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OBJECTIVE: Pain and traumatic stress symptoms often co-occur. Evidence suggests that the neuropeptide oxytocine and pro-inflammatory cytokines are associated with both stress and pain. The aim of this pilot study was to explore relations between self-reported pain and traumatic stress, oxytocin and three cytokines in burn wounds.METHODS: An observational study in three burn centres was performed. Patients were invited to participate in the study when deep dermal injury was suspected. Patients completed the Impact of Event Scale (IES), a self-report questionnaire assessing traumatic stress symptoms, and they rated their pain the day prior to surgery. During surgery, eschar (i.e., burned tissue) was collected and stored at -80 ° C until analysis. When the data collection was complete, oxytocin and cytokine levels were analysed.RESULTS: Eschar from 53 patients was collected. Pain and stress scores were available from 42 and 36 patients respectively. Spearman correlational analyses showed an association between lower oxytocin levels at wound site and a higher total IES score (r = -0.37) and pain (r = -0.32). Mann-Whitney U tests comparing groups scoring high or low on pain or stress confirmed these associations.CONCLUSION: These analyses lend support to a hormonal pathway that may explain how psychological distress affects pain at skin level in patients with traumatic stress symptoms.

Oxidative potential (OP) has been suggested as a health-relevant measure of air pollution. Little information is available about OP spatial variation and the possibility to model its spatial variability. Our aim was to measure the spatial variation of OP within and between 10 European study areas. The second aim was to develop land use regression (LUR) models to explain the measured spatial variation. OP was determined with the dithiothreitol (DTT) assay in ten European study areas. DTT of PM2.5 was measured at 16–40 sites per study area, divided over street, urban and regional background sites. Three two-week samples were taken per site in a one-year period in three different seasons. We developed study-area specific LUR models and a LUR model for all study areas combined to explain the spatial variation of OP. Significant contrasts between study areas in OP were found. OP DTT levels were highest in southern Europe. DTT levels at street sites were on average 1.10 times higher than at urban background locations. In 5 of the 10 study areas LUR models could be developed with a median R2 of 33%. A combined study area model explained 30% of the measured spatial variability. Overall, LUR models did not explain spatial variation well, possibly due to low levels of OP DTT and a lack of specific predictor variables. © 2016 Elsevier Ltd

Background: Particulate matter (PM) air pollution is a human lung carcinogen; however, the components responsible have not been identified. We assessed the associations between PM components and lung cancer incidence. Methods: We used data from 14 cohort studies in eight European countries. We geocoded baseline addresses and assessed air pollution with land-use regression models for eight elements (Cu, Fe, K, Ni, S, Si, V and Zn) in size fractions of PM2.5 and PM10. We used Cox regression models with adjustment for potential confounders for cohort-specific analyses and random effect models for meta-analysis. Results: The 245,782 cohort members contributed 3,229,220 person–years at risk. During follow-up (mean, 13.1 years), 1878 incident cases of lung cancer were diagnosed. In the meta-analyses, elevated hazard ratios (HRs) for lung cancer were associated with all elements except V; none was statistically significant. In analyses restricted to participants who did not change residence during follow-up, statistically significant associations were found for PM2.5 Cu (HR, 1.25; 95% CI, 1.01–1.53 per 5 ng/m3), PM10 Zn (1.28; 1.02–1.59 per 20 ng/m3), PM10 S (1.58; 1.03–2.44 per 200 ng/m3), PM10 Ni (1.59; 1.12–2.26 per 2 ng/m3) and PM10 K (1.17; 1.02–1.33 per 100 ng/m3). In two-pollutant models, associations between PM10 and PM2.5 and lung cancer were largely explained by PM2.5 S. Conclusions: This study indicates that the association between PM in air pollution and lung cancer can be attributed to various PM components and sources. PM containing S and Ni might be particularly important. Keywords: Air pollution, Particulate matter, Sulfur, Nickel, Cohort study, Lung cancer

Background: Particulate matter (PM) air pollution is a human lung carcinogen; however, the components responsible have not been identified. We assessed the associations between PM components and lung cancer incidence. Methods: We used data from 14 cohort studies in eight European countries. We geocoded baseline addresses and assessed air pollution with land-use regression models for eight elements (Cu, Fe, K, Ni, S, Si, V and Zn) in size fractions of PM2.5 and PM10. We used Cox regression models with adjustment for potential confounders for cohort-specific analyses and random effect models for meta-analysis. Results: The 245,782 cohort members contributed 3,229,220person-years at risk. During follow-up (mean, 13.1 years), 1878 incident cases of lung cancer were diagnosed. In the meta-analyses, elevated hazard ratios (HRs) for lung cancer were associated with all elements except V; none was statistically significant. In analyses restricted to participants who did not change residence during follow-up, statistically significant associations were found for PM2.5 Cu (HR, 1.25; 95% CI, 1.01-1.53 per 5 ng/m3), PM10 Zn (1.28; 1.02-1.59 per 20 ng/m3), PM10 S (1.58; 1.03-2.44 per 200 ng/m3), PM10 Ni (1.59; 1.12-2.26 per 2 ng/m3) and PM10 K (1.17; 1.02-1.33 per 100 ng/m3). In two-pollutant models, associations between PM10 and PM2.5 and lung cancer were largely explained by PM2.5 S. Conclusions: This study indicates that the association between PM in air pollution and lung cancer can be attributed to various PM components and sources. PM containing S and Ni might be particularly important. © 2015 Elsevier Ltd.

Item does not contain fulltext BACKGROUND: Patients with clinical N1 (cN1) lung cancer based on imaging are at risk for malignant mediastinal nodal involvement (N2 disease). Endosonography with a needle technique is suggested over surgical staging as a best first test for preoperative invasive mediastinal staging. The addition of a confirmatory mediastinoscopy seems questionable in patients with a normal mediastinum on imaging. This prospective multicenter trial investigated the sensitivity of preoperative linear endosonography and mediastinoscopy for mediastinal nodal staging of cN1 lung cancer. METHODS: Consecutive patients with operable and resectable cN1 non-small cell lung cancer underwent a lobe-specific mediastinal nodal staging by endosonography. The primary study outcome was sensitivity to detect N2 disease. The secondary end points were the prevalence of N2 disease, the negative predictive value (NPV) of both endosonography and endosonography with confirmatory mediastinoscopy, and the number of patients needed to detect one additional N2 disease with mediastinoscopy. RESULTS: Of the 100 patients with cN1 on imaging, 24 patients were diagnosed with N2 disease. Invasive mediastinal nodal staging with endosonography alone has a sensitivity of 38%, which can be increased to 73% by adding a mediastinoscopy. NPV was 81% and 91%, respectively. Ten mediastinoscopies are needed to detect one additional N2 disease missed by endosonography. CONCLUSIONS: Endosonography alone has an unsatisfactory sensitivity to detect mediastinal nodal metastasis in cN1 lung cancer, and the addition of a confirmatory mediastinoscopy is of added value. TRIAL REGISTRY: ClinicalTrials.gov; No.: NCT01456429; URL: www.clinicaltrials.gov.

Background: Studies have shown associations between mortality and long-term exposure to particulate matter air pollution. Few cohort studies have estimated the effects of the elemental composition of particulate matter on mortality. oBjectives: Our aim was to study the association between natural-cause mortality and long-term exposure to elemental components of particulate matter. Methods: Mortality and confounder data from 19 European cohort studies were used. Residential exposure to eight a priori–selected components of particulate matter (PM) was characterized following a strictly standardized protocol. Annual average concentrations of copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc within PM size fractions ≤ 2.5 μm (PM2.5) and ≤ 10 μm (PM10) were estimated using land-use regression models. Cohort-specific statistical analyses of the associations between mortality and air pollution were conducted using Cox proportional hazards models using a common protocol followed by meta-analysis. results: The total study population consisted of 291,816 participants, of whom 25,466 died from a natural cause during follow-up (average time of follow-up, 14.3 years). Hazard ratios were positive for almost all elements and statistically significant for PM2.5 sulfur (1.14; 95% CI: 1.06, 1.23 per 200 ng/m3). In a two-pollutant model, the association with PM2.5 sulfur was robust to adjustment for PM2.5 mass, whereas the association with PM2.5 mass was reduced. conclusions: Long-term exposure to PM2.5 sulfur was associated with natural-cause mortality. This association was robust to adjustment for other pollutants and PM2.5. © 2015, Public Health Services, US Dept of Health and Human Services. All rights reserved.

An increasing number of epidemiological studies suggest that adverse health effects of air pollution may be related to particulate matter (PM) composition, particularly trace metals. However, we lack comprehensive data on the spatial distribution of these elements.We measured PM2.5 and PM10 in twenty study areas across Europe in three seasonal two-week periods over a year using Harvard impactors and standardized protocols. In each area, we selected street (ST), urban (UB) and regional background (RB) sites (totaling 20) to characterize local spatial variability. Elemental composition was determined by energy-dispersive X-ray fluorescence analysis of all PM2.5 and PM10 filters. We selected a priori eight (Cu, Fe, K, Ni, S, Si, V, Zn) well-detected elements of health interest, which also roughly represented different sources including traffic, industry, ports, and wood burning.PM elemental composition varied greatly across Europe, indicating different regional influences. Average street to urban background ratios ranged from 0.90 (V) to 1.60 (Cu) for PM2.5 and from 0.93 (V) to 2.28 (Cu) for PM10.Our selected PM elements were variably correlated with the main pollutants (PM2.5, PM10, PM2.5 absorbance, NO2 and NOx) across Europe: in general, Cu and Fe in all size fractions were highly correlated (Pearson correlations above 0.75); Si and Zn in the coarse fractions were modestly correlated (between 0.5 and 0.75); and the remaining elements in the various size fractions had lower correlations (around 0.5 or below). This variability in correlation demonstrated the distinctly different spatial distributions of most of the elements. Variability of PM10_Cu and Fe was mostly due to within-study area differences (67% and 64% of overall variance, respectively) versus between-study area and exceeded that of most other traffic-related pollutants, including NO2 and soot, signaling the importance of non-tailpipe (e.g., brake wear) emissions in PM. © 2015 Elsevier Ltd.

Background: Land use regression (LUR) models have been developed mostly to explain intraurban variations in air pollution based on often small local monitoring campaigns. Transferability of LUR models from city to city has been investigated, but little is known about the performance of models based on large numbers of monitoring sites covering a large area. Objectives: We aimed to develop European and regional LUR models and to examine their transferability to areas not used for model development. Methods: We evaluated LUR models for nitrogen dioxide (NO2) and particulate matter (PM; PM2.5, PM2.5 absorbance) by combining standardized measurement data from 17 (PM) and 23 (NO2) ESCAPE (European Study of Cohorts for Air Pollution Effects) study areas across 14 European countries for PM and NO2. Models were evaluated with cross-validation (CV) and hold-out validation (HV). We investigated the transferability of the models by successively excluding each study area from model building. Results: The European model explained 56% of the concentration variability across all sites for NO2, 86% for PM2.5, and 70% for PM2.5 absorbance. The HV R2s were only slightly lower than the model R2 (NO2, 54%; PM2.5, 80%; PM2.5 absorbance, 70%). The European NO2, PM2.5, and PM2.5 absorbance models explained a median of 59%, 48%, and 70% of within-area variability in individual areas. The transferred models predicted a modest-to-large fraction of variability in areas that were excluded from model building (median R2: NO2, 59%; PM2.5, 42%; PM2.5 absorbance, 67%). Conclusions: Using a large data set from 23 European study areas, we were able to develop LUR models for NO2 and PM metrics that predicted measurements made at independent sites and areas reasonably well. This finding is useful for assessing exposure in health studies conducted in areas where no measurements were conducted.

Background Few studies on long-term exposure to air pollution and mortality have been reported from Europe. Within the multicentre European Study of Cohorts for Air Pollution Effects (ESCAPE), we aimed to investigate the association between natural-cause mortality and long-term exposure to several air pollutants. Methods We used data from 22 European cohort studies, which created a total study population of 367 251 participants. All cohorts were general population samples, although some were restricted to one sex only. With a strictly standardised protocol, we assessed residential exposure to air pollutants as annual average concentrations of particulate matter (PM) with diameters of less than 2.5 μm (PM2.5), less than 10 μm (PM 10), and between 10 μm and 2.5 μm (PMcoarse), PM2.5 absorbance, and annual average concentrations of nitrogen oxides (NO2 and NOx) with land use regression models. We also investigated two traffic intensity variables-traffic intensity on the nearest road (vehicles per day) and total traffic load on all major roads within a 100 m buffer. We did cohort-specific statistical analyses using confounder models with increasing adjustment for confounder variables, and Cox proportional hazards models with a common protocol. We obtained pooled effect estimates through a random-effects metaanalysis. Findings The total study population consisted of 367 251 participants who contributed 5 118 039 person-years at risk (average follow-up 13.9 years), of whom 29 076 died from a natural cause during follow-up. A significantly increased hazard ratio (HR) for PM2.5 of 1.07 (95% CI 1.02-1.13) per 5 μg/m3 was recorded. No heterogeneity was noted between individual cohort effect estimates (I2 p value=0.95). HRs for PM2.5 remained significantly raised even when we included only participants exposed to pollutant concentrations lower than the European annual mean limit value of 25 μg/m3 (HR 1.06, 95% CI 1.00-1.12) or below 20 μg/m3 (1.07, 1.01-1.13). Interpretation Long-term exposure to fine particulate air pollution was associated with natural-cause mortality, even within concentration ranges well below the present European annual mean limit value.

Land use regression (LUR) models have been used to model concentrations of mainly traffic-related air pollutants (nitrogen oxides (NOx), particulate matter (PM) mass or absorbance). Few LUR models are published of PM composition, whereas the interest in health effects related to particle composition is increasing. The aim of our study was to evaluate LUR models of polycyclic aromatic hydrocarbons (PAH), hopanes/steranes, and elemental and organic carbon (EC/OC) content of PM2.5. In 10 European study areas, PAH, hopanes/steranes, and EC/OC concentrations were measured at 16-40 sites per study area. LUR models for each study area were developed on the basis of annual average concentrations and predictor variables including traffic, population, industry, natural land obtained from geographic information systems. The highest median model explained variance (R2) was found for EC - 84%. The median R2 was 51% for OC, 67% for benzo[a]pyrene, and 38% for sum of hopanes/steranes, with large variability between study areas. Traffic predictors were included in most models. Population and natural land were included frequently as additional predictors. The moderate to high explained variance of LUR models and the overall moderate correlation with PM2.5 model predictions support the application of especially the OC and PAH models in epidemiological studies. © 2014 American Chemical Society.

Rationale: Prospective cohort studies have shown that chronic exposure to particulate matter and traffic-related air pollution is associated with reduced survival. However, the effects on nonmalignant respiratory mortality are less studied, and the data reported are less consistent. Objectives: We have investigated the relationship of long-term exposure to air pollution and nonmalignant respiratory mortality in 16 cohorts with individual level data within the multicenter European Study of Cohorts for Air Pollution Effects (ESCAPE). Methods: Data from 16 ongoing cohort studies from Europe were used. The total number of subjects was 307,553. There were 1,559 respiratory deaths during follow-up. Measurements and Main Results: Air pollution exposure was estimated by land use regression models at the baseline residential addresses of study participants and traffic-proximity variables were derived from geographical databases following a standardized procedure within the ESCAPE study. Cohort-specific hazard ratios obtained by Cox proportional hazard models from standardized individual cohort analyses were combined using metaanalyses. We found no significant associations between air pollution exposure and nonmalignant respiratory mortality. Most hazard ratios were slightly below unity, with the exception of the traffic-proximity indicators. Conclusions: In this study of 16 cohorts, there was no association between air pollution exposure and nonmalignant respiratorymortality.Copyright © 2014 by the American Thoracic Society.

Limited information is available on the contribution of organic components in particulate matter to health effects related to fine particles. Spatial variability of specific fine particle organic components has not been assessed with consistent methods. The aim of this paper is to assess spatial variation of organic components of fine particles within and between European study areas. Highly standardized measurements of polycyclic aromatic hydrocarbons (PAH), hopanes/steranes, elemental/organic carbon (EC/OC) and levoglucosan were performed measured in ten study areas across Europe. In each study area, measurements were conducted at street, urban and regional background sites. Three two-week samples were taken per site and the annual average levels of pollutants were calculated using continuous measurements at one background site as a reference.Substantial variations within and between the study areas were found. EC/OC and hopanes/steranes concentrations were highest in southern European study areas and lowest in northern locations. PAH concentrations were lowest in London/Oxford and highest in Copenhagen, Rome and Athens. Concentrations at street locations were higher than at background locations in all study areas and for all components. However, these differences varied considerably between study areas and components. EC had the highest median street to urban background ratio (1.62), OC the lowest (1.32). EC was highly correlated with NOx and PM2.5 absorbance in all areas, with median r=0.85 and r=0.89, respectively. The correlation between OC and other components was variable, with a median correlation of 0.65 with PM2.5 mass and a weak (0.18) correlation with σhopanes/steranes. σPAH correlated moderately with EC (r=0.59) and weakly with ∑hopanes/steranes (r=0.36).In conclusion, substantial variability was found in spatial patterns of atmospheric EC, OC, PAH and hopanes/steranes both within and between European study areas. The application of this highly standardized measurement approach across different locations will contribute to a consistent assessment of air pollutant levels and potentially contribute to understanding health effects associated with them. © 2014 Elsevier Ltd.

Background: Associations between long-term exposure to ambient particulate matter (PM) and cardiovascular (CVD) mortality have been widely recognized. However, health effects of long-term exposure to constituents of PM on total CVD mortality have been explored in a single study only. Aims: The aim of this study was to examine the association of PM composition with cardiovascular mortality. Methods: We used data from 19 European ongoing cohorts within the framework of the ESCAPE (European Study of Cohorts for Air Pollution Effects) and TRANSPHORM (Transport related Air Pollution and Health impacts - Integrated Methodologies for Assessing Particulate Matter) projects. Residential annual average exposure to elemental constituents within particle matter smaller than 2.5 and 10μm (PM2.5 and PM10) was estimated using Land Use Regression models. Eight elements representing major sources were selected a priori (copper, iron, potassium, nickel, sulfur, silicon, vanadium and zinc). Cohort-specific analyses were conducted using Cox proportional hazards models with a standardized protocol. Random-effects meta-analysis was used to calculate combined effect estimates. Results: The total population consisted of 322,291 participants, with 9545 CVD deaths. We found no statistically significant associations between any of the elemental constituents in PM2.5 or PM10 and CVD mortality in the pooled analysis. Most of the hazard ratios (HRs) were close to unity, e.g. for PM10 Fe the combined HR was 0.96 (0.84-1.09). Elevated combined HRs were found for PM2.5 Si (1.17, 95% CI: 0.93-1.47), and S in PM2.5 (1.08, 95% CI: 0.95-1.22) and PM10 (1.09, 95% CI: 0.90-1.32). Conclusion: In a joint analysis of 19 European cohorts, we found no statistically significant association between long-term exposure to 8 elemental constituents of particles and total cardiovascular mortality. •Few studies explored long term effects of particle composition exposure to cardiovascular mortality.•We included a large population of 322,291 subjects from 19 cohorts in 12 countries of Europe.•Standardized cohort specific analyses were conducted individually and the results were pooled in meta-analysis.•We found no significant association between elemental constituents representing major sources and cardiovascular mortality.•Positive though non-significant associations were found for S and Si. © 2014 Elsevier Ltd.

Background: Land-use regression (LUR) and dispersion models (DM) are commonly used for estimating individual air pollution exposure in population studies. Few comparisons have however been made of the performance of these methods. Objectives: Within the European Study of Cohorts for Air Pollution Effects (ESCAPE) we explored the differences between LUR and DM estimates for NO2, PM10 and PM2.5. Methods: The ESCAPE study developed LUR models for outdoor air pollution levels based on a harmonised monitoring campaign. In thirteen ESCAPE study areas we further applied dispersion models. We compared LUR and DM estimates at the residential addresses of participants in 13 cohorts for NO2; 7 for PM10 and 4 for PM2.5. Additionally, we compared the DM estimates with measured concentrations at the 20-40 ESCAPE monitoring sites in each area. Results: The median Pearson R (range) correlation coefficients between LUR and DM estimates for the annual average concentrations of NO2, PM10 and PM2.5 were 0.75 (0.19-0.89), 0.39 (0.23-0.66) and 0.29 (0.22-0.81) for 112,971 (13 study areas), 69,591 (7) and 28,519 (4) addresses respectively. The median Pearson R correlation coefficients (range) between DM estimates and ESCAPE measurements were of 0.74 (0.09-0.86) for NO2; 0.58 (0.36-0.88) for PM10 and 0.58 (0.39-0.66) for PM2.5. Conclusions: LUR and dispersion model estimates correlated on average well for NO2 but only moderately for PM10 and PM2.5, with large variability across areas. DM predicted a moderate to large proportion of the measured variation for NO2 but less for PM10 and PM2.5. © 2014 Elsevier Ltd.

Background: Air pollution has been associated with cardiovascular mortality, but it remains unclear as to whether specific pollutants are related to specific cardiovascular causes of death. Within the multicenter European Study of Cohorts for Air Pollution Effects (ESCAPE), we investigated the associations of long-term exposure to several air pollutants with all cardiovascular disease (CVD) mortality, as well as with specific cardiovascular causes of death. Methods: Data from 22 European cohort studies were used. Using a standardized protocol, study area-specific air pollution exposure at the residential address was characterized as annual average concentrations of the following: nitrogen oxides (NO2and NOx); particles with diameters of less than 2.5 μm (PM2.5), less than 10 μm (PM10), and 10 μm to 2.5 μm (PMcoarse); PM2.5absorbance estimated by land-use regression models; and traffic indicators. We applied cohort-specific Cox proportional hazards models using a standardized protocol. Random-effects meta-analysis was used to obtain pooled effect estimates. Results: The total study population consisted of 367,383 participants, with 9994 deaths from CVD (including 4,992 from ischemic heart disease, 2264 from myocardial infarction, and 2484 from cerebrovascular disease). All hazard ratios were approximately 1.0, except for particle mass and cerebrovascular disease mortality; for PM2.5, the hazard ratio was 1.21 (95% confidence interval = 0.87-1.69) per 5 μg/m and for PM10, 1.22 (0.91-1.63) per 10 μg/m. Conclusion: In a joint analysis of data from 22 European cohorts, most hazard ratios for the association of air pollutants with mortality from overall CVD and with specific CVDs were approximately 1.0, with the exception of particulate mass and cerebrovascular disease mortality for which there was suggestive evidence for an association. Copyright © 2014 by Lippincott Williams & Wilkins.

Land use regression models (LUR) frequently use leave-one-out-cross- validation (LOOCV) to assess model fit, but recent studies suggested that this may overestimate predictive ability in independent data sets. Our aim was to evaluate LUR models for nitrogen dioxide (NO2) and particulate matter (PM) components exploiting the high correlation between concentrations of PM metrics and NO2. LUR models have been developed for NO2, PM2.5 absorbance, and copper (Cu) in PM10 based on 20 sites in each of the 20 study areas of the ESCAPE project. Models were evaluated with LOOCV and "hold-out evaluation (HEV)" using the correlation of predicted NO2 or PM concentrations with measured NO2 concentrations at the 20 additional NO2 sites in each area. For NO2, PM2.5 absorbance and PM10 Cu, the median LOOCV R2s were 0.83, 0.81, and 0.76 whereas the median HEV R 2 were 0.52, 0.44, and 0.40. There was a positive association between the LOOCV R2 and HEV R2 for PM2.5 absorbance and PM10 Cu. Our results confirm that the predictive ability of LUR models based on relatively small training sets is overestimated by the LOOCV R2s. Nevertheless, in most areas LUR models still explained a substantial fraction of the variation of concentrations measured at independent sites. © 2013 American Chemical Society.

Estimating within-city variability in air pollution concentrations is important. Land use regression (LUR) models are able to explain such small-scale within-city variations. Transparency in LUR model development methods is important to facilitate comparison of methods between different studies. We therefore developed LUR models in a standardized way in 36 study areas in Europe for the ESCAPE (European Study of Cohorts for Air Pollution Effects) project.Nitrogen dioxide (NO2) and nitrogen oxides (NOx) were measured with Ogawa passive samplers at 40 or 80 sites in each of the 36 study areas. The spatial variation in each area was explained by LUR modelling. Centrally and locally available Geographic Information System (GIS) variables were used as potential predictors. A leave-one out cross-validation procedure was used to evaluate the model performance.There was substantial contrast in annual average NO2 and NOx concentrations within the study areas. The model explained variances (R2) of the LUR models ranged from 55% to 92% (median 82%) for NO2 and from 49% to 91% (median 78%) for NOx. For most areas the cross-validation R2 was less than 10% lower than the model R2. Small-scale traffic and population/household density were the most common predictors. The magnitude of the explained variance depended on the contrast in measured concentrations as well as availability of GIS predictors, especially traffic intensity data were important. In an additional evaluation, models in which local traffic intensity was not offered had 10% lower R2 compared to models in the same areas in which these variables were offered.Within the ESCAPE project it was possible to develop LUR models that explained a large fraction of the spatial variance in measured annual average NO2 and NOx concentrations. These LUR models are being used to estimate outdoor concentrations at the home addresses of participants in over 30 cohort studies. © 2013 Elsevier Ltd.

Background: Ambient air pollution is suspected to cause lung cancer. We aimed to assess the association between long-term exposure to ambient air pollution and lung cancer incidence in European populations. Methods: This prospective analysis of data obtained by the European Study of Cohorts for Air Pollution Effects used data from 17 cohort studies based in nine European countries. Baseline addresses were geocoded and we assessed air pollution by land-use regression models for particulate matter (PM) with diameter of less than 10 μm (PM10), less than 2·5 μm (PM2·5), and between 2·5 and 10 μm (PMcoarse), soot (PM2·5absorbance), nitrogen oxides, and two traffic indicators. We used Cox regression models with adjustment for potential confounders for cohort-specific analyses and random effects models for meta-analyses. Findings: The 312-944 cohort members contributed 4-013-131 person-years at risk. During follow-up (mean 12·8 years), 2095 incident lung cancer cases were diagnosed. The meta-analyses showed a statistically significant association between risk for lung cancer and PM10 (hazard ratio [HR] 1·22 [95% CI 1·03-1·45] per 10 μg/m3). For PM2·5 the HR was 1·18 (0·96-1·46) per 5 μg/m3. The same increments of PM10 and PM2·5 were associated with HRs for adenocarcinomas of the lung of 1·51 (1·10-2·08) and 1·55 (1·05-2·29), respectively. An increase in road traffic of 4000 vehicle-km per day within 100 m of the residence was associated with an HR for lung cancer of 1·09 (0·99-1·21). The results showed no association between lung cancer and nitrogen oxides concentration (HR 1·01 [0·95-1·07] per 20 μg/m3) or traffic intensity on the nearest street (HR 1·00 [0·97-1·04] per 5000 vehicles per day). Interpretation: Particulate matter air pollution contributes to lung cancer incidence in Europe. Funding: European Community's Seventh Framework Programme. © 2013 Elsevier Ltd.

Land Use Regression (LUR) models have been used to describe and model spatial variability of annual mean concentrations of traffic related pollutants such as nitrogen dioxide (NO2), nitrogen oxides (NOx) and particulate matter (PM). No models have yet been published of elemental composition. As part of the ESCAPE project, we measured the elemental composition in both the PM10 and PM2.5 fraction sizes at 20 sites in each of 20 study areas across Europe. LUR models for eight a priori selected elements (copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V), and zinc (Zn)) were developed. Good models were developed for Cu, Fe, and Zn in both fractions (PM10 and PM 2.5) explaining on average between 67 and 79% of the concentration variance (R2) with a large variability between areas. Traffic variables were the dominant predictors, reflecting nontailpipe emissions. Models for V and S in the PM10 and PM2.5 fractions and Si, Ni, and K in the PM10 fraction performed moderately with R2 ranging from 50 to 61%. Si, NI, and K models for PM2.5 performed poorest with R2 under 50%. The LUR models are used to estimate exposures to elemental composition in the health studies involved in ESCAPE. © 2013 American Chemical Society.

Land Use Regression (LUR) models have been used increasingly for modeling small-scale spatial variation in air pollution concentrations and estimating individual exposure for participants of cohort studies. Within the ESCAPE project, concentrations of PM2.5, PM2.5 absorbance, PM10, and PMcoarse were measured in 20 European study areas at 20 sites per area. GIS-derived predictor variables (e.g., traffic intensity, population, and land-use) were evaluated to model spatial variation of annual average concentrations for each study area. The median model explained variance (R2) was 71% for PM2.5 (range across study areas 35-94%). Model R2 was higher for PM2.5 absorbance (median 89%, range 56-97%) and lower for PMcoarse (median 68%, range 32- 81%). Models included between two and five predictor variables, with various traffic indicators as the most common predictors. Lower R2 was related to small concentration variability or limited availability of predictor variables, especially traffic intensity. Cross validation R2 results were on average 8-11% lower than model R2. Careful selection of monitoring sites, examination of influential observations and skewed variable distributions were essential for developing stable LUR models. The final LUR models are used to estimate air pollution concentrations at the home addresses of participants in the health studies involved in ESCAPE. © 2012 American Chemical Society.

The ESCAPE study (European Study of Cohorts for Air Pollution Effects) investigates relationships between long-term exposure to outdoor air pollution and health using cohort studies across Europe. This paper analyses the spatial variation of PM2.5, PM2.5 absorbance, PM10 and PMcoarse concentrations between and within 20 study areas across Europe.We measured NO2, NOx, PM2.5, PM2.5 absorbance and PM10 between October 2008 and April 2011 using standardized methods. PMcoarse was determined as the difference between PM10 and PM2.5. In each of the twenty study areas, we selected twenty PM monitoring sites to represent the variability in important air quality predictors, including population density, traffic intensity and altitude. Each site was monitored over three 14-day periods spread over a year, using Harvard impactors. Results for each site were averaged after correcting for temporal variation using data obtained from a reference site, which was operated year-round.Substantial concentration differences were observed between and within study areas. Concentrations for all components were higher in Southern Europe than in Western and Northern Europe, but the pattern differed per component with the highest average PM2.5 concentrations found in Turin and the highest PMcoarse in Heraklion. Street/urban background concentration ratios for PMcoarse (mean ratio 1.42) were as large as for PM2.5 absorbance (mean ratio 1.38) and higher than those for PM2.5 (1.14) and PM10 (1.23), documenting the importance of non-tailpipe emissions. Correlations between components varied between areas, but were generally high between NO2 and PM2.5 absorbance (average R2 = 0.80). Correlations between PM2.5 and PMcoarse were lower (average R2 = 0.39). Despite high correlations, concentration ratios between components varied, e.g. the NO2/PM2.5 ratio varied between 0.67 and 3.06.In conclusion, substantial variability was found in spatial patterns of PM2.5, PM2.5 absorbance, PM10 and PMcoarse. The highly standardized measurement of particle concentrations across Europe will contribute to a consistent assessment of health effects across Europe. © 2012 Elsevier Ltd.

The ESCAPE study (European Study of Cohorts for Air Pollution Effects) investigates long-term effects of exposure to air pollution on human health in Europe. This paper documents the spatial variation of measured NO2 and NOx concentrations between and within 36 ESCAPE study areas across Europe.In all study areas NO2 and NOx were measured using standardized methods between October 2008 and April 2011. On average, 41 sites were selected per study area, including regional and urban background as well as street sites. The measurements were conducted in three different seasons, using Ogawa badges. Average concentrations for each site were calculated after adjustment for temporal variation using data obtained from a routine monitor background site.Substantial spatial variability was found in NO2 and NOx concentrations between and within study areas; 40% of the overall NO2 variance was attributable to the variability between study areas and 60% to variability within study areas. The corresponding values for NOx were 30% and 70%. The within-area spatial variability was mostly determined by differences between street and urban background concentrations. The street/urban background concentration ratio for NO2 varied between 1.09 and 3.16 across areas. The highest median concentrations were observed in Southern Europe, the lowest in Northern Europe.In conclusion, we found significant contrasts in annual average NO2 and NOx concentrations between and especially within 36 study areas across Europe. Epidemiological long-term studies should therefore consider different approaches for better characterization of the intra-urban contrasts, either by increasing of the number of monitors or by modelling. © 2012 Elsevier Ltd.

Evidence is increasing that long-term exposure to ambient air pollution is associated with deaths from cardiopulmonary diseases. In a 2002 pilot study, we reported clear indications that traffic-related air pollution, especially at the local scale, was related to cardiopulmonary mortality in a randomly selected subcohort of 5000 older adults participating in the ongoing Netherlands Cohort Study (NLCS) on diet and cancer. In the current study, referred to as NLCS-AIR, our objective was to obtain more precise estimates of the effects of traffic-related air pollution by analyzing associations with cause-specific mortality, as well as lung cancer incidence, in the full cohort of approximately 120,000 subjects. Cohort members were 55 to 69 years of age at enrollment in 1986. Follow-up was from 1987 through 1996 for mortality (17,674 deaths) and from late 1986 through 1997 for lung cancer incidence (2234 cases). Information about potential confounding variables and effect modifiers was available from the questionnaire that subjects completed at enrollment and from publicly available data (including neighborhood-scale information such as income distributions). The NLCS was designed for a case-cohort approach, which makes use of all the cases in the full cohort, while data for the random subcohort are used to estimate person-time experience in the study. Full information on confounders was available for the subjects in the random subcohort and for the emerging cases of mortality and lung cancer incidence during the follow-up period, and in NLCS-AIR we used the case-cohort approach to examine the relation between exposure to air pollution and cause-specific mortality and lung cancer. We also specified a standard Cox proportional hazards model within the full cohort, for which information on potential confounding variables was much more limited. Exposure to air pollution was estimated for the subjects' home addresses at baseline in 1986. Concentrations were estimated for black smoke (a simple marker for soot) and nitrogen dioxide (NO2) as indicators of traffic-related air pollution, as well as nitric oxide (NO), sulfur dioxide (SO2), and particulate matter with aerodynamic diameter 65 A-weighted decibels (dB(A); decibels with the sound pressure scale adjusted to conform with the frequency response of the human ear). Examination of sex, smoking status, educational level, and vegetable and fruit intake as possible effect modifiers showed that for overall black smoke concentrations, associations with mortality tended to be stronger in case-cohort subjects with lower levels of education and those with low fruit intake, but differences between strata were not statistically significant. For lung cancer incidence, we found essentially no relation to exposure to NO2, black smoke, PM2.5, SO2, or several traffic indicators. Associations of overall air pollution concentrations and traffic indicator variables with lung cancer incidence were, however, found in subjects who had never smoked, with an RR of 1.47 (95% CI, 1.01-2.16) for a 10-microg/m3 increase in overall black smoke concentration. In the current study, the mortality risks associated with both background air pollution and traffic exposure variables were much smaller than the estimate previously reported in the pilot study for risk of cardiopulmonary mortality associated with living near a major road (RR, 1.95; 95% CI, 1.09-3.51). The differences are most likely due to the extension of the follow-up period in the current study and to random error in the pilot study related to sampling from the full cohort. Though relative risks were generally small in the current study, long-term average concentrations of black smoke, NO2, and PM2.5 were related to mortality, and associations of black smoke and NO2 exposure with natural-cause and respiratory mortality were statistically significant. Traffic intensity near the home was also related to natural-cause mortality. The highest relative risks associated with background air pollution and traffic variables were for respiratory mortality, though the number of deaths was smaller than for the other mortality categories.

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The long-term effects of a standard lactate-buffered dialysis fluid and a new, two-chamber, bicarbonate/lactate-buffered dialysis fluid (with fewer glucose degradation products and a neutral pH) were compared in an in vivo peritoneal exposure model. Rats were given daily injections, via an access port, of 10 ml of standard solution or bicarbonate/lactate-buffered solution for 9 to 10 wk. The omentum, peritoneum, and mesothelial cell layer were screened for morphologic changes. In addition, the bacterial clearing capacity of the peritoneal cells was studied. Significantly more milky spots and blood vessels were observed in the omenta of animals treated with standard solution (P < 0.03 for both parameters). Electron-microscopic analysis demonstrated dramatic changes in the appearance of the vascular endothelial cells of the milky spots and a severely damaged or even absent mesothelium on the peritoneal membrane of the standard solution-treated animals. In contrast, the mesothelium was still present in the bicarbonate/lactate-buffered solution group, although the cells lost microvilli. Both peritoneal dialysis fluids significantly increased the density of mesothelial cells (per square millimeter) on the surface of the liver and the thickness of the submesothelial extracellular matrix of the peritoneum (both P < 0.04 for both fluids versus control). A significantly better ex vivo bacterial clearing capacity was observed with peritoneal cells from the bicarbonate/lactate-buffered solution group, compared with the standard solution group (P < 0.05 in both experiments). These results demonstrate that instillation of bicarbonate/lactate-buffered solution into rats for 9 to 10 wk preserves both morphologic and immune parameters much more effectively, compared with standard solution. These findings may be of considerable clinical importance.

CD163 is a member of the group B scavenger receptor cysteine-rich (SRCR) superfamily. This study describes aspects of the tissue distribution, the regulation of expression, and signal transduction after cross-linking of this receptor at the cell surface of macrophages. CD163 showed an exclusive expression on resident macrophages (e.g., red pulp macrophages, alveolar macrophages). The expression was inducible on monocyte-derived macrophages by glucocorticoids but not by interleukin-4 (IL-4), granulocyte-macrophage colony-stimulating factor (GM-CSF), and interferon-gamma. The combination of IL-4 or GM-CSF with glucocorticoids resulted in a further increase. Subcellular analysis of alveolar macrophages by immunoelectron microscopy showed a plasma membrane localization of the antigen. Cross-linking of CD163 with monoclonal antibody induced a protein tyrosine kinase-dependent signal that resulted in (1) slow-type calcium mobilization, (2) inositol triphosphate production, and (3) secretion of IL-6 and GM-CSF. The data suggest a function for the SRCR-superfamily receptor CD163 in the regulation of inflammatory processes by macrophages.

CD163 is a member of the group B scavenger receptor cysteine-rich (SRCR) superfamily. This study describes aspects of the tissue distribution, the regulation of expression, and signal transduction after cross-linking of this receptor at the cell surface of macrophages. CD163 showed an exclusive expression on resident macrophages (e.g., red pulp macrophages, alveolar macrophages). The expression was inducible on monocyte-derived macrophages by glucocorticoids but not by interleukin-4 (IL-4), granulocyte-macrophage colony-stimulating factor (GM-CSF), and interferon-gamma. The combination of IL-4 or GM-CSF with glucocorticoids resulted in a further increase. Subcellular analysis of alveolar macrophages by immunoelectron microscopy showed a plasma membrane localization of the antigen. Cross-linking of CD163 with monoclonal antibody induced a protein tyrosine kinase-dependent signal that resulted in (1) slow-type calcium mobilization, (2) inositol triphosphate production, and (3) secretion of IL-6 and GM-CSF. The data suggest a function for the SRCR-superfamily receptor CD163 in the regulation of inflammatory processes by macrophages.

To study the long-term effects of dialysis fluids on the peritoneal cavity, an in vivo model for continuous peritoneal dialysis in rats was developed. Mini vascular access ports were implanted subcutaneously in the neck of the rats and an attached catheter was instilled into the peritoneal cavity. Rats were injected daily with 10 mL of standard 3.86% Dianeal or saline for a period up to 12 weeks. In the peritoneal cavity an initial increase in total cells was observed after 4 weeks of fluid instillation. This had declined after 12 weeks. A similar trend was also seen for macrophage and neutrophil numbers, whereas the percentage of lymphocytes kept increasing in time. An effect of fluid instillation was observed on the density and the morphology of the mesothelial monolayer of the rats. A higher density of cells was observed after 12 weeks, and foci of young mesothelial cells within activated mesothelium were found. The results show that the rat model presented can be compared with the situation in the peritoneal cavity of continuous ambulatory peritoneal dialysis (CAPD) patients, and therefore is suitable for intervention studies

Peritoneal macrophages (PMs) are very potent producers of proinflammatory stimuli, such as interleukin (IL)-1 beta and tumor necrosis factor (TNF)-alpha. After contact with invading micro-organisms, PMs produce different cytokines, both pro- and anti-inflammatory. Therefore, they are crucial in the regulation of inflammatory events. The aim of this study was to investigate whether the production of IL-1 beta and TNF-alpha is dependent on the bacterial species used. PMs were harvested from spent peritoneal dialysis effluent and subsequently stimulated with five strains of bacteria in two different concentrations. After 24 hours of stimulation, supernatants were harvested and analyzed for both IL-1 beta and TNF-alpha content. IL-1 beta was measured with a commercial ELISA, and TNF-alpha was determined with a bioassay. Both the IL-1 beta and the TNF-alpha production were species-dependent. One strain of Staphylococcus aureus and one strain of Staphylococcus epidermidis induced a markedly higher response in both IL-1 beta and TNF-alpha than the other species. This response was also dose-dependent, and this holds true for all species. In conclusion, the IL-1 beta and TNF-alpha response by PMs is both species- and dose-dependent

Previous studies have demonstrated that mesothelial cells (MC) are important in the local host defense system of the peritoneal cavity. Most studies on the function of MC are performed on MC derived from material of patients with normal renal function (NRF). The aim of the present study was to examine differences in interleukin (IL)-8 expression by MC from patients with NRF and from patients with end-stage renal disease (ESRD). Therefore, MC were isolated from the omentum and pleural exudate of patients with NRF, from spent effluent of stable peritoneal dialysis (PD) patients, and from omentum obtained during catheter implantation prior to PD treatment. MC were stimulated with increasing doses of IL-1 beta or tumor necrosis factor-alpha for 24 hours, after which the supernatant was analyzed for IL-8 content. The IL-8 background level of MC isolated from patients with NRF was significantly lower than the IL-8 background level of MC derived from patients with ESRD. Although IL-8 production appeared to be higher in the ESRD MC, this difference was not significant after stimulation. While the overall immunity is depressed in uremia, MC are activated. The relatively high background of IL-8 might lead to an insensitivity of neutrophils by blocking the receptors and explain their impaired chemotaxis in uremia

OBJECTIVE: To investigate whether or not a change in dialysate interleukin-8 (IL-8) concentration precedes the onset of clinically overt peritonitis and is significant in the recruitment of granulocytes during continuous ambulatory peritoneal dialysis (CAPD)-related peritonitis. DESIGN: CAPD patients stored their overnight effluent at 4 degrees C, which was routinely thrown away after 2 days. If peritonitis developed, patients delivered their effluent of the preceding two nights and the peritonitis effluent for analysis. A control study was performed 1 to 3 months after recovery. Dialysate samples were analyzed for number of cells, differential cell count, IL-8 and elastase concentrations, and their neutrophil chemoattractive capacity. In addition, serum samples during peritonitis were analyzed for IL-8 concentrations. RESULTS: Ten peritonitis episodes in 7 patients were analyzed. Numbers of neutrophils and levels of dialysate IL-8 and elastase started to increase 4 to 12 hours before the first peritonitis effluent. The dialysate/serum IL-8 ratio was 423.5 during peritonitis and 7.0 in the postperitonitis controls. There was a significant correlation between the number of neutrophils and IL-8 concentration in the dialysate. The in vitro neutrophil chemotaxis was increased toward the peritonitis effluents, as compared to control effluents. Incubation of the peritonitis effluents with anti-IL-8 monoclonal antibody blocked the increase in neutrophil chemotaxis above control levels by an average of 26.7%. CONCLUSION: IL-8 is produced in the peritoneal cavity during CAPD treatment and may mediate part of the neutrophil recruitment and degranulation in the initial phase of a CAPD peritonitis

To investigate which members of the recently discovered family of chemotactic cytokines (chemokines) are important in leukocyte recruitment to a bacterial inflammation site, four different chemokines in the effluent of peritoneal dialysis patients suffering from acute bacterial peritonitis were measured. The presence of two neutrophil-attracting chemokines, interleukin-8 and human melanoma growth-stimulating activity (huGRO alpha), and two monocyte-attracting members of the chemokine superfamily, monocyte chemotactic protein-1 (MCP-1) and regulated on activation normal T cell expressed and secreted (RANTES), was investigated in patient effluents just before, during, and after a peritonitis episode. This was studied in seven peritonitis effluents of five patients by using chemokine-specific enzyme-linked immunosorbent assays. Cell populations in the dialysates were differentiated on cytocentrifuge preparations. The contribution of the detected chemokines to neutrophilic and monocytic cell influxes in the inflamed peritoneal cavity was analyzed by correlating concentrations of chemokines to the relevant cell numbers present in the dialysates of these patients. The detection of the neutrophil-attracting chemokine interleukin-8 during peritonitis was in accordance with other studies. Moreover, a second neutrophil chemoattractant, huGRO alpha, was identified in vivo. Both were elevated during inflammation (P < 0.02) and contributed significantly to the neutrophilic cell influx (P < 0.05). One of the monocyte-attracting chemokines, RANTES, could not be detected in any of the effluents, whereas the other, MCP-1, was significantly elevated during peritonitis (P < 0.02). In contrast to the other chemokines measured, MCP-1 concentration was relatively high in steady-state peritoneal dialysates. An absolute correlation between dialysate MCP-1 concentration and the number of macrophages in these effluents was absent. However, in a 48-well chemotaxis assay, monocyte migration toward peritonitis, as well as steady-state patient dialysates, could be blocked with antibodies to MCP-1. It was concluded, therefore, that MCP-1 is the most important monocyte chemoattractant in peritoneal dialysis steady-state and peritonitis patients; whereas, besides interleukin-8, huGRO alpha was identified as a major neutrophil-attracting chemokine in the peritonitis situation

Mesothelial cells that line the peritoneal cavity are capable of producing several proinflammatory cytokines such as interleukin-6 and interleukin-8. Since they are the most numerous cell in the peritoneal cavity when the lining mesothelial cells are included, they may play a major role in the local antibacterial defence mechanism. Cancer antigen (CA)125 is expressed by mesothelial cells (as by other coelomic epithelium-derived cells) and might therefore be considered a marker of the mesothelium. The aim of this study was to determine whether CA125 is a bulk or an activation stage mesothelial cell marker. A positive correlation was found between the mesothelial cell number and the CA125 concentration in dialysate of stable PD patients (P = 0.03). CA125 release by mesothelial cell cultures during confluence showed that the release per cell was constant in time. Stimulation of mesothelial cells in a confluential phase with IL1 beta, TNF alpha, IFN gamma and TGF beta did not result in an increase in CA125 release. Cell lysis showed that CA125 is also present intracellularly. This implies that release of intracellular CA125 can be a disturbing factor in interpreting the CA125 concentration of dialysate in situations where mesothelial cell death may occur, such as in peritonitis. It can be concluded, that our data show that dialysate CA125 is a bulk marker for the mesothelial cell mass in stable PD patients and can thus provide data on the state of the peritoneal membrane in the follow-up of the individual patient

We analysed the peritoneal cellular immune system 24-48 h before the onset of a clinical peritonitis. Peritoneal cells were obtained from the overnight dialysis effluents 1 or 2 days (day-1 and day-2) preceding the day of peritonitis, the last overnight effluent before the peritonitis effluent (day P), and the first peritonitis effluent. Nine peritonitis episodes of six patients were studied. The number of Fc receptor positive cells, the chemotactic activity, and immunophenotype of the peritoneal cell population at day-2 and day-1 were similar to the postperitonitis control effluent. However, immunophagocytosis and phagocytosis capacity of the peritoneal macrophages was decreased in five of six episodes at day-2 and -1 compared to control peritoneal macrophages. The overnight effluents of day P revealed a moderate influx of neutrophilic granulocytes and an increase of bacterial killing capacity and chemotactic activity. Activation of the peritoneal T cells at day P was shown by the increase in MHC class II positive T cells and an increase in the CD4/CD8 ratio. Bacterial cell cultures of the effluents were positive in three episodes 24-48 h before peritonitis, and of all overnight effluents at day P. These results indicate that malfunctioning of phagocytosis by peritoneal macrophages may contribute to the development of a CAPD peritonitis

In this study we have investigated whether mesothelial cells (MC) and mesothelial extracellular matrix (ECM) are suitable substrates for the adherence of Staphylococci. Mesothelial cells were isolated from the peritoneal dialysis effluent by making use of their lack of Fc-receptors and capacity to attach firmly to plastic. After 10 days post-confluency the MC monolayer was removed with 0.1% Triton-X100 and the presence of an ECM shown by enzyme linked immunosorbent assay (ELISA). The ELISA showed the presence of fibronectin and laminin but not of type IV collagen and vitronectin. Bacterial adherence assays with Staphylococcus aureus (N:3 isolates) adhered well to both ECM (33.4%) and MC monolayers (40.2%; ECM vs. MC monolayers p < 0.03). Staphylococcus aureus adhered significantly better to both ECM (p < 0.05) and MC monolayers (p < 0.05) when compared to plastic. Staphylococcus epidermidis (N:3 isolates) showed similar adherence for plastic (22.1%) and MC monolayers (23.5%); mesothelial ECM was a relatively poor substrate for adherence (6.8%, p < 0.03). In conclusion, results obtained sofar do not indicate an increased risk for adherence of Staphylococci when the mesothelial ECM is exposed