879 resultados para Sources of Information


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High fat diets and accompanying hepatic steatosis are highly prevalent conditions. Previous work has shown that steatosis is accompanied by enhanced generation of reactive oxygen species (ROS), which may mediate further liver damage. Here we investigated mechanisms leading to enhanced ROS generation following high fat diets (HFD). We found that mitochondria from HFD livers present no differences in maximal respiratory rates and coupling, but generate more ROS specifically when fatty acids are used as substrates. Indeed, many acyl-CoA dehydrogenase isoforms were found to be more highly expressed in HFD livers, although only the very long chain acyl-CoA dehydrogenase (VLCAD) was more functionally active. Studies conducted with permeabilized mitochondria and different chain length acyl-CoA derivatives suggest that VLCAD is also a source of ROS production in mitochondria of HFD animals. This production is stimulated by the lack of NAD+. Overall, our studies uncover VLCAD as a novel, diet-sensitive, source of mitochondrial ROS.

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We derive lower bounds on the density of sources of ultra-high energy cosmic rays from the lack of significant clustering in the arrival directions of the highest energy events detected at the Pierre Auger Observatory. The density of uniformly distributed sources of equal intrinsic intensity was found to be larger than ~(0.06 - 5) × '10 POT. -4' 'Mpc POT. -3' at 95% CL, depending on the magnitude of the magnetic deflections. Similar bounds, in the range (0.2 - 7) × '10 POT. -4' 'Mpc POT. -3', were obtained for sources following the local matter distribution.

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[EN] Background: Culicoides (Diptera: Ceratopogonidae) biting midges are vectors for a diversity of pathogens including bluetongue virus (BTV) that generate important economic losses. BTV has expanded its range in recent decades, probably due to the expansion of its main vector and the presence of other autochthonous competent vectors. Although the Canary Islands are still free of bluetongue disease (BTD), Spain and Europe have had to face up to a spread of bluetongue with disastrous consequences. Therefore, it is essential to identify the distribution of biting midges and understand their feeding patterns in areas susceptible to BTD. To that end, we captured biting midges on two farms in the Canary Islands (i) to identify the midge species in question and characterize their COI barcoding region and (ii) to ascertain the source of their bloodmeals using molecular tools.Methods: Biting midges were captured using CDC traps baited with a 4-W blacklight (UV) bulb on Gran Canaria and on Tenerife. Biting midges were quantified and identified according to their wing patterns. A 688 bp segment of the mitochondrial COI gene of 20 biting midges (11 from Gran Canaria and 9 from Tenerife) were PCR amplified using the primers LCO1490 and HCO2198. Moreover, after selected all available females showing any rest of blood in their abdomen, a nested-PCR approach was used to amplify a fragment of the COI gene from vertebrate DNA contained in bloodmeals. The origin of bloodmeals was identified by comparison with the nucleotide-nucleotide basic alignment search tool (BLAST). Results: The morphological identification of 491 female biting midges revealed the presence of a single morphospecies belonging to the Obsoletus group. When sequencing the barcoding region of the 20 females used to check genetic variability, we identified two haplotypes differing in a single base. Comparison analysis using the nucleotide-nucleotide basic alignment search tool (BLAST) showed that both haplotypes belong to Culicoides obsoletus, a potential BTV vector. As well, using molecular tools we identified the feeding sources of 136 biting midges and were able to confirm that C. obsoletus females feed on goats and sheep on both islands.Conclusions: These results confirm that the feeding pattern of C. obsoletus is a potentially important factor in BTV transmission to susceptible hosts in case of introduction into the archipelago. Consequently, in the Canary Islands it is essential to maintain vigilance of Culicoides-transmitted viruses such as BTV and the novel Schmallenberg virus.

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The first part of my work consisted in samplings conduced in nine different localities of the salento peninsula and Apulia (Italy): Costa Merlata (BR), Punta Penne (BR), Santa Cesarea terme (LE), Santa Caterina (LE), Torre Inserraglio (LE), Torre Guaceto (BR), Porto Cesareo (LE), Otranto (LE), Isole Tremiti (FG). I collected data of species percentage covering from the infralittoral rocky zone, using squares of 50x50 cm. We considered 3 sites for location and 10 replicates for each site, which has been taken randomly. Then I took other data about the same places, collected in some years, and I combined them together, to do a spatial analysis. So I started from a data set of 1896 samples but I decided not to consider time as a factor because I have reason to think that in this period of time anthropogenic stressors and their effects (if present), didn’t change considerably. The response variable I’ve analysed is the covering percentage of an amount of 243 species (subsequently merged into 32 functional groups), including seaweeds, invertebrates, sediment and rock. 2 After the sampling, I have been spent a period of two months at the Hopkins Marine Station of Stanford University, in Monterey (California,USA), at Fiorenza Micheli's laboratory. I've been carried out statistical analysis on my data set, using the software PRIMER 6. My explorative analysis starts with a nMDS in PRIMER 6, considering the original data matrix without, for the moment, the effect of stressors. What comes out is a good separation between localities and it confirms the result of ANOSIM analysis conduced on the original data matrix. What is possible to ensure is that there is not a separation led by a geographic pattern, but there should be something else that leads the differences. Is clear the presence of at least three groups: one composed by Porto cesareo, Torre Guaceto and Isole tremiti (the only marine protected areas considered in this work); another one by Otranto, and the last one by the rest of little, impacted localities. Inside the localities that include MPA(Marine Protected Areas), is also possible to observe a sort of grouping between protected and controlled areas. What comes out from SIMPER analysis is that the most of the species involved in leading differences between populations are not rare species, like: Cystoseira spp., Mytilus sp. and ECR. Moreover I assigned discrete values (0,1,2) of each stressor to all the sites I considered, in relation to the intensity with which the anthropogenic factor affect the localities. 3 Then I tried to estabilish if there were some significant interactions between stressors: by using Spearman rank correlation and Spearman tables of significance, and taking into account 17 grades of freedom, the outcome shows some significant stressors interactions. Then I built a nMDS considering the stressors as response variable. The result was positive: localities are well separeted by stressors. Consequently I related the matrix with 'localities and species' with the 'localities and stressors' one. Stressors combination explains with a good significance level the variability inside my populations. I tried with all the possible data transformations (none, square root, fourth root, log (X+1), P/A), but the fourth root seemed to be the best one, with the highest level of significativity, meaning that also rare species can influence the result. The challenge will be to characterize better which kind of stressors (including also natural ones), act on the ecosystem; and give them a quantitative and more accurate values, trying to understand how they interact (in an additive or non-additive way).

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This thesis tackles the problem of the automated detection of the atmospheric boundary layer (BL) height, h, from aerosol lidar/ceilometer observations. A new method, the Bayesian Selective Method (BSM), is presented. It implements a Bayesian statistical inference procedure which combines in an statistically optimal way different sources of information. Firstly atmospheric stratification boundaries are located from discontinuities in the ceilometer back-scattered signal. The BSM then identifies the discontinuity edge that has the highest probability to effectively mark the BL height. Information from the contemporaneus physical boundary layer model simulations and a climatological dataset of BL height evolution are combined in the assimilation framework to assist this choice. The BSM algorithm has been tested for four months of continuous ceilometer measurements collected during the BASE:ALFA project and is shown to realistically diagnose the BL depth evolution in many different weather conditions. Then the BASE:ALFA dataset is used to investigate the boundary layer structure in stable conditions. Functions from the Obukhov similarity theory are used as regression curves to fit observed velocity and temperature profiles in the lower half of the stable boundary layer. Surface fluxes of heat and momentum are best-fitting parameters in this exercise and are compared with what measured by a sonic anemometer. The comparison shows remarkable discrepancies, more evident in cases for which the bulk Richardson number turns out to be quite large. This analysis supports earlier results, that surface turbulent fluxes are not the appropriate scaling parameters for profiles of mean quantities in very stable conditions. One of the practical consequences is that boundary layer height diagnostic formulations which mainly rely on surface fluxes are in disagreement to what obtained by inspecting co-located radiosounding profiles.