PM2.5 exposure contributes to anxiety and depression-like behaviors via phenyl-containing compounds interfering with dopamine receptor.

As a global problem, fine particulate matter (PM2.5) really needs local fixes. Considering the increasing epidemiological relevance to anxiety and depression but inconsistent toxicological results, the most important question is to clarify whether and how PM2.5 causally contributes to these mental disorders and which components are the most dangerous for crucial mitigation in a particular place. In the present study, we chronically subjected male mice to a real-world PM2.5 exposure system throughout the winter heating period in a coal combustion area and revealed that PM2.5 caused anxiety and depression-like behaviors in adults such as restricted activity, diminished exploratory interest, enhanced repetitive stereotypy, and elevated acquired immobility, through behavioral tests including open field, elevated plus maze, marble-burying, and forced swimming tests. Importantly, we found that dopamine signaling was perturbed using mRNA transcriptional profile and bioinformatics analysis, with Drd1 as a potential target. Subsequently, we developed the Drd1 expression-directed multifraction isolating and nontarget identifying framework and identified a total of 209 compounds in PM2.5 organic extracts capable of reducing Drd1 expression. Furthermore, by applying hierarchical characteristic fragment analysis and molecular docking and dynamics simulation, we clarified that phenyl-containing compounds competitively bound to DRD1 and interfered with dopamine signaling, thereby contributing to mental disorders. Taken together, this work provides experimental evidence for researchers and clinicians to identify hazardous factors in PM2.5 and prevent adverse health outcomes and for local governments and municipalities to control source emissions for diminishing specific disease burdens.

How do taxi drivers expose to fine particulate matter (PM2.5) in a Chinese megacity: a rapid assessment incorporating with satellite-derived information and urban mobility data.

BACKGROUND: Taxi drivers in a Chinese megacity are frequently exposed to traffic-related particulate matter (PM2.5) due to their job nature, busy road traffic, and urban density. A robust method to quantify dynamic population exposure to PM2.5 among taxi drivers is important for occupational risk prevention, however, it is limited by data availability. METHODS: This study proposed a rapid assessment of dynamic exposure to PM2.5 among drivers based on satellite-derived information, air quality data from monitoring stations, and GPS-based taxi trajectory data. An empirical study was conducted in Wuhan, China, to examine spatial and temporal variability of dynamic exposure and compare whether drivers' exposure exceeded the World Health Organization (WHO) and China air quality guideline thresholds. Kernel density estimation was conducted to further explore the relationship between dynamic exposure and taxi drivers' activities. RESULTS: The taxi drivers' weekday and weekend 24-h PM2.5 exposure was 83.60 µg/m3 and 55.62 µg/m3 respectively, 3.4 and 2.2 times than the WHO's recommended level of 25 µg/m3. Specifically, drivers with high PM2.5 exposure had a higher average trip distance and smaller activity areas. Although major transportation interchanges/terminals were the common activity hotspots for both taxi drivers with high and low exposure, activity hotspots of drivers with high exposure were mainly located in busy riverside commercial areas within historic and central districts bounded by the "Inner Ring Road", while hotspots of drivers with low exposure were new commercial areas in the extended urbanized area bounded by the "Third Ring Road". CONCLUSION: These findings emphasized the need for air quality management and community planning to mitigate the potential health risks of taxi drivers.

Genome-Wide DNA methylation profile analysis identifies differentially methylated loci associated with personal PM2.5 exposure in adults with asthma.

Particulate matter with aerodynamic diameters ≤2.5 µm (PM2.5) is a major environmental risk factor for acute asthma exacerbation, and the underlying mechanism is not completely understood. Studies have indicated that DNA methylation is a potential mechanism linking PM2.5 to its health effects. We conducted a panel study involving 24 adult patients with asthma in Beijing,China between 2017 and 2019. PM2.5 and other atmospheric pollutant exposure data were repeatedly measured. Blood samples were collected for genome-wide DNA methylation analysis. A linear mixed-effects (LME) model was conducted to identify differentially methylated probes (DMPs) associated with PM2.5 exposure. After filtering out probes that did not meet the criteria through quality control, 811,001 CpG sites were included in the LME model, and 36 DMPs were strongly associated with personal PM2.5 exposure at false discovery rate (FDR) < 0.05, of which 22 and 14 DMPs negatively and positively correlated with personal PM2.5 exposure, respectively. Functional analysis revealed that DMPs affected smooth muscle cell contraction and development, extracellular matrix synthesis and secretion, T cell activation and differentiation, and inflammatory factor production. This study provides evidence linking personal PM2.5 exposure to genome-wide DNA methylation in adult patients with asthma. Identifying enrichment pathways can provide biological insights into the acute health effects of PM2.5.

Secular trends in type 2 diabetes mellitus attributable to PM2.5 exposure in China from 1990 to 2019: an age-period-cohort analysis.

Secular trends of mortality and disability-adjusted life years (DALY) in type 2 diabetes mellitus (T2DM) attributable to PM2.5 exposure in China remain unclear. This study applied the joinpoint regression analysis and age-period-cohort model to assess the secular trends. There was a slight alternation in age-standardized rate of mortality and DALY in the total population, while the changes were increased in males and decreased in females from 1990 to 2019. Meanwhile, the changes attributable to ambient particular matter pollution exposure (APE) increased significantly and reduced household air pollution from solid fuels exposure (HPE). Longitudinal age curves showed that T2DM mortality and DALY increased with age. Period rate ratios (RR) attributable to APE increased but fell to HPE. Similar trends were observed in the cohort RR. PM2.5 exposure is more harmful to males and older people. The type of air pollution responsible for T2DM has changed from HPE to APE.

Air Purifier Intervention to Remove Indoor PM2.5 in Urban China: A Cost-Effectiveness and Health Inequality Impact Study.

Using air purifiers is an intervention to reduce exposure to fine particulate matter (PM2.5) for health benefits. We performed a comprehensive simulation in urban China to estimate the cost-effectiveness of long-term use of air purifiers to remove indoor PM2.5 from indoor and ambient air pollution in five intervention scenarios (S1-S5), where the indoor PM2.5 targets were 35, 25, 15, 10, and 5 µg/m3, respectively. In scenarios S1 to S5, 5221 (95% uncertainty interval: 3886-6091), 6178 (4554-7242), 8599 (6255-10,109), 11,006 (7962-13,013), and 14,990 (10,888-17,610) thousand disability-adjusted-life-years (DALYs) can be avoided at the cost of 201 (199-204), 240 (238-243), 364 (360-369), 522 (515-530), and 921 (905-939) billion Chinese Yuan (CNY), respectively. A high disparity in per capita health benefits and costs was observed by city, which expanded with the decrease of the indoor PM2.5 target. The net benefits of using purifiers in cities varied across scenarios. Cities with a lower ratio of annual average outdoor PM2.5 concentration to gross domestic product (GDP) per capita tended to achieve higher net benefits in the scenario with a lower indoor PM2.5 target. Controlling ambient PM2.5 pollution and developing the economy can reduce the inequality in air purifier use across China.

EASIUR-HR: A Model To Evaluate Exposure Inequality Caused by Ground-Level Sources of Primary Fine Particulate Matter.

People of color disproportionately bear the health impacts of air pollution, making air quality a critical environmental justice issue. However, quantitative analysis of the disproportionate impacts of emissions is rarely done due to a lack of suitable models. Our work develops a high-resolution reduced-complexity model (EASIUR-HR) to evaluate the disproportionate impacts of ground-level primary PM2.5 emissions. Our approach combines a Gaussian plume model for near-source impacts of primary PM2.5 with a previously developed reduced-complexity model, EASIUR, to predict primary PM2.5 concentrations at a spatial resolution of 300 m across the contiguous United States. We find that low-resolution models underpredict important local spatial variation of air pollution exposure to primary PM2.5 emissions, potentially underestimating the contribution of these emissions to national inequality in PM2.5 exposure by more than a factor of 2. We apply EASIUR-HR to analyze the impacts of vehicle electrification on exposure disparities. While such a policy has small aggregate air quality impacts nationally, it reduces exposure disparity for race/ethnic minorities. Our high-resolution RCM for primary PM2.5 emissions (EASIUR-HR) is a new, publicly available tool to assess inequality in air pollution exposure across the United States.

PM2.5 exposure promotes asthma in aged Brown-Norway rats: Implication of multiomics analysis.

Children are disproportionately represented among those who suffer asthma, which is a kind of chronic airway inflammation. Asthma symptoms might worsen when exposed to the air pollutant particulate matter 2.5 (PM2.5). However, it is becoming more prevalent among older adults, with more asthma-related deaths occurring in this pollution than in any other age group, and symptoms caused by asthma can reduce the quality of life of the elderly, whose asthma is underdiagnosed due to physiological factors. Therefore, in an effort to discover a therapy for older asthma during exposure to air pollution, we sought to ascertain the effects of pre-exposure (PA) and persistent exposure (PAP) to PM2.5 in aged asthma rats. In this study, we exposed aged rats to PM2.5 at different times (PA and PAP) and established an ovalbumin-mediated allergic asthma model. The basic process of elderly asthma caused by PM2.5 exposure was investigated by lung function detection, enzyme-linked immunosorbent assay (ELISA), histopathology, cytology, cytokine microarray, untargeted metabolomics, and gut microbiota analysis. Our findings demonstrated that in the PA and PAP groups, exposure to PM2.5 reduced lung function and exacerbated lung tissue damage, with varying degrees of effect on immunoglobulin levels, the findings of a cytological analysis, cytokines, and chemokines. The PA and PAP rats had higher amounts of polycyclic aromatic hydrocarbons (PAHs), such as naphthalene, 2-methylNaphthalene, 1-methylNaphthalene and flourene. Moreover, exposure to PM2.5 at different times showed different effects on plasma metabolism and gut microbiota. Bioinformatics analysis showed a strong correlation between PAHs, cytokines, and gut microbiota, and PAHs may cause metabolic disorders through the gut microbiota. These findings point to a possible mechanism for the development of asthma in older people exposure to PM2.5 that may be related to past interactions between PAHs, cytokines, gut microbiota, and plasma metabolites.

Diverse Pathways for Power Sector Decarbonization in Texas Yield Health Cobenefits but Fail to Alleviate Air Pollution Exposure Inequities.

Decarbonizing power systems is a critical component of climate change mitigation, which can have public health cobenefits by reducing air pollution. Many studies have examined strategies to decarbonize power grids and quantified their health cobenefits. However, few of them focus on near-term cobenefits at community levels, while comparing various decarbonization pathways. Here, we use a coupled power system and air quality modeling framework to quantify the costs and benefits of decarbonizing the Texas power grid through a carbon tax; replacing coal with natural gas, solar, or wind; and internalizing human health impacts into operations. Our results show that all decarbonization pathways can result in major reductions in CO2 emissions and public health impacts from power sector emissions, leading to large net benefits when considering the costs to implement these strategies. Operational changes with existing infrastructure can serve as a transitional strategy during the process of replacing coal with renewable energy, which offers the largest benefits. However, we also find that Black and lower-income populations receive disproportionately higher air pollution damages and that none of the examined decarbonization strategies mitigate this disparity. These findings suggest that additional interventions are necessary to mitigate environmental inequity while decarbonizing power grids.

Toward Cleaner Transport Alternatives: Reduction in Exposure to Air Pollutants in a Mass Public Transport.

Commuters are often exposed to higher concentrations of air pollutants due to its proximity to mobile sources. Despite recent trends in urban transport toward zero- and low-tailpipe emission alternatives, the assessments of the impact of these transformations on commuter exposure are limited by the low frequency of such studies. In this work, we use a unique data set of personal exposure concentration measurements collected over the span of 5 years to analyze changes due to the introduction of a new fleet for Bogotá's Bus Rapid Transit System. In that system, over a thousand Euro-II and -III diesel-powered buses were replaced with Euro-VI compressed natural gas and filter-equipped Euro-V diesel buses. We measured personal exposure concentrations of equivalent black carbon (eBC), fine particulate (PM2.5), and ultra fine particles (UFP) during and after the retirement of old buses and the introduction of new ones. Observations collected prior to the fleet renewal were used as baseline and later compared to data collected over two follow-up campaigns in 2019 and 2020. Significant reductions in the concentration of PM2.5 and eBC were observed during the 2019 campaign, with a 48% decrease for mean in-bus eBC (89.9 to 46.4 µg m-3) and PM2.5 (180.7 to 95.4 µg m-3) concentrations. Further reductions were observed during the 2020 follow-up, when the fleet renovation was completed, with mean in-bus eBC decreasing to 17.7 µg m-3 and PM2.5 to 42.3 µg m-3. These observations imply nearly a 5-fold reduction in eBC exposure and a 4-fold decrease in PM2.5. There was a much smaller reduction of in-bus UFP concentration between 2019 and 2020, indicating a persistent presence of high particle number concentrations in the near-road environment despite the fleet renovation process. In-bus UFP concentrations ranged between 65 000 and 104 500 cm-3 during the follow-up campaigns. The results in this work illustrate the immediate benefits of reducing personal exposure through the adoption of vehicles with more stringent emission standards.

Association of ambient fine particulate matter exposure with gestational diabetes mellitus and blood glucose levels during pregnancy.

BACKGROUND: Previous studies have examined the associations between ambient fine particulate matter (PM2.5) exposure and gestational diabetes mellitus (GDM). However, limited studies explored the relationships between PM2.5 exposure and blood glucose levels during pregnancy, especially in highly polluted areas. OBJECTIVES: To examine the associations of prenatal ambient PM2.5 exposure with GDM and blood glucose levels, and to identify the sensitive exposure windows in a highly air-polluted area. METHODS: From July 2016 to October 2017, a birth cohort study was conducted in Beijing, China. Participants were interviewed in each trimester regarding demographics, lifestyle, living and working environment, and medical conditions. Participant's daily ambient PM2.5 levels from 3 m before last menstrual period (LMP) to the third trimester was estimated by a hybrid spatiotemporal model. Indoor air quality index was calculated based on environmental tobacco smoke, ventilation, cooking, painting, pesticide, and herbicide use. Distributed lag non-linear model was applied to explore the sensitive weeks of PM2.5 exposure. RESULTS: Of 165 pregnant women, 23 (13.94%) developed GDM. After adjusting for potential confounders, PM2.5 exposure during the 1st trimester was associated with higher odds of GDM (10 µg/m3 increase: OR = 1.89, 95% CI: 1.04-3.49). Each 10 µg/m3 increase in PM2.5 during the 2nd trimester was associated with 17.70% (2.21-33.20), 15.99% (2.96-29.01), 18.82% (4.11-33.52), and 17.10% (3.28-30.92) increase in 1-h, 2-h, Δ1h-fasting (1-h minus fasting), and Δ2h-fasting (2-h minus fasting) blood glucose levels, respectively. PM2.5 exposure at 24th-27th weeks after LMP was associated with increased GDM risk. We identified sensitive exposure windows of 21st-24th weeks for higher 1-h and 2-h blood glucose levels and of 20th-22nd weeks for increased Δ1h-fasting and Δ2h-fasting. CONCLUSIONS: Ambient PM2.5 exposure during the second trimester was associated with higher odds of GDM and higher blood glucose levels. Avoiding exposure to high air pollution levels during the sensitive windows might prevent women from developing GDM.

Associations between PM2.5 exposure and Alzheimer's Disease prevalence Among elderly in eastern China.

BACKGROUND: Studies showed that PM2.5 might be associated with various neurogenic diseases such as Alzheimer's Disease (AD). However, this topic had been little studied in Zhejiang province of China.  METHODS: In 2018, we established a cohort of AD high-risk population with 1,742 elderly aged 60 and above. In 2020, the cohort was followed up, a total of 1,545 people participated the 2 surveys. Data collection included questionnaires and basic physical examinations. The average residential exposure to PM2.5 for each participant, that in a 5-years period prior to the first survey, was estimated using a satellite-based spatial statistical model. We determined the association between PM2.5 and AD prevalence by cox proportional hazards regression model.  RESULTS: This study showed that an increase in the PM2.5 level was an important associated risk factor that contributed to AD. The average PM2.5 exposure levels among the study population ranged from 32.69 µg/m3 to 39.67 µg/m3 from 2013 to 2017, which were much higher than 5 µg/m3 that specified in the WHO air quality guidelines. There was an association between PM2.5 exposure and AD, and the correlations between PM2.5 and Mini-Mental State Examination, Montreal cognitive assessment scale scores were statistically significant. An increase in the PM2.5 level by 10 µg/m3 elevated the risk of AD among residents by 2%-5% (HR model 2-model 4 = 1.02 to 1.05, CI model 2-model 4 = 1.01-1.10). The subgroups of male, with old age, with low education levels, used to work as farmers or blue-collar workers before retirement, overweight and obese were associated with a higher effect of PM2.5. CONCLUSIONS: Reducing PM2.5 exposure might be a good way to prevent AD.

Exposure to traffic-related fine particulate matter 2.5 causes respiratory damage via peroxisome proliferator-activated receptor gamma-regulated inflammation.

Exposure to particulate matter 2.5 (PM2.5) potentially triggers airway inflammation. Peroxisome proliferator-activated receptor gamma (PPARγ) has been reported to regulate inflammatory responses in diverse cell types. Therefore, this work investigated the mechanisms of PPARγ in regulating traffic-related PM2.5-induced airway inflammation. Using the diffusion flame burner soot generation, traffic-related PM2.5 was generated and adsorbed. BALB/c male mice and human bronchial epithelial cells (16-HBE) were exposed to PM2.5 alone or co-treatment with rosiglitazone (RSG), an agonist of PPARγ. To the end of exposure, bronchoalveolar lavage fluid (BALF), venous blood and arterial blood, trachea, bronchus and lung tissues were collected. The levels of IL-1ß, IL-6, and IL-17 were detected by ELISA, and the cell types in BALF were counted. Hematoxylin-eosin (H&E) assay were used to analyze the pathological conditions of lung, bronchus, and pulmonary artery. Apoptosis was detected by TUNEL, and PPARγ expression in lung and bronchus was detected by immunohistochemical (IHC) staining. Western Blot was used to detect PPARγ, NF-kB, AP-1 and STAT3 expression in lung and bronchus. The viability was detected by MTT method. PM2.5 exposure caused pathological damage to the lung, bronchus and pulmonary artery tissue, which induced apoptosis of bronchial epithelial cells. PM2.5 exposure caused local inflammation of the whole body and airway. PPARγ expression increased after PM2.5 exposure. PM2.5 exposure regulated the downstream signaling pathways to affect the inflammatory response through PPARγ. Exposure to traffic-related PM2.5 caused respiratory damage via PPARγ-regulated inflammation.

Quantifying the multiple environmental, health, and economic benefits from the electrification of the Delhi public transport bus fleet, estimating a district-wise near roadway avoided PM2.5 exposure.

This study investigates the co-benefits from the utilization of the battery-electric bus (BEB) fleet in the Delhi public transportation system as a part of the Delhi electric vehicles policy 2020. To this aim, an integrated quantitative assessment framework is developed to estimate the expected environmental, health, and economic co-benefits from replacing the currently existing public bus fleet with the new BEBs in Delhi. First, the model estimates the avoided emissions from deploying the BEB fleet, using a detailed battery energy simulation model, considering the impact of the battery capacity loss on the annual operational time (hours of service) of the BEB. The annual operational time of the BEB is greatly affected by its battery degradation, which results in time lost due to charging the battery. This indicates that the annual passenger-kilometer (PKM) delivered by the BEB is less than the regular bus, under the same traveling condition. Second, considering fine particles (PM2.5) as the most health-harming pollutant, the model calculates the near roadway avoided PM2.5 exposure in the selected traffic zones of 11 major districts of Delhi, using a Gaussian dispersion model. Third, the near roadway avoided PM2.5 exposure is further used in a health impact assessment model, which considers concentration-response functions for several diseases to evaluate the public health benefits from introducing the BEB fleet in Delhi. The research findings indicate that, the utilization of the new BEB fleet leads to a 74.67% reduction in the total pollutant emissions from the existing bus fleet in Delhi. The results of the integrated co-benefits assessment reveal a significant reduction in PM2.5 emissions (44 t/y), leading to avoidance of mortality (1370 cases) and respiratory diseases related hospital admissions (2808 cases), respectively, and an annual savings of about USD 383 million from the avoided mortality and morbidity cases in Delhi.

Air pollution and the pandemic: Long-term PM2.5 exposure and disease severity in COVID-19 patients.

BACKGROUND AND OBJECTIVE: Ecological studies have suggested an association between exposure to particulate matter ≤2.5 µm (PM2.5 ) and coronavirus disease 2019 (COVID-19) severity. However, these findings are yet to be validated in individual-level studies. We aimed to determine the association of long-term PM2.5 exposure with hospitalization among individual patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: We estimated the 10-year (2009-2018) PM2.5 exposure at the residential zip code of COVID-19 patients diagnosed at the University of Cincinnati healthcare system between 13 March 2020 and 30 September 2020. Logistic regression was used to determine the odds ratio (OR) and 95% CI for COVID-19 hospitalizations associated with PM2.5 , adjusting for socioeconomic characteristics and comorbidities. RESULTS: Among the 14,783 COVID-19 patients included in our study, 13.6% were hospitalized; the geometric mean (SD) PM2.5 was 10.48 (1.12) µg/m3 . In adjusted analysis, 1 µg/m3 increase in 10-year annual average PM2.5 was associated with 18% higher hospitalization (OR: 1.18, 95% CI: 1.11-1.26). Likewise, 1 µg/m3 increase in PM2.5 estimated for the year 2018 was associated with 14% higher hospitalization (OR: 1.14, 95% CI: 1.08-1.21). CONCLUSION: Long-term PM2.5 exposure is associated with increased hospitalization in COVID-19. Therefore, more stringent COVID-19 prevention measures may be needed in areas with higher PM2.5 exposure to reduce the disease morbidity and healthcare burden.

Estimating long-term time-resolved indoor PM2.5 of outdoor and indoor origin using easily obtainable inputs.

To evaluate the separate impacts on human health and establish effective control strategies, it is crucial to estimate the contribution of outdoor infiltration and indoor emission to indoor PM2.5 in buildings. This study used an algorithm to automatically estimate the long-term time-resolved indoor PM2.5 of outdoor and indoor origin in real apartments with natural ventilation. The inputs for the algorithm were only the time-resolved indoor/outdoor PM2.5 concentrations and occupants' window actions, which were easily obtained from the low-cost sensors. This study first applied the algorithm in an apartment in Tianjin, China. The indoor/outdoor contribution to the gross indoor exposure and time-resolved infiltration factor were automatically estimated using the algorithm. The influence of outdoor PM2.5 data source and algorithm parameters on the estimated results was analyzed. The algorithm was then applied in four other apartments located in Chongqing, Shenyang, Xi'an, and Urumqi to further demonstrate its feasibility. The results provided indirect evidence, such as the plausible explanations for seasonal and spatial variation, to partially support the success of the algorithm used in real apartments. Through the analysis, this study also identified several further development directions to facilitate the practical applications of the algorithm, such as robust long-term outdoor PM2.5  monitoring using low-cost light-scattering sensors.

Acute effect of fine particulate matter on blood pressure, heart rate and related inflammation biomarkers: A panel study in healthy adults.

Epidemiological evidence of short-term fine particulate matter (PM2.5) exposure on blood pressure (BP), heart rate (HR) and related inflammation biomarkers has been inconsistent. We aimed to explore the acute effect of PM2.5 on BP, HR and the mediation effect of related inflammation biomarkers. A total of 32 healthy college students were recruited to perform 4 h of exposure at two sites with different PM2.5 concentrations in Wuhan between May 2019 and June 2019. The individual levels of PM2.5 concentration, BP and HR were measured hourly for each participant. Blood was drawn from each participant after each visit and we measured the levels of inflammation markers, including serum high-sensitivity C-reactive protein and plasma fibrinogen. Linear mixed-effect models were to explore the acute effect of PM2.5 exposure on BP, HR, and related inflammation biomarkers. In addition, we evaluated related inflammation biomarkers as the mediator in the association of PM2.5 and cardiovascular health indicators. The results showed that a 10 µg/m3 increment in PM2.5 concentration was associated with an increase of 0.84 (95% CI: 0.54, 1.15) beats/min (bpm) in HR and a 3.52% (95% CI: 1.60%, 5.48%) increase in fibrinogen. The lag effect model showed that the strongest effect on HR was observed at lag 3 h of PM2.5 exposure [1.96 bpm (95% CI: 1.19, 2.75)], but for fibrinogen, delayed exposure attenuated the association. Increased fibrinogen levels may account for 39.07% (P = 0.44) of the elevated HR by PM2.5. Null association was observed when it comes to short-term PM2.5 exposure and BP. Short-term exposure to PM2.5 was associated with elevated HR and increased fibrinogen levels. But our finding was not enough to suggest that exposure to PM2.5 might induce adverse cardiovascular effects by the pathway of inflammation.

Maternal PM2.5 exposure and abnormal placental nutrient transport.

Epidemiological studies of human and animal experiments indicated that gestational exposure to atmospheric pollutants could be followed by the abnormal placental development. However, the effects of this exposure on the placental transportation for nutrients have not been systematically investigated. In this study, fine particulate matters (PM2.5) samples were collected in Taiyuan and pregnant rodent models were administered with 3 mg/kg b.w. PM2.5 by oropharyngeal aspiration every other day starting on embryonic day 0.5 (E0.5). Then the pregnant mice were sacrificed and their placentas were collected at different time points. The results showed that maternal PM2.5 exposure (MPE) disrupted the expression of proliferating cell nuclear antigen (PCNA) at all time points and inhibited the cell proliferation in placenta. Following that, the capacity for placental nutrient transport was impaired. The changes at E18.5 were observed most significantly, showing the altered mRNA expression of amino acid, long-chain polyunsaturated fatty acid (LCPUFA), glucose and folate transporters. In addition, the glycogen content was elevated at E18.5, and the triglyceride content was increased at E13.5 and E15.5 and decreased at E18.5 in the placenta after MPE. In a word, the adverse effect induced by MPE revealed that MPE led tothe disruption on the nutrient supply to the developing fetus via modulating the abundance of placental nutrient transporters (PNT).

Magnetic resonance imaging investigations reveal that PM2.5 exposure triggers visual dysfunction in mice.

OBJECTIVES: To investigate how PM2.5 exposure affects the microstructure, metabolites or functions of the visual system. METHODS: C57BL/6J mice were randomly assigned to groups exposed to the filtered air (the control group) or the concentrated ambient PM2.5 (the PM2.5 group). Visual evoked potentials (VEP), electroretinograms (ERG), diffusion tensor imaging (DTI), proton magnetic resonance spectroscopy (1H-MRS) and resting-state functional MRI (rsfMRI) were performed. Parameters were obtained and compared between the two groups, including latencies and amplitudes of the P1 wave, N1 wave and P2 wave from VEP, latencies and amplitudes of the a wave and b wave from ERG, fractional anisotropy (FA), mean diffusion (MD), axial diffusivity (AD) and radial diffusivity (RD) from DTI, visual cortex (VC) metabolites from 1H-MRS, and regional homogeneity (ReHo) from rsfMRI. RESULTS: Compared with the values of the control group, the PM2.5 group showed a prolonged N1 latency (43.11 ±â€¯7.94 ms vs. 38.75 ±â€¯4.60 ms) and lowered P1 amplitude (5.62 ±â€¯4.38 µV vs. 8.56 ±â€¯5.92 µV) on VEP (all p < 0.05). On ERG, the amplitude of the a wave was lowered (- 91.39 ±â€¯56.29 µV vs. - 138.68 ±â€¯89.05 µV), the amplitude of the b wave was lowered (194.38 ±â€¯126.27 µV vs. 284.72 ±â€¯170.99 µV), and the latency of the b wave was prolonged (37.78 ±â€¯10.72 ms vs. 33.01 ±â€¯4.34 ms) than the values of the control group (all p < 0.05). DTI indicated FA increase in the bilateral piriform cortex (Pir), FA decrease in the bilateral somatosensory cortex (S) and the bilateral striatum (Stri), AD decrease in the bilateral VC, the right S and the bilateral Pir, MD decrease in the bilateral Pir, and RD decrease in the bilateral Pir in the PM2.5 mice (all p < 0.05, Alphasim corrected). 1H-MRS showed Glutamate (Glu) increase and Phosphocholine (PCh) increase in the VC of the PM2.5 group than those of the control group (PCh 1.63 ±â€¯0.25 vs. 1.50 ±â€¯0.25; PCh/total creatine(tCr) 0.19 ±â€¯0.03 vs. 0.18 ±â€¯0.03; Glu 10.46 ±â€¯1.50 vs. 9.60 ±â€¯1.19; Glu/tcr 1.23 ±â€¯0.11 vs. 1.12 ±â€¯0.11) (all p < 0.05). rsfMRI showed higher ReHo in the PM2.5 mice in the left superior colliculus, the left motor cortex, the hippocampus, the periaqueductal gray and the right mesencephalic reticular formation (all p < 0.01, AlphaSim corrected). CONCLUSIONS: This study revealed that PM2.5 exposure triggered visual dysfunction, and altered microstructure, metabolite and function in the retina and visual brain areas along the visual system.

Application of a real-ambient fine particulate matter exposure system on different animal models.

Simulation of fine particulate matter (PM2.5) exposure is essential for evaluating adverse health effects. In this work, an ambient exposure system that mimicked real atmospheric conditions was installed in Taiyuan, China to study impacts of chronic PM2.5 exposure on adult and aged mice as well as Sirtuin3 knockout (Sirt3 KO) mice and wild-type (WT) mice. The real-ambient exposure system eliminated the possible artificial effects caused from exposure experiments and maintained the physiochemical characteristics of PM2.5. The case studies indicated that aged mice exhibited apparent heart dysfunction involving increased heart rate and decreased blood pressure after 17-week of real-ambient PM2.5 exposure. Meanwhile, 15-week of real-ambient PM2.5 exposure decreased the heart rate and amounts of associated catecholamines to induce heart failure in Sirt3 KO mice. Additionally, the increased pro-inflammatory cytokines and decreased platelet related indices suggested that inflammation occurred. The changes of biomarkers detected by targeted metabolomics confirmed metabolic disorder in WT and Sirt3 KO mice after exposed to real-ambient PM2.5. These results indicated that the real-ambient PM2.5 exposure system could evaluate the risks of certain diseases associated with air pollution and have great potential for supporting the investigations of PM2.5 effects on other types of rodent models.

Ovarian Dysfunction Induced by Chronic Whole-Body PM2.5 Exposure.

Fine particulate matter (PM2.5) pollution arouses public health concerns over the world. Increasing epidemiologic evidence suggests that exposure to ambient airborne PM2.5 increases the risk of female infertility. However, relatively few studies have systematically explored the harmful effect of chronic PM2.5 exposure on ovarian function and the underlying mechanisms. In this study, female C57BL/6J mice are exposed to filtered air or urban airborne PM2.5 for 4 months through a whole-body exposure system. It is found that PM2.5 exposure significantly caused the alteration of estrus cycles, reproductivity, hormone levels, and ovarian reserve. The granulosa cell apoptosis via the mitochondria dependent pathway contributes to the follicle atresia. With RNA-sequencing technique, the differentially expressed genes induced by PM2.5 exposure are mainly enriched in ovarian steroidogenesis, reactive oxygen species and oxidative phosphorylation pathways. Furthermore, it is found that increased PM2.5 profoundly exacerbated ovarian oxidative stress and inflammation in mice through the NF-κB/IL-6 signaling pathway. Notably, dietary polydatin (PD) supplement has protective effect in mice against PM2.5-induced ovarian dysfunction.These striking findings demonstrate that PM2.5 and/or air pollution is a critical factor for ovarian dysfunction through mitochondria-dependent and NF-κB/IL-6-mediated pathway, and PD may serve as a pharmaceutic candidate for air pollution-associated ovarian dysfunction.