66 resultados para pre-symptomatic testing
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El objetivo del proyecto es el desarrollo de una herramienta de trabajo para un departamento de Calidad. A través de ella, se deben poder ejecutar unos test automatizados sobre unas funcionalidades que tiene la aplicación Logic Class: el Cálculo de Nómina y Seguros Sociales.
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In this paper we give new characterization of the classical Morrey space. Complementary global Morrey-type spaces are introduced. It is proved that for particular values of parameters these spaces give new pre-dual space of the classical Morrey space. We also show that our new pre-dual space of the Morrey space coincides with known pre-dual spaces.
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L´artroplastia total de cadera (ATC) es un dels procediments ortopédics més exitosos que es realitzen avui en dia. En aquest estudi es valora l´evolució de l´estat funcional i de l´estat de salut abans, al mes i ½ i als 3 mesos de la cirurgia. Després de l´ATC s´observa una millora de la condició funcional i de l´estat de salut. L´obtenció d´ecuacions de regresió lineal permitiria aproximar l´estat previ a la cirugia, i el grau de millora esperable per a l´estat de salut als 3 mesos.
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This article discusses the lessons learned from developing and delivering the Vocational Management Training for the European Tourism Industry (VocMat) online training programme, which was aimed at providing flexible, online distance learning for the European tourism industry. The programme was designed to address managers ‘need for flexible, senior management level training which they could access at a time and place which fitted in with their working and non-work commitments. The authors present two main approaches to using the Virtual Learning Environment, the feedback from the participants, and the implications of online Technology in extending tourism training opportunities
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In standard multivariate statistical analysis common hypotheses of interest concern changes in mean vectors and subvectors. In compositional data analysis it is now well established that compositional change is most readily described in terms of the simplicial operation of perturbation and that subcompositions replace the marginal concept of subvectors. To motivate the statistical developments of this paper we present two challenging compositional problems from food production processes.Against this background the relevance of perturbations and subcompositions can beclearly seen. Moreover we can identify a number of hypotheses of interest involvingthe specification of particular perturbations or differences between perturbations and also hypotheses of subcompositional stability. We identify the two problems as being the counterpart of the analysis of paired comparison or split plot experiments and of separate sample comparative experiments in the jargon of standard multivariate analysis. We then develop appropriate estimation and testing procedures for a complete lattice of relevant compositional hypotheses
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Durante los procedimientos endovasculares en el ictus isquémico la información per-procedimiento del daño cerebral ayudaría a tomar decisiones sobre intentar la recanalización arterial. Métodos Se estudiaron parámetros gasométricos de sangre extraída durante los procedimientos endovasculares de recanalización. Se obtuvieron muestras proximal y distal a la oclusión. Un estudio gasométrico se realizo inmediatamente. Resultados El estudio mostró diferencias significativas entre las muestras pre-oclusión y postoclusión en la presión parcial de oxígeno (PaO2Pre78,9±16.3mmHgVs73.4±14.9 mmHg,p&0,001). Una curva ROC determinó que una Post-PaO2&70 mmHg predice mejoría clínica. Los pacientes con post-PaO2&70mmHg tuvieron mejor autonomía (medianaMRS:3Vs.6, p=0,024). En el análisis multivariante el único predictor independiente de mejoría clínica fue la Post-PaO2&70(OR:5,21IC95%:1.38-67.24,p=0,013). Conclusión Es posible la obtención de muestras de sangre del tejido lesionado distal a la oclusión. La información puede ser utilizada para predecir evolución clínica y en las decisiones durante el procedimiento.
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Eating disorders (EDs) are complex psychiatric diseases that include anorexia nervosa and bulimia nervosa, and have higher than 50% heritability. Previous studies have found association of BDNF and NTRK2 to ED, while animal models suggest that other neurotrophin genes might also be involved in eating behavior. We have performed a family-based association study with 151 TagSNPs covering 10 neurotrophin signaling genes: NGFB, BDNF, NTRK1, NGFR/p75, NTF4/5, NTRK2, NTF3, NTRK3, CNTF and CNTFR in 371 ED trios of Spanish, French and German origin. Besides several nominal associations, we found a strong significant association after correcting for multiple testing (P = 1.04 × 10−4) between ED and rs7180942, located in the NTRK3 gene, which followed an overdominant model of inheritance. Interestingly, HapMap unrelated individuals carrying the rs7180942 risk genotypes for ED showed higher levels of expression of NTRK3 in lymphoblastoid cell lines. Furthermore, higher expression of the orthologous murine Ntrk3 gene was also detected in the hypothalamus of the anx/anx mouse model of anorexia. Finally, variants in NGFB gene appear to modify the risk conferred by the NTRK3 rs7180942 risk genotypes (P = 4.0 × 10−5) showing a synergistic epistatic interaction. The reported data, in addition to the previous reported findings for BDNF and NTRK2, point neurotrophin signaling genes as key regulators of eating behavior and their altered cross-regulation as susceptibility factors for EDs.
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The functional interactions between the endogenous cannabinoid and opioid systems were evaluated in pre-proenkephalin-deficient mice. Antinociception induced in the tail-immersion test by acute Delta9-tetrahydrocannabinol was reduced in mutant mice, whereas no difference between genotypes was observed in the effects induced on body temperature, locomotion, or ring catalepsy. During a chronic treatment with Delta9-tetrahydrocannabinol, the development of tolerance to the analgesic responses induced by this compound was slower in mice lacking enkephalin. In addition, cannabinoid withdrawal syndrome, precipitated in Delta9-tetrahydrocannabinol-dependent mice by the injection of SR141716A, was significantly attenuated in mutant mice. These results indicate that the endogenous enkephalinergic system is involved in the antinociceptive responses of Delta9-tetrahydrocannabinol and participates in the expression of cannabinoid abstinence.
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Removal of introns during pre-mRNA splicing is a critical process in gene expression, and understanding its control at both single-gene and genomic levels is one of the great challenges in Biology. Splicing takes place in a dynamic, large ribonucleoprotein complex known as the spliceosome. Combining Genetics and Biochemistry, Saccharomyces cerevisiae provides insights into its mechanisms, including its regulation by RNA-protein interactions. Recent genome-wide analyses indicate that regulated splicing is broad and biologically relevant even in organisms with a relatively simple intronic structure, such as yeast. Furthermore, the possibility of coordination in splicing regulation at genomic level is becoming clear in this model organism. This should provide a valuable system to approach the complex problem of the role of regulated splicing in genomic expression.
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Background: Recent advances on high-throughput technologies have produced a vast amount of protein sequences, while the number of high-resolution structures has seen a limited increase. This has impelled the production of many strategies to built protein structures from its sequence, generating a considerable amount of alternative models. The selection of the closest model to the native conformation has thus become crucial for structure prediction. Several methods have been developed to score protein models by energies, knowledge-based potentials and combination of both.Results: Here, we present and demonstrate a theory to split the knowledge-based potentials in scoring terms biologically meaningful and to combine them in new scores to predict near-native structures. Our strategy allows circumventing the problem of defining the reference state. In this approach we give the proof for a simple and linear application that can be further improved by optimizing the combination of Zscores. Using the simplest composite score () we obtained predictions similar to state-of-the-art methods. Besides, our approach has the advantage of identifying the most relevant terms involved in the stability of the protein structure. Finally, we also use the composite Zscores to assess the conformation of models and to detect local errors.Conclusion: We have introduced a method to split knowledge-based potentials and to solve the problem of defining a reference state. The new scores have detected near-native structures as accurately as state-of-art methods and have been successful to identify wrongly modeled regions of many near-native conformations.
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Background and purpose: Individual rupture risk assessment of intracranial aneurysms is a major issue in the clinical management of asymptomatic aneurysms. Aneurysm rupture occurs when wall tension exceeds the strength limit of the wall tissue. At present, aneurysmal wall mechanics are poorly understood and thus, risk assessment involving mechanical properties is inexistent. Aneurysm computational hemodynamics studies make the assumption of rigid walls, an arguable simplification. We therefore aim to assess mechanical properties of ruptured and unruptured intracranial aneurysms in order to provide the foundation for future patient-specific aneurysmal risk assessment. This work also challenges some of the currently held hypotheses in computational flow hemodynamics research. Methods: A specific conservation protocol was applied to aneurysmal tissues following clipping and resection in order to preserve their mechanical properties. Sixteen intracranial aneurysms (11 female, 5 male) underwent mechanical uniaxial stress tests under physiological conditions, temperature, and saline isotonic solution. These represented 11 unruptured and 5 ruptured aneurysms. Stress/strain curves were then obtained for each sample, and a fitting algorithm was applied following a 3-parameter (C(10), C(01), C(11)) Mooney-Rivlin hyperelastic model. Each aneurysm was classified according to its biomechanical properties and (un)rupture status.Results: Tissue testing demonstrated three main tissue classes: Soft, Rigid, and Intermediate. All unruptured aneurysms presented a more Rigid tissue than ruptured or pre-ruptured aneurysms within each gender subgroup. Wall thickness was not correlated to aneurysmal status (ruptured/unruptured). An Intermediate subgroup of unruptured aneurysms with softer tissue characteristic was identified and correlated with multiple documented risk factors of rupture. Conclusion: There is a significant modification in biomechanical properties between ruptured aneurysm, presenting a soft tissue and unruptured aneurysms, presenting a rigid material. This finding strongly supports the idea that a biomechanical risk factor based assessment should be utilized in the to improve the therapeutic decision making.
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This paper discusses the role of deterministic components in the DGP and in the auxiliary regression model which underlies the implementation of the Fractional Dickey-Fuller (FDF) test for I(1) against I(d) processes with d ∈ [0, 1). This is an important test in many economic applications because I(d) processess with d & 1 are mean-reverting although, when 0.5 ≤ d & 1,, like I(1) processes, they are nonstationary. We show how simple is the implementation of the FDF in these situations, and argue that it has better properties than LM tests. A simple testing strategy entailing only asymptotically normally distributed tests is also proposed. Finally, an empirical application is provided where the FDF test allowing for deterministic components is used to test for long-memory in the per capita GDP of several OECD countries, an issue that has important consequences to discriminate between growth theories, and on which there is some controversy.
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This paper proposes a method to conduct inference in panel VAR models with cross unit interdependencies and time variations in the coefficients. The approach can be used to obtain multi-unit forecasts and leading indicators and to conduct policy analysis in a multiunit setups. The framework of analysis is Bayesian and MCMC methods are used to estimate the posterior distribution of the features of interest. The model is reparametrized to resemble an observable index model and specification searches are discussed. As an example, we construct leading indicators for inflation and GDP growth in the Euro area using G-7 information.
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Aquest projecte s'ha dut a terme amb el Grup de visió per computador del departamentd'Arquitectura i Tecnologia de Computadors (ATC) de la Universitat de Girona. Està enfocat a l'anàlisi d'imatges mèdiques, en concret s'analitzaran imatges de pròstata en relació a desenvolupaments que s'estan realitzant en el grup de visió esmentat. Els objectius fixats per aquest projecte són desenvolupar dos mòduls de processamentm d'imatges els quals afrontaran dos blocs important en el tractament d'imatges, aquests dos mòduls seran un pre-processat d'imatges, que constarà de tres filtres i un bloc de segmentació per tal de cercar la pròstata dintre de les imatges a tractar. En el projecte es treballarà amb el llenguatge de programació C++, concretament amb unes llibreries que es denominen ITK (Insight Toolkit ) i són open source enfocades al tractament d'imatges mèdiques. A part d'aquesta eina s'utilitzaran d'altres com les Qt que és una biblioteca d'eines per crear entorns gràfics
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It is common in econometric applications that several hypothesis tests arecarried out at the same time. The problem then becomes how to decide whichhypotheses to reject, accounting for the multitude of tests. In this paper,we suggest a stepwise multiple testing procedure which asymptoticallycontrols the familywise error rate at a desired level. Compared to relatedsingle-step methods, our procedure is more powerful in the sense that itoften will reject more false hypotheses. In addition, we advocate the useof studentization when it is feasible. Unlike some stepwise methods, ourmethod implicitly captures the joint dependence structure of the teststatistics, which results in increased ability to detect alternativehypotheses. We prove our method asymptotically controls the familywise errorrate under minimal assumptions. We present our methodology in the context ofcomparing several strategies to a common benchmark and deciding whichstrategies actually beat the benchmark. However, our ideas can easily beextended and/or modied to other contexts, such as making inference for theindividual regression coecients in a multiple regression framework. Somesimulation studies show the improvements of our methods over previous proposals. We also provide an application to a set of real data.