21 resultados para 949.6103


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The Phenotype MicroArray (TM) (PM) technology was used to study the metabolic characteristics of 29 Salmonella strains belonging to seven serotypes of S. enterica spp. enterica. Strains of serotypes Typhimurium (six strains among definite phage types DTs 1, 40 and 104) and Agona (two strains) were tested for 949 substrates, Enteritidis (six strains of phage type PT1), Give, Hvittingfoss, Infantis and Newport strains (two of each) were tested for 190 substrates and seven other Agona strains for 95 substrates. The strains represented 18 genotypes in pulsed-field gel electrophoresis (PFGE). Among 949 substrates, 18 were identified that could be used to differentiate between the strains of those seven serotypes or within a single serotype. Unique metabolic differences between the Finnish endemic Typhimurium DT1 and Agona strains were detected, for example, in the metabolism of d-tagatose, d-galactonic acid gamma-lactone and l-proline as a carbon source. Thus, the PM technique is a useful tool for identifying potential differential markers on a metabolic basis that could be used for epidemiological surveillance.

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Metrics are often used to compare the climate impacts of emissions from various sources, sectors or nations. These are usually based on global-mean input, and so there is the potential that important information on smaller scales is lost. Assuming a non-linear dependence of the climate impact on local surface temperature change, we explore the loss of information about regional variability that results from using global-mean input in the specific case of heterogeneous changes in ozone, methane and aerosol concentrations resulting from emissions from road traffic, aviation and shipping. Results from equilibrium simulations with two general circulation models are used. An alternative metric for capturing the regional climate impacts is investigated. We find that the application of a metric that is first calculated locally and then averaged globally captures a more complete and informative signal of climate impact than one that uses global-mean input. The loss of information when heterogeneity is ignored is largest in the case of aviation. Further investigation of the spatial distribution of temperature change indicates that although the pattern of temperature response does not closely match the pattern of the forcing, the forcing pattern still influences the response pattern on a hemispheric scale. When the short-lived transport forcing is superimposed on present-day anthropogenic CO2 forcing, the heterogeneity in the temperature response to CO2 dominates. This suggests that the importance of including regional climate impacts in global metrics depends on whether small sectors are considered in isolation or as part of the overall climate change.

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Mean field models (MFMs) of cortical tissue incorporate salient, average features of neural masses in order to model activity at the population level, thereby linking microscopic physiology to macroscopic observations, e.g., with the electroencephalogram (EEG). One of the common aspects of MFM descriptions is the presence of a high-dimensional parameter space capturing neurobiological attributes deemed relevant to the brain dynamics of interest. We study the physiological parameter space of a MFM of electrocortical activity and discover robust correlations between physiological attributes of the model cortex and its dynamical features. These correlations are revealed by the study of bifurcation plots, which show that the model responses to changes in inhibition belong to two archetypal categories or “families”. After investigating and characterizing them in depth, we discuss their essential differences in terms of four important aspects: power responses with respect to the modeled action of anesthetics, reaction to exogenous stimuli such as thalamic input, and distributions of model parameters and oscillatory repertoires when inhibition is enhanced. Furthermore, while the complexity of sustained periodic orbits differs significantly between families, we are able to show how metamorphoses between the families can be brought about by exogenous stimuli. We here unveil links between measurable physiological attributes of the brain and dynamical patterns that are not accessible by linear methods. They instead emerge when the nonlinear structure of parameter space is partitioned according to bifurcation responses. We call this general method “metabifurcation analysis”. The partitioning cannot be achieved by the investigation of only a small number of parameter sets and is instead the result of an automated bifurcation analysis of a representative sample of 73,454 physiologically admissible parameter sets. Our approach generalizes straightforwardly and is well suited to probing the dynamics of other models with large and complex parameter spaces.

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Matrix-assisted laser desorption/ionisation (MALDI) mass spectrometry (MS) is a highly versatile and sensitive analytical technique, which is known for its soft ionisation of biomolecules such as peptides and proteins. Generally, MALDI MS analysis requires little sample preparation, and in some cases like MS profiling it can be automated through the use of robotic liquid-handling systems. For more than a decade now, MALDI MS has been extensively utilised in the search for biomarkers that could aid clinicians in diagnosis, prognosis, and treatment decision making. This review examines the various MALDI-based MS techniques like MS imaging, MS profiling and proteomics in-depth analysis where MALDI MS follows fractionation and separation methods such as gel electrophoresis, and how these have contributed to prostate cancer biomarker research. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.

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The purpose of this paper is to report on the facilities available, organisation of, and staff attitudes to early years outdoor education from schools within the south east of England, focusing on provision for children aged three to five. One component of the successful education of the child involves providing an ‘environment for learning’, including the facilities, layout and routines. This paper presents findings concerning the type and variety of facilities available outside; the various styles of organisation of the space; staff attitudes about: their roles, their aims for the environment, children’s behaviour and learning, and perceived drawbacks to practice. This paper draws on empirical data collected from schools within the University of Reading partnership. The findings suggest that although all early years settings must adhere to the statutory framework there are a range of facilities available, and there are a number of ways this environment is organised. Further there appears to be uncertainty about the adult role outside and the aims for activities. The conclusions drawn indicate that staff do not appear to be linking their aims for outdoor education to the facilities provided or to their actions outside. This means there is not a clear link between what staff provide outside and the declared ambitions for learning. This study is important as all educators need to be certain about their aims for education to ensure best outcomes for children. The implications of these findings for early years teachers are that they need to be able to articulate their aims for outdoor education and to provide the correct facilities to achieve these aims. Finally this study was undertaken to raise debate, posit questions and to ascertain the parameters for further research about the early years outdoor environment.

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1. Species’ distributions are likely to be affected by a combination of environmental drivers. We used a data set of 11 million species occurrence records over the period 1970–2010 to assess changes in the frequency of occurrence of 673 macro-moth species in Great Britain. Groups of species with different predicted sensitivities showed divergent trends, which we interpret in the context of land-use and climatic changes. 2. A diversity of responses was revealed: 260 moth species declined significantly, whereas 160 increased significantly. Overall, frequencies of occurrence declined, mirroring trends in less species-rich, yet more intensively studied taxa. 3. Geographically widespread species, which were predicted to be more sensitive to land use than to climate change, declined significantly in southern Britain, where the cover of urban and arable land has increased. 4. Moths associated with low nitrogen and open environments (based on their larval host plant characteristics) declined most strongly, which is also consistent with a land-use change explanation. 5. Some moths that reach their northern (leading edge) range limit in southern Britain increased, whereas species restricted to northern Britain (trailing edge) declined significantly, consistent with a climate change explanation. 6. Not all species of a given type behaved similarly, suggesting that complex interactions between species’ attributes and different combinations of environmental drivers determine frequency of occurrence changes. 7. Synthesis and applications. Our findings are consistent with large-scale responses to climatic and land-use changes, with some species increasing and others decreasing. We suggest that land-use change (e.g. habitat loss, nitrogen deposition) and climate change are both major drivers of moth biodiversity change, acting independently and in combination. Importantly, the diverse responses revealed in this species-rich taxon show that multifaceted conservation strategies are needed to minimize negative biodiversity impacts of multiple environmental changes. We suggest that habitat protection, management and ecological restoration can mitigate combined impacts of land-use change and climate change by providing environments that are suitable for existing populations and also enable species to shift their ranges.