The stress-responsive cytotoxic effect of diesel exhaust particles on lymphatic endothelial cells.

Diesel exhaust particles (DEPs) are very small (typically < 0.2 µm) fragments that have become major air pollutants. DEPs are comprised of a carbonaceous core surrounded by organic compounds such as polycyclic aromatic hydrocarbons (PAHs) and nitro-PAHs. Inhaled DEPs reach the deepest sites in the respiratory system where they could induce respiratory/cardiovascular dysfunction. Additionally, a previous study has revealed that a portion of inhaled DEPs often activate immune cells and subsequently induce somatic inflammation. Moreover, DEPs are known to localize in lymph nodes. Therefore, in this study we explored the effect of DEPs on the lymphatic endothelial cells (LECs) that are a constituent of the walls of lymph nodes. DEP exposure induced cell death in a reactive oxygen species (ROS)-dependent manner. Following exposure to DEPs, next-generation sequence (NGS) analysis identified an upregulation of the integrated stress response (ISR) pathway and cell death cascades. Both the soluble and insoluble components of DEPs generated intracellular ROS. Three-dimensional Raman imaging revealed that DEPs are taken up by LECs, which suggests internalized DEP cores produce ROS, as well as soluble DEP components. However, significant cell death pathways such as apoptosis, necroptosis, ferroptosis, pyroptosis, and parthanatos seem unlikely to be involved in DEP-induced cell death in LECs. This study clarifies how DEPs invading the body might affect the lymphatic system through the induction of cell death in LECs.

PM2.5 regulates the progression of lung adenocarcinoma through the axis of HCG18, miR-195 and ATG14.

Relevant studies have indicated the association of HCG18 with tumour occurrence and progression. In this study, we observed that PM2.5 can enhance the growth of lung adenocarcinoma cells by modulating the expression of HCG18. Further investigations, including overexpression and knockout experiments, elucidated that HCG18 suppresses miR-195, which in turn upregulates the expression of ATG14, resulting in the upregulation of autophagy. Consequently, exposure to PM2.5 leads to elevated HCG18 expression in lung tissues, which in turn increases Atg14 expression and activates autophagy pathways through inhibition of miR-195, thereby contributing to oncogenesis.

Accumulation of Atmospheric PAHs in White Mustard - Can the Seeds Be Affected?

Traffic-related particulate matter emissions have been considerably reduced due to stringent regulations in Europe. However, emission of diesel-powered vehicles still poses a significant environmental threat, affecting rural ecosystems and agriculture. Several studies have reported that polycyclic aromatic hydrocarbons (PAHs), a group of potentially toxic organic compounds, can accumulate in crops and vegetables. In our study, white mustard (Sinapis alba L.) plants were experimentally treated with an extract of diesel exhaust. PAH concentrations were measured in the different plant compartments (stems, leaves and seeds), bioconcentration factors (BCFs) were also calculated. Significant accumulation was measured in the leaves and seeds, stems showed lower accumulation potential. All plant matrices showed high tendency to accumulate higher molecular weight PAHs, BCF was the highest in the 6-ring group. The fact that considerable accumulation was experienced in the seeds might show the risk of cultivating crops nearby roads highly impacted by traffic-related emissions.

Long-term exposure to PM2.5 and mortality in a national cohort in South Korea: effect modification by community deprivation, medical infrastructure, and greenness.

BACKGROUND: Long-term exposure to PM2.5 has been linked to increased mortality risk. However, limited studies have examined the potential modifying effect of community-level characteristics on this association, particularly in Asian contexts. This study aimed to estimate the effects of long-term exposure to PM2.5 on mortality in South Korea and to examine whether community-level deprivation, medical infrastructure, and greenness modify these associations. METHODS: We conducted a nationwide cohort study using the National Health Insurance Service-National Sample Cohort. A total of 394,701 participants aged 30 years or older in 2006 were followed until 2019. Based on modelled PM2.5 concentrations, 1 to 3-year and 5-year moving averages of PM2.5 concentrations were assigned to each participant at the district level. Time-varying Cox proportional-hazards models were used to estimate the association between PM2.5 and non-accidental, circulatory, and respiratory mortality. We further conducted stratified analysis by community-level deprivation index, medical index, and normalized difference vegetation index to represent greenness. RESULTS: PM2.5 exposure, based on 5-year moving averages, was positively associated with non-accidental (Hazard ratio, HR: 1.10, 95% Confidence Interval, CI: 1.01, 1.20, per 10 µg/m3 increase) and circulatory mortality (HR: 1.22, 95% CI: 1.01, 1.47). The 1-year moving average of PM2.5 was associated with respiratory mortality (HR: 1.33, 95% CI: 1.05, 1.67). We observed higher associations between PM2.5 and mortality in communities with higher deprivation and limited medical infrastructure. Communities with higher greenness showed lower risk for circulatory mortality but higher risk for respiratory mortality in association with PM2.5. CONCLUSIONS: Our study found mortality effects of long-term PM2.5 exposure and underlined the role of community-level factors in modifying these association. These findings highlight the importance of considering socio-environmental contexts in the design of air quality policies to reduce health disparities and enhance overall public health outcomes.

Short-term prediction of PM2.5 concentration by hybrid neural network based on sequence decomposition.

Accurate forecasting of PM2.5 concentrations serves as a critical tool for mitigating air pollution. This study introduces a novel hybrid prediction model, termed MIC-CEEMDAN-CNN-BiGRU, for short-term forecasting of PM2.5 concentrations using a 24-hour historical data window. Utilizing the Maximal Information Coefficient (MIC) for feature selection, the model integrates Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Convolutional Neural Network (CNN), and Bidirectional Recurrent Gated Neural Network (BiGRU) to optimize predictive accuracy. We used 2016 PM2.5 monitoring data from Beijing, China as the empirical basis of this study and compared the model with several deep learning frameworks. RNN, LSTM, GRU, and other hybrid models based on GRU, respectively. The experimental results show that the prediction results of the hybrid model proposed in this question are more accurate than those of other models, and the R2 of the hybrid model proposed in this paper improves the R2 by nearly 5 percentage points compared with that of the single model; reduces the MAE by nearly 5 percentage points; and reduces the RMSE by nearly 11 percentage points. The results show that the hybrid prediction model proposed in this study is more accurate than other models in predicting PM2.5.

The Long Hazy Tail: Analysis of the Impacts and Trends of Severe Outdoor and Indoor Air Pollution in North China.

China, especially the densely populated North China region, experienced severe haze events in the past decade that concerned the public. Although the most extreme cases have been largely eliminated through recent mitigation measures, severe outdoor air pollution persists and its environmental impact needs to be understood. Severe indoor pollution draws less public attention due to the short visible distance indoors, but its public health impacts cannot be ignored. Herein, we assess the trends and impacts of severe outdoor and indoor air pollution in North China from 2014 to 2021. Our results demonstrate the uneven contribution of severe hazy days to ambient and exposure concentrations of particulate matter with an aerodynamic diameter <2.5 (PM2.5). Although severe indoor pollution contributes to indoor PM2.5 concentrations (23%) to a similar extent as severe haze contributes to ambient PM2.5 concentrations (21%), the former's contribution to premature deaths was significantly higher. Furthermore, residential emissions contributed more in the higher PM2.5 concentration range both indoors and outdoors. Notably, severe haze had greater health impacts on urban residents, while severe indoor pollution was more impactful in rural areas. Our findings suggest that, besides reducing severe haze, mitigating severe indoor pollution is an important aspect of combating air pollution, especially toward improving public health.

Understanding the Disparities of PM2.5 Air Pollution in Urban Areas via Deep Support Vector Regression.

In densely populated urban areas, PM2.5 has a direct impact on the health and quality of residents' life. Thus, understanding the disparities of PM2.5 is crucial for ensuring urban sustainability and public health. Traditional prediction models often overlook the spillover effects within urban areas and the complexity of the data, leading to inaccurate spatial predictions of PM2.5. We propose Deep Support Vector Regression (DSVR) that models the urban areas as a graph, with grid center points as the nodes and the connections between grids as the edges. Nature and human activity features of each grid are initialized as the representation of each node. Based on the graph, DSVR uses random diffusion-based deep learning to quantify the spillover effects of PM2.5. It leverages random walk to uncover more extensive spillover relationships between nodes, thereby capturing both the local and nonlocal spillover effects of PM2.5. And then it engages in predictive learning using the feature vectors that encapsulate spillover effects, enhancing the understanding of PM2.5 disparities and connections across different regions. By applying our proposed model in the northern region of New York for predictive performance analysis, we found that DSVR consistently outperforms other models. During periods of PM2.5 surges, the R-square of DSVR reaches as high as 0.729, outperforming non-spillover models by 2.5 to 5.7 times and traditional spatial metric models by 2.2 to 4.6 times. Therefore, our proposed model holds significant importance for understanding disparities of PM2.5 air pollution in urban areas, taking the first steps toward a new method that considers both the spillover effects and nonlinear feature of data for prediction.

Determining the toxicological effects of indoor air pollution on both a healthy and an inflammatory-comprised model of the alveolar epithelial barrier in vitro.

Exposure to indoor air pollutants (IAP) has increased recently, with people spending more time indoors (i.e. homes, offices, schools and transportation). Increased exposures of IAP on a healthy population are poorly understood, and those with allergic respiratory conditions even less so. The objective of this study, therefore, was to implement a well-characterised in vitro model of the human alveolar epithelial barrier (A549 + PMA differentiated THP-1 incubated with and without IL-13, IL-5 and IL-4) to determine the effects of a standardised indoor particulate (NIST 2583) on both a healthy lung model and one modelling a type-II (stimulated with IL-13, IL-5 and IL-4) inflammatory response (such as asthma).Using concentrations from the literature, and an environmentally appropriate exposure we investigated 232, 464 and 608ng/cm2 of NIST 2583 respectively. Membrane integrity (blue dextran), viability (trypan blue), genotoxicity (micronucleus (Mn) assay) and (pro-)/(anti-)inflammatory effects (IL-6, IL-8, IL-33, IL-10) were then assessed 24 h post exposure to both models. Models were exposed using a physiologically relevant aerosolisation method (VitroCell Cloud 12 exposure system).No changes in Mn frequency or membrane integrity in either model were noted when exposed to any of the tested concentrations of NIST 2583. A significant decrease (p < 0.05) in cell viability at the highest concentration was observed in the healthy model. Whilst cell viability in the "inflamed" model was decreased at the lower concentrations (significantly (p < 0.05) after 464ng/cm2). A significant reduction (p < 0.05) in IL-10 and a significant increase in IL-33 was seen after 24 h exposure to NIST 2583 (464, 608ng/cm2) in the "inflamed" model.Collectively, the results indicate the potential for IAP to cause the onset of a type II response as well as exacerbating pre-existing allergic conditions. Furthermore, the data imposes the importance of considering unhealthy individuals when investigating the potential health effects of IAP. It also highlights that even in a healthy population these particles have the potential to induce this type II response and initiate an immune response following exposure to IAP.

Epidemiological trends and age-period-cohort effects on cardiovascular diseases burden attributable to ambient air pollution across BRICS.

Long-term exposure to ambient air pollution raises the risk of deaths and morbidity worldwide. From 1990 to 2019, we observed the epidemiological trends and age-period-cohort effects on the cardiovascular diseases (CVD) burden attributable to ambient air pollution across Brazil, Russia, India, China, and South Africa (BRICS). The number of CVD deaths related to ambient particulate matter (PM) pollution increased nearly fivefold in China [5.0% (95% CI 4.7, 5.2)] and India [5.7% (95% CI 5.1, 6.3)] during the study period. The age-standardized CVD deaths and disability-adjusted life years (DALYs) due to ambient PM pollution significantly increased in India and China but decreased in Brazil and Russia. Due to air pollution, the relative risk (RR) of premature CVD mortality (< 70 years) was higher in Russia [RR 12.6 (95% CI 8.7, 17.30)] and India [RR 9.2 (95% CI 7.6, 11.20)]. A higher period risk (2015-2019) for CVD deaths was found in India [RR 1.4 (95% CI 1.4, 1.4)] followed by South Africa [RR 1.3 (95% CI 1.3, 1.3)]. Across the BRICS countries, the RR of CVD mortality markedly decreased from the old birth cohort to young birth cohorts. In conclusion, China and India showed an increasing trend of CVD mortality and morbidity due to ambient PM pollution and higher risk of premature CVD deaths were observed in Russia and India.

PM2.5 toxicity in blood impairs cardiac redox balance and promotes mitochondrial dysfunction in rat heart that further aggravates ischemia reperfusion injury by modulating PI3K/AKT/mTOR/NF-kB signaling axis.

According to the pathophysiological mechanisms linking particulate matter (PM2.5) exposure and cardiovascular diseases, PM2.5 may directly translocate into the blood stream and remote target organs and thereby induce cardiovascular effects. The toxicity of PM2.5 is known to induce oxidative stress in pulmonary tissue, but its impact on the redox state in heart (distant organ) is unknown and how it modulates the cardiac response to ischemia reperfusion (IR) remains unclear. In the present study, we evaluated the toxic effect of PM2.5 on cardiac physiology in the presence and absence of IR after introducing PM2.5 into the blood. Female Wistar rats were injected with diesel particulate matter (DPM) via i.p & i.v routes at a concentration of 10 µg/ml. The toxic impact of PM2.5 not only adversely affects the cardiac ultra-structure (leading to nuclear infiltration, edema, irregularities in heart muscle and nuclear infiltration), but also altered the cellular redox balance, elevated inflammation and promoted the upregulation of proapoptotic mediator genes at the basal level of myocardium. The results showed alterations in cardiac ultrastructure, elevated oxidative stress and significant redox imbalance, increased inflammation and proapoptotic mediators at the basal level of myocardium. Moreover, the cardioprotective pro survival signaling axis was declined along with an increased NF-kB activation at the basal level. IR inflicted further injury with deterioration of cardiac hemodynamic indices (Heart rate [HR], Left ventricular developed pressure [LVDP], Left ventricular end-diastolic pressure [LVEDP] and rate pressure product [RPP]) along with prominent inactivation of signaling pathways. Furthermore, the levels of GSH/GSSG, NADH/NAD, NADPH/NADP were significantly low along with increased lipid peroxidation in mitochondria of PM2.5 treated IR rat hearts. This observation was supported by downregulation of glutaredoxin and peroxiredoxin genes in the myocardium. Similarly the presence of oxidative stress inducing metals was found at a higher concentration in cardiac mitochondria. Thus, the toxic impact of PM2.5 in heart augment the IR associated pathological changes by altering the physiological response, initiating cellular metabolic alterations in mitochondria and modifying the signaling molecules.

Salidroside Ameliorates Lung Injury Induced by PM 2.5by Regulating SIRT1-PGC-1α in Mice.

Objective: This study aimed to clarify the intervention effect of salidroside (SAL) on lung injury caused by PM 2.5 in mice and illuminate the function of SIRT1-PGC-1ɑ axis. Methods: Specific pathogen-free (SPF) grade male C57BL/6 mice were randomly assigned to the following groups: control group, SAL group, PM 2.5 group, SAL+PM 2.5 group. On the first day, SAL was given by gavage, and on the second day, PM 2.5 suspension was given by intratracheal instillation. The whole experiment consist of a total of 10 cycles, lasting 20 days. At the end of treatment, blood samples and lung tissues were collected and analyzed. Observation of pathological changes in lung tissue using inverted microscopy and transmission electron microscopy. The expression of inflammatory, antioxidants, apoptosis, and SIRT1-PGC-1ɑ proteins were detected by Western blotting. Results: Exposure to PM 2.5 leads to obvious morphological and pathologica changes in the lung of mice. PM 2.5 caused a decline in levels of antioxidant-related enzymes and protein expressions of HO-1, Nrf2, SOD2, SIRT1 and PGC-1ɑ, and an increase in the protein expressions of IL-6, IL-1ß, Bax, caspase-9 and cleaved caspase-3. However, SAL reversed the aforementioned changes caused by PM 2.5 by activating the SIRT1-PGC-1α pathway. Conclusion: SAL can activate SIRT1-PGC-1ɑ to ameliorate PM 2.5-induced lung injury.

Influence of meteorological variables and air pollutants on fog/smog formation in seven major cities of Indo-Gangetic Plain.

The Indo-Gangetic Plains (IGP) of the Indian subcontinent during winters experience widespread fog episodes. The low visibility is not only attributed to meteorological conditions but also to the increased pollution levels in the region. The study was carried out for Tier 1 and Tier II cities of the IGP of India, including Kolkata, Amritsar, Patiala, Hisar, Delhi, Patna, and Lucknow. This work analyzes data from 1990 to 2023 (33 years) employing the Mann-Kendall-Theil-Sen slope to determine the trends in fog occurrences and the relation between fog and meteorological parameters using multiple linear regressions. Furthermore, identifying the most relevant fog (visibility)-impacting factors from a set of both meteorological factors and air pollutants using step-wise regression. All cities indicated trend in the number of foggy days except for Kolkata. The multiple regression analysis reveals relatively low associations between fog occurrences and meteorological factors (30 to 59%), although the association was stronger when air pollution levels were considered (60 to 91%). Relative humidity, PM2.5, and PM10 have the most influence on fog formation. The study provides comprehensive insights into fog trends by incorporating meteorological data and air pollution analysis. The findings highlight the significance of acknowledging meteorological and pollution factors to understand and mitigate the impacts of reduced visibility. Hence, this information can guide policymakers, urban planners, and environmental management agencies in developing effective strategies to manage fog-related risks and improve air quality.

Ambient fine particulate matter and daily mortality: a comparative analysis of observed and estimated exposure in 347 cities.

BACKGROUND: Model-estimated air pollution exposure products have been widely used in epidemiological studies to assess the health risks of particulate matter with diameters of ≤2.5 µm (PM2.5). However, few studies have assessed the disparities in health effects between model-estimated and station-observed PM2.5 exposures. METHODS: We collected daily all-cause, respiratory and cardiovascular mortality data in 347 cities across 15 countries and regions worldwide based on the Multi-City Multi-Country collaborative research network. The station-observed PM2.5 data were obtained from official monitoring stations. The model-estimated global PM2.5 product was developed using a machine-learning approach. The associations between daily exposure to PM2.5 and mortality were evaluated using a two-stage analytical approach. RESULTS: We included 15.8 million all-cause, 1.5 million respiratory and 4.5 million cardiovascular deaths from 2000 to 2018. Short-term exposure to PM2.5 was associated with a relative risk increase (RRI) of mortality from both station-observed and model-estimated exposures. Every 10-µg/m3 increase in the 2-day moving average PM2.5 was associated with overall RRIs of 0.67% (95% CI: 0.49 to 0.85), 0.68% (95% CI: -0.03 to 1.39) and 0.45% (95% CI: 0.08 to 0.82) for all-cause, respiratory, and cardiovascular mortality based on station-observed PM2.5 and RRIs of 0.87% (95% CI: 0.68 to 1.06), 0.81% (95% CI: 0.08 to 1.55) and 0.71% (95% CI: 0.32 to 1.09) based on model-estimated exposure, respectively. CONCLUSIONS: Mortality risks associated with daily PM2.5 exposure were consistent for both station-observed and model-estimated exposures, suggesting the reliability and potential applicability of the global PM2.5 product in epidemiological studies.

Effects of extreme meteorological factors and high air pollutant concentrations on the incidence of hand, foot and mouth disease in Jining, China.

Background: The evidence on the effects of extreme meteorological conditions and high air pollution levels on incidence of hand, foot and mouth disease (HFMD) is limited. Moreover, results of the available studies are inconsistent. Further investigations are imperative to elucidate the specific issue. Methods: Data on the daily cases of HFMD, meteorological factors and air pollution were obtained from 2017 to 2022 in Jining City. We employed distributed lag nonlinear model (DLNM) incorporated with Poisson regression to explore the impacts of extreme meteorological conditions and air pollution on HFMD incidence. Results: We found that there were nonlinear relationships between temperature, wind speed, PM2.5, SO2, O3 and HFMD. The cumulative risk of extreme high temperature was higher at the 95th percentile (P95th) than at the 90th percentile(P90th), and the RR values for both reached their maximum at 10-day lag (P95th RR = 1.880 (1.261-2.804), P90th RR = 1.787 (1.244-2.569)), the hazardous effect of extreme low temperatures on HFMD is faster than that of extreme high temperatures. The cumulative effect of extreme low wind speeds reached its maximum at 14-day lag (P95th RR = 1.702 (1.389-2.085), P90th RR = 1.498(1.283-1.750)). The cumulative effect of PM2.5 concentration at the P90th was largest at 14-day lag (RR = 1.637 (1.069-2.506)), and the cumulative effect at the P95th was largest at 10-day lag (RR = 1.569 (1.021-2.411)). High SO2 concentration at the P95th at 14-day lag was associated with higher risk for HFMD (RR: 1.425 (1.001-2.030)). Conclusion: Our findings suggest that high temperature, low wind speed, and high concentrations of PM2.5 and SO2 are associated with an increased risk of HFMD. This study not only adds insights to the understanding of the impact of extreme meteorological conditions and high levels of air pollutants on HFMD incidence but also holds practical significance for the development and enhancement of an early warning system for HFMD.

Adopting electric school buses in the United States: Health and climate benefits.

Electric school buses have been proposed as an alternative to reduce the health and climate impacts of the current U.S. school bus fleet, of which a substantial share are highly polluting old diesel vehicles. However, the climate and health benefits of electric school buses are not well known. As they are substantially more costly than diesel buses, assessing their benefits is needed to inform policy decisions. We assess the health benefits of electric school buses in the United States from reduced adult mortality and childhood asthma onset risks due to exposure to ambient fine particulate matter (PM2.5). We also evaluate climate benefits from reduced greenhouse-gas emissions. We find that replacing the average diesel bus in the U.S. fleet in 2017 with an electric bus yields $84,200 in total benefits. Climate benefits amount to $40,400/bus, whereas health benefits amount to $43,800/bus due to 4.42*10-3 fewer PM2.5-attributable deaths ($40,000 of total) and 7.42*10-3 fewer PM2.5-attributable new childhood asthma cases ($3,700 of total). However, health benefits of electric buses vary substantially by driving location and model year (MY) of the diesel buses they replace. Replacing old, MY 2005 diesel buses in large cities yields $207,200/bus in health benefits and is likely cost-beneficial, although other policies that accelerate fleet turnover in these areas deserve consideration. Electric school buses driven in rural areas achieve small health benefits from reduced exposure to ambient PM2.5. Further research assessing benefits of reduced exposure to in-cabin air pollution among children riding buses would be valuable to inform policy decisions.

Evaluation of Pm2.5 Influence on Human Lung Cancer Cells Using a Microfluidic Platform.

In this study, we developed a microfluidic device that is able to monitor cell biology under continuous PM2.5 treatment. The effects of PM2.5 on human alveolar basal epithelial cells, A549 cells, and uncovered several significant findings were investigated. The results showed that PM2.5 exposure did not lead to a notable decrease in cell viability, indicating that PM2.5 did not cause cellular injury or death. However, the study found that PM2.5 exposure increased the invasion and migration abilities of A549 cells, suggesting that PM2.5 might promote cell invasiveness. Results of RNA sequencing revealed 423 genes that displayed significant differential expression in response to PM2.5 exposure, with a particular focus on pathways associated with the generation of reactive oxygen species (ROS) and mitochondrial dysfunction. Real-time detection demonstrated an increase in ROS production in A549 cells after exposure to PM2.5. JC1 assay, which indicated a loss of mitochondrial membrane potential (ΔΨm) in A549 cells exposed to PM2.5. The disruption of mitochondrial membrane potential further supports the detrimental effects of PM2.5 on A549 cells. These findings highlight several adverse effects of PM2.5 on A549 cells, including enhanced invasion and migration capabilities, altered gene expression related to ROS pathways, increased ROS production and disruption of mitochondrial membrane potential. These findings contribute to our understanding of the potential mechanisms through which PM2.5 can impact cellular function and health.

Palliative effects of carnosol on lung-deposited pollutant particles-induced thrombogenicity and vascular injury in mice.

The toxicity of inhaled particulate air pollution perseveres even at lower concentrations than those of the existing air quality limit. Therefore, the identification of safe and effective measures against pollutant particles-induced vascular toxicity is warranted. Carnosol is a bioactive phenolic diterpene found in rosemary herb, with anti-inflammatory and antioxidant actions. However, its possible protective effect on the thrombotic and vascular injury induced by diesel exhaust particles (DEP) has not been studied before. We assessed here the potential alleviating effect of carnosol (20 mg/kg) administered intraperitoneally 1 h before intratracheal (i.t.) instillation of DEP (20 µg/mouse). Twenty-four hours after the administration of DEP, various parameters were assessed. Carnosol administration prevented the increase in the plasma concentrations of C-reactive protein, fibrinogen, and tissue factor induced by DEP exposure. Carnosol inhibited DEP-induced prothrombotic effects in pial microvessels in vivo and platelet aggregation in vitro. The shortening of activated partial thromboplastin time and prothrombin time induced by DEP was abated by carnosol administration. Carnosol inhibited the increase in pro-inflammatory cytokines (interleukin-6 and tumor necrosis factor α) and adhesion molecules (intercellular adhesion molecule-1, vascular cell adhesion molecule-1, E-selectin, and P-selectin) in aortic tissue. Moreover, it averted the effects of DEP-induced increase of thiobarbituric acid reactive substances, depletion of antioxidants and DNA damage in the aortic tissue. Likewise, carnosol prevented the decrease in the expression of nuclear factor erythroid 2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1) caused by DEP. We conclude that carnosol alleviates DEP-induced thrombogenicity and vascular inflammation, oxidative damage, and DNA injury through Nrf2 and HO-1 activation.

[Research progress on the role of imbalanced high and low molecular weight hyaluronic acid in respiratory system inflammation caused by atmospheric particulate matter].

Atmospheric particulate matter has an association with respiratory system inflammation, and low molecular weight hyaluronic acid (LMW-HA) is a key biomarker of inflammatory cascade reaction. This review summarized the possible pathways and biomarkers of atmospheric particulate matter causing respiratory system inflammation through high molecular weight hyaluronic acid (HMW-HA)/LMW-HA imbalance, including the synthesis and decomposition of HA, the reduction of particulate matter and HMW-HA, the increase of LMW-HA, and the relationship between LMW-HA and respiratory system inflammation. Furthermore, inhibitors and therapeutic drugs targeting certain biomarkers were further listed. This review could shed light on the mechanism of respiratory system inflammation caused by atmospheric particulate matter and the weak points that need attention in subsequent research.

[Association between ambient air pollution and biological aging among the middle-aged and older adults: a systematic review].

Objective: To summarize and elucidate the impact of ambient air pollution on biological aging among middle-aged and older adults. Methods: "Air pollution""Biological age""Epigenetic age""Biological aging"and"Epigenetic aging", as well as specific names of air pollutants and biological age were used as search keywords. This study searched the databases of PubMed and Web of Science for eligible English articles and CNKI, CQVIP, Wanfang, CBM, CSTP and other Chinese databases for eligible Chinese articles from inception until June 30, 2023. The language was limited to Chinese and English. Results: Among the 14 included articles, five studies investigated the impact of air pollution on DNA methylation age using different algorithms, while six studies explored the relationship between air pollutants and telomere length. Six studies focused on frailty as an outcome, and an additional study revealed the relationship between fine particulate matter (PM2.5) and its components with composite indicator age (KDM age). The results indicated that, although different forms of biological ages were susceptible to different ambient air pollutants at different degrees, previous studies had consistently found that the increased levels of PM2.5 and one of its major components, black carbon (BC), could significantly accelerate the biological aging of middle-aged and older adults. Similar trends were observed with nitrogen oxides (NOx) and ozone (O3) but with relatively limited evidence. Conclusion: Major air pollutants could accelerate the biological aging of middle-aged and older adults.

Assessing the Impact of PM2.5-Bound Arsenic on Cardiovascular Risk among Workers in a Non-ferrous Metal Smelting Area: Insights from Chemical Speciation and Bioavailability.

Inhalation of fine particulate matter PM2.5-bound arsenic (PM2.5-As) may cause significant cardiovascular damage, due to its high concentration, long transmission range, and good absorption efficiency in organisms. However, both the contribution and the effect of the arsenic exposure pathway, with PM2.5 as the medium, on cardiovascular system damage in nonferrous smelting sites remain to be studied. In this work, a one-year site sample collection and analysis work showed that the annual concentration of PM2.5-As reached 0.74 µg/m3, which was 120 times the national standard. The predominant species in the PM2.5 samples were As (V) and As (III). A panel study among workers revealed that PM2.5-As exposure dominantly contributed to human absorption of As. After exposure of mice to PM2.5-As for 8 weeks, the accumulation of As in the high exposure group reached equilibrium, and its bioavailability was 24.5%. A series of animal experiments revealed that PM2.5-As exposure induced cardiac injury and dysfunction at the environmental relevant concentration and speciation. By integrating environmental and animal exposure assessments, more accurate health risk assessment models exposed to PM2.5-As were established for metal smelting areas. Therefore, our research provides an important scientific basis for relevant departments to formulate industry supervision, prevention and control policies.