946 resultados para Bayesian method


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Objective: To use our Bayesian method of motor unit number estimation (MUNE) to evaluate lower motor neuron degeneration in ALS. Methods: In subjects with ALS we performed serial MUNE studies. We examined the repeatability of the test and then determined whether the loss of MUs was fitted by an exponential or Weibull distribution. Results: The decline in motor unit (MU) numbers was well-fitted by an exponential decay curve. We calculated the half life of MUs in the abductor digiti minimi (ADM), abductor pollicis brevis (APB) and/or extensor digitorum brevis (EDB) muscles. The mean half life of the MUs of ADM muscle was greater than those of the APB or EDB muscles. The half-life of MUs was less in the ADM muscle of subjects with upper limb than in those with lower limb onset. Conclusions: The rate of loss of lower motor neurons in ALS is exponential, the motor units of the APB decay more quickly than those of the ADM muscle and the rate of loss of motor units is greater at the site of onset of disease. Significance: This shows that the Bayesian MUNE method is useful in following the course and exploring the clinical features of ALS. 2012 International Federation of Clinical Neurophysiology.

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This study uses borehole geophysical log data of sonic velocity and electrical resistivity to estimate permeability in sandstones in the northern Galilee Basin, Queensland. The prior estimates of permeability are calculated according to the deterministic log–log linear empirical correlations between electrical resistivity and measured permeability. Both negative and positive relationships are influenced by the clay content. The prior estimates of permeability are updated in a Bayesian framework for three boreholes using both the cokriging (CK) method and a normal linear regression (NLR) approach to infer the likelihood function. The results show that the mean permeability estimated from the CK-based Bayesian method is in better agreement with the measured permeability when a fairly apparent linear relationship exists between the logarithm of permeability and sonic velocity. In contrast, the NLR-based Bayesian approach gives better estimates of permeability for boreholes where no linear relationship exists between logarithm permeability and sonic velocity.

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Introduced in this paper is a Bayesian model for isolating the resonant frequency from combustion chamber resonance. The model shown in this paper focused on characterising the initial rise in the resonant frequency to investigate the rise of in-cylinder bulk temperature associated with combustion. By resolving the model parameters, it is possible to determine: the start of pre-mixed combustion, the start of diffusion combustion, the initial resonant frequency, the resonant frequency as a function of crank angle, the in-cylinder bulk temperature as a function of crank angle and the trapped mass as a function of crank angle. The Bayesian method allows for individual cycles to be examined without cycle-averaging|allowing inter-cycle variability studies. Results are shown for a turbo-charged, common-rail compression ignition engine run at 2000 rpm and full load.

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Os pacientes agressivos e/ou agitados correspondem a 10% de todas as internações em emergências psiquiátricas. Dependendo do grau de agitação, esses pacientes representam um risco para a integridade física, tanto para os profissionais que ali estão como para si mesmos. Dentre as alternativas para lidar com esses casos está a contenção física. Ainda que amplamente utilizada, seu uso é controverso e proibido em alguns países. No Brasil inexistem protocolos orientando o seu uso. O objetivo deste estudo foi conhecer a freqüência e os fatores associados a esta prática através de uma revisão sistemática e de um estudo em emergências psiquiátricas do município do Rio de Janeiro. A revisão identificou apenas quatro estudos, sendo três nos EUA e um na Índia. A freqüência de contenção em pacientes agitados e/ou agressivos nos serviços de emergência psiquiátrica variou de 14% até 59%. Os desenhos adotados, assim como as análises estatísticas, mostraram fragilidades para a investigação dos fatores explicativos para o uso de contenção física. O estudo nas emergências psiquiátricas do Rio de Janeiro lançou mão de informações sobre o uso de contenção física entre 298 pacientes participantes de um ensaio clínico comparando dois medicamentos para lidar com quadros de agitação psicomotora e comportamento agressivo nesses serviços. As variáveis investigadas foram aquelas coletadas antes da entrada do paciente no ensaio clínico. Portanto, variáveis que antecederam a decisão do médico conter o paciente. A análise dos dados fez uso do método Bayesiano. As prioris dos parâmetros utilizadas no modelo de regressão binária foram obtidas de um outro ensaio clínico, conduzido em uma das três emergências envolvidas no presente estudo. A freqüência no emprego da contenção física foi 24,5%, sem diferença entre os três hospitais. O estudo mostrou ainda que pacientes mais jovens, com quadros mais intensos, com suspeita diagnóstica de entrada de abuso de substâncias e que foram atendidos na parte da manhã apresentaram maior chance de serem fisicamente contidos. O presente trabalho aponta para a necessidade de conduzir estudos especificamente desenhados para avaliar a freqüência e os fatores associados com o uso de contenção física, os quais deverão subsidiar o desenvolvimento de protocolos sobre o uso desta prática em nosso meio.

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Este trabalho tem como objetivos analisar as semelhanças das respostas dos países da Zona do Euro aos choques na política monetária e no câmbio (identificados através de restrições de sinais nas funções impulso-resposta) e investigar a simetria das flutuações na taxa de crescimento do nível de atividade na região através da análise da importância relativa da resposta do crescimento do PIB destes países aos choques comum e específico identificados pelo modelo FAVAR utilizado, que foi estimado através de um método Bayesiano desenvolvido para incorporar prioris de Litterman (1986). A importância do choque comum (relativamente ao específico) nos diversos países, fornece uma medida do grau de integração dos diversos membros da Zona do Euro. O trabalho contribui para a análise do grau de integração dos países da Zona do Euro ao utilizar uma metodologia que permite o uso de um amplo conjunto de variáveis e ao identificar o grau de simetria das flutuações na taxa de crescimento do nível de atividade dos membros da região através da identificação dos choques comuns e específicos. Foram utilizados dados trimestrais de 1999.I a 2013.I para os 17 países da região. Os resultados encontrados apontam para a existência de uma maior integração entre as grandes economias da Zona do Euro ( com exceção da França) e uma integração menor para as menores economias (com exceção da Finlândia).

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We present a nonparametric Bayesian method for disease subtype discovery in multi-dimensional cancer data. Our method can simultaneously analyse a wide range of data types, allowing for both agreement and disagreement between their underlying clustering structure. It includes feature selection and infers the most likely number of disease subtypes, given the data. We apply the method to 277 glioblastoma samples from The Cancer Genome Atlas, for which there are gene expression, copy number variation, methylation and microRNA data. We identify 8 distinct consensus subtypes and study their prognostic value for death, new tumour events, progression and recurrence. The consensus subtypes are prognostic of tumour recurrence (log-rank p-value of $3.6 \times 10^{-4}$ after correction for multiple hypothesis tests). This is driven principally by the methylation data (log-rank p-value of $2.0 \times 10^{-3}$) but the effect is strengthened by the other 3 data types, demonstrating the value of integrating multiple data types. Of particular note is a subtype of 47 patients characterised by very low levels of methylation. This subtype has very low rates of tumour recurrence and no new events in 10 years of follow up. We also identify a small gene expression subtype of 6 patients that shows particularly poor survival outcomes. Additionally, we note a consensus subtype that showly a highly distinctive data signature and suggest that it is therefore a biologically distinct subtype of glioblastoma. The code is available from https://sites.google.com/site/multipledatafusion/

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Connective tissue growth factor (CTGF) plays an important role in regulation of cell growth, differentiation, apoptosis and individual development in animals. The study of sequences variation and molecular evolution of CTGF gene across various species of the cyprinid could be helpful for understanding of speciation and gene divergence in this kind of fish. In this study, 19 novel sequences of CTGF gene were obtained from the representative species of the family Cyprinidae using PCR amplification, cloning and sequencing. Phylogenetic relationships of Cyprinidae were reconstructed by neighbor-joining (NJ), maximum parsimony (MP), maximum likelihood (ML) and Bayesian method. Oryzias latipes from the family Cyprinodontidae was assigned to be the outgroup taxon. Leuciscini and Barbini were clustered into the monophyletic lineages, respectively, with the high nodal supports. The estimation of the ratio of non-synonymous to synonymous substitution (dN/dS) for the various branches indicated that there stood the different evolution rates between the Leuciscini and the Barbini. With the ratio of dN/dS of the Leuciscini being lower than that of the Barbini, species within the Barbini were demonstrated to be subjected to the relatively less selection pressure and under the relaxable evolution background. A 6 by indel (insertion/deletion) was found at the 5' end of CTGF gene of Cyprinidae, and this 6 by deletion only appeared in the Leuciscini, which is a typical characteristic of the Leuciscini and provides evidence for the monophylogeny of the Leuciscini. For the amino acid sequences of CTGF protein, the most variations and indels were distributed in the signal region and IGFBP region of this protein, implying that these variations were correlated with the regulation of the CTGF gene expression and protein activity. (c) 2007 National Natural Science Foundation of China and Chinese Academy of Sciences. Published by Elsevier Limited and Science in China Press. All rights reserved.

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The complete sequence of the 16,539 nucleotide mitochondrial genome from the single species of the catfish family Cranoglanididae, the helmet catfish Cranoglanis bouderius, was determined using the long and accurate polymerase chain reaction (LA PCR) method. The nucleotide sequences of C. bouderius mitochondrial DNA have been compared with those of three other catfish species in the same order. The contents of the C. bouderius mitochondrial genome are 13 protein-coding genes, two ribosomal RNA and 22 transfer RNA genes, and a non-coding control region, the gene order of which is identical to that observed in most other vertebrates. Phylogenetic analyses for 13 otophysan fishes were performed using Bayesian method based on the concatenated mtDNA protein-coding gene sequence and the individual protein-coding gene sequence data set. The competing otophysan topologies were then tested by using the approximately unbiased test, the Kishino-Hasegawa test, and the Shimodaira-Hasegawa test. The results show that the grouping ((((Characifonnes, Gymnotiformes), Siluriformes), Cyprinifionnes), outgroup) is the most likely but there is no significant difference between this one and the other alternative hypotheses. In addition, the phylogenetic placement of the family Cranoglanididae among siluriform families was also discussed. (c) 2006 Elsevier B.V. All rights reserved.

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Introduction. Le VIH-1 évolue en fonction de la réponse immunitaire spécifique de l’hôte. La pression sélective exercée par la réponse immunitaire VIH-spécifique de l’hôte entraine l’évolution des gènes viraux et à terme détermine l’évolution de la maladie. Cette évolution du virus à l’échelle d’un individu façonne également l’évolution du virus à l’échelle de la population et détermine le devenir de l’épidémie. Le VIH utilise les corécepteurs d’entrée CCR5 (virus R5) et CXCR4 (virus X4) afin d’infecter la cellule cible, et l’évolution du tropisme du virus de R5 vers X4, appelé switch du tropisme, est associé à la progression de la maladie. Les virus R5 sont rencontrés en début d’infection tandis que les virus X4 apparaissent en fin de maladie chez un certain de nombre de patients et sont considérés comme plus virulents. La pression sélective immunitaire exercée sur le gène de l’enveloppe (env) peut donc entrainer l’évolution du tropisme du VIH. La grossesse est un état immunitaire particulier considéré comme étant principalement caractérisé par un biais Th2 nécessaire à l’établissement de la tolérance materno-fétale. Le switch de tropisme de R5 vers X4 en grossesse n’a jamais été documenté, de même que l’évolution des déterminants du tropisme à l’échelle de la population. Hypothèses. Les changements immunitaires associés à l’initiation et la progression de la grossesse engendrent des changements dans la pression immunitaire exercée sur l’enveloppe et peuvent favoriser le switch du tropisme. L’évolution du tropisme du VIH-1 peut être observé à l’échelle de la population au même titre que l’évolution de l’enveloppe virale. Objectifs. Analyser l’évolution du tropisme et décrire la pression sélective sur l’enveloppe des femmes enceintes infectées par le VIH-1. Analyser l’évolution des déterminants du tropisme à l’échelle de la population. Méthodes. Nous avons dans un premier temps analysé l’évolution des déterminants du tropisme et déterminé le génotype et phénotype du VIH-1 chez 19 femmes enceintes issues de la cohorte du centre maternel et infantile sur le SIDA de l’hôpital Sainte-Justine (CMIS). Nous avons ensuite caractérisé et comparé la pression sélective exercée sur env, par une méthode bayésienne, chez 31 femmes enceinte et 29 femmes non-enceintes. Enfin, nous avons analysé et comparé des déterminants du tropisme entre des séquences d’enveloppe contemporaines et anciennes, issues des bases de données du NCBI. Résultats. Nos résultats montrent la présence de virus X4 chez la moitié de notre cohorte, et un switch de tropisme de R5 vers X4 chez 5/19 sujets. Les séquences des femmes enceintes présentaient des taux de substitutions plus élevées que celles des femmes non-enceintes. La pression sélective dans la région C2 était plus faible chez les femmes enceintes que chez les femmes non-enceintes, et différait dans 4 positions entre ces 2 groupes. Cette sélection diminuait au cours de la grossesse chez les patientes traitées. Enfin, une accumulation de mutations X4 a été observée dans les séquences R5 contemporaines par rapport aux séquences R5 anciennes. Conclusion. Les changements immunitaires associés à la grossesse semblent induire des modifications subtiles dans la pression sélective exercée sur env, suffisant à influencer l’évolution du tropisme de R5 vers X4. Un switch du tropisme à l’échelle de la population impliquerait une épidémie évoluant vers une plus grande virulence du virus. Nos résultats sont d’importance en ce qui concerne la prophylaxie antirétrovirale pour la santé de la mère et la prévention de la transmission mère-enfant du VIH-1. Ils sont aussi importants concernant l’avenir de la thérapie antirétrovirale dans le contexte d’une épidémie évoluant vers une plus grande virulence

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Bayesian inference has been used to determine rigorous estimates of hydroxyl radical concentrations () and air mass dilution rates (K) averaged following air masses between linked observations of nonmethane hydrocarbons (NMHCs) spanning the North Atlantic during the Intercontinental Transport and Chemical Transformation (ITCT)-Lagrangian-2K4 experiment. The Bayesian technique obtains a refined (posterior) distribution of a parameter given data related to the parameter through a model and prior beliefs about the parameter distribution. Here, the model describes hydrocarbon loss through OH reaction and mixing with a background concentration at rate K. The Lagrangian experiment provides direct observations of hydrocarbons at two time points, removing assumptions regarding composition or sources upstream of a single observation. The estimates are sharpened by using many hydrocarbons with different reactivities and accounting for their variability and measurement uncertainty. A novel technique is used to construct prior background distributions of many species, described by variation of a single parameter . This exploits the high correlation of species, related by the first principal component of many NMHC samples. The Bayesian method obtains posterior estimates of , K and following each air mass. Median values are typically between 0.5 and 2.0 × 106 molecules cm−3, but are elevated to between 2.5 and 3.5 × 106 molecules cm−3, in low-level pollution. A comparison of estimates from absolute NMHC concentrations and NMHC ratios assuming zero background (the “photochemical clock” method) shows similar distributions but reveals systematic high bias in the estimates from ratios. Estimates of K are ∼0.1 day−1 but show more sensitivity to the prior distribution assumed.

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This study compares the infant mortality profiles of 128 infants from two urban and two rural cemetery sites in medieval England. The aim of this paper is to assess the impact of urbanization and industrialization in terms of endogenous or exogenous causes of death. In order to undertake this analysis, two different methods of estimating gestational age from long bone lengths were used: a traditional regression method and a Bayesian method. The regression method tended to produce more marked peaks at 38 weeks, while the Bayesian method produced a broader range of ages and were more comparable with the expected "natural" mortality profiles. At all the sites, neonatal mortality (28-40 weeks) outweighed post-neonatal mortality (41-48 weeks) with rural Raunds Furnells in Northamptonshire, showing the highest number of neonatal deaths and post-medieval Spitalfields, London, showing a greater proportion of deaths due to exogenous or environmental factors. Of the four sites under study, Wharram Percy in Yorkshire showed the most convincing "natural" infant mortality profile, suggesting the inclusion of all births (i.e., stillbirths and unbaptised infants).

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[1] Cloud cover is conventionally estimated from satellite images as the observed fraction of cloudy pixels. Active instruments such as radar and Lidar observe in narrow transects that sample only a small percentage of the area over which the cloud fraction is estimated. As a consequence, the fraction estimate has an associated sampling uncertainty, which usually remains unspecified. This paper extends a Bayesian method of cloud fraction estimation, which also provides an analytical estimate of the sampling error. This method is applied to test the sensitivity of this error to sampling characteristics, such as the number of observed transects and the variability of the underlying cloud field. The dependence of the uncertainty on these characteristics is investigated using synthetic data simulated to have properties closely resembling observations of the spaceborne Lidar NASA-LITE mission. Results suggest that the variance of the cloud fraction is greatest for medium cloud cover and least when conditions are mostly cloudy or clear. However, there is a bias in the estimation, which is greatest around 25% and 75% cloud cover. The sampling uncertainty is also affected by the mean lengths of clouds and of clear intervals; shorter lengths decrease uncertainty, primarily because there are more cloud observations in a transect of a given length. Uncertainty also falls with increasing number of transects. Therefore a sampling strategy aimed at minimizing the uncertainty in transect derived cloud fraction will have to take into account both the cloud and clear sky length distributions as well as the cloud fraction of the observed field. These conclusions have implications for the design of future satellite missions. This paper describes the first integrated methodology for the analytical assessment of sampling uncertainty in cloud fraction observations from forthcoming spaceborne radar and Lidar missions such as NASA's Calipso and CloudSat.

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The identification of signatures of natural selection in genomic surveys has become an area of intense research, stimulated by the increasing ease with which genetic markers can be typed. Loci identified as subject to selection may be functionally important, and hence (weak) candidates for involvement in disease causation. They can also be useful in determining the adaptive differentiation of populations, and exploring hypotheses about speciation. Adaptive differentiation has traditionally been identified from differences in allele frequencies among different populations, summarised by an estimate of F-ST. Low outliers relative to an appropriate neutral population-genetics model indicate loci subject to balancing selection, whereas high outliers suggest adaptive (directional) selection. However, the problem of identifying statistically significant departures from neutrality is complicated by confounding effects on the distribution of F-ST estimates, and current methods have not yet been tested in large-scale simulation experiments. Here, we simulate data from a structured population at many unlinked, diallelic loci that are predominantly neutral but with some loci subject to adaptive or balancing selection. We develop a hierarchical-Bayesian method, implemented via Markov chain Monte Carlo (MCMC), and assess its performance in distinguishing the loci simulated under selection from the neutral loci. We also compare this performance with that of a frequentist method, based on moment-based estimates of F-ST. We find that both methods can identify loci subject to adaptive selection when the selection coefficient is at least five times the migration rate. Neither method could reliably distinguish loci under balancing selection in our simulations, even when the selection coefficient is twenty times the migration rate.

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Inferring the spatial expansion dynamics of invading species from molecular data is notoriously difficult due to the complexity of the processes involved. For these demographic scenarios, genetic data obtained from highly variable markers may be profitably combined with specific sampling schemes and information from other sources using a Bayesian approach. The geographic range of the introduced toad Bufo marinus is still expanding in eastern and northern Australia, in each case from isolates established around 1960. A large amount of demographic and historical information is available on both expansion areas. In each area, samples were collected along a transect representing populations of different ages and genotyped at 10 microsatellite loci. Five demographic models of expansion, differing in the dispersal pattern for migrants and founders and in the number of founders, were considered. Because the demographic history is complex, we used an approximate Bayesian method, based on a rejection-regression algorithm. to formally test the relative likelihoods of the five models of expansion and to infer demographic parameters. A stepwise migration-foundation model with founder events was statistically better supported than other four models in both expansion areas. Posterior distributions supported different dynamics of expansion in the studied areas. Populations in the eastern expansion area have a lower stable effective population size and have been founded by a smaller number of individuals than those in the northern expansion area. Once demographically stabilized, populations exchange a substantial number of effective migrants per generation in both expansion areas, and such exchanges are larger in northern than in eastern Australia. The effective number of migrants appears to be considerably lower than that of founders in both expansion areas. We found our inferences to be relatively robust to various assumptions on marker. demographic, and historical features. The method presented here is the only robust, model-based method available so far, which allows inferring complex population dynamics over a short time scale. It also provides the basis for investigating the interplay between population dynamics, drift, and selection in invasive species.

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A Bayesian method of estimating multivariate sample selection models is introduced and applied to the estimation of a demand system for food in the UK to account for censoring arising from infrequency of purchase. We show how it is possible to impose identifying restrictions on the sample selection equations and that, unlike a maximum likelihood framework, the imposition of adding up at both latent and observed levels is straightforward. Our results emphasise the role played by low incomes and socio-economic circumstances in leading to poor diets and also indicate that the presence of children in a household has a negative impact on dietary quality.