72 resultados para Disease evolution model


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This study examined the utility of a stress/coping model in explaining adaptation in two groups of people at-risk for Huntington's Disease (HD): those who have not approached genetic testing services (non-testees) and those who have engaged a testing service (testees). The aims were (1) to compare testees and non-testees on stress/coping variables, (2) to examine relations between adjustment and the stress/coping predictors in the two groups, and (3) to examine relations between the stress/coping variables and testees' satisfaction with their first counselling session. Participants were 44 testees and 40 non-testees who completed questionnaires which measured the stress/coping variables: adjustment (global distress, depression, health anxiety, social and dyadic adjustment), genetic testing concerns, testing context (HD contact, experience, knowledge), appraisal (control, threat, self-efficacy), coping strategies (avoidance, self-blame, wishful thinking, seeking support, problem solving), social support and locus of control. Testees also completed a genetic counselling session satisfaction scale. As expected, non-testees reported lower self-efficacy and control appraisals, higher threat and passive avoidant coping than testees. Overall, results supported the hypothesis that within each group poorer adjustment would be related to higher genetic testing concerns, contact with HD, threat appraisals, passive avoidant coping and external locus of control, and lower levels of positive experiences with HD, social support, internal locus of control, self-efficacy, control appraisals, problem solving, emotional approach and seeking social support coping. Session satisfaction scores were positively correlated with dyadic adjustment, problem solving and positive experience with HD, and inversely related to testing concerns, and threat and control appraisals. Findings support the utility of the stress/coping model in explaining adaptation in people who have decided not to seek genetic testing for HD and those who have decided to engage a genetic testing service.

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The development of resistance to sulfadoxine-pyrimethamine by Plasmodium parasites is a major problem for the effective treatment of malaria, especially P. falciparum malaria. Although the molecular basis for parasite resistance is known, the factors promoting the development and transmission of these resistant parasites are less clear. This paper reports the results of a quantitative comparison of factors previously hypothesized as important for the development of drug resistance, drug dosage, time of treatment, and drug elimination half-life, with an in-host dynamics model of P. falciparum malaria in a malaria-naive host. The results indicate that the development of drug resistance can be categorized into three stages. The first is the selection of existing parasites with genetic mutations in the dihydrofolate reductase or dihydropteroate synthetase gene. This selection is driven by the long half-life of the sulfadoxine-pyrimethamine combination. The second stage involves the selection of parasites with allelic types of higher resistance within the host during an infection. The timing of treatment relative to initiation of a specific anti-P. falciparum EMP1 immune response is an important factor during this stage, as is the treatment dosage. During the third stage, clinical treatment failure becomes prevalent as the parasites develop sufficient resistance mutations to survive therapeutic doses of the drug combination. Therefore, the model output reaffirms the importance of correct treatment of confirmed malaria cases in slowing the development of parasite resistance to sulfadoxine-pyrimethamine.

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We have previously shown that complement factor 5a(C5a) plays a role in the pathogenesis of 2,4,6-trinitrobenzene sulfonic acid (TNBS)-induced colitis in rats by using the selective, orally active C5a antagonist AcF-[OP(D-Cha) WR]. This study tested the efficacy and potency of a new C5a antagonist, hydrocinnamate (HC)-[OP(D-Cha) WR], which has limited intestinal lumenal metabolism, in this model of colitis. Analogs of AcF-[OP(D-Cha) WR] were examined for their susceptibility to alimentary metabolism in the rat using intestinal mucosal washings. One metabolically stable analog, HC-[OP(D-Cha)WR], was then evaluated pharmacokinetically and investigated at a range of doses (0.03 - 10 mg/kg/ day p.o.) in the 8-day rat TNBS- colitis model, against the comparator drug AcF-[OP(D-Cha) WR]. Using various amino acid substitutions, it was determined that the AcF moiety of AcF-[OP(D-Cha) WR] was responsible for the metabolic instability of the compound in intestinal mucosal washings. The analog HC-[OP( D-Cha) WR], equiactive in vitro to AcF-[OP(D-Cha) WR], was resistant to intestinal metabolism, but it displayed similar oral bioavailability to AcF-[OP(D-Cha) WR]. However, in the rat TNBS- colitis model, HC-[OP(D-Cha) WR] was effective at reducing mortality, colon edema, colon macroscopic scores, and increasing food consumption and body weights, at 10- to 30- fold lower oral doses than AcF-[OP( D-Cha) WR]. These studies suggest that resistance to intestinal metabolism by HC-[OP(D-Cha) WR] may result in increased local concentrations of the drug in the colon, thus affording efficacy with markedly lower oral doses than AcF-[OP(D-Cha) WR] against TNBS-colitis. This large increase in potency and high efficacy of this compound makes it a potential candidate for clinical development against intestinal diseases such as inflammatory bowel disease.

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Caveolae are an abundant feature of many animal cells. However, the exact function of caveolae remains unclear. We have used the zebrafish, Danio rerio, as a system to understand caveolae function focusing on the muscle-specific caveolar protein, caveolin-3 (Cav3). We have identified caveolin-1 (alpha and beta), caveolin-2 and Cav3 in the zebrafish. Zebrafish Cav3 has 72% identity to human CAV3, and the amino acids altered in human muscle diseases are conserved in the zebrafish protein. During embryonic development, cav3 expression is apparent by early segmentation stages in the first differentiating muscle precursors, the adaxial cells and slightly later in the notochord. cav3 expression appears in the somites during mid-segmentation stages and then later in the pectoral fins and facial muscles. Cav3 and caveolae are located along the entire sarcolemma of late stage embryonic muscle fibers, whereas beta-dystroglycan is restricted to the muscle fiber ends. Down-regulation of Cav3 expression causes gross muscle abnormalities and uncoordinated movement. Ultrastructural analysis of isolated muscle fibers reveals defects in myoblast fusion and disorganized myofibril and membrane systems. Expression of the zebrafish equivalent to a human muscular dystrophy mutant, CAV3P104L, causes severe disruption of muscle differentiation. In addition, knockdown of Cav3 resulted in a dramatic up-regulation of eng1a expression resulting in an increase in the number of muscle pioneer-like cells adjacent to the notochord. These studies provide new insights into the role of Cav3 in muscle development and demonstrate its requirement for correct intracellular organization and myoblast fusion.

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Reliable, comparable information about the main causes of disease and injury in populations, and how these are changing, is a critical input for debates about priorities in the health sector. Traditional sources of information about the descriptive epidemiology of diseases, injuries and risk factors are generally incomplete, fragmented and of uncertain reliability and comparability. Lack of a standardized measurement framework to permit comparisons across diseases and injuries, as well as risk factors, and failure to systematically evaluate data quality have impeded comparative analyses of the true public health importance of various conditions and risk factors. As a consequence the impact of major conditions and hazards on population health has been poorly appreciated, often leading to a lack of public health investment. Global disease and risk factor quantification improved dramatically in the early 1990s with the completion of the first Global Burden of Disease Study. For the first time, the comparative importance of over 100 diseases and injuries, and ten major risk factors, for global and regional health status could be assessed using a common metric (Disability-Adjusted Life Years) which simultaneously accounted for both premature mortality and the prevalence, duration and severity of the non-fatal consequences of disease and injury. As a consequence, mental health conditions and injuries, for which non-fatal outcomes are of particular significance, were identified as being among the leading causes of disease/injury burden worldwide, with clear implications for policy, particularly prevention. A major achievement of the Study was the complete global descriptive epidemiology, including incidence, prevalence and mortality, by age, sex and Region, of over 100 diseases and injuries. National applications, further methodological research and an increase in data availability have led to improved national, regional and global estimates for 2000, but substantial uncertainty around the disease burden caused by major conditions, including, HIV, remains. The rapid implementation of cost-effective data collection systems in developing countries is a key priority if global public policy to promote health is to be more effectively informed.

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Topological measures of large-scale complex networks are applied to a specific artificial regulatory network model created through a whole genome duplication and divergence mechanism. This class of networks share topological features with natural transcriptional regulatory networks. Specifically, these networks display scale-free and small-world topology and possess subgraph distributions similar to those of natural networks. Thus, the topologies inherent in natural networks may be in part due to their method of creation rather than being exclusively shaped by subsequent evolution under selection. The evolvability of the dynamics of these networks is also examined by evolving networks in simulation to obtain three simple types of output dynamics. The networks obtained from this process show a wide variety of topologies and numbers of genes indicating that it is relatively easy to evolve these classes of dynamics in this model. (c) 2006 Elsevier Ireland Ltd. All rights reserved.

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Model transformations are an integral part of model-driven development. Incremental updates are a key execution scenario for transformations in model-based systems, and are especially important for the evolution of such systems. This paper presents a strategy for the incremental maintenance of declarative, rule-based transformation executions. The strategy involves recording dependencies of the transformation execution on information from source models and from the transformation definition. Changes to the source models or the transformation itself can then be directly mapped to their effects on transformation execution, allowing changes to target models to be computed efficiently. This particular approach has many benefits. It supports changes to both source models and transformation definitions, it can be applied to incomplete transformation executions, and a priori knowledge of volatility can be used to further increase the efficiency of change propagation.

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In this paper, we present a framework for pattern-based model evolution approaches in the MDA context. In the framework, users define patterns using a pattern modeling language that is designed to describe software design patterns, and they can use the patterns as rules to evolve their model. In the framework, design model evolution takes place via two steps. The first step is a binding process of selecting a pattern and defining where and how to apply the pattern in the model. The second step is an automatic model transformation that actually evolves the model according to the binding information and the pattern rule. The pattern modeling language is defined in terms of a MOF-based role metamodel, and implemented using an existing modeling framework, EMF, and incorporated as a plugin to the Eclipse modeling environment. The model evolution process is also implemented as an Eclipse plugin. With these two plugins, we provide an integrated framework where defining and validating patterns, and model evolution based on patterns can take place in a single modeling environment.

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We investigate here a modification of the discrete random pore model [Bhatia SK, Vartak BJ, Carbon 1996;34:1383], by including an additional rate constant which takes into account the different reactivity of the initial pore surface having attached functional groups and hydrogens, relative to the subsequently exposed surface. It is observed that the relative initial reactivity has a significant effect on the conversion and structural evolution, underscoring the importance of initial surface chemistry. The model is tested against experimental data on chemically controlled char oxidation and steam gasification at various temperatures. It is seen that the variations of the reaction rate and surface area with conversion are better represented by the present approach than earlier random pore models. The results clearly indicate the improvement of model predictions in the low conversion region, where the effect of the initially attached functional groups and hydrogens is more significant, particularly for char oxidation. It is also seen that, for the data examined, the initial surface chemistry is less important for steam gasification as compared to the oxidation reaction. Further development of the approach must also incorporate the dynamics of surface complexation, which is not considered here.

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A simplified model for anisotropic mantle convection based on a novel class of rheologies, originally developed for folding instabilities in multilayered rock (MUHLHAUS et al., 2002), is extended ¨ through the introduction of a thermal anisotropy dependent on the local layering. To examine the effect of the thermal anisotropy on the evolution of mantle material, a parallel implementation of this model was undertaken using the Escript modelling toolkit and the Finley finite-element computational kernel (DAVIES et al., 2004). For the cases studied, there appears too little if any effect. For comparative purposes, the effects of anisotropic shear viscosity and the introduced thermal anisotropy are also presented. These results contribute to the characterization of viscous anisotropic mantle convection subject to variation in thermal conductivities and shear viscosities.

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A virulent strain of Wolbachia has recently been identified in Drosophila that drastically reduces adult lifespan. It has been proposed that this phenotype might be introduced into insect disease vector populations to reduce pathogen transmission. Here we model the requirements for spread of such an agent and the associated reduction in disease transmission. First, a simulation of mosquito population age structure was used to describe the age distribution of mosquitoes transmitting dengue virus. Second, given varying levels of cytoplasmic incompatibility and fecundity effect, the maximum possible longevity reduction that would allow Wolbachia to invade was obtained. Finally, the two models were combined to estimate the reduction in disease transmission according to different introduction frequencies. With strong CI and limited effect of fecundity, an introduction of Wolbachia with an initial frequency of 0.4 could result in a 60–80% reduction of transmitting mosquitoes. Greater reductions are possible at higher initial release rates.