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At least 217 records · Page 12Linked to original sources

Hominoid phylogeny estimated by model selection using goodness of fit significance tests.

Phylogeny estimation from nucleotide sequence data may be thought of as a problem of choosing between different evolutionary models that vary with the branching pattern of the phylogeny and with the stochastic process of nucleotide sequence change occurring on the branches of the phylogenetic tree. Thus, each evolutionary model consists of both a particular stochastic process and a particular phylogeny. Such models produce multinomial distributions of nucleotide character patterns. As first suggested by Cavalli-Sforza and Edwards [Evolution 21: 550-570 (1967)] the distribution of patterns expected under each model can be compared to the actual observed distribution of patterns by a goodness of fit statistic such as the loglikelihood ratio G2 or Pearson's X2 after the numerical parameters for the model have been chosen to minimize the respective statistic. For each evolutionary model, the probability P of getting a value of the goodness of fit statistic greater than the observed value is computed. A very small P value means that either a rare event has occurred or that the model is false. Employing for each of 16 models a stochastic process which has 12 parameters to describe the mode of nucleotide change on each branch of each putative phylogenetic tree, we examined all 15 unrooted dichotomously branching arrangements of orthologous noncoding sequences from the gamma hemoglobin genomic region of the five hominoids (gibbon, orangutan, gorilla, chimpanzee, and human) plus the branching arrangement with a trichotomous separation of gorilla, chimpanzee, and human. Of these 16 models, all had P values less than 0.01, except for the arrangement of human joined by chimpanzee, in turn joined by gorilla, and then orangutan and gibbon. This analysis allows convincing claims to be made about hominoid phylogenetic relationships by testing the applicability of the assumed stochastic process for nucleotide sequence evolution at the same time as testing the inferred phylogenetic branching arrangement.

Animals↗

Cell-nuclear data reduction and prognostic model selection in bladder tumor recurrence.

OBJECTIVE: The paper aims at improving the prediction of superficial bladder recurrence. To this end, feedforward neural networks (FNNs) and a feature selection method based on unsupervised clustering, were employed. MATERIAL AND METHODS: A retrospective prognostic study of 127 patients diagnosed with superficial urinary bladder cancer was performed. Images from biopsies were digitized and cell nuclei features were extracted. To design FNN classifiers, different training methods and architectures were investigated. The unsupervised k-windows (UKW) and the fuzzy c-means clustering algorithms were applied on the feature set to identify the most informative feature subsets. RESULTS: UKW managed to reduce the dimensionality of the feature space significantly, and yielded prediction rates 87.95% and 91.41%, for non-recurrent and recurrent cases, respectively. The prediction rates achieved with the reduced feature set were marginally lower compared to the ones attained with the complete feature set. The training algorithm that exhibited the best performance in all cases was the adaptive on-line backpropagation algorithm. CONCLUSIONS: FNNs can contribute to the accurate prognosis of bladder cancer recurrence. The proposed feature selection method can remove redundant information without a significant loss in predictive accuracy, and thereby render the prognostic model less complex, more robust, and hence suitable for clinical use.

Algorithms↗

Model selection and parameterization of the concentration-response functions for population-level effects.

As concentration response functions for chronic population-level effects of pollutant chemicals, three mathematical models were presented and examined for goodness of fit to published toxicological data that estimated the population-level effects of chemicals in terms of the intrinsic rate of population growth (r). Among the examined concentration-r functions, the power function model, that is, r(x) = r(0)[1 - (x/alpha)beta], in which x is the exposure concentration and alpha and beta are parameters, performed with the best fit to each data set. The power function model is characterized by two parameters representing the absolute value of toxicity, alpha, and the curvature of responses, beta. The bootstrap simulation, conducted on the entire data set consisting of all published data that we collected, indicated that the observed variance of beta among actual data sets could be mostly explained by the random error variation generated from the bootstrap resamplings. The generic beta value, determined from the entire data set and expected to denote the best estimate of beta if the variability of beta was completely due to random sampling error, was estimated as 1.84. It was implied that the response of the intrinsic rate of natural increase (r) to chemical exposure was nearly quadratic in many cases.

Animals↗

Model selection techniques for the covariance matrix for incomplete longitudinal data.

In longitudinal studies with incomplete data, where the number of time points can become numerous, it is often advantageous to model the covariance matrix. We describe several covariance models (for example, mixed models, compound symmetry, AR(1)-type models, and combination models) that offer parsimonious alternatives to unstructured sigma. We evaluate each covariance model with longitudinal data concerning cholesterol as the repeated outcome measure. We discuss strategies for deciding the 'best' model and show a graphical technique for judging goodness-of-fit of covariance models.

Cholesterol↗

The effects of model selection on confidence intervals for the size of a closed population.

One encounters in the literature estimates of some rates of genetic and congenital disorders based on log-linear methods to model possible interactions among sources. Often the analyst chooses the simplest model consistent with the data for estimation of the size of a closed population and calculates confidence intervals on the assumption that this simple model is correct. However, despite an apparent excellent fit of the data to such a model, we note here that the resulting confidence intervals may well be misleading in that they can fail to provide an adequate coverage probability. We illustrate this with a simulation for a hypothetical population based on data reported in the literature from three sources. The simulated nominal 95 per cent confidence intervals contained the modelled population size only 30 per cent of the time. Only if external considerations justify the assumption of plausible interactions of sources would use of the simpler model's interval be justified.

Confidence Intervals↗

Model selection and efficiency testing for normalization of cDNA microarray data.

In this study we present two novel normalization schemes for cDNA microarrays. They are based on iterative local regression and optimization of model parameters by generalized cross-validation. Permutation tests assessing the efficiency of normalization demonstrated that the proposed schemes have an improved ability to remove systematic errors and to reduce variability in microarray data. The analysis also reveals that without parameter optimization local regression is frequently insufficient to remove systematic errors in microarray data.

Algorithms↗

Modelling selective activation of small myelinated nerve fibres using a monopolar point electrode.

The aim of this study is to investigate theoretically the possibility for activation of small myelinated nerve fibres without activating larger ones when stimulating a nerve fibre bundle using a monopolar point electrode. Therefore, the sensitivity of excitation and blocking threshold currents of nerve fibres to fibre diameter, electrode-fibre distance and pulse duration has been simulated by a computer model. A simple infinite, homogeneous volume conductor and a cathodal point source were used in combination with a model representing the electrical properties of a myelinated nerve fibre. The results show that selective activation of small myelinated fibres may be possible in a region at some distance from the electrode.

Computer Simulation↗

Development and application of a quasi-static Langmuir isotherm for modelling selected resin acid fate in pulp mill wastewater treatment.

Resin acids are pulp mill effluent contaminants that exhibit significant solubility, diffusivity, and surfactancy changes with pH within the range typically used for biological treatment. Such physical-chemical property changes which can influence removal during biological wastewater treatment, can be characterized by dynamic surface tension measurements. Dynamic surface tension measurements were made by the maximum bubble pressure method during batch treatment of selected resin acids in pulp mill effluent. Interpretation of dynamic surface tension data was made through the framework of a quasi-static Langmuir isotherm model that was derived as part of this investigation. The results suggested that under acidic conditions, resin acids form associations with other dissolved organic matter contained in pulp mill effluent, while under alkaline conditions, they behave as relatively soluble surfactants. A resin acid residuum, or threshold concentration, has been found to increase under acidic growth conditions. This residuum increase corresponded to an inferred reduction in resin acid bioavailability that was suggested from the isotherm modelling. The development of quasi-static isotherm adsorption models has application in computer simulation for design of adsorption based unit processes, and could potentially be utilized as an informative treatment process monitor.

Acids↗

Tobacco demarketing campaigns and role model selection in developing countries: the case of Bangladesh.

Tobacco production and consumption is on the increase in developing countries. It is imperative that effective demarketing of tobacco products be initiated. This will call for effective and credible role models. A major study conducted in Dhaka, Bangladesh indicates that doctors are the most credible source of information concerning the dangers of tobacco consumption. Campaigns utilizing elderly male doctors as role models are called for in working to correct to problem of tobacco used in developing countries.

Attitude to Health↗

Inter-generational longitudinal study of social class and depression: a test of social causation and social selection models.

BACKGROUND: Generations of epidemiologists have documented an association between low socio-economic status (SES) and depression (variously defined), but debate continues as to which is the causative factor. AIMS: To test the extent to which social causation (low SES causing depression) and social selection (depression causing low SES) processes are in evidence in an inter-generational longitudinal study. METHOD: Participants (n = 756) were interviewed up to four times over 17 years using the Schedule for Affective Disorders and Schizophrenia (SADS). RESULTS: Low parental education was associated with increased risk for offspring depression, even after controlling for parental depression, offspring gender and offspring age. Neither parental nor offspring depression predicted later levels of offspring occupation, education or income. CONCLUSION: There is evidence for an effect of parental SES on offspring depression (social causation) but not for an effect of either parental or offspring depression on offspring SES (social selection).

Adolescent↗

Model selection for the adsorption of phenobarbital by activated charcoal.

Activated charcoal is known to adsorb a wide variety of substances from solution, and several equations have been used to fit the resulting adsorption data. The determination of the correct model to fit phenobarbital adsorption onto activated charcoal was made using a calorimetric method. The differential heats of displacement of water by phenobarbital for four activated charcoals were determined and found to be linearly related to the amount of phenobarbital adsorbed. The activated charcoals studied had statistically similar heats of displacement. The linear relationship between heat evolved and the amount of phenobarbital adsorbed is consistent with the assumptions implicit in the Langmuir model.

Adsorption↗

The use of the ionization constant (pKa) in selecting models of toxicity in phenols.

Phenols elicit a toxic response by one of two mechanisms: polar narcosis or uncoupling of oxidative phosphorylation, and pKa values appear to be useful in predicting the mechanism of toxic action of a given phenol. The relative biological response (log BR) of 21 selected phenols in the static Tetrahymena pyriformis population growth test was determined. Seven derivatives, including dinitro- and polyhalogen-substituted phenols, were selected for testing because they were potential uncoupling agents. The other 14 derivatives were all suspected polar narcotics. 1-octanol/water partition coefficient (log Kow)-dependent regression analysis of the two subsets of derivatives results in two linear equations. The polar narcosis model is log BR = 0.6128 (log Kow) - 1.1297; r2 = 0.958, s = 0.187. The uncoupling of oxidative phosphorylation model is log BR = 0.4485 (log Kow) + 0.3007; r2 = 0.985, s = 0.209. Polar narcotic chemicals have pKa values greater than 8.00, while uncoupling agents have pKa values less than 6.50. Combining descriptors and modeling across mechanisms of toxicity in the model log BR = 0.5671 (log Kow) - 0.1885 pKa + 0.8190; r2 = 0.958, s = 0.225.

Animals↗

Effect of phenobarbital on the gamma-glutamyltranspeptidase activity and the remodeling of nodules induced by the initiation-selection model.

The effect of subsequent administration of phenobarbital on the gamma-glutamyltranspeptidase (GGT) activity and on the remodeling of nodules induced by the Solt-Farber procedure was examined in rats. GGT-nodules were initiated by diethylnitrosamine (DENA) followed by selection with 2-acetylaminofluorene (2AAF) in the diet and a partial hepatectomy (PH). Phenobarbital (500 ppm in the drinking water), administered to rats that were previously treated according to the Solt-Farber procedure, (1) increased the persistence of the GGT-nodules, (2) increased the percentage of the liver occupied by GGT positive cells, (3) increased the area of GGT activity per nodule and (4) increased the incidence of eosinophilic lesions. Subsequent treatment with phenobarbital did not alter the incidence of either GGT-nodules or hepatocellular carcinoma. Thus, phenobarbital increased the GGT activity of nodules induced by the Solt-Farber procedure and slowed both the loss of GGT activity by these nodules and their concurrent remodeling, but had no effect on the occurrence of cancer.

2-Acetylaminofluorene↗