The effect of adherence to statin therapy on cardiovascular mortality : quantification of unmeasured bias using falsification end-points

Background: To determine the clinical effectiveness of statins on cardiovascular mortality in practice, observational studies are needed. Control for confounding is essential in any observational study. Falsification end-points may be useful to determine if bias is present after adjustment has taken place. Methods: We followed starters on statin therapy in the Netherlands aged 46 to 100 years over the period 1996 to 2012, from initiation of statin therapy until cardiovascular mortality or censoring. Within this group (n = 49,688, up to 16 years of follow-up), we estimated the effect of adherence to statin therapy (0 = completely non-adherent, 1 = fully adherent) on ischemic heart diseases and cerebrovascular disease (ICD10-codes I20-I25 and I60-I69) as well as respiratory and endocrine disease mortality (ICD10-codes J00-J99 and E00-E90) as falsification end points, controlling for demographic factors, socio-economic factors, birth cohort, adherence to other cardiovascular medications, and diabetes using time-varying Cox regression models. Results: Falsification end-points indicated that a simpler model was less biased than a model with more controls. Adherence to statins appeared to be protective against cardiovascular mortality (HR: 0.70, 95 % CI 0.61 to 0.81). Conclusions: Falsification end-points helped detect overadjustment bias or bias due to competing risks, and thereby proved to be a useful technique in such a complex setting

RIO: A NOVEL APPROACH FOR AIR POLLUTION MAPPING

Real-time assessment of the ambient air quality has gained an increased interest in recent years. To give support to this evolution, the statistical air pollution interpolation model RIO is developed. Due to the very low computational cost this interpolation model is an efficient tool for an environment agency when performing real-time air quality assessments. Beside this, a reliable interpolation model can be used to produce analysed maps of historical data records as well. RIO is an interpolation model that can be classified as a detrended Kriging model. In a first step the local character of the air pollution sampling values is removed in a detrending procedure. Subsequently, the site-independent data is interpolated by an Ordinary Kriging scheme. Finally, in a retrending step a local bias is added to the Kriging interpolation results. As spatially resolved driving force in the detrending process, a land use indicator is developed based on the CORINE land cover data set. The indicator is optimized independently for the three pollutants O3, NO2 and PM10. As a result, the RIO model is able to account for the local character of the air pollution phenomenon at locations where no monitoring stations are available. Through a cross-validation procedure the superiority of the RIO model over standard interpolation techniques, such as the Ordinary Kriging is demonstrated. Air quality maps are presented for the three pollutants mentioned and compared to maps based on standard interpolation techniques

High-resolution 3D and (sub-)cellular level LA-ICP-MS imaging approaches : accumulation of toxic metals in biological material

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LINKING URBAN (STREET CANYON) MODELS WITH REGIONAL AIR QUALITY MODELS THROUGH URBAN BOUNDARY CONDITIONS

This contribution addresses the question of how detailed information from the urban canopy can be assimilated into regional models. This detailed information concerns, among others, road transport emissions, specific exchange and turbulence patterns in the built up canopy, and effects of roads and roughness elements on wind direction and wind speed. This information is typically obtained from detailed street canyon models in combination with traffic emission models. In order to integrate the dynamics of the urban canopy into regional air quality models, we propose the formulation of urban boundary conditions. The formulation has been tested and compared with measurements for benzene and NOx in the city of Antwerp, Belgium

Metabarcoding of marine zooplankton communities in the North Sea using nanopore sequencing

Zooplankton are crucial organisms both in terms of biodiversity and their unique position in aquatic food webs. As such, it is crucial that we improve our insights into how anthropogenic and natural factors may affect these pelagic organisms. Although easily collected in large numbers, the subsequent processing and identification of specimens has usually been a barrier to large-scale biodiversity assessments. DNA barcoding, the use of standardized short gene regions to discriminate species, has been increasingly used by non-taxonomists to identify species. Here, we measured the diversity and community composition of zooplankton in the Belgian part of the North Sea over the course of one year. We identified zooplankton using both a traditional approach, based on morphological characteristics, and by metabarcoding of a 650 bp fragment of the 18S rRNA gene using the MinION™, a portable nanopore-based DNA sequencing platform. We established a method for characterizing zooplankton communities in marine samples using nanopore sequencing. We were able to identify several taxa at the species level, across a broad taxonomic scale and we thus could obtain several diversity metrics, allowing comparisons of diversity and community composition

CFD SIMULATIONS OF THE IMPACT OF A LINE VEGETATION ELEMENT ALONG A MOTORWAY ON LOCAL AIR QUALITY

In the paper a CFD-based micro scale air quality model called ENVI-met will be presented. ENVI-met distinguishes itself from other CFD-models due the implementation of a detailed vegetation model which describes the interaction of local vegetation, not only on the wind field, but also on the thermodynamic processes and the diffusion and deposition of gases and particulate matter. This makes the model particularly suitable for a recent research programme initiated by the Air Quality Innovation Project (IPL), founded by the Dutch Ministry for Transport, Public Works and Water Management (Rijkswaterstaat) and the Ministry of Housing, Spatial Planning & the Environment (Ministry of VROM). One of the seven branches of the IPL-project is to investigate both by measurements and modelling the effect of line vegetation along a motorway on local air quality. Recently the model results have been compared to a first measurement campaign

First molecular evidence of an invasive agricultural pest, Drosophila suzukii, in the diet of a common bat, Pipistrellus pipistrellus, in Belgian orchards

Bats are major consumers of arthropods, including many agricultural pest species, and can thus reduce and prevent crop damage. However, few, if any, data is available on the potential role of bats in pest control in central Europe. Evidence that bats prey upon locally important pest species would be an important first step to demonstrate their value to local farmers and facilitate conservation measures. In this pilot study, we used a DNA metabarcoding approach to investigate the diet composition of common pipistrelles and brown long-eared bats captured in orchards in Belgium. We show that the spotted wing drosophila (Drosophila suzukii), one of the most harmful pest species in this region, was part of the diet of common pipistrelles. This pest species was recorded in one of the five samples from common pipistrelles. Our results indicate that bats can be valuable assets for biological pest suppression in West-European orchards, thus setting a path for future studies

RIO: A NOVEL APPROACH FOR AIR POLLUTION MAPPING

Real-time assessment of the ambient air quality has gained an increased interest in recent years. To give support to this evolution, the statistical air pollution interpolation model RIO is developed. Due to the very low computational cost this interpolation model is an efficient tool for an environment agency when performing real-time air quality assessments. Beside this, a reliable interpolation model can be used to produce analysed maps of historical data records as well. RIO is an interpolation model that can be classified as a detrended Kriging model. In a first step the local character of the air pollution sampling values is removed in a detrending procedure. Subsequently, the site-independent data is interpolated by an Ordinary Kriging scheme. Finally, in a retrending step a local bias is added to the Kriging interpolation results. As spatially resolved driving force in the detrending process, a land use indicator is developed based on the CORINE land cover data set. The indicator is optimized independently for the three pollutants O3, NO2 and PM10. As a result, the RIO model is able to account for the local character of the air pollution phenomenon at locations where no monitoring stations are available. Through a cross-validation procedure the superiority of the RIO model over standard interpolation techniques, such as the Ordinary Kriging is demonstrated. Air quality maps are presented for the three pollutants mentioned and compared to maps based on standard interpolation techniques