Interactions of high energy mesons with complex nuclei

In order to study further the reaction of 300 MeV π (^-) mesons with carbon nuclei, it was necessary to acquire with good statistics the energy of the secondaries at different angular intervals. Apparatus was designed and built to support nuclear emulsion plates in a vertical plane around a central target. The apparatus was inserted between the poles of a magnet in a field of 25.5 kilogauss during the exposure. The plates were then area scanned for suitable tracks. A method of analysis was developed especially to cope with the problem of a finite target. pβ measurements were also made on secondaries from interactions in a carbon target. The actual incident beam energy was determined and was 285 MeV in both cases. The two sets of results agreed well over the angular interval where comparison could be made. The results were also compatible with previous experimental results at 300 MeV. Comparison was also made with the results predicted by a Monte Carlo nuclear cascade calculation (Bertini), but although the energy-angular distributions were almost identical, the momentum distributions at any one specific emission angle did not give good agreement. The observed angular distribution can be explained if the pion is subject to a potential on entering the nucleus, and if the nucleons have a momentum distribution extending up to at least 275 MeV/c. The nuclear well depth is estimated to be on average 53 MeV. An exclusion principle operates preventing pion-nucleon interaction if the nucleon is not thereby raised to the top of the nuclear well

Mouse adenovirus type 1 infection of natural killer cell-deficient mice

AbstractNatural killer (NK) cells contribute to the initial nonspecific response to viral infection, and viruses exhibit a range of sensitivities to NK cells in vivo. We investigated the role of NK cells in infection of mice by mouse adenovirus type 1 (MAV-1) using antibody-mediated depletion and knockout mice. MAV-1 causes encephalomyelitis and replicates to highest levels in brains. NK cell-depleted mice infected with MAV-1 showed brain viral loads 8–20 days p.i. that were similar to wild-type control non-depleted mice. Mice genetically deficient for NK cells behaved similarly to wild-type control mice with respect to brain viral loads and survival. We conclude that NK cells are not required to control virus replication in the brains of MAV-1-infected mice

Automated generation of node-splitting models for assessment of inconsistency in network meta-analysis

Network meta-analysis enables the simultaneous synthesis of a network of clinical trials comparing any number of treatments. Potential inconsistencies between estimates of relative treatment effects are an important concern, and several methods to detect inconsistency have been proposed. This paper is concerned with the node-splitting approach, which is particularly attractive because of its straightforward interpretation, contrasting estimates from both direct and indirect evidence. However, node-splitting analyses are labour-intensive because each comparison of interest requires a separate model. It would be advantageous if node-splitting models could be estimated automatically for all comparisons of interest. We present an unambiguous decision rule to choose which comparisons to split, and prove that it selects only comparisons in potentially inconsistent loops in the network, and that all potentially inconsistent loops in the network are investigated. Moreover, the decision rule circumvents problems with the parameterisation of multi-arm trials, ensuring that model generation is trivial in all cases. Thus, our methods eliminate most of the manual work involved in using the node-splitting approach, enabling the analyst to focus on interpreting the results. (C) 2015 The Authors Research Synthesis Methods Published by John Wiley & Sons Ltd

Evidence Synthesis for Decision Making 6:Embedding Evidence Synthesis in Probabilistic Cost-effectiveness Analysis

When multiple parameters are estimated from the same synthesis model, it is likely that correlations will be induced between them. Network meta-analysis (mixed treatment comparisons) is one example where such correlations occur, along with meta-regression and syntheses involving multiple related outcomes. These correlations may affect the uncertainty in incremental net benefit when treatment options are compared in a probabilistic decision model, and it is therefore essential that methods are adopted that propagate the joint parameter uncertainty, including correlation structure, through the cost-effectiveness model. This tutorial paper sets out 4 generic approaches to evidence synthesis that are compatible with probabilistic cost-effectiveness analysis. The first is evidence synthesis by Bayesian posterior estimation and posterior sampling where other parameters of the cost-effectiveness model can be incorporated into the same software platform. Bayesian Markov chain Monte Carlo simulation methods with WinBUGS software are the most popular choice for this option. A second possibility is to conduct evidence synthesis by Bayesian posterior estimation and then export the posterior samples to another package where other parameters are generated and the cost-effectiveness model is evaluated. Frequentist methods of parameter estimation followed by forward Monte Carlo simulation from the maximum likelihood estimates and their variance-covariance matrix represent’a third approach. A fourth option is bootstrap resampling—a frequentist simulation approach to parameter uncertainty. This tutorial paper also provides guidance on how to identify situations in which no correlations exist and therefore simpler approaches can be adopted. Software suitable for transferring data between different packages, and software that provides a user-friendly interface for integrated software platforms, offering investigators a flexible way of examining alternative scenarios, are reviewed

AS CRENÇAS NO RIO OITOCENTISTA: UM ESTUDO SOBRE A REPRESENTAÇÃO DO SAGRADO RELIGIOSO EM ESAÚ E JACÓ DE MACHADO DE ASSIS

RESUMO: A obra machadiana possui todas as suas facetas amplamente estudadas e, como não poderia deixar de ser, a marca da religiosidade na produção literária deste autor é também uma característica que deve ser descrita e analisada. No presente trabalho, procuramos estudar os aspectos religiosos que compõem grande parte da temática do romance Esaú e Jacó (1904). Chamamos a atenção, nesta análise, para o destaque que Machado de Assis dá ao sincretismo religioso tão característico da cultura brasileira, já que, apesar de profundamente influenciado pela tradição cristã, o romance supracitado descreve cenas, idéias e reflexões que se relacionam com outras crenças e religiões

Evidence Synthesis for Decision Making 2:A Generalized Linear Modeling Framework for Pairwise and Network Meta-analysis of Randomized Controlled Trials

We set out a generalized linear model framework for the synthesis of data from randomized controlled trials. A common model is described, taking the form of a linear regression for both fixed and random effects synthesis, which can be implemented with normal, binomial, Poisson, and multinomial data. The familiar logistic model for meta-analysis with binomial data is a generalized linear model with a logit link function, which is appropriate for probability outcomes. The same linear regression framework can be applied to continuous outcomes, rate models, competing risks, or ordered category outcomes by using other link functions, such as identity, log, complementary log-log, and probit link functions. The common core model for the linear predictor can be applied to pairwise meta-analysis, indirect comparisons, synthesis of multiarm trials, and mixed treatment comparisons, also known as network meta-analysis, without distinction. We take a Bayesian approach to estimation and provide WinBUGS program code for a Bayesian analysis using Markov chain Monte Carlo simulation. An advantage of this approach is that it is straightforward to extend to shared parameter models where different randomized controlled trials report outcomes in different formats but from a common underlying model. Use of the generalized linear model framework allows us to present a unified account of how models can be compared using the deviance information criterion and how goodness of fit can be assessed using the residual deviance. The approach is illustrated through a range of worked examples for commonly encountered evidence formats

Evidence Synthesis for Decision Making 5:The Baseline Natural History Model

Most cost-effectiveness analyses consist of a baseline model that represents the absolute natural history under a standard treatment in a comparator set and a model for relative treatment effects. We review synthesis issues that arise on the construction of the baseline natural history model. We cover both the absolute response to treatment on the outcome measures on which comparative effectiveness is defined and the other elements of the natural history model, usually “downstream” of the shorter-term effects reported in trials. We recommend that the same framework be used to model the absolute effects of a “standard treatment” or placebo comparator as that used for synthesis of relative treatment effects and that the baseline model is constructed independently from the model for relative treatment effects, to ensure that the latter are not affected by assumptions made about the baseline. However, simultaneous modeling of baseline and treatment effects could have some advantages when evidence is very sparse or when other research or study designs give strong reasons for believing in a particular baseline model. The predictive distribution, rather than the fixed effect or random effects mean, should be used to represent the baseline to reflect the observed variation in baseline rates. Joint modeling of multiple baseline outcomes based on data from trials or combinations of trial and observational data is recommended where possible, as this is likely to make better use of available evidence, produce more robust results, and ensure that the model is internally coherent