Search Results (1,915)

Fine particulate matter (PM_2.5) exposure has been linked to increased lung damage due to compromised vascular barrier function, while 3-deoxysappanchalcone (3-DSC), a chalcone derived from Caesalpinia sappan, is known for its pharmacological benefits such as anti-cancer, anti-inflammatory, and antioxidant effects; however, its potential role in mitigating PM_2.5-induced pulmonary damage remains unexplored. To confirm the inhibitory effects of 3-DSC on PM_2.5-induced pulmonary injury, this research focused on evaluating how 3-DSC influences PM_2.5-induced disruption of the barrier of the endothelial cells (ECs) in the lungs and the resulting pulmonary inflammation. Permeability, leukocyte migration, proinflammatory protein activation, reactive oxygen species (ROS) generation, and histology were assessed in PM_2.5-treated ECs and mice. This study demonstrated that 3-DSC effectively neutralized the reactive oxygen species (ROS) generated by PM_2.5 exposure in the lung endothelial cells, suppressing ROS-triggered p38 MAPK activation while enhancing Akt signaling pathways critical to preserving vascular barrier function. In animal models, 3-DSC administration markedly decreased vascular permeability, attenuated the influx of immune cells into the lung tissue, and lowered inflammatory mediators like cytokines in the airways of PM_2.5-exposed mice. These data suggest that 3-DSC might exert protective effects on PM_2.5-induced inflammatory lung injury and vascular hyperpermeability. Full article

Ultrahigh resolution fine particulate matter (PM_2.5) mass concentration remote sensing products are crucial for atmospheric environmental monitoring, pollution source verification, health exposure risk assessment, and other fine-scale applications in urban environments. This study developed an ultrahigh resolution retrieval algorithm to estimate 30 m resolution PM_2.5 mass concentrations over urban areas from Landsat-8 and Sentinel-2A/B satellite measurements. The algorithm utilized aerosol optical depth (AOD) products retrieved from the Landsat-8 OLI and Sentinel-2 MSI measurements from 2017 to 2020, combined with multi-source auxiliary data to establish a PM_2.5-AOD relationship model across China. The results showed an overall high coefficient of determination (R²) of 0.82 and 0.76 for the model training accuracy based on samples and stations, respectively. The model prediction accuracy in Beijing and Wuhan reached R² values of 0.86 and 0.85. Applications in both cities demonstrated that ultrahigh resolution PM_2.5 has significant advantages in resolving fine-scale spatial patterns of urban air pollution and pinpointing pollution hotspots. Furthermore, an analysis of point source pollution at a typical heavy pollution emission enterprise confirmed that ultrahigh spatial resolution PM_2.5 can accurately identify the diffusion trend of point source pollution, providing fundamental data support for refined monitoring of urban air pollution and air pollution prevention and control. Full article

Background: As a well-known environmental hazard, ambient fine particulate matter (PM_2.5, aerodynamic diameter ≤ 2.5 µm) has been positively correlated with an increased risk of digestive system diseases, including appendicitis, inflammatory bowel disease, and gastrointestinal cancer. Additionally, PM_2.5 exposure has been shown to alter microbiota composition and diversity in human and animal models. However, its impact on goblet cells and gut mucus barrier integrity remains unclear. Methods: To address this, 8-week-old male and female interleukin-10 knockout (IL10^−/−) mice, serving as a spontaneous colitis model, were exposed to concentrated ambient PM_2.5 or filtered air (FA) in a whole-body exposure system for 17 weeks. Colon tissues from the PM_2.5-exposed mice and LS174T goblet cells were analyzed using H&E staining, transmission electron microscopy (TEM), and transcriptomic profiling. Results: The average PM_2.5 concentration in the exposure chamber was 100.20 ± 13.79 µg/m³. PM_2.5 exposure in the IL10^−/− mice led to pronounced colon shortening, increased inflammatory infiltration, ragged villi brush borders, dense goblet cells with sparse enterocytes, and lipid droplet accumulation in mitochondria. Similar ultrastructure changes were exhibited in the LS174T goblet cells after PM_2.5 exposure. Transcriptomic analysis revealed a predominantly upregulated gene expression spectrum, indicating an overall enhancement rather than suppression of metabolic activity after PM_2.5 exposure. Integrated enrichment analyses, including GO, KEGG, and GSEA, showed enrichment in pathways related to oxidative stress, xenobiotic (exogenous compound) metabolism, and energy metabolism. METAFlux, a metabolic activity analysis, further substantiated that PM_2.5 exposure induces a shift in cellular energy metabolism preference and disrupts redox homeostasis. Conclusions: The findings of exacerbated gut barrier impairment and goblet cell dysfunction following PM_2.5 exposure provide new evidence of environmental factors contributing to colitis, highlighting new perspectives on its role in the pathogenesis of colitis. Full article

With the ongoing advancement of industrialization and rapid urbanization, the emission of volatile organic compounds (VOCs) has increased significantly. As key precursors of PM_2.5 and ozone formation, VOCs pose a growing threat to the health of ecosystems. Due to their complex and dynamic transformation processes across air, water, and soil media, the ecological risks associated with VOCs have attracted increasing attention from both the scientific community and policy-makers. This study systematically reviews the core literature on the ecological impacts of VOCs published between 2005 and 2024, based on data from the Web of Science and Google Scholar databases. Utilizing three bibliometric tools (CiteSpace, VOSviewer, and Bibliometrix), we conducted a comprehensive visual analysis, constructing knowledge maps from multiple perspectives, including research trends, international collaboration, keyword evolution, and author–institution co-occurrence networks. The results reveal a rapid growth in the ecological impact of VOCs (EIVOCs), with an average annual increase exceeding 11% since 2013. Key research themes include source apportionment of air pollutants, ecotoxicological effects, biological response mechanisms, and health risk assessment. China, the United States, and Germany have emerged as leading contributors in this field, with China showing a remarkable surge in research activity in recent years. Keyword co-occurrence and burst analyses highlight “air pollution”, “exposure”, “health”, and “source apportionment” as major research hotspots. However, challenges remain in areas such as ecosystem functional responses, the integration of multimedia pollution pathways, and interdisciplinary coordination mechanisms. There is an urgent need to enhance monitoring technology integration, develop robust ecological risk assessment frameworks, and improve predictive modeling capabilities under climate change scenarios. This study provides scientific insights and theoretical support for the development of future environmental protection policies and comprehensive VOCs management strategies. Full article

Exposure to fine particulate matter (PM_2.5) is linked to metabolic dysfunction, yet evidence on its impact on hormonal regulation remains limited. This study examined seasonal changes in insulin, adiponectin, leptin, and HOMA-IR levels among healthy individuals and those with metabolic syndrome (MS) in Chiang Mai, Thailand. Fifty participants (25 healthy, 25 with MS) were assessed during high (February–April)- and low (May–July)-PM_2.5 seasons. Insulin levels increased in healthy individuals (mean: 9.3 to 14.9 µIU/mL; p = 0.051) and decreased in participants with MS (22.0 to 13.7 µIU/mL; p = 0.214), with a significant interaction effect (p = 0.020). Leptin increased significantly in both groups, but more markedly in the MS group (p < 0.001), also with a significant interaction (p < 0.001). HOMA-IR rose significantly in healthy individuals (p = 0.036) but not in participants with MS. Adiponectin remained stable across groups and seasons. At baseline, the MS group had significantly higher rates of diabetes (p = 0.050), hypertension (p = 0.001), and hyperlipidemia (p = 0.049). These findings suggest that PM_2.5 may influence metabolic and hormonal profiles, particularly in individuals with existing metabolic disorders. Full article

The air quality within urban public transport is a critical determinant of passenger health. In the crowded and poorly ventilated cabins of Almaty’s metro, buses, and trolleybuses, concentrations of CO₂ and PM_2.5 often accumulate, elevating the risk of respiratory and cardiovascular diseases. This study investigates the air quality along three of the city’s busiest transport corridors, analyzing how the concentrations of CO₂, PM_2.5, and PM₁₀, as well as the temperature and relative humidity, fluctuate with the passenger density and time of day. Continuous measurements were collected using the Tynys mobile IoT device, which was bench-calibrated against a commercial reference sensor. Several machine learning models (logistic regression, decision tree, XGBoost, and random forest) were trained on synchronized environmental and occupancy data, with the XGBoost model achieving the highest predictive accuracy at 91.25%. Our analysis confirms that passenger occupancy is the primary driver of in-cabin pollution and that these machine learning models effectively capture the nonlinear relationships among environmental variables. Since the surveyed routes serve Almaty’s most densely populated districts, improving the ventilation on these lines is of immediate importance to public health. Furthermore, the high-temporal-resolution data revealed short-term pollution spikes that correspond with peak ridership, advancing the current understanding of exposure risks in transit. These findings highlight the urgent need to combine real-time monitoring with ventilation upgrades. They also demonstrate the practical value of using low-cost IoT technologies and data-driven analytics to safeguard public health in urban mobility systems. Full article

This study investigates the health impacts of air pollution in the Greater Athens Area (GAA), Greece, by estimating the Relative Risk (RR) of hospital admissions (HA) for cardiovascular (CVD) and respiratory diseases (RD) from 2018 to 2020. The analysis focuses on daily exceedances of key air pollutants—PM₁₀, O₃, and NO₂—based on the “Fair” threshold and above, as defined by the European Union Air Quality Index (EU AQI). Data from ten monitoring stations operated by the Ministry of Environment and Energy were spatially matched with six hospitals across the GAA. A Distributed Lag Non-linear Model (DLNM) was employed to capture both the delayed and non-linear exposure–response (ER) relationships between pollutant exceedances and daily HA. Additionally, the synergistic effects of pollutant interactions were assessed to provide a more comprehensive understanding of cumulative health risks. The combined exposure term showed a peak RR of 1.49 (95% CI: 0.79–2.78), indicating a notable amplification of risk when multiple pollutants exceed thresholds simultaneously. The study utilizes R for data processing and statistical modeling. Findings aim to inform public health strategies by identifying critical exposure thresholds and time-lagged effects, ultimately supporting targeted interventions in urban environments experiencing air quality challenges. Full article

Clean and safe air quality is essential for public health, yet particulate matter (PM) significantly degrades air quality and poses serious health risks. The Gulf Cooperation Council (GCC) countries are particularly vulnerable to frequent and intense dust storms due to their vast desert landscapes. This study presents the first health risk assessment of carcinogenic and non-carcinogenic risks associated with exposure to PM2.5 and PM10 bound heavy metals and polycyclic aromatic hydrocarbons (PAHs) based on air quality data collected during the years of 2016–2018 near Dubai International Airport and Abu Dhabi International Airport. The results reveal no significant carcinogenic risks for lead (Pb), cobalt (Co), nickel (Ni), and chromium (Cr). Additionally, AI-based regression analysis was applied to time-series dust monitoring data to enhance predictive capabilities in environmental monitoring systems. The estimated incremental lifetime cancer risk (ILCR) from PAH exposure exceeded the acceptable threshold (10⁻⁶) in several samples at both locations. The relationship between visibility and key environmental variables—PM1, PM2.5, PM10, total suspended particles (TSPs), wind speed, air pressure, and air temperature—was modeled using three machine learning algorithms: linear regression, support vector machine (SVM) with a radial basis function (RBF) kernel, and artificial neural networks (ANNs). Among these, SVM with an RBF kernel showed the highest accuracy in predicting visibility, effectively integrating meteorological data and particulate matter variables. These findings highlight the potential of machine learning models for environmental monitoring and the need for continued assessments of air quality and its health implications in the region. Full article

Renewable energy stands as a pivotal solution to environmental concerns, prompting substantial research and development endeavors to promote its adoption and enhance energy efficiency. Despite the recognized environmental superiority of renewable energy systems, there is a lack of globally standardized indicators specifically focused on renewable energy efficiency. This study aims to develop and apply a non-parametric data envelopment analysis (DEA) indicator, termed the Renewable Energy Indicator (REI), to measure environmental performance at the national level and to identify differences in renewable energy efficiency across countries grouped by development status and income level. The REI incorporates new factors such as agricultural methane emissions (thousand metric tons of ${\mathrm{CO}}_2$ equivalent), PM2.5 air pollution exposure (µg/m³), and aspects related to electricity, including consumption (as % of total final energy consumption), production from renewable sources, excluding hydroelectric (kWh), and accessibility in rural and urban areas (% of population with access), aligning with the emerging paradigm outlined by the United Nations. By segmenting the REI into global, developmental, and income group classifications, this study conducts the Mann–Whitney U test and the Kruskal–Wallis H tests to identify variations in renewable energy efficiency among different country groups. Our findings reveal top-performing countries globally, highlighting both developed (e.g., Sweden) and developing nations (e.g., Costa Rica, Sri Lanka). Central and North European countries demonstrate high efficiency, while those facing political and economic instability perform poorly. Agricultural-dependent nations like Australia and Argentina exhibit lower REI due to significant methane emissions. Disparities between developed and developing markets underscore the importance of understanding distinct socio-economic dynamics for effective policy formulation. Comparative analysis across income groups informs specific strategies tailored to each category. Full article

We report the first case of pleural mesothelioma (PM) occurring in a child affected by NF2-related schwannomatosis (NF2-SWN) and without any history of environmental exposure to asbestos. Mesothelioma is a rare secondary tumor in brain cancer patients and the association with NF2-SWN has been described only in a few anecdotal cases and never in the pediatric field. NF2-SWN is an autosomal dominant disease caused by inactivating germline mutations of the NF2 tumor suppressor gene, one of the most common mutations associated with human primary mesothelioma too. By MLPA assay, array-CGH analysis, and NGS on blood and tumor DNA, we determined the mutation profile of this rare NF2-driven PM and we identified several atypical chromosomal aberrations in tumor cells, suggesting a different genomic signature between pediatric and adult mesothelioma. Full article

Particulate matter (PM), polycyclic aromatic hydrocarbons (PAHs), and heavy metals (HMs) present in polluted air are strongly associated with an increased risk of respiratory diseases. In our study, we grouped cities based on their pollution levels using a method called Ward’s cluster analysis and looked at the increased cancer risk from PM₁₀-bound harmful substances for adult men and women living in Polish cities. The analysis was based on data from 8 monitoring stations where concentrations of PM₁₀, PAHs, and HMs were measured simultaneously between 2018 and 2022. The cluster analysis made it possible to distinguish three separate agglomeration clusters: cluster I (Upper Silesia, Wroclaw) with the highest concentrations of heavy metals and PAHs, with mean levels of lead 14.97 ± 7.27 ng·m⁻³, arsenic 1.73 ± 0.60 ng·m⁻³, nickel 1.77 ± 0.95 ng·m⁻³, cadmium 0.49 ± 0.28 ng·m⁻³, and ∑PAHs 15.53 ± 6.44 ng·m⁻³, cluster II (Warsaw, Łódź, Lublin, Cracow) with dominant road traffic emissions and low emissions, with average levels of lead 8.00 ± 3.14 ng·m⁻³, arsenic 0.70 ± 0.17 ng·m⁻³, nickel 1.64 ± 0.96 ng·m⁻³, and cadmium 0.49 ± 0.28 ng·m⁻³, and cluster III (Szczecin, Tricity) with the lowest concentration levels with favourable ventilation conditions. All calculated ILCR values were in the range of 1.20 × 10⁻⁶ to 1.11 × 10⁻⁵, indicating a potential cancer risk associated with long-term exposure. The highest ILCR values were reached in Upper Silesia and Wroclaw (cluster I), and the lowest in Tricity, which was classified in cluster III. Our findings suggest that there are continued preventive actions and stricter air quality control. The results confirm that PM₁₀ is a significant carrier of airborne carcinogens and should remain a priority in both environmental and public health policy. Full article

Background/Objectives: Lung function decline is influenced by metabolic risk factors (e.g., obesity, hyperglycemia, dyslipidemia) and environmental exposures (e.g., PM2.5), which may jointly contribute to airway inflammation and lung function impairment. This study aimed to investigate these associations in northern Thai adults and identify factors linked to lung function impairment. Methods: A cross-sectional study was conducted in San Pa Thong, Chiang Mai, Thailand, involving 137 adults. Data on metabolic indicators and spirometry were collected. Statistical analyses included Spearman’s correlation, multivariable linear regression, and logistic regression. Results: Higher triglyceride levels and shorter 6-min walk test (6MWT) distances were associated with reduced forced expiratory volume in one second (FEV₁) and forced vital capacity (FVC). Only 6MWT distance remained a significant factor for lung function impairment in logistic regression (adjusted OR = 0.763, 95% CI: 0.588–0.990, p = 0.042). Conclusions: Combining metabolic and respiratory assessments may improve early detection of lung function impairment in high-risk populations, particularly given the dual burden of metabolic disorders and air pollution in northern Thailand. These findings support the integration of metabolic and respiratory screening in community health programs to enhance preventive strategies. Full article

Allergic sensitization (AS) to pets is a notable health concern, with a 10–30% prevalence in developed countries, significantly higher than in developing nations; however, the critical exposure windows and reasons for this global disparity remain unclear. This study aimed to investigate associations between perinatal and current animal exposure and childhood AS among 2598 preschoolers (aged 3–6) in Changsha, China. Data on AS and pet exposure were gathered via questionnaires, while children’s prenatal and current exposure to outdoor air pollutants (PM₁₀, NO₂) was estimated from monitoring stations. Multiple logistic regression models revealed an overall AS prevalence of 1.8%. Current animal or pet exposure was significantly associated with childhood AS (adjusted OR 2.40, 95% CI 1.12–4.29). Conversely, no significant association was found for perinatal exposure. Intriguingly, a stratified analysis showed that the association with current exposure was significant only in children exposed to low levels of outdoor PM₁₀ (adj. OR 2.97, 95% CI 1.21–7.27) and NO₂ (adj. OR 3.01, 95% CI 1.23–7.37). The study concludes that current exposure to pets significantly increases childhood AS risk. This effect is unexpectedly magnified in environments with low outdoor air pollution. This novel finding not only may explain the higher prevalence of pet allergies in developed countries but also suggests that as air quality improves alongside rising pet ownership, developing nations like China could face a significant future increase in pet sensitization, highlighting a critical emerging public health challenge. Full article

Neuroinflammation is a key process in Alzheimer’s disease (AD). We aimed to examine the development and evaluation of a comprehensive in vitro model that captures the complex interplay between neurons and immune cell types. Retinoic acid-differentiated SH-SY5Y neuroblastoma cells exposed to LPS-conditioned media (CM) from RAW264.7 macrophages, BV2 microglia, and HL60 promyelocytic cells differentiated into neutrophil- or monocyte-like phenotypes were analyzed. The effects of CM containing inflammatory factors on neuronal viability and function were systematically evaluated. Neuronal oxidative stress, mitochondrial function, autophagy and protein aggregates were analyzed. The involvement of insulin resistance was studied by assaying glucose uptake and determining its IC₅₀ values for cell viability improvement and GSK3β phosphorylation. After short-term exposure (3 h), most inflammatory CMs induced peroxide production in neurons, with the strongest effect observed in media from DMSO- or RA-differentiated HL60 cells. Mitochondrial membrane potential was markedly reduced by LPS-stimulated BV2 and HL60-derived CMs. Prolonged exposure (72 h) revealed partial normalization of oxidative stress and mitochondrial membrane potential. Glucose uptake was significantly impaired in cells treated with LPS-activated RAW264.7, BV2, and DMSO-differentiated HL60 cell media, while insulin partially rescued this effect, except for the CM of BV2 cells. Notably, insulin IC₅₀ increased dramatically under LPS-treated BV2 cells induced inflammation (35 vs. 198 pM), confirming the development of insulin resistance. Immune cell-specific inflammation causes distinct effects on neuronal oxidative stress, mitochondrial function, protein aggregation, insulin signaling and viability. LPS-activated BV2-derived CM best recapitulates AD-related pathology, offering a relevant in vitro model for further studies. Full article

Particulate matter (PM) and volatile organic compounds (VOCs) are major air pollutants that can cause significant risks to public health. To mitigate exposure, fibrous filters have been widely utilized for air purification. In this study, we developed electrospun silk fibroin/poly (ethylene oxide)/cyclodextrin (SF/PEO/CD) nanofibers as multifunctional air filters capable of efficiently reducing PM_2.5 and degrading VOCs. The resulting SF/PEO/10CD demonstrated the best multifunctional filtration performance, achieving PM_2.5 capture efficiencies of 91.3% with a minimal pressure drop of 4 Pa and VOC removal efficiency of 50%. These characteristics highlight the potential of the SF/PEO/10CD nanofiber with effective, multifunctional properties and environmental benefits for sustainable air filtration application. Full article