Search Results (1,961)

The Mediterranean Diet (MD) has emerged as a comprehensive model for promoting human health and environmental sustainability. This review proposes reconceptualization of the traditional MD pyramid, highlighting its functional food components and their relevance to modern health challenges. Rooted in a rich cultural and gastronomic heritage, the MD extends beyond nutritional adequacy. It offers substantial nutraceutical benefits due to its high content of bioactive compounds such as polyphenols, carotenoids, omega-3 fatty acids, and phytosterols. These compounds contribute to the prevention and management of chronic non-communicable diseases through antioxidant and anti-inflammatory mechanisms. Simultaneously, the MD aligns with sustainable food system principles: it is predominantly plant-based; it promotes seasonal and local food sourcing; and it supports minimal food waste. In addition, this dietary pattern has been associated with a significantly lower ecological footprint compared to Western diets, thus supporting broader environmental goals. Ultimately, the MD stands as a scientifically grounded, culturally embedded, and ecologically viable approach to foster both individual and planetary wellbeing (One Health concept). Full article

Background: Dementia is a progressive neurodegenerative condition that impairs cognitive functions such as memory, language comprehension, and problem-solving. Assistive technologies can provide vital support at various stages of dementia, significantly improving the quality of life by aiding daily activities and care. However, for these technologies to be effective and widely adopted, a human-centred design (HCD) approach is of consequence for both their development and evaluation. Objectives: This scoping review aims to explore how HCD principles have been applied in the design of assistive technologies for people with dementia and to identify the extent and nature of their involvement in the design process. Eligibility Criteria: Studies published between 2017 and 2025 were included if they applied HCD methods in the design of assistive technologies for individuals at any stage of dementia. Priority was given to studies that directly involved people with dementia in the design or evaluation process. Sources of Evidence: A systematic search was conducted across five databases: Web of Science, JSTOR, Scopus, and ProQuest. Charting Methods: Articles were screened in two stages: title/abstract screening (n = 350) and full-text review (n = 89). Data from eligible studies (n = 49) were extracted and thematically analysed to identify design approaches, types of technologies, and user involvement. Results: The 49 included studies covered a variety of assistive technologies, such as robotic systems, augmented and virtual reality tools, mobile applications, and Internet of Things (IoT) devices. A wide range of HCD approaches were employed, with varying degrees of user involvement. Conclusions: HCD plays a critical role in enhancing the development and effectiveness of assistive technologies for dementia care. The review underscores the importance of involving people with dementia and their carers in the design process to ensure that solutions are practical, meaningful, and capable of improving quality of life. However, several key gaps remain. There is no standardised HCD framework for healthcare, stakeholder involvement is often inconsistent, and evidence on real-world impact is limited. Addressing these gaps is crucial to advancing the field and delivering scalable, sustainable innovations. Full article

The rapid development of generative artificial intelligence (GenAI) has revolutionized how individuals and organizations interact with technology. These systems, ranging from conversational agents to creative tools, are increasingly embedded in daily life. However, their effectiveness relies heavily on the usability of their graphical user interfaces (GUIs), which serve as the primary medium for user interaction. Moreover, the design of these interfaces must align with ethical principles such as transparency, fairness, and user autonomy to ensure responsible usage. This study evaluates the usability of GUIs for three widely-used GenAI applications, including ChatGPT (GPT-4), Gemini (1.5), and Claude (3.5 Sonnet) , using a heuristics-based and user-based testing approach (experimental-qualitative investigation). A total of 12 participants from a research organization in Australia, participated in structured usability evaluations, applying 14 usability heuristics to identify key issues and ethical concerns. The results indicate that Claude’s GUI is the most usable among the three, particularly due to its clean and minimalistic design. However, all applications demonstrated specific usability issues, such as insufficient error prevention, lack of shortcuts, and limited customization options, affecting the efficiency and effectiveness of user interactions. Despite these challenges, each application exhibited unique strengths, suggesting that while functional, significant enhancements are needed to fully support user satisfaction and ethical usage. The insights of this study can guide organizations in designing GenAI systems that are not only user-friendly but also ethically sound. Full article

This study investigates the perceptions of halal food among theology students from three culturally diverse cities: Istanbul, Berlin, and Kuala Lumpur. As individuals receiving formal religious education, theology students are expected to exhibit strong awareness of Islamic dietary principles. Utilizing a quantitative research design, data were collected from 210 participants via online surveys using validated Likert-type scales measuring halal awareness, halal literacy, religious commitment, social influence, perceived behavioral control, price value, hedonic motivation, and consumption habits. One-way ANOVA and post hoc Tukey tests revealed significant differences between cities in nearly all variables. Students in Kuala Lumpur consistently demonstrated higher scores, indicating a stronger alignment with institutionalized halal systems and collectivist cultural norms. Berlin participants reported lower awareness and influence levels, likely reflecting a more secular and individualistic environment. Istanbul students fell between the two, showing strong religious motivation but less structural support. The findings highlight how halal food perceptions are shaped not only by individual religiosity but also by cultural, political, and economic contexts. This study contributes to the literature by offering a cross-cultural perspective on halal consumption and underscores the importance of integrating structural and cultural factors into religious food behavior research. Full article

In recent years, there has been rapid advancement in single-molecule techniques, driven by their unparalleled precision in studying molecules whose sizes are beyond the diffraction limit. Among these techniques, optoplasmonic whispering gallery mode sensing has demonstrated great potential in label-free single-molecule characterization. It combines the principles of localized surface plasmon resonance (LSPR) and whispering gallery mode (WGM) sensing, offering exceptional sensing capabilities, even at the level of single ions. However, current optoplasmonic WGM sensing operates in a multiplexed channel, making it challenging to focus on individual binding sites of analyte molecules. In this article, we characterize different binding sites of DNA analyte molecules hybridizing to docking strands on the optoplasmonic WGM sensor, using the ratio of the resonance shift between sequential polar WGM modes. We identify specific docking sites that undergo transient interactions and eventually hybridize with the complementary analyte strands permanently. Full article

Background: Neonatal seizures are critical neurological events with long-term implications for brain development. Standard antiseizure medications, such as phenobarbital, often yield suboptimal seizure control and may be associated with neurotoxicity. This narrative review explores the role of vitamin B6 as a precision therapy in neonatal seizure syndromes, particularly in pyridoxine-responsive conditions. Methods: We conducted a narrative review of the biochemical functions of vitamin B6, focusing on its active form, pyridoxal 5′-phosphate (PLP), and its role as a coenzyme in neurotransmitter synthesis. We examined the genetic and metabolic disorders linked to vitamin B6 deficiency, such as mutations in pyridox(am)ine 5’-phosphate oxidase (PNPO), Aldehyde Dehydrogenase 7 Family Member A1 (ALDH7A1), alkaline locus phosphatase (ALPL), and cystathionine β-synthase (CBS), and discussed the clinical rationale for empirical administration in acute neonatal seizure settings. Results: Vitamin B6 is essential for the synthesis of gamma-aminobutyric acid (GABA), dopamine, and serotonin, with PLP-dependent enzymes such as glutamic acid decarboxylase and aromatic L-amino acid decarboxylase playing central roles. Deficiencies in PLP due to genetic mutations or metabolic disruptions can result in treatment-resistant neonatal seizures. Early supplementation, especially in suspected vitamin B6-dependent epilepsies, may provide both diagnostic clarity and seizure control, potentially reducing exposure to conventional antiseizure medications. Conclusions: Vitamin B6-responsive epilepsies highlight the clinical value of mechanism-based, individualized treatment approaches in neonatology. Incorporating genetic and metabolic screening into seizure management may improve outcomes and aligns with the principles of precision medicine. Full article

Background: The anatomical variability of the nasal cavity affects intranasal drug delivery, especially to the olfactory region for nose-to-brain treatments. While previous studies used average models or 2D measurements to account for inter-individual variability, 3D shape variation of the region crossed by drug particles that target the olfactory area, namely the region of interest (ROI), remains unexplored to our knowledge. Methods: A geometric morphometric analysis was performed on the ROI of 151 unilateral nasal cavities from the CT scans of 78 patients. Ten fixed landmarks and 200 sliding semi-landmarks were digitized, using Viewbox 4.0, and standardized via Generalized Procrustes Analysis. Shape variability was analyzed through Principal Component Analysis. Morphological clusters were identified using Hierarchical Clustering on Principal Components, and characterized with MANOVA, ANOVA, and Tukey tests. Results: Validation tests confirmed the method’s reliability. Three morphological clusters were identified. Variations were significant in the X and Y axes, and minimal in Z. Cluster 1 had a broader anterior cavity with shallower turbinate onset, likely improving olfactory accessibility. Cluster 3 was narrower with deeper turbinates, potentially limiting olfactory accessibility. Cluster 2 was intermediate. Notably, 31.5% of patients had at least one cavity in cluster 1. Conclusion: Three distinct morphotypes of the region of the nasal cavity that potentially influence accessibility were identified. These findings will guide future computational fluid dynamics studies for optimizing nasal drug targeting and represent a practical step toward tailoring nose-to-brain drug delivery strategies in alignment with the principles of personalized medicine. Full article

Decision Support Systems (DSSs) are increasingly shaping high-performance sport by translating complex time series data into actionable insights for coaches and practitioners. This paper outlines a structured, five-stage DSS development pipeline, grounded in the Schelling and Robertson framework, and demonstrates its application in professional basketball. Using changepoint analysis, we present a novel approach to dynamically quantify Most Demanding Scenarios (MDSs) using high-resolution optical tracking data in this context. Unlike fixed-window methods, this approach adapts scenario duration to real performance, improving the ecological validity and practical interpretation of MDS metrics for athlete profiling, benchmarking, and training prescription. The system is realized as an interactive web dashboard, providing intuitive visualizations and individualized feedback by integrating validated workload metrics with contextual game information. Practitioners can rapidly distinguish normative from outlier performance periods, guiding recovery and conditioning strategies, and more accurately replicating game demands in training. While illustrated in basketball, the pipeline and principles are broadly transferable, offering a replicable blueprint for integrating context-aware analytics and enhancing data-driven decision-making in elite sport. Full article

English writing proficiency is pivotal to sustainable academic success and employability. In Chinese higher education, however, conventional instruction often constrains students’ self-regulation and access to individualized feedback. Drawing on self-regulated learning (SRL) and co-regulated learning (CoRL), this study investigates whether a CoRL-guided generative AI virtual teacher (CoRL-VT), designed as a “more capable other,” is associated with enhanced undergraduate writing outcomes relative to standard AI support. Using a 12-week quasi-experimental design with two intact classes (N = 61) in Anhui, China, we compared a control condition (standard AI) with an intervention (CoRL-VT). Writing proficiency was assessed via IELTS Writing Task 2 at pre- and post-test; three certified examiners scored all scripts with strong agreement (ICC = 0.87). Analyses adjusting for baseline yielded an estimated group difference favoring CoRL-VT. Teacher interview testimony aligned with the quantitative pattern, noting clearer macro-organization, richer lexical choices, and more teacherly formative feedback among CoRL-VT students. Taken together, these findings offer exploratory, descriptive evidence consistent with the potential of structured, CoRL-informed AI scaffolding in sustainable writing pedagogy and outline design principles for replicable CoRL-VT implementations in resource-conscious contexts. Full article

Background: Conventional rehabilitation after anterior cruciate ligament reconstruction often follows a rigid, phase-based model. This structure may overlook individual differences in healing, neuromuscular control, and psychological readiness, leading to low return-to-sport rates and a high risk of reinjury. Methods: This narrative review proposes a flexible rehabilitation framework based on overlapping progression blocks. Inspired by principles of strength and conditioning, motor learning, and cognitive training, this model emphasizes continuous, individualized development instead of fixed timelines. Results: The proposed model integrates essential components—such as joint mobility, muscle activation, motor control, and psychological factors—throughout the entire recovery process. Functional testing is redefined as a dynamic and ongoing diagnostic tool that helps clinicians identify areas needing further development, rather than acting as a simple pass/fail gateway. Progression is guided by demonstrated readiness rather than time or phase completion. Conclusions: Rehabilitation using adaptive, overlapping progression blocks offers a more holistic and responsive approach. It allows for better personalization, supports safer decision-making, and improves the transition back to sport through sustained development of physical and cognitive capacities. Full article

Knowledge translation (KT) is an essential process in bridging the gap between research evidence and healthcare practice, particularly in community health and primary care settings. In Saudi Arabia, KT is gaining increasing importance as the healthcare system undergoes a major transformation under Saudi Vision 2030 and the new Saudi Model of Care. The new model of care emphasizes the importance of healthy communities and primary care as early elements of healthcare service delivery before reaching the secondary and tertiary healthcare levels. Additionally, healthcare transformation under Saudi Vision 2030 encourages the utilization of evidence and KT to improve healthcare services provided to individuals and enhance the standardization of healthcare delivery. Nonetheless, the application of KT principles in community health and primary care contexts has faced some challenges during the period preceding the establishment of the new Saudi Model of Care. While Saudi Arabia has achieved significant advances in health research and institutional capacity building, KT remains underutilized in local community health initiatives. This narrative review aims to provide a conceptual overview of KT and explore its implications within the contexts of community health and primary care in Saudi Arabia. Additionally, the review introduces the key components of KT—evidence synthesis, dissemination, exchange, and application—and examines how these can be implemented in community and primary care contexts. The review emphasizes the necessity of stakeholder engagement, community-based participatory research, and the integration of frameworks such as the knowledge to action and social–ecological models to ensure effective KT in community health settings. Future directions should focus on expanding KT training, promoting its integration across health institutions involved in primary care delivery, and sustaining community health through strong partnerships among academic, governmental, and community stakeholders. Full article

This study aims to investigate the syntactic complexity in individuals with Alzheimer’s disease (AD) by conducting a comprehensive analysis that incorporates mean dependency distance (MDD), fine-grained grammatical metrics, and dependency network structures. A total of 150 adults with AD and 150 healthy controls (HC) responded in English to interview prompts based on the Cookie Theft picture description task, and the results were compared. The key findings are as follows: (1) The primary syntactic change is a strategic shift from hierarchical, clause-based constructions to linear, phrase-based ones, a direct consequence of working memory deficits designed to minimize cognitive load. (2) This shift is executed via a resource reallocation, where costly, long-distance clausal dependencies are systematically avoided in favor of a compensatory reliance on local dependencies, such as intra-phrasal modification and simple predicate structures. (3) This strategic reallocation leads to a systemic reorganization of the syntactic network, transforming it from a flexible, distributed system into a rigid, centralized one that becomes critically dependent on the over-leveraged structural role of function words to maintain basic connectivity. (4) The overall syntactic profile is the result of a functional balance governed by the principle of cognitive economy, where expressive richness and grammatical depth are sacrificed to preserve core communicative functions. These findings suggest that the syntactic signature of AD is not a random degradation of linguistic competence but a profound and systematic grammatical adaptation, where the entire linguistic system restructures itself to function under the severe constraints of diminished cognitive resources. Full article

People Who Use Substances (PWUS) are among the most stigmatised groups in society. Stigma associated with substance use is known to be detrimental to the individual’s wellbeing, and substance use is often used as a mechanism by policy makers and services to legitimise exclusion. PWUS often do not benefit from the drug and alcohol services that are available to them. Community Asset Mapping (CAM) is a strengths-based approach involving the re-engagement of communities through active involvement in research. There are criticisms and concerns about equity and the burden on participants involved in CAM projects; however, the broad aim of CAM is to identify and document the strengths and pre-existing resources that exist within a community. In the following study, we utilised CAM processes and principles in a large city in the Northeast of England to enable people with lived experience of substance use and practitioners working in drug treatment services to come together and identify resources in the form of services and groups that support recovery. In the process, we were concerned with identifying, engaging with, and involving groups that were known to the recovery community but also were not part of an existing recovery network. Qualitative data were obtained from semi-structured interviews (n = 13) and focus groups (n = 2). A reflexive thematic analysis approach was used to analyse the transcriptions, and from this we generated four themes: (1) community visibility, (2) ownership of the recovery agenda, (3) the impact of stigma and shame, and (4) the benefits of involvement. Our findings revealed a partly fragmented but also well-established, connectedand resourced local recovery community in the city. We were also able to identify a number of recovery groups and services that had previously not been known to the existing recovery community. Additionally, we identified that public and societal substance-related stigma continued to be a barrier that inhibited individuals and recovery groups from making themselves more visible and available to others. Full article

Artificial intelligence (AI) is transforming the diagnosis, treatment, and management of speech-language disorders through advances in speech recognition, natural language processing, automated assessments, and personalized intervention. These tools have the potential to enhance clinical decision-making, improve diagnostic accuracy, and increase access to services for individuals with speech and language disorders, particularly in underserved populations. Despite this progress, adoption is challenged by data bias, lack of transparency, and limited integration into clinical workflows. To realize the potential of AI in communication sciences, both technical development and ethical safeguards are required. This paper outlines core applications, emerging opportunities, and major challenges in applying AI to speech-language pathology and proposes ethical principles for its responsible use. Full article

Background: Healthcare systems globally face complex challenges including rising costs, increasing chronic disease burden, and fragmentation of care. Systems-based models represent promising approaches to healthcare transformation, yet their implementation remains incompletely understood. Objective: To critically analyze the Saudi model of Care (MoC) as a case study of systems-based healthcare transformation, examining its conceptual framework, implementation strategies, and projected health outcomes. Methods: We conducted a narrative review synthesizing publicly available official documents on the Saudi MoC, primarily the 2017 overview and 2025 revision, identified through targeted searches of Ministry of Health websites and grey literature portals (no date restrictions); formal quality appraisal was not applied as sources were official policy documents, with bias mitigated through cross-verification and critical analysis. Results: The Saudi MoC exemplifies systems-based transformation through its multi-layered framework organized around six patient-centered systems of care spanning the lifecycle. Key innovations include: (1) an architectural approach integrating activated individuals, healthy communities, virtual care, and traditional clinical settings; (2) a comprehensive intervention taxonomy with 42 specific initiatives; (3) explicit contextual adaptations for diverse settings; and (4) a phased implementation approach with detailed performance metrics. National indicators improved during the reform period, including life expectancy and maternal and child health. These are national trends observed during the period of health reforms. Causal attribution to the Model of Care requires a counterfactual evaluation. Conclusions: This analysis of the Saudi MoC contributes to the literature on systems-based healthcare transformation by illuminating how theoretical principles can be operationalized at national scale. The model’s patient-centered design, comprehensive intervention taxonomy, and attention to implementation factors offer valuable insights for other healthcare systems pursuing transformation. Further research should examine actual implementation outcomes as the model matures. Full article