Jeddah University

Adults with cardiometabolic conditions are at high risk of smoking-related morbidity and mortality. However, little is known about patterns and predictors of e-cigarette use in this population. The study therefore aims to examine the prevalence and predictors of current e-cigarette use among adults with cardiometabolic conditions. We analysed data from 6633 adults with cardiometabolic conditions who participated in the 2017, 2018, 2019, and 2021 waves of the Scottish Health Survey. For this study, cardiometabolic conditions were defined broadly to include diabetes, high blood pressure, angina, heart attack, and stroke, as well as other physician-diagnosed cardiovascular conditions (irregular heart rhythm, heart murmur, and other heart conditions). Current e-cigarette use was defined as self-reported present use of an e-cigarette or vaping device. Firth penalised multivariable logistic regression was used to examine sociodemographic, behavioural, and health related predictors of e-cigarette use, reporting adjusted odds ratios (AORs), 95 % confidence intervals (CIs), and p values. Overall, 5.2 % (95 % CI: 4.6-5.8) of adults with cardiometabolic conditions were current e-cigarette users, with prevalence ranging from 4.6 % (95 % CI: 4.0-5.2) among those with high blood pressure to 8.0 % (95 % CI: 6.1-10.5) among stroke survivors. E-cigarette use was more common in younger adults. Compared with those aged 16-24 years, adults aged 25-34 years (AOR 0.39, 95 % CI: 0.18-0.87, p = 0.021) and those aged 75+ years (AOR 0.05, 95 % CI: 0.02-0.12, p < 0.001) had lower odds of current e-cigarette use. Compared with never smokers, odds were substantially higher among current smokers (AOR 31.27, 95 % CI: 13.19-74.14, p < 0.001) and ex-smokers (AOR 39.65, 95 % CI: 18.06-87.06, p < 0.001). Reporting a desire to quit smoking was associated with higher odds of e-cigarette use compared with not wanting to quit or not smoking (AOR 2.12, 95 % CI: 1.38-3.25, p = 0.001). Higher odds were also observed among individuals with no educational qualifications (AOR 1.75, 95 % CI: 1.18-2.59, p = 0.005) and those reporting poor general health (AOR 1.36, 95 % CI: 1.04-1.77, p = 0.023). Sex, ethnicity, deprivation, psychological distress, and alcohol consumption were not significantly associated with use in the adjusted model. Among adults with cardiometabolic conditions, e-cigarette use was more common among younger adults, current smokers, ex-smokers, those who wanted to quit smoking, individuals with lower educational attainment, and those reporting poorer health. These findings suggest the need for clinicians managing patients with cardiometabolic conditions to address e-cigarette use in the context of smoking cessation and secondary prevention.

ABSTRACTRestless legs syndrome (RLS) is a neurological sensorimotor disorder characterized by an irresistible urge to move the legs, typically worsening at night and leading to sleep disturbance. While first‐generation antihistamines are recognized as common pharmacological triggers, second‐generation nonsedating antihistamines are rarely implicated. We report the case of a 35‐year‐old man with allergic rhinitis who developed new‐onset RLS after 1 month of treatment with fexofenadine 180 mg daily. His symptoms included an uncomfortable urge to move his legs, particularly in the evening and at night, which interfered significantly with sleep quality. Clinical examination and laboratory studies, including renal function and iron indices, were unremarkable. Despite several medical consultations, the symptoms persisted until fexofenadine was discontinued. Remarkably, his symptoms resolved completely within days of withdrawal without pharmacologic intervention and did not recur on follow‐up. This case highlights a rare but clinically relevant association between fexofenadine and RLS. Although fexofenadine is classified as a peripherally selective, nonsedating antihistamine, this report underscores that even second‐generation agents may contribute to RLS in susceptible individuals. Recognition of this potential adverse effect is important, as prompt discontinuation of the offending medication alone can result in rapid and complete symptom resolution. Clinicians should therefore maintain vigilance when evaluating patients with new‐onset RLS and carefully review medication histories, including use of second‐generation antihistamines such as fexofenadine.

Listeria monocytogenes is a significant foodborne pathogen that poses serious risks to public health and the food industry. In humans, infections can lead to severe clinical outcomes, including gastroenteritis, septicemia, meningitis, encephalitis, and pregnancy-related complications such as stillbirths and spontaneous miscarriages. Contamination of meat and meat products has been associated with numerous outbreaks and sporadic cases worldwide. The detection and identification of L. monocytogenes involve traditional microbiological and biochemical methods, as well as advanced molecular techniques, including the polymerase chain reaction and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. This review provides a comprehensive overview of the microbiological characteristics, global prevalence, and antibiotic resistance profiles of L. monocytogenes . The emergence of multidrug-resistant strains underscores the importance of ongoing surveillance, effective antimicrobial stewardship, and rigorous adherence to food safety measures. Integrated efforts across the meat production and processing chain, combined with rapid diagnostic tools and public health interventions, are crucial to reducing the risk of listeriosis and ensuring the safety of meat products globally.

Chronic kidney disease (CKD) is a systemic condition marked by progressive loss of renal function, often accompanied by complications beyond the kidneys. Among these, oral soft tissue inflammation remains under-recognized despite its growing clinical relevance. Individuals with CKD frequently experience gingivitis, periodontitis, oral mucosal lesions, and xerostomia, all of which may exacerbate systemic inflammation. The bidirectional relationship between renal dysfunction and oral disease is mediated through immune suppression, accumulation of uremic toxins, and microbial dysbiosis. Neutrophil impairment, altered cytokine profiles, and changes in salivary composition contribute to a compromised oral environment, allowing chronic inflammation to persist in soft tissues. The inflammatory burden from oral tissues may influence CKD progression by elevating systemic markers such as interleukin-6 and C-reactive protein. Moreover, patients with advanced CKD or those receiving dialysis often report nutritional challenges due to oral discomfort, which further complicates disease management. Periodontal pathogens and their byproducts may enter systemic circulation, potentially aggravating endothelial dysfunction and cardiovascular risks associated with renal impairment. Despite these associations, oral health is seldom integrated into CKD care protocols. Preventive strategies involving routine screening, patient education, and interdisciplinary collaboration are essential for early detection and intervention. Coordinated care models involving nephrologists and dental professionals can facilitate timely treatment and reduce systemic complications. Enhancing awareness of the oral-systemic link and prioritizing oral health within CKD management may improve long-term outcomes and quality of life for affected individuals.

This chapter explores Artificial Intelligence's (AI) role in promoting digital equity in education from 2024 to 2030. As digital technologies reshape learning, AI offers solutions to bridge the digital divide, with projections of a 20% improvement in underserved students' outcomes by 2026 and a 50% reduction in achievement gaps by 2030. Key areas include adaptive learning systems, Intelligent Tutoring Systems (ITS), predictive analytics for resource allocation, and accessibility tools. The chapter addresses critical challenges such as data privacy, algorithmic bias, and equitable access, presenting case studies and benchmarks for success. It outlines a roadmap for AI integration, recommending 80% AI literacy among educators by 2025, robust data protection frameworks, and 95% student digital literacy by 2030. This framework balances innovation with ethical considerations, offering actionable steps for institutions to ensure inclusive, AI-driven transformation.

Thalassemia is an inherited hemoglobin disease characterized by persistent anemia, oxidative and iron overload due to transfusion, creating severe clinical and economic issues in South Asia. The adverse effects and adverse effects of current treatment options highlight the need to have safer and multi-target options. In this study, a comprehensive in silico pharmacoinformatic methodology was applied to determine the therapeutic value of Azadirachta indica (Neem) phytochemicals on thalassemia-related targets. One hundred and five phytocompounds were shortlisted, and the number of those passing drug-likeness and ADMET filters evaluated at SwissADME, MolSoft (v6.8) and ADMETlab 3.0 was 350. The intersecting genes were predicted by target prediction with SwissTargetPrediction and functionally enriched with the help of DAVID (v6.8) and KEGG (v113.0). Significantly enriched pathways were Lipid and Atherosclerosis (Benjamini [Formula: see text] 0.0236), Apoptosis ([Formula: see text] 0.043) and Chemical Carcinogenesis ([Formula: see text] 0.00167). The central hub genes were TNF, TP53, PPARG, CYP3A44 and found by the network analysis with the help of STRING (v11.5) and Cytoscape (v3.10.0). Molecular docking was done using PyRx (v0.9.8) with AutoDock Vina (v1.2.3) being implemented. The highest affinity of the screened compounds was found to be Naringenin, with a binding energy of −9.8 kcal/mol (PDB ID: 1v04), and it was greater than that of Hydroxyurea (−8.9 kcal/mol), Deferiprone (−5.3 kcal/mol) and Deferasirox (−5.3 kcal/mol). Quercetin, Luteolin and Genistein had a good binding profile with the presence of stable hydrogen bonding and [Formula: see text]–[Formula: see text] interactions as illustrated in PyMOL (v2.5). This cumulative computational pipeline lays significant evidence that phytochemicals derived from Neem are prime multi-target lead compounds to use as adjuncts in the treatment of thalassemia. These findings require further confirmation through molecular dynamics simulations and experimental confirmation.