851 resultados para Correlation based analysis


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Whether total extraperitoneal inguinal hernia repair (TEP) is associated with worse outcomes than transabdominal preperitoneal inguinal hernia repair (TAPP) continues to be a matter of debate. The objective of this large cohort study is to compare outcomes between patients undergoing TEP or TAPP.

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The prognosis of even early-stage esophageal cancer is poor. Because there is not a consensus on how to manage T2 N0 disease, we examined survival after resection of T2 N0 esophageal cancer, with or without radiation therapy.

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BACKGROUND Moraxella catarrhalis, a major nasopharyngeal pathogen of the human respiratory tract, is exposed to rapid downshifts of environmental temperature when humans breathe cold air. The prevalence of pharyngeal colonization and respiratory tract infections caused by M. catarrhalis is greatest in winter. We investigated how M. catarrhalis uses the physiologic exposure to cold air to regulate pivotal survival systems that may contribute to M. catarrhalis virulence. RESULTS In this study we used the RNA-seq techniques to quantitatively catalogue the transcriptome of M. catarrhalis exposed to a 26 °C cold shock or to continuous growth at 37 °C. Validation of RNA-seq data using quantitative RT-PCR analysis demonstrated the RNA-seq results to be highly reliable. We observed that a 26 °C cold shock induces the expression of genes that in other bacteria have been related to virulence a strong induction was observed for genes involved in high affinity phosphate transport and iron acquisition, indicating that M. catarrhalis makes a better use of both phosphate and iron resources after exposure to cold shock. We detected the induction of genes involved in nitrogen metabolism, as well as several outer membrane proteins, including ompA, m35-like porin and multidrug efflux pump (acrAB) indicating that M. catarrhalis remodels its membrane components in response to downshift of temperature. Furthermore, we demonstrate that a 26 °C cold shock enhances the induction of genes encoding the type IV pili that are essential for natural transformation, and increases the genetic competence of M. catarrhalis, which may facilitate the rapid spread and acquisition of novel virulence-associated genes. CONCLUSION Cold shock at a physiologically relevant temperature of 26 °C induces in M. catarrhalis a complex of adaptive mechanisms that could convey novel pathogenic functions and may contribute to enhanced colonization and virulence.

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Purpose Recently, multiple clinical trials have demonstrated improved outcomes in patients with metastatic colorectal cancer. This study investigated if the improved survival is race dependent. Patients and Methods Overall and cancer-specific survival of 77,490 White and Black patients with metastatic colorectal cancer from the 1988–2008 Surveillance Epidemiology and End Results registry were compared using unadjusted and multivariable adjusted Cox proportional hazard regression as well as competing risk analyses. Results Median age was 69 years, 47.4 % were female and 86.0 % White. Median survival was 11 months overall, with an overall increase from 8 to 14 months between 1988 and 2008. Overall survival increased from 8 to 14 months for White, and from 6 to 13 months for Black patients. After multivariable adjustment, the following parameters were associated with better survival: White, female, younger, better educated and married patients, patients with higher income and living in urban areas, patients with rectosigmoid junction and rectal cancer, undergoing cancer-directed surgery, having well/moderately differentiated, and N0 tumors (p<0.05 for all covariates). Discrepancies in overall survival based on race did not change significantly over time; however, there was a significant decrease of cancer-specific survival discrepancies over time between White and Black patients with a hazard ratio of 0.995 (95 % confidence interval 0.991–1.000) per year (p=0.03). Conclusion A clinically relevant overall survival increase was found from 1988 to 2008 in this population-based analysis for both White and Black patients with metastatic colorectal cancer. Although both White and Black patients benefitted from this improvement, a slight discrepancy between the two groups remained.

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The genetic variability of milk protein genes may influence the nutritive value or processing and functional properties of the milk. While numerous protein variants are known in ruminants, knowledge about milk protein variability in horses is still limited. Mare's milk is, however, produced for human consumption in many countries. Beta-lactoglobulin belonging to the protein family of lipocalins, which are known as common food- and airborne allergens, is a major whey protein. It is absent from human milk and thus a key agent in provoking cow's milk protein allergy. Mare's milk is, however, usually better tolerated by most affected people. Several functions of β-lactoglobulin have been discussed, but its ultimate physiological role remains unclear. In the current study, the open reading frames of the two equine β-lactoglobulin paralogues LGB1 and LGB2 were re-sequenced in 249 horses belonging to 14 different breeds in order to predict the existence of protein variants at the DNA-level. Thereby, only a single signal peptide variant of LGB1, but 10 different putative protein variants of LGB2 were identified. In horses, both genes are expressed and in such this is a striking previously unknown difference in genetic variability between the two genes. It can be assumed that LGB1 is the ancestral paralogue, which has an essential function causing a high selection pressure. As horses have very low milk fat content this unknown function might well be related to vitamin-uptake. Further studies are, however, needed, to elucidate the properties of the different gene products.

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The genomic era brought by recent advances in the next-generation sequencing technology makes the genome-wide scans of natural selection a reality. Currently, almost all the statistical tests and analytical methods for identifying genes under selection was performed on the individual gene basis. Although these methods have the power of identifying gene subject to strong selection, they have limited power in discovering genes targeted by moderate or weak selection forces, which are crucial for understanding the molecular mechanisms of complex phenotypes and diseases. Recent availability and rapid completeness of many gene network and protein-protein interaction databases accompanying the genomic era open the avenues of exploring the possibility of enhancing the power of discovering genes under natural selection. The aim of the thesis is to explore and develop normal mixture model based methods for leveraging gene network information to enhance the power of natural selection target gene discovery. The results show that the developed statistical method, which combines the posterior log odds of the standard normal mixture model and the Guilt-By-Association score of the gene network in a naïve Bayes framework, has the power to discover moderate/weak selection gene which bridges the genes under strong selection and it helps our understanding the biology under complex diseases and related natural selection phenotypes.^

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The biggest problem when analyzing the brain is that its synaptic connections are extremely complex. Generally, the billions of neurons making up the brain exchange information through two types of highly specialized structures: chemical synapses (the vast majority) and so-called gap junctions (a substrate of one class of electrical synapse). Here we are interested in exploring the three-dimensional spatial distribution of chemical synapses in the cerebral cortex. Recent research has showed that the three-dimensional spatial distribution of synapses in layer III of the neocortex can be modeled by a random sequential adsorption (RSA) point process, i.e., synapses are distributed in space almost randomly, with the only constraint that they cannot overlap. In this study we hypothesize that RSA processes can also explain the distribution of synapses in all cortical layers. We also investigate whether there are differences in both the synaptic density and spatial distribution of synapses between layers. Using combined focused ion beam milling and scanning electron microscopy (FIB/SEM), we obtained three-dimensional samples from the six layers of the rat somatosensory cortex and identified and reconstructed the synaptic junctions. A total volume of tissue of approximately 4500μm3 and around 4000 synapses from three different animals were analyzed. Different samples, layers and/or animals were aggregated and compared using RSA replicated spatial point processes. The results showed no significant differences in the synaptic distribution across the different rats used in the study. We found that RSA processes described the spatial distribution of synapses in all samples of each layer. We also found that the synaptic distribution in layers II to VI conforms to a common underlying RSA process with different densities per layer. Interestingly, the results showed that synapses in layer I had a slightly different spatial distribution from the other layers.

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We introduce a method of functionally classifying genes by using gene expression data from DNA microarray hybridization experiments. The method is based on the theory of support vector machines (SVMs). SVMs are considered a supervised computer learning method because they exploit prior knowledge of gene function to identify unknown genes of similar function from expression data. SVMs avoid several problems associated with unsupervised clustering methods, such as hierarchical clustering and self-organizing maps. SVMs have many mathematical features that make them attractive for gene expression analysis, including their flexibility in choosing a similarity function, sparseness of solution when dealing with large data sets, the ability to handle large feature spaces, and the ability to identify outliers. We test several SVMs that use different similarity metrics, as well as some other supervised learning methods, and find that the SVMs best identify sets of genes with a common function using expression data. Finally, we use SVMs to predict functional roles for uncharacterized yeast ORFs based on their expression data.

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Computer models were used to examine whether and under what conditions the multimeric protein complex is inhibited by high concentrations of one of its components—an effect analogous to the prozone phenomenon in precipitin tests. A series of idealized simple “ball-and-stick” structures representing small oligomeric complexes of protein molecules formed by reversible binding reactions were analyzed to determine the binding steps leading to each structure. The equilibrium state of each system was then determined over a range of starting concentrations and Kds and the steady-state concentration of structurally complete oligomer calculated for each situation. A strong inhibitory effect at high concentrations was shown by any protein molecule forming a bridge between two or more separable parts of the complex. By contrast, proteins linked to the outside of the complex by a single bond showed no inhibition whatsoever at any concentration. Nonbridging, multivalent proteins in the body of the complex could show an inhibitory effect or not depending on the structure of the complex and the strength of its bonds. On the basis of this study, we suggest that the prozone phenomenon will occur widely in living cells and that it could be a crucial factor in the regulation of protein complex formation.