Search Results (9,582)

This study examines the influence of layer thickness (0.9, 1.6, 2.4, and 4 mm) on the distribution of residual stress, microstructural evolution, and tensile properties of Cu18150/Al1060/Cu18150 multilayered composites fabricated via a combined cast-rolling and hot-rolling technique. The grain refinement, dislocation density, and residual stress gradients across the interfaces were characterized and analyzed using integrated electron backscatter diffraction and kernel average misorientation mapping. The results demonstrated that specimens with a lower layer thickness (0.9–1.6 mm) possess a significantly improved tensile strength of 351 MPa, which is mainly due to the significant grain refinement and the presence of compressive residual stresses at the region of the Al/Cu interfaces. However, tensile strength decreased to 261 MPa in specimens with thicker layers (4 mm), accompanied by improved ductility, e.g., elongation of 30%. This is associated with a reduction in the degrees of interfacial constraint and the formation of more homogeneous deformation structures that accommodate a larger strain. The intermediate layer thickness of 2.4 mm offers an optimal compromise, achieving a tensile strength of 317 MPa while maintaining balanced mechanical performance. These results emphasize the importance of layer thickness in controlling such stress profiles and optimizing the mechanical behavior of hybrid metal composites, providing useful guidance on the design and fabrication of superior structural-form materials. Full article

Background/Objectives: This study investigated how phase-specific dietary strategies and weight regulation influence gut microbiota composition and diversity in competitive weightlifters. Particular emphasis was placed on integrating energy intake, macronutrient clustering, and weight fluctuations across distinct training phases. Methods: Thirteen competitive weightlifters were recruited, with 10–12 contributing complete data per phase. Fecal and dietary samples were collected during the preparation, competition, and transition phases. Gut microbiota was profiled via 16S rRNA gene sequencing, and alpha/beta diversity was analyzed using QIIME2. K-means clustering based on caloric/macronutrient intake identified dietary patterns. Taxonomic differences were assessed using DESeq2, and microbial structures were compared across training phases, weight classes, and weight-change categories. Results: Overall phylum- and genus-level profiles and diversity indices remained stable across training phases, indicating community-level resilience. However, specific genera varied with dietary and physiological factors. Enterococcus was higher during the preparation phase, whereas Lactobacillus was enriched during the competition and transition phases as well as in the high-calorie cluster. Lightweight and heavyweight athletes also showed distinct microbial structures, and pre- and post-competition weight changes were associated with shifts in selected taxa. Notably, the low-calorie group exhibited higher Shannon diversity than the high-calorie group (p = 0.0058), with Lactobacillus dominance contributing to reduced evenness in high-energy diets. Conclusions: Despite overall microbial stability, dietary energy availability and body-weight regulation modulated specific taxa relevant to performance and recovery. By integrating dietary clustering, weight-class comparison, and pre- and post-competition weight changes, this study provides novel insight into the microbiota of resistance-trained athletes, a population underrepresented in previous research. Despite the modest sample size and single-season scope, this study offers new evidence linking dietary strategies, weight regulation, and gut microbiota in weightlifters, and highlights the need for validation in broader cohorts. Full article

Silver nanoparticles (AgNPs) have attracted significant attention in recent years in diverse fields owing to their broad mechanisms of action. In particular, the wound healing process has become one of the main fields where the therapeutic potential of AgNPs is highlighted. AgNPs can be used as monotherapy or incorporated into composite structures in various formulations such as nanogels, hydrogels, powders, ointments, and sprays, for the treatment of a wide range of wound types including burns, excisional and incisional wounds, bone defects, surgical wounds, and diabetic ulcers. This widespread use is attributed to the strong antibacterial, anti-inflammatory, antioxidant, and cell proliferation-promoting biological properties of AgNPs. Moreover, AgNPs exhibit synergistic effects when combined with conventional antibiotics, enhancing their efficiency against resistant bacterial strains or even restoring the lost antibacterial activity. These biological properties enable AgNPs to reduce infection risk while simultaneously promoting high-quality healing by accelerating tissue regeneration. The therapeutic effectiveness of AgNPs is influenced by their physicochemical properties, including particle size, shape, and surface chemistry. In particular, synthesis methods play a significant role in determining both the biological activity and the safety profile of AgNPs. Among various methods, green synthesis approaches stand out for enabling the production of environmentally friendly, non-toxic, and highly biocompatible AgNPs. In this review, the mechanisms of action of AgNPs in wound healing are examined in detail, and recent scientific developments in this field are evaluated based on current in vitro, in vivo, and clinical studies. Full article

This study evaluates the feasibility of employing rainwater as an alternative feedstock for hydrogen production via electrolysis. While conventional systems typically rely on high-purity water—such as deionized or distilled variants—these can be cost-prohibitive and environmentally intensive. Rainwater, being naturally available and minimally treated, presents a potential sustainable alternative. In this work, a series of comparative experiments was conducted using a proton exchange membrane electrolyzer system operating with both deionized water and rainwater collected from different Austrian locations. The chemical composition of rainwater samples was assessed through inductively coupled plasma, ion chromatography and visual rapid tests to identify impurities and ionic profiles. The electrolyzer’s performance was evaluated under equivalent operating conditions. Results indicate that rainwater, in some cases, yielded comparable or marginally superior efficiency compared to deionized water, attributed to its inherent ionic content. The study also examines the operational risks linked to trace contaminants and explores possible strategies for their mitigation. Full article

High-mountain microalgae exhibit remarkable adaptability to extreme environments, making them promising candidates for sustainable biorefineries. We evaluated how photoperiod (12:12, 18:6, 24:0 h) and LED spectra (cool white, full spectrum, red–blue 4:1) affect growth and metabolite formation in Chlorella sp. UFPS019 and Scenedesmus sp. UFPS021. Biomass peaked in Chlorella under red–blue 18:6 (≈1.8 g L⁻¹) and in Scenedesmus under red–blue 24:0 (≈1.7 g L⁻¹), revealing species-specific responses. Carbohydrate fractions were maximized under red–blue 12:12 in both species, and continuous light (24:0) depressed carbohydrate content—most notably under full spectrum. Protein content was highest under red–blue 18:6 in Chlorella sp. and under red–blue 12:12–18:6 in Scenedesmus sp. Lipid fractions increased with light duration, peaking under red–blue 18:6–24:0 in Chlorella and under red–blue 18:6–24:0—with Cool White 24:0 also high—in Scenedesmus sp. Although extended illumination favored lipids, intermediate photoperiods (12:12–18:6) provided better productivity-to-energy trade-offs and broader metabolic profiles. These results show that tuning spectral composition and photoperiod to species-specific physiology enables the targeted, energy-aware production of proteins, carbohydrates, or lipids; red–blue at intermediate durations is a robust, energy-efficient regime, whereas longer exposures can be used strategically when lipid enrichment is prioritized. Full article

Consumers increasingly seek clean-label meat products with improved nutrition and stability. We evaluated a collagen hydrolysate–cranberry mixture (CH-CR) as a functional additive in cooked sausages. Two formulations—control and CH-CR—were assessed for fatty acid profile; lipid and protein oxidation during storage; antioxidant capacity ferric-reducing antioxidant power (FRAP), 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging, and half-maximal inhibitory concentration (IC50); amino acid composition; and instrumental color. Relative to the control, CH-CR produced a more favorable lipid profile: lower saturated fatty acids (SFAs) 23.9% vs. 28.0%, higher monounsaturated fatty acids (MUFAs) 53.2% vs. 49.3%, slightly higher polyunsaturated fatty acids (PUFAs) 23.3% vs. 22.7%, a higher PUFA/SFA ratio of 0.97 vs. 0.81, and a lower omega-6/omega-3 (n-6/n-3) ratio of 13.5 vs. 27.1, driven by higher alpha-linolenic acid (ALA) 1.6% vs. 0.8%, with trans fats <0.1%. Storage studies showed attenuated oxidation in CH-CR: lower peroxide value (PV) at day 10 8.1 ± 0.4 vs. 9.8 ± 0.5 meq/kg and lower thiobarbituric acid-reactive substances (TBARS) at day 6 0.042 ± 0.004 vs. 0.055 ± 0.006 mg MDA/kg and day 10 0.156 ± 0.016 vs. 0.590 ± 0.041 mg MDA/kg); the acid value at day 10 was similar. Antioxidant capacity increased with CH-CR FRAP 30.5 mg gallic acid equivalents (GAE)/g vs. not detected; DPPH inhibition was 29.88% vs. 10.23%; IC50 56.22 vs. 149.51 µg/mL. The amino acid profile reflected collagen incorporation—higher glycine+proline+hydroxyproline 2.37 vs. 1.38 g/100 g and a modest rise in indispensable amino acids (IAAs) 5.72 vs. 5.42 g/100 g, increasing the IAA/total amino acid (TAA) ratio to 0.411 vs. 0.380. CH-CR samples were lighter and retained redness better under light, with comparable overall color stability. Overall, CH-CR is a natural strategy to improve fatty acid quality and oxidative/color stability in sausages. Full article

Background/Objectives: The search for new bioactive molecules increasingly extends beyond conventional medicinal plants, highlighting the importance of exploring alternative botanical sources. Parasitic plants represent a promising but underexploited reservoir of pharmacologically relevant compounds. Cuscuta australis (CA), a parasitic species with a history of traditional use, remains poorly characterized. This study aimed to investigate its phytochemical composition and evaluate its antioxidant, anti-inflammatory, and hepatoprotective properties. Methods: The phytochemical profile of CA extract was characterized by LC-MS. Antioxidant capacity was assessed using DPPH and ABTS assays. In vivo hepatoprotection was evaluated in male rats subjected to CCl₄-induced hepatotoxicity and treated orally with CA (30 or 60 mg/kg body weight). Biochemical, lipid, oxidative stress, and histological parameters were determined. Molecular docking was conducted to predict the binding of major identified compounds against selected protein targets. Results: CA significantly and dose-dependently improved biochemical and histological markers. At 60 mg/kg, ALT, AST, ALP, and bilirubin were reduced by 32%, 33%, 63%, and 51%, respectively. Lipid metabolism was improved by decreased TC, TG, and LDL-C with increased HDL-C. Antioxidant defense was enhanced through elevated CAT, SOD, and GPx activities, accompanied by reduced MDA levels. TNF-α and IL-6 decreased by 48% and 53%, respectively. Histopathology confirmed hepatoprotection and reduced fibrosis. Docking studies revealed strong binding affinities (−7.07 to −19.20 kcal/mol) for several metabolites, notably quercetin glucoside, diosmetin glucoside, caffeic acid glucoside, feruloylquinic acid, and isorhamnetin glucoside, against CYP450, IL-2, TNF-α, and IL-6. Conclusions: These findings demonstrate that C. australis is a promising source of bioactive compounds with hepatoprotective, antioxidant, antihyperlipidemic, and anti-inflammatory effects, supporting its potential as a natural therapeutic agent. Full article

Background: Eleutherococcus senticosus (Rupr. et Maxim.) Maxim., widely used in Russian and Chinese traditional medicine for its anti-inflammatory activity, contains bioactive compounds capable of stabilizing epithelial function and reducing inflammation. Despite prior research on its effects in the colon, the impact and mechanism of action of E. senticosus fruit extract on epithelial tissues of the upper digestive and respiratory tract remains unexplored. Objectives: This study aimed to evaluate the influence of E. senticosus fruit extract on the transepithelial electrical potential and resistance in the tracheal and small intestinal epithelium of rabbits. In addition, the chemical composition of the extract was also profiled by the means of UHPLC-DAD-MS. Methods: Tissue segments from the trachea and small intestine of New Zealand white male rabbits were examined using the Ussing chamber technique. Three concentrations of E. senticosus fruit extract (0.001, 0.1, 10 mg/100 mL) were applied, and changes in transepithelial electrical potential (dPD) and resistance (R) were recorded. Chemical analysis of the extract was conducted using UHPLC-DAD-MS. Results: For the first time, we have discovered that the E. senticosus extract increased membrane resistance in tracheal tissue, suggesting enhanced barrier integrity. In contrast, a slight decrease in resistance was observed in small intestinal tissue. UHPLC-DAD-MS confirmed the presence of chlorogenic acid, dicaffeoylquinic acids, quercetin derivatives, and myo-inositol, compounds known for their antioxidant, anti-inflammatory, and membrane-stabilizing effects. Conclusions: The differential response of respiratory and intestinal epithelium to the E. senticosus extract highlights its tissue-specific action and supports its traditional use in the prevention and treatment of diseases characterized by epithelial barrier dysfunction, such as asthma, COPD, and Crohn’s disease. Full article

This study examined the impact of five grapevine rootstocks (R110, 140Ru, 3309C, 41B, and FERCAL) on must composition, nitrogen status, and sensory attributes of Vitis vinifera L. cv. Assyrtiko wines. Vines were grown under uniform vineyard conditions, and microvinifications were conducted consistently across treatments. Rootstock genotype significantly influenced Baumé, density, titratable acidity, pH, and yeast-assimilable nitrogen (YAN). Musts from R110 contained the highest YAN (226.80 ± 0.99 mg/L) and intermediate Baumé (12.5°), whereas 140Ru exhibited the lowest YAN (132.60 ± 0.46 mg/L) and Baumé (11.7°). Wines from R110 contained the highest tannin concentration (0.375 g/L), while FERCAL produced the highest ethanol content (13.1% vol). Sensory evaluation revealed significant rootstock effects on color intensity, aroma intensity, aroma complexity, balance, and overall quality, with R110 and 3309C receiving the highest scores. The findings demonstrate that rootstock selection may affect the chemical and sensory profile of Assyrtiko wines, providing a practical tool for optimizing wine style and quality across diverse viticultural environments. Further research is needed to confirm these findings and explore extra parameters and novel rootstock–scion interactions. Full article

Sex differences are known to influence both micronutrient metabolism and cardiometabolic health outcomes. However, the extent to which these sex-specific factors interact, particularly in the relationship between micronutrient status and cardiometabolic risk, remains insufficiently understood. The present study aimed to investigate sex differences in health and micronutrient status, and their association with blood lipids, body mass index, and body weight. The final sample size included 488 Austrian adults (median age: 38 years; comprising 256 males and 232 females) who successfully met the inclusion criteria. Blood analyses were conducted to measure whole-blood micronutrients and serum levels of various cardiometabolic health biomarkers, including blood lipids. Micronutrient status (including deficiencies and excesses) was calculated using sex-specific reference ranges. There were significant differences between males and females for most (19 out of 28) blood biomarkers of cardiometabolic health (p < 0.05), with females generally showing a healthier cardiometabolic profile. Significant sex differences were also observed in the adjusted values of three micronutrients: copper was higher in females, while iron and vitamin B₁₂ were higher in males (p < 0.05). Sex differences in micronutrient status indicated a higher prevalence of iron deficiency and copper excess among females (p < 0.05). Different patterns were observed between males and females in the association of blood lipids and body composition with micronutrients and demographic factors. These findings highlight the importance of individualized approaches in preventive and therapeutic health interventions based on differences between males and females. Full article

Phenolic compounds are key contributors to the bioactivity and antioxidant potential of honey, yet reliable indicators for rapid quality assessment remain limited. This study characterized phenolic profiles in 44 mono-floral and poly-floral honey samples from 11 Albanian regions using LC–MS/MS method. Total phenolic content ranged from 29.8 to 171 mg·kg⁻¹, with flavonoids accounting for 6.1–56.4% of total phenolics. Gallic acid was the dominant phenolic compound (5.5–127 mg·kg⁻¹), which is strongly correlated with the total content of polyphenols (r = 0.863, p < 0.001). Analysis of variance (ANOVA) confirmed significant differences in phenolic and flavonoid levels across geographic zones and floral types, with mono-floral honeys consistently exhibiting higher bioactive parameters. These findings demonstrate that gallic acid may serve as a practical biochemical marker for estimating antioxidant potential in honey. This insight has implications for authenticity verification and quality control, particularly in regions like Albania where diverse floral sources contribute to honey variability. By linking phenolic composition to antioxidant potential, this study supports the broader application of phenolic markers for the standardization and valorization of honey as a functional food. Full article

Background: Amlodipine besylate (AML) is recognized as a calcium channel blocker curative for hypertension. However, the drug emerged recently as an antibacterial cure that competently prevails over resistant strains. Methods: Incorporating amlodipine into zein nanoparticles was employed to innovate a suitable carrier for loading and targeting deep corneal infection. The Box–Behnken design was adopted to produce various formulations of amlodipine-loaded zein nanoparticles (AML-ZNs) with diversity in composition concentration (% w/v), comprising zein, Labrafac, and poloxamer 407. Results: Relying on the optimization criterion, the chosen preference formulation concentration (% w/v) consists of 2.068 for zein, 0.75 for Labrafac, and 1.0 for Poloxamer. Morphological micrography of AML-ZNs showed regular spherical particles in the nanometric scale, and physicochemical characterization procedures confirmed system suitability. While tracking eyedrop optimum features, sodium alginate was selected for coating nanoparticles to improve stability and system viscosity. Both pH and sterility were also considered and maintained. Comparative studies were conducted pre- and post-coating, and the assessed features for the final selected formulation were 349.9 ± 5.8 nm, 0.2186 ± 0.0271, −55.45 ± 1.84 mV, 81.293 ± 0.9%, and 19.3 ± 0.19 cp for size, PDI, surface charge, entrapment, and viscosity, respectively. The AML-ZNs-Alg formulation demonstrates a more controlled pattern of release of roughly 40% of the drug released after 48 h, while the permeation profile shows 37 ± 3.52% permeated after 24 h, confirmed visually. In vitro microbial assay alongside the corneal in vivo microbial and histological pathology evaluation proved the efficacy of amlodipine as an antibacterial agent. Conclusions: These findings highlighted that the prepared AML-ZNs-Alg eyedrop can be a promising system as an antibacterial therapy. Full article

Understanding the intricate relationship between composition, processing conditions, and material properties is essential for optimizing Cu-based alloys. Machine learning offers a powerful tool for decoding these complex interactions, enabling more efficient alloy design. This work introduces a comprehensive machine learning framework aimed at accurately predicting key properties such as hardness and electrical conductivity of low-alloyed Cu-based alloys. By integrating various input parameters, including chemical composition and thermo-mechanical processing parameters, the study develops and validates multiple machine learning models, including Multi-Layer Perceptron with Production-Aware Deep Architecture (MLP-PADA), Deep Feedforward Network with Multi-Regularization Framework (DFF-MRF), Feedforward Network with Self-Adaptive Optimization (FFN-SAO), and Feedforward Network with Materials Mapping (FFN-TMM). On a held-out test set, DFF-MRF achieved the best generalization (R²_test = 0.9066; RMSE_test = 5.3644), followed by MLP-PADA (R²_test = 0.8953; RMSE_test = 5.7080) and FFN-TMM (R²_test = 0.8914; RMSE_test = 5.8126), with FFN-SAO slightly lower (R²_test = 0.8709). Additionally, a computational performance analysis was conducted to evaluate inference time, memory usage, energy consumption, and batch scalability across all models. Feature importance analysis was conducted, revealing that aging temperature, Cr, and aging duration were the most influential factors for hardness. In contrast, aging duration, aging temperature, solution treatment temperature, and Cu played key roles in electrical conductivity. The results demonstrate the effectiveness of these advanced machine learning models in predicting critical material properties, offering insightful advancements for materials science research. This study introduces the first controlled, statistically validated, multi-model benchmark that integrates composition and thermo-mechanical processing with deployment-grade profiling for property prediction of low-alloyed Cu alloys. Full article

Oxidative stress plays a critical role in the development of various chronic diseases, leading to major health problems worldwide. There has been increasing interest in using natural antioxidants as complementary agents for maintaining redox homeostasis and assuring a healthy lifestyle. This study aimed to systematically screen the antioxidant potential and cytotoxicity profiles of 19 plant-derived extracts using both a cell-free Fenton reaction-based assay and human monocytic THP-1 cells in vitro. The radical-scavenging capacity varied markedly among the extracts, with Acalypha virginica Linnaeus (ACALYPHA), Acorus calamus Linnaeus (ACORUS), Actinidia deliciosa (A.Chev.) C.F. Liang & A.R. Ferguson (ACTINIDIA), and Heuchera sanguinea Pursh (HEUCHERA) demonstrating strong activity in the chemical assay. In the cellular model, 15 extracts significantly reduced intracellular reactive oxygen species (ROS) levels without inducing cytotoxicity at effective concentrations. Notably, Acalypha virginica Linnaeus (ACALYPHA), Actinidia deliciosa (A.Chev.) C.F. Liang & A.R. Ferguson (ACTINIDIA), Dianthus superbus Linnaeus subsp. superbus (DIANTHUS), Succisa pratensis Moench (SUCCISA), and Typha laxmannii Lepech (TYPHA) exhibited consistent antioxidant efficacy across multiple doses. At higher concentrations, all extracts triggered apoptosis and/or necrosis, emphasizing the importance of defining safe ranges. These findings provide a comprehensive comparative analysis of Mediterranean plant-based natural antioxidants obtained by an in vitro approach. The selected plant extracts could be considered as promising candidates for the development of strategies targeting oxidative stress-related disorders. Further investigations considering the specific phytochemical composition of each extract and in vivo validation are needed to confirm their efficacy and safety. Full article

Wastewater treatment plants (WWTPs) function as engineered ecosystems in which microbial consortia mediate nutrient cycling, xenobiotic degradation, and heavy metal detoxification. This review discusses a forward-looking roadmap that integrates microbial ecology, multi-omics diagnostics, and artificial intelligence (AI) for next-generation treatments. Meta-analyses suggest that a globally conserved core microbiome indicates sludge functions, with high predictive value for treatment stability. Multi-omics approaches, including metagenomics, metatranscriptomics, and environmental DNA (eDNA) profiling, have integrated microbial composition with greenhouse gas (GHG) emissions, showing that WWTPs contribute 2–5% of anthropogenic nitrous oxide (N₂O) emissions. Emerging AI-enhanced eDNA models have achieved >90% predictive accuracy for effluent quality and antibiotic resistance gene (ARG) prevalence, facilitating near-real-time monitoring and adaptive control of effluent quality. Key advances include microbial strategies for degrading organic pollutants, pesticides, and heavy metals and monitoring industrial effluents. This review highlights both translational opportunities, including engineered microbial consortia, AI-driven digital twins and molecular indices, and persistent barriers, including ARG dissemination, resilience under environmental stress and regulatory integration. Future WWTPs are envisioned as adaptive, climate-conscious biorefineries that recover resources, mitigate ecological risks, and reduce their carbon footprint. Full article