20 resultados para Legal Analysis and Writing


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Abstract Background Intronic and intergenic long noncoding RNAs (lncRNAs) are emerging gene expression regulators. The molecular pathogenesis of renal cell carcinoma (RCC) is still poorly understood, and in particular, limited studies are available for intronic lncRNAs expressed in RCC Methods Microarray experiments were performed with custom-designed arrays enriched with probes for lncRNAs mapping to intronic genomic regions. Samples from 18 primary RCC tumors and 11 nontumor adjacent matched tissues were analyzed. Meta-analyses were performed with microarray expression data from three additional human tissues (normal liver, prostate tumor and kidney nontumor samples), and with large-scale public data for epigenetic regulatory marks and for evolutionarily conserved sequences. Results A signature of 29 intronic lncRNAs differentially expressed between RCC and nontumor samples was obtained (false discovery rate (FDR) <5%). A signature of 26 intronic lncRNAs significantly correlated with the RCC five-year patient survival outcome was identified (FDR <5%, p-value ≤0.01). We identified 4303 intronic antisense lncRNAs expressed in RCC, of which 22% were significantly (p <0.05) cis correlated with the expression of the mRNA in the same locus across RCC and three other human tissues. Gene Ontology (GO) analysis of those loci pointed to 'regulation of biological processes’ as the main enriched category. A module map analysis of the protein-coding genes significantly (p <0.05) trans correlated with the 20% most abundant lncRNAs, identified 51 enriched GO terms (p <0.05). We determined that 60% of the expressed lncRNAs are evolutionarily conserved. At the genomic loci containing the intronic RCC-expressed lncRNAs, a strong association (p <0.001) was found between their transcription start sites and genomic marks such as CpG islands, RNA Pol II binding and histones methylation and acetylation. Conclusion Intronic antisense lncRNAs are widely expressed in RCC tumors. Some of them are significantly altered in RCC in comparison with nontumor samples. The majority of these lncRNAs is evolutionarily conserved and possibly modulated by epigenetic modifications. Our data suggest that these RCC lncRNAs may contribute to the complex network of regulatory RNAs playing a role in renal cell malignant transformation.

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Bacterial GatCAB amidotransferases are responsible for the transamidation of mischarged glutamyl-tRNA(Gln) into glutaminyl-tRNA(Gln). Mitochondria matrix also has a multienzymatic complex necessary for the transamidation of glutamyl-tRNA(Gln). Gtf1p, Her2p and Pet112p are the constituents of mitochondrial GatFAB amidotransferase complex. Her2p is subunit A of GatFAB complex, while Gtf1p is subunit F, a connector protein between Pet112p (subunit B) and Her2p. Here we evaluate through molecular modeling and amino acid correlation analysis the HER2 protein family. Localization studies indicated that Her2p is predominantly localized in the mitochondrial outer membrane, but it is also located in the mitochondrial matrix where together with Pet112p and Gtf1p constitutes the GatFAB complex. Finally, HER2 random mutagenesis unveiled important residues that provide thermo stability for the complex and are differently suppressed by overexpression of GTF1 or PET112. For instance, her2/ts11 mutant showed its fermentative growth impaired, and poorly rescued by GTF1 indicating that Her2p unknown function in the mitochondria outer membrane affects cell viability.

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The effect of CO2 continuous laser irradiation on the surface properties of veneering porcelains has already been tested. The surface observed after laser irradiation is similar to that achieved by auto-glaze in terms of roughness and color parameters (Sgura R, et al. Dental Materials 2011;27(Suppl. 1):e72–73). The purpose of this study was to analyze the surface porosity of porcelain discs after CO2 laser treatment and compare it to auto-glaze treatment, in furnace. A morphological analysis of the porcelain surface was conducted using atomic force microscopy (AFM) and conventional optical microscopy (OM).

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In this paper,we present a novel texture analysis method based on deterministic partially self-avoiding walks and fractal dimension theory. After finding the attractors of the image (set of pixels) using deterministic partially self-avoiding walks, they are dilated in direction to the whole image by adding pixels according to their relevance. The relevance of each pixel is calculated as the shortest path between the pixel and the pixels that belongs to the attractors. The proposed texture analysis method is demonstrated to outperform popular and state-of-the-art methods (e.g. Fourier descriptors, occurrence matrix, Gabor filter and local binary patterns) as well as deterministic tourist walk method and recent fractal methods using well-known texture image datasets.

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Dynamic texture is a recent field of investigation that has received growing attention from computer vision community in the last years. These patterns are moving texture in which the concept of selfsimilarity for static textures is extended to the spatiotemporal domain. In this paper, we propose a novel approach for dynamic texture representation, that can be used for both texture analysis and segmentation. In this method, deterministic partially self-avoiding walks are performed in three orthogonal planes of the video in order to combine appearance and motion features. We validate our method on three applications of dynamic texture that present interesting challenges: recognition, clustering and segmentation. Experimental results on these applications indicate that the proposed method improves the dynamic texture representation compared to the state of the art.