Project description:Genome-wide analysis of lncRNA expression profiles in COPD rat model exposed by cigarette smoking (CS) and fine particulate matter (PM2.5). Goal was to explore the differences and similarities lncRNAs expression in rats model of COPD exposed by CS and PM2.5.
Project description:Several studies have pointed to fine particulate matter (PM2.5) as the main responsible for air pollution toxic effects. Indeed, PM2.5 may not only cause respiratory and cardiovascular abnormalities but it may also affect other organs such as the liver. Be that as it may, only a few studies have evaluated the PM2.5 effects on hepatic tissue. Moreover, most of them have not analyzed the relationship between particles composition and toxicological effects. In this study, healthy rats were subjected to urban levels of PM2.5 particles in order to assess their structural and functional effects on the liver. During the exposure periods, mean PM2.5 concentrations were slightly higher than the value suggested by the daily guideline of the World Health Organization. The exposed rats showed a hepatic increase of Cr, Zn, Fe, Ba, Tl and Pb levels. This group also showed leukocyte infiltration, sinusoidal dilation, hydropic inclusions and alterations in carbohydrates distribution. These histologic lesions were accompanied by serological changes, such as increase of total cholesterol and triglycerides, as well as genotoxic damage in their nuclei. We also observed significant associations between several biomarkers and PM2.5 composition. Our results show that exposure to low levels of PM2.5 might cause histologic and serological changes in liver tissue, suggesting that PM2.5 toxicity is influenced not only by their concentration but also by their composition and the exposure frequency.
Project description:We evaluate fine particulate matter (PM2.5) exposure-response models to propose a consistent set of global effect factors for product and policy assessments across spatial scales and across urban and rural environments. Relationships among exposure concentrations and PM2.5-attributable health effects largely depend on location, population density, and mortality rates. Existing effect factors build mostly on an essentially linear exposure-response function with coefficients from the American Cancer Society study. In contrast, the Global Burden of Disease analysis offers a nonlinear integrated exposure-response (IER) model with coefficients derived from numerous epidemiological studies covering a wide range of exposure concentrations. We explore the IER, additionally provide a simplified regression as a function of PM2.5 level, mortality rates, and severity, and compare results with effect factors derived from the recently published global exposure mortality model (GEMM). Uncertainty in effect factors is dominated by the exposure-response shape, background mortality, and geographic variability. Our central IER-based effect factor estimates for different regions do not differ substantially from previous estimates. However, IER estimates exhibit significant variability between locations as well as between urban and rural environments, driven primarily by variability in PM2.5 concentrations and mortality rates. Using the IER as the basis for effect factors presents a consistent picture of global PM2.5-related effects for use in product and policy assessment frameworks.
Project description:BackgroundCerebrovascular diseases play an important role in dementia. Air pollution is associated with cardiovascular disease, with growing links to neurodegeneration. Prior studies demonstrate associations between fine particulate matter (PM2.5) and biomarkers of endothelial injury in the blood; however, no studies have evaluated these biomarkers in cerebrospinal fluid (CSF).ObjectiveWe evaluate associations between short-term and long-term PM2.5 exposure with CSF vascular cell adhesion molecule-1 (VCAM-1) and e-selectin in cognitively normal and mild cognitive impairment (MCI)/Alzheimer's disease (AD) individuals.MethodsWe collected CSF from 133 community volunteers at VA Puget Sound between 2001-2012. We assigned short-term PM2.5 from central monitors and long-term PM2.5 based on annual average exposure predictions linked to participant addresses. We performed analyses stratified by cognitive status and adjusted for key covariates with tiered models. Our primary exposure windows for the short-term and long-term analyses were 7-day and 1-year averages, respectively.ResultsAmong cognitively normal individuals, a 5 μg/m3 increase in 7-day and 1-year average PM2.5 was associated with elevated VCAM-1 (7-day: 35.4 (9.7, 61.1) ng/ml; 1-year: 51.8 (6.5, 97.1) ng/ml). A 5 μg/m3 increase in 1-year average PM2.5, but not 7-day average, was associated with elevated e-selectin (53.3 (11.0, 95.5) pg/ml). We found no consistent associations among MCI/AD individuals.ConclusionsWe report associations between short-term and long term PM2.5 and CSF biomarkers of vascular damage in cognitively normal adults. These results are aligned with prior research linking PM2.5 to vascular damage in other biofluids as well as emerging evidence of the role of PM2.5 in neurodegeneration.
Project description:Epidemiologic and health impact studies are inhibited by the paucity of global, long-term measurements of the chemical composition of fine particulate matter. We inferred PM2.5 chemical composition at 0.1° × 0.1° spatial resolution for 2004-2008 by combining aerosol optical depth retrieved from the MODIS and MISR satellite instruments, with coincident profile and composition information from the GEOS-Chem global chemical transport model. Evaluation of the satellite-model PM2.5 composition data set with North American in situ measurements indicated significant spatial agreement for secondary inorganic aerosol, particulate organic mass, black carbon, mineral dust, and sea salt. We found that global population-weighted PM2.5 concentrations were dominated by particulate organic mass (11.9 ± 7.3 ?g/m(3)), secondary inorganic aerosol (11.1 ± 5.0 ?g/m(3)), and mineral dust (11.1 ± 7.9 ?g/m(3)). Secondary inorganic PM2.5 concentrations exceeded 30 ?g/m(3) over East China. Sensitivity simulations suggested that population-weighted ambient PM2.5 from biofuel burning (11 ?g/m(3)) could be almost as large as from fossil fuel combustion sources (17 ?g/m(3)). These estimates offer information about global population exposure to the chemical components and sources of PM2.5.
Project description:BackgroundExposure to fine particles (PM2.5) during pregnancy has been linked to lower birth weight; however, the chemical composition of PM2.5 varies widely. The health effects of PM2.5 constituents are unknown.MethodsWe investigated whether PM2.5 mass, constituents, and sources are associated with birth weight for term births. PM2.5 filters collected in 3 Connecticut counties and 1 Massachusetts county from August 2000 through February 2004 were analyzed for more than 50 elements. Source apportionment was used to estimate daily contributions of PM2.5 sources, including traffic, road dust/crustal, oil combustion, salt, and regional (sulfur) sources. Gestational and trimester exposure to PM2.5 mass, constituents, and source contributions were examined in relation to birth weight and risk of small-at-term birth (term birth <2500 g) for 76,788 infants.ResultsRoad dust and related constituents such as silicon and aluminum were associated with lower birth weight, as were the motor-vehicle-related species such as elemental carbon and zinc, and the oil-combustion-associated elements vanadium and nickel. An interquartile range increase in exposure was associated with low birthweight for zinc (12% increase in risk), elemental carbon (13%), silicon (10%), aluminum (11%), vanadium (8%), and nickel (11%). Analysis by trimester showed effects of third-trimester exposure to elemental carbon, nickel, vanadium, and oil-combustion PM2.5.ConclusionsExposures of pregnant women to higher levels of certain PM2.5 chemical constituents originating from specific sources are associated with lower birth weight.
Project description:ImportanceWhile rates of cigarette use are declining, more US adults are using cannabis. Perceptions of safety are important drivers of substance use and public policy; however, little is known about the comparative views of US adults on tobacco and cannabis safety.ObjectiveTo compare public perceptions of safety of cannabis vs tobacco smoke and evaluate how perceptions may be changing over time.Design, setting, and participantsThis longitudinal survey study was conducted using a web-based survey administered in 2017, 2020, and 2021. US adults participating in Ipsos KnowledgePanel, a nationally representative, population-based survey panel, were included. Data were analyzed from March 2021 through June 2023.Main outcomes and measuresTwo questions directly compared the perception of safety of cannabis vs tobacco in terms of daily smoking and secondhand smoke exposure. Additional questions assessed perceptions of safety of secondhand tobacco smoke for adults, children, and pregnant women, with an analogous set of questions for secondhand cannabis smoke.ResultsA total of 5035 participants (mean [SD] age, 53.4 [16.2] years; 2551 males [50.7%]) completed all 3 surveys and provided responses for tobacco and cannabis risk questions. More than one-third of participants felt that daily smoking of cannabis was safer than tobacco, and their views increasingly favored safety of cannabis vs tobacco over time (1742 participants [36.7%] in 2017 vs 2107 participants [44.3%] in 2021; P < .001). The pattern was similar for secondhand cannabis smoke, with 1668 participants (35.1%) responding that cannabis was safer than tobacco in 2017 vs 1908 participants (40.2%) in 2021 (P < .001). Participants who were younger (adjusted odds ratio [aOR] for ages 18-29 years vs ≥60 years, 1.4 [95% CI, 1.1-1.8]; P = .01) or not married (aOR, 1.2 [95% CI, 1.0-1.4]; P = .01) were more likely to move toward safer views of cannabis use over time, while those who were retired (aOR vs working, 0.8 [95% CI, 0.7-0.9]; P = .01) were less likely to move toward a safer view of cannabis. Participants were also more likely to rate secondhand smoke exposure to cannabis vs tobacco as completely or somewhat safe in adults (629 participants [12.6%] vs. 119 participants [2.4%]; P < .001), children (238 participants [4.8%] vs. 90 participants [1.8%]; P < .001), and pregnant women (264 participants [5.3%] vs. 69 participants [1.4%]; P < .001).Conclusions and relevanceThis study found that US adults increasingly perceived daily smoking and secondhand exposure to cannabis smoke as safer than tobacco smoke from 2017 to 2021. Given that these views do not reflect the existing science on cannabis and tobacco smoke, the findings may have important implications for public health and policy as the legalization and use of cannabis increase.
Project description:ImportanceThe degree that in-home cannabis smoking can be detected in the urine of resident children is unclear.ObjectiveTest association of in-home cannabis smoking with urinary cannabinoids in children living at home.Design, setting, and participantsThis cross-sectional study used baseline data from Project Fresh Air, a 2012-2016 randomized clinical trial to reduce fine particulate matter levels. Eligible participants were recruited from households in San Diego County, California, with children under age 14 years and an adult tobacco smoker in residence. Children's urine samples were analyzed in 2022.ExposuresIn-home cannabis smoking, measured by: parent or guardian report of in-home cannabis smoking; number of daily nonspecific smoking events computed via an air particle count algorithm; and number of daily cannabis smoking events ascertained by residualization, adjusting for air nicotine, tobacco smoking, and other air particle generating or ventilating activities.Main outcomes and measuresLevels of the cannabis biomarker Δ9-tetrahydrocannabinol (THC) and its major metabolites, 11-hydroxy-Δ9-tetrahydrocannabinol and 11-nor-9-carboxy-Δ9-tetrahydrocannabinol. Biomarker molar equivalents were summed to represent total THC equivalents (TTE) in urine. Logistic regression assessed whether in-home smoking was associated with cannabis biomarker detection. For children with detectable urinary cannabinoids, linear regression assessed in-home smoking association with quantity of urinary TTE.ResultsA total of 275 children were included in analysis (mean [SD] age, 3.6 [3.6] years; 144 male [52.4%]; 38 Black [13.8%], 132 Hispanic [48.0%], and 52 White [18.9%]). Twenty-nine households (10.6%) reported in-home cannabis smoking in the past 7 days; 75 children [27.3%] had detectable urinary cannabinoids. Odds of detectable TTE in children's urine were significantly higher in households with reported in-home cannabis smoking than households without (odds ratio [OR], 5.0; 95% CI, 2.4-10.4) and with each additional ascertained daily cannabis smoking event (OR, 2.5; 95% CI, 1.6-3.9). Although the point estimate for TTE levels was higher among children with detectable urinary cannabinoids and exposure to more daily cannabis smoking events (increase per event, 35.68%; 95% CI, -7.12% to 98.21%), the difference was not statistically significant.Conclusions and relevanceIn this cross-sectional study, in-home cannabis smoking was associated with significantly increased odds of child exposure to cannabis smoke, as assessed by urinary cannabinoid biomarkers. As young children spend most of their time at home, reducing in-home cannabis smoking could substantially reduce their exposure to the toxic and carcinogenic chemicals found in cannabis smoke.