149 research outputs found

    Cirsium species show disparity in patterns of genetic variation at their range-edge, despite similar patterns of reproduction and isolation

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    Genetic variation was assessed across the UK geographical range of Cirsium acaule and Cirsium heterophyllum. A decline in genetic diversity and increase in population divergence approaching the range edge of these species was predicted based on parallel declines in population density and seed production reported seperately. Patterns were compared with UK populations of the widespread Cirsium arvense.Populations were sampled along a latitudinal transect in the UK and genetic variation assessed using microsatellite markers. Cirsium acaule shows strong isolation by distance, a significant decline in diversity and an increase in divergence among range-edge populations. Geographical structure is also evident in C. arvense, whereas no such patterns are seen in C.heterophyllum. There is a major disparity between patterns of genetic variation in C. acaule and C. heterophyllum despite very similar patterns in seed production and population isolation in these species. This suggests it may be misleading to make assumptions about the geographical structure of genetic variation within species based solely on the present-day reproduction and distribution of populations

    Brain classification reveals the right cerebellum as the best biomarker of dyslexia

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    Background Developmental dyslexia is a specific cognitive disorder in reading acquisition that has genetic and neurological origins. Despite histological evidence for brain differences in dyslexia, we recently demonstrated that in large cohort of subjects, no differences between control and dyslexic readers can be found at the macroscopic level (MRI voxel), because of large variances in brain local volumes. In the present study, we aimed at finding brain areas that most discriminate dyslexic from control normal readers despite the large variance across subjects. After segmenting brain grey matter, normalizing brain size and shape and modulating the voxels' content, normal readers' brains were used to build a 'typical' brain via bootstrapped confidence intervals. Each dyslexic reader's brain was then classified independently at each voxel as being within or outside the normal range. We used this simple strategy to build a brain map showing regional percentages of differences between groups. The significance of this map was then assessed using a randomization technique. Results The right cerebellar declive and the right lentiform nucleus were the two areas that significantly differed the most between groups with 100% of the dyslexic subjects (N = 38) falling outside of the control group (N = 39) 95% confidence interval boundaries. The clinical relevance of this result was assessed by inquiring cognitive brain-based differences among dyslexic brain subgroups in comparison to normal readers' performances. The strongest difference between dyslexic subgroups was observed between subjects with lower cerebellar declive (LCD) grey matter volumes than controls and subjects with higher cerebellar declive (HCD) grey matter volumes than controls. Dyslexic subjects with LCD volumes performed worse than subjects with HCD volumes in phonologically and lexicon related tasks. Furthermore, cerebellar and lentiform grey matter volumes interacted in dyslexic subjects, so that lower and higher lentiform grey matter volumes compared to controls differently modulated the phonological and lexical performances. Best performances (observed in controls) corresponded to an optimal value of grey matter and they dropped for higher or lower volumes. Conclusion These results provide evidence for the existence of various subtypes of dyslexia characterized by different brain phenotypes. In addition, behavioural analyses suggest that these brain phenotypes relate to different deficits of automatization of language-based processes such as grapheme/phoneme correspondence and/or rapid access to lexicon entries. article available here: http://www.biomedcentral.com/1471-2202/10/6

    Effects of Brood Pheromone Modulated Brood Rearing Behaviors on Honey Bee (Apis mellifera L.) Colony Growth

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    A hallmark of eusociality is cooperative brood care. In most social insect systems brood rearing labor is divided between individuals working in the nest tending the queen and larvae, and foragers collecting food outside the nest. To place brood rearing division of labor within an evolutionary context, it is necessary to understand relationships between individuals in the nest engaged in brood care and colony growth in the honey bee. Here we examined responses of the queen, queen-worker interactions, and nursing behaviors to an increase in the brood rearing stimulus environment using brood pheromone. Colony pairs were derived from a single source and were headed by open-mated sister queens, for a total of four colony pairs. One colony of a pair was treated with 336 µg of brood pheromone, and the other a blank control. Queens in the brood pheromone treated colonies laid significantly more eggs, were fed longer, and were less idle compared to controls. Workers spent significantly more time cleaning cells in pheromone treatments. Increasing the brood rearing stimulus environment with the addition of brood pheromone significantly increased the tempo of brood rearing behaviors by bees working in the nest resulting in a significantly greater amount of brood reared

    Angular and Current-Target Correlations in Deep Inelastic Scattering at HERA

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    Correlations between charged particles in deep inelastic ep scattering have been studied in the Breit frame with the ZEUS detector at HERA using an integrated luminosity of 6.4 pb-1. Short-range correlations are analysed in terms of the angular separation between current-region particles within a cone centred around the virtual photon axis. Long-range correlations between the current and target regions have also been measured. The data support predictions for the scaling behaviour of the angular correlations at high Q2 and for anti-correlations between the current and target regions over a large range in Q2 and in the Bjorken scaling variable x. Analytic QCD calculations and Monte Carlo models correctly describe the trends of the data at high Q2, but show quantitative discrepancies. The data show differences between the correlations in deep inelastic scattering and e+e- annihilation.Comment: 26 pages including 10 figures (submitted to Eur. J. Phys. C

    Plastisol Foaming Process. Decomposition of the Foaming Agent, Polymer Behavior in the Corresponding Temperature Range and Resulting Foam Properties

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    The decomposition of azodicarbonamide, used as foaming agent in PVC - plasticizer (1/1) plastisols was studied by DSC. Nineteen different plasticizers, all belonging to the ester family, two being polymeric (polyadipates), were compared. The temperature of maximum decomposition rate (in anisothermal regime at 5 K min-1 scanning rate), ranges between 434 and 452 K. The heat of decomposition ranges between 8.7 and 12.5 J g -1. Some trends of variation of these parameters appear significant and are discussed in terms of solvent (matrix) and viscosity effects on the decomposition reactions. The shear modulus at 1 Hz frequency was determined at the temperature of maximum rate of foaming agent decomposition, and differs significantly from a sample to another. The foam density was determined at ambient temperature and the volume fraction of bubbles was used as criterion to judge the efficiency of the foaming process. The results reveal the existence of an optimal shear modulus of the order of 2 kPa that corresponds roughly to plasticizer molar masses of the order of 450 ± 50 g mol-1. Heavier plasticizers, especially polymeric ones are too difficult to deform. Lighter plasticizers such as diethyl phthalate (DEP) deform too easily and presumably facilitate bubble collapse

    Factors and processes shaping the population structure and distribution of genetic variation across the species range of the freshwater snail radix balthica (Pulmonata, Basommatophora)

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    Background: Factors and processes shaping the population structure and spatial distribution of genetic diversity across a species' distribution range are important in determining the range limits. We comprehensively analysed the influence of recurrent and historic factors and processes on the population genetic structure, mating system and the distribution of genetic variability of the pulmonate freshwater snail Radix balthica. This analysis was based on microsatellite variation and mitochondrial haplotypes using Generalised Linear Statistical Modelling in a Model Selection framework. Results: Populations of R. balthica were found throughout North-Western Europe with range margins marked either by dispersal barriers or the presence of other Radix taxa. Overall, the population structure was characterised by distance independent passive dispersal mainly along a Southwest-Northeast axis, the absence of isolation-by-distance together with rather isolated and genetically depauperated populations compared to the variation present in the entire species due to strong local drift. A recent, climate driven range expansion explained most of the variance in genetic variation, reducing at least temporarily the genetic variability in this area. Other factors such as geographic marginality and dispersal barriers play only a minor role. Conclusions: To our knowledge, such a population structure has rarely been reported before. It might nevertheless be typical for passively dispersed, patchily distributed taxa (e.g. freshwater invertebrates). The strong local drift implied in such a structure is expected to erode genetic variation at both neutral and coding loci and thus probably diminish evolutionary potential. This study shows that the analysis of multiple factors is crucial for the inference of the processes shaping the distribution of genetic variation throughout species ranges. Additional files Additional file 1: Distribution of Radix taxa. Spatial distribution of the Radix MOTU as defined in Pfenninger et al. 2006 plus an additional, newly discovered taxon. This map is the basis for the inference of the species range of R. balthica. Additional file 2: Sampling site table and spatial distribution of diversity indices, selfing estimates and inferred population bottlenecks for R. balthica. Table of sampling site code, geographical position in decimal degrees latitude and longitude, number of individuals analysed with microsatellites (Nnuc), expected heterozygosity (HE) and standard deviation across loci, mean rarefied number of alleles per microsatellite locus (A) and their standard deviation, number of individuals analysed for mitochondrial variation (Nmt), rarefied number of mitochondrial COI haplotypes (Hmt), number of individuals measured for body size (Nsize). Figures A1 - A3 show a graphical representation of the spatial distribution of He, Hmt and, s, respectively. Additional file 3: Assessment of environmental marginality. PCA (principle component analysis) on 35 climatic parameters for the period from 1960 - 2000 from publicly availableWorldClim data. Additional file 4: Inference of a recent climate driven range expansion in R. balthica. Analysis of the freshwater benthos long term monitoring data of the Swedish national monitoring databases at the Swedish University of Agricultural Sciences SLU with canonical correspondence analysis

    Inflammatory Gene Regulatory Networks in Amnion Cells Following Cytokine Stimulation: Translational Systems Approach to Modeling Human Parturition

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    A majority of the studies examining the molecular regulation of human labor have been conducted using single gene approaches. While the technology to produce multi-dimensional datasets is readily available, the means for facile analysis of such data are limited. The objective of this study was to develop a systems approach to infer regulatory mechanisms governing global gene expression in cytokine-challenged cells in vitro, and to apply these methods to predict gene regulatory networks (GRNs) in intrauterine tissues during term parturition. To this end, microarray analysis was applied to human amnion mesenchymal cells (AMCs) stimulated with interleukin-1β, and differentially expressed transcripts were subjected to hierarchical clustering, temporal expression profiling, and motif enrichment analysis, from which a GRN was constructed. These methods were then applied to fetal membrane specimens collected in the absence or presence of spontaneous term labor. Analysis of cytokine-responsive genes in AMCs revealed a sterile immune response signature, with promoters enriched in response elements for several inflammation-associated transcription factors. In comparison to the fetal membrane dataset, there were 34 genes commonly upregulated, many of which were part of an acute inflammation gene expression signature. Binding motifs for nuclear factor-κB were prominent in the gene interaction and regulatory networks for both datasets; however, we found little evidence to support the utilization of pathogen-associated molecular pattern (PAMP) signaling. The tissue specimens were also enriched for transcripts governed by hypoxia-inducible factor. The approach presented here provides an uncomplicated means to infer global relationships among gene clusters involved in cellular responses to labor-associated signals

    Angular and Current-target Correlations in Deep Inelastic Scattering at HERA

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    Correlations between charged particles in deep inelastic e+ p scattering have been studied in the Breit frame with the ZEUS detector at HERA using an integrated luminosity of 6.4pb-1. Short-range correlations are analysed in terms of the angular separation between current-region particles within a cone centred around the virtual photon axis. Long-range correlations between the current and target regions have also been measured. The data support predictions for the scaling behaviour of the angular correlations at high Q2 and for anti-correlations between the current and target regions over a large range in Q2 and in the Bjorken scaling variable x. Analytic QCD calculations and Monte Carlo models correctly describe the trends of the data at high Q2, but show quantitative discrepancies. The data show differences between the correlations in deep inelastic scattering and e+e- annihilation

    Brain energy rescue:an emerging therapeutic concept for neurodegenerative disorders of ageing

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    The brain requires a continuous supply of energy in the form of ATP, most of which is produced from glucose by oxidative phosphorylation in mitochondria, complemented by aerobic glycolysis in the cytoplasm. When glucose levels are limited, ketone bodies generated in the liver and lactate derived from exercising skeletal muscle can also become important energy substrates for the brain. In neurodegenerative disorders of ageing, brain glucose metabolism deteriorates in a progressive, region-specific and disease-specific manner — a problem that is best characterized in Alzheimer disease, where it begins presymptomatically. This Review discusses the status and prospects of therapeutic strategies for countering neurodegenerative disorders of ageing by improving, preserving or rescuing brain energetics. The approaches described include restoring oxidative phosphorylation and glycolysis, increasing insulin sensitivity, correcting mitochondrial dysfunction, ketone-based interventions, acting via hormones that modulate cerebral energetics, RNA therapeutics and complementary multimodal lifestyle changes

    Mean-field transport theory for the two-flavour NJL model

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    By making decomposition of the Wigner function simultaneously in both the spinor and the isospin spaces we derive a set of kinetic equations for the quark distribution functions and the spin densities. A detailed analysis of the consequences imposed by the chiral invariance on the form of the transport equations is presented.Comment: Revtex, 25 pages, no figure
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