920 resultados para nonparametric inference


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In a sample of censored survival times, the presence of an immune proportion of individuals who are not subject to death, failure or relapse, may be indicated by a relatively high number of individuals with large censored survival times. In this paper the generalized log-gamma model is modified for the possibility that long-term survivors may be present in the data. The model attempts to separately estimate the effects of covariates on the surviving fraction, that is, the proportion of the population for which the event never occurs. The logistic function is used for the regression model of the surviving fraction. Inference for the model parameters is considered via maximum likelihood. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. Finally, a data set from the medical area is analyzed under the log-gamma generalized mixture model. A residual analysis is performed in order to select an appropriate model.

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In a previous study, we observed no spatial genetic structure in Mexican populations of the parasitoids Chelonus insularis Cresson (Hymenoptera: Braconidae) and Campoletis sonorensis Cameron (Hymenoptera: Ichneumonidae) by using microsatellite markers In the current study, we Investigated whether for these important parasitoids of the fall armyworm (Lepidoptera: Noctuidae) there is any genetic structure at a larger scale Insects of both species were collected across the American continent and their phylogeography was Investigated using both nuclear and mitochondria] markers Our results suggest an ancient north-south migration of C insularis, whereas no clear pattern] could be determined for C sonorensis. Nonetheless, the resulting topology indicated the existence of a cryptic taxon within this later species. a few Canadian specimens determined as C. sonorensis branch outside a clack composed of the Argentinean Chelonus grioti Blanchard, the Brazilian Chelonus flavicincta Ashmead, and the rest of the C sonorensis individuals The individuals revealing the cryptic taxon were collected from Thichoplusia in (Hubner) (Lepidoptera. Noctuidae) on tomato (Lycopersicon spp) and may represent a biotype that has adapted to the early season phenology of its host. Overall, the loosely defined spatial genetic structure previously shown at a local fine scale also was found at the larger scale, for both species Dispersal of these insects may be partly driven by wind as suggested by genetic similarities between Individuals coming from very distant locations.

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Xylella fastidiosa is a vector-borne, plant-pathogenic bacterium that causes disease in citrus (citrus variegated chlorosis [CVC]) and coffee (coffee leaf scorch [CLS]) plants in Brazil. CVC and CLS occur sympatrically and share leafhopper vectors; thus, determining whether X. fastidiosa isolates can be dispersed from one crop to another and cause disease is of epidemiological importance. We sought to clarify the genetic and biological relationships between CVC- and CLS-causing X. fastidiosa isolates. We used cross-inoculation bioassays and microsatellite and multilocus sequence typing (MLST) approaches to determine the host range and genetic structure of 26 CVC and 20 CLS isolates collected from different regions in Brazil. Our results show that citrus and coffee X. fastidiosa isolates are biologically distinct. Cross-inoculation tests showed that isolates causing CVC and CLS in the field were able to colonize citrus and coffee plants, respectively, but not the other host, indicating biological isolation between the strains. The microsatellite analysis separated most X. fastidiosa populations tested on the basis of the host plant from which they were isolated. However, recombination among isolates was detected and a lack of congruency among phylogenetic trees was observed for the loci used in the MLST scheme. Altogether, our study indicates that CVC and CLS are caused by two biologically distinct strains of X. fastidiosa that have diverged but are genetically homogenized by frequent recombination.

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Causal inference methods - mainly path analysis and structural equation modeling - offer plant physiologists information about cause-and-effect relationships among plant traits. Recently, an unusual approach to causal inference through stepwise variable selection has been proposed and used in various works on plant physiology. The approach should not be considered correct from a biological point of view. Here, it is explained why stepwise variable selection should not be used for causal inference, and shown what strange conclusions can be drawn based upon the former analysis when one aims to interpret cause-and-effect relationships among plant traits.

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Background Very few studies have investigated, in the elderly, the effect of rheumatic inflammatory states on phagocyte function and free radical production. The objective of this article is to evaluate phagocytosis by neutrophils and the production of nitric oxide (.NO) by monocytes in elderly women recruited among patients of the Brazilian Public Health System. Methods: Forty patients aged more than 60 years with rheumatic inflammatory diseases were studied. Phagocytosis was measured by flow cytometry. .NO production was measured by the total nitrite assay and conventional inflammation markers were determined. Data were analyzed with the Mann Whitney nonparametric test and P<0.05 was considered significant. Results. C-reactive protein levels and white blood cell counts were significantly higher in inflammation than in the control group (P<0.05). The phagocytosis fluorescence intensity per neutrophil and the percentual of neutrophils expressing phagocytosis were significantly higher (P<0.05) in the test than in the control group. Furthermore, there was significant .NO overproduction by monocytes, (P<0.05). Conclusion: Phagocytosis and .NO production are affected by rheumatic states. This suggests that the increased .NO levels may play a part in the increased oxidative stress in rheumatic diseases in elderly women. J. Clin. Lab. Anal. 25:47-51, 2011. (C) 2011 Wiley-Liss, Inc.

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Traditionally the basal ganglia have been implicated in motor behavior, as they are involved in both the execution of automatic actions and the modification of ongoing actions in novel contexts. Corresponding to cognition, the role of the basal ganglia has not been defined as explicitly. Relative to linguistic processes, contemporary theories of subcortical participation in language have endorsed a role for the globus pallidus internus (GPi) in the control of lexical-semantic operations. However, attempts to empirically validate these postulates have been largely limited to neuropsychological investigations of verbal fluency abilities subsequent to pallidotomy. We evaluated the impact of bilateral posteroventral pallidotomy (BPVP) on language function across a range of general and high-level linguistic abilities, and validated/extended working theories of pallidal participation in language. Comprehensive linguistic profiles were compiled up to 1 month before and 3 months after BPVP in 6 subjects with Parkinson's disease (PD). Commensurate linguistic profiles were also gathered over a 3-month period for a nonsurgical control cohort of 16 subjects with PD and a group of 16 non-neurologically impaired controls (NC). Nonparametric between-groups comparisons were conducted and reliable change indices calculated, relative to baseline/3-month follow-up difference scores. Group-wise statistical comparisons between the three groups failed to reveal significant postoperative changes in language performance. Case-by-case data analysis relative to clinically consequential change indices revealed reliable alterations in performance across several language variables as a consequence of BPVP. These findings lend support to models of subcortical participation in language, which promote a role for the GPi in lexical-semantic manipulation mechanisms. Concomitant improvements and decrements in postoperative performance were interpreted within the context of additive and subtractive postlesional effects. Relative to parkinsonian cohorts, clinically reliable versus statistically significant changes on a case by case basis may provide the most accurate method of characterizing the way in which pathophysiologically divergent basal ganglia linguistic circuits respond to BPVP.

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An on-line priming experiment was used to investigate discourse-level processing in four matched groups of subjects: individuals with nonthalamic subcortical lesions (NSL) ( n =10), normal control subjects ( n =10), subjects with Parkinsons disease (PD) ( n =10), and subjects with cortical lesions ( n =10). Subjects listened to paragraphs that ended in lexical ambiguities, and then made speeded lexical decisions on visual letter strings that were: nonwords, matched control words, contextually appropriate associates of the lexical ambiguity, contextually inappropriate associates of the ambiguity, and inferences (representing information which could be drawn from the paragraphs but was not explicitly stated). Targets were presented at an interstimulus interval (ISI) of 0 or 1000ms. NSL and PD subjects demonstrated priming for appropriate and inappropriate associates at the short ISI, similar to control subjects and cortical lesion subjects, but were unable to demonstrate selective priming of the appropriate associate and inference words at the long ISI. These results imply intact automatic lexical processing and a breakdown in discourse-based meaning selection and inference development via attentional/strategic mechanisms.

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Genetic recombination can produce heterogeneous phylogenetic histories within a set of homologous genes. Delineating recombination events is important in the study of molecular evolution, as inference of such events provides a clearer picture of the phylogenetic relationships among different gene sequences or genomes. Nevertheless, detecting recombination events can be a daunting task, as the performance of different recombination-detecting approaches can vary, depending on evolutionary events that take place after recombination. We recently evaluated the effects of post-recombination events on the prediction accuracy of recombination-detecting approaches using simulated nucleotide sequence data. The main conclusion, supported by other studies, is that one should not depend on a single method when searching for recombination events. In this paper, we introduce a two-phase strategy, applying three statistical measures to detect the occurrence of recombination events, and a Bayesian phylogenetic approach in delineating breakpoints of such events in nucleotide sequences. We evaluate the performance of these approaches using simulated data, and demonstrate the applicability of this strategy to empirical data. The two-phase strategy proves to be time-efficient when applied to large datasets, and yields high-confidence results.

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The generalized Gibbs sampler (GGS) is a recently developed Markov chain Monte Carlo (MCMC) technique that enables Gibbs-like sampling of state spaces that lack a convenient representation in terms of a fixed coordinate system. This paper describes a new sampler, called the tree sampler, which uses the GGS to sample from a state space consisting of phylogenetic trees. The tree sampler is useful for a wide range of phylogenetic applications, including Bayesian, maximum likelihood, and maximum parsimony methods. A fast new algorithm to search for a maximum parsimony phylogeny is presented, using the tree sampler in the context of simulated annealing. The mathematics underlying the algorithm is explained and its time complexity is analyzed. The method is tested on two large data sets consisting of 123 sequences and 500 sequences, respectively. The new algorithm is shown to compare very favorably in terms of speed and accuracy to the program DNAPARS from the PHYLIP package.

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Genetic recombination can produce heterogeneous phylogenetic histories within a set of homologous genes. Delineating recombination events is important in the study of molecular evolution, as inference of such events provides a clearer picture of the phylogenetic relationships among different gene sequences or genomes. Nevertheless, detecting recombination events can be a daunting task, as the performance of different recombination-detecting approaches can vary, depending on evolutionary events that take place after recombination. We previously evaluated the effects of post-recombination events on the prediction accuracy of recombination-detecting approaches using simulated nucleotide sequence data. The main conclusion, supported by other studies, is that one should not depend on a single method when searching for recombination events. In this paper, we introduce a two-phase strategy, applying three statistical measures to detect the occurrence of recombination events, and a Bayesian phylogenetic approach to delineate breakpoints of such events in nucleotide sequences. We evaluate the performance of these approaches using simulated data, and demonstrate the applicability of this strategy to empirical data. The two-phase strategy proves to be time-efficient when applied to large datasets, and yields high-confidence results.

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Most populations and some species of ticks of the genera Boophilus (5 spp.) and Rhipicephalus (ca. 75 spp.) cannot be distinguished phenotypically. Moreover, there is doubt about the validity of species in these genera. I studied the entire second internal transcribed spacer (ITS 2) rRNA of 16 populations of rhipicephaline ticks to address these problems: Boophilus,microplus from Australia, Kenya, South Africa and Brazil (4 populations); Boophilus decoloratus from Kenya; Rhipicephalus appendiculatus from Kenya, Zimbabwe and Zambia (7 populations); Rhipicephalus zambesiensis from Zimbabwe (3 populations); and Rhipicephalus evertsi from Kenya. Each of the 16 populations had a unique ITS 2, but most of the nucleotide variation occurred among species and genera. ITS 2 rRNA can be used to distinguish the populations and species of Boophilus and Rhipicephalus studied here. Little support was found for the hypothesis that B. microplus from Australia and South Africa are different species. ITS 2 appears useful for phylogenetic inference in the Rhipicephalinae because in genetic distance, maximum likelihood, and maximum parsimony analyses, most branches leading to species had >95% bootstrap support. Rhipicephalus appendiculatus and R, zambeziensis are closely related, yet their ITS 2 sequences could be distinguished unambiguously. This lends weight to a previous proposal that Rhipicephalus sanguineus and Rhipicephalus turanicus, and Rhipicephalus pumlilio and Rhipicephalus camicasi, respectively, are conspecific, because each of these pairs of species had identical sequences for ca. 250 bp of ITS 2 rRNA.

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This paper presents the unique collection of additional features of Qu-Prolog, a variant of the Al programming language Prolog, and illustrates how they can be used for implementing DAI applications. By this we mean applications comprising communicating information servers, expert systems, or agents, with sophisticated reasoning capabilities and internal concurrency. Such an application exploits the key features of Qu-Prolog: support for the programming of sound non-clausal inference systems, multi-threading, and high level inter-thread message communication between Qu-Prolog query threads anywhere on the internet. The inter-thread communication uses email style symbolic names for threads, allowing easy construction of distributed applications using public names for threads. How threads react to received messages is specified by a disjunction of reaction rules which the thread periodically executes. A communications API allows smooth integration of components written in C, which to Qu-Prolog, look like remote query threads.

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With the advent of functional neuroimaging techniques, in particular functional magnetic resonance imaging (fMRI), we have gained greater insight into the neural correlates of visuospatial function. However, it may not always be easy to identify the cerebral regions most specifically associated with performance on a given task. One approach is to examine the quantitative relationships between regional activation and behavioral performance measures. In the present study, we investigated the functional neuroanatomy of two different visuospatial processing tasks, judgement of line orientation and mental rotation. Twenty-four normal participants were scanned with fMRI using blocked periodic designs for experimental task presentation. Accuracy and reaction time (RT) to each trial of both activation and baseline conditions in each experiment was recorded. Both experiments activated dorsal and ventral visual cortical areas as well as dorsolateral prefrontal cortex. More regionally specific associations with task performance were identified by estimating the association between (sinusoidal) power of functional response and mean RT to the activation condition; a permutation test based on spatial statistics was used for inference. There was significant behavioral-physiological association in right ventral extrastriate cortex for the line orientation task and in bilateral (predominantly right) superior parietal lobule for the mental rotation task. Comparable associations were not found between power of response and RT to the baseline conditions of the tasks. These data suggest that one region in a neurocognitive network may be most strongly associated with behavioral performance and this may be regarded as the computationally least efficient or rate-limiting node of the network.

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The majority of past and current individual-tree growth modelling methodologies have failed to characterise and incorporate structured stochastic components. Rather, they have relied on deterministic predictions or have added an unstructured random component to predictions. In particular, spatial stochastic structure has been neglected, despite being present in most applications of individual-tree growth models. Spatial stochastic structure (also called spatial dependence or spatial autocorrelation) eventuates when spatial influences such as competition and micro-site effects are not fully captured in models. Temporal stochastic structure (also called temporal dependence or temporal autocorrelation) eventuates when a sequence of measurements is taken on an individual-tree over time, and variables explaining temporal variation in these measurements are not included in the model. Nested stochastic structure eventuates when measurements are combined across sampling units and differences among the sampling units are not fully captured in the model. This review examines spatial, temporal, and nested stochastic structure and instances where each has been characterised in the forest biometry and statistical literature. Methodologies for incorporating stochastic structure in growth model estimation and prediction are described. Benefits from incorporation of stochastic structure include valid statistical inference, improved estimation efficiency, and more realistic and theoretically sound predictions. It is proposed in this review that individual-tree modelling methodologies need to characterise and include structured stochasticity. Possibilities for future research are discussed. (C) 2001 Elsevier Science B.V. All rights reserved.

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From an experiment in which corals are transplanted between two depths on a Panamanian coral reef, Baker1 infers that bleaching may sometimes help reef corals to survive environmental change. Although Baker's results hint at further mechanisms by which reef-building corals may acclimatize to changing light conditions, we do not consider that the evidence supports his inference.