10 resultados para GROUP-4

em CentAUR: Central Archive University of Reading - UK


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Background: Insulin sensitivity (Si) is improved by weight loss and exercise, but the effects of the replacement of saturated fatty acids (SFAs) with monounsaturated fatty acids (MUFAs) or carbohydrates of high glycemic index (HGI) or low glycemic index (LGI) are uncertain. Objective: We conducted a dietary intervention trial to study these effects in participants at risk of developing metabolic syndrome. Design: We conducted a 5-center, parallel design, randomized controlled trial [RISCK (Reading, Imperial, Surrey, Cambridge, and Kings)]. The primary and secondary outcomes were changes in Si (measured by using an intravenous glucose tolerance test) and cardiovascular risk factors. Measurements were made after 4 wk of a high-SFA and HGI (HS/HGI) diet and after a 24-wk intervention with HS/HGI (reference), high-MUFA and HGI (HM/HGI), HM and LGI (HM/LGI), low-fat and HGI (LF/HGI), and LF and LGI (LF/LGI) diets. Results: We analyzed data for 548 of 720 participants who were randomly assigned to treatment. The median Si was 2.7 × 10−4 mL · μU−1 · min−1 (interquartile range: 2.0, 4.2 × 10−4 mL · μU−1 · min−1), and unadjusted mean percentage changes (95% CIs) after 24 wk treatment (P = 0.13) were as follows: for the HS/HGI group, −4% (−12.7%, 5.3%); for the HM/HGI group, 2.1% (−5.8%, 10.7%); for the HM/LGI group, −3.5% (−10.6%, 4.3%); for the LF/HGI group, −8.6% (−15.4%, −1.1%); and for the LF/LGI group, 9.9% (2.4%, 18.0%). Total cholesterol (TC), LDL cholesterol, and apolipoprotein B concentrations decreased with SFA reduction. Decreases in TC and LDL-cholesterol concentrations were greater with LGI. Fat reduction lowered HDL cholesterol and apolipoprotein A1 and B concentrations. Conclusions: This study did not support the hypothesis that isoenergetic replacement of SFAs with MUFAs or carbohydrates has a favorable effect on Si. Lowering GI enhanced reductions in TC and LDL-cholesterol concentrations in subjects, with tentative evidence of improvements in Si in the LF-treatment group. This trial was registered at clinicaltrials.gov as ISRCTN29111298.

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1. Nicotine has been implicated as a causative factor in the intrauterine growth retardation associated with smoking in pregnancy. A study was set up to ascertain the effect of nicotine on fetal growth and whether this could be related to the actions of this drug on maternal adipose tissue metabolism. 2. Sprague-Dawley rats were mated and assigned to control and nicotine groups, the latter receiving nicotine in the drinking-water throughout pregnancy. Animals were weighed at regular intervals and killed on day 20 of pregnancy. Rates of maternal adipose tissue lipolysis and lipogenesis were measured. Fetal and placental weights were recorded and analysis of fetal body water, fat, protein and DNA carried out. 3. Weight gains of mothers in the nicotine group were less in the 1st and 2nd weeks of pregnancy, but similar to controls in the 3rd week. Fetal body-weights, DNA, protein and percentage water contents were similar in both groups. Mean fetal body fat (g/kg) was significantly higher in the nicotine group (96.2 (SE 5.1)) compared with controls (72.0 (SE 2.9)). Rates of maternal lipolysis were also higher in the nicotine group. 4. The cause of these differences and their effects on maternal and fetal well-being is discussed.

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Both enantiomers of serine adsorb on the intrinsically chiral Cu{531} surface in two different adsorption geometries, depending on the coverage. At saturation, substrate bonds are formed through the two oxygen atoms of the carboxylate group and the amino group (μ3 coordination), whereas at lower coverage, an additional bond is formed through the deprotonated β−OH group (μ4 coordination). The latter adsorption geometry involves substrate bonds through three side groups of the chiral center, respectively, which leads to significantly larger enantiomeric differences in adsorption geometries and energies compared to the μ3 coordination, which involves only two side groups. This relatively simple model system demonstrates, in direct comparison, that attractive interactions of three side groups with the substrate are much more effective in inducing strong enantiomeric differences in heterogeneous chiral catalyst systems than hydrogen bonds or repulsive interactions.

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The global atmospheric electric circuit is driven by thunderstorms and electrified rain/shower clouds and is also influenced by energetic charged particles from space. The global circuit maintains the ionosphere as an equipotential at∼+250 kV with respect to the good conducting Earth (both land and oceans). Its “load” is the fair weather atmosphere and semi-fair weather atmosphere at large distances from the disturbed weather “generator” regions. The main solar-terrestrial (or space weather) influence on the global circuit arises from spatially and temporally varying fluxes of galactic cosmic rays (GCRs) and energetic electrons precipitating from the magnetosphere. All components of the circuit exhibit much variability in both space and time. Global circuit variations between solar maximum and solar minimum are considered together with Forbush decrease and solar flare effects. The variability in ion concentration and vertical current flow are considered in terms of radiative effects in the troposphere, through infra-red absorption, and cloud effects, in particular possible cloud microphysical effects from charging at layer cloud edges. The paper identifies future research areas in relation to Task Group 4 of the Climate and Weather of the Sun-Earth System (CAWSES-II) programme.

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This paper presents single-column model (SCM) simulations of a tropical squall-line case observed during the Coupled Ocean-Atmosphere Response Experiment of the Tropical Ocean/Global Atmosphere Programme. This case-study was part of an international model intercomparison project organized by Working Group 4 ‘Precipitating Convective Cloud Systems’ of the GEWEX (Global Energy and Water-cycle Experiment) Cloud System Study. Eight SCM groups using different deep-convection parametrizations participated in this project. The SCMs were forced by temperature and moisture tendencies that had been computed from a reference cloud-resolving model (CRM) simulation using open boundary conditions. The comparison of the SCM results with the reference CRM simulation provided insight into the ability of current convection and cloud schemes to represent organized convection. The CRM results enabled a detailed evaluation of the SCMs in terms of the thermodynamic structure and the convective mass flux of the system, the latter being closely related to the surface convective precipitation. It is shown that the SCMs could reproduce reasonably well the time evolution of the surface convective and stratiform precipitation, the convective mass flux, and the thermodynamic structure of the squall-line system. The thermodynamic structure simulated by the SCMs depended on how the models partitioned the precipitation between convective and stratiform. However, structural differences persisted in the thermodynamic profiles simulated by the SCMs and the CRM. These differences could be attributed to the fact that the total mass flux used to compute the SCM forcing differed from the convective mass flux. The SCMs could not adequately represent these organized mesoscale circulations and the microphysicallradiative forcing associated with the stratiform region. This issue is generally known as the ‘scale-interaction’ problem that can only be properly addressed in fully three-dimensional simulations. Sensitivity simulations run by several groups showed that the time evolution of the surface convective precipitation was considerably smoothed when the convective closure was based on convective available potential energy instead of moisture convergence. Finally, additional SCM simulations without using a convection parametrization indicated that the impact of a convection parametrization in forced SCM runs was more visible in the moisture profiles than in the temperature profiles because convective transport was particularly important in the moisture budget.

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The reaction of 2-chloro-3-methyl-1,4-naphthoquinone (3) with the anion of ethyl cyanoacetate led to a mixture of two epimeric fused-ring cyclopropane compounds, characterised as exo- and endo-1-cyano-1 -ethoxycarbonyl-1a-methyl-1a,7a-dihydro-1H-cyclopropa[b]naphthalene-2,7-dione (8) and (9). Various hydrolysis products of these were prepared and an X-ray crystallographic analysis was carried out on one of them, 1-carbamoyl-1 -carboxy-1a-methyl-1a,7a-dihydro-1H-cyclopropa[b]-naphthalene-2,7-dione (17). The reaction of 2-methyl-1,4-naphthoquinone (1) with ethyl diazoacetate gave a fused pyrazoline derivative, 3-ethoxycarbonyl-4-hydroxy-9a-methyl-1,9a-dihydro-benz[f]indazol-9-one (22), while reaction of 2-methyl-3-nitro-1,4-naphthoquinone (5) with diazomethane led to a fused Δ2-isoxazoline N-oxide, 3a-methyl-3,3a-dihydroisoxazolo[3,4-b]naphthalene-4,9-dione 1-oxide (26).

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1 Plant species differ in their capacity to influence soil organic matter, soil nutrient availability and the composition of soil microbial communities. Their influences on soil properties result in net positive or negative feedback effects, which influence plant performance and plant community composition. 2 For two grassland systems, one on a sandy soil in the Netherlands and one on a chalk soil in the United Kingdom, we investigated how individual plant species grown in monocultures changed abiotic and biotic soil conditions. Then, we determined feedback effects of these soils to plants of the same or different species. Feedback effects were analysed at the level of plant species and plant taxonomic groups (grasses vs. forbs). 3 In the sandy soils, plant species differed in their effects on soil chemical properties, in particular potassium levels, but PLFA (phospholipid fatty acid) signatures of the soil microbial community did not differ between plant species. The effects of soil chemical properties were even greater when grasses and forbs were compared, especially because potassium levels were lower in grass monocultures. 4 In the chalk soil, there were no effects of plant species on soil chemical properties, but PLFA profiles differed significantly between soils from different monocultures. PLFA profiles differed between species, rather than between grasses and forbs. 5 In the feedback experiment, all plant species in sandy soils grew less vigorously in soils conditioned by grasses than in soils conditioned by forbs. These effects correlated significantly with soil chemical properties. None of the seven plant species showed significant differences between performance in soil conditioned by the same vs. other plant species. 6 In the chalk soil, Sanguisorba minor and in particular Briza media performed best in soil collected from conspecifics, while Bromus erectus performed best in soil from heterospecifics. There was no distinctive pattern between soils collected from forb and grass monocultures, and plant performance could not be related to soil chemical properties or PLFA signatures. 7 Our study shows that mechanisms of plant-soil feedback can depend on plant species, plant taxonomic (or functional) groups and site-specific differences in abiotic and biotic soil properties. Understanding how plant species can influence their rhizosphere, and how other plant species respond to these changes, will greatly enhance our understanding of the functioning and stability of ecosystems.

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With 25% of the UK population predicted to be obese by 2010, the costs to individuals and society are set to rise. Due to the extra economic and social pressures obesity causes, there is an increasing need to understand what motivates and prevents consumers from eating a healthy diet so as to be able to tailor policy interventions to specific groups in society. In so doing, it is important to explore potential variations in attitudes, motivation and behaviour as a function of age and gender. Both demographic factors are easily distinguished within society and a future intervention study which targets either, or both, of these would likely be both feasible and cost-effective for policy makers. As part of a preliminary study, six focus groups (total n = 43) were conducted at the University of Reading in November 2006, with groups segmented on the basis of age and gender. In order to gather more sensitive information, participants were also asked to fill out a short anonymous questionnaire before each focus group began, relating to healthy eating, alcohol consumption and body dissatisfaction. Making use of thematic content analysis, results suggested that most participants were aware of the type of foods that contribute to a healthy diet and the importance of achieving a healthy balance within a diet. However, they believed that healthy eating messages were often conflicting, and were uncertain about where to find information on the topic. Participants believed that the family has an important role in educating children about eating habits. Despite these similarities, there were a number of key differences among the groups in terms of their reasons for making food choices. Older participants (60+ years old) were more likely to make food choices based on health considerations. Participants between the ages of 18–30 were less concerned with this link, and instead focused on issues of food preparation and knowledge, prices and time. Younger female participants said they had more energy when they ate healthier diets; however, very often their food choices related to concern with their appearance. Older female participants also expressed this concern within the questionnaire, rather than in the group discussions. Overall, these results suggest that consumer motivations for healthy eating are diverse and that this must be considered by government, retailers and food producers.

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In clinical trials, situations often arise where more than one response from each patient is of interest; and it is required that any decision to stop the study be based upon some or all of these measures simultaneously. Theory for the design of sequential experiments with simultaneous bivariate responses is described by Jennison and Turnbull (Jennison, C., Turnbull, B. W. (1993). Group sequential tests for bivariate response: interim analyses of clinical trials with both efficacy and safety endpoints. Biometrics 49:741-752) and Cook and Farewell (Cook, R. J., Farewell, V. T. (1994). Guidelines for monitoring efficacy and toxicity responses in clinical trials. Biometrics 50:1146-1152) in the context of one efficacy and one safety response. These expositions are in terms of normally distributed data with known covariance. The methods proposed require specification of the correlation, ρ between test statistics monitored as part of the sequential test. It can be difficult to quantify ρ and previous authors have suggested simply taking the lowest plausible value, as this will guarantee power. This paper begins with an illustration of the effect that inappropriate specification of ρ can have on the preservation of trial error rates. It is shown that both the type I error and the power can be adversely affected. As a possible solution to this problem, formulas are provided for the calculation of correlation from data collected as part of the trial. An adaptive approach is proposed and evaluated that makes use of these formulas and an example is provided to illustrate the method. Attention is restricted to the bivariate case for ease of computation, although the formulas derived are applicable in the general multivariate case.

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There is increasing interest in combining Phases II and III of clinical development into a single trial in which one of a small number of competing experimental treatments is ultimately selected and where a valid comparison is made between this treatment and the control treatment. Such a trial usually proceeds in stages, with the least promising experimental treatments dropped as soon as possible. In this paper we present a highly flexible design that uses adaptive group sequential methodology to monitor an order statistic. By using this approach, it is possible to design a trial which can have any number of stages, begins with any number of experimental treatments, and permits any number of these to continue at any stage. The test statistic used is based upon efficient scores, so the method can be easily applied to binary, ordinal, failure time, or normally distributed outcomes. The method is illustrated with an example, and simulations are conducted to investigate its type I error rate and power under a range of scenarios.