3,374 research outputs found

    Factors affecting inter-regional academic scientific collaboration within Europe: the role of economic distance

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    This paper offers some insights into scientific collaboration (SC) at the regional level by drawing upon two lines of inquiry. The first involves examining the spatial patterns of university SC across the EU-15 (all countries belonging to the European Union between 1995 and 2004). The second consists of extending the current empirical analysis on regional SC collaboration by including the economic distance between regions in the model along with other variables suggested by the extant literature. The methodology relies on co-publications as a proxy for academic collaboration, and in order to test the relevance of economic distance for the intensity of collaboration between regions, we put forward a gravity equation. The descriptive results show that there are significant differences in the production of academic scientific papers between less-favoured regions and core regions. However, the intensity of collaboration is similar in both types of regions. Our econometric findings suggest that differences in scientific resources (as measured by R&D expenditure) between regions are relevant in explaining academic scientific collaborations, while distance in the level of development (as measured by per capita GDP) does not appear to play any significant role. Nevertheless, other variables in the analysis, including geographical distance, specialization and cultural factors, do yield significant estimated coefficients, and this is consistent with the previous literature on regional SC

    Determinants of adults' intention to vaccinate against pandemic swine flu

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    This article has been made available through the Brunel Open Access Publishing Fund.This article has been made available through the Brunel Open Access Publishing Fund.Background: Vaccination is one of the cornerstones of controlling an influenza pandemic. To optimise vaccination rates in the general population, ways of identifying determinants that influence decisions to have or not to have a vaccination need to be understood. Therefore, this study aimed to predict intention to have a swine influenza vaccination in an adult population in the UK. An extension of the Theory of Planned Behaviour provided the theoretical framework for the study. Methods: Three hundred and sixty two adults from the UK, who were not in vaccination priority groups, completed either an online (n = 306) or pen and paper (n = 56) questionnaire. Data were collected from 30th October 2009, just after swine flu vaccination became available in the UK, and concluded on 31st December 2009. The main outcome of interest was future swine flu vaccination intentions. Results: The extended Theory of Planned Behaviour predicted 60% of adults’ intention to have a swine flu vaccination with attitude, subjective norm, perceived control, anticipating feelings of regret (the impact of missing a vaccination opportunity), intention to have a seasonal vaccine this year, one perceived barrier: “I cannot be bothered to get a swine flu vaccination” and two perceived benefits: “vaccination decreases my chance of getting swine flu or its complications” and “if I get vaccinated for swine flu, I will decrease the frequency of having to consult my doctor,” being significant predictors of intention. Black British were less likely to intend to have a vaccination compared to Asian or White respondents. Conclusions: Theoretical frameworks which identify determinants that influence decisions to have a pandemic influenza vaccination are useful. The implications of this research are discussed with a view to maximising any future pandemic influenza vaccination uptake using theoretically-driven applications.This article is available through the Brunel Open Access Publishing Fund

    Differential expression analysis for sequence count data

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    *Motivation:* High-throughput nucleotide sequencing provides quantitative readouts in assays for RNA expression (RNA-Seq), protein-DNA binding (ChIP-Seq) or cell counting (barcode sequencing). Statistical inference of differential signal in such data requires estimation of their variability throughout the dynamic range. When the number of replicates is small, error modelling is needed to achieve statistical power.

*Results:* We propose an error model that uses the negative binomial distribution, with variance and mean linked by local regression, to model the null distribution of the count data. The method controls type-I error and provides good detection power. 

*Availability:* A free open-source R software package, _DESeq_, is available from the Bioconductor project and from "http://www-huber.embl.de/users/anders/DESeq":http://www-huber.embl.de/users/anders/DESeq

    Upregulation of the cell-cycle regulator RGC-32 in Epstein-Barr virus-immortalized cells

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    Epstein-Barr virus (EBV) is implicated in the pathogenesis of multiple human tumours of lymphoid and epithelial origin. The virus infects and immortalizes B cells establishing a persistent latent infection characterized by varying patterns of EBV latent gene expression (latency 0, I, II and III). The CDK1 activator, Response Gene to Complement-32 (RGC-32, C13ORF15), is overexpressed in colon, breast and ovarian cancer tissues and we have detected selective high-level RGC-32 protein expression in EBV-immortalized latency III cells. Significantly, we show that overexpression of RGC-32 in B cells is sufficient to disrupt G2 cell-cycle arrest consistent with activation of CDK1, implicating RGC-32 in the EBV transformation process. Surprisingly, RGC-32 mRNA is expressed at high levels in latency I Burkitt's lymphoma (BL) cells and in some EBV-negative BL cell-lines, although RGC-32 protein expression is not detectable. We show that RGC-32 mRNA expression is elevated in latency I cells due to transcriptional activation by high levels of the differentially expressed RUNX1c transcription factor. We found that proteosomal degradation or blocked cytoplasmic export of the RGC-32 message were not responsible for the lack of RGC-32 protein expression in latency I cells. Significantly, analysis of the ribosomal association of the RGC-32 mRNA in latency I and latency III cells revealed that RGC-32 transcripts were associated with multiple ribosomes in both cell-types implicating post-initiation translational repression mechanisms in the block to RGC-32 protein production in latency I cells. In summary, our results are the first to demonstrate RGC-32 protein upregulation in cells transformed by a human tumour virus and to identify post-initiation translational mechanisms as an expression control point for this key cell-cycle regulator

    TLR7-mediated skin inflammation remotely triggers chemokine expression and leukocyte accumulation in the brain

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    Background: The relationship between the brain and the immune system has become increasingly topical as, although it is immune-specialised, the CNS is not free from the influences of the immune system. Recent data indicate that peripheral immune stimulation can significantly affect the CNS. But the mechanisms underpinning this relationship remain unclear. The standard approach to understanding this relationship has relied on systemic immune activation using bacterial components, finding that immune mediators, such as cytokines, can have a significant effect on brain function and behaviour. More rarely have studies used disease models that are representative of human disorders. Methods: Here we use a well-characterised animal model of psoriasis-like skin inflammation—imiquimod—to investigate the effects of tissue-specific peripheral inflammation on the brain. We used full genome array, flow cytometry analysis of immune cell infiltration, doublecortin staining for neural precursor cells and a behavioural read-out exploiting natural burrowing behaviour. Results: We found that a number of genes are upregulated in the brain following treatment, amongst which is a subset of inflammatory chemokines (CCL3, CCL5, CCL9, CXCL10, CXCL13, CXCL16 and CCR5). Strikingly, this model induced the infiltration of a number of immune cell subsets into the brain parenchyma, including T cells, NK cells and myeloid cells, along with a reduction in neurogenesis and a suppression of burrowing activity. Conclusions: These findings demonstrate that cutaneous, peripheral immune stimulation is associated with significant leukocyte infiltration into the brain and suggest that chemokines may be amongst the key mediators driving this response

    A cautionary note regarding count models of alcohol consumption in randomized controlled trials

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    BACKGROUND: Alcohol consumption is commonly used as a primary outcome in randomized alcohol treatment studies. The distribution of alcohol consumption is highly skewed, particularly in subjects with alcohol dependence. METHODS: In this paper, we will consider the use of count models for outcomes in a randomized clinical trial setting. These include the Poisson, over-dispersed Poisson, negative binomial, zero-inflated Poisson and zero-inflated negative binomial. We compare the Type-I error rate of these methods in a series of simulation studies of a randomized clinical trial, and apply the methods to the ASAP (Addressing the Spectrum of Alcohol Problems) trial. RESULTS: Standard Poisson models provide a poor fit for alcohol consumption data from our motivating example, and did not preserve Type-I error rates for the randomized group comparison when the true distribution was over-dispersed Poisson. For the ASAP trial, where the distribution of alcohol consumption featured extensive over-dispersion, there was little indication of significant randomization group differences, except when the standard Poisson model was fit. CONCLUSION: As with any analysis, it is important to choose appropriate statistical models. In simulation studies and in the motivating example, the standard Poisson was not robust when fit to over-dispersed count data, and did not maintain the appropriate Type-I error rate. To appropriately model alcohol consumption, more flexible count models should be routinely employed

    The Role of TLR4 in the Paclitaxel Effects on Neuronal Growth In Vitro

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    Paclitaxel (Pac) is an antitumor agent that is widely used for treatment of solid cancers. While being effective as a chemotherapeutic agent, Pac in high doses is neurotoxic, specifically targeting sensory innervations. In view of these toxic effects associated with conventional chemotherapy, decreasing the dose of Pac has been recently suggested as an alternative approach, which might limit neurotoxicity and immunosuppression. However, it remains unclear if low doses of Pac retain its neurotoxic properties or might exhibit unusual effects on neuronal cells. The goal of this study was to analyze the concentration-dependent effect of Pac on isolated and cultured DRG neuronal cells from wild-type and TLR4 knockout mice. Three different morphological parameters were analyzed: the number of neurons which developed neurites, the number of neurites per cell and the total length of neurites per cell. Our data demonstrate that low concentrations of Pac (0.1 nM and 0.5 nM) do not influence the neuronal growth in cultures in both wild type and TLR4 knockout mice. Higher concentrations of Pac (1-100 nM) had a significant effect on DRG neurons from wild type mice, affecting the number of neurons which developed neurites, number of neurites per cell, and the length of neurites. In DRG from TLR4 knockout mice high concentrations of Pac showed a similar effect on the number of neurons which developed neurites and the length of neurites. At the same time, the number of neurites per cell, indicating the process of growth cone initiation, was not affected by high concentrations of Pac. Thus, our data showed that Pac in high concentrations has a significant damaging effect on axonal growth and that this effect is partially mediated through TLR4 pathways. Low doses of Pac are devoid of neuronal toxicity and thus can be safely used in a chemomodulation mode. © 2013 Ustinova et al

    Emotional intelligence buffers the effect of physiological arousal on dishonesty

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    We studied the emotional processes that allow people to balance two competing desires: benefitting from dishonesty and keeping a positive self-image. We recorded physiological arousal (skin conductance and heart rate) during a computer card game in which participants could cheat and fail to report a certain card when presented on the screen to avoid losing their money. We found that higher skin conductance corresponded to lower cheating rates. Importantly, emotional intelligence regulated this effect; participants with high emotional intelligence were less affected by their physiological reactions than those with low emotional intelligence. As a result, they were more likely to profit from dishonesty. However, no interaction emerged between heart rate and emotional intelligence. We suggest that the ability to manage and control emotions can allow people to overcome the tension between doing right or wrong and license them to bend the rules
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