, and dialysate composition). By employing the limited-memory Broyden-Fletcher-Goldfarb-Shanno-B (L-BFGS-B) algorithm with patient-specific box constraints, the model enforces patient-specific physiological safety limits while dynamically balancing clinical targets. Numerical simulations demonstrate the stabilization of key parameters within ±5% of clinical benchmarks (e.

Prediction of cellular morphology changes under perturbations with a transcriptome-guided diffusion model.

Investigating cell morphology changes after perturbations using high-throughput image-based profiling is increasingly important for phenotypic drug discovery, including predicting mechanisms of action (MOA) and compound bioactivity. The vast space of chemical and genetic perturbations makes it impractical to explore all possibilities using conventional methods. Here we propose MorphDiff, a transcriptome-guided latent diffusion model that simulates high-fidelity cell morphological responses to perturbations.

Blockchain-enhanced electoral integrity: a robust model for secure digital voting systems in Oman.

Background: Ensuring the security and trustworthiness of a digitized and automated electoral process remains a significant challenge in democratic systems. As digital voting systems are increasingly being investigated worldwide, ensuring the integrity of the process using robust security measures is of great importance. This paper presents a simplified model to enhance electoral integrity by leveraging Blockchain technology in the context of Oman's digital voting system.

Balancing the local-international dialectic in community psychology pedagogy: Lessons from adapting American curricula in the United Arab Emirates.

This study analyzes the localization of a US-designed Social Innovation course in the UAE as a contested site of knowledge production rather than a straightforward curricular adaptation. Using reflexive thematic analysis of lesson plans and faculty reflections, we identified two themes: Curricular Containment and Cultural Substitution Without Epistemic Transformation. These demonstrate how localization efforts simplified content and replaced cultural references without embedding local epistemologies or challenging dominant frameworks.

Heavy Metal Pollution in Arid Urban Environments: Anthropogenic and Geogenic Insights from Road Dust in the United Arab Emirates.

Dust is a significant environmental concern due to its pervasive nature and potential health risks, particularly from heavy metals. This is exacerbated in urban areas, where dust can act as a reservoir for pollutants, posing risks to human health through various exposure pathways. This study aims to explore and compare the distribution of heavy metals in road dust from two distinct cities in the UAE: Dubai, a commercial hub, and Khor Fakkan, a coastal town with industrial activities.

Dual-model approach for accurate chest disease detection using GViT and swin transformer V2.

The precise detection and localization of abnormalities in radiological images are very crucial for clinical diagnosis and treatment planning. To build reliable models, large and annotated datasets are required that contain disease labels and abnormality locations. Most of the time, radiologists face challenges in identifying and segmenting thoracic diseases such as COVID-19, Pneumonia, Tuberculosis, and lung cancer due to overlapping visual patterns in X-ray images.

A Systematic Review of School-Based Behavioral Interventions and the Symbolic Labor of Inclusion for Children with Chronic Illness.

Chronic illness affects children's health and disrupts the spatial and temporal aspects of schooling by complicating attendance, interrupting learning routines, and exposing institutional rigidity. While many educational systems treat chronicity as an exception to be managed, this review reconceptualizes it as a pedagogical and symbolic challenge to normative assumptions about inclusion, care, and participation. To systematically examine how school-based behavioral and psychosocial interventions support children and adolescents with chronic health conditions (CHCs) in inclusive educational settings and to analyze what these interventions reveal about institutional practices of care and recognition.

High GVHD Prevalence in Travel-Based SCT despite Young Patients and HLA Matching.

: Patients from regions without stem cell transplantation (SCT) facilities often seek treatment abroad and return home for post-transplant care. Although extensive data exist on graft-versus-host disease (GVHD) and its risk factors, information on international SCT patients returning to countries that lack transplant facilities and expertise is scarce and not well documented. : We screened 149 transplant recipients and analyzed the data of 91 patients who received transplants abroad and were followed up at our center from January 2019 to December 2022.

Transgene-free generation of mouse post-gastrulation whole embryo models solely from naive ESCs and iPSCs.

The generation of post-gastrulation stem cell-derived mouse embryo models (SEMs) exclusively from naive embryonic stem cells (nESCs) has underscored their ability to give rise to embryonic and extra-embryonic lineages. However, existing protocols for mouse SEMs rely on the separate induction of extra-embryonic lineages and on ectopic expression of transcription factors to induce nESC differentiation into trophectoderm (TE) or primitive endoderm (PrE). Here, we demonstrate that mouse nESCs and naive induced pluripotent stem cells (niPSCs) can be simultaneously co-induced, via signaling pathway modulation, to generate PrE and TE extra-embryonic cells that self-organize into embryonic day (E) 8.

Assessing the adversarial robustness of multimodal medical AI systems: insights into vulnerabilities and modality interactions.

The emergence of both task-specific single-modality models and general-purpose multimodal large models presents new opportunities, but also introduces challenges, particularly regarding adversarial attacks. In high-stakes domains like healthcare, these attacks can severely undermine model reliability and their applicability in real-world scenarios, highlighting the critical need for research focused on adversarial robustness. This study investigates the behavior of multimodal models under various adversarial attack scenarios.

What drives weight status among female university students? A machine learning analysis of sociodemographic, dietary, and lifestyle determinants.

Background: Obesity and underweight are increasingly common among young adult women, often resulting from complex interactions between diet, lifestyle, and socioeconomic factors. This study addresses that gap by applying machine learning to a wide range of behavioral, dietary, and demographic data. The main research question asks: What are the key factors influencing weight status among female university students, and how accurately can machine learning models identify them? We hypothesize that different factors are significantly associated with underweight, overweight, and obesity, and that machine learning can reliably detect these patterns.

Digital Stress Scale (DSC): Development and Psychometric Validation of a Measure of Stress in the Digital Age.

(1) Background: The integration of digital technologies such as electronic health records (EHRs), telepsychiatry, and communication platforms has transformed the mental health sector a lot compared to in previous years. While these tools enhance service delivery, they also introduce unique stressors. Despite growing concerns, there is no validated instrument specifically designed to measure the digital stress experienced by mental health professionals.

Vitamin K and women's health: a review.

Vitamin K is a fat-soluble vitamin essential in various physiological functions such as blood coagulation, bone metabolism, cardiovascular health, glucose regulation, immune function, neuroprotection, and vascular health. In this narrative review, studies from databases including PubMed, Google Scholar, Scopus, and the institutional database of Zayed University were selected. The role of vitamin K in women's health, with a focus on osteoporosis, postmenopausal health, cardiovascular health, diabetes, cancer, kidney health, brain health, vascular health, and pregnancy were explored.

Two origins of the winter subsidence in and around the Arabian Peninsula.

Hydrological surface loads, such as snowpack and soil moisture, are the main drivers of seasonal crustal movements as seen by space geodetic techniques. In addition to that, seawater sometimes exerts additional forces for coastal stations, and the atmosphere often plays an important role for stations within continents. Here we report a case in and around the Arabian Peninsula.

Drug Development in Abu Dhabi: Advancing Innovation Through Government Support and a Thriving Ecosystem.

Drug development is a complex, high-risk, and resource-intensive process, with global challenges such as high costs, regulatory hurdles, and low clinical trial success rates. These obstacles are especially acute for biotech startups and companies in emerging markets, where access to infrastructure, patient populations, and capital can be limited. This Perspective advocates for Abu Dhabi's emerging life sciences ecosystem as a potential framework for other regions seeking to accelerate pharmaceutical innovation.

Trends in the use of non-nutritive sweeteners among female university students in the United Arab Emirates.

Objective: This study aimed to explore the consumption patterns of non-nutritive sweeteners (NNS) among female university students in the United Arab Emirates (UAE), in the context of rising health awareness.

Methods: A cross-sectional survey was conducted from February to April 2023 among female university students in the UAE. A total of 192 participants aged 18 and above were recruited through convenience sampling.

Diet quality and food insecurity in Lebanon: insights into dietary diversity, mediterranean diet adherence, and phytochemical intake among adults.

Lebanon is undergoing a nutrition transition that increases the risk of nutritional deficiencies and noncommunicable diseases. This study assessed diet quality-measured by adherence to the Mediterranean diet (MD), household dietary diversity (HDD), and the dietary phytochemical index (DPI)-and examined its associations with sociodemographic factors and food insecurity (FI) among Lebanese adults. A cross-sectional survey was conducted from May to September 2022, involving a nationally representative sample of 444 adults aged 18-64 years.

Effect of Vitamin D Supplementation on Human Gut Microbiota: A Systematic Review of Randomized Controlled Trials.

Context: Studies findings have suggested that vitamin D plays a critical role in maintaining overall health, including having a potential impact on gut microbiota composition, which influences various physiological processes.

Objectives: To examine the effects of vitamin D supplementation on human gut microbiota composition and diversity by analyzing findings from randomized controlled trials (RCTs).

Data Sources: A comprehensive search of the MEDLINE, Web of Science, Scopus, and the Cochrane Library electronic databases was conducted to identify relevant studies published from January 1, 2015, to November 30, 2024.

Cross-attention graph neural networks for inferring gene regulatory networks with skewed degree distribution.

Background: Inferring Gene Regulatory Networks (GRNs) from gene expression data is a pivotal challenge in systems biology. Most existing methods fail to consider the skewed degree distribution of genes, complicating the application of directed graph embedding methods.

Results: The Cross-Attention Complex Dual Graph Embedding Model (XATGRN) was proposed to address this issue.

A hybrid fog-edge computing architecture for real-time health monitoring in IoMT systems with optimized latency and threat resilience.

The advancement of the Internet of Medical Things (IoMT) has transformed healthcare delivery by enabling real-time health monitoring. However, it introduces critical challenges related to latency and, more importantly, the secure handling of sensitive patient data. Traditional cloud-based architectures often struggle with latency and data protection, making them inefficient for real-time healthcare scenarios.

Deep phenotyping of health-disease continuum in the Human Phenotype Project.

The Human Phenotype Project (HPP) is a large-scale deep-phenotype prospective cohort. To date, approximately 28,000 participants have enrolled, with more than 13,000 completing their initial visit. The project is aimed at identifying novel molecular signatures with diagnostic, prognostic and therapeutic value, and at developing artificial intelligence (AI)-based predictive models for disease onset and progression.