968 resultados para vector-borne diseases
Resumo:
Reverse genetics has facilitated the use of non-segmented negative strand RNA viruses (NNSV) as vectors. Currently, heterologous gene expression necessitates insertion of extra-numeral transcription units (ENTUs), which may alter the NNSV polar transcription gradient and attenuate growth relative to wildtype (Wt). We hypothesized that rescuing recombinant Sendai Virus (rSeV) with a bicistronic gene might circumvent this attenuation but still allow heterologous open reading frame (ORF) expression. Therefore, we used a 9-nucleotide sequence previously described with internal ribosome entry site (IRES) activity, which, when constructed as several repeats, synergistically increased the level of expression of the second cistron [Chappell, S.A., Edelman, G.M., Mauro, V.P., 2000. A 9-nt segment of a cellular mRNA can function as an internal ribosome entry site (IRES) and when present in linked multiple copies greatly enhances IRES activity. Proc. Natl. Acad. Sci. U.S.A. 97, 1536-1541]. We inserted the Renilla luciferase (rLuc) ORF, preceded by 1, 3 or 7 IRES copies, downstream of the SeV N ORF in an infectious clone. Corresponding rSeVs were successfully rescued. Interestingly, bicistronic rSeVs grew as fast as or faster than Wt rSeV. Furthermore, SeV gene transcription downstream of the N/rLuc gene was either equivalent to, or slightly enhanced, compared to Wt rSeV. Importantly, all rSeV/rLuc viruses efficiently expressed rLuc. IRES repetition increased rLuc expression at a multiplicity of infection of 0.1, although without evidence of synergistic enhancement. In conclusion, our approach provides a novel way of insertion and expression of foreign genes in NNSVs. (C) 2008 Elsevier B.V. All rights reserved.
Resumo:
Purose: The traditional approach for identifying subjects at risk from cardiovascular diseases (CVD) is to determine the extent of clustering of biological risk factors adjusted for lifestyle. Recently, markers of endothelial dysfunction and low grade inflammation, including high sensitivity C-reactive protein (hsCRP), soluble intercellular adhesion molecules (sICAM), and soluble vascular adhesion molecules (sVCAM), have been included in the detection for high risk individuals. However, the relationship of these novel biomarkers with CVD risk in adolescents remains unclear. The purpose of this study, therefore, was to establish the association of hsCRP, sICAM, and sVCAM with CVD risk in an adolescent population.
Methods: Data from the Young Hearts 2000 cross-sectional cohort study, carried out in 1999-2001, were used. From a total of 2,017 male and female participants, 95 obese subjects were identified and matched according to age, sex, and cigarette smoking, with 95 overweight and 95 normal-weight adolescents. Clustered CVD risk was computed using a sum of Z-scores of biological risk factors. The relationship was described using multiple linear regression analyses.
Results: hsCRP, sICAM, and sVCAM showed significant associations with CVD risk. hsCRP and sICAM had a positive relation with CVD risk, whereas sVCAM showed an inverse relationship. In this study, lifestyle factors showed no relation with CVD risk.
Conclusion: The results fit the hypothesized role of low grade inflammation and endothelial dysfunction in CVD risk in asymptomatic adolescents. The inverse relationship of VCAM, however, is hard to explain and indicates the complex mechanisms underlying CVD. Further research is needed to draw firm conclusions on the biomarkers used.
Resumo:
Climate change is perhaps the most pressing and urgent environmental issue facing the world today. However our ability to predict and quantify the consequences of this change is severely limited by the paucity of in situ oceanographic measurements. Marine animals equipped with sophisticated oceanographic data loggers to study their behavior offer one solution to this problem because marine animals range widely across the world's ocean basins and visit remote and often inaccessible locations. However, unlike the information being collected from conventional oceanographic sensing equipment, which has been validated, the data collected from instruments deployed on marine animals over long periods has not. This is the first long-term study to validate in situ oceanographic data collected by animal oceanographers. We compared the ocean temperatures collected by leatherback turtles (Dermochelys coriacea) in the Atlantic Ocean with the ARGO network of ocean floats and could find no systematic errors that could be ascribed to sensor instability. Animal-borne sensors allowed water temperature to be monitored across a range of depths, over entire ocean basins, and, importantly, over long periods and so will play a key role in assessing global climate change through improved monitoring of global temperatures. This finding is especially pertinent given recent international calls for the development and implementation of a comprehensive Earth observation system ( see http://iwgeo.ssc.nasa.gov/documents.asp?s=review) that includes the use of novel techniques for monitoring and understanding ocean and climate interactions to address strategic environmental and societal needs.
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Chronic kidney disease is common with up to 5% of the adult population reported to have an estimated glomerular filtration rate of
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Background: Pea encodes eukaryotic translation initiation factor eIF4E (eIF4E(S)), which supports the multiplication of Pea seed-borne mosaic virus (PSbMV). In common with hosts for other potyviruses, some pea lines contain a recessive allele (sbm1) encoding a mutant eIF4E (eIF4E(R)) that fails to interact functionally with the PSbMV avirulence protein, VPg, giving genetic resistance to infection.
Resumo:
Phage metagenomes isolated from wastewater over a 12-month period were analyzed. The results suggested that various strains of Proteobacteria, Bacteroidetes, and other phyla are likely to participate in transduction. The patterns of 16S rRNA sequences found in phage metagenomes did not follow changes in the total bacterial community.
Resumo:
Nonlinear principal component analysis (PCA) based on neural networks has drawn significant attention as a monitoring tool for complex nonlinear processes, but there remains a difficulty with determining the optimal network topology. This paper exploits the advantages of the Fast Recursive Algorithm, where the number of nodes, the location of centres, and the weights between the hidden layer and the output layer can be identified simultaneously for the radial basis function (RBF) networks. The topology problem for the nonlinear PCA based on neural networks can thus be solved. Another problem with nonlinear PCA is that the derived nonlinear scores may not be statistically independent or follow a simple parametric distribution. This hinders its applications in process monitoring since the simplicity of applying predetermined probability distribution functions is lost. This paper proposes the use of a support vector data description and shows that transforming the nonlinear principal components into a feature space allows a simple statistical inference. Results from both simulated and industrial data confirm the efficacy of the proposed method for solving nonlinear principal component problems, compared with linear PCA and kernel PCA.