577 research outputs found

    Industry in focus

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    ThesisIt is since 1839 that photography has been a vital means of communication and expression. Photography is at once a science and art. Both these aspects were inseparably linked throughout its rise from a replacement for skill of hand to a form of art on its own. Industrial photography was one of the later developments o~ photography. Over these years it has also undergone vast changes. Today industrial photography plays a major role in the world of modern adverti s ing

    Structural modelling of adhesive joints in automotive bodies

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    The behaviour of a vehicle is dependent on the stiffness of the joints between the sheet components in the body shell. Although spot-welding is the predominant joining method for the construction of steel bodies in the automotive industry, other alternatives are now being considered. Adhesive bonding offers the best potential because the uniform load distribution in the joint reduces the stress concentrations produced when using spot-welding. It is generally observed that adhesive bonded structures are stiffer than assemblies fabricated with mechanical fasteners or spot-welds. The use of adhesives, either as an alternative or a supplement to spot-welding, is of interest because of the potential improvements in joint stiffness and in the overall behaviour of the structure. The effective stiffness of an adhesively bonded joint may be difficult to quantify, as it is dependent on many design variables of the actual joint. Finite element models have been developed to study the effects of various design parameters, such as different joining techniques, on car body characteristics. However, finite element models of large vehicle structures involve large numbers of elements which as a result can impose excessive demands in computer capacity. Because of this, approximations are commonly made in the model to reduce the number of elements consequently resulting in inaccuracies. The main inaccuracy develops from the lack of geometric details within local joints which may lead to some uncertainty in local joint stiffness. As a consequence, this may introduce errors in the prediction of global vehicle stiffness. In this project, the errors which result from the inaccuracies in macro modelling methods have been addressed through a parallel study of detailed micro models. Various adhesive joint configurations have been analysed using finite element methods to predict joint stiffness; comparative results were obtained through experimental testing of similar joints. A primary objective was to obtain characteristics of smaller joint structures and compare these to results from macro models of similar joints which could then be translated into larger-scale structure models for improved accuracy. A methodology has been developed to translate micro model joint characteristics into large- scale structures through an undercut element technique. When applied to macro models which lack geometric details of joints, the undercut element method enables more accurate predictions of behaviour, particularly stiffness performance, to be made. The method has been shown to be applicable to a number of typical joints and also for different loading conditions. Validation of the method has been demonstrated by its application to progressively larger substructures, from which experimental test data was available for comparison. Because of the ease of use of the undercut method it may be conveniently applied to automotive bodies. The method provides a more accurate finite element model resulting in less computational time for analysis than other existing solutions

    Il fascino del surreale nella prosa di Etgar Keret

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    The EEF1A2 gene expression as risk predictor in localized prostate cancer

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    Background: Besides clinical stage and Gleason score, risk-stratification of prostate cancer in the pretherapeutic setting mainly relies on the serum PSA level. Yet, this is associated with many uncertainties. With regard to therapy decision-making, additional markers are needed to allow an exact risk prediction. Eukaryotic translation elongation factor 1 alpha 2 (EEF1A2) was previously suggested as driver of tumor progression and potential biomarker. In the present study its functional and prognostic relevance in prostate cancer was investigated. Methods: EEF1A2 expression was analyzed in two cohorts of patients (n = 40 and n = 59) with localized PCa. Additionally data from two large expression dataset (MSKCC, Cell, 2010 with n = 131 localized, n = 19 metastatic PCa and TCGA provisional data, n = 499) of PCa patients were reanalyzed. The expression of EEF1A2 was correlated with histopathology features and biochemical recurrence (BCR). To evaluate the influence of EEF1A2 on proliferation and migration of metastatic PC3 cells, siRNA interference was used. Statistical significance was tested with t-test, Mann-Whitney-test, Pearson correlation and log-rank test. Results: qRT-PCR revealed EEF1A2 to be significantly overexpressed in PCa tissue, with an increase according to tumor stage in one cohort (p = 0.0443). In silico analyses in the MSKCC cohort confirmed the overexpression of EEF1A2 in localized PCa with high Gleason score (p = 0.0142) and in metastatic lesions (p = 0.0038). Patients with EEF1A2 overexpression had a significantly shorter BCR-free survival (p = 0.0028). EEF1A2 expression was not correlated with serum PSA levels. Similar results were seen in the TCGA cohort, where EEF1A2 overexpression only occurred in tumors with Gleason 7 or higher. Patients with elevated EEF1A2 expression had a significantly shorter BCR-free survival (p = 0.043). EEF1A2 knockdown significantly impaired the migration, but not the proliferation of metastatic PC3 cells. Conclusion: The overexpression of EEF1A2 is a frequent event in localized PCa and is associated with histopathology features and a shorter biochemical recurrence-free survival. Due to its independence from serum PSA levels, EEF1A2 could serve as valuable biomarker in risk-stratification of localized PCa

    The fidelity of dynamic signaling by noisy biomolecular networks

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    This is the final version of the article. Available from Public Library of Science via the DOI in this record.Cells live in changing, dynamic environments. To understand cellular decision-making, we must therefore understand how fluctuating inputs are processed by noisy biomolecular networks. Here we present a general methodology for analyzing the fidelity with which different statistics of a fluctuating input are represented, or encoded, in the output of a signaling system over time. We identify two orthogonal sources of error that corrupt perfect representation of the signal: dynamical error, which occurs when the network responds on average to other features of the input trajectory as well as to the signal of interest, and mechanistic error, which occurs because biochemical reactions comprising the signaling mechanism are stochastic. Trade-offs between these two errors can determine the system's fidelity. By developing mathematical approaches to derive dynamics conditional on input trajectories we can show, for example, that increased biochemical noise (mechanistic error) can improve fidelity and that both negative and positive feedback degrade fidelity, for standard models of genetic autoregulation. For a group of cells, the fidelity of the collective output exceeds that of an individual cell and negative feedback then typically becomes beneficial. We can also predict the dynamic signal for which a given system has highest fidelity and, conversely, how to modify the network design to maximize fidelity for a given dynamic signal. Our approach is general, has applications to both systems and synthetic biology, and will help underpin studies of cellular behavior in natural, dynamic environments.We acknowledge support from a Medical Research Council and Engineering and Physical Sciences Council funded Fellowship in Biomedical Informatics (CGB) and a Scottish Universities Life Sciences Alliance chair in Systems Biology (PSS). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

    Interleukin-27 Is a Potential Rescue Therapy for Acute Severe Colitis Through Interleukin-10-Dependent, T-Cell-Independent Attenuation of Colonic Mucosal Innate Immune Responses

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    Background: If treatment with intravenous steroids fail, inflammatory bowel disease patients with acute severe colitis face systemic anti–tumor necrosis factor biologic rescue therapy or colectomy. Interleukin (IL)-27 is a cytokine with an immunosuppressive role in adaptive immune responses. However, the IL-27 receptor complex is also expressed on innate immune cells, and there is evidence that IL-27 can impact the function of innate cell subsets, although this particular functionality in vivo is not understood. Our aim was to define the efficacy of IL-27 in acute severe colitis and characterize novel IL-27–driven mechanisms of immunosuppression in the colonic mucosa. Methods: We assessed oral delivery of Lactococcus lactis expressing an IL-27 hyperkine on the innate immune response in vivo in a genetically intact, noninfective, acute murine colitis model induced by intrarectal instillation of 2,4,6-trinitrobenzenesulfonic acid in SJL/J mice. Results: IL-27 attenuates acute severe colitis through the reduction of colonic mucosal neutrophil infiltrate associated with a decreased CXC chemokine gradient. This suppression was T cell independent and IL-10 dependent, initially featuring enhanced mucosal IL-10. IL-27 was associated with a reduction in colonic proinflammatory cytokines and induced a multifocal, strong, positive nuclear expression of phosphorylated STAT-1 in mucosal epithelial cells. Conclusion: We have defined novel mechanisms of IL-27 immunosuppression toward colonic innate immune responses in vivo. Mucosal delivery of IL-27 has translational potential as a novel therapeutic for inflammatory bowel disease, and it is a future mucosal directed rescue therapy in acute severe inflammatory bowel disease

    Anchoring of proteins to lactic acid bacteria

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    The anchoring of proteins to the cell surface of lactic acid bacteria (LAB) using genetic techniques is an exciting and emerging research area that holds great promise for a wide variety of biotechnological applications. This paper reviews five different types of anchoring domains that have been explored for their efficiency in attaching hybrid proteins to the cell membrane or cell wall of LAB. The most exploited anchoring regions are those with the LPXTG box that bind the proteins in a covalent way to the cell wall. In recent years, two new modes of cell wall protein anchoring have been studied and these may provide new approaches in surface display. The important progress that is being made with cell surface display of chimaeric proteins in the areas of vaccine development and enzyme- or whole-cell immobilisation is highlighted.
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