Search Results (1,232)

Traffic-related air pollution (TRAP) is known to contribute to oxidative stress in the central nervous system (CNS) and has been linked to increased risk of Alzheimer’s disease (AD). Alterations in the renin–angiotensin system (RAS), specifically increased angiotensin II (Ang II) signaling via the angiotensin II type 1 (AT₁) receptor, are implicated in increased oxidative stress in the CNS via activation of NADPH oxidase (NOX). As exposure to TRAP may further elevate AD risk, we investigated whether exposure to inhaled mixed gasoline and diesel vehicle emissions (MVE) promotes RAS-dependent expression of factors that contribute to AD pathophysiology in an apolipoprotein E-deficient (ApoE^−/−) mouse model. Male ApoE^−/− mice (6–8 weeks old) on a high-fat diet were treated with either an ACE inhibitor (captopril, 4 mg/kg/day) or water and exposed to filtered air (FA) or MVE (200 µg PM/m³) for 30 days. MVE exposure elevated plasma Ang II, inflammation, and oxidative stress in the hippocampus, associated with increased levels of Aph-1 homolog B (APH1B), a gamma-secretase subunit, and beta-secretase 1 (BACE1), involved in Aβ production. Each of these endpoints was normalized with ACEi treatment. These findings indicate that TRAP exposure in ApoE^−/− mice drives a RAS- and NOX-dependent oxidative and inflammatory response and shifts Aβ processing towards an amyloidogenic profile before overt Aβ deposition, suggesting a potential therapeutic approach for air pollution-induced AD risk. Full article

Cardiovascular disease (CVD) remains a leading cause of global morbidity and mortality, and its initiation and progression are closely associated with multiple molecular mechanisms. Neutrophil extracellular traps (NETs) are mesh-like structures composed of DNA, histones, and antimicrobial proteins that are released by neutrophils during inflammation or infection. They play a crucial role in innate immune defense. However, when the dynamic balance of NETs is disrupted by excessive formation, persistent accumulation, or impaired clearance, NETs are no longer merely bystanders. Instead, they actively drive pathological processes in multiple CVDs and serve as a critical link between inflammation and cardiovascular injury. Given the central role of NETs in CVD pathogenesis, including atherosclerosis, myocardial ischemia–reperfusion injury, pulmonary arterial hypertension, atrial fibrillation, and heart failure, therapeutic strategies targeting NETs, such as inhibiting aberrant formation, enhancing clearance, or neutralizing toxic components, have emerged as promising approaches. In recent years, traditional Chinese medicine (TCM) and natural products have shown potential therapeutic value by modulating NET formation and promoting NET degradation, owing to their multitarget, multipathway regulatory effects. This article reviews the mechanisms by which NETs operate in CVDs and explores potential pathways through which TCM and natural active ingredients prevent and treat CVDs by regulating NETs. This review provides theoretical support for further research and clinical application. Full article

This study proposes an artificial intelligence-integrated Six Sigma framework for reducing multiple critical defects in plastic injection molding using real industrial production data from a washing-machine control-panel manufacturing line. Predictive models were developed under severe class imbalance conditions and combined with SHAP-based interpretability to identify the most influential process parameters. A multi-objective NSGA-II optimization strategy was then employed to simultaneously minimize major defect types, including gas-trapped burn (GTB), short shot (SS), sink mark (SK), and flash (FL). The proposed framework was validated through on-site continuous trial production of 300 parts after process stabilization, demonstrating substantial and consistent defect reduction. The results indicate that the integration of data-driven modeling, explainable artificial intelligence, and evolutionary multi-objective optimization provides a practical and scalable approach for quality improvement in industrial injection molding processes. Full article

Systemic lupus erythematosus (SLE) is an autoimmune disease with multiple and heterogeneous clinical manifestations (e.g., skin lesions, kidney damage, neuropsychiatric dysfunction), that primarily affects women and whose etiology remains unclear. Various therapies that regulate and reduce the immune system activity are in use or are being developed; however, many of them have serious side effects. Therefore, new approaches are needed to maximize remission periods and reduce associated side effects. In this review, we summarize the currently recommended therapeutic strategies. Furthermore, we hypothesize that the combined use of drugs targeting various dysregulated cellular processes in SLE (i.e., cytokine production, neutrophil extracellular traps (NETs), phagocytosis) might have therapeutic potential, at least in some disease phenotypes. Preliminary data show that Toll-like receptors 7/8 (TLR 7/8) inhibition (e.g., Enpatoran) may reduce interferon-α (IFN-α) production by monocytes and NET formation by neutrophils. Our hypothesis is that future therapies combining compounds that modulate the three cellular processes might result in a better disease management as current therapies. Full article

Microparticle detection technology uses materials that can specifically recognize complex biostructures, such as antibodies and aptamers, as trapping agents. The development of antibody production technology and simplification of sensing signal output methods have facilitated commercialization of disposable biosensors, making rapid diagnosis possible. Although this contributed to the early resolution of pandemics, traditional biosensors face issues with sensitivity, durability, and rapid response times. We aimed to fabricate microspaces using metallic materials to further enhance durability of mold fabrication technologies, such as molecular imprinting. Low-damage metal deposition was performed on target protozoa and Norovirus-like particles (NoV-LPs) to produce thin metallic films that adhere to the material. The procedure for fitting the object into the bio structured space formed on the thin metal film took less than a minute, and sensitivity was 10 fg/mL for NoV-LPs. Furthermore, because it was a metal film, no decrease in reactivity was observed even when the same substrate was stored at room temperature and reused repeatedly after fabrication. These findings underscore the potential of integrating stable metallic structures with bio-recognition elements to significantly enhance robustness and reliability of environmental monitoring. This contributes to public health strategies aimed at early detection and containment of infectious diseases. Full article

Horse flies (Tabanidae) negatively affect livestock by reducing productivity, compromising animal welfare, and serving as mechanical vectors of pathogens. However, the spatial processes shaping their community organization in southern Brazil’s Coastal Plain of Rio Grande do Sul (CPRS) remain poorly understood. To address this, we conducted standardized Malaise-trap surveys and combined them with historical–contemporary comparisons to examine distance–decay patterns in community composition. We evaluated both abundance-based (Bray–Curtis) and presence–absence (Jaccard) dissimilarities using candidate models. Across sites, Tabanus triangulum emerged as the dominant species. Dissimilarity in community structure increased monotonically with geographic distance, with no evidence of abrupt thresholds. The square-root model provided the best fit for abundance-based data, whereas a linear model best described presence–absence patterns, reflecting dispersal limitation and environmental filtering across a heterogeneous coastal landscape. Sites within riparian forests and conservation units displayed higher diversity, emphasizing the ecological role of protected habitats and the importance of maintaining connected corridors. Collectively, these findings establish a process-based framework for surveillance and landscape management strategies to mitigate vector, host contact. Future directions include integrating remote sensing and host distribution, applying predictive validation across temporal scales. Full article

This study presents a quantitative simulation analysis of hydrogen-enriched methane (HENG) storage with nitrogen as the cushion-gas in a depleted gas reservoir by varying three key operational parameters: the injection/withdrawal period, hydrogen blending ratio (5–20%), and injection depth. Ten injection–withdrawal cycles were modeled for each scenario, and performance was evaluated using cycle-averaged and cumulative hydrogen purity, recovery factors, and the mixing zone size. Extending the injection period increased hydrogen purity to 20.00–20.26% and reduced nitrogen to 0.001–0.003%, but recovery decreased from 65.63 to 53.83–41.09% due to enhanced dispersion and residual trapping. The blending ratio was the dominant control: 20% blending yielded 19.9–20.0% purity with nitrogen as low as 0.00–0.03%, whereas 5–10% blending produced lower purity but minimized nitrogen production to 0.97–1.08%. Injection depth affected nitrogen recovery more than purity, increasing from 0.72–1.20% (upper) to 1.46–1.61% (lower), along with thicker mixing zones. Final mixing zone size ranged from 3176 to 5546 blocks, with smaller zones consistently linked to higher purity and lower nitrogen breakthrough. The shut-in period further reduced nitrogen recovery from 6.49 to 1.33% and stabilized mixing behavior. Overall, minimizing late-cycle mixing zone thickness is essential for maintaining HENG storage performance. Although this study provides quantitative insights into HENG operational strategies, the use of a homogeneous grid and simplified fluid properties limits representation of geological heterogeneity and reactive processes. Future work will incorporate heterogeneity and reaction modeling into field-scale simulations to validate and refine these operating strategies for practical deployment. Full article

Lithuania covers the deepest parts of the Baltic basin and contains many reservoirs that have been explored for Hydrocarbon production and gas storage projects, including CO₂ and hydrocarbon gas storage. Studies have also been conducted to assess the storage potential of these reservoirs for gases like CO₂ and Hydrogen. In the studies, four saline aquifers, including Syderiai, Vaskai, and D11, and depleted hydrocarbon reservoirs in the Gargzdai structure were evaluated for potential CO₂ storage. However, the long-term fate of these gases’ migration at the field scale has not been reported previously. In response to the existing gap, this study aims to evaluate the risks and challenges associated with subsurface CO₂ and Hydrogen storage by conducting numerical simulations at two injection rates, of fluid migration, pH variations, and geomechanical responses using the tNavigator platform, complemented by laboratory experiments on outcrops representative of Syderiai formation, to achieve a detailed understanding of geochemical interactions between rocks and fluids. The results reveal distinct gas-specific behaviors: CO₂ exhibits enhanced solubility trapping, density-driven convective mixing, and pronounced pH reduction, whereas Hydrogen demonstrates rapid buoyant migration, higher pressure buildup, and negligible geochemical reactivity. Both gases demonstrate short-term storage viability in the Syderiai aquifer under the modeled conditions, with pressure and total vertical stress remaining below the bottom-hole pressure limit of 450 bars. This integrated simulation and experimental study enhances our understanding of Lithuanian reservoirs for the safe, long-term storage of both CO₂ and Hydrogen. Full article

The Yellow River Basin (YRB), a typical river system facing the challenge of balancing ecological conservation and economic development, offers valuable insights for global sustainable watershed governance through its forestry green transformation. Based on panel data from nine provinces in the basin from 2005 to 2022, this study constructs an efficiency evaluation indicator system for forestry green development. This system incorporates four inputs (labor, land, capital, and energy), two desirable outputs (economic and ecological benefits), and three undesirable outputs (wastewater, waste gas, and solid waste). By systematically integrating the undesirable outputs-based super-SBM model and the global Malmquist–Luenberger (GML) index, this study provides an assessment from both static and dynamic perspectives. The findings are as follows. (1) Forestry green development efficiency showed fluctuations over the study period, with the basin-wide average remaining below the production frontier. Spatially, it exhibits a pattern of “downstream > upstream > midstream”. (2) The average GML index is 0.984 during the study period, representing an average annual decline in forestry green total factor productivity of 1.6%. The growth dynamics transitioned from a stage dominated solely by technological progress to a dual-driver model involving both technological progress and technical efficiency. (3) The drivers of forestry green total factor productivity growth in the basin show profound regional heterogeneity. The downstream region demonstrates a synergistic dual-driver model of technical efficiency and technological progress, the midstream region is trapped in “dual stagnation” of both technical efficiency and technological progress, and the upstream region differentiates into four distinct pathways: technology-driven yet foundationally weak, efficiency-improving yet technology-lagged, endowment-advantaged yet transformation-constrained, and condition-constrained with efficiency limitations. The assessment framework and empirical findings established in this study can provide empirical evidence and policy insights for basins worldwide to resolve the ecological-development dilemma and promote forestry green transformation. Full article

Mushrooms like Inonotus obliquus and Ganoderma lucidum show significant pharmacological promise. This review analyzes fungi as sources of natural inhibitors against Advanced Glycation End-products (AGEs)—key drivers of diabetes and neurodegeneration. We highlight that extracts from Lignosus rhinocerus and Auricularia auricula exhibit antiglycation potency (IC₅₀ as low as 0.001 mg/mL) superior to aminoguanidine. Inhibitory effects are attributed to bioactive fractions including FYGL proteoglycans, uronic acid-rich polysaccharides, and fungal-specific metabolites like ergothioneine. These compounds act through multi-target mechanisms across the glycation cascade: competitive inhibition of Schiff base formation, trapping reactive dicarbonyls (e.g., methylglyoxal), transition metal chelation, and direct scavenging of reactive oxygen species (ROS). Furthermore, the review addresses the transition from in vitro potency to in vivo efficacy (RAGE pathway modulation), stability during food processing (UV-B irradiation), and critical safety issues regarding heavy metal bioaccumulation. Mushroom-derived inhibitors represent a sustainable therapeutic alternative to synthetic agents, offering broader protection against glycative stress. This synthesis provides a foundation for developing standardized mushroom-based nutraceuticals for managing AGE-related chronic disorders. Full article

In situ preparation routes have become central to advancing lead sulfide (PbS) quantum dots (QDs) for solar-energy conversion, owing to their ability to create strongly coupled QD/oxide interfaces that are difficult to achieve with ex situ colloidal methods, along with their simplicity and potential for low-cost, scalable processing. This review systematically examines the fundamental mechanisms, processing levers, and device implications of the dominant in situ approaches successive ionic layer adsorption and reaction (SILAR), voltage-assisted SILAR (V-SILAR), and chemical bath deposition (CBD). These methods enable conformal QD nucleation within mesoporous scaffolds, improved electronic coupling, and scalable low-temperature fabrication, forming the materials foundation for high-performance PbS-based architectures. We further discuss how these in situ strategies translate into enhanced solar-energy applications, including quantum-dot-sensitized solar cells (QDSSCs) and photoelectrochemical (PEC) hydrogen production, highlighting recent advances in interfacial passivation, scaffold optimization, and bias-assisted growth that collectively suppress recombination and boost photocurrent utilization. Representative device metrics reported in recent studies indicate that in-situ-grown PbS quantum dots can deliver photocurrent densities on the order of ~5 mA cm⁻² at applied potentials around 1.23 V versus RHE in photoelectrochemical systems, while PbS-based quantum-dot-sensitized solar cells typically achieve power conversion efficiencies in the range of ~4–10%, depending on interface engineering and device architecture. These performances are commonly associated with conformal PbS loading within mesoporous scaffolds and quantum-dot sizes in the few-nanometer regime, underscoring the critical role of morphology and interfacial control in charge transport and recombination. Recent studies indicate that performance improvements in PbS-based solar-energy devices are primarily governed by interfacial charge-transfer kinetics and recombination suppression rather than QD loading alone, with hybrid heterostructures and inorganic passivation layers playing a key role in modifying band offsets and surface trap densities at the PbS/oxide interface. Remaining challenges are associated with defect-mediated recombination, transport limitations in densely loaded porous scaffolds, and long-term chemical stability, which must be addressed to enable scalable and durable PbS-based photovoltaic and photoelectrochemical technologies. Full article

Lipid nanoparticles (LNPs) are now the go-to method for delivering genetic medicines, backed by real-world use in patients. Things like which fats they are made of, their shape at the molecular level, how ingredients mix, and how they are built, matter a lot. This review attempts to take a close look at how different components, such as ionizable lipids, auxiliary lipids (DSPC, DOPE), cholesterol, and PEG-based lipids, affect the bioavailability of LNPs. It also focuses on key functions of LNPs, including packaging genetic material, escaping cellular traps, spreading in the body, and remaining active in the blood. New data show that lipids with the right handedness and highly sensitive chiroptical quality control can sharpen delivery accuracy and boost transport rates, turning stereochemistry into a practical design knob. Rather than simply listing results, we examine real-world examples that are already used to regulate gene expression, enhance mRNA expression, splenic targeting, and show great potential for gene repair, protein replacement, and DNA base-editing applications. Also, recent advances in AI-based designs for LNPs that take molecular shape into account and help speed up modifications to lipid arrangements and mixture configurations are highlighted. In summary, this paper presents a practical and scientific blueprint to support smarter production of advanced LNPs used in genetic medicine, addressing existing obstacles, balanced with future opportunities. Full article

Background: The in vivo accumulation of Advanced Glycation End products (AGEs) is associated with the development of several chronic aging-related and degenerative diseases, as they alter protein structures and activate oxidative and inflammatory processes through interactions with the receptor for AGEs (RAGE). Plant secondary metabolites play a key role in counteracting the glycation process through various mechanisms of action. Therefore, Aloysia citrodora leaf polyphenolic extract could represent a source of anti-glycative compounds. Methods: The methanolic extract was characterized by RP-HPLC-DAD-MSⁿ, and its anti-glycative properties were investigated using several in vitro assays mimicking the different steps of the glycation reaction. In parallel, molecular docking studies were carried out to evaluate potential interactions between the identified metabolites and RAGE. Furthermore, A. citrodora metabolites’ stability under simulated in vitro digestion was assessed, and the anti-glycative activity of the bioaccessible fraction was investigated. Results:A. citrodora extract, rich in iridoid glycosides, phenylethanoid glycosides, and flavones, strongly inhibited AGE formation (from 10% to 100%) in both the middle and end step of the reaction and had high methylglyoxal and glyoxal trapping capacity. However, the digestion process affected extract stability, particularly under intestinal conditions, yielding an overall bioaccessibility of about 40% and leading to a subsequent reduction in anti-glycative properties. Finally, molecular modeling analysis highlighted the ability of the studied metabolites to bind RAGE. Conclusions:A. citrodora represents a promising source of natural anti-glycative agents with potential applications as food ingredients. However, it is essential to improve the extract bioaccessibility and to preserve its anti-glycative properties by developing a suitable formulation. Full article

The development of shale gas reservoirs relies on complex fracture networks created via multistage hydraulic fracturing, yet most existing models still use oversimplified fracture geometries and therefore cannot fully capture the coupled effects of multiscale fracture topology on flow and production. To address this gap, in this study, we combine fractal geometry with the Embedded Discrete Fracture Model (EDFM) to analyze the production dynamics of hydraulically fractured horizontal wells in shale gas reservoirs. A tree-like fractal fracture network is first generated using a stochastic fractal growth algorithm, where the iteration number, branching number, scale factor, and deviation angle control the self-similar hierarchical structure and spatial distribution of fractures. The resulting fracture network is then embedded into an EDFM-based, fully implicit finite-volume simulator with Non-Neighboring Connections (NNCs) to represent multiscale fracture–matrix flow. A synthetic shale gas reservoir model, constructed using representative geological and engineering parameters and calibrated against field production data, is used for all numerical experiments. The results show that increasing the initial water saturation from 0.20 to 0.35 leads to a 26.4% reduction in cumulative gas production due to enhanced water trapping. Optimizing hydraulic fracture spacing to 200 m increases cumulative production by 3.71% compared with a 100 m spacing, while longer fracture half-lengths significantly improve both early-time and stabilized gas rates. Increasing the fractal iteration number from 1 to 3 yields a 36.4% increase in cumulative production and markedly enlarges the pressure disturbance region. The proposed fractal–EDFM framework provides a synthetic yet field-calibrated tool for quantifying the impact of fracture complexity and design parameters on shale gas well productivity and for guiding fracture network optimization. Full article

The relationship between insect diversity and crop production has been of continuous scientific interest. Understanding insect community dynamics using various sampling and monitoring methods at different crop phenology stages is crucial for enhancing pest management and ecosystem service functioning. The present study assessed the influence of four trap types (Blue, Yellow, White, and Malaise) applied at four tomato developmental stages (start of planting, flowering, flowering fruit development and harvest) on insect diversity in northeastern Tunisian open-field conditions. A total of 1771 insect individuals belonging to seven orders and 31 families were trapped, with the order Hymenoptera being the most common in the sampled plots, which was represented by 25 families. Trap type exerted a strong effect on both abundance and alpha diversity parameters. Yellow pan traps showed the highest diversity, with family richness (S) ranging from 1 to 16, Shannon diversity (H) reaching 2.54, Simpson (Is) diversity ranging from 0.72 to 0.90 and Pielou’s evenness (J) ranging from 0.83 to 0.98. Blue and white traps displayed intermediate diversity (Blue: S = 6 and H = 1.7; White: S = 7 and H = 1.6), while Malaise traps captured the least diverse assemblages (S = 4, H = 1.2 and Is = 0.65). These differences were highly significant (p < 0.05). Phenological stage significantly structured Hymenoptera diversity. Richness peaked at the start of planting (S = 1–16 and H up to 2.54) and declined sharply at harvest (S = 1–6). Pollinator families (Apidae, Halictidae, Megachilidae) were the most abundant during flowering, whereas parasitoid families (Braconidae, Eulophidae) dominated during the fruit development stage. Beta diversity analyses (NMDS, stress = 0.25) and PERMANOVA showed that trap type and phenological stage jointly explained 15.5% of the variation in community composition (R² = 0.155, p = 0.014). Although a strong taxonomic overlap among traps was observed, Indicator Value analysis revealed significant trap-specific associations, including the family Andrenidae with Blue traps and the family Scoliidae with White and Yellow traps. Overall, the results of the present study demonstrate that both trap type and crop phenology significantly influence insect population diversity. A multi-trap sampling strategy combining colored pan traps and Malaise traps could be recommended to accurately characterize insect communities and associated ecosystem services in Mediterranean open-field tomato systems. Full article