979 resultados para Platelet Activating Factor


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Generation of homogeneous oligodendrocytes as donor cells is essential for human embryonic stem cell (hESC)-based cell therapy for demylinating diseases. Herein we present a novel method for efficiently obtaining mature oligodendrocytes from hESCs with high purity (79.7 +/- 6.9%), using hepatocyte growth factor (HGF) and G5 supplement(containing insulin, transferrin, selenite, biotin, hydrocortisone, basic fibroblast growth factor and epidermal growth factor) in a four-step method. We induced hESCs into neural progenitors (NP) with HGF (5 ng/ml) and G5 (1 x) supplemented medium in an adherent differentiation system. The purified NPs were amplified in suspension as neurospheres for 1 month, and terminal oligodendrocyte differentiation was then induced by G5 supplement withdrawal and HGF treatment (20 ng/ml). The cells generated displayed typical morphologies of mature oligodendrocytes and expressed oligodendrocyte markers O4 and myelin basic protein (MBP). Our result revealed that HGF significantly enhanced the proliferation of hESC-derived NPs and promoted the differentiation as well as the maturation of oligodendrocytes from NPs. Further studies suggest that HGF/c-Met signaling pathway might play an important role in oligodendrocyte differentiation in our system. Our studies provide a means for generating the clinically relevant cell type and a platform for deciphering the molecular mechanisms that control oligodendrocyte differentiation. (C) 2009 International Society of Differentiation. Published by Elsevier Ltd. All rights reserved.

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Condition factor based on length-weight relationship and food and feeding habits of Arius dussumieri (Black lip sea catfish) and Osteogeneiosus militaris (Soldier catfish) from the Mumbai coast have been studied. Relative Condition Factor showed variations on a monthly basis, and appear to be influenced by feeding and breeding activities. Both the species studied are carnivorous bottom feeders, with crustaceans followed by other smaller fishes forming the major food item in the gut contents.

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Vascular endothelial growth factor (VEGF) plays an important role in normal and pathological angiogenesis. VEGF receptors (VEGFRs, including VEGFR-1, VEGFR-2, and VEGFR-3) and neuropilins (NRPs, including NRP-1 and NRF-2) are high-affinity receptors for V

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MITOMAP is by far the most frequently cited Web resource that is referred to in substantiating novelty of an mtDNA mutation. This database, as is now known, has quite an incomplete coverage of the mtDNA mutations from the literature. This circumstance has

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A highly active cobra venom factor (CVF) was isolated from the venom of Naja kaouthia by sequential column chromatography. It displays strong anticomplementary activity, and has 1515 U of anti complementary activity per mg protein. A single dose of 0.1 mg/kg CVF given i.v. to rats completely abrogated complement activity for nearly 5 days. Given 0.02 mg/kg of CVF. the complement activity of rats was reduced by more than 96.5% in 6 It. In guinea pig-to-rat heart transplant model, rats treated with a single dose of 0.05 mg/kg CVF had significantly prolonged xenograft survival (56.12 +/- 6.27 h in CVF-treated rats vs. 0.19 +/- 0.07 h in control rats, P < 0.001). (C) 2003 Elsevier Ltd. All rights reserved.

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Vector Taylor Series (VTS) model based compensation is a powerful approach for noise robust speech recognition. An important extension to this approach is VTS adaptive training (VAT), which allows canonical models to be estimated on diverse noise-degraded training data. These canonical model can be estimated using EM-based approaches, allowing simple extensions to discriminative VAT (DVAT). However to ensure a diagonal corrupted speech covariance matrix the Jacobian (loading matrix) relating the noise and clean speech is diagonalised. In this work an approach for yielding optimal diagonal loading matrices based on minimising the expected KL-divergence between the diagonal loading matrix and "correct" distributions is proposed. The performance of DVAT using the standard and optimal diagonalisation was evaluated on both in-car collected data and the Aurora4 task. © 2012 IEEE.

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We offer a solution to the problem of efficiently translating algorithms between different types of discrete statistical model. We investigate the expressive power of three classes of model-those with binary variables, with pairwise factors, and with planar topology-as well as their four intersections. We formalize a notion of "simple reduction" for the problem of inferring marginal probabilities and consider whether it is possible to "simply reduce" marginal inference from general discrete factor graphs to factor graphs in each of these seven subclasses. We characterize the reducibility of each class, showing in particular that the class of binary pairwise factor graphs is able to simply reduce only positive models. We also exhibit a continuous "spectral reduction" based on polynomial interpolation, which overcomes this limitation. Experiments assess the performance of standard approximate inference algorithms on the outputs of our reductions.