Search Results (55,027)

Tumor-associated macrophages (TAMs) are pivotal in shaping the immunosuppressive tumor microenvironment (TME). Reprogramming TAMs towards an anti-tumor M1 phenotype represents a promising strategy to enhance anti-tumor immunity. While Fe₃O₄ nanoparticles (NPs) possess immunomodulatory potential, the influence of NP size on macrophage polarization and the underlying mechanisms remain unclear. This study aims to systematically investigate the size-dependent immunomodulatory effects of Fe₃O₄ NPs and elucidate their mechanisms. We synthesized a series of Fe₃O₄ NPs of controlled sizes (5 nm, 10 nm, 30 nm, and 100 nm) via the polyol method. Among these, the 10 nm NPs demonstrated superior cellular uptake efficiency in macrophages. This enhanced uptake induced a significant increase in intracellular reactive oxygen species (ROS) levels. Subsequently, the elevated ROS activated the NF-κB signaling pathway, promoting M1 macrophage polarization. This polarization was evidenced by enhanced CD86 expression, increased nitric oxide (NO) release, and elevated secretion of pro-inflammatory cytokines. This study identifies 10 nm as the optimal size for Fe₃O₄ NPs to elicit their maximal immunomodulatory effects. Our findings establish a crucial size-design principle for the rational development of nano-immunotherapeutic agents and identify 10 nm Fe₃O₄ NPs as a promising candidate for TAM-targeted cancer therapy. Full article

Tendinopathy involves a dysregulated inflammatory microenvironment in which cytokines, growth factors (GF) and extracellular matrix components interact dynamically. Platelet-rich plasma (PRP) is widely used as a regenerative therapy, but its mechanisms of action in inflamed tendon remain unclear. This study evaluated whether platelet-rich gel supernatant (PRGS) reprograms the inflammatory–anabolic mediator network in an equine in vitro tendon explant system stimulated with lipopolysaccharide (LPS). Tendon explants were cultured under six experimental conditions, including non-stimulated control, LPS-stimulated control, and LPS combined with 25% or 50% PRGS or platelet-poor gel supernatant (PPGS). Cytokines, GF, and hyaluronic acid (HA) were quantified at 1 h and 48 h and analyzed using linear mixed-effects models, mediator ratios, correlation networks, and principal component analysis. PRGS contained higher concentrations of PDGF-BB (2044 pg/mL, 95% CI 1382–2706) and IL-1ra (1196 pg/mL, 95% CI 424–1967) compared with PPGS. In LPS-stimulated explants, PRGS significantly increased IL-1ra and PDGF-BB, while IL-1β and HA exhibited significant time-dependent changes (F = 8.675 and F = 10.752, respectively). The PDGF-BB:HA ratio remained consistently higher in PRGS-treated groups (F = 46.100, p < 0.001). Multivariate analysis showed that the first two principal components explained 62% of the total variance and revealed coordinated shifts in mediator organization over time. These findings indicate that PRGS does not simply suppress inflammation but actively reprograms the tendon microenvironment toward a regulatory and reparative phenotype within this experimental system. Full article

Soil organic carbon (SOC) storage in forests is governed by complex interactions between site conditions and vegetation. This study quantifies SOC stocks across a gradient of Target Management Sets (TMS) in the Czech Republic (Central Europe) to evaluate the baseline storage capacity of distinct ecological sites and the modifying effects of dominant tree species, specifically Norway spruce and European beech. Utilizing large-scale spatial data, linear mixed-effects models, and piecewise structural equation modeling (pSEM), we analyzed SOC stratification across middle (≈400–600 m a.s.l.) and higher (≈600–800 m a.s.l.) elevational zones. The results indicate that while overall SOC stocks inherently increase with elevation due to climatic constraints, tree species dictate the vertical carbon distribution within the soil profile. Specifically, conifers (i.e., Norway spruce and Scots pine) accumulate SOC primarily in the organic layer, whereas broadleaves (mainly European beech and oak) translocate and stabilize carbon in deeper mineral horizons. The pSEM analysis revealed that beech functions as a ‘calcium pump’, increasing topsoil pH and driving calcium-mediated SOC stabilization in mineral soils. This mechanism is highly effective at middle elevations but partially overridden by abiotic limits at higher elevations. We conclude that inherent site conditions (TMS) determine total SOC capacity, whereas tree species management controls SOC stability. Although no significant differences were observed in total SOC stocks between conifers and broadleaves at the same sites (medians of total SOC ranged from approx. 5 to 16 kg·m⁻², depending on the site), converting purely coniferous stands into broadleaves represents an effective strategy for long-term mineral SOC stabilization, particularly in middle-elevation sites. Full article

Metallurgical batching—governing raw material proportioning across sintering, blast furnace ironmaking, converter steelmaking, and non-ferrous smelting—critically determines product quality, energy consumption, and production cost throughout the full process chain. Its inherent complexity, characterized by strong nonlinear physicochemical coupling, measurement delays of up to 1.5 h, and multi-source raw material disturbances, renders conventional linear programming and empirical methods inadequate for dynamic, multi-objective industrial environments. This review systematically examines 98 representative studies (2020–2026) on intelligent algorithms applied to metallurgical batching optimization. A two-dimensional analysis framework of the fusion algorithm function and metallurgical scene is established. All kinds of methods are divided into three categories: prediction-oriented, optimization-oriented and decision-oriented, covering four typical scenes of sintering burdening, blast furnace ironmaking, converter steelmaking and non-ferrous metal smelting. Traditional machine learning models achieve sintering burn-through point prediction with R² ≈ 0.85 and offer superior interpretability via SHAP analysis. Deep learning architectures deliver blast furnace silicon content prediction with RMSE ≈ 0.04%, while multi-objective evolutionary algorithms provide mature Pareto optimization for batching cost and carbon objectives. Reinforcement learning holds long-term potential for closed-loop adaptive control but remains constrained by Sim-to-Real safety barriers. Converter steelmaking and non-ferrous smelting are identified as underexplored domains. Three priority directions are proposed: domain-adaptive predictive modeling for cross-plant generalization, real-time re-optimization embedding mechanism constraints, and safe reinforcement learning transfer via high-fidelity digital twins. Full article

To address the neglect of real-time mass transfer effects by traditional analysis methods during the side-by-side offloading process of Floating Production Storage and Offloading (FPSO) and shuttle tankers, a numerical model incorporating the variable mass effect is established to enable the simulation of dynamic offloading processes. Using this model, the dynamic response characteristics under different offloading rates and sea conditions are systematically investigated and validated against towing tank tests. Based on the previously optimized benchmark configuration, which includes 16 side-by-side mooring lines, six floating fenders, and an anchor line angle of 60° for the FPSO, the evolution laws of mooring line tension and fender pressure under different offloading rates were systematically investigated under normal and extreme sea conditions. The results show that an increase in offloading rate significantly amplifies the system’s fender load; when the offloading rate reaches approximately 1.4 t/s, the system transitions from the quasi-static response region to a significant nonlinear coupling region, demonstrating obvious sea condition–rate coupling characteristics. Under the combined action of high offloading rates and severe sea conditions, fender pressure rapidly approaches the design limit, becoming the primary safety bottleneck for the system. Model test results indicate that the numerical model can well predict mechanical responses under low and medium offloading rate conditions. The research results can provide a reference for offloading rate control, safety assessment, and operational window determination during FPSO side-by-side dynamic offloading operations. Full article

Background: Menthol is a naturally occurring volatile terpene alcohol, widely used in food, pharmaceutical, and tobacco products; however, its high volatility leads to significant flavor loss during storage and handling. Methods: Herein, bimodal mesoporous silica materials (BMMs) were employed as carriers to encapsulate menthol, the loading and release behaviors were systematically compared using normal-temperature and alcohol-thermal loading methods. Results: Comprehensive characterizations (XRD and SAXS patterns, FT-IR spectra, SEM images, and N₂-sorption isotherms) confirmed that menthol incorporation did not disrupt the hierarchical mesoporous channels of BMMs. The alcohol-thermal loading method achieved a superior menthol loading capacity of 87%, significantly outperforming the normal-temperature loading (58%). Release performances revealed a transition in the dominant release mechanism, from diffusion-controlled behavior at low loading levels to concentration gradient-driven desorption at high loadings. Molecular dynamics simulations further demonstrated that alcohol-thermal loading enabled faster molecular diffusion and a more uniform distribution of menthol within the mesopores due to weaker interfacial interactions, whereas normal-temperature loading induced localized multilayer adsorption, resulting in mesopore blockage and hindered diffusion. In addition, long-term atmospheric release tests assessed sustained menthol retention over 30 days. Conclusions: Overall, this work establishes alcohol-thermal loading as an effective approach for regulating adsorption and release in mesoporous carriers, providing a foundation for developing volatile compound encapsulation strategies. Full article

Manganese (Mn) is an essential trace element crucial for antioxidant defense, metabolism, and neuronal function, yet both deficiency and excess may induce oxidative stress and organ-specific damage. This study investigated the effects of dietary manganese exclusion and replacement of standard MnCO₃ with Mn₂O₃ nanoparticles on redox status and oxidative damage in rats. Twenty-four male Wistar rats were divided into three groups: control (K) receiving 65 mg/kg Mn as MnCO₃, manganese-deficient (B), and nanoparticle-supplemented (N) receiving 65 mg/kg Mn as Mn₂O₃ nanoparticles. After 12 weeks, tissues were analyzed for oxidative stress markers and antioxidant enzyme activities. Manganese deficiency resulted in decreased plasma SOD activity, increased lipid peroxidation, and severe oxidative–nitrosative damage in the brain and jejunum, despite hepatic compensatory mechanisms. Mn₂O₃ nanoparticle supplementation enhanced hepatic and renal antioxidant capacity, reducing oxidative damage in these organs. However, nanoparticles induced pronounced neurotoxicity, characterized by GSH depletion, elevated DNA damage (8-OHdG), protein nitration (3-NT), and caspase activation in brain tissue. These findings demonstrate that while Mn₂O₃ nanoparticles offer improved bioavailability and hepatorenal benefits, they pose significant neurotoxic risks, necessitating caution in dietary supplementation strategies. Full article

This study investigated the effect of post-silanization processing on the surface chemistry and dispersion stability of 3 mol% yttria-stabilized tetragonal zirconia polycrystal (3Y-TZP) nanoparticles intended for the reinforcement of dental photopolymer resins. The nanoparticles were silanized using 3-Methacryloxypropyltrimethoxysilane and subjected to different post-treatment protocols, including control, drying, and centrifugation. Particle morphology was examined using field-emission scanning electron microscopy (FE-SEM) and transmission electron microscopy (TEM). Dispersion behavior was analyzed by dynamic light scattering (DLS) and zeta potential measurements, performed in triplicate (n = 3), while surface chemical modifications were evaluated using Fourier transform infrared spectroscopy (FT-IR) and X-ray photoelectron spectroscopy (XPS). Post-silanization processing significantly influenced nanoparticle surface chemistry and dispersion stability. Centrifugation promoted the formation of Si-O-Zr and Si-O-Si linkages, reduced loosely adsorbed silane species, decreased particle agglomeration, and increased zeta potential magnitude, resulting in a more uniform hydrodynamic size distribution compared to the dried group (Z-average » 814 nm, PDI » 0.44). These findings suggest that post-silanization centrifugation acts as an interfacial selection mechanism that distinguishes covalently grafted silane from weakly adsorbed species. Within the limitations of this in vitro study, further investigations under varied conditions are required to confirm broader applicability. Full article

Producing high-conductivity aluminum conductors for power transmission involves 23 trace elements and multiple interconnected thermo-mechanical stages. The ultra-low alloying levels required to preserve high electrical conductivity create a narrow compositional window and highly imbalanced distributions, which hinder traditional data-driven learning. Here, we developed a physics-guided machine-learning framework based on 4458 valid industrial production records to predict tensile strength and electrical resistivity. In addition to raw composition and process parameters, we introduce ratio descriptors (e.g., Fe/Si and Al/Si) and propose a physics-informed metric termed the Equivalent Solute–Heat Index (ESHI) to couple key solute chemistry (Si, Fe, B) with normalized thermal-history intensity. Fe and Si primarily influence resistivity through impurity/solute scattering, while B mainly affects microstructural uniformity via grain refinement. Incorporating ESHI as an augmented signal into the best-performing XGB surrogate markedly improves generalizability, increasing the tensile strength R² from 0.75 to ~0.92. SHAP analysis reveals that ESHI dominates the decision logic by modulating both targets with metallurgically interpretable mechanisms: solute-controlled scattering and thermal history-traced second-phase evolution that stabilizes the microstructure. NSGA-III was further employed to map the Pareto front and identify composition–process combinations that optimize the strength–conductivity trade-off, enabling improved mechanical reliability while minimizing resistive losses in practical power-transmission applications. Experimental validation on industrial wires confirms this reliability. Full article

Heat-assisted metal spinning comprises incremental forming routes, conventional spinning, shear spinning and flow forming, performed at elevated temperature to increase formability. This review consolidates the main advances of the last fifteen years. It outlines spinning mechanics and the rationale for heating (higher ductility, lower forming forces and microstructure control), then compares global and local heating strategies (furnace, flame, induction, laser and hot-gas convection) in terms of temperature uniformity, industrial practicality, energy efficiency and cost. Key process parameters (spindle speed, feed rate and thickness reduction) are discussed with respect to defect formation, and representative windows for defect mitigation are reported. Progress in modeling is reviewed, including coupled thermo-mechanical finite element simulations, damage/formability prediction and emerging data-driven optimization. The review also summarizes microstructural evolution under heat-assisted conditions, phase transformation, dynamic recrystallisation and grain growth, and its impact on final properties. Across more than 100 studies, evidence shows that robust thermal management can roughly double achievable deformation before failure and enables property tailoring in difficult-to-form alloys (Ni-based alloys, high-strength steels, Al, Mg and Ti). Remaining challenges include reliable in situ temperature measurement/control and improved predictive fidelity of simulations. Future opportunities include digital twins, real-time sensing and adaptive, machine-learning-assisted control. Full article

Сommercial TiO₂ ceramic membranes were modified using a slip-casting method with coal fly ash (CFA) obtained from a thermal power plant, Almaty, Kazakhstan. The aim was to enhance membrane surface properties for improved oil-in-water emulsion separation while maintaining structural integrity. Suspension of CFA, stabilized with N-dodecylpyridinium chloride (DPC) and polyvinyl alcohol (PVA), was applied as a coating layer on the TiO₂ surface and subsequently sintered under controlled conditions. The resulting membranes were characterized by SEM-EDX (scanning electron microscopy with energy-dispersive X-ray), Raman spectroscopy, contact angle measurements, and zeta potential analysis. The modified membranes exhibited increased hydrophilicity, as indicated by a reduction in water contact angle (WCA) from 43.6 ± 2° to approximately 0°, and a decrease in the underoil contact angle of water (UOCA) from 147.6 ± 2° to 87 ± 2°. Raman spectroscopy confirmed that the TiO₂ structure remained predominantly rutile, with no additional crystalline phases detected from CFA. Despite the improved wettability, pure water and oil-in-water emulsion fluxes decreased slightly, while filtrates displayed smaller oil droplet sizes, indicating enhanced emulsion stability after passage through the modified surface. These findings demonstrate that CFA-modified TiO₂ membranes can serve as a sustainable and cost-effective approach for treating emulsified wastewater, utilizing industrial waste to improve performance without compromising mechanical robustness. Full article

To clarify the migration and structural evolution of mining-induced overburden following grouting reconstruction of the Fourth Aquifer, the inner section of Panel 1022-2 in Wugou Coal Mine was taken as the engineering background. The evolution law of overburden movement and the development characteristics of the caving zone were systematically investigated via theoretical analysis, similar-material simulation, and numerical simulation. In addition, the maximum caving-zone height of Panel 1022-2 was calculated based on the measured caving-to-mining ratio of the adjacent Panel 1010-1. The results show that following grouting reconstruction of the Fourth Aquifer, the water inflow and permeability coefficient decreased significantly, the mining-induced water-body grade was classified as Grade III, and the required coal pillar type was converted from a waterproof safety coal (rock) pillar to an anti-collapse safety coal (rock) pillar. The bedrock failure morphology evolved sequentially from a symmetrical trapezoid to a stepped shape and finally to an asymmetrical saddle shape, with a maximum caving-zone height of 19.0 m, whereas the Fourth Aquifer evolved from fracture initiation and bed separation to asymmetrical overall subsidence. Overburden migration is jointly controlled by bedrock thickness and the mechanical properties of the unconsolidated layer, presenting a distinct three-stage evolution pattern. As the size of the reserved safety coal (rock) pillar decreases, the overburden failure mode changes from overall plastic failure under relatively thick bedrock, to semi-block failure with longitudinal fractures penetrating to the base of the Fourth Aquifer and transverse fractures and interlayer separation initiating inside the aquifer, and finally to intensified failure under thin-bedrock conditions. Based on field analogy with Panel 1010-1, the maximum caving-zone height of Panel 1022-2 was calculated to be 19.73 m, which is in good agreement with the numerical and similar-material simulation results, verifying the reliability of the three-stage overburden evolution law and the caving-zone height evaluation. Full article

Long-term continuous cropping often leads to soil-borne pathogen enrichment, and reducing pathogen abundance in continuously cropped soils is an important control measure. In this study, three rotation crops—carrot (C), garlic (G), and bok choy (B)—were introduced into potato pathogen-infested soils. The effects of different systems on pathogen abundance, soil physicochemical properties, and soil microbial abundance were investigated to preliminarily clarify mechanisms by which crop rotation suppressed pathogen enrichment. The results showed that all rotation systems significantly reduced soil pathogen abundance (Fusarium oxysporum, Fo). Among the rotation systems, carrot rotation achieved the greatest Fo reduction and exhibited the strongest increase in soil pH, followed by garlic rotation, while bok choy rotation had the weakest effect. Carrot rotation significantly increased soil bacterial abundance over other treatments. Moreover, crop rotation effectively suppressed soil pathogen enrichment by increasing soil pH and bacterial abundance. Importantly, carrot rotation enhanced soil pathogen-suppressive enzyme activities and the abundance of antagonistic bacteria in the soil. In contrast, garlic root exudates directly inhibited the pathogen, while bok choy and carrot root exudates promoted pathogen growth. These findings demonstrated different rotation crops exhibit distinct pathogen suppression mechanisms. Carrot rotation may indirectly suppress soil pathogen enrichment by increasing the abundance of antagonistic bacteria and enhancing antifungal enzymes, whereas garlic rotation may directly inhibit the pathogen via root exudates. This study provides practical guidance for growers to select optimal rotation crops and design rational continuous cropping systems. Full article

Autism spectrum disorder (ASD) has been associated with alterations in the gut microbiota and its metabolites, particularly short-chain fatty acids (SCFAs) and microbiota-derived tryptophan catabolites, which may influence neurodevelopment through immune and epigenetic mechanisms. We investigated whether stool SCFAs and tryptophan-pathway metabolites differ between children with ASD and typically developing controls, and whether these metabolites associate with ASD severity and systemic biochemical signatures. In this cross-sectional study, we analyzed stool samples from 229 children (160 with ASD, 69 controls) with complete SCFA and tryptophan-metabolite data, while urine metabolomics data were available for a subset and were used for exploratory stool–urine integration analyses. Children with ASD and controls were similar in age, but the ASD group had a higher proportion of males. Absolute concentrations of individual SCFAs, total SCFAs, and derived indices were broadly comparable between groups; nominal differences in propionate/acetate ratio and caproate did not remain significant after false discovery rate correction. Similarly, stool tryptophan-pathway metabolites reported as ng/a.u. based on the NanoDrop-derived proxy (tryptophan, kynurenine, indole-3-acetic, indole-3-lactic, indole-3-propionic, indole-3-aldehyde, N-acetyl-tryptophan, serotonin, melatonin, tryptamine) and functional ratios (kynurenine/tryptophan, indole-derived/tryptophan, serotonin/tryptophan) showed no robust ASD–control differences; N-acetyl-tryptophan was nominally higher in ASD but did not survive multiple-testing correction. In the ASD subgroup with available Childhood Autism Rating Scale (CARS) data (n = 34), SCFA and tryptophan indices showed only weak, non-significant correlations with global ASD severity. In contrast, correlation analyses revealed two coherent metabolic modules, i.e., an SCFA block with very strong internal correlations among individual SCFAs and total SCFAs and a tryptophan block with strong correlations between metabolites and their normalized ratios, while cross-module correlations were modest. These results indicate that stool SCFA and microbiota-derived tryptophan profiles do not robustly distinguish ASD from controls in this cohort, but they form stable metabolic modules compatible with microbiome–epigenome frameworks. Full article

The widespread application of detonation nanodiamonds (DNDs) is limited by surface-coated non-diamond sp² carbon impurities. In this work, an efficient salt-assisted catalytic purification strategy is developed to achieve selective oxidation removal of sp² carbon. DND black powder was mixed with various chloride, carbonate, and bicarbonate salts and thermally treated in air to systematically investigate the effects of anions and cations on purification efficiency. Thermogravimetric analysis reveals that all tested salts significantly reduce the oxidation onset temperature of sp² carbon and exhibit distinct catalytic trends: for anions, bicarbonates > carbonates > chlorides; for cations, Cs⁺ ≈ K⁺ > Na⁺. Among them, KHCO₃ introduced via a wet-wrapping method shows the optimal performance, lowering the oxidation temperature by approximately 160 °C. Moreover, the wet-wrapping process effectively suppresses particle sintering and agglomeration during purification, resulting in purified DNDs with reduced average particle size and markedly improved dispersibility. Mechanistic investigations demonstrate that free alkali metal cations act as active sites, preferentially catalyzing sp² carbon oxidation through a synergistic oxygen spillover–electron transfer mechanism. This study provides an effective and highly selective approach for DND purification. The proposed salt-assisted strategy, integrating catalytic oxidation and dispersion control, also offers valuable insights for the preparation of high-performance nanomaterials. Full article