393 research outputs found
Quartz!? A randomized controlled quartz exposure intervention in the construction industry
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Prevention is better than a cure: practical control measures to prevent tick-borne encephalitis in military personnel and working dogs
No full textZowel militairen als hun werkhonden lopen het risico geïnfecteerd te worden met tekenencefalitis in endemische gebieden. Voor werkhonden zijn verschillende praktische preventieve maatregelen beschikbaar om dit risico te verkleinen. Het verdient aanbeveling om tijdens de voorbereidingen van oefeningen en uitzendingen stil te staan bij de verschillende dierziekterisico’s die in het beoogde operatiegebied kunnen worden aangetroffen
The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases
No full textThe SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article
Gender differences in lung function recovery after cessation of occupational endotoxin exposure: a complex story
No full textImpact of fine particles in ambient air on lung cancer
No full textRecently, the International Agency for Research on Cancer (IARC) has classified outdoor air pollution and the particulate matter component of outdoor air pollution as class I carcinogen. Air pollution is consistently associated with lung cancer in epidemiologic and experimental studies. The IARC assessment is specifically designed as hazard identification, and it does not quantify the magnitude of the cancer risk. This article addresses the magnitude of the lung cancer risk in the population due to ambient air pollution exposure
Temporal associations of ambient PM2.5 elemental concentrations with indoor and personal concentrations
No full textTime series studies increasingly evaluate health relevance of the elemental composition of particles smaller than 2.5 mu m (PM2.5). Validation studies have documented that temporal variation of outdoor PM2.5 concentration is correlated with temporal variation of personal exposure, but very few papers have investigated the temporal correlation between outdoor concentration and personal exposure for the elemental composition of PM2.5. We evaluated the temporal association between outdoor concentration and personal exposure for the elements copper (Cu), zinc (Zn), iron (Fe), potassium (K), nickel (Ni), vanadium (V), silicon (Si) and sulfur (S) in three European cities. In Helsinki (Finland), Utrecht (the Netherlands) and Barcelona (Spain) five participants from urban background, five from suburban/rural background and five from busy street sites were selected (15 participants per city). Six outdoor, indoor and personal 96-h average PM2.5 concentrations were measured simultaneously in three different seasons (winter, summer and spring/autumn). Concurrently, samples were collected at a central reference site, reflecting urban background air pollution levels. The temporal variation at the central site was highly correlated with personal exposure for all elements, except Cu. The highest correlations (Pearson's R) were found for S and V (R between 0.87 and 0.98). Lower correlations were found for the elements Cu, Fe and Si associated with non-tailpipe traffic emissions and road dust (Pearson's R between 0.34 and 0.79). For PM2.5 mass the R was lower (between -0.37 and 0.70). Exclusion of observations most affected by indoor sources increased the personal to central site correlations but did not fully explain differences between elements. The generally high correlation between temporal variation of the outdoor concentration and personal exposure supports the use of a central site for assessing exposure of PM components in time series studies for most elements. The different correlations found for the eight elements suggests that epidemiological associations are affected by differences in measurement error. (C) 2014 Elsevier Ltd. All rights reserved
Land use regression models for estimating individual NOx and NO2 exposures in a metropolis with a high density of traffic roads and population
No full textThis study is conducted to characterize the intra-urban distribution of NOx and NO2; develop land use regression (LUR) models to assess outdoor NOx and NO2 concentrations, using the ESCAPE modeling approach with locally specific land use data; and compare NOx and NO2 exposures for children in the Taipei Metropolis by the LUR models, the nearest monitoring station, and kriging methods based on data collected at the measurement sites. NOx and NO2 were measured for 2 weeks during 3 seasons at 40 sampling sites by Ogawa passive badges to represent their concentrations at urban backgrounds and streets from October 2009 to September 2010. land use data and traffic-related information in different buffer zones were combined with measured concentrations to derive LUR models using supervised forward stepwise multiple regressions. The annual average concentrations of NOx and NO2 in Taipei were 72.4 +/- 22.5 and 48.9 +/- 12.2 mu g/m(3), respectively, which were at the high end of all 36 European areas in the ESCAPE project. Spatial contrasts in Taipei were lower than those of the European areas in the ESCAPE project. The NOx LUR model included 6 land use variables, which were lengths of major roads within 25 m, 25-50 m, and 50-500 m, urban green areas within 300 m and 300-5000 m, and semi-natural and forested areas within 500 m, with R-2 = 0.81. The NO2 LUR model included 4 land use variables, which were lengths of major roads within 25 m, urban green areas within 100 m, semi-natural and forested areas within 500 m, and low-density residential area within 500 m, with R-2 = 0.74. The LUR models gave a wider variation in estimating NOx and NO2 exposures than either the ordinary kriging method or the nearest measurement site did for the children of Taiwan Birth Cohort Study (TBCS) in Taipei. (C) 2013 Published by Elsevier B.V
Airborne Transmission of Coxiella burnetii: Spatial dispersion modelling and the effects of meteorological and environmental conditions on Q fever incidence
No full textThe Netherlands experienced the largest human and veterinary Q fever epidemic ever described. From 2007 through 2010, over 4,000 human cases were notified and approximately a twelve-fold higher number was probably infected by Coxiella burnetii, the causative agent of Q fever. Dairy goat farms, and to a lesser extent dairy sheep farms, were identified as the major source of these human infections with high Coxiella burnetii shedding rates during parturition of the animals. The epidemic curves showed a very clear seasonal pattern with peaks of human Q fever cases following the lambing and kidding season of sheep and goats. In addition, a very clear spatial pattern was visible as well: the majority of the infected farms and human patients were located/living in the same areas in the south of the country, and most human cases were spatially clustered close to the infected farms. Several published papers describing other outbreaks suggested an association between human Q fever incidence and specific meteorological and environmental conditions, such as wind speed and wind direction. With respect to the Dutch epidemic, the potential effects of meteorological and environmental conditions were confirmed by two pilot studies. The current project was based on these two pilot studies and aimed at (1) modelling the airborne dispersion of Coxiella burnetii in the environment with a focus on farm-to-human transmission, and (2) identifying environmental risk factors for the transmission of Coxiella burnetii from infected farms to humans. The main conclusions of this work include: 1) Livestock-related sources of Coxiella burnetii could be identified, even in the early stages of local outbreaks assuming an exponential incidence-distance method. 2) The distance between positive farms and the residential addresses of cases was a major predictor for Q fever incidence rates. 3) Atmospheric dispersion models - mechanistic models describing the transport of particles in the atmosphere using meteorological information (wind speed, wind direction, temperature, solar radiation, etc.) – are suitable for dispersion modelling of airborne pathogens. Modelled airborne Coxiella burnetii concentrations were a better predictor for Q fever incidence than distance alone. 4) Several variables related to transmission through re-aerosolisation from a contaminated environment – such as the sensitivity of soils to wind erosion – increased the correlation to reported Q fever incidence rates and thus probably influenced Coxiella burnetii exposure. The output tools from this study thus include a source identification model and a model to determine the time-dependent areas at risk given the location of a known source and atmospheric and environmental conditions. The latter tool could be fed with meteorological forecast data to establish predictions up to a few days ahead, or even with long-term climate scenarios. Nevertheless, we highly recommend applying our methods to other outbreak data and pathogens to better validate our findings. Also, more effort should be invested in determining time-dependent emission rates of Coxiella burnetii and defining a protocol for systematic and active surveillance (including air sampling) during future outbreaks of Coxiella burnetii or other zoonoses. This could lead to a better estimation of the public health risk of a future outbreak, and to more detailed and accurate hazard maps that could be used for spatial planning of livestock operations
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