Search Results (25,842)

Design Thinking (DT) has emerged as a relevant methodology for addressing global challenges aligned with the United Nations Sustainable Development Goals (SDGs). This study presents a systematic literature review, conducted following PRISMA 2020 guidelines, which analyzes 42 peer-reviewed publications from 2013 to 2023. Through inductive content analysis, 10 core DT principles—such as empathy, iteration, user-centeredness, and systems thinking—I identified and thematically mapped to specific SDGs, including goals related to health, education, innovation, and climate action. The study also presents five real-world cases from diverse sectors such as technology, healthcare, and urban planning, illustrating how DT has been applied to address practical challenges aligned with the SDGs. However, the review identifies persistent gaps in the field: the lack of standardized evaluation frameworks, limited integration across SDG domains, and weak adaptation of ethical and contextual considerations, particularly in vulnerable communities. As a response, this paper recommends the adoption of structured impact assessment tools (e.g., Cities2030, Responsible Design Thinking), integration of design justice principles, and the development of participatory, iterative ecosystems for innovation. By offering both conceptual synthesis and applied insights, this article positions Design Thinking as a strategic and systemic approach for driving sustainable transformation aligned with the 2030 Agenda. Full article

Crimean–Congo hemorrhagic fever (CCHF) is a zoonotic viral disease endemic to parts of Africa, Asia and southeastern Europe. Bulgaria is one of the few European countries with the consistent annual reporting of human CCHF cases. This study provides a descriptive overview of 24 confirmed CCHF cases in Bulgaria between 2015 and 2024. Laboratory confirmation was performed by an enzyme-linked immunosorbent assay (ELISA) and/or real-time reverse transcriptase polymerase chain reaction (RT-qPCR) testing. Common findings included fever, fatigue, gastrointestinal symptoms, thrombocytopenia, leukopenia, liver dysfunction and coagulopathy. Two fatal cases were recorded. Two samples collected in 2016 and 2024 were subjected to whole-genome sequencing. Phylogenetic analysis showed that both strains clustered within the Turkish branch of the Europe 1 genotype and shared high genetic similarity with previous Bulgarian strains, as well as strains from neighboring countries. These findings suggest the long-term persistence of a genetically stable viral lineage in the region. Continuous molecular and clinical surveillance is necessary to monitor the evolution and public health impact of CCHFV in endemic areas. Full article

Pediatric asthma is a multifactorial and heterogeneous disease determined by the dynamic interplay of genetic susceptibility, environmental exposures, and immune dysregulation. Recent advances have highlighted the pivotal role of epigenetic mechanisms, in particular, DNA methylation, histone modifications, and non-coding RNAs, in the regulation of inflammatory pathways contributing to asthma phenotypes and endotypes. This review examines the role of respiratory viruses such as respiratory syncytial virus (RSV), rhinovirus (RV), and other bacterial and fungal infections that are mediators of infection-induced epithelial inflammation that drive epithelial homeostatic imbalance and induce persistent epigenetic alterations. These alterations lead to immune dysregulation, remodeling of the airways, and resistance to corticosteroids. A focused analysis of T2-high and T2-low asthma endotypes highlights unique epigenetic landscapes directing cytokines and cellular recruitment and thereby supports phenotype-specific aspects of disease pathogenesis. Additionally, this review also considers the role of miRNAs in the control of post-transcriptional networks that are pivotal in asthma exacerbation and the severity of the disease. We discuss novel and emerging epigenetic therapies, such as DNA methyltransferase inhibitors, histone deacetylase inhibitors, miRNA-based treatments, and immunomodulatory probiotics, that are in preclinical or early clinical development and may support precision medicine in asthma. Collectively, the current findings highlight the translational relevance of including pathogen-related biomarkers and epigenomic data for stratifying pediatric asthma patients and for the personalization of therapeutic regimens. Epigenetic dysregulation has emerged as a novel and potentially transformative approach for mitigating chronic inflammation and long-term morbidity in children with asthma. Full article

Accurate estimation of actual evapotranspiration (ET) is critical for understanding hydrothermal cycles and ecosystem functioning in arid regions, where water scarcity governs ecological resilience. To address persistent gaps in ET quantification, this study integrates multi-source remote sensing data, energy balance modeling, and ground-based validation that significantly enhances spatiotemporal ET accuracy in the vulnerable desert steppe ecosystems. The study utilized meteorological data from several national stations and Landsat-8 imagery to process monthly remote sensing images in 2019. The Surface Energy Balance System (SEBS) model, chosen for its ability to estimate ET over large areas, was applied to derive modeled daily ET values, which were validated by a large-weighted lysimeter. It was shown that ET varied seasonally, peaking in July at 6.40 mm/day, and reaching a minimum value in winter with 1.83 mm/day in December. ET was significantly higher in southern regions compared to central and northern areas. SEBS-derived ET showed strong agreement with lysimeter measurements, with a mean relative error of 4.30%, which also consistently outperformed MOD16A2 ET products in accuracy. This spatial heterogeneity was driven by greater vegetation coverage and enhanced precipitation in the southeast. The steppe ET showed a strong positive correlation with surface temperatures and vegetation density. Moreover, the precipitation gradients and land use were primary controllers of spatial ET patterns. The process-based SEBS frameworks demonstrate dual functionality as resource-optimized computational platforms while enabling multi-scale quantification of ET spatiotemporal heterogeneity; it was therefore a reliable tool for ecohydrological assessments in an arid steppe, providing critical insights for water resource management and drought monitoring. Full article

Background: The relationship between sports participation and food preferences in adults, as well as the influence of gender, is still unclear. Objective: The objective of this study was to investigate the association between sports participation and individual food preferences and to explore potential gender differences among sports participants in a large group of Italian adults. Methods: This cross-sectional study involved 2665 adults (aged ≥ 18 years) who lead normal lives and underwent a routine lifestyle and dietary assessment at a clinical centre specialising in nutrition, metabolic health, and lifestyle counselling in Rome. Participants completed an online questionnaire on food preferences (19 foods) and sports practice. Multivariate logistic regression models, adjusted for age, sex, and smoking, were used to assess associations. Results: Sports participation was defined as engaging in structured physical activity at least once per week and was reported by 53.5% of subjects (men: 60.1%; women: 49.0%; p < 0.0001). After adjustment, active individuals were significantly more likely to prefer plant-based drinks, low-fat yoghurt, fish, cooked and raw vegetables, fruit, whole grains, tofu, and dark chocolate (all p < 0.05) and less likely to prefer cow’s milk (p = 0.018). Among sport participants, males were more likely to prefer meat (general, white, red, processed) and eggs, while females preferred plant-based drinks. No significant gender differences were observed for dairy products, legumes, or fish. Differences in food preferences were also observed according to the type of sport, with bodybuilders showing higher preference for tofu and dark chocolate. The strongest associations were found in the 25–44 age group. Conclusions: Sports participation is independently associated with specific food preferences, characterised by greater preference for plant-based and fibre-rich foods, and gender differences in food choices persist even among active adults. These findings highlight the need to consider both sports participation and gender when designing nutritional interventions. Full article

Fileless malware is a type of malware that does not rely on executable files to persist or propagate. Unlike traditional file-based malware, fileless malware is more difficult to detect and remove, posing a significant threat to organizations. This paper introduces a novel hybrid analysis model that combines static and dynamic analysis techniques to identify fileless malware. Applied to four real-world and two custom-created fileless malware samples, the proposed model demonstrated its qualitative effectiveness in uncovering complex behaviors and evasion tactics, such as obfuscated macros, process injection, registry persistence, and covert network communications, which often bypass single-method analyses. While the analysis reveals the potential for significant damage to organizational reputation, resources, and operations, the paper also outlines a set of mitigation measures that cybersecurity professionals and researchers can adopt to protect users and organizations against threats posed by fileless malware. Overall, this research offers valuable insights and a novel analysis model to better address and understand fileless malware threats. Full article

This study develops and validates an artificial intelligence (AI)-assisted internship learning platform for automotive electronics based on the Llama 3 large language model, aiming to enhance pedagogical effectiveness within vocational training contexts. Addressing critical issues such as the persistent theory–practice gap and limited innovation capability prevalent in existing curricula, we leverage the natural language processing (NLP) capabilities of Llama 3 through fine-tuning based on transfer learning to establish a specialized knowledge base encompassing fundamental circuit principles and fault diagnosis protocols. The implementation employs the Hugging Face Transformers library with optimized hyperparameters, including a learning rate of 5 × 10⁻⁵ across five training epochs. Post-training evaluations revealed an accuracy of 89.7% on validation tasks (representing a 12.4% improvement over the baseline model), a semantic comprehension precision of 92.3% in technical question-and-answer assessments, a mathematical computation accuracy of 78.4% (highlighting this as a current limitation), and a latency of 6.3 s under peak operational workloads (indicating a system bottleneck). Although direct trials involving students were deliberately avoided, the platform’s technical feasibility was validated through multidimensional benchmarking against established models (BERT-base and GPT-2), confirming superior domain adaptability (F1 = 0.87) and enhanced error tolerance (σ² = 1.2). Notable limitations emerged in numerical reasoning tasks (Cohen’s d = 1.15 compared to human experts) and in real-time responsiveness deterioration when exceeding 50 concurrent users. The study concludes that Llama 3 demonstrates considerable promise for automotive electronics skills development. Proposed future enhancements include integrating symbolic AI modules to improve computational reliability, implementing Kubernetes-based load balancing to ensure latency below 2 s at scale, and conducting longitudinal pedagogical validation studies with trainees. This research provides a robust technical foundation for AI-driven vocational education, especially suited to mechatronics fields that require close integration between theoretical knowledge and practical troubleshooting skills. Full article

A new generation of compact radon detectors with high sensitivity and fine spatial resolution (1–2 cm scale) was used to investigate indoor radon distribution and identify potential entry pathways. Solid-state nuclear track detectors (Kodak-Pathe LR-115 type II, Dosirad, France), combined with activated carbon fabric (ACC-5092-10), enabled sensitive, spatially resolved radon measurements. Two case studies were conducted: Case 1 involves a room with elevated radon levels suspected to originate from the floor. Case 2 involves a house with persistently high indoor radon concentrations despite active basement ventilation. In the first case, radon emission from the floor was found to be highly inhomogeneous, with concentrations varying by more than a factor of four. In the second, unexpectedly high radon levels were detected at electrical switches and outlets on walls in the living space, suggesting radon transport through wall voids and entry via non-hermetic electrical fittings. These novel detectors facilitate fine-scale mapping of indoor radon concentrations, revealing ingress routes that were previously undetectable. Their use can significantly enhance radon diagnostics and support the development of more effective mitigation strategies. Full article

Background: Trichosporon spp. are opportunistic fungi, capable of causing infection, especially in critically ill individuals who often use broad-spectrum antibiotics, invasive devices, and have comorbidities. Objectives The aim of this study was to analyze individuals’ clinical characteristics, evaluate tolerance to biocides, as well as biofilm formation and efflux pump activity in isolates of Trichosporon asahii. Methods: Clinical isolates of T. asahii collected between 2020 and 2023 from both hospitalized and non-hospitalized individuals, of both sexes, regardless of age, were tested for tolerance to sodium hypochlorite, hydrogen peroxide, benzalkonium chloride, and ethyl alcohol. Efflux pump activity was also assessed using ethidium bromide, and biofilm formation was measured with the Safranin test. Clinical parameters such as outcomes, source, and length of hospitalization were analyzed through electronic medical records. Results: A total of 37 clinical isolates of T. asahii were identified. Thirty-three (83.8%) isolates were from hospitalized individuals, with 81.82% collected in ICUs, an average hospital stay of 35 days, and a mortality rate of 51.6%. The tested strains displayed the largest mean inhibition zone for 2% sodium hypochlorite, indicating lower tolerance. A high level of efflux pump expression was detected among clinical isolates. Biofilm formation was detected in 25/67.5% of the isolates. Conclusions: These findings highlight the clinical relevance of T. asahii, particularly in critically ill individuals, and underscore the pathogen’s ability to tolerate biocides, express efflux pumps, and form biofilms, all of which may contribute to its persistence and pathogenicity in hospital environments. Enhanced surveillance and effective microbial control measures are essential to mitigate the risks associated with T. asahii infections. Full article

Sodium p-perfluorous nonenoxybenzenesulfonate (OBS) has been proposed as a substitute for perfluorooctanesulfonic acid (PFOS), yet it has garnered increasing attention due to its environmental persistence and potential toxicity. Despite these concerns, the neurotoxic mechanisms of OBS remain unclear. This study investigates and compares the neurotoxic effects and mechanisms of OBS and PFOS in Caenorhabditis elegans. L4-stage worms were exposed to OBS (0.1–100 μM) or PFOS (100 μM) for 24 h. Neurobehavioral analysis showed that OBS exposure induced concentration-dependent neurobehavioral deficits, with 100 μM OBS significantly reducing pharyngeal pumping rate (29.8%), head swing frequency (23.4%), and body bending frequency (46.6%), surpassing the effects of PFOS. Both compounds decreased the fluorescence intensity of dopaminergic, glutamatergic, and γ-aminobutyric acid neurons and downregulated neurotransmitter-associated genes. They also increased ROS generation and inhibited antioxidant gene expression. Molecular docking revealed that OBS had a stronger binding affinity to p38 MAPK key protein (PMK-1) than PFOS. OBS and PFOS upregulated pmk-1 and skn-1, modulating oxidative stress and neuronal function. pmk-1 mutation differentially affected OBS-induced neurobehavioral changes and gene expression alterations. Our findings indicate that OBS exhibits stronger neurotoxicity than PFOS in Caenorhabditis elegans, mediated through the PMK-1 pathway. These results highlight the need for further investigation into the safety of OBS as a PFOS alternative. Full article

Ventricular tachycardia (VT) remains a major cause of morbidity and mortality in patients with structural heart disease. While catheter ablation has become a cornerstone in VT management, recurrence rates remain substantial due to limitations in electroanatomic mapping (EAM), particularly in cases of deep or heterogeneous arrhythmogenic substrates. Cardiac imaging, especially when multimodal and integrated with mapping systems, has emerged as a critical adjunct to enhance procedural efficacy, safety, and individualized strategy. This comprehensive review explores the evolving role of various imaging modalities, including echocardiography, cardiac magnetic resonance (CMR), computed tomography (CT), positron emission tomography (PET), and intracardiac echocardiography (ICE), in the preprocedural and intraprocedural phases of VT ablation. We highlight their respective strengths in substrate identification, anatomical delineation, and real-time guidance. While limitations persist, including costs, availability, artifacts in device carriers, and lack of standardization, future advances are likely to redefine procedural workflows. Full article

Reactive oxygen species (ROS) are often seen solely as harmful byproducts of oxidative metabolism, yet evidence reveals their paradoxical roles in both promoting and inhibiting cancer progression. Despite advances, precise context-dependent mechanisms by which ROS modulate oncogenic signaling, therapeutic response, and tumor microenvironment dynamics remain unclear. Specifically, the spatial and temporal aspects of ROS regulation (i.e., the distinct effects of mitochondrial versus cytosolic ROS on the PI3K/Akt and NF-κB pathways, and the differential cellular outcomes driven by acute versus chronic ROS exposure) have been underexplored. Additionally, the specific contributions of ROS-generating enzymes, like NOX isoforms and xanthine oxidase, to tumor microenvironment remodeling and immune modulation remain poorly understood. This review synthesizes current findings with a focus on these critical gaps, offering novel mechanistic insights into the dualistic nature of ROS in cancer biology. By systematically integrating data on ROS source-specific functions and redox-sensitive signaling pathways, the complex interplay between ROS concentration, localization, and persistence is elucidated, revealing how these factors dictate the paradoxical support of tumor progression or induction of cancer cell death. Particular attention is given to antioxidant mechanisms, including NRF2-mediated responses, that may undermine the efficacy of ROS-targeted therapies. Recent breakthroughs in redox biosensors (i.e., redox-sensitive fluorescent proteins, HyPer variants, and peroxiredoxin–FRET constructs) enable precise, real-time ROS imaging across subcellular compartments. Translational advances, including redox-modulating drugs and synthetic lethality strategies targeting glutathione or NADPH dependencies, further highlight actionable vulnerabilities. This refined understanding advances the field by highlighting context-specific vulnerabilities in tumor redox biology and guiding more precise therapeutic strategies. Continued research on redox-regulated signaling and its interplay with inflammation and therapy resistance is essential to unravel ROS dynamics in tumors and develop targeted, context-specific interventions harnessing their dual roles. Full article

Fluorescent dyes, such as cyanine dyes, are widely used in fluorescence-imaging-guided tumor therapy due to their high absorbance and fluorescence quantum yield. However, challenges persist in optimizing the performance of fluorescent nanoparticles, particularly due to the aggregation-caused quenching (ACQ) effect of cyanine dyes. Here, a novel counterion construction strategy is introduced using cyanine dye as a model ACQ dye. Through dynamic-controlled flash nanoprecipitation, fluorescent nanoparticles (CyINPs) with tunable structures are developed, investigating the effects of various factors, including counterions, block copolymers, and dye concentrations, on CyINPs’ stability and fluorescence enhancement. The optimized CyINPs with good water solubility show a 21-fold increase in fluorescence intensity and a 3.5-fold increase in encapsulation efficiency compared to CyINPs prepared by a thermodynamic-driven method. Under the efforts of polymers and counterions, dyes are separated, which reduces the impact of the ACQ effect and results in stronger fluorescence intensity, providing insights into improving nanoparticle biocompatibility and energy utilization efficiency. Full article

The integration of Inquiry-Based Learning (IBL) and mobile technologies can transform science education, offering experimentation opportunities to students from budget-constrained schools. This study investigates the efficacy of smartphone-assisted experimentation (SAE) within IBL to enhance pre-service science teachers’ understanding of human physiology and presents a newly developed and validated rubric for assessing their scientific skills. Students (N = 286) from a Science and Mathematics Teacher Education Program participated in a summative IBL activity (“Investigating the Human Physiology”—iHPhys) where they designed experimental projects using smartphone applications to collect body sign data. The scoring rubric, assessing seven criteria including hypothesis formulation, methodological design, data presentation, and conclusion writing, was validated as substantial to almost perfect inter-rater reliability. Results reveal that students exhibited strong skills in hypothesis clarity, theoretical grounding, and experimental design, with a high degree of methodological innovation observed. However, challenges persisted in predictive reasoning and evidence-based conclusion writing. The students were strongly interested in inquiring about the cardiovascular and nervous systems. Correlational analyses suggest a positive relationship between project originality and overall academic performance. Thus, integrating SAE and IBL fosters critical scientific competencies, creativity, and epistemic cognition while democratizing access to scientific experimentation and engaging students in tech-savvy pedagogical practices. Full article

Background: Atrial fibrosis is a key contributor to atrial cardiomyopathy and can be assessed invasively using mean left atrial voltage (MLAV) from electroanatomical mapping. However, the invasive nature of this procedure limits its clinical applicability. Machine learning (ML), particularly regression tree-based models, may offer a non-invasive approach for predicting MLAV using clinical and echocardiographic data, improving non-invasive atrial fibrosis characterisation beyond current dichotomous classifications. Methods: We prospectively included and followed 113 patients with paroxysmal or persistent atrial fibrillation (AF) undergoing pulmonary vein isolation (PVI) with ultra-high-density voltage mapping (uHDvM), from whom MLAV was estimated. Standardised two-dimensional transthoracic echocardiography was performed before ablation, and clinical and echocardiographic variables were analysed. A regression tree model was constructed using the Classification and Regression Trees—CART-algorithm to identify key predictors of MLAV. Results: The regression tree model exhibited moderate predictive accuracy (R² = 0.63; 95% CI: 0.55–0.71; root mean squared error = 0.90; 95% CI: 0.82–0.98), with indexed minimum LA volume and passive emptying fraction emerging as the most influential variables. No significant differences in AF recurrence-free survival were found among MLAV tertiles or model-based generated groups (log-rank p = 0.319 and p = 0.126, respectively). Conclusions: We present a novel ML-based regression tree model for non-invasive prediction of MLAV, identifying minimum LA volume and passive emptying fraction as the most significant predictors. This model offers an accessible, non-invasive tool for refining atrial cardiomyopathy characterisation by reflecting the fibrotic substrate as a continuum, a crucial advancement over existing dichotomous approaches to guide tailored therapeutic strategies. Full article