982 resultados para certificate signatures


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Here we reported the fatty-acids and their δ 13C values in seep carbonates collected from Green Canyon lease block 185 (GC 185; Sample GC-F) at upper continental slope (water depth: ∼540 m), and Alaminos Canyon lease block 645 (GC 645; Sample AC-E) at lower continental slope (water depth: ∼2200 m) of the Gulf of Mexico. More than thirty kinds of fatty acids were detected in both samples. These fatty acids are maximized at C16. There is a clear even-over-odd carbon number predominance in carbon number range. The fatty acids are mainly composed of n-fatty acids, iso-/anteiso-fatty acids and terminally branched odd-numbered fatty acids (iso/anteiso). The low δ 13C values (−39.99‰ to.32.36‰) of n-C12:0, n-C13:0, i-C14:0and n-C14:0 suggest that they may relate to the chemosynthetic communities at seep sites. The unsaturated fatty acids n-C18:2 and C18:1Δ9 have the same δ 13C values, they may originate from theBeggiatoa/Thioploca. Unlike other fatty acids, the terminally branched fatty acids (iso/anteiso) show lowerδ 13C values (as low as −63.95‰) suggesting a possible relationship to sulfate reducing bacteria, which is common during anaerobic oxidation of methane at seep sites.

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Interpretation of high-resolution two-dimensional (2D) and three-dimensional (3D) seismic data collected in the Qiongdongnan Basin, South China Sea reveals the presence of polygonal faults, pockmarks, gas chimneys and slope failure in strata of Pliocene and younger age. The gas chimneys are characterized by low-amplitude reflections, acoustic turbidity and low P-wave velocity indicating fluid expulsion pathways. Coherence time slices show that the polygonal faults are restricted to sediments with moderate-amplitude, continuous reflections. Gas hydrates are identified in seismic data by the presence of bottom simulating reflectors (BSRs), which have high amplitude, reverse polarity and are subparallel to seafloor. Mud diapirism and mounded structures have variable geometry and a great diversity regarding the origin of the fluid and the parent beds. The gas chimneys, mud diapirism, polygonal faults and a seismic facies-change facilitate the upward migration of thermogenic fluids from underlying sediments. Fluids can be temporarily trapped below the gas hydrate stability zone, but fluid advection may cause gas hydrate dissociation and affect the thickness of gas hydrate zone. The fluid accumulation leads to the generation of excess pore fluids that release along faults, forming pockmarks and mud volcanoes on the seafloor. These features are indicators of fluid flow in a tectonically-quiescent sequence, Qiongdongnan Basin. Geofluids (2010) 10, 351-368.

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The Leaving Certificate (LC) is the national, standardised state examination in Ireland necessary for entry to third level education – this presents a massive, raw corpus of data with the potential to yield invaluable insight into the phenomena of learner interlanguage. With samples of official LC Spanish examination data, this project has compiled a digitised corpus of learner Spanish comprised of the written and oral production of 100 candidates. This corpus was then analysed using a specific investigative corpus technique, Computer-aided Error Analysis (CEA, Dagneaux et al, 1998). CEA is a powerful apparatus in that it greatly facilitates the quantification and analysis of a large learner corpus in digital format. The corpus was both compiled and analysed with the use of UAM Corpus Tool (O’Donnell 2013). This Tool allows for the recording of candidate-specific variables such as grade, examination level, task type and gender, therefore allowing for critical analysis of the corpus as one unit, as separate written and oral sub corpora and also of performance per task, level and gender. This is an interdisciplinary work combining aspects of Applied Linguistics, Learner Corpus Research and Foreign Language (FL) Learning. Beginning with a review of the context of FL learning in Ireland and Europe, I go on to discuss the disciplinary context and theoretical framework for this work and outline the methodology applied. I then perform detailed quantitative and qualitative analyses before going on to combine all research findings outlining principal conclusions. This investigation does not make a priori assumptions about the data set, the LC Spanish examination, the context of FLs or of any aspect of learner competence. It undertakes to provide the linguistic research community and the domain of Spanish language learning and pedagogy in Ireland with an empirical, descriptive profile of real learner performance, characterising learner difficulty.

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BACKGROUND: Mutations in the TP53 gene are extremely common and occur very early in the progression of serous ovarian cancers. Gene expression patterns that relate to mutational status may provide insight into the etiology and biology of the disease. METHODS: The TP53 coding region was sequenced in 89 frozen serous ovarian cancers, 40 early stage (I/II) and 49 advanced stage (III/IV). Affymetrix U133A expression data was used to define gene expression patterns by mutation, type of mutation, and cancer stage. RESULTS: Missense or chain terminating (null) mutations in TP53 were found in 59/89 (66%) ovarian cancers. Early stage cancers had a significantly higher rate of null mutations than late stage disease (38% vs. 8%, p < 0.03). In advanced stage cases, mutations were more prevalent in short term survivors than long term survivors (81% vs. 30%, p = 0.0004). Gene expression patterns had a robust ability to predict TP53 status within training data. By using early versus late stage disease for out of sample predictions, the signature derived from early stage cancers could accurately (86%) predict mutation status of late stage cancers. CONCLUSIONS: This represents the first attempt to define a genomic signature of TP53 mutation in ovarian cancer. Patterns of gene expression characteristic of TP53 mutation could be discerned and included several genes that are known p53 targets or have been described in the context of expression signatures of TP53 mutation in breast cancer.

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A steady increase in knowledge of the molecular and antigenic structure of the gp120 and gp41 HIV-1 envelope glycoproteins (Env) is yielding important new insights for vaccine design, but it has been difficult to translate this information to an immunogen that elicits broadly neutralizing antibodies. To help bridge this gap, we used phylogenetically corrected statistical methods to identify amino acid signature patterns in Envs derived from people who have made potently neutralizing antibodies, with the hypothesis that these Envs may share common features that would be useful for incorporation in a vaccine immunogen. Before attempting this, essentially as a control, we explored the utility of our computational methods for defining signatures of complex neutralization phenotypes by analyzing Env sequences from 251 clonal viruses that were differentially sensitive to neutralization by the well-characterized gp120-specific monoclonal antibody, b12. We identified ten b12-neutralization signatures, including seven either in the b12-binding surface of gp120 or in the V2 region of gp120 that have been previously shown to impact b12 sensitivity. A simple algorithm based on the b12 signature pattern was predictive of b12 sensitivity/resistance in an additional blinded panel of 57 viruses. Upon obtaining these reassuring outcomes, we went on to apply these same computational methods to define signature patterns in Env from HIV-1 infected individuals who had potent, broadly neutralizing responses. We analyzed a checkerboard-style neutralization dataset with sera from 69 HIV-1-infected individuals tested against a panel of 25 different Envs. Distinct clusters of sera with high and low neutralization potencies were identified. Six signature positions in Env sequences obtained from the 69 samples were found to be strongly associated with either the high or low potency responses. Five sites were in the CD4-induced coreceptor binding site of gp120, suggesting an important role for this region in the elicitation of broadly neutralizing antibody responses against HIV-1.

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BACKGROUND: Previous work has demonstrated the potential for peripheral blood (PB) gene expression profiling for the detection of disease or environmental exposures. METHODS AND FINDINGS: We have sought to determine the impact of several variables on the PB gene expression profile of an environmental exposure, ionizing radiation, and to determine the specificity of the PB signature of radiation versus other genotoxic stresses. Neither genotype differences nor the time of PB sampling caused any lessening of the accuracy of PB signatures to predict radiation exposure, but sex difference did influence the accuracy of the prediction of radiation exposure at the lowest level (50 cGy). A PB signature of sepsis was also generated and both the PB signature of radiation and the PB signature of sepsis were found to be 100% specific at distinguishing irradiated from septic animals. We also identified human PB signatures of radiation exposure and chemotherapy treatment which distinguished irradiated patients and chemotherapy-treated individuals within a heterogeneous population with accuracies of 90% and 81%, respectively. CONCLUSIONS: We conclude that PB gene expression profiles can be identified in mice and humans that are accurate in predicting medical conditions, are specific to each condition and remain highly accurate over time.

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BACKGROUND: Genetic association studies are conducted to discover genetic loci that contribute to an inherited trait, identify the variants behind these associations and ascertain their functional role in determining the phenotype. To date, functional annotations of the genetic variants have rarely played more than an indirect role in assessing evidence for association. Here, we demonstrate how these data can be systematically integrated into an association study's analysis plan. RESULTS: We developed a Bayesian statistical model for the prior probability of phenotype-genotype association that incorporates data from past association studies and publicly available functional annotation data regarding the susceptibility variants under study. The model takes the form of a binary regression of association status on a set of annotation variables whose coefficients were estimated through an analysis of associated SNPs in the GWAS Catalog (GC). The functional predictors examined included measures that have been demonstrated to correlate with the association status of SNPs in the GC and some whose utility in this regard is speculative: summaries of the UCSC Human Genome Browser ENCODE super-track data, dbSNP function class, sequence conservation summaries, proximity to genomic variants in the Database of Genomic Variants and known regulatory elements in the Open Regulatory Annotation database, PolyPhen-2 probabilities and RegulomeDB categories. Because we expected that only a fraction of the annotations would contribute to predicting association, we employed a penalized likelihood method to reduce the impact of non-informative predictors and evaluated the model's ability to predict GC SNPs not used to construct the model. We show that the functional data alone are predictive of a SNP's presence in the GC. Further, using data from a genome-wide study of ovarian cancer, we demonstrate that their use as prior data when testing for association is practical at the genome-wide scale and improves power to detect associations. CONCLUSIONS: We show how diverse functional annotations can be efficiently combined to create 'functional signatures' that predict the a priori odds of a variant's association to a trait and how these signatures can be integrated into a standard genome-wide-scale association analysis, resulting in improved power to detect truly associated variants.

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Objectives: One third of the world population is considered latently infected with Mycobacterium tuberculosis(LTBI) and sterilizing this reservoir of bacteria that may reactivate is required for tuberculosis (TB) elimination. Thegroup of individuals with LTBI is heterogeneous with some of them being more at risk to develop TB disease thanothers. Improved diagnosis of subjects with LTBI is needed, allowing to differentiate subjects with LTBI from thosewith active TB, and to select among LTBI subjects those who are more at risk to develop active TB. We havecharacterized at the cellular level both the quantitative and qualitative T cell responses to different mycobacterialantigens in selected populations of infected subjects in order to identify new biomarkers that could help to identify M.tuberculosis-infected subjects and to stratify them in risk groups for reactivation of the infection.Methods: Lymphoblast frequencies and cytokine production (IFN-γ, TNF-α, IL-2) among CD4+ and CD8+ T cellswere analyzed by flow cytometry after in vitro stimulation with the latency antigen heparin-binding haemagglutinin(HBHA) or early-secreted antigen Target-6 (ESAT-6) of peripheral blood mononuclear cells from clinically wellcharacterized M. tuberculosis-infected humans (28 LTBI, 22 TB disease,12 controls). The LTBI group definedaccording to the Center for Disease Control guidelines was subdivided into QuantiFERON-TB Gold in-Tube (QFT)positive and negative subgroups.Results: Similar to TB patients, QFT+ LTBI subjects had higher proportions of HBHA-induced TNF-αsingle+ CD4+lymphocytes than QFT- LTBI subjects (p<0.05). Compared to LTBI subjects, TB patients had higher frequencies ofESAT-6-induced CD8+ lymphoblasts (p<0.001), higher proportions of ESAT-6-induced IFN-γ+TNF-α+ CD4+ Tlymphocytes (p<0.05), and lower proportions of HBHA-induced IFN-γ+TNF-α+IL-2+ (p<0.05) CD4+ T lymphocytes.Conclusions: These data provide new biomarkers to discriminate active TB from LTBI, and more interestingly,help to identify LTBI subjects with increased likelihood to develop TB disease.