Uşak University is a university located in Uşak, Turkey. It was established in 2006.
Objectives This study examined the relationship between e-healthy nutrition literacy, maternal feeding attitudes, and anxiety levels in mothers of children with food allergies. Method This descriptive and correlational study was conducted between November 2024 and May 2025 with 174 mothers of children aged 0–6 years diagnosed with food allergies in western Türkiye. Data were collected through face-to-face interviews using the Sociodemographic Information Form, the e-Healthy Nutrition Literacy Scale, the Maternal Attitudes Toward Feeding Scale, and the Trait Anxiety Inventory to assess maternal anxiety. Descriptive statistics, correlation analyses, and multiple linear regression analyses including allergy-related symptom categories as predictors were performed. Results No significant relationship was found between e-healthy nutrition literacy and maternal anxiety or feeding attitudes. However, maternal feeding attitudes were positively associated with anxiety levels (p < 0.001). Regression analyses showed that e-healthy nutrition literacy was not a significant predictor of maternal anxiety or feeding attitudes. Breastfeeding status and systemic/cardiovascular symptoms were associated with maternal anxiety, whereas breastfeeding status, number of children, income level, and systemic/cardiovascular symptoms were associated with feeding attitudes. Mean scores were 37.23 ± 6.11 for e-healthy nutrition literacy, 71.40 ± 16.86 for maternal feeding attitudes, and 46.39 ± 7.47 for trait anxiety. Conclusion Maternal anxiety and feeding attitudes appear to be influenced more by clinical and caregiving-related factors than by e-healthy nutrition literacy alone. These findings highlight the importance of holistic approaches addressing both clinical and psychosocial dimensions in childhood food allergy management. Practice implications Nursing interventions focusing on symptom management and maternal coping may help reduce anxiety and improve the feeding process.
The purposes of the study were to offer a holistic approach to the assessment of global environmental sustainability, using spatial analysis, clustering, and explainable machine learning by employing data from 180 countries of the 2024 Environmental Performance Index. The methodological approach used is based on the integration of K-means clustering, regression analysis, and explainability using the SHAP model. Spatial analysis shows that regional gaps persist with Western Europe, North America, and parts of East Asia having good levels of performance, while Sub-Saharan Africa and South Asia consistently rank the lowest. The K-Means clustering method identified five structurally different types of countries, offering differentiation beyond aggregate rankings. Finally, in the predictive phase, the best accuracy is found to be through the Stacking Regressor method (R2: 0.9997; MAE: 0.1235), followed by Gradient Boosting (R2: 0.9490) and XGBoost (R2: 0.9070). The results of the feature importance using the SHAP method have identified the top drivers to be Ecosystem Vitality (3.1394) and Environmental Health (3.0261); however, it is noticeable that Climate Change, Air Quality, Water Resources, and Sanitation/Drinking Water have also played a role. The results illustrate the value of the argument that different countries with similar overall scores may have significantly different environmental structures. The proposed framework offers a clear instrument for the development of sustainability-oriented policies.
This study aimed to investigate the genotype-specific responses of five strawberry genotypes, two commercial cultivars (Festival, Rubygem), and three advanced breeding lines (Genotypes 36, 61, and 112), to two-spotted spider mite, Tetranychus urticae Koch (Acari: Tetranychidae) infestations under the contrasting pesticide regimes. Pest mite suppression significantly enhanced fruit yield from 289 to 702 g per plant, accompanied by increased fruit weight (14.6 to 18.5 g) and number (19.8 to 38.1 berries). Genotype 61 displayed consistently high levels of glucose (4.04 g/100 g FW), malic acid (2.34 g/kg FW), catechin (58.5 mg/kg), and ellagic acid (26.1 mg/kg) under untreated conditions, reflecting strong basal metabolic defense involving osmoprotective sugars, malic acid-driven respiratory flux for energy and antioxidant phenolics aiding redox homeostasis. Festival, maintained high anthocyanin (403 mg C3G/kg) and antioxidant capacity (1473 µmol/100 g FW) even after pest removal, indicating robust and sustained secondary metabolism regardless of stress presence. PCA confirmed genotype × treatment interactions, revealing a trade-off between yield-related traits and metabolites, where genotypes achieving higher productivity tended to exhibit downregulation of antioxidant and quality-related compounds. Results obtained emphasize the necessity of breeding metabolically resilient genotypes that can balance yield performance and quality-related metabolism for sustainable strawberry production under increasing pest pressure, which may be further influenced by changing environmental conditions.
The aim of this paper was to develop a novel triple network (TN) hydrogel via optimization of the composition of the hydrogel regarding self healing property. Poly hydroxyethyl methacrylate (PHEMA), gelatin and polyvinyl alcohol (PVA) based hydrogels were synthesized as first, second and third network structures respectively. The TN hydrogels were prepared via copolymerization, thermal gelation and freeze-thawing respectively. The three dimensional structure was formed through non-covalent interactions between polymer chains. The Box-Behnken design model was applied to the independent variables of the amounts of poly ethylene glycoldiacrylate (PEGDA) (X1), glutaraldehyde (X2) and gelatin (X3) against a dependent variable (self healing score). The further characterization of the TN hydrogel with ‘best’ self healing capability was performed with SEM, swelling, in-vitro hydrolytic degradation, in vitro cytotoxicity against L929 cell lines and mechanical tests. The cumulative release of lidocaine from TN hydrogel matrix was investigated for 48 h. The TN hydrogel with self healing capability, high biocompatibility, highly porous structure, high swelling capacity, moderate mechanical strength presented high potential as a drug delivery vehicle for various biomedical applications.
Deep eutectic solvents (DESs) have emerged as promising green alternatives to conventional organic solvents for the extraction of bioactive compounds from natural matrices because of their tunable physicochemical properties, low toxicity, and environmental compatibility. However, most existing reviews primarily focus on application-based results, with limited mechanistic and process engineering interpretations necessary for industrial applications. This review provides a comprehensive analysis of DES-based extraction from the perspective of separation and process engineering, emphasizing the relationships between DES composition, physicochemical properties, mass-transfer behavior, and extraction performance. Key parameters, including viscosity, hydrogen bonding interactions, solvent-to-feed ratio, temperature, and water content, are critically evaluated in terms of their influence on extraction efficiency, selectivity, and scalability. Furthermore, solvent recovery, process intensification strategies, and industrial implementation challenges are discussed to bridge the gap between laboratory research and large-scale application. By integrating mechanistic insights with process-level considerations, this review provides a systematic framework for the rational design and optimization of DES-based extraction processes as sustainable and scalable-separation technologies.
