Search Results (15,271)

Background/Objectives: Type 2 diabetes mellitus (T2DM) is a major public health challenge, and several lifestyle-related factors associated with later T2DM may already emerge during the secondary school years. Socioeconomic status (SES), nutrition-related behaviors, physical activity, and basic diabetes-related knowledge may shape these early risk-related patterns. This study examined the relationships between SES, adapted FINDRISC-based T2DM-related risk patterns, and diabetes-related knowledge among Hungarian secondary school students aged 16–20 years. Methods: A nationwide, cross-sectional questionnaire survey was conducted among students attending Hungarian Baptist secondary schools (N = 1585). SES was classified by Two-Step cluster analysis based on parental education, parental occupation, number of books in the household, and frequency of travel abroad. Relative T2DM-related risk patterns were described using an age-adapted FINDRISC-based screening approach, and basic diabetes-related knowledge was assessed using a 12-item questionnaire. Associations were examined using cross-tabulation and regression analyses in SPSS version 27.0. Results: Most respondents fell into the lower categories of the adapted FINDRISC-based screening framework, whereas 7.4% were classified into the moderate or high adapted FINDRISC-based screening categories. SES was significantly associated with adapted FINDRISC-based screening categories (p < 0.001). Compared with the medium-SES group, students in the low-SES group had higher odds of belonging to a higher adapted FINDRISC-based screening category (OR = 1.81; 95% CI: 1.27–2.57; p = 0.001). SES was also significantly associated with basic diabetes-related knowledge profiles (p = 0.015); students with high SES were less likely to be in the low-knowledge group than in the high-knowledge group (OR = 0.62; p = 0.039). Conclusions: Social inequalities in T2DM-related risk patterns and diabetes-related knowledge are already visible among secondary school students aged 16–20 years. The adapted FINDRISC-based approach may be useful as a school-based, non-invasive descriptive screening framework for characterizing relative T2DM-related risk patterns, but it is not a validated risk prediction instrument for this age group. Full article

Brain tumor classification from magnetic resonance imaging, which is also known as MRI, plays a sensitive role in computer-assisted diagnosis systems. In recent years, deep learning models have achieved high classification accuracy. However, their sensitivity to adversarial perturbations has become an important reliability concern in medical applications. This study suggests a robust brain tumor classification framework that combines non-negative matrix factorization (NNMF or NMF), lightweight convolutional neural networks (CNNs), and diffusion-based feature purification. Initially, MRI images are preprocessed and converted into a non-negative data matrix, from which compact and interpretable NNMF feature representations are extracted. Statistical metrics, including AUC, Cohen’s d, and p-values, are used to rank and choose the most discriminative components. Then, a lightweight CNN classifier is trained directly on the selected feature groups. To improve adversarial robustness, a diffusion-based feature-space purification module is introduced. A forward noise method followed by a learned denoiser network is used before classification. System performance is estimated using both clean accuracy and robust accuracy under powerful adversarial attacks created by AutoAttack. The experimental results show that the proposed framework achieves competitive classification performance while significantly enhancing robustness against adversarial perturbations. The findings presuppose that combining interpretable NNMF-based representations with a lightweight deep approach and diffusion-based defense technique supplies an effective and reliable solution for medical image classification under adversarial conditions. Full article

Parental involvement is widely recognized as a key component of effective schooling, particularly in educational environments that emphasize community, developmental continuity, and holistic pedagogy. Alternative education models such as Waldorf schools have expanded internationally, yet empirical evidence on how parents perceive and structure their experiences within these institutions remains limited. This study investigates parental perceptions of Waldorf education in Hungary through a nationwide questionnaire survey of 585 parents whose children attend Waldorf schools. To explore the latent structure of parental evaluations, Exploratory Factor Analysis was conducted, followed by Confirmatory Factor Analysis to test the stability of the resulting model. The analyses identified four coherent dimensions of parental experience: Trust and Pedagogy, Community and Engagement, Perceived Long-Term Educational Prosperity, and Information and Transparency. Additional analyses examined how these dimensions vary according to institutional characteristics, parental participation in school community activities, and intentions regarding long-term enrollment. The results indicate that pedagogical trust constitutes a relatively stable evaluative dimension across institutions, while perceptions related to community engagement, long-term educational prospects, and transparency are more strongly associated with institutional maturity. Parents who intend to remain in Waldorf education until the completion of upper secondary schooling report consistently higher evaluations across all dimensions. By empirically identifying the structure of parental experiences in a European alternative education context, the study contributes to research on parental engagement, school choice, and the institutional cultures of alternative schooling. Full article

Background/Objectives: Dietary sweetener use is common among individuals with diabetes, yet little is known about the socioeconomic and dietary factors that influence the choice between caloric and artificial sweeteners in Central and Eastern Europe. This study examined the determinants of caloric and artificial sweetener use among adults with diabetes mellitus (DM) in Hungary. Methods: We conducted a cross-sectional analysis using frequency-based self-reported dietary measures of 542 adults with self-reported DM from the 2019 European Health Interview Survey (EHIS). Weighted descriptive statistics and multivariable logistic regression models were used to evaluate associations between sweetener use and sociodemographic, lifestyle, and dietary characteristics. Results: Overall, 28.0% of participants reported daily use of caloric sweeteners, and 45.2% reported daily use of artificial sweeteners. Higher educational attainment and healthier dietary patterns, including greater fruit and vegetable consumption, were associated with lower odds of caloric sweetener use. Individuals with lower fruit and vegetable intake, less frequent fruit juice consumption, and poor adherence to diabetic diet recommendations were more likely to use caloric sweeteners. In contrast, artificial sweetener use was strongly associated with daily fruit consumption, lower intake of fruit juice, and adherence to a diabetic diet. Vegetable intake showed a positive association with artificial sweetener use, which may reflect compensatory patterns in dietary self-management. Conclusions: Caloric and artificial sweetener use were associated with distinct socioeconomic and dietary profiles. Caloric sweetener use was linked to less healthy dietary behaviors, whereas artificial sweetener use appeared to be consistent with sugar-reduction strategies. These findings highlight the need for tailored dietary counseling that addresses both sweetener use and broader dietary patterns among individuals with diabetes in Hungary. Full article

Trained immunity is a concept that is currently in development and refers to the long-term functional reprogramming of innate immune cells in response to microbial or inflammatory stimuli. This process serves a dual purpose in the gastrointestinal tract, contributing to chronic inflammatory conditions like inflammatory bowel disease and maintaining host defense. The production of pro-inflammatory mediators is augmented by epigenetic and metabolic changes that are induced by the persistent activation of innate immune cells, which is triggered by microbial components and damage-associated signals. Although this increased responsiveness may initially be protective, sustained activation leads to tissue damage, epithelial barrier dysfunction, and chronic inflammation. These mechanisms are significant contributors to colorectal carcinogenesis, particularly in colitis-associated cancer. Through the activation of oncogenic signaling pathways, the establishment of a pro-tumorigenic microenvironment, and an increase in oxidative stress, trained immunity also influences tumor development. Additionally, the systemic reprogramming of hematopoietic progenitor cells has the potential to exacerbate inflammation and facilitate the progression of tumors. The identification of epigenetic and metabolic biomarkers associated with trained immunity can lead to novel diagnostic opportunities. Targeting metabolic and epigenetic pathways, as well as regulating the intestinal microbiota, is a promising therapeutic approach that could enhance the effectiveness of treatments for colorectal cancer while minimizing adverse effects on the immune system. Nevertheless, it is necessary to maintain a delicate equilibrium to suppress pathological inflammation without compromising protective immune responses. In general, trained immunity may represent a potentially relevant mechanistic link between chronic inflammation and colorectal cancer; however, its role remains context-dependent and not yet fully defined. Full article

This study investigated phase-dependent changes in gut microbiome composition, predicted functional potential, and lipid metabolism in intensively reared broiler chickens and ducks across the starter, grower, and finisher phases (from day-old to 42 days of age), over six production cycles (four chicken and two duck cycles), using 16S rRNA sequencing and blood lipids profiling. A total of 70 pooled manure samples were collected (46 from chickens and 24 from ducks), along with 34 blood samples (22 from chickens and 12 from ducks), all obtained under standard production conditions. Microbial diversity remained stable across growth phases within each species, whereas clear interspecies differences were observed (p < 0.01). Microbiome maturation involved a shift from early facultative and environmentally associated taxa during the starter phase (day-old to 14 days of age), including Acinetobacter (p < 0.01) and Enterococcus (p < 0.001), toward a more stable, host-adapted community. At the level of predicted functional pathways, shifts between growth phases were more pronounced in ducks. Predicted gene-level profiles showed phase-specific differentiation in chickens, with starter-associated genes linked to core carbon and nitrogen metabolism and finisher-associated genes related to structural and transport functions, whereas ducks exhibited a more balanced reorganization involving carbohydrate, energy, and nitrogen metabolism. Host lipid profiles between adjacent growth phases showed dynamic shifts in ducks (p < 0.05). These species-specific lipid patterns were mirrored by microbiome–lipid associations, as demonstrated by correlation analyses between dominant bacterial genera and blood lipid parameters, revealing more coordinated relationships in chickens and more heterogeneous patterns in ducks. Overall, these findings demonstrate species-specific organization of gut microbiome changes and their integration with blood lipid profiles under intensive production conditions. Full article

Green husks, which are the fleshy pericarp of Juglans regia L. fruit, are an abundant yet under-utilized source of bioactive compounds. They are useful for plant defense and have potential for valorization to multiple commercial products. This study characterized total phenolic content (TPC) and individual phenolics in green husks of four Hungarian-bred cultivars (Milotai 10, Milotai intenzív, Milotai kései, Esterhazy kései) and one U.S. cultivar (Chandler). Phenolic compounds were extracted with aqueous organic solvents, quantified by HPLC-DAD and qualitatively identified by HPLC-MS. Linear mixed-effects models were used to assess the effects of cultivar, year, sampling time, and cumulative growing degree days (GDDs) on TPC and compound profiles. Mean TPC ranged from 34.9 to 57.2 mg GAE g⁻¹ DW, with significantly higher values in the warmest year, 2024, and in cultivar Esterhazy kései compared with Chandler. Across cultivars and years, phenolic levels were generally elevated at early lignification (S1, BBCH 73–75) and at full maturity (S5–S6, BBCH 87–88), with depressed concentrations during mid-fruit development (S2–S4, BBCH 77–86). Several hydroxycinnamic acids, flavonoids, and naphthoquinones showed cultivar-specific and year-dependent patterns. Thermal conditions (cumulative GDDs) explained a substantial proportion of residual variation in TPC. These results highlight the combined roles of genotype, seasonal climate, and developmental stage dependencies in biosynthetic processes of phenolics in walnut green husks despite the diversity in factor effects. Full article

Falls are a leading cause of paediatric injuries, yet school-based prevention relies heavily on subjective observation rather than objective biomechanical assessment. This paper introduces the Safe Fall framework, integrating a judo-inspired educational programme with an occlusion-robust computer vision pipeline to quantify safe falling strategies. We analysed video recordings of 285 schoolchildren using a multi-stage architecture combining YOLOv8 for detection, SAM 2 for segmentation, and MMPose for skeletal tracking. The intervention yielded significant improvements in 60% of kinematic metrics ($p<0.05$), most notably a $+61.4\%$ increase in descent rate and expanded rolling ranges, indicating a shift from hazardous “freezing” behaviours to controlled energy dissipation. Unsupervised clustering confirmed a migration of students towards safe motor profiles, while a Random Forest classifier achieved an accuracy of 98.3% and an AUC of 0.998 in distinguishing fall quality. These findings demonstrate that integrating pedagogical training with automated vision modelling provides a scalable and evidence-based approach for reducing injury risk in real-world school environments. Full article

The operation of driver assistance systems and autonomous vehicles requires a sensor system and a control algorithm. Sensors provide information to detect people, vehicles and objects in the vehicle’s environment; however, their performance can be degraded by adverse environmental conditions and contamination. This literature review identified factors that reduce sensor visibility, such as weather conditions and external contamination. In this study, the detection efficiency of state-of-the-art neural network-based object detectors was examined in a simulation environment using a synthetic dataset. A custom dataset comprising six urban and suburban traffic scenarios was created, including clean images and ten contaminated variants per scene with increasing mud coverage. The results show that contamination leads to a measurable reduction in detection performance across all models. Smaller variants are more sensitive to degradation, while medium-complexity models provide a favorable balance between robustness and computational cost. Increasing model size yields limited additional robustness, and performance differences between architectures highlight the importance of model design. Furthermore, the spatial distribution of contamination, particularly near the image center, has a significant impact on performance in addition to its overall extent. Full article

The Vehicle-to-Grid (V2G) technology is considered one of the best solutions for integrating renewable energy systems; however, most literature reports favorable economic results using synthetic data, without accounting for seasonal or market limitations. The current research presents the results of the MATLAB R2023b (Version 23.2, MathWorks, Natick, MA, USA) simulation of the 100-household energy community in Debrecen, Hungary, with 30 electric vehicles (EVs) using entirely simulation-based Lithium Iron Phosphate (LiFePO4) batteries, a simulation-based 150 kW solar photovoltaic (PV) system, and a simulation-based 200 kW wind power system, using real meteorological data for January 2024. The optimization of charging/discharging for electric vehicles was performed using a multi-objective genetic algorithm (GA) over 30 days at a 15 min time resolution, accounting for stochastic loads and temperature effects on battery degradation, with a sensitivity analysis of key parameters. The results of the optimized solution for the electric vehicle charging/discharging were unexpected: the total energy cost increased by 68.9% ($4337.65 to $7327.54), the peak demand increased by 266.2% (31.9 to 116.9 kW), the degradation cost was $479.63, the load factor was reduced from 0.847 to 0.722, and the SOC constraint was violated for 0.758% of measurements. The V2G is not economically viable under current Hungarian pricing and Central Europe winter conditions. Results are robust for varying parameters using sensitivity analysis and Pareto front tracing. The break-even point is achieved when ratios of peak-to-off-peak prices are above 3.5:1. Seasonal policies and market reforms are critical for V2G viability. Importantly, the influence of inherent design deficiencies in the optimization model on the reported results cannot be ruled out. Full article

Conceptual ambiguity in People–Place Relationships (PPR) research limits consistent operationalization and cross-context comparability, particularly in under-represented cultural settings. This study develops an integrated, context-sensitive framework for assessing PPR in residential environments and empirically examines its measurement structure. The framework is applied in Damascus as a pilot context to assess its structural validity, internal consistency, and applicability. The methodological approach comprised two stages: conceptual development and empirical validation. First, two rounds of case-study analysis derived from a prior systematic literature review synthesized environmental (social and urban) and relational (cognitive, affective, attachment) dimensions into a coherent framework. Second, the framework was operationalized and tested using survey data from 1610 residents across Damascus districts. Six first-order indices and one composite PPR index were constructed and evaluated using exploratory factor analysis and Cronbach’s alpha with item–total correlation analysis. Results demonstrate a stable multidimensional structure that integrates evaluative environmental conditions with relational processes, moving beyond emotion-dominant interpretations of attachment. The framework advances existing approaches by linking theoretical constructs to empirically tested measurement dimensions. While further validation in diverse contexts is required, the results indicate that the model provides a coherent and adaptable basis for assessing residential PPR in socio-culturally complex urban environments. Full article

Background/Objectives: Several recent human studies have associated the use of certain medicines, such as antibiotics and antacids, with allergic conditions, potentially through microbiome disruption. In contrast, probiotics which may prevent dysbiosis, could have protective effects. Our meta-analysis aimed to evaluate the impact of these drugs (consumed during pregnancy or early life) on the risk of childhood food allergy, based on the available literature. Methods: Literature searches were conducted in the EMBASE, PubMed, Cochrane, and Web of Science databases using predefined PICO criteria. Overall, our meta-analysis included 25 studies involving 1,662,861 mothers and 5,164,280 children. Results: Using the random-effects model, we found that prenatal and early life antibiotic use (up to 2 years of age) was associated with higher odds of food allergy in childhood (OR: 1.34; 95% CI [1.10, 1.63], OR: 1.53; 95% CI [1.18, 1.98], respectively). Proton pump inhibitors were also associated with a risk of food allergies (OR: 2.65; 95% CI [1.22–5.77]), whereas the impact of H2-receptor antagonists was non-significant (OR: 2.07; 95% CI [0.96–4.45]). Probiotic use during the first two years of life was not associated with decreased risk for food allergy in children (OR: 1.25; 95% CI [0.46, 3.38]). Conclusions: These findings suggest an association between microbiome-disrupting medications during pregnancy and early childhood and an increased risk of childhood food allergy, especially those with a family history of food allergy. However, due to the predominantly observational design of the included studies, causality cannot be established. These results highlight the need for cautious and judicious use of such medications in these populations. Full article

Weed control of solanaceous weeds growing with solanaceous crops is a constant challenge. Infected by viruses, they can also act as virus reservoirs, complicating this problem further. Viromes of annual Solanum nigrum, Datura stramonium, and Solanum dulcamara, a perennial climbing shrub, were investigated using RNA sequencing and validated using RT-PCR, revealing infection with nine viruses. Broad bean wilt virus 1 (BBWV1), cucumber mosaic virus (CMV), and potato virus M (PVM) were found to infect S. nigrum. Investigating only 46 plants revealed infection with Solanum dulcamara yellow fleck virus (SDYFV) not only in S. dulcamara but in a new host, D. stramonium, which also represents a new host of turnip yellows virus (TuYV). We described the first presence of a potato virus H (PVH)-like, and Oxybasis rubra mitovirus 1 (OxruMV1)-like virus in Europe, in S. dulcamara as a new host. Our results highlight the unexpected complexity of the viromes of solanaceous weeds, which should be considered during reliable and efficient plant protection strategies, in order to alleviate the virus reservoir role of the weeds. Full article

Thermal processing of biomass can induce chemical transformations that lead to the formation of fluorescent carbonaceous products. In this study, six β-glucan-rich medicinal mushrooms, Ganoderma lucidum, Cordyceps sinensis, Inonotus obliquus, Lentinula edodes, Grifola frondosa, and Hericium erinaceus, were subjected to mild pyrolytic treatment (200 °C for 3 h) to investigate the formation of water-soluble fluorescent fractions. Physicochemical characterization of aqueous extracts was performed using high-performance liquid chromatography size-exclusion chromatography (HPLC-SEC), fluorescence emission spectroscopy, Fourier-transform infrared spectroscopy (FTIR), and β-glucan quantification. Fluorescence emission spectra revealed species-dependent differences in emission intensity, with the most pronounced signals observed for G. lucidum and C. sinensis. HPLC-SEC analysis showed only minor changes in molecular weight distribution after thermal treatment, suggesting limited polymer degradation. FTIR spectra indicated moderate structural modifications consistent with partial carbonization and chemical rearrangement within the mushroom matrices. Despite the mild processing conditions, measurable increases in fluorescence intensity were observed in several species, indicating the formation of fluorescent carbon-rich molecular structures. These findings demonstrate that moderate thermal treatment of β-glucan-rich fungal biomass can generate water-soluble fluorescent carbonaceous fractions without extensive breakdown of the original polysaccharide matrix. The results provide new insights into thermally induced photophysical changes in medicinal mushrooms and contribute to understanding the formation of fluorescent carbonaceous products from natural biomaterials. Full article

This study aimed to collect survey data on physical activity and organized sport participation among children across different weight categories. Using online data collection, 906 parents provided information about 1002 children (age = 10.9 ± 2.5 years, body height = 150.2 ± 16.4 cm, and body mass = 42.4 ± 15.8 kg). Most children (79%) achieved the recommended 60 min. of moderate-to-vigorous physical activity (MVPA) per day; 50% participated in club sports; and 41% took part in organized sports. Most of them (69%) were in the healthy weight category, 7% were underweight, and 22% of the children were overweight or obese. Participation in sports activities among overweight and obese children was nearly as high as among their peers. Achieving 60 min. of MVPA/day was associated with significantly lower odds (OR = 0.51 CI: 0.30–0.85; p < 0.01) of childhood obesity in the total sample. Football was the most popular club and organized sport among boys, while dancing was most preferred among girls. The preferred sports were generally well-suited to the respective weight categories. The relatively high levels of physical activity observed may be explained by daily physical education (PE) classes in schools and governmental support for sports. Our findings suggest that further research is needed to support effective obesity prevention, particularly those examining dietary habits and other lifestyle factors. Full article