Search Results (4,344)

Whole-grain rice (Oryza sativa L.) is a rich source of polyphenols. The in vivo mechanisms linking its phytochemical profile to antioxidant and anti-inflammatory effects remain incompletely defined. This study investigated the antioxidant and anti-inflammatory activity of a whole-grain rice flour 70% ethanol extract (OSEE) and correlated these effects with its phenolic composition. OSEE showed high total phenolic content 0.121 ± 0.002 mg GAE/g d.w.), a lower total flavonoid content (61.83 ± 4.03 µg QE/g d.w.), and a phenolic profile dominated by phenolic acids (~87%), with ferulic and protocatechuic acids among the most abundant constituents. OSEE displayed significant in vitro antioxidant activity in DPPH, FRAP, hydrogen peroxide, and nitric oxide scavenging assays. In vivo activity was evaluated in male Wistar rats with turpentine oil-induced acute inflammation using both therapeutic (post-induction) and prophylactic (pre-induction) protocols, testing three oral doses of lyophilized extract (1.0, 0.50, and 0.25 g/kg/day). In vivo, OSEE attenuated systemic oxidative stress (TOS, TAC, OSI, AOPP, MDA, NOx, 3-nitrotyrosine, total thiols) and the expression of pro-inflammatory markers (NF-κB p65, IL-1β, IL-18, caspase-1) in a dose-dependent manner with both protocols, with the highest dose producing the most consistent reductions, while the expression level of the anti-inflammatory factor IL-10 remained unchanged. PCA supported a shift in biomarker networks toward a non-inflamed profile. These findings indicate that OSEE exerts coordinated antioxidant and anti-inflammatory effects in vivo that are strongly associated with its phenolic composition. Full article

Metal-free electrodes are essential to promote electrochemical reactions, the core of sustainable energy resources. In search of better carbon-based electrode materials, we have explored several spatial arrangements of boron (B) within proximity in the graphene lattice, as evident in recent experimental observations. Multi-boron substitution enriches sites by tuning electronic structure and strengthens binding of key intermediates of oxygen reduction, oxygen evolution, and hydrogen evolution reactions facilitating electrocatalytic performance. Our optimal B-doped site shows near thermo-neutral H adsorption ($\Delta G_{H^{*}}$∼$\pm 0.4\mathrm{eV}$), consistent with experiments. The overpotentials are highly sensitive to the dopant motifs and the spread among configurations shows that experimentally accessible multi-B doping can serve as a practical active site engineering knob to achieve optimized multi-functional performance. In parallel, we find that specific multi-B configurations selectively capture and pre-activate NO_x (NO/NO₂) under ambient conditions while retaining weak affinity for NH₃. These sites also interact with SO₂ and related hazardous species, enabling selective air filtration and targeted NO_x control within the electrocatalytic scope of this study. Full article

Background: Tyrosine kinase inhibitors (TKIs) have transformed cancer therapy; however, they are associated with cardiovascular toxicity. Metabolomics provides a comprehensive framework for identifying early biochemical disruptions that precede clinical manifestations and for formulating mechanism-based intervention strategies. Methods: We conducted a narrative synthesis of published preclinical and translational studies on TKI cardiotoxicity, focusing on untargeted and targeted metabolomic findings and complementary proteomic and transcriptomic data. Functional validation was performed using rodent and cellular models. Mechanistic themes were identified, and implications for biomarker panels, multi-omic integration, and metabolomics-guided interventions were proposed. Conclusions: Metabolomic analyses of various TKIs identified convergent signatures along three interconnected axes: (1) mitochondrial bioenergetic dysfunction characterized by impaired long-chain fatty acid oxidation and adenylate depletion; (2) disruption of endothelial nitric oxide signaling with redox imbalance, including increased nitrotyrosine, Nox activation, and eNOS uncoupling; and (3) an inflammatory metabolic profile marked by elevated branched-chain and aromatic amino acids, creatine, and osmolytes. Rodent models of sunitinib and sorafenib replicate these signatures and demonstrate histological injury, contractile dysfunction, and fibrosis. Preclinical intervention data, particularly restoration of myocardial carnitine, AMPK signaling, and fatty acid oxidation by L-carnitine, provide proof of concept for metabolomics-guided cardioprotection. Metabolomics can identify mechanistic biomarkers that facilitate the early detection, risk stratification, and targeted prevention of TKI-induced cardiovascular injury. Translation into precision cardio-oncology requires prospective validation, standardized assays, and biomarker-driven interventional trials. Full article

To address the complex calibration parameters and low optimization efficiency of dual-fuel engines, this paper innovatively proposes an optimization calibration method based on a simulation model and the Non-Dominated Sorting Whale Optimization Algorithm (NSWOA). Taking the YC6K dual-fuel engine as the research object, a high-precision simulation model was constructed within the GT-Power environment, and its reliability was confirmed through the external characteristic curve (the maximum deviation of torque and specific fuel consumption rate is less than 5%). A total of 260 parameter samples were generated using a Sobol sequence space-filling experimental design, and a performance prediction model was established by combining the Crested Porcupine Optimization algorithm and the Back-Propagation Neural Network (CPO-BP). The experimental results show that the CPO-BP model exhibits excellent predictive capability, with the coefficient of determination (R²) of nitrogen oxides (NO_x) and brake-specific fuel consumption rate (BSFC) reaching 0.98964 and 0.99501 respectively. Based on this, the NSWOA algorithm was introduced to optimize key parameters such as speed, torque, main injection timing, and rail pressure, with the optimization objectives being NO_x emissions and BSFC. The optimization results show that under 100% load conditions, the reduction in BSFC ranges from 1.5% to 4.3%, and NO_x emissions are reduced by 48.6% to 67.1%. The effectiveness of the optimized parameters was also verified through bench tests, providing an efficient solution for complex engineering optimization problems. Full article

This work investigates the influence of hybrid NiO–SiO₂ nanoparticles on the engine behavior of biodiesel derived from waste sunflower oil and evaluates the experimental outcomes using a data-driven modeling approach. Biodiesel was produced via transesterification and doped with nanoparticles at concentrations of 50, 75, and 100 ppm. Performance and emission tests were conducted on a single-cylinder diesel engine operating at constant speed under varying loads. Specific fuel consumption, brake thermal efficiency, CO, HC, NO_x, smoke opacity, and exhaust gas temperature were recorded and analyzed. The incorporation of nanoparticles improved combustion quality and contributed to substantial reductions in harmful emissions. The WSOB20 blend containing 100 ppm NiO–SiO₂ provided the most balanced results, decreasing CO, HC, and smoke emissions by 39.50%, 39.40%, and 35.20%, respectively, relative to diesel fuel, while preserving competitive thermal efficiency. A linear regression model developed for CO prediction produced a low mean squared error (1.08 × 10⁻⁵), indicating strong predictive capability. The findings confirm that hybrid nanoparticle additives can enhance biodiesel performance while supporting accurate emission forecasting. Full article

Heavy-duty vehicles (HDVs) are major greenhouse gas emitters, and liquefied natural gas (LNG)-powered HDVs have emerged as a promising low-carbon alternative. However, their real-world emission performance and mitigation potential remain insufficiently studied, necessitating the characterization of LNG container trucks’ on-road CO₂ emissions via advanced sensing technologies. To characterize HDVs’ emission characteristics, real-driving emissions from China VI LNG and diesel-powered container trucks were measured employing portable emissions measurement systems (PEMS). The results reveal that high CO₂ emissions predominantly occur during low- to medium-speed acceleration and at speeds above 40 km/h with an acceleration exceeding 0.3 m/s² on highways, whereas emissions on port roads are more dispersed. A third-degree polynomial function fits emissions well with vehicle-specific power (VSP). Engine parameters mainly influence CO₂ emissions for LNG trucks, while VSP and acceleration significantly impact diesel trucks. The Random Forest model achieves superior prediction accuracy, particularly in highway scenarios, and significantly better CO₂ forecasting for LNG-powered trucks. These findings validate the effectiveness of PEMS-based sensing in characterizing low-carbon HDVs’ real-world emissions. The integration of multi-source sensor data and machine learning also provides a reference for intelligent sensing in transportation environmental monitoring. Full article

Inflammatory bowel disease (IBD) is triggered by genetic predisposition and chronic inflammation, with aberrant activation of the innate immune complex NLRP3 inflammasome playing a pivotal role in its pathogenesis. In this study, we investigated the effects of a hot water extract from the brown alga Endarachne binghamiae (EB-WE) on the inhibition of NLRP3 inflammasome activation, with a focus on its antioxidant properties, in various inflammation models. In bone marrow-derived macrophages (BMDMs), NLRP3 inflammasome activation was induced using LPS and ATP, and EB-WE pretreatment (100, 200 µg/mL) significantly reduced the secretion of IL-1β and IL-18. Confocal immunofluorescence analysis further confirmed that EB-WE suppressed the formation of the NLRP3-ASC/caspase-1 complex. Furthermore, the in vivo anti-IBD efficacy of EB-WE was assessed using a DSS-induced mouse model, in which colonic inflammation and NLRP3-mediated responses were prominent. Oral administration of EB-WE (2 or 5 mg/day) markedly ameliorated clinical symptoms, such as weight loss, diarrhea, and rectal bleeding, and significantly reduced the disease activity index (DAI). EB-WE also decreased serum pro-inflammatory cytokine levels and the expression of NLRP3 inflammasome-related molecules in colon tissue at both the gene and protein levels. In both BMDMs and the IBD mouse model, we further analyzed the upstream regulatory pathway involving NOX2-iNOS. EB-WE efficiently inhibited the activation of the NOX-iNOS axis and NF-κB phosphorylation, thereby alleviating inflammasome activation associated with DSS-induced oxidative stress and neutrophil/macrophage infiltration. Collectively, these results demonstrate that EB-WE effectively suppresses the formation and activation of the NLRP3 inflammasome by modulating the NOX-iNOS axis and the NF-κB pathway via antioxidant mechanisms. These findings suggest that EB-WE holds promise as a novel marine-derived natural therapeutic agent for the treatment of chronic inflammatory diseases. Full article

This study provides a comprehensive assessment of the impacts of COVID-19 pandemic-induced lockdowns on urban air quality at Marienplatz in Stuttgart, Germany, from 2018 to 2022. Utilizing high-resolution temporal datasets and advanced analytical techniques, including meteorological normalization and Shapley Additive Explanations (SHAP), the research disentangles the effects of emission reductions from meteorological variability on key atmospheric pollutants (CO, NO, NO₂, O₃, PM2.5, PM10). The findings reveal that the lockdown phases resulted in pronounced and significant reductions in primary traffic-related pollutants, with CO and NO concentrations declining by more than 50% relative to pre-pandemic baselines. In contrast, secondary pollutants, notably ozone, exhibited substantial increases (up to 50%), attributable to altered photochemical regimes and reduced NO_x titration, as confirmed by O_x-NO_x relationship analyses and photochemical sensitivity diagnostics. Particulate matter trends revealed limited short-term response, indicating persistent contributions from non-traffic sources such as residential heating and regional transport. Meteorologically normalized trends and SHAP analyses further confirmed that emission reductions, rather than meteorological fluctuations, were the primary drivers of the observed improvements in air quality. These insights highlight the transient and pollutant-specific nature of air-quality responses to abrupt emission reductions and provide critical scientific evidence to inform the design of robust, multi-sectoral urban air quality management and climate adaptation strategies in the post-pandemic era. Full article

Decarbonizing the maritime sector requires not only adopting alternative fuels and propulsion technologies but also quantitatively assessing their impacts on coastal and urban air quality. This study develops a stochastic, time-resolved air-quality modelling framework to evaluate ship-related pollutant dispersion in port environments. The approach integrates Automatic Identification System (AIS) trajectories, vessel-specific emission factors, and meteorological inputs within a moving-source Gaussian dispersion model to simulate the spatio-temporal evolution of pollutant concentrations. A 24 h case study for the Ports of Los Angeles and Long Beach demonstrates highly intermittent emission behaviour, with peak aggregated emission rates reaching approximately 1.2 kg/s for CO₂ and 3.8 g/s for SO₂. Temporally integrated concentration fields reveal maximum cumulative dosages of 0.145 g·s/m³ for NO_x, 0.023 g·s/m³ for SO₂, 0.014 g·s/m³ for total PM, and 7.5 g·s/m³ for CO₂ in near-port traffic corridors. Sensitivity analysis indicates that effective emission height variations alter cumulative exposure by up to 17%, whereas temporal resolution changes produce deviations below 7%, confirming numerical stability. Monte Carlo uncertainty propagation demonstrates bounded but non-negligible variability in exposure estimates under realistic emission and wind uncertainties. Results show that cumulative exposure patterns differ substantially from short-term concentration peaks, highlighting the importance of time-integrated and receptor-based metrics for port air quality assessment. The proposed AIS-driven stochastic framework provides a reproducible and computationally efficient tool for evaluating operational mitigation strategies and supporting evidence-based maritime decarbonization pathways. Full article

Human skin and hair act as multifunctional barriers but are highly sensitive to environmental pollutants originating from air, water, and cosmetic products. Epidemiological studies report that exposure to particulate matter (PM_2.5–PM₁₀), nitrogen oxides (NO_x), and volatile organic compounds increases the risk of skin and hair disorders. For instance, women in high-traffic areas (N = 211) show significantly more pigment spots and nasolabial wrinkles compared to those in rural areas (N = 189), indicating accelerated skin ageing. Children aged 9–11 exposed to PM₁₀, benzene, and NO_x exhibit increased incidence of atopic dermatitis. Systemic exposure to dioxins causes chloracne, while co-exposure to polycyclic aromatic hydrocarbons (PAHs) and UVA radiation elevates skin cancer risk. Psoriasis flares are associated with mean pollutant concentrations over the 60 days preceding flare events in 957 patients, and hyperpigmentation prevalence increases in populations exposed to traffic-related PM and ROS-inducing pollutants. Hair loss is linked to oxidative stress from PM and PAHs absorbed on hair fibers, with in vitro studies showing keratinocyte apoptosis in scalp hair follicles. This review evaluates natural adsorbents such as zeolites, clays, activated carbon, and polyphenol-rich plant extracts for anti-pollution cosmetic formulations. Adsorption capacities range from 60 to 150 mg·g⁻¹ depending on the pollutant, with removal efficiencies of 30–55% in model topical systems. Mechanisms include ion exchange, surface adsorption, hydrophobic interactions, and radical scavenging. Incorporating 2–5% w/w of these adsorbents in cosmetic formulations significantly reduces pollutant deposition on skin and hair. These findings support the development of evidence-based, sustainable anti-pollution cosmetic strategies that quantitatively mitigate environmental stressor effects. Full article

To evaluate the risk of cardiorespiratory mortality associated with exposure to air pollution produced by a cement plant, a population-based retrospective cohort study was conducted in an area of southern Italy (n = 29,495; follow-up 2006–2019; person-years = 317,810). Exposure areas were defined using the quartiles of the spatial distribution of the nitrogen oxide (NO_x) mean concentration in 2016 as a proxy for the cement plant’s emissions and estimated using a meteorological–atmospheric dispersion model. The relationship between NO_x and cause-specific mortality was quantified with time-dependent, sex-specific Cox regression analyses, controlling for age and proxies of socioeconomic deprivation and traffic pollution, accompanied by the confidence interval at 95% probability (CI95%) and an indicator (1 − p value) with values between 0 and 1, representing the likelihood of having a risk association. In the most exposed area, excesses of circulatory system diseases [men: HR = 1.60 (IC95% 1.24–2.06; 1 − p = 0.999); women: HR = 1.17 (0.93–1.48; 0.823)], heart diseases [men: HR = 1.66 (1.21–2.30; 0.998); women: HR = 1.24 (0.93–1.67; 0.855)], cerebrovascular diseases [men: HR = 2.11 (1.27–3.53; 0.996); women: HR = 1.52 (0.99–2.34; 0.946)], and acute respiratory diseases in women (HR = 2.46 (0.91–6.66; 0.924) were observed. The results, in line with the literature, suggest a deeper assessment of the potential impact of the cement plant, reinforcing the study design. Full article

This study develops and optimizes a hybrid plant that couples a recompression sCO₂ Brayton cycle to a central-tower particle receiver with a bottoming Organic Rankine Cycle (ORC), including environmental and exergy balances. The two scenarios revealed Pareto points that raised the exergy efficiency to 0.65 in winter and reduced the fuel flow to 15 kg/s. Scenario number two achieves an overall thermal efficiency of 0.50 with total daily emissions of 2520 t CO₂ and 2850 kg NO_x, enabling nearly constant net power. Exergy destruction is concentrated in the high-temperature recuperator (HTR) and ORC turbines (27% each) and the ORC condenser (25%). Compared to a non-optimized baseline, the best solutions increased the ORC and Brayton efficiencies by 6.8–12.66% and 33.4–33.5%, respectively; cut gas-turbine power by 34% and ORC power to 10%; and lowered daily CO₂ and NO_x emissions by 52%. The gains stem from the coordinated adjustments of key levers: lower gas-turbine inlet temperature (about 10%), reduced Brayton mass flow (23%), and tuned ORC turbine inlet pressure. Full article

Background/Objectives: Xu Chunfu’s Modified Xianglian Pill (XXLP) has been used for centuries in Chinese medicine to treat “diarrhea” and “dysentery,” conditions analogous to modern ulcerative colitis (UC). However, the scientific basis for its efficacy and mechanisms remains unclear. Methods: The chemical composition of XXLP was analyzed via UPLC-ESI-MS/MS. A colitis mouse model was established using DSS, and the therapeutic effects were assessed based on body weight, disease activity index (DAI), colon length, and histopathology. Inflammatory cytokines were measured using ELISA. Proteomic analysis and molecular docking identified key targets, which were validated using LPS-induced HT-29 cells via Western blot (WB), qRT-PCR, immunofluorescence (IF), and transmission electron microscopy (TEM). Gut microbiota composition was analyzed using 16S rRNA gene sequencing. Results: Analysis of XXLP led to the detection of 373 compounds. XXLP significantly improved colitis symptoms, including weight loss and colon shortening, and reduced the concentrations of inflammatory markers IL-1β, IL-18, TNF-α, and IL-6. Proteomics and molecular docking identified NADPH oxidase 2 (NOX2) as a key target of XXLP intervention in mice with colitis. qRT-PCR, WB, IF, and TEM results further confirmed that XXLP effectively suppressed the expression of NOX2 and its associated protein levels. Sequencing analysis of 16S rRNA showed that XXLP significantly increased the relative abundance of beneficial bacterial genera (Muribaculaceae and Ruminococcaceae) while markedly reducing the levels of harmful bacteria (Enterobacteriaceae). Correlation analysis revealed that specific microorganisms were correlated with NOX2-related protein expression and severity of colonic inflammation. Conclusions: XXLP effectively alleviates colitis by suppressing inflammatory responses. Its mechanism involves regulating the NOX2/ROS/mitochondria/NLRP3 axis and altering gut microbiota composition, providing novel insights for colitis treatment. Full article

Vehicular emissions are a significant anthropogenic source of air pollutants in South Africa, driven by urbanisation and industrialisation. Thulamela Municipality in Limpopo Province faces increasing air quality challenges associated with rising vehicle kilometres travelled (VKT) and population growth. A reliable baseline emission inventory is therefore required to inform effective air quality management. This study quantified emissions and developed a vehicular emission inventory (VEI) for Thulamela Municipality using a bottom-up approach for the period 2012–2021. VKT was estimated using odometer readings obtained through a questionnaire-based seven-day vehicle survey, together with registered vehicle population data from the National Traffic Information System (NaTIS). Results indicate that VKT increased over the study period, with light-duty vehicles (LDVs) contributing the most, followed by passenger cars (PCs), heavy-duty vehicles (HDVs), and heavy-passenger vehicles (HPVs). Cumulative emissions of CO, NO_x, PM₁₀, PM_2.5, and SO₂ over the 10 years were 32,781.1, 22,326.0, 1367.8, 1291.7, and 547.2 tons, respectively, with growth rates ranging from 39% to 41%. In 2021, total vehicular emissions reached 6647.6 tons, dominated by CO (56%) and NO_x (38%), with PM₁₀ (3%), PM_2.5 (2%), and SO₂ (1%). LDVs contributed 82% of total emissions, followed by PCs (9%), HDVs (6%), and HPVs (3%). A positive correlation between vehicle numbers and Gross Domestic Product (GDP) further suggests that economic growth is associated with higher emissions. These findings show that vehicular emissions are a key contributor to air pollution in the area and highlight the need for targeted mitigation strategies to improve air quality and protect public health. Full article

Urban business-to-business distribution in Casablanca relies heavily on light commercial vehicles (LCVs) operating in a constrained street environment where loading/unloading access, intersection capacity, and recurring bottlenecks jointly shape performance and environmental impacts. However, high-resolution freight origin–destination (OD) observations and junction calibration data are limited, which complicates direct estimations of congestion and externalities attributable to commercial activity. This study develops a reproducible, large-scale modeling workflow that couples tour-based freight demand generation in order units with simulation-based traffic assignment (SBA) on a metropolitan network and translates network performance into emissions and monetary losses. Warehouses are modeled as primary producers and commercial activity zones as attractors via sector-tagged production and attraction functions; the resulting order distribution is converted to OD vehicle trips using the tour-based trip generation procedure with the mean targets-per-tour fixed to one to ensure numerical stability, yielding a direct-shipment approximation appropriate for stress–response analysis. Junction impedance is represented through turn-type volume–delay relationships and node-level impedance procedures, and congestion is evaluated using vehicle kilometers traveled/vehicle hours traveled (VKT/VHT)-based indicators, delay-intensity measures, and link/node bottleneck rankings. Across demand-scaling scenarios, VKT increases from 302,159 to 1,017,686 veh·km/day, while network delay rises nonlinearly from 392.5 to 2738.4 veh·h/day, indicating saturation-driven amplification of time losses. The Handbook of Emission Factors for Road Transport (HBEFA)-compatible emission estimates scale with activity: total carbon dioxide (CO₂) increases from 154.1 to 519.5 t/day, and nitrogen oxides (NOx) and particulate matter (PM_2.5) totals rise proportionally under fixed fleet assumptions. Monetizing delay with a purchasing-power-adjusted value-of-time range yields a congestion cost per trip that increases from approximately 0.20 to 0.41 Moroccan dirham, MAD/trip (at 60 MAD/veh·h), consistent with rising delay intensity. Bottleneck extraction shows welfare losses to be structurally concentrated on a small persistent corridor set, led by ‘Boulevard de la Résistance’, with recurrent hotspots including ‘Rue d’Arcachon’ and ‘Rue d’Ifni’. The framework supports policy-relevant reporting of congestion, emissions, and welfare impacts under data scarcity, with explicit sensitivity bounds. Full article