Search Results (2,880)

Background: Smartphones are ubiquitous among young adults today. However, many young adults exhibit characteristics of problematic or dependent phone use. These individuals often have sleep disturbances and difficulties with emotional regulation. Currently, the research on the connection between these three variables is scarce, with particular gaps in studies of nursing professionals in this population. Objective: The study aimed to identify the prevalence of problematic phone use among young adults and the relationship between these three variables: problematic phone use, sleep disturbances, and difficulties with emotion regulation. The study will also investigate the potential of sleep disturbances to mediate the relationship between problematic phone use and difficulties with emotion regulation. Methods: Data was collected from participants aged 18 years or older through a self-administered, anonymous web survey. The web survey was disseminated via social media and used snowball sampling to collect responses from individuals from various regions. There were no investigators involved in data collection from any particular institution or to reduce researcher bias. A power analysis was performed to determine the ideal sample size; the results from the 167 participants exceeded the ideal sample size requirement. The Smartphone Addiction Scale–Short Version (SAS-SV), a sleep disruption score derived from the Pittsburgh Sleep Quality Index (PSQI), and the Difficulties in Emotion Regulation Scale–Short Form (DERS-SF) were used to collect data. Data were analyzed using descriptive and inferential statistics, including Cronbach’s alpha, Pearson correlations, independent-samples t tests, one-way ANOVA, multiple linear regression, and bootstrapped mediation (n = 5000 resamples). The CHERRIES guidelines were adhered to throughout the research study. Results: The participants were aged a mean of 21.6 years old (SD = 4.6). The majority of the participants (n = 117, 70.1%) identified as female. The internal consistency reliability for the SAS-SV and DERS-SF was high (SAS-SV α = 0.94; DERS-SF α = 0.88). Based upon the sex-specific cutoffs for the SAS-SV, a total of 63 participants (37.7%) screened positive for problematic phone use. There were significant positive correlations between problematic phone use and sleep disturbances (r = 0.41, p < 0.001) as well as problematic phone use and difficulties with emotion regulation (r = 0.54, p < 0.001). There was a significant positive correlation between sleep disturbances and difficulties with emotion regulation (r = 0.37, p < 0.001). The amount of time each individual spent on their smartphone on an average daily basis differed significantly across self-reported daily use bands (F_2,164 = 6.26, p = 0.002), with dependency highest among those reporting more than 5 h of daily use. There were no significant differences in this relationship based upon sex. Multiple linear regression analysis revealed that problematic phone use was a significant predictor of difficulties with emotion regulation (β = 0.47, p < 0.001); once the effects of problematic phone use were accounted for, sleep disturbances also significantly predicted difficulties with emotion regulation (β = 0.18, p = 0.01). In a complete-case analysis excluding 12 participants with uninterpretable sleep-duration data (n = 155), the bootstrapped indirect effect of sleep disturbances on the relationship between problematic phone use and difficulties with emotion regulation was statistically significant (ab = 0.081, 95% CI = 0.015 to 0.174, adjusting for age and sex); an earlier analysis that had scored these 12 cases as zero rather than excluding them found a smaller, non-significant indirect effect (ab = 0.060, 95% CI = −0.014 to 0.140). Conclusions: Problematic phone use is common among young adults today. The use of problematic phone behavior is positively associated with sleep disturbances and difficulties with emotion regulation. In a corrected complete-case analysis, sleep disturbances significantly mediated part of this relationship, though this cross-sectional association should not be interpreted as demonstrating a causal mechanism, and it should be weighed against a smaller, non-significant estimate obtained before this missing-data correction. These findings suggest that both problematic phone use and, cautiously, sleep health may be relevant targets for nursing-led digital-wellness interventions, though the effectiveness of such interventions would need to be established in prospective studies before implementation. Full article

Background/Objectives: Alginate hydrogels are widely used in tissue engineering; however, their reported properties vary significantly due to differences in formulations and processing conditions, which limits direct comparison across studies. This study aims to systematically evaluate the relative and combined effects of alginate viscosity grade, polymer concentration, and CaCl₂ crosslinking concentration on hydrogel structural, mechanical, and biological behaviour. Methods: Hydrogels were prepared using three commercially available alginates of low, medium, and high viscosity. Polymer concentration (0.5–2% w/v) and CaCl₂ concentration (2.5–10% w/v) were systematically varied under controlled fabrication conditions. Morphology was analysed using scanning electron microscopy, swelling and water uptake were quantified, mechanical properties were assessed via dynamic mechanical analysis, and cell viability was evaluated using Chinese hamster ovary (CHO) cells encapsulation over 20 days. Statistical analysis was performed using two-way ANOVA. Results: Hydrogel properties were governed by non-linear interactions between formulation parameters. CaCl₂ concentration was identified as the dominant factor influencing structural and biological outcomes, with increasing crosslinking concentration reducing pore size, swelling, and water uptake, and decreasing cell viability by up to ~60%. In contrast, polymer concentration and alginate viscosity grade primarily controlled mechanical behaviour, with increased polymer content and viscosity resulting in higher storage and Young’s moduli. Significant interaction effects confirmed that hydrogel properties are not independently tunable but depend on the combined influence of all parameters. Conclusions: Crosslinking concentration dominates structural and biological responses in alginate hydrogels, while polymer parameters modulate mechanical properties within this constraint. These findings establish a formulation-dependent trade-off between mechanical stiffness and cytocompatibility, providing a comparative framework for rational selection of alginate systems based on application-specific requirements. Full article

Background/Objectives: Circulating amino acids are not only markers of nutritional status; in experimental and interventional models they have been linked to hepatic lipogenesis, lipoprotein assembly, mitochondrial fatty acid oxidation, and bile acid conjugation, which makes them plausible candidate correlates of obesity-related lipid dysregulation. Despite this, most metabolomic studies of excess adiposity have focused either on a single lipid parameter—typically triglycerides—or only on branched-chain amino acids (BCAAs). This pilot study was designed to generate hypotheses about these associations across the full standard lipid panel using a targeted 19-amino acid liquid chromatography–tandem mass spectrometry (LC-MS/MS) panel in adults spanning the body mass index (BMI) spectrum, with an analytical framework oriented around lipid phenotype variance rather than body weight classification. The design is cross-sectional and the analysis exploratory; no causal or predictive claim is made. Methods: Targeted LC-MS/MS quantification of 19 plasma amino acids was performed in 50 adults grouped as normal weight (n = 20; BMI 22 ± 1.5 kg/m²), overweight (n = 20; BMI 28 ± 1.5 kg/m²), or obese (n = 10; BMI 34 ± 2.0 kg/m²). The analytical framework included: (i) one-way analysis of variance (ANOVA) with Bonferroni correction; (ii) Pearson correlation analysis; (iii) principal component analysis (PCA) performed on the lipid profile itself with amino acid projection vectors; (iv) K-means clustering based on lipid phenotype (K = 3); (v) Ward-linkage hierarchical clustering of the amino acid–lipid correlation matrix; (vi) Random Forest permutation importance for all four lipid outcomes; and (vii) composite lipid risk indices including atherogenic index (TG/HDL-C) and non-HDL cholesterol. Results: A distinct amino acid correlation pattern was observed for each of the four lipid fractions. Triglycerides (TG) correlated most strongly with glutamic acid (r = 0.58) and inversely with glutamine (r = −0.58). High-density lipoprotein cholesterol (HDL-C) correlated most strongly with glutamic acid (r = −0.61) and serine (r = 0.49). The strongest correlates of low-density lipoprotein cholesterol (LDL-C) were phenylalanine (r = 0.56) and leucine (r = 0.56), and those of total cholesterol (TC) were leucine (r = 0.63) and, inversely, glycine (r = −0.54). The atherogenic index (TG/HDL-C) increased 2.9-fold from normal to obese and was most strongly correlated with glutamic acid, isoleucine, and glycine. In the multivariable models the amino acid panel accounted for a modest share of the variance in TG (adjusted R² = 0.43; F(19,30) = 2.97, p = 0.004) and HDL-C (adjusted R² = 0.35; F(19,30) = 2.40, p = 0.016). For LDL-C and TC the adjusted R² values were close to zero (0.06 for both) and the overall models were not statistically significant (both p > 0.33); no interpretable amino acid signal was therefore present for these two fractions, and no predictors are reported for them. Lipid-based K-means clustering identified three lipid-phenotype clusters (Favorable, Intermediate, Adverse lipid profiles) with differences in amino acid z-scores. Conclusions: In this exploratory pilot cohort, lipid dysregulation in abnormal BMI was associated with two partially separable amino acid axes: a glutamic acid–glutamine axis (TG and partially HDL-C), and a glycine–serine putatively protective pattern opposing all atherogenic lipid parameters. These findings extend the established BCAA–insulin-resistance paradigm and suggest that targeted amino acid profiling—particularly for glutamic acid, leucine, glycine, and serine—may serve as a way of discovering candidate biomarkers for further study for dyslipidemia in individuals with abnormal BMI. Full article

Parents of infants in the Neonatal Intensive Care Unit (NICU) frequently experience significant emotional distress, yet neonatology fellows receive limited training in psychosocial support. This study evaluates the use of online standardized-patient simulation to improve fellows’ communication skills addressing parent concerns. Fellows (n = 13) completed two virtual interactions with standardized parents, with feedback from a neonatal mental health professional (NMHP), a former NICU parent, and a neonatologist using narrative comments and the Gap–Kalamazoo Communication Skills Assessment Scale. Narrative data underwent thematic analysis, and a within-subjects, repeated measures ANOVA examined communication ratings; knowledge and self-efficacy scores were analyzed using descriptive statistics and paired t-tests. Communication scores differed significantly across raters (F(2, 24) = 6.2, p < 0.007). Fellow and faculty ratings were comparable (p = 0.37), whereas parent ratings exceeded fellow self-ratings (p = 0.005). NMHPs and parents identified more thematic codes than fellows (22/26 and 25/26 vs. 15/26), highlighting information delivery, mental health, relationship building, and communication. Fellows’ self-efficacy decreased after participation, (t(12) = 2.88, p = 0.02, d = 0.83). This decline, alongside positive feedback on the simulation’s relevance, reflects increased recognition of the complexity of addressing parental distress and underscores the need for ongoing training and real-world application. This study provides preliminary evidence for the feasibility of using online simulation to train neonatology fellows in communication strategies that support the psychosocial needs of NICU parents. Full article

Climate change poses increasing risks not only to natural ecosystems but also to cultural heritage sites and the communities that depend on them. Climate literacy, encompassing knowledge, awareness, and decision-making capacity, is essential for strengthening local resilience and supporting effective climate adaptation. This study investigates climate literacy and perceptions of climate change across historic settlements with different conservation statuses and socio-cultural characteristics. Amasra, Mudurnu, and Taraklı were selected as case studies because of their distinctive historic urban identities and heritage values. A quantitative research design was adopted, and face-to-face surveys were conducted with 300 participants between 15 May and 15 June 2026 using a structured questionnaire consisting of a climate literacy scale and questions on climate change perceptions. The data were analyzed using descriptive statistics, one-way analysis of variance (ANOVA), and K-Means cluster analysis. The analysis revealed meaningful differences in climate literacy across the three historic settlements, while the cluster analysis further showed that participants could be grouped into low, moderate, and high levels of climate awareness. These patterns suggest that climate literacy is not shaped solely by individual knowledge, but is also closely related to the geographical, conservation, and socio-cultural contexts in which people live. The findings therefore point to the importance of place-based climate education and heritage-sensitive approaches to climate adaptation in historic settlements. Full article

Friction stir welding (FSW) is a solid-state joining process widely used for aluminum alloys due to its low heat input, reduced distortion, and ability to produce high-quality joints. However, excessive tool forces generated during the welding process can increase machine loading, accelerate tool wear, and negatively affect the process efficiency. Therefore, understanding the relationship between welding parameters, tool forces, and the joint performance is essential for achieving high-quality welds while avoiding unnecessary mechanical loads. In this study, 4 mm thick AA5754 aluminum alloy plates were joined using the FSW process, and the feasibility of using tool force measurements for process optimization was investigated. A comprehensive experimental matrix consisting of nine different rotational speeds and ten different tool travel speeds was established based on preliminary studies and previous literature. During each welding operation, forces acting on the tool in the F_x, F_y, and F_z directions were continuously recorded. The welded joints were evaluated through tensile testing (Zwick Z300 universal testing machine, ZwickRoell, Ulm, Germany), hardness measurements, and microstructural characterization using scanning electron microscopy (SEM) (ZEISS Merlin scanning electron microscope, Carl Zeiss Microscopy GmbH, Oberkochen, Jena, and Göttingen, Germany). A Pearson correlation analysis and a two-way analysis of variance (ANOVA) were performed at a 95% confidence level to quantify the relationships and statistical significance of the process parameters. The results showed that F_z was the dominant force component during welding. The rotational speed had a statistically significant effect on the tensile strength, yield strength and hardness (p < 0.05), accounting for 99.39% of the total variation in hardness. For the mean tool force, both the rotational speed and the tool travel speed were statistically significant (p < 0.0001), contributing 38.48% and 47.16% of the total variation, respectively. The rotational speed also accounted for 81.55% of the variation in the maximum axial force. The Pearson correlation analysis showed a strong negative correlation between the rotational speed and hardness (r = −0.73), whereas the tool travel speed showed positive correlations with F_x (r = 0.61), F_z (r = 0.62), and the mean tool force (r = 0.68). Despite the increased tool loading associated with higher travel speeds, no corresponding improvement in the mechanical performance was observed. The results demonstrated that appropriately selected welding conditions produced joints with a yield strength and hardness exceeding 90% of the corresponding base material properties while maintaining relatively lower tool forces. SEM observations confirmed grain refinement in the stir zone. Overall, the combined correlation and ANOVA results demonstrate that real-time tool force monitoring can provide a quantitative basis for selecting FSW parameters that achieve an adequate mechanical performance while minimizing unnecessary machine and tool loading. Full article

Introduction: Vitamin D status has been investigated as a modifiable risk factor with cognitive decline. However, studies pertaining to this remain inconsistent across populations, and there are fewer studies associating vitamin D status, cognitive decline, amyloid markers and oxidative stress markers in older adults. Therefore, this study was conducted to analyze the association between these parameters. Methodology: This cross-sectional study included 145 older adults aged between 51 and 80 years. Participants were categorized based on serum vitamin D levels into sufficient (n = 53), insufficient (n = 61), and deficient (n = 31) groups. Cognitive performance was assessed using the Modified Mini Mental State (3MS) test. Plasma levels of Aβ 1-40 and Aβ 1-42 and oxidative stress markers (TBARS, GPx, SOD) were measured. Statistical analysis was performed using ANOVA and Spearman’s correlation. Results: Results showed that the vitamin D concentrations did not differ significantly between cognitively impaired and normal individuals within vitamin D strata (vitamin D sufficient, insufficient and deficient groups). Plasma Aβ 1-40 levels were significantly elevated in cognitively impaired participants across all vitamin D groups. A reduced Aβ 1-42/Aβ 1-40 ratio was observed in sufficient and insufficient Vitamin D groups. Additionally, GPx levels were significantly higher in the vitamin D-deficient group. Correlation analysis showed that 3MS scores were negatively associated with age (r = −0.2607, p = 0.0015), Aβ 1-40 (r = −0.4016, p = 0.0001), and Aβ 1-42 (r = −0.3025, p = 0.0002), and positively correlated with Aβ 1-42/Aβ 1-40 ratio (r = 0.2176, p = 0.0086). Conclusions: These findings suggest that cognitive impairment in older adults is strongly associated with amyloid burden, oxidative stress, and age, whereas vitamin D status was not directly correlated with cognitive performance in this cohort. Full article

Background: Cholera remains a persistent and deadly global public health challenge. Recent resurgences have caused large-scale outbreaks. Due to gaps in public health risk awareness, effective risk communication using the HBM is now critical for cholera control and prevention. During the 2024 cholera outbreak, Lagos Island residents mainly relied on social media peers to exchange risk information. This study examined cholera risk perception among residents in the hotspot areas, established how the six HBM constructs were used in the cholera-related social media peer interactions, identified dominant cues to action in social media peer interactions, and established the association between exposure to peer-generated cholera messages and risk perception and the adoption of preventive behaviours. Methods: This is a cross-sectional study that combined a survey of social media users on Lagos Island and a quantitative content analysis of Facebook and X posts during the outbreak. A total of 350 Lagos Island residents were surveyed using a multi-stage cluster sampling strategy; 540 Facebook posts and 894 X tweets were content-analysed from a large corpus of data scraped from the platforms. Results: Findings showed high exposure to peer-generated cholera messages and cues to action on X and Facebook. HBM constructs appeared in varying proportions across platforms. ANOVA results and Games–Howell post-hoc comparisons showed a statistically significant difference in average engagement across the HBM constructs [p < 0.05]. Chi-square tests indicated a significant association between exposure to peer-generated cues to action and the adoption of cholera health behaviours [p < 0.05]. Conclusions: The study concluded that social media peer communication was significantly associated with residents’ understanding and perception of cholera risk during the outbreak. Health agencies should identify influential local voices on X and Facebook and assimilate them into public health communication strategies to strengthen the relevance, resonance, and effectiveness of digital health messages in outbreak contexts. Full article

This study investigated and optimized the operational process parameters of an extrusion-based 3D food printing system to maximize the dimensional fidelity of newly developed Wolffia globosa (duckweed) starch hydrogel constructs relative to a nominal target specification of 30 × 30 × 30 mm. Prior to parameter optimization, synchrotron X-ray tomographic microscopy (SR-XTM) was used to characterize Wolffia globosa particle size and dispersion within the starch matrix, showing that grinding eliminated large particle agglomerates (up to approximately 150 µm) and was necessary for smooth, continuous extrusion; the ground formulation was accordingly selected for all printing trials. A full factorial experimental configuration was executed to examine the synchronized effects of three core process parameters: print-head traverse speed (5–15 mm/s), extrusion speed (5–15 steps/mm), and layer height (1.9–3.7 mm). Experimental responses were evaluated via Three-Way Analysis of Variance (ANOVA) and Response Surface Methodology (RSM) using triplicate measurements (n = 3) at each of the 27 tested parameter combinations. Residual diagnostics indicated an approximately normal distribution for the height model (Shapiro–Wilk p = 0.716), whereas the width and length models showed some departure from normality (p < 0.01), consistent with the significant lack-of-fit detected for these two responses. Three-way ANOVA confirmed that print-head (nozzle) speed was the dominant factor governing the in-plane dimensions (width and length; partial η² ≈ 0.98), while height was jointly governed by all three factors, with layer height and print-head speed contributing the largest effects. With the statistical power afforded by replicate measurements, all two- and three-way interactions among the three factors were also statistically significant for width and length (p < 0.001), refining the single-replicate interaction pattern reported previously. Empirical second-order polynomial equations explained a substantial share of the variance in each dimension (R² = 0.70–0.85), although formal lack-of-fit testing indicated that higher-order interactions not captured by the quadratic terms remained statistically significant, and the equations should therefore be interpreted as descriptive rather than as precise predictive tools. Based on the triplicate means, a print-head speed of 5 mm/s, extrusion speed of 15 steps/mm, and a layer height of 1.9 mm minimized the mean cumulative absolute error to 4.01 mm, yielding a mean dimensional profile of 28.63 ± 0.78 mm width, 27.76 ± 0.96 mm length, and 30.41 ± 0.70 mm height (mean ± SD, n = 3). Full article

Background: Periodontitis is a chronic inflammatory disease characterized by dysregulated host immune responses that drive connective tissue destruction and alveolar bone loss. Human gingival fibroblasts (HGFs) are central regulators of periodontal inflammation through their production of cytokines, chemokines, matrix-remodeling enzymes, and other inflammatory mediators. Although cannabinoid receptor 2 (CB2) activation has demonstrated anti-inflammatory properties, its coordinated effects on multiple inflammatory pathways in gingival fibroblasts remain poorly understood. This study investigated the transcriptomic effects of the selective CB2 agonist HU-308 on IL-1β-induced inflammatory responses in HGFs. Methods: Primary HGFs were divided into untreated controls, IL-1β-stimulated cells (10 ng/mL), and IL-1β-stimulated cells treated with HU-308 (10 μM). Twenty-four hours after stimulation, transcriptome-wide expression profiling was performed using Affymetrix Human Clariom S microarrays, followed by targeted analysis of selected inflammation-related transcriptional domains. Selected transcripts were evaluated within predefined biological domains including cytokines, chemokines, extracellular matrix-associated genes, NO/cGMP-related genes, transporter-associated genes, and GPCR-related transcripts. Gene expression was analyzed using one-way ANOVA with Tukey’s post hoc test. Results: IL-1β induced a coordinated inflammatory transcriptional program characterized by increased expression of pro-inflammatory cytokines, chemokines, matrix metalloproteinases, glucose transporter genes, and multiple GPCR-related transcripts, while suppressing collagen-associated genes, NOS3, GPR4, and GPR78. HU-308 broadly attenuated these inflammatory responses by reducing the expression of cytokines, chemokines, matrix metalloproteinases, and several GPCR-related genes while restoring collagen-associated transcripts, nitric oxide signaling components, anti-inflammatory mediators, and selected glucose transporters toward basal levels. Schematic multidimensional visualizations were used to illustrate relative expression patterns among selected transcripts within each functional domain; these visualizations do not represent statistically derived gene networks or molecular interactions. Conclusions: Pharmacological modulation of CB2 by HU-308 exerts broad immunomodulatory effects in IL-1β-stimulated human gingival fibroblasts by coordinately regulating multiple transcriptional networks involved in periodontal inflammation. These findings demonstrate that HU-308 treatment is associated with coordinated modulation of inflammatory, extracellular matrix, nitric oxide, metabolic, and GPCR-associated transcriptional pathways in IL-1β-stimulated HGFs. The results support the hypothesis that CB2 signaling may participate in the broader regulation of these interconnected responses; however, receptor-specific studies using CB2 antagonism or CNR2 knockdown are required to establish causality. Full article

The widespread deployment of Internet of Things (IoT) devices has expanded the attack surface of modern networks, making IoT botnets a persistent cybersecurity threat. Although machine learning-based intrusion detection systems (IDSs) have demonstrated promising detection capability, their performance is often hindered by redundant high-dimensional features and limited model interpretability. This study presents an explainability-guided feature selection framework that employs SHAP values derived from an XGBoost model to rank features and systematically compares its effectiveness with Mutual Information (MI), Analysis of Variance (ANOVA), and Principal Component Analysis (PCA) across nine machine learning classifiers using the N-BaIoT dataset. Experimental results indicate that LightGBM with SHAP-selected features achieves an accuracy of 0.9994 using only the top 10 features. Among the evaluated feature selection methods, SHAP achieves the highest classification performance on seven of the nine classifiers, while Wilcoxon signed-rank tests indicate a statistically significant difference between SHAP and ANOVA (p = 3.03 × 10⁻⁵); the difference between SHAP and MI is significant at the conventional threshold (p = 2.86 × 10⁻²) but does not remain significant after Bonferroni correction for multiple comparisons. Furthermore, SHAP-based analysis reveals distinct traffic statistical signatures between the Mirai and Gafgyt botnet families, offering actionable insights for explainability-aware IoT intrusion detection. The proposed framework provides a practical solution for balancing detection performance and model interpretability in IoT botnet detection. Full article

The increasing integration of AI in education imposes the need to examine the competencies of teachers for its pedagogically meaningful, safe, and responsible application. The goal of this research was to examine the self-assessments of teachers’ AI-related competencies, as well as to determine whether there were statistically significant differences regarding the subject area and years of teaching experience. The research was conducted on a sample of 165 primary and secondary school teachers in the Republic of Serbia. Data were collected using the Serbian-language version of the original Teacher Artificial Intelligence Competence Self-Efficacy (TAICS) Scale. The reliability and factor structure of the instrument were checked using Cronbach’s alpha coefficient, Kaiser–Meyer–Olkin (KMO) indicator, Bartlett’s test of sphericity, and exploratory factor analysis using principal axis factoring with Varimax rotation, while one-way analysis of variance (ANOVA) was used to examine differences. The results showed high internal consistency of the scale (Cronbach’s α = 0.972) and an interpretable three-factor solution explaining 71.202% of the total variance. The following factors were extracted: pedagogical–evaluative AI competencies, ethical–safety AI competencies, and operational–technical AI competencies. No statistically significant differences in pedagogical–evaluative or ethical–safety AI competencies were found according to subject area or years of teaching experience. For operational–technical AI competencies, an unadjusted difference was observed according to teaching experience; however, this finding did not remain statistically significant after the Bonferroni correction for multiple testing. These findings should be interpreted as preliminary and require replication in larger and more representative samples. The findings indicate that the competencies of teachers for artificial intelligence should be viewed as a multidimensional basis for further research, improvement of teaching practice, and planning of professional development in the field of application of AI in education. Full article

Background: Evidence regarding the longitudinal use of infrared thermography in elite under-18 soccer players remains limited. Most previous studies have relied on cross-sectional designs or short observation periods. Methods: This prospective longitudinal observational study monitored 18 elite under-18 male outfield soccer players across 16 official matches (96 valid assessments). Thermographic evaluations were performed 48 h post-match under standardized conditions across six bilateral lower-limb regions. A thermal asymmetry was defined as relevant if ΔTsk ≥ 0.5 °C. Linear mixed-effects models, paired t-tests and chi-square tests were used for statistical analysis. Results: Relevant asymmetries were detected in 79.2% of assessments (mean maximum ΔTsk 0.77 ± 0.43 °C). Posterior Thigh BF (40.6%) and Posterior Thigh ST (35.4%) showed the highest prevalence (χ² = 16.31, p = 0.006). Significant side-to-side differences were found for Anterior Thigh (p = 0.004), Adductor (p = 0.039) and Posterior Thigh BF (p = 0.032). The intraclass correlation coefficient for Thermal Asymmetry Burden was very low (ICC = 0.024). Fifteen athletes (83.3%) showed recurrent asymmetry and 13 (72.2%) showed a recurrent same-region pattern. Match-to-match variation in TAB was significant (Kruskal–Wallis p = 0.025; ANOVA p = 0.011). No time-loss muscle injuries occurred. Conclusions: Post-match thermal asymmetries are highly prevalent in elite youth soccer and appear to reflect dynamic, load-dependent recovery responses rather than stable thermal phenotypes. Longitudinal thermographic monitoring may help characterise individual recovery patterns when interpreted alongside other monitoring tools. Full article

This study evaluates the green synthesis of iron nanoparticles (Fe-NPs) using agricultural waste extracts and their application for modifying natural zeolite from Chihuahua (Mexico) to remove ciprofloxacin (CPX) from aqueous media. The approach provides an environmentally friendly alternative to conventional nanoparticle synthesis by employing biomass-derived reducing agents. The natural and Fe-NP-modified zeolites were characterized by FTIR, EDX, and XRD. CPX adsorption was evaluated through kinetic and equilibrium isotherm experiments, supported by comprehensive statistical analyses, including correlation coefficients (R), ANOVA and statistical evaluation of model parameters. Langmuir modeling yielded maximum adsorption capacities (q_max) of 19.11 mg g⁻¹ for natural zeolite and 22.99 mg g⁻¹ for Fe-NP-modified zeolite, representing an approximately 20.3% higher model-estimated capacity after Fe modification. However, the overlapping confidence intervals indicate that this increase should be interpreted cautiously. Isotherm analysis showed that both the Langmuir and Freundlich models adequately described CPX adsorption, while statistical criteria indicated a better fit of the Freundlich model for the Fe-modified zeolite, consistent with a more heterogeneous adsorption surface. Overall, Fe-NP modification appears to alter the adsorption capacity and energetic characteristics of zeolite rather than simply producing a large increase in experimentally observed uptake. These findings highlight the potential of green Fe-NP-modified zeolites as tunable, low-cost materials for antibiotic removal from water. Full article

Three-dimensionally (3D)-printed denture teeth are increasingly used in clinical practice; however, their wear resistance and surface hardness may be insufficient for long-term clinical application. Moreover, the effect of post-treatment under elevated temperature and pressure on these properties remains unclear. This study aimed to evaluate the effect of such post-treatment on the wear resistance and Vickers hardness of 3D-printed denture teeth resin. One hundred disk-shaped specimens (10 × 2 mm) were 3D-printed using Dima denture teeth resin and randomly assigned to four post-treatment groups (121 °C at 2 bar for 4, 30, 60, and 90 min) and one untreated control group. Within each group, specimens were allocated for wear resistance (n = 10) and Vickers hardness (n = 10) testing. Wear resistance was measured using an impact-sliding wear testing machine in a polymethyl methacrylate slurry, while Vickers hardness was measured using a hardness tester under a 50 g load with a 15 s dwell time. Statistical analyses included one-way analysis of variance (ANOVA), Kruskal–Wallis, and Welch’s ANOVA (α = 0.05). All post-treatment groups exhibited significantly lower depth loss and higher hardness than the control group (p < 0.05). Specimens post-treated for ≥30 min exhibited significantly lower volume loss than the control group (p < 0.05). The 121 °C/90 min group demonstrated the highest wear resistance and Vickers hardness. Within the limitations of this study, post-treatment under elevated temperature and pressure significantly improved the wear resistance and Vickers hardness of the tested 3D-printed denture teeth resin, with the 90 min protocol yielding the greatest enhancement. Thus, thermal-pressure post-treatment may be a promising approach for enhancing the mechanical performance of additively manufactured denture teeth. Full article