973 resultados para 1,2,3,4-TetraClBz max
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OBJECTIVE The cause precipitating intracranial aneurysm rupture remains unknown in many cases. It has been observed that aneurysm ruptures are clustered in time, but the trigger mechanism remains obscure. Because solar activity has been associated with cardiovascular mortality and morbidity, we decided to study its association to aneurysm rupture in the Swiss population. METHODS Patient data were extracted from the Swiss SOS database, at time of analysis covering 918 consecutive patients with angiography-proven aneurysmal subarachnoid hemorrhage treated at 7 Swiss neurovascular centers between January 1, 2009, and December 31, 2011. The daily rupture frequency (RF) was correlated to the absolute amount and the change in various parameters of interest representing continuous measurements of solar activity (radioflux [F10.7 index], solar proton flux, solar flare occurrence, planetary K-index/planetary A-index, Space Environment Services Center [SESC] sunspot number and sunspot area) using Poisson regression analysis. RESULTS During the period of interest, there were 517 days without recorded aneurysm rupture. There were 398, 139, 27, 12, 1, and 1 days with 1, 2, 3, 4, 5, and 6 ruptures per day. Poisson regression analysis demonstrated a significant correlation of F10.7 index and RF (incidence rate ratio [IRR] = 1.006303; standard error (SE) 0.0013201; 95% confidence interval (CI) 1.003719-1.008894; P < 0.001), according to which every 1-unit increase of the F10.7 index increased the count for an aneurysm to rupture by 0.63%. A likewise statistically significant relationship of both the SESC sunspot number (IRR 1.003413; SE 0.0007913; 95% CI 1.001864-1.004965; P < 0.001) and the sunspot area (IRR 1.000419; SE 0.0000866; 95% CI 1.000249-1.000589; P < 0.001) emerged. All other variables analyzed showed no significant correlation with RF. CONCLUSIONS We found greater radioflux, SESC sunspot number, and sunspot area to be associated with an increased count of aneurysm rupture. The clinical meaningfulness of this statistical association must be interpreted carefully and future studies are warranted to rule out a type-1 error.
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[Carl Oestreich]
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Regulation of tissue size requires fine tuning at the single-cell level of proliferation rate, cell volume, and cell death. Whereas the adjustment of proliferation and growth has been widely studied [1, 2, 3, 4 and 5], the contribution of cell death and its adjustment to tissue-scale parameters have been so far much less explored. Recently, it was shown that epithelial cells could be eliminated by live-cell delamination in response to an increase of cell density [6]. Cell delamination was supposed to occur independently of caspase activation and was suggested to be based on a gradual and spontaneous disappearance of junctions in the delaminating cells [6]. Studying the elimination of cells in the midline region of the Drosophila pupal notum, we found that, contrary to what was suggested before, Caspase 3 activation precedes and is required for cell delamination. Yet, using particle image velocimetry, genetics, and laser-induced perturbations, we confirmed [ 6] that local tissue crowding is necessary and sufficient to drive cell elimination and that cell elimination is independent of known fitness-dependent competition pathways [ 7, 8 and 9]. Accordingly, activation of the oncogene Ras in clones was sufficient to compress the neighboring tissue and eliminate cells up to several cell diameters away from the clones. Mechanical stress has been previously proposed to contribute to cell competition [ 10 and 11]. These results provide the first experimental evidences that crowding-induced death could be an alternative mode of super-competition, namely mechanical super-competition, independent of known fitness markers [ 7, 8 and 9], that could promote tumor growth.
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The problem of analyzing data with updated measurements in the time-dependent proportional hazards model arises frequently in practice. One available option is to reduce the number of intervals (or updated measurements) to be included in the Cox regression model. We empirically investigated the bias of the estimator of the time-dependent covariate while varying the effect of failure rate, sample size, true values of the parameters and the number of intervals. We also evaluated how often a time-dependent covariate needs to be collected and assessed the effect of sample size and failure rate on the power of testing a time-dependent effect.^ A time-dependent proportional hazards model with two binary covariates was considered. The time axis was partitioned into k intervals. The baseline hazard was assumed to be 1 so that the failure times were exponentially distributed in the ith interval. A type II censoring model was adopted to characterize the failure rate. The factors of interest were sample size (500, 1000), type II censoring with failure rates of 0.05, 0.10, and 0.20, and three values for each of the non-time-dependent and time-dependent covariates (1/4,1/2,3/4).^ The mean of the bias of the estimator of the coefficient of the time-dependent covariate decreased as sample size and number of intervals increased whereas the mean of the bias increased as failure rate and true values of the covariates increased. The mean of the bias of the estimator of the coefficient was smallest when all of the updated measurements were used in the model compared with two models that used selected measurements of the time-dependent covariate. For the model that included all the measurements, the coverage rates of the estimator of the coefficient of the time-dependent covariate was in most cases 90% or more except when the failure rate was high (0.20). The power associated with testing a time-dependent effect was highest when all of the measurements of the time-dependent covariate were used. An example from the Systolic Hypertension in the Elderly Program Cooperative Research Group is presented. ^
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Hydrocarbon seeps are ubiquitous at gas-prone Cenozoic deltas such as the Nile Deep Sea Fan (NDSF) where seepage into the bottom water has been observed at several mud volcanoes (MVs) including North Alex MV (NAMV). Here we investigated the sources of hydrocarbon gases and sedimentary organic matter together with biomarkers of microbial activity at four locations of NAMV to constrain how venting at the seafloor relates to the generation of hydrocarbon gases in deeper sediments. At the centre, high upward flux of hot (70 °C) hydrocarbon-rich fluids is indicated by an absence of biomarkers of Anaerobic Oxidation of Methane (AOM) and nearly constant methane (CH4) concentration depth-profile. The presence of lipids of incompatible thermal maturities points to mixing between early-mature petroleum and immature organic matter, indicating that shallow mud has been mobilized by the influx of deep-sourced hydrocarbon-rich fluids. Methane is enriched in the heavier isotopes, with values of d13C ~-46.6 per mil VPDB and dD ~-228 per mil VSMOW, and is associated with high amounts of heavier homologues (C2+) suggesting a co-genetic origin with the petroleum. On the contrary at the periphery, a lower but sustained CH4 flux is indicated by deeper sulphate-methane transition zones and the presence of 13C-depleted biomarkers of AOM, consistent with predominantly immature organic matter. Values of d13C-CH4 ~-60 per mil VPDB and decreased concentrations of 13C-enriched C2+ are typical of mixed microbial CH4 and biodegraded thermogenic gas from Plio-Pleistocene reservoirs of the region. The maturity of gas condensate migrated from pre-Miocene sources into Miocene reservoirs of the Western NDSF is higher than that of the gas vented at the centre of NAMV, supporting the hypothesis that it is rather released from the degradation of oil in Neogene reservoirs. Combined with the finding of hot pore water and petroleum at the centre, our results suggest that clay mineral dehydration of Neogene sediments, which takes place posterior to reservoir filling, may contribute to intense gas generation at high sedimentation rate deltas.
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This data set contains aboveground community biomass (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Aboveground community biomass was harvested twice in 2004 just prior to mowing (during peak standing biomass in late May and in late August) on all experimental plots of the main experiment. This was done by clipping the vegetation at 3 cm above ground in four rectangles of 0.2 x 0.5 m per large plot. The location of these rectangles was assigned prior to each harvest by random selection of coordinates within the core area of the plots (i.e. the central 10 x 15 m). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The data for individual samples and the mean over samples for the biomass measures on the community level are given. Overall, analyses of the community biomass data have identified species richness as well as functional group composition as important drivers of a positive biodiversity-productivity relationship.
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This data set contains aboveground community biomass (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Aboveground community biomass was harvested twice in 2007 just prior to mowing (during peak standing biomass in early June and in late August) on all experimental plots of the main experiment. This was done by clipping the vegetation at 3 cm above ground in four (May) or three (August) rectangles of 0.2 x 0.5 m per large plot. The location of these rectangles was assigned prior to each harvest by random selection of coordinates within the core area of the plots (i.e. the central 10 x 15 m). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The data for individual samples and the mean over samples for the biomass measures on the community level are given. Overall, analyses of the community biomass data have identified species richness as well as functional group composition as important drivers of a positive biodiversity-productivity relationship.
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This data set contains aboveground community biomass (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Aboveground community biomass was harvested twice in 2006 just prior to mowing (during peak standing biomass in early June and in late August) on all experimental plots of the main experiment. This was done by clipping the vegetation at 3 cm above ground in four rectangles of 0.2 x 0.5 m per large plot. The location of these rectangles was assigned prior to each harvest by random selection of coordinates within the core area of the plots (i.e. the central 10 x 15 m). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The data for individual samples and the mean over samples for the biomass measures on the community level are given. Overall, analyses of the community biomass data have identified species richness as well as functional group composition as important drivers of a positive biodiversity-productivity relationship.
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This data set contains measurements of plant height: vegetative height (non-flowering indviduals) and regenerative height (flowering individuals) in 2002 from the Main Experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the Main Experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In 2002, plant height was recorded twice a year: in late June and just before biomass harvest during peak standing biomass in late August. For 3 target plant individuals (if present) per sown species from the central area of the plots, vegetative height (non-flowering indviduals) and regenerative height (flowering individuals) were measured as stretched height. Provided are the indivdiual measurements and the mean over the measured plants per plot (in June) and the mean over the measured plants per plot (in August).
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This data set contains measurements of dissolved organic carbon in samples of soil water collected from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In April 2002 glass suction plates with a diameter of 12 cm, 1 cm thickness and a pore size of 1-1.6 mm (UMS GmbH, Munich, Germany) were installed in depths of 10, 20, 30 and 60 cm to collect soil solution. The sampling bottles were continuously evacuated to a negative pressure between 50 and 350 mbar, such that the suction pressure was about 50 mbar above the actual soil water tension. Thus, only the soil leachate was collected. Cumulative soil solution was sampled biweekly and analyzed for dissolved organic carbon concentration by a high TOC elemental analyzer (Elementar Analysensysteme GmbH, Hanau, Germany). Samples were analyzed as soon as possible and stored at 4°C if necessary. Often in summer, no free soil solution was available for collection, especially in the upper soil layers. Annual mean values of measured biweekly concentrations of dissolved organic carbon are provided.
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This data set contains measurements of dissolved organic carbon in samples of soil water collected from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In April 2002 glass suction plates with a diameter of 12 cm, 1 cm thickness and a pore size of 1-1.6 mm (UMS GmbH, Munich, Germany) were installed in depths of 10, 20, 30 and 60 cm to collect soil solution. The sampling bottles were continuously evacuated to a negative pressure between 50 and 350 mbar, such that the suction pressure was about 50 mbar above the actual soil water tension. Thus, only the soil leachate was collected. Cumulative soil solution was sampled biweekly and analyzed for dissolved organic carbon concentration by a high TOC elemental analyzer (Elementar Analysensysteme GmbH, Hanau, Germany). Samples were analyzed as soon as possible and stored at 4°C if necessary. Often in summer, no free soil solution was available for collection, especially in the upper soil layers. Annual mean values of measured biweekly concentrations of dissolved organic carbon are provided.
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This data set contains measurements of dissolved organic carbon in samples of soil water collected from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In April 2002 glass suction plates with a diameter of 12 cm, 1 cm thickness and a pore size of 1-1.6 mm (UMS GmbH, Munich, Germany) were installed in depths of 10, 20, 30 and 60 cm to collect soil solution. The sampling bottles were continuously evacuated to a negative pressure between 50 and 350 mbar, such that the suction pressure was about 50 mbar above the actual soil water tension. Thus, only the soil leachate was collected. Cumulative soil solution was sampled biweekly and analyzed for dissolved organic carbon concentration by a high TOC elemental analyzer (Elementar Analysensysteme GmbH, Hanau, Germany). Samples were analyzed as soon as possible and stored at 4°C if necessary. Often in summer, no free soil solution was available for collection, especially in the upper soil layers. Annual mean values of measured biweekly concentrations of dissolved organic carbon are provided.
Resumo:
This data set contains aboveground community biomass (Sown plant community, Weed plant community, Dead plant material, and Unidentified plant material; all measured in biomass as dry weight) and species-specific biomass from the sown species of the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Aboveground community biomass was harvested twice in 2003 just prior to mowing (during peak standing biomass in late May and in late August) on all experimental plots of the main experiment. This was done by clipping the vegetation at 3 cm above ground in four rectangles of 0.2 x 0.5 m per large plot. The location of these rectangles was assigned prior to each harvest by random selection of coordinates within the core area of the plots (i.e. the central 10 x 15 m). The positions of the rectangles within plots were identical for all plots. The harvested biomass was sorted into categories: individual species for the sown plant species, weed plant species (species not sown at the particular plot), detached dead plant material (i.e., dead plant material in the data file), and remaining plant material that could not be assigned to any category (i.e., unidentified plant material in the data file). All biomass was dried to constant weight (70°C, >= 48 h) and weighed. Sown plant community biomass was calculated as the sum of the biomass of the individual sown species. The data for individual samples and the mean over samples for the biomass measures on the community level are given. Overall, analyses of the community biomass data have identified species richness as well as functional group composition as important drivers of a positive biodiversity-productivity relationship.