Search Results (1,885)

Background: In the context of global population aging, nutritional risk has emerged as an important factor associated with both physical and mental health among older adults. This study aimed to examine the associations between nutritional risk, depression, and cognitive function in older adults and to explore potential variations across residential area, educational attainment, employment status, frailty status, and activities of daily living (ADL). Methods: Data were obtained from 9955 community-dwelling older adults aged 65 years and older who participated in the 2023 National Survey of Older Koreans. Nutritional risk was assessed using the DETERMINE checklist (21-point scale), a multidimensional screening tool reflecting dietary, functional, and social risk factors. Depression was measured using the Short-form Geriatric Depression Scale (15-point scale), and cognitive function was assessed using the Korean version of the Mini-Mental State Examination-2 (K-MMSE-2; 30-point scale). Hierarchical multiple linear regression, correlation, subgroup, and sensitivity analyses were conducted, adjusting for sociodemographic characteristics, health behaviors, and geriatric factors. Results: Correlation analyses showed significant associations between nutritional risk and cognitive function (r = −0.191, p < 0.05), nutritional risk and depression (r = 0.440, p < 0.05), and depression and cognitive function (r = −0.259, p < 0.05). Higher nutritional risk scores were significantly associated with greater depressive symptoms (B = 0.314, p < 0.001) and lower cognitive function (B = −0.051, p < 0.05). While some subgroup differences were observed, not all interaction effects reached statistical significance, and these findings should be interpreted with caution. Conclusions: These findings suggest that nutritional risk is associated with depressive symptoms and cognitive function in older adults. Given that the DETERMINE checklist reflects multidimensional vulnerability, the results should be interpreted as indicating broader risk contexts rather than direct nutritional status alone. These findings highlight the importance of integrated, multidimensional approaches to support older adults at nutritional risk in community settings. Full article

Online asynchronous learning offers considerable flexibility but frequently faces challenges in sustaining engagement, interactivity, and inclusivity across diverse learner populations. This study introduces the OPTIMAL framework—an Online, Pedagogy- and Technology-Integrated, Microcurricula Approach for interactive and inclusive Learning—synthesising universal design for learning, active learning, and constructive alignment with technology integration frameworks (TPACK and PICRAT), operationalised through a microcurricula-as-a-service architecture. A three-year longitudinal case study (2022/23 to 2024/25) examined the application of the framework to a data literacy and analytics module serving over 5000 students across more than 15 programs and five faculties at Dublin City University. The module design constructively aligned learning outcomes, content, and technology at three levels to support multiple learning pathways, formative assessment, and transdisciplinary engagement, deliberately fostering transformative uses of technology in a fully asynchronous environment. Mixed-methods evaluation—combining learning analytics, surveys (n = 1743), and qualitative feedback—demonstrated sustained positive outcomes across all three years, including 95–99% completion rates, consistently high satisfaction, and longitudinal gains in engagement and pass rates. These findings demonstrate how the deliberate integration of pedagogical theory, technological frameworks, and modular curriculum architecture can deliver scalable, inclusive, and high-engagement online education, offering both a transferable, evidence-based model for educators and curriculum designers and longitudinal empirical validation for researchers. Full article

Background/Objectives: Japan, the world’s first super-aged society, has confronted rapid population aging and increasing healthcare demands earlier than any other country. In this context, dysphagia rehabilitation has become a critical issue affecting quality of life and survival. With nearly 30% of the population aged ≥65 years, Japan has developed a distinctive dysphagia rehabilitation model characterized by interprofessional collaboration and dental involvement. This narrative review describes its historical evolution and structural characteristics. Methods: This narrative review employed a structured literature search of PubMed and Ichushi-Web, supplemented by manual searches of policy documents and professional guidelines. Publications from 1980 to January 2026 were included if they addressed dysphagia rehabilitation systems or dental involvement in Japan. Both English- and Japanese-language sources were analyzed using thematic synthesis. Results: Japan’s dysphagia rehabilitation model evolved alongside population aging and is embedded within the universal health insurance and long-term care insurance systems. A prominent characteristic is the sustained involvement of dental professionals, who contributed to the foundational development of the field and remain actively involved across care settings, particularly within community- and home-based care. The system is further supported by certification frameworks, a triadic model integrating rehabilitation, nutrition, and oral health, and institutionalized interprofessional education. Conclusions: Previous studies have examined specific aspects of dysphagia care in Japan, but few have examined the overall structure of the system. This review maps the fundamental structure of Japan’s dysphagia rehabilitation model within its historical and policy context, offering insights relevant to dysphagia care in other aging societies. Full article

Artificial Intelligence (AI) is increasingly used in recruitment, performance management, and algorithmic work management, with potentially divergent implications for worker inclusion, exclusion, and discrimination. This systematic review synthesizes peer-reviewed evidence on (i) which AI applications in labor-market settings are linked to inclusion/exclusion outcomes, (ii) the mechanisms and contextual moderators shaping these effects, and (iii) governance and human-resource management responses proposed in the literature. Guided by PRISMA 2020, we searched Scopus and Web of Science (Title/Abstract/Keywords) for English-language journal articles published between 2015 and 2025. Nineteen studies met the eligibility criteria and were analyzed using qualitative thematic synthesis. The evidence indicates an ambivalent pattern: AI can support inclusion through assistive technologies and improved matching, but it can also exacerbate occupational polarization, digital exclusion, and discriminatory outcomes when models are trained on biased data or deployed without transparency and accountability. Outcomes depend on complementary organizational practices, workers’ access to skills, and the regulatory environment. Based on an evidence map of the included studies, we propose a hybrid governance model combining technical and organizational audits, inclusive upskilling/reskilling, participatory regulation, and responsible HR policies to align AI innovation with decent and inclusive work. Given the focused Title/Abstract/Keywords query and the small, heterogeneous corpus, the findings are interpreted as a scoped evidence map rather than an exhaustive census of all AI-and-work research. The model’s contribution lies in integrating four interdependent governance layers—technical, organizational, workforce, and regulatory—within a single labor-market framework. Accordingly, the review should be read as a focused qualitative evidence synthesis, and the proposed model as an evidence-informed conceptual framework that warrants future empirical validation. Full article

Children are largely absent from circular economy and bioeconomy research, limiting opportunities for early development of systems thinking, sustainability competencies, and inclusive knowledge production. This paper presents a qualitative case study of the Horizon 2020 AgroCycle project (2016–2019), examining how primary school children were engaged as co-researchers through a transdisciplinary, participatory model. Analysis draws on project deliverables, educational resources, workshop records, internal reports, and dissemination materials. The study shows how children and adult co-researchers explored waste valorisation, bioresource transformation, and biobased material innovation in Irish schools. Valorisation in the context of the bioeconomy is the process of converting residues from farming, food, forestry and marine sources into high-value products such as biofertilisers, biofuels and biochemicals. It situates AgroCycle within European sustainability policy, highlighting its influence on subsequent initiatives, including Horizon Europe BioBeo and BiOrbic, Research Ireland’s Centre for Bioeconomy. By combining qualitative case study methodology with reflective practitioner analysis, the paper demonstrates how child-centred, transdisciplinary research can enhance sustainability education, support SDG-aligned competencies, and promote inclusive approaches to circular economy and bioeconomy transitions. Full article

Background and Objectives: Angiogenesis plays an important role in many types of cancers, including melanoma. Mast cells are among the most important cellular partners involved in the angiogenic process. The purpose of the present study is to establish the interrelations between microvessels and mast cell density, and to describe the prognostic role of mast cells in malignant melanoma. Materials and Methods: A total of 92 cases of melanoma were evaluated. Hematoxylin–eosin staining and CD34/mast cell tryptase double immunostaining were performed. Results: Of the cases, 28 were classified as T1 (30.43%), 31 as T2 (33.69%), 21 as T3 (22.82%), and 12 as T4 (13.04%). Mast cells were mainly located in the infiltrate area in cases with inflammatory infiltrate. Few mast cells were observed in the absence of infiltrate. A granular type was observed in intratumoral areas with an isolated and perivascular distribution of mast cells. A significant correlation was found between intratumoral MVD and intratumoral MCD (mast cell density) in T1 and T4 melanoma cases (p = 0.0001 and p = 0.0029, respectively). In T2 cases, significant correlations were found between intratumoral and peritumoral MVD and G (p = 0.0169, p = 0.0003), between intratumoral MCD and MVD (p = 0.0041), and between peritumoral MVD and the number of peritumoral mast cells (p = 0.0011). T3 cases showed a significant correlation between the density of intratumoral mast cells and peritumoral ones (p = 0.001); between the MVD and mast cell density of the intratumoral area (p = 0.0001); between the intratumoral MVD and peritumoral mast cell density (p = 0.0001); between the MVD and mast cell density of the peritumoral area (p = 0.0325); and between the peritumoral MVD and intratumoral mast cell density (p = 0.0458). Conclusions: Both intratumoral and peritumoral mast cells were found to participate in melanoma progression, and they showed greater involvement in the early phases of angiogenesis in malignant melanoma. Full article

9-Mesitylacridinium salts are widely recognized as efficient organic photoredox catalysts owing to their strong excited-state oxidizing power and stability under visible-light irradiation. In this study, a new mesityl acridinium derivative bearing a di-tert-butylphenyl substituent on the nitrogen atom was synthesized. The introduction of tert-butyl groups on the N-aryl moiety was primarily aimed at improving solubility and chemical stability of the acridinium salt. Starting from a 9(10H)-acridinone precursor, the target compound was obtained in high overall yield through a concise synthetic sequence. The synthesis consists of a copper-catalyzed C–N coupling reaction to install the aryl substituent on the nitrogen atom, followed by a Grignard reaction and subsequent acid treatment to afford the corresponding acridinium salt. All transformations proceeded smoothly, providing efficient access to the desired novel acridinium derivative. This work presents a practical example of the structural modification of mesitylacridinium derivatives directed toward enhanced solubility and stability, and provides a useful synthetic platform for the preparation of structurally diverse acridinium salts. Full article

Regular social, economic and agricultural interactions occurred between the Horn of Africa and Southern Arabian Peninsula for millennia, raising questions about potential geo-culinary exchanges, including of the little-studied fermented flatbreads produced in these areas. A comparative analysis of Somali laxoox/canjeero, Ethiopian injera, Sudanese kisra and Yemeni/Saudi lahoh was conducted by combining a literature review and consultations with 17 local experts, then processing the data in a hierarchical cluster analysis to quantify “biocultural” diversity. In an interdisciplinary approach, technical aspects (bread appearance, ingredients, and production stages) and cultural characteristics (consumption patterns and social function) were considered to identify key descriptors of the breads. A dendrogram generated through cluster analysis of a binary (0/1) matrix, structured with the key descriptors, showed that each bread has a distinct biocultural identity, and enabled the quantification of their similarities. Somali laxoox/canjeero and Yemeni/Saudi lahoh had a 64% similarity to each other (Jaccard index); each had a 53% similarity to Ethiopian injera; while all of them were 41% similar to Sudanese kisra. Hierarchical cluster analysis, applied for the first time to flatbreads, contributes to their comprehensive characterization and comparison in this unique geographic region and lays the foundations for policies to protect their identity and quality. Full article

Food waste presents a major challenge to global sustainability. Up to 60% of this waste occurs at the household level, at which point labeling confusion causes avoidable loss. The present study employed the motivation–opportunity–ability framework to conduct a narrative synthesis of 82 studies and pieces of gray literature, incorporating policies and industry practices to elucidate how food labeling modulates food waste behavior through interactions with consumer motivation, external opportunities, and individual abilities. Food labeling should be considered a systemic intervention tool spanning the entire food supply chain rather than mere carriers of information. The present findings indicate that although standardizing quality and safety label terminology mitigates cognitive confusion, it may have limited efficacy to reduce food waste. Extending shelf life and providing explicit storage guidance are critical strategies that are often undervalued and comparatively underexplored. Labels most effectively reduce waste when they simultaneously activate motivation, opportunity, and ability. When all three elements cannot be activated concurrently, stakeholders should prioritize improving external opportunities or enhancing individual abilities rather than stimulating motivation. Food labeling interventions can only be effective at waste mitigation if systemic and transdisciplinary synergy is achieved among all stakeholders in food supply chains. Full article

Leaders and managers frequently face the need to make highly complex decisions with incomplete or fragmented information. Traditional decision support systems largely emphasize the visualization of data but often fall short in producing context-sensitive insights that can directly inform decision-making. This paper examines how narrative techniques combined with machine learning can strengthen communication across organizational hierarchies, particularly by improving the transfer of tacit expertise and contextual knowledge. To explore this, a transdisciplinary literature review was conducted using articles published within the last five years from databases such as Scopus, Web of Science, and ScienceDirect. The review highlights that narrative-driven reporting has been most commonly applied in fields such as accounting and sustainability, where expert interpretation replaces purely numerical summaries with more meaningful analytical explanations. Such approaches can also embed sentiment and personalization, commonly referred to as Narrative Disclosure Tone. Building on this foundation, the study investigates how Artificial Intelligence-driven decision support can formally integrate narrative elements to enhance report clarity, usability, and strategic relevance. Findings suggest that combining machine learning with expert-driven narrative reporting supports more innovative decision support systems and facilitates the alignment of tacit knowledge with data-driven insights. Full article

(1) Background: The increasing contribution of anthropogenic electromagnetic radiation has altered the Earth’s electromagnetic landscape and poses a serious problem for electromagnetic ecology and medicine. The aim of this study was to develop a working theoretical framework to describe the current state of interaction between the human body and electromagnetic fields in the external environment and to facilitate transdisciplinary collaboration among scientists in studying and addressing this problem. (2) Methods: Extensive research has been conducted in the literature to provide a comprehensive presentation of data, enabling a working concept of the interaction between the human body and electromagnetic fields in the external environment. (3) Results: General data, theoretical foundations, mechanisms, and results of the interaction of external electromagnetic fields with the human body were presented. (4) Conclusions: There is a proven interaction between the human body and external electromagnetic fields, as the body is part of the Earth’s electromagnetic landscape and has biophysical mechanisms for coupling with it. The increase in anthropogenic electromagnetic radiation is an electromagnetic environmental problem, and this requires further study of the safety issues and the impact of anthropogenic electromagnetic fields on the human body, and a reassessment of their biological impact on the human body, tightening the standards and requirements for electromagnetic safety in places where people live, a moratorium on further deployment of 5G, urgent application of the precautionary principle, and stricter exposure limits, especially for Wireless Communication Electromagnetic Fields. Full article

Background: This study compared two xenogeneic bone graft materials, A-Oss (bovine-derived) and The Graft (porcine-derived), using a rabbit calvarial defect model and a canine mandibular dehiscence-type defect model. Methods: Healing was evaluated at 6 and 12 weeks in rabbits and at 24 weeks in mongrel dogs. Micro-computed tomography quantified mineralized tissue fill (defect closure) in rabbits and, in dogs, the compartments classified as new bone and residual graft, together with vertical and horizontal volumetric maintenance. Hematoxylin and eosin (H&E) sections provided complementary qualitative observations. Results: In rabbits, defect closure did not differ between materials at 6 weeks (67.1 ± 12.7% vs. 70.2 ± 15.1%, p = 0.090) or 12 weeks (78.6 ± 5.9% vs. 72.3 ± 0.9%, p = 0.124). In dogs, new bone was similar between groups (43.5 ± 3.2% vs. 45.9 ± 1.1%, p = 0.208), whereas residual graft showed a numerical trend toward higher values with A-Oss (20.2 ± 3.5% vs. 13.3 ± 4.5%, p = 0.069). Vertical volume maintenance also trended higher with A-Oss (91.1 ± 1.6% vs. 87.8 ± 1.3%, p = 0.056), while horizontal maintenance was comparable (94.5 ± 1.8% vs. 91.4 ± 2.8%, p = 0.241). Histology in both models showed graft particles within the defect/augmented regions with surrounding eosinophilic matrix and intervening tissue spaces. Conclusions: Overall, both materials produced similar healing profiles across models, with small between-material differences most apparent in the canine dehiscence setting. Full article

Contemporary societies are facing converging crises, including environmental degradation, worsening social inequalities, aging populations, and increasingly costly healthcare systems, prompting sustainable health to be proposed as an integrative conceptual perspective for rethinking health, its determinants, and collective action. This narrative review aims to trace the historical evolution of the concept, clarify the vision it offers for public health, and identify its implications for research, policy, and intervention. A literature search (May 2025) was conducted in PubMed, Google Scholar, and Google, with no restrictions on language, time period, or document type. Of 40 relevant documents, 21 were selected for in-depth analysis by two independent reviewers, with duplicate data extraction. The results show that sustainable health broadens the World Health Organisation (WHO) definition of health by incorporating sustainability, intergenerational justice, ecological limits, and social equity. Close to, but distinct from Planetary Health, One Health, and EcoHealth, sustainable health is based on ecological, social and ethical, economic, behavioral, intergenerational, and systemic/intersectoral dimensions. Sustainable health thus emerges as a systemic and transdisciplinary conceptual approach for transforming health systems, living environments, and public policy, requiring further conceptual clarification, robust interdisciplinary research programs, and intersectoral initiatives involving communities. Full article

The world evolves continuously across space and time. Massive volumes of data are generated through sensing, simulation, remote observation, and human activities, capturing dynamic processes in environmental, social, economic, and engineered systems. Critical insights are embedded within these large-scale spatiotemporal datasets. Spatiotemporal Data Science provides a conceptual and methodological framework for analyzing such data by integrating spatiotemporal thinking, computational infrastructure, artificial intelligence, and domain knowledge. The field advances methods for data acquisition, harmonization, modeling, visualization, and decision support, enabling applications in natural disaster response, public health, climate adaptation, infrastructure resilience, and geopolitical analysis. By leveraging emerging technologies—including generative Artificial Intelligence (AI), large-scale cloud platforms, Graphics Processing Unit (GPU) acceleration, and digital twin systems—Spatiotemporal Data Science enables scalable, interoperable, and solution-oriented research and innovation. It represents a critical frontier for scientific discovery, engineering advancement, technological innovation, education, and societal benefit. Spatiotemporal Data Science is a transdisciplinary field that studies and models dynamic phenomena across space and time by integrating spatial theory, temporal reasoning, artificial intelligence, and scalable computational infrastructure. It enables the development of adaptive, predictive, and increasingly autonomous systems for understanding and managing complex real-world processes. Full article

Biological manipulation via physical stimuli such as light and magnetism has become a central goal in modern biotechnology. Among these modalities, magnetic fields offer unique advantages, including deep tissue penetration and untethered interventions in living systems. An ideal platform for such a magnetogenetic toolkit would be a genetically encodable protein with tunable magnetic features under physiological conditions. However, the development of such tools has been hindered by the lack of robust and stable protein scaffolds with strong intrinsic magnetic properties. Inspired by animal magnetoreception in nature, here, we rationally designed and systematically screened single-chain variants of the magnetoreceptor MagR. Through nine iterative rounds of design and experimental validation, we generated 25 constructs and ultimately identified a stable single-chain-dimer-based-tetramer, SDT-MagR, as the optimal magnetic molecular platform. This engineered protein exhibits exceptional structural stability and state-dependent magnetic behavior, showing ferrimagnetic-like characteristics in the solid state and paramagnetic behavior in solution. With enhanced magnetic susceptibility, purified SDT-MagR can be directly attracted by a magnet in vitro, establishing it as a promising new platform for future biomagnetic manipulation and magnetogenetics applications. Full article