302 research outputs found

    Herstelmaatregelen in heideterreinen; invloed op de fauna

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    Aanleiding voor deze publicatie zijn de resultaten van het onderzoek naar de effecten van herstelmaatregelen op dieren van het heidelandschap. De afgelopen jaren werd steeds duidelijker dat het onderzoek en de toepassing daarvan moeten worden opgeschaald naar het niveau van het landschap. Dat is ook hier zichtbaar geworden: het gaat niet alleen over de droge en de natte heide, maar ook over vennen en over struwelen en bosranden. Kortom: het gaat over het complete heidelandschap, met al zijn variatie en (geleidelijke of abrupte) overgangen. En juist bij zo’n divers en samenhangend landschap is de fauna gebaa

    Synaptotagmin 13 is neuroprotective across motor neuron diseases

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    In amyotrophic lateral sclerosis (ALS) and spinal muscular atrophy (SMA), spinal and lower brainstem motor neurons degenerate, but some motor neuron subtypes are spared, including oculomotor neurons (OMNs). The mechanisms responsible for this selective degeneration are largely unknown, but the molecular signatures of resistant and vulnerable motor neurons are distinct and offer clues to neuronal resilience and susceptibility. Here, we demonstrate that healthy OMNs preferentially express Synaptotagmin 13 (SYT13) compared to spinal motor neurons. In end-stage ALS patients, SYT13 is enriched in both OMNs and the remaining relatively resilient spinal motor neurons compared to controls. Overexpression of SYT13 in ALS and SMA patient motor neurons in vitro improves their survival and increases axon lengths. Gene therapy with Syt13 prolongs the lifespan of ALS mice by 14% and SMA mice by 50% by preserving motor neurons and delaying muscle denervation. SYT13 decreases endoplasmic reticulum stress and apoptosis of motor neurons, both in vitro and in vivo. Thus, SYT13 is a resilience factor that can protect motor neurons and a candidate therapeutic target across motor neuron diseases

    Urinary pesticide mixture patterns and exposure determinants in the adult population from the Netherlands and Switzerland : Application of a suspect screening approach

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    INTRODUCTION: Non-occupational sources of pesticide exposure may include domestic pesticide usage, diet, occupational exposure of household members, and agricultural activities in the residential area. We conducted a study with the ambition to characterize pesticide mixture patterns in a sample of the adult population of the Netherlands and Switzerland, using a suspect screening approach and to identify related exposure determinants. METHODS: A total of 105 and 295 adults participated in the Dutch and Swiss studies, respectively. First morning void urine samples were collected and analyzed in the same laboratory. Harmonized questionnaires about personal characteristics, pesticide-related activities, and diet were administered. Detection rates and co-occurrence patterns were calculated to explore internal pesticide exposure patterns. Censored linear and logistic regression models were constructed to investigate the association between exposure and domestic pesticide usage, consumption of homegrown and organic foods, household members' exposure, and distance to agricultural and forest areas. RESULTS: From the 37 detected biomarkers, 3 (acetamiprid (-CH2), chlorpropham (4-HSA), and flonicamid (-C2HN)) were detected in ≄40% of samples. The most frequent combination of biomarkers (acetamiprid-flonicamid) was detected in 22 (5.5%) samples. Regression models revealed an inverse association between high organic vegetable and fruit consumption and exposure to acetamiprid, chlorpropham, propamocarb (+O), and pyrimethanil (+O + SO3). Within-individual correlations in repeated samples (summer/winter) from the Netherlands were low (≀0.3), and no seasonal differences in average exposures were observed in Switzerland. CONCLUSION: High consumption of organic fruit and vegetables was associated with lower pesticide exposure. In the two countries, detection rates and co-occurrence were typically low, and within-person variability was high. Our study results provide an indication for target biomarkers to include in future studies aimed at quantifying urinary exposure levels in European adult populations

    Hillslope Hydrology in Global Change Research and Earth System Modeling

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    Earth System Models (ESMs) are essential tools for understanding and predicting global change, but they cannot explicitly resolve hillslope‐scale terrain structures that fundamentally organize water, energy, and biogeochemical stores and fluxes at subgrid scales. Here we bring together hydrologists, Critical Zone scientists, and ESM developers, to explore how hillslope structures may modulate ESM grid‐level water, energy, and biogeochemical fluxes. In contrast to the one‐dimensional (1‐D), 2‐ to 3‐mdeep, and free‐draining soil hydrology in most ESM land models, we hypothesize that 3‐D, lateral ridge‐to‐valley flow through shallow and deep paths and insolation contrasts between sunny and shady slopes are the top two globally quantifiable organizers of water and energy (and vegetation) within an ESM grid cell. We hypothesize that these two processes are likely to impact ESM predictions where (and when) water and/or energy are limiting. We further hypothesize that, if implemented in ESM land models, these processes will increase simulated continental water storage and residence time, buffering terrestrial ecosystems against seasonal and interannual droughts. We explore efficient ways to capture these mechanisms in ESMs and identify critical knowledge gaps preventing us from scaling up hillslope to global processes. One such gap is our extremely limited knowledge of the subsurface, where water is stored (supporting vegetation) and released to stream baseflow (supporting aquatic ecosystems). We conclude with a set of organizing hypotheses and a call for global syntheses activities and model experiments to assess the impact of hillslope hydrology on global change predictions

    Semi-automatic identification of punching areas for tissue microarray building: the tubular breast cancer pilot study

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    Background: Tissue MicroArray technology aims to perform immunohistochemical staining on hundreds of different tissue samples simultaneously. It allows faster analysis, considerably reducing costs incurred in staining. A time consuming phase of the methodology is the selection of tissue areas within paraffin blocks: no utilities have been developed for the identification of areas to be punched from the donor block and assembled in the recipient block.Results: The presented work supports, in the specific case of a primary subtype of breast cancer (tubular breast cancer), the semi-automatic discrimination and localization between normal and pathological regions within the tissues. The diagnosis is performed by analysing specific morphological features of the sample such as the absence of a double layer of cells around the lumen and the decay of a regular glands-and-lobules structure. These features are analysed using an algorithm which performs the extraction of morphological parameters from images and compares them to experimentally validated threshold values. Results are satisfactory since in most of the cases the automatic diagnosis matches the response of the pathologists. In particular, on a total of 1296 sub-images showing normal and pathological areas of breast specimens, algorithm accuracy, sensitivity and specificity are respectively 89%, 84% and 94%.Conclusions: The proposed work is a first attempt to demonstrate that automation in the Tissue MicroArray field is feasible and it can represent an important tool for scientists to cope with this high-throughput technique

    Evaluation of the atmosphere–land–ocean–sea ice interface processes in the Regional Arctic System Model version 1 (RASM1) using local and globally gridded observations

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    The Regional Arctic System Model version 1 (RASM1) has been developed to provide high-resolution simulations of the Arctic atmosphere–ocean–sea ice–land system. Here, we provide a baseline for the capability of RASM to simulate interface processes by comparing retrospective simulations from RASM1 for 1990–2014 with the Community Earth System Model version 1 (CESM1) and the spread across three recent reanalyses. Evaluations of surface and 2 m air temperature, surface radiative and turbulent fluxes, precipitation, and snow depth in the various models and reanalyses are performed using global and regional datasets and a variety of in situ datasets, including flux towers over land, ship cruises over oceans, and a field experiment over sea ice. These evaluations reveal that RASM1 simulates precipitation that is similar to CESM1, reanalyses, and satellite gauge combined precipitation datasets over all river basins within the RASM domain. Snow depth in RASM is closer to upscaled surface observations over a flatter region than in more mountainous terrain in Alaska. The sea ice–atmosphere interface is well simulated in regards to radiation fluxes, which generally fall within observational uncertainty. RASM1 monthly mean surface temperature and radiation biases are shown to be due to biases in the simulated mean diurnal cycle. At some locations, a minimal monthly mean bias is shown to be due to the compensation of roughly equal but opposite biases between daytime and nighttime, whereas this is not the case at locations where the monthly mean bias is higher in magnitude. These biases are derived from errors in the diurnal cycle of the energy balance (radiative and turbulent flux) components. Therefore, the key to advancing the simulation of SAT and the surface energy budget would be to improve the representation of the diurnal cycle of radiative and turbulent fluxes. The development of RASM2 aims to address these biases. Still, an advantage of RASM1 is that it captures the interannual and interdecadal variability in the climate of the Arctic region, which global models like CESM cannot do
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