Associations between urinary biomarkers of oxidative stress and air pollutants observed in a randomized crossover exposure to steel mill emissions

Metal and oxidative potential exposure through particle inhalation and oxidative stress biomarkers: a 2-week pilot prospective study among Parisian subway workers

OBJECTIVE

In this pilot study on subway workers, we explored the relationships between particle exposure and oxidative stress biomarkers in exhaled breath condensate (EBC) and urine to identify the most relevant biomarkers for a large-scale study in this field.

METHODS

We constructed a comprehensive occupational exposure assessment among subway workers in three distinct jobs over 10 working days, measuring daily concentrations of particulate matter (PM), their metal content and oxidative potential (OP). Individual pre- and post-shift EBC and urine samples were collected daily. Three oxidative stress biomarkers were measured in these matrices: malondialdehyde (MDA), 8-hydroxy-2'deoxyguanosine (8-OHdG) and 8-isoprostane. The association between each effect biomarker and exposure variables was estimated by multivariable multilevel mixed-effect models with and without lag times.

RESULTS

The OP was positively associated with Fe and Mn, but not associated with any effect biomarkers. Concentration changes of effect biomarkers in EBC and urine were associated with transition metals in PM (Cu and Zn) and furthermore with specific metals in EBC (Ba, Co, Cr and Mn) and in urine (Ba, Cu, Co, Mo, Ni, Ti and Zn). The direction of these associations was both metal- and time-dependent. Associations between Cu or Zn and MDAEBC generally reached statistical significance after a delayed time of 12 or 24 h after exposure. Changes in metal concentrations in EBC and urine were associated with MDA and 8-OHdG concentrations the same day.

CONCLUSION

Associations between MDA in both EBC and urine gave opposite response for subway particles containing Zn versus Cu. This diverting Zn and Cu pattern was also observed for 8-OHdG and urinary concentrations of these two metals. Overall, MDA and 8-OHdG responses were sensitive for same-day metal exposures in both matrices. We recommend MDA and 8-OHdG in large field studies to account for oxidative stress originating from metals in inhaled particulate matter.

Effects of personal exposure to the oxidative potential of PM2.5 on oxidative stress biomarkers in pregnant women

Oxidative stress is a prominent pathway for the health effects associated with fine particulate matter (PM2.5) exposure. Oxidative potential (OP) of PM has been associated to several health endpoints, but studies on its impact on biomarkers of oxidative stress remains insufficient. 300 pregnant women from the SEPAGES cohort (France) carried personal PM2.5 samplers for a week and OP was measured using ascorbic acid (AA) and dithiothreitol (DTT) assays, and normalized by 1) PM2.5 mass (OPm) and 2) sampled air volume (OPv). A pool of three urine spots collected on the 7th day of PM sampling was analyzed for biomarkers, namely 8-hydroxy-2-deoxyguanosine (8-OHdG), malondialdehyde (MDA) and 8-isoprostaglandin-F2α (8-isoPGF2α). Associations were investigated using adjusted multiple linear regressions. OP effects were additionally investigated by stratifying by median PM2.5 concentration (14 μg m-3). In the main models, no association was observed with 8-isoPGF2α, nor MDA. An interquartile range (IQR) increase in OPmAA exposure was associated with increased 8-OHdG (percent change: 6.2 %; 95 % CI: 0.2 % to 12.6 %). In the stratified analysis, exposure to OPmAA was associated with 8-OHdG for participants exposed to low levels of PM2.5 (percent change: 11.4 %; 95 % CI: 3.3 % to 20.1 %), but not for those exposed to high levels (percent change: -1.0 %; 95 % CI: -10.6 % to 9.6 %). Associations for OPmDTT also followed a similar pattern (p-values for OPmAA-PM and OPmDTT-PM interaction terms were 0.12 and 0.11, respectively). Overall, our findings suggest that OPmAA may be associated with increased DNA oxidative damage. This association was not observed with PM2.5 mass concentration exposure. The effects of OPmAA in 8-OHdG tended to be stronger at lower (below median) vs. higher concentrations of PM2.5. Further epidemiological, toxicological and aerosol research are needed to further investigate the OPmAA effects on 8-OHdG and the potential modifying effect of PM mass concentration on this association.

The Protective Effect and Mechanism of Mild Hypothermia on Lung Injury after Cardiopulmonary Resuscitation in Pigs

To explore the protective effect and mechanism of mild hypothermia on lung tissue damage after cardiopulmonary resuscitation in pigs. In this experiment, we electrically stimulated 16 pigs (30 ± 2 kg) for 10 min to cause ventricular fibrillation. The successfully resuscitated animals were randomly divided into two groups, a mild hypothermia group and a control group. We took arterial blood 0.5, 1, 3, and 6 h after ROSC recovery in the two groups of animals for blood gas analysis. We observed the structural changes of lung tissue under an electron microscope and calculate the wet weight/dry weight (W/D) ratio. We quantitatively analyzed the expression differences of representative inflammatory factors [interleukin-6 (IL-6) and tumor necrosis factor-alpha TNF-α)] through the ELISA test. We detected the expression levels of Bax, Bcl-2, and Caspase-3 proteins in lung tissues by Western blot. After 3 h and 6 h of spontaneous circulation was restored, compared with the control group, PaO2/FiO2 decreased significantly (P < 0.05). In addition, the pathological changes, lung W/D and lung MDA of the mild hypothermia group were better than those of the control group. The levels of IL-6 and TNF-α in the lung tissue of the mild hypothermia group were significantly lower than those of the control group (P < 0.05). The content of Caspase-3 and Bax in the mild hypothermia group was significantly lower than that of the control group. Our experiments have shown that mild hypothermia can reduce lung tissue damage after cardiopulmonary resuscitation.

Effects of domestic solid fuel combustion emissions on the biomarkers of homemakers in rural areas of the Fenwei Plain, China

BACKGROUND

The health effects of heavy solid fuel use in winter in rural China are of concern. The effects of air pollution resulting from domestic solid fuel combustion in rural households on rural homemakers' biomarkers were revealed in this study.

METHODS

In total, 75 female homemakers from rural areas of Guanzhong Basin, the Fenwei Plain, People's Republic of China, were randomly selected and divided into three groups (biomass users, coal users, and nonusers of solid fuel user [control group]). The differences in biological indicators, including 8-hydrox-2'-deoxyguanosine (8-OHdG), interlukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α) in urine samples as well as blood pressure (BP, including systolic BP [SBP] and diastolic BP [DBP]) and heart rate (HR) among the groups in winter and summer were investigated using statistical analysis.

RESULTS

IL-6, 8-OHdG, HR, SBP, and DBP were significantly higher in winter than in summer (P < 0.05) owing to the poor air quality resulted from the excessive use of solid fuels in winter. Significant seasonal differences in 8-OHdG were observed for both coal and biomass users. After the influence of confounders was removed, only IL-6 levels in the urine of solid fuel users were significantly higher than that of the control group.

CONCLUSIONS

IL-6 is a sensitive biomarker representing inflammatory responses to particulate matter emitted through household solid fuel combustion. Locally, excessive use of solid fuels in winter posed serious PM_2.5 pollution in this area and adverse effects on inflammatory biomarkers in these rural homemakers and induced DNA damage related to oxidative stress.

Causal effect of environmental factors, economic indicators and domestic material consumption using frequency domain causality test

Economic growth-induced climate change is multifaceted with different dimensions, hence, requires scientific scrutiny. Herein, an assessment of the causal effect of environmental factors, economic assessment and domestic material consumption is presented. We utilized the novel Breitung-Candelon spectral Granger-causality aka frequency domain causality and parameter stability tests to account for the direction of causality. These tests, a resemblance to machine learning algorithm were required to examine the sequential shock of unobserved features of series not reported in traditional Granger-causality tests. The empirical results found a short-run relationship between renewables and economic growth, suggesting a strong effect of wealth on renewable energy consumption. We confirmed a strong and long-term metallurgical coal-controlled metal footprint through steelmaking, and coal-driven energy-based economic structure. The feedback hypothesis was validated between biomass consumption and economic growth. There was evidence that metal ore consumption predicts economic growth, income level and renewable energy consumption while it causes ambient air pollution. From a policy perspective, the study demonstrates that the diversification of the energy mix with renewable energy sources will reduce fossil fuel footprint.

Evaluation of vehicular pollution levels using line source model for hot spots in Muscat, Oman

A detailed investigation was carried out to assess the concentration of near-road traffic-related air pollution (TRAP) using a dispersion model in Muscat. Two ambient air quality monitoring (AQM) stations were utilized separately at six locations near major roadways (each location for 2 months) to monitor carbon monoxide (CO) and nitrogen oxides (NOx). The study aimed to measure the concentration of near-road TRAP in a city hot spots and develop a validated dispersion model via performance measures. The US Environmental Protection Agency (US EPA) Line Source Model was implemented in which the pollutant emission factors were obtained through Comprehensive Modal Emission Model (CMEM) and COmputer Programme to calculate Emissions from Road Transport (COPERT) model. Traffic data of all vehicle categories under normal driving conditions including average vehicle speed limits and local meteorological conditions were included in the modeling study. The analysis of monitoring data showed that hourly (00:00 to 23:00) concentrations of CO were within the US EPA limits, while NOx concentration was exceeded in most locations. Also, the measured pollutant levels were consistent with hourly peak and off-peak traffic volumes. The overall primary statistical performance measures showed that COPERT model was better than CMEM due to the high sensitivity of CMEM to the local meteorological factors. The best fractional bias (0.47 and 0.39), normalized mean square error (0.44 and 0.50), correlation coefficient (0.64 and 0.70), geometric mean bias (1.07 and 1.57), and geometric variance (2.00 and 2.32) were obtained for CO and NOx, respectively. However, the bootstrap 95% CI estimates over normalized mean square error, fractional bias, and correlation coefficient for COPERT and CMEM were found to be statistically significant from 0 in the case of combined model comparison across all the traffic locations for both CO and NOx. In overall, certain roads showed weak performance mainly due to the terrain features and the lack of reliable background concentrations, which need to be considered in the future study.

Effect of industrial point-source air pollutants on fractional exhaled nitric oxide in healthy volunteers

BACKGROUND

Few studies have examined the effects of industrial, fixed-site sources of air pollution on lung inflammation in nearby residents. We investigated the effects of short-term exposure to ambient air near a steel plant on the fractional exhaled concentration of nitric oxide (FeNO), a measure of airway inflammation, in healthy volunteers.

METHODS

A cross-over study design was used. Fifty-nine non-smoking participants (mean age 24 years) were randomly assigned to each of two 5-day exposure scenarios: breathing ambient air adjacent to a steel plant or 5 km away at a college campus site. FeNO and on-site air pollutants were measured daily. Mixed effects linear regression models were used for data analysis, adjusting for sex, temperature, humidity and day of week.

RESULTS

Compared with the college site, PM _2.5, ultrafine PM, SO₂, NO₂ and CO levels were significantly greater near the steel plant. FeNO was 15.3% (95% CI, 6.6%, 24.8%) higher near the plant compared to the college site.

CONCLUSIONS

Exposure to ambient air near a steel plant was associated with increased airway inflammation as measured by exhaled nitric oxide.

Health effects of particulate matter air pollution in underground railway systems - a critical review of the evidence

BACKGROUND

Exposure to ambient airborne particulate matter is a major risk factor for mortality and morbidity, associated with asthma, lung cancer, heart disease, myocardial infarction, and stroke, and more recently type 2 diabetes, dementia and loss of cognitive function. Less is understood about differential effects of particulate matter from different sources. Underground railways are used by millions of people on a daily basis in many cities. Poor air exchange with the outside environment means that underground railways often have an unusually high concentration of airborne particulate matter, while a high degree of railway-associated mechanical activity produces particulate matter which is physicochemically highly distinct from ambient particulate matter. The implications of this for the health of exposed commuters and employees is unclear.

MAIN BODY

A literature search found 27 publications directly assessing the potential health effects of underground particulate matter, including in vivo exposure studies, in vitro toxicology studies, and studies of particulate matter which might be similar to that found in underground railways. The methodology, findings, and conclusions of these studies were reviewed in depth, along with further publications directly relevant to the initial search results. In vitro studies suggest that underground particulate matter may be more toxic than exposure to ambient/urban particulate matter, especially in terms of endpoints related to reactive oxygen species generation and oxidative stress. This appears to be predominantly a result of the metal-rich nature of underground particulate matter, which is suggestive of increased health risks. However, while there are measureable effects on a variety of endpoints following exposure in vivo, there is a lack of evidence for these effects being clinically significant as may be implied by the in vitro evidence.

CONCLUSION

There is little direct evidence that underground railway particulate matter exposure is more harmful than ambient particulate matter exposure. This may be due to disparities between in vivo exposures and in vitro models, and differences in exposure doses, as well as statistical under powering of in vivo studies of chronic exposure. Future research should focus on outcomes of chronic in vivo exposure, as well as further work to understand mechanisms and potential biomarkers of exposure.

Quantification of malondialdehyde in exhaled breath condensate using pseudo two-dimensional ultra-performance liquid chromatography coupled with single quadrupole mass spectrometry

We developed a robust analytical method for quantification of malondialdehyde (MDA) in exhaled breath condensate (EBC) via derivatization with 2,4-dinitrophenylhydrazine (DNPH). The target MDA-DNPH hydrazone was separated by ultra-performance liquid chromatography using two reversed-phase analytical columns (C18 and phenyl-hexyl) inter-connected via a two-position, six-port switching valve to a single-quadrupole mass spectrometer. The target derivative was analyzed under positive electrospray ionization using single ion monitoring mode (m/z = 235 for the target derivative, and m/z = 237 for its labeled isotopic analog). This pseudo two-dimensional chromatographic separation provided optimum separation conditions for the target derivative resulting in the limit of detection of 0.58 nM in EBC sample (or 36.2 pmol on-column amount), which is comparable to those reported previously using different techniques, including tandem mass spectrometry. Based on the calibration solutions, the method had a linear quantification range of 1.0-200 nM (r2 = 0.998). The method showed good relative recoveries (92.2-102.0%) and acceptable precisions (3.6-12.2% for inter-day precision, and 4.3-12.4% for intra-day precision for two quality control levels, prepared from 5 nM and 25 nM solutions). The derivative was found to be stable at room temperature for 48 h or during analysis. The method was used to analyze 205 exhaled breath condensate samples collected from individuals from a healthy population of student athletes. MDA was detected in approximately 95% of these samples, with concentrations ranging from 1.16 to 149.63 nM. The median concentration was 6.82 nM, (IQR 4.08-9.88). These data demonstrate that our method can be successfully used to measure MDA in population studies.

Exposure to PM2.5 via vascular endothelial growth factor relationship: Meta-analysis

This study investigated the association of PM2.5 exposure with VEGF by conducting a systematic review of existing literature and performing a meta-analysis. We searched all the studies published in the Cochrane Library, PUBMED, Embase, China National Knowledge Infrastructure China National Knowledge Infrastructure, and WanFang Electronic Database before June 2017. Finally six studies were identified. It confirmed that the increase in VEGF (β = 1.23 pg/ml, 95% CI: 0.45, 2.01) was significantly associated with the PM2.5 mass concentration of 10 μg/m³. Studies from Canada showed that PM2.5 exposure statistically elevated the level of VEGF level that an increase of 1.20 pg/ml (95% CI: 0.88, 1.52) in VEGF was associated with per 10 μg/m³ increase in PM2.5 concentration. Other subgroup analyses indicated that the effects of PM2.5 exposure on VEGF differed per the in different exposure assessment methods, study designs, and study settings. It was concluded that elevated VEGF levels was significantly positive associated with PM2.5 exposure. Exposure assessment methods and study countries were the major sources of heterogeneity among studies.