Search Results (10,676)

Background/Objectives: Social media’s impact on adult well-being varies by engagement patterns, highlighting the need for evidence to inform digital well-being strategies. This study examines the association between social media use and self-esteem, a key psychological indicator linked to adult well-being, with the aim of identifying modifiable behavioral targets relevant to clinical, workplace, and public health contexts. Methods: A cross-sectional survey of 81 Greek adults assessed daily social media use, engagement patterns, and self-esteem using the Rosenberg Self-Esteem Scale. Analyses included linear and exploratory quadratic regression models, multiple regression with demographic covariates (age, gender), and descriptive group comparisons. Results: A small but statistically significant negative association was observed between daily social media use and self-esteem (R² = 0.078), indicating limited explanatory power. Exploratory analyses did not provide strong evidence of non-linear effects. Demographic factors and usage categories were not significant predictors, likely reflecting limited statistical power. Participant self-reports highlighted potentially disruptive patterns such as intensive use at specific times/conditions, perceived sleep impact, and cognitive preoccupation with social media, as well as motivation to reduce or stop use. Conclusions: Time spent online is a weak predictor of self-esteem, underscoring the importance of engagement quality over frequency. From a management perspective, the findings support shifting attention from generic screen-time reduction to targeting specific potentially high-risk patterns of engagement in future policy and practice. This exploratory pilot study provides initial, hypothesis-generating evidence within a Greek adult sample and highlights the need for larger, population-based studies to confirm and extend these findings. Full article

Fruit size and pungency are key yield and quality traits in chili. This study combines high-throughput genotyping with bulk segregant analysis (BSA) to identify candidate SNPs and quantitative trait loci (QTLs) by analyzing extreme phenotypes from a Ghotki × Chakwal-4 F2 population. The traits were fruit length, diameter, length-to-diameter ratio, and weight, along with capsaicin content. Significant correlations were observed among length, diameter, and length-to-diameter ratio. A total of 534 single nucleotide polymorphisms (SNP) markers were used to develop genetic maps from 4315 to 6607 cM long. The SNP frequency data was pooled for the 25% of individuals showing extreme values for each measured trait, and bulk segregant analysis (BSA) was performed. BSA identified high-scoring SNPs associated with pungency (SNP 1_41308232; SNP 12_104377148), fruit length (SNP 1_92509300; SNP 6_218780813), and fruit weight (SNP 6_100989762 and SNP 6_138660974). Genetic mapping identified twelve pungency QTLs, three for fruit length, two for fruit diameter, two for the length-to-diameter ratio, and thirteen for fruit weight. Overlapping QTL regions on chromosome 6 influence fruit length, fruit width, and capsaicin content, indicating potential pleiotropy and offering promising targets for multi-trait selection in chili breeding. The study identifies key SNPs and QTLs that simultaneously influence chili fruit size and pungency, providing valuable targets for multi-trait breeding. Full article

Background/Objectives: Otoscopic examination is essential for the evaluation of ear diseases; however, conventional diagnostic devices have limitations related to portability, cost, and patient comfort. This study aimed to evaluate the feasibility and diagnostic performance of a newly developed pen-shaped otoscope compared with conventional otologic examination equipment. Methods: In this prospective study, 19 patients (28 ears) who underwent otologic examination at a tertiary referral center between April and June 2024 were included. Images of the external auditory canal and tympanic membrane were obtained using a pen-shaped otoscope, a video endoscope, and a microscope. Visualization of key tympanic membrane structures was assessed by physicians, and patients completed questionnaires evaluating pain, fear, image quality, and understanding of their disease. This prospective pilot feasibility study assessed the safety, usability, and preliminary diagnostic performance of the device. Results: Visualization rates of tympanic membrane structures using the pen-shaped otoscope, video endoscope, and microscope, respectively, were as follows: annulus tympanicus (57.1% vs. 89.3% vs. 9.1%), pars flaccida (89.3% vs. 96.4% vs. 45.5%), handle of the malleus (96.4% vs. 100% vs. 81.8%), and tympanic membrane vasculature (89.3% vs. 100% vs. 100%). No patients reported pain with the pen-shaped otoscope, whereas one patient reported pain with the video endoscope. Despite slightly lower image quality and disease understanding scores, several patients preferred the pen-shaped otoscope because of its ease of use and lack of discomfort. Conclusions: The pen-shaped otoscope provided clear visualization of key tympanic membrane structures, albeit with slightly lower image quality than the endoscope, while demonstrating high safety, portability, and ease of use. Its markedly lower cost supports its potential utility in smaller hospitals, outpatient clinics, and telemedicine applications. Further validation in larger cohorts and pediatric populations is warranted. Full article

Background/Objectives: Adequate hydration is essential for health; however, water consumption behaviors are influenced not only by physiological needs but also by hydration knowledge and perceptions of drinking water quality. Empirical evidence examining these factors in Eastern European populations remains limited. This study aimed to assess hydration knowledge, water consumption patterns, and attitudes toward drinking water quality among adults in Romania, and to examine their associations with daily water intake and water source preferences. Methods: A cross-sectional study was conducted between November 2024 and November 2025 among adults residing in Romania. Data were collected from 165 participants using an anonymous, self-developed, paper-based questionnaire administered in person to adult patients attending routine visits in four primary care clinics in Arad, Romania, using a convenience sampling approach. The questionnaire assessed sociodemographic characteristics, hydration knowledge, water consumption behaviors, and attitudes toward drinking water quality. Descriptive statistics, chi-square tests, correlation analyses, and multivariable linear and logistic regression models were applied to identify factors associated with daily water intake, adequate hydration (≥2 L/day), and bottled water consumption. Results: Hydration knowledge was moderate overall and was significantly associated with education level and gender. Higher hydration knowledge was positively correlated with daily water intake (r = 0.21, p = 0.006) and was independently associated with higher intake and adequate hydration (OR = 1.28, 95% CI: 1.10–1.49; p = 0.002). Greater trust in tap water was also positively associated with daily intake (r = 0.27, p = 0.001) and adequate hydration (OR = 1.31, 95% CI: 1.12–1.54; p < 0.001). Lower trust in tap water and stronger beliefs regarding bottled water were significant predictors of bottled water use as the primary drinking water source. Education level emerged as a consistent predictor across multiple hydration-related outcomes. Conclusions: Hydration knowledge and perceptions of drinking water quality are key, modifiable factors associated with water consumption behaviors. Educational strategies integrated into primary care and transparent communication regarding tap water safety may support adequate and sustainable hydration among adults. Full article

Urban populations are exposed to elevated local temperatures compared to surrounding rural areas due to the urban heat island (UHI) effect, which increases health risks and energy demand. The literature highlights that accurately quantifying UHIs at broader territorial scales remains challenging because of limited microscale climate data availability and, at the same time, the difficulty of increasing the spatial coverage of the outcomes. Within the PRIN2022-PNRR CRiStAll (Climate Resilient Strategies by Archetype-based Urban Energy Modeling) project, this work addresses these limitations by coupling Urban Building Energy Modeling with archetype-based representation of urban form and high-resolution climatic data. Urban archetypes are defined as representative microscale configurations derived from combinations of urban canyon geometries and building typologies, accounting for different climatic zones, use categories, and construction periods. The proposed methodology was applied to the city of Turin (Italy), where representative urban blocks were identified and modeled to evaluate key urban context metrics under short-, medium-, and long-term climate scenarios. The UHI effect was assessed using Urban Weather Generator, while energy simulations were performed with CitySim. The urban archetype approach enables both fine spatial resolution and extensive spatial coverage, supporting urban-scale mapping. Full article

Rice (Oryza sativa L.) readily accumulates cadmium (Cd), posing dietary exposure risks in populations dependent on rice-based diets. This study investigated how sulfur (S) redox processes regulate Cd mobility in S-deficient, Cd-contaminated paddy soil under waterlogged conditions. A pot experiment was conducted with two S treatments (−S and +S, 30 mg kg⁻¹) throughout the rice growing season. S addition markedly increased pore water S²⁻ concentrations during early growth (tillering) and mid-season (booting) and suppressed the diffusion of SO₄²⁻ from non-rhizosphere to rhizosphere at later stages (filling–maturity). Consequently, Cd in soil pore water was significantly lower in +S than −S treatments at all stages. Sulfur-amended soil showed a redistribution of Cd from labile fractions (exchangeable and carbonate-bound) to more stable fractions (Fe/Mn oxide-bound). Sulfur application also altered the rhizosphere microbiome: the relative abundance of sulfate-reducing bacteria (SRB) increased at the booting and filling stages, while sulfur-oxidizing bacteria (SOB) became more dominant at maturity. Additionally, +S enhanced Cd sequestration on rice root iron plaque by 32–67% during the grain-filling and maturity stages compared to −S. Throughout the rice growing period, redox-driven shifts in the S²⁻/SO₄²⁻ ratio emerged as a key control on Cd behavior, with low pe + pH (strongly reducing conditions) promoting Cd sulfide precipitation and high pe + pH (more oxidizing conditions) causing Cd remobilization. Full article

Background: The rapid advancement in artificial intelligence (AI) has fundamentally reshaped gut microbiome research by enabling high-resolution analysis of complex, high-dimensional microbial communities and their functional interactions with the human host. Objective: This narrative review aims to synthesize recent methodological advances in AI-driven gut microbiome research and to evaluate their translational relevance for therapeutic optimization, personalized nutrition, and precision medicine. Methods: A narrative literature review was conducted using PubMed, Google Scholar, Web of Science, and IEEE Xplore, focusing on peer-reviewed studies published between approximately 2015 and early 2025. Representative articles were selected based on relevance to AI methodologies applied to gut microbiome analysis, including machine learning, deep learning, transformer-based models, graph neural networks, generative AI, and multi-omics integration frameworks. Additional seminal studies were identified through manual screening of reference lists. Results: The reviewed literature demonstrates that AI enables robust identification of diagnostic microbial signatures, prediction of individual responses to microbiome-targeted therapies, and design of personalized nutritional and pharmacological interventions using in silico simulations and digital twin models. AI-driven multi-omics integration—encompassing metagenomics, metatranscriptomics, metabolomics, proteomics, and clinical data—has improved functional interpretation of host–microbiome interactions and enhanced predictive performance across diverse disease contexts. For example, AI-guided personalized nutrition models have achieved AUC exceeding 0.8 for predicting postprandial glycemic responses, while community-scale metabolic modeling frameworks have accurately forecast individualized short-chain fatty acid production. Conclusions: Despite substantial progress, key challenges remain, including data heterogeneity, limited model interpretability, population bias, and barriers to clinical deployment. Future research should prioritize standardized data pipelines, explainable and privacy-preserving AI frameworks, and broader population representation. Collectively, these advances position AI as a cornerstone technology for translating gut microbiome data into actionable insights for diagnostics, therapeutics, and precision nutrition. Full article

Inflammatory bowel disease (IBD) comprises mainly Crohn’s disease (CD) and Ulcerative Colitis (UC). The Western model suggests that environmental factors, immunological factors, the gut microbiome, and genetic disposition all contribute to the onset and sustained symptoms that define CD, although the pathogenesis of CD remains unresolved. Current studies propose that in individuals who are genetically susceptible, genetic factors linked to immune dysregulation, in combination with environmental exposure, can result in dysbiosis of the gut microbiome and intestinal barrier dysfunction, leading to immune dysregulation. In Malaysia, the incidence of IBD is rising with CD increasing disproportionally compared to UC, and the incidence of CD currently mirrors that of the United Kingdom in the 1930s, which now has one of the highest incidences worldwide. Given the suggested role of Mycobacterium avium subspecies paratuberculosis (MAP) in CD in Western countries, which is subject to some controversy, this review summarises for the first time the current evidence on genetic, environmental, and microbial factors that could contribute to the rise of Crohn’s disease in Malaysia and proposes preventive approaches. We note the increasing reliance of Malaysia on imported cattle and milk products from areas of high Johne’s Disease prevalence to meet increasing demand and changes in milk preferences in the Malaysian population, both key indicators for human-MAP exposure in the Western model. Therefore, should MAP be shown to be associated with CD in Malaysia, some preventative measures are suggested, such as screening imported and native beef and dairy cattle, dairy products and ultimately water, both recreational and potable. Full article

Background: Emergency radiology often demands rapid integration of clinical cues, biochemical markers, and imaging findings to support time-critical diagnostic reasoning. However, educational resources that explicitly structure this interdisciplinary integration particularly between radiology and laboratory medicine remain limited. Objective: Our objective was to develop an Integrated Radiology–Biochemistry Diagnostic Flow Framework as a simulation-based methodological proof-of-concept and to document its structure, logic pathways, and internal consistency across common emergency presentations. Methods: We designed an algorithmic framework combining (i) clinical triggers, (ii) targeted biochemical markers with predefined threshold and trajectory rules, (iii) imaging indication and modality selection (US/CTA/MRI/NCCT), and (iv) key radiologic patterns linked to escalation pathways. No patient data or human participants were included. Instead, forty fully synthetic emergency scenarios were generated to populate the framework and to examine logical completeness, branching coherence, and red-flag escalation routes. Results: The framework yielded scenario-specific diagnostic flowcharts that systematically connect biochemical escalation cues with imaging selection and expected imaging findings. The synthetic scenario library demonstrated consistent branching logic across conditions and enabled transparent visualization of imaging-centered decision pathways suitable for simulation-based teaching and structured case discussion. Conclusions: This study reports a reproducible methodological proof-of-concept framework and a synthetic emergency scenario library. Further learner-based studies are required to evaluate usability, perceived realism, and educational effectiveness in authentic training settings. Full article

Over the past decades, remarkable progress in multimodal therapy has significantly improved survival outcomes for children with cancer. Yet, considerable variability in treatment response and toxicity persists, often driven by underlying genetic differences that affect the pharmacokinetics and pharmacodynamics of anticancer drugs. Pharmacogenomics, the study of genetic determinants of drug response, offers a powerful approach to personalize pediatric cancer therapy by optimizing efficacy while minimizing adverse effects. This review synthesizes current evidence on key pharmacogenetic variants influencing the response to major classes of antineoplastic agents used in children, including thiopurines, methotrexate, anthracyclines, alkylating agents, vinca alkaloids, and platinum compounds. Established gene–drug associations such as TPMT, NUDT15, DPYD, SLC28A3, and RARG are discussed alongside emerging biomarkers identified through genome-wide and multi-omics studies. The review also examines the major challenges that impede clinical implementation, including infrastructural limitations, cost constraints, population-specific variability, and ethical considerations. Furthermore, it highlights how integrative multi-omics, systems pharmacology, and artificial intelligence may accelerate the translation of pharmacogenomic data into clinical decision-making. The integration of pharmacogenomic testing into pediatric oncology protocols has the potential to transform cancer care by improving drug safety, enhancing treatment precision, and paving the way toward ethically grounded, personalized therapy for children. Full article

Fetal hemoglobin (HbF) plays a central role in mitigating the pathophysiological effects of sickle cell disease (SCD). Understanding the genetic determinants influencing HbF expression is essential for identifying the factors contributing to its modulation. This review provides an updated synthesis of evidence on HbF modulation, focusing on β^s haplotypes and their molecular characterization through Sanger sequencing, polymorphisms consistently associated with HbF levels in genome-wide association studies (GWAS), and recent advances in gene editing targeting HbF expression. An integrative review (2016–2025) was conducted using PubMed/MEDLINE, Scopus, and Web of Science, encompassing original research, experimental studies, systematic reviews, and genomic analyses. Key regulatory loci such as BCL11A, HBS1L-MYB (HMIP), and the HBB cluster explain a significant proportion of HbF variability across populations. Furthermore, additional variants in KLF1, NFIX, BACH2, and ZBTB7A have emerged as potential modulators in specific cohorts. Regarding advances in γ-globin editing, “prime editing”, although still in the experimental phase, has recently emerged as an innovative approach capable of introducing multiple HPFH-like mutations within γ-globin promoters, expanding future therapeutic possibilities in SCD. This review also provides a comparative overview of prime editing and other gene-editing strategies for HbF modulation, such as CRISPR-Cas9 and Base editing. Collectively, this work outlines the current landscape of HbF modulation and provides an informative basis for future research aimed at advancing precision-oriented therapeutic strategies in sickle cell disease. Full article

Pediatric tuberculosis (TB) remains a critically underrecognized contributor to global childhood morbidity and mortality, with the highest burden concentrated in low-resource settings. Although children comprise a minority of overall TB cases, mortality is disproportionately high, particularly among those under five years of age, driven largely by delayed diagnosis, inadequate linkage to care, and limited access to effective treatment. The continued rise of pediatric multidrug-resistant TB (MDR-TB), especially in regions with low sociodemographic development, further highlights persistent gaps in current control strategies. This review synthesizes key aspects of pediatric TB pathogenesis and host immune responses that predispose young children to rapid disease progression and severe outcomes, including immune immaturity and paucibacillary infection. We summarize pulmonary and extrapulmonary disease manifestations and identify populations at heightened risk, including children with HIV, malnutrition, type 1 diabetes mellitus, and congenital or treatment-related immunosuppression. Ongoing challenges in diagnosis and treatment are discussed, including limitations of existing microbiologic and immunologic tests, specimen collection constraints, regimen toxicity, and barriers to adherence. Prevention remains central to reducing pediatric TB mortality. We highlight the sustained importance of bacille Calmette–Guérin (BCG) vaccination in preventing severe disease and death, the context-dependent variability in vaccine effectiveness, and the structural and socioeconomic determinants of vaccine coverage. We conclude that integrating equitable vaccine delivery, scalable preventive therapy, and child-adapted diagnostic strategies is essential to meaningfully reduce the global pediatric TB burden. Full article

The expansion of renewables in modern power systems and the coordinated development of upstream and downstream industrial chains are promoting a shift on the utility side from traditional settlement by energy toward operation driven by data and models. Industrial electricity consumption data exhibit pronounced multi-scale temporal structures and sectoral heterogeneity, which makes unified long-term load and generation forecasting while maintaining accuracy, interpretability, and scalability a challenge. From a modern system identification perspective, this paper proposes a System Identification in Adaptive Bayesian Framework (SIABF) for medium- and long-term industrial load forecasting based on daily freeze electricity time series. By combining daily aggregation of high-frequency data, frequency domain analysis, sparse identification, and long-term extrapolation, we first construct daily freeze series from 15 min measurements, and then we apply discrete Fourier transforms and a spectral complexity index to extract dominant periodic components and build an interpretable sinusoidal basis library. A sparse regression formulation with ${\ell }_1$ regularization is employed to select a compact set of key basis functions, yielding concise representations of sector and enterprise load profiles and naturally supporting multivariate and joint multi-sector modeling. Building on this structure, we implement a state-space-implicit physics-informed Bayesian forecasting model and evaluate it on real data from three representative sectors, namely, steel, photovoltaics, and chemical, using one year of 15 min measurements. Under a one-month-ahead evaluation using one year of 15 min measurements, the proposed framework attains a Mean Absolute Percentage Error (MAPE) of 4.5% for a representative PV-related customer case and achieves low single-digit MAPE for high-inertia sectors, often outperforming classical statistical models, sparse learning baselines, and deep learning architectures. These results should be interpreted as indicative given the limited time span and sample size, and broader multi-year, population-level validation is warranted. Full article

Background/Objectives: Institutional catering serves vulnerable populations, including schoolchildren. Surfaces in food preparation environments are key control points for food safety and reservoirs and transmission routes for antimicrobial-resistant (AMR) bacteria. This study characterized the hygienic status of food-contact surfaces (FCS) and non-food-contact surfaces (NFCS) in Hungarian school kitchens, identified contamination hotspots, and examined how routine monitoring can support AMR prevention. Methods: We retrospectively analyzed routine environmental hygiene monitoring records from 96 school kitchens (2019–2024). In total, 8412 swab samples were collected, 8407 had quantifiable counts, 6233 from FCS (e.g., plates, trays, boards, utensils), and 2174 from NFCS (e.g., sinks, fridges, workers’ hands). Total aerobic mesophilic counts were measured with a redox-potential method and expressed as CFU/100 cm²; 250 CFU/100 cm² (2.4 log₁₀) was the hygienic threshold. Results: Overall, 12.4% of surfaces exceeded the threshold. Non-food-contact surfaces were more likely to be non-compliant than food-contact surfaces (OR 2.77, 95% CI 2.43–3.17; p < 0.001). Hotspots included transport-container lids (67.2% non-compliant; OR 43.82), sink basins (32.8%; OR 10.46), and cutting boards (21.6%; OR 5.89). Seasonally, non-compliance was highest in summer (16.5%) and lowest in winter (9.0%; p < 0.001). Conclusions: Multi-year monitoring revealed substantial contamination concentrated in a few hotspots that, within a One Health framework—which recognizes the interconnectedness of human, animal, and environmental health—may represent environmental reservoirs and cross-contamination nodes relevant to AMR prevention. Targeted optimization of cleaning and disinfection for these surfaces, combined with trend analysis of indicator data and periodic AMR-focused environmental sampling, could reduce foodborne and AMR-related risks in public catering. Full article

Canada’s ageing population continues to grow rapidly and significantly more diverse, which will require unique health and home service needs. The COVID-19 pandemic exacerbated existing challenges in Canada’s healthcare system and demonstrated the need for long-term care (LTC). Semi-structured interviews were conducted with 17 decision makers, managers, and leaders in long-term ethnically focused facility care. Braun & Clarke’s six-stage process of thematic analysis was applied using an iterative, deductive approach to examine the experiences of stakeholders involved in the operational, managerial, financial, and clinical aspects of an ethnicity-focused LTC. Findings highlighted salient characteristics of impactful ethnicity-focused care and factors were uniquely shaped by the delivery of culturally specific care. Key subthemes included social isolation and emotional impact, operational and logistic difficulties during COVID-19, mitigation measures implemented in response, and the social, behavioural, and health benefits observed among seniors living in these LTC homes. Participants identified political and economic constraints (e.g., provincial funding) to establishing ethnicity-focused care homes but proposed several solutions and highlighted potential benefits that could support successful implementation. Analysis of experiences of operational challenges in safely and adequately running ethnicity-focused LTC reinforces the value of ethnicity-focused LTC during times of crisis such as the COVID-19 pandemic, as they provide a culturally safe and familiar space with preventive measures applied in a timely manner for seniors to engage with their peers in an environment that meets their health needs, ensuring safety standards. Full article