41 research outputs found

    PPAR? Downregulation by TGF in Fibroblast and Impaired Expression and Function in Systemic Sclerosis: A Novel Mechanism for Progressive Fibrogenesis

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    The nuclear orphan receptor peroxisome proliferator-activated receptor-gamma (PPAR-γ) is expressed in multiple cell types in addition to adipocytes. Upon its activation by natural ligands such as fatty acids and eicosanoids, or by synthetic agonists such as rosiglitazone, PPAR-γ regulates adipogenesis, glucose uptake and inflammatory responses. Recent studies establish a novel role for PPAR-γ signaling as an endogenous mechanism for regulating transforming growth factor-ß (TGF-ß)- dependent fibrogenesis. Here, we sought to characterize PPAR-γ function in the prototypic fibrosing disorder systemic sclerosis (SSc), and delineate the factors governing PPAR-γ expression. We report that PPAR-γ levels were markedly diminished in skin and lung biopsies from patients with SSc, and in fibroblasts explanted from the lesional skin. In normal fibroblasts, treatment with TGF-ß resulted in a time- and dose-dependent down-regulation of PPAR-γ expression. Inhibition occurred at the transcriptional level and was mediated via canonical Smad signal transduction. Genome-wide expression profiling of SSc skin biopsies revealed a marked attenuation of PPAR-γ levels and transcriptional activity in a subset of patients with diffuse cutaneous SSc, which was correlated with the presence of a ''TGF-ß responsive gene signature'' in these biopsies. Together, these results demonstrate that the expression and function of PPAR-γ are impaired in SSc, and reveal the existence of a reciprocal inhibitory cross-talk between TGF-ß activation and PPAR-γ signaling in the context of fibrogenesis. In light of the potent anti-fibrotic effects attributed to PPAR-γ, these observations lead us to propose that excessive TGF-ß activity in SSc accounts for impaired PPAR-γ function, which in turn contributes to unchecked fibroblast activation and progressive fibrosis. © 2010 Wei et al

    Pattern Recognition Based Speed Forecasting Methodology for Urban Traffic Network

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    A full methodology of short-term traffic prediction is proposed for urban road traffic network via Artificial Neural Network (ANN). The goal of the forecasting is to provide speed estimation forward by 5, 15 and 30 min. Unlike similar research results in this field, the investigated method aims to predict traffic speed for signalized urban road links and not for highway or arterial roads. The methodology contains an efficient feature selection algorithm in order to determine the appropriate input parameters required for neural network training. As another contribution of the paper, a built-in incomplete data handling is provided as input data (originating from traffic sensors or Floating Car Data (FCD)) might be absent or biased in practice. Therefore, input data handling can assure a robust operation of speed forecasting also in case of missing data. The proposed algorithm is trained, tested and analysed in a test network built-up in a microscopic traffic simulator by using daily course of real-world traffic

    Targeting vascular endothelial growth factor receptor 2 and protein kinase d1 related pathways by a multiple kinase inhibitor in angiogenesis and inflammation related processes in vitro.

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    Emerging evidence suggests that the vascular endothelial growth factor receptor 2 (VEGFR2) and protein kinase D1 (PKD1) signaling axis plays a critical role in normal and pathological angiogenesis and inflammation related processes. Despite all efforts, the currently available therapeutic interventions are limited. Prior studies have also proved that a multiple target inhibitor can be more efficient compared to a single target one. Therefore, development of novel inflammatory pathway-specific inhibitors would be of great value. To test this possibility, we screened our molecular library using recombinant kinase assays and identified the previously described compound VCC251801 with strong inhibitory effect on both VEGFR2 and PKD1. We further analyzed the effect of VCC251801 in the endothelium-derived EA.hy926 cell line and in different inflammatory cell types. In EA.hy926 cells, VCC251801 potently inhibited the intracellular activation and signaling of VEGFR2 and PKD1 which inhibition eventually resulted in diminished cell proliferation. In this model, our compound was also an efficient inhibitor of in vitro angiogenesis by interfering with endothelial cell migration and tube formation processes. Our results from functional assays in inflammatory cellular models such as neutrophils and mast cells suggested an anti-inflammatory effect of VCC251801. The neutrophil study showed that VCC251801 specifically blocked the immobilized immune-complex and the adhesion dependent TNF-alpha -fibrinogen stimulated neutrophil activation. Furthermore, similar results were found in mast cell degranulation assay where VCC251801 caused significant reduction of mast cell response. In summary, we described a novel function of a multiple kinase inhibitor which strongly inhibits the VEGFR2-PKD1 signaling and might be a novel inhibitor of pathological inflammatory pathways

    Investigation of inter- and intraspecies variation through genome sequencing of Aspergillus section Nigri

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    Aspergillus section Nigri comprises filamentous fungi relevant to biomedicine, bioenergy, health, and biotechnology. To learn more about what genetically sets these species apart, as well as about potential applications in biotechnology and biomedicine, we sequenced 23 genomes de novo, forming a full genome compendium for the section (26 species), as well as 6 Aspergillus niger isolates. This allowed us to quantify both inter-and intraspecies genomic variation. We further predicted 17,903 carbohydrateactive enzymes and 2,717 secondary metabolite gene clusters, which we condensed into 455 distinct families corresponding to compound classes, 49% of which are only found in single species. We performed metabolomics and genetic engineering to correlate genotypes to phenotypes, as demonstrated for the metabolite aurasperone, and by heterologous transfer of citrate production to Aspergillus nidulans. Experimental and computational analyses showed that both secondary metabolism and regulation are key factors that are significant in the delineation of Aspergillus species.Peer reviewe
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