SEARCH · PubMed Health

Results for “threshold model”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16Linked to original sources

PubMed1991

Simulation study on covariance component estimation for two binary traits in an underlying continuous scale.

The usefulness of the variance and covariance component estimation methods based on a threshold model was studied in a multiple-trait situation with two binary traits. Estimation equations that yield marginal maximum likelihood estimates of variance components on the underlying continuous variable scale and point estimates of location parameters with empirical Bayesian properties are described. Methods were tested on simulated data sets that were generated to exhibit three different incidences, 25, 15, and 5%. Results were compared with analyses of the same data sets with a REML method based on normal distribution and a linear model. Heritabilities and residual correlations calculated from discrete observations were transformed to underlying parameters. In estimation of heritabilities, all methods performed equally well at all incidence levels and with no detectable bias. As suggested by threshold theory, the genetic correlation was accurately estimated directly from the observations without any need of correction for incidence. Marginal maximum likelihood estimates of genetic correlations were similar to linear model estimates; discrepancies from the true parameters were consistent with both methods. In estimation of residual correlations, the method with the linear model approach yielded satisfactory estimates only at the highest incidence level, 25%. For 5% incidence, the uncorrected estimate of residual correlation was 50% less than the true value, and after correction for incidence, the parameter was overestimated by 90%. The estimates of residual correlation from the threshold model were regarded fair, except at the lowest level of incidence, where the estimate was 27% higher than the true value. Results indicated that when an accurate estimate of residual correlation is needed, the marginal maximum likelihood estimates are superior to the estimates calculated with the linear model. Using correction for the incidence level for residual correlation did not work well except at the highest incidence level.

Analysis of Variance↗

PubMed2000

Bayesian mapping of quantitative trait loci for complex binary traits.

A complex binary trait is a character that has a dichotomous expression but with a polygenic genetic background. Mapping quantitative trait loci (QTL) for such traits is difficult because of the discrete nature and the reduced variation in the phenotypic distribution. Bayesian statistics are proved to be a powerful tool for solving complicated genetic problems, such as multiple QTL with nonadditive effects, and have been successfully applied to QTL mapping for continuous traits. In this study, we show that Bayesian statistics are particularly useful for mapping QTL for complex binary traits. We model the binary trait under the classical threshold model of quantitative genetics. The Bayesian mapping statistics are developed on the basis of the idea of data augmentation. This treatment allows an easy way to generate the value of a hypothetical underlying variable (called the liability) and a threshold, which in turn allow the use of existing Bayesian statistics. The reversible jump Markov chain Monte Carlo algorithm is used to simulate the posterior samples of all unknowns, including the number of QTL, the locations and effects of identified QTL, genotypes of each individual at both the QTL and markers, and eventually the liability of each individual. The Bayesian mapping ends with an estimation of the joint posterior distribution of the number of QTL and the locations and effects of the identified QTL. Utilities of the method are demonstrated using a simulated outbred full-sib family. A computer program written in FORTRAN language is freely available on request.

Algorithms↗

PubMed1997

Effect of genetic heterogeneity and assortative mating on linkage analysis: a simulation study.

Linkage studies of complex genetic traits raise questions about the effects of genetic heterogeneity and assortative mating on linkage analysis. To further understand these problems, I have simulated and analyzed family data for a complex genetic disease in which disease phenotype is determined by two unlinked disease loci. Two models were studied, a two-locus threshold model and a two-locus heterogeneity model. Information was generated for a marker locus linked to one of the disease-defining loci. Random-mating and assortative-mating samples were generated. Linkage analysis was then carried out by use of standard methods, under the assumptions of a single-locus disease trait and a random-mating population. Results were compared with those from analysis of a single-locus homogeneous trait in samples with the same levels of assortative mating as those considered for the two-locus traits. The results show that (1) introduction of assortative mating does not, in itself, markedly affect the estimate of the recombination fraction; (2) the power of the analysis, reflected in the LOD scores, is somewhat lower with assortative rather than random mating. Loss of power is greater with increasing levels of assortative mating; and (3) for a heterogeneous genetic disease, regardless of mating type, heterogeneity analysis permits more accurate estimate of the recombination fraction but may be of limited use in distinguishing which families belong to each homogeneous subset. These simulations also confirmed earlier observations that linkage to a disease "locus" can be detected even if the disease is incorrectly defined as a single-locus (homogeneous) trait, although the estimated recombination fraction will be significantly greater than the true recombination fraction between the linked disease-defining locus and the marker locus.

Computer Simulation↗

PubMed2002

Analytic approaches to twin data using structural equation models.

The classical twin study is the most popular design in behavioural genetics. It has strong roots in biometrical genetic theory, which allows predictions to be made about the correlations between observed traits of identical and fraternal twins in terms of underlying genetic and environmental components. One can infer the relative importance of these 'latent' factors (model parameters) by structural equation modelling (SEM) of observed covariances of both twin types. SEM programs estimate model parameters by minimising a goodness-of-fit function between observed and predicted covariance matrices, usually by the maximum-likelihood criterion. Likelihood ratio statistics also allow the comparison of fit of different competing models. The program Mx, specifically developed to model genetically sensitive data, is now widely used in twin analyses. The flexibility of Mx allows the modelling of multivariate data to examine the genetic and environmental relations between two or more phenotypes and the modelling to categorical traits under liability-threshold models.

Chi-Square Distribution↗

PubMed1998

Shifting T-cell activation thresholds in autoimmunity and determinant spreading.

The best-characterized autoimmune T-cell response is that to myelin basic protein (MBP). MBP has classically been regarded as a sequestered antigen that does not cause negative selection. This view has been fostered by the observation that T-cell receptor-transgenic T cells that are specific for the "immunodominant determinant" on the molecule, MBP:Ac1-11, persist as naive cells in MBP-expressing H-2u mice. The same T cells, however, can cause autoimmune pathology once they have been primed by environmental stimulation to become memory cells. Once the autoimmune response to Ac1-11 has been engaged, determinant spreading occurs and second-wave T-cell responses that are specific for weaker, "cryptic" determinants like MBP:121-140 develop. Although the nature of these cryptic determinants has been enigmatic, recent studies using MBP-/- mice have provided new insights. These studies showed that MBP is not a sequestered antigen, but one that causes negative selection; as MBP:121-140 is actually the immunodominant determinant in MBP-/- mice, it tolerizes high avidity clones in MBP+/+ mice, making it appear cryptic. Based on this new information, we attempt here to redefine the MBP-specific repertoire within the theoretical framework of the threshold model for negative selection, and we propose a model of shifting T-cell activation thresholds to explain how ignorant/naive T cells can become effector cells of autoimmune pathology and why this effector cell repertoire spreads.

Animals↗

PubMed1999

Estimation of genetic and phenotypic parameters for clinical mastitis, somatic cell production deviance, and protein yield in dairy cattle using Gibbs sampling.

When including clinical mastitis in the breeding goal, it is useful to know what measure of the trait is most appropriate and its relationship to the primary production traits and indicator traits in the relevant population. In this paper, genetic and phenotypic parameters for clinical mastitis, somatic cell production deviance, and protein yield were estimated for the dairy breed Danish Red. In preliminary analyses, the heritability for clinical mastitis was found to be highest in early lactation, and its genetic correlation to clinical mastitis at other stages of lactation were high. Therefore, clinical mastitis defined in early lactation was the measure of clinical mastitis used in subsequent analyses. Two bivariate analyses were performed. Each analysis fitted clinical mastitis and either somatic cell production deviance or protein yield as a continuous trait. The bivariate model was composed of a Gaussian model for the continuous trait and a threshold model for mastitis. The analyses were performed in a Bayesian setting, using the Gibbs sampler. Point estimates (mean of marginal posterior densities) of heritability for mastitis on the underlying scale were estimated to be 0.10 and 0.12 in the two analyses. The genetic correlation between mastitis and protein yield was 0.43 and between mastitis and somatic cell production deviance was 0.80. These results make clear the importance of including clinical mastitis in the breeding goal and the usefulness of somatic cell production deviance as the indicator trait for clinical mastitis. The best measure of clinical mastitis was to consider only cases in early lactation.

Animals↗

PubMed2001

Nonpharmacologic interventions for inappropriate behaviors in dementia: a review, summary, and critique.

Inappropriate behaviors are very common in dementia and impose an enormous toll both emotionally and financially. Three main psychosocial theoretical models have generally been utilized to explain inappropriate behaviors in dementia: the "unmet needs" model, a behavioral/learning model, and an environmental vulnerability/reduced stress-threshold model. A literature search yielded 83 nonpharmacological intervention studies, which utilized the following categories of interventions: sensory, social contact (real or simulated), behavior therapy, staff training, structured activities, environmental interventions, medical/nursing care interventions, and combination therapies. The majority are reported to have a positive, albeit not always significant, impact. Better matching of the available interventions to patients' needs and capabilities may result in greater benefits to patients and their caregivers.

Aged↗

PubMed2002

[The mechanism and application of posttranscriptional gene silencing].

The purpose of this review is to confirm the reason resulted the gene silence and explore the countermeasure avoiding the gene silence in transgene plant. The method is to divide the gene silencing into transcriptional gene silencing(TGS) and posttranscriptional gene silencing(PTGS). Several models resulted PTGS were analyzed by RNA threshold model, ectopic pairing and aberrant RNA model and ds-RNA model. The results showed that it was important to decide the phenomena of restraining transgene silencing and the mechanism of PTGS. The strategies of identification of gene function and prevention of virus were presented by RNAi and gene silencing respectively, etc.

Animals↗

PubMedDate not supplied

[Potential role of hormesis in risk assessment in occupational toxicology].

Over the past few decades there has been a gradual decline in concentrations of airborne chemical agents in the workplace. This improvement in the workplace has led to a concomitant need to study the effects of low dose exposure in order to assess possible risks. The paradigm used in toxicology to evaluate risk and to establish exposure limits for substances employed in industry, is that the dose-response relationship is expressed by a linear model for carcinogenic substances and by a threshold model for those which are not. Alongside these two traditional models, there has been a recent proposal to describe relationships using hormesis which is characterised by a biphasic curve corresponding to moderate stimulation resulting from response to low doses, and by inhibition at high doses. Although hormesis has been widely observed in experimental contexts, it still has to be tested in occupational toxicology to determine the possibility of obtaining a more accurate evaluation of the risk of exposure to low doses present in the workplace.

Humans↗

PubMed1987

Intrinsic features contributing to spike train patterning in proprioceptive cuneate neurons.

The intrinsic processes contributing to the three discharge patterns of proprioceptive cuneate neurons described by Surmeier and Towe were studied experimentally and with computer simulation. Examination of the alterations in excitability produced by antidromic activation suggested that a prolonged inhibition was a concomitant of discharge in proprioceptive cuneate neurons. Computer simulation was performed to test the possible roles of inhibitory hyperpolarizing processes in governing the observed discharge patterns. These simulations used two constant threshold models. The simplest model linearly integrated synaptic potentials until the spike threshold was reached. After the discharge, synaptic potentials that preceded the spike were ignored (i.e., the model was "reset"). The second model was similar to the first except that following a spike two hyperpolarizing processes were activated and preceding events continued to play a role in membrane potential. Simulation of class A spike trains that possessed positive correlations between nearby intervals was successful only with a resetting model. This suggested that class A neurons have fast, no-memory postspike conductance changes, which effectively shunt synaptic charge. Simulation of class B spike trains was possible with the nonresetting model. At least two periodic inputs, which evoked brief, relatively large EPSPs, were required. In addition, a prominent, fast, spike-dependent hyperpolarization and a small-amplitude, slow hyperpolarization were required. Simulation of class C spike trains was also possible with the nonresetting model. Several periodic inputs were required; one input had to evoke a slow suprathreshold EPSP. In contrast to class B simulations, class C spike train simulation required that a large-amplitude, slow hyperpolarization, as well as a brief hyperpolarization, following spike initiation. The results of class B and C simulations suggested that these two groups differed primarily in the amplitude of a slow, hyperpolarizing, postspike conductance. Some role may also be played by the time course of the driving EPSPs.

Animals↗

PubMed1994

Effects of the non-NMDA antagonists NBQX and the 2,3-benzodiazepine GYKI 52466 on different seizure types in mice: comparison with diazepam and interactions with flumazenil.

1. GYKI 52466 is a benzodiazepine derivative that has muscle relaxant and anticonvulsant properties thought to be mediated by highly selective, noncompetitive antagonism of non-NMDA receptors. However, recent electrophysiological data showed that, in addition to non-NMDA receptors, the GABAA-receptor associated benzodiazepine site is involved in the depressant effect of GYKI 52466 on spinal reflex transmission. In view of the structural similarities between the 2,3 benzodiazepine derivative GYKI 52466 and 1,4-benzodiazepines such as diazepam, the benzodiazepine site of GABAA receptor complex could also be involved in the anticonvulsant activity of GYKI 52466, which has not yet been proven. This prompted us to study the effect of the benzodiazepine receptor antagonist, flumazenil, on anticonvulsant and adverse effects of GYKI 52466 in different seizure models in mice. The non-NMDA antagonist, NBQX and diazepam were used for comparison. 2. Seizure threshold models for different types of generalized seizures were used. The threshold for maximal (tonic) electroshock seizures (MES) was significantly increased by GYKI 52466 (10-20 mg kg-1), NBQX (80-120 mg kg-1) and diazepam (5 mg kg-1) shortly after i.p. drug administration. The same dose-range of the non-NMDA antagonists also significantly increased the threshold for myoclonic and clonic seizures induced by i.v. infusion of pentylenetetrazol (PTZ), although the magnitude of threshold increases obtained with the respective drugs, differed, at least in part, from that seen in the MES experiments. GYKI 52466 was clearly less potent in increasing PTZ thresholds for myoclonic and clonic seizures than on the MES threshold, while NBQX exerted about the same potency in both models. In contrast to the non-NMDA antagonists, diazepam was capable of increasing themyoclonic and clonic PTZ seizure threshold at much lower doses than the MES threshold. The PTZ threshold for tonic seizures was markedly increased by GYKI 52466, while NBQX and diazepam were clearly less potent in this respect.3. With respect to adverse effects, GYKI 52466 and NBQX induced significant seizure threshold increases in the different seizure models only at doses which caused sedation and ataxia, while diazepam increased the myoclonic and clonic PTZ seizure threshold at doses below those inducing motor impairment.4. Flumazenil (5-20 mg kg-1) antagonized the anticonvulsant and adverse effects of diazepam but not GYKI 52466. Instead, the anticonvulsant effect of GYKI 52466 was potentiated by flumazenil in some experiments. The anticonvulsant activity of NBQX was slightly reduced by flumazenil in the MES model but not in the PTZ test.5. The data indicate that the GABAA receptor-associated benzodiazepine site is not critically involved in anticonvulsant or adverse effects of GYKI 52466. However, both GYKI 52466 and NBQX were unable to increase seizure thresholds at doses below those inducing sedation and motor impairment,thus demonstrating that non-NMDA antagonists lack a selective anticonvulsant action in standard models of generalized seizures.

Animals↗

PubMed1999

Threshold-linear versus linear-linear analysis of birth weight and calving ease using an animal model: I. Variance component estimation.

Birth weight and calving difficulty were analyzed with Bayesian methodology using univariate linear models, a bivariate linear model, a threshold model for calving difficulty, and a joint threshold-linear model using a probit approach. Field data included 26,006 records of Gelbvieh cattle. Simulated populations were generated using parameters estimated from the field data. The Gibbs sampler was used to obtain estimates of the marginal posterior mean and standard deviation of the (co)variance components, heritabilities, and correlations. In the univariate analyses, the posterior mean of direct heritability for calving difficulty was .23 with the threshold model and .18 with the linear model. Maternal heritabilities were .10 and .08, respectively. In the bivariate analysis, posterior means of direct heritability for calving difficulty were .21 and .18 for the bivariate linear-threshold and linear-linear model, respectively. Maternal heritabilities were .09 and .06, respectively. Direct heritability for birth weight was .25 for the univariate model and .26 for bivariate models. Maternal heritability was .05 for the linear-threshold model and the univariate model and .06 for the bivariate linear model. Genetic correlation between direct genetic effects in both traits was .81 for the linear-threshold model and .79 for the bivariate linear. Residual correlation was .35 for the bivariate linear model and .50 for the bivariate linear-threshold. A simulation study confirmed that the posterior mean of the marginal distribution was suitable as a point estimate for univariate threshold and bivariate linear-threshold models.

Animals↗

PubMed2003

A new version of the size-advantage hypothesis for sex change: incorporating sperm competition and size-fecundity skew.

Traditional sex-change theory cannot explain the existence of protogynous species in which the largest females do not change sex when provided an opportunity. We present an expected reproductive success threshold model that incorporates previously unconsidered factors (size-fecundity skew and sperm competition) that can strongly affect reproductive expectations. The model predicts a variety of circumstances when the largest females remaining in a social group should not change sex in the absence of the dominant male, yet it also predicts that these same conditions should promote sex change in smaller females. If a large female's fecundity is markedly higher than the aggregate of the other members of her social group (i.e., there exists a skew in the size-fecundity distribution that raises a large female's expected reproductive success threshold), she should defer from sex change. Sperm competition can strongly lower the expectation of paternity obtained as a sex-changed male, and this also raises the threshold. The model suggests that deferral of sex change should be more common in species in which intense sperm competition is prevalent (such as fishes living in seagrass beds). This prediction appears consistent with patterns seen in nature.

Animals↗

PubMed2005

A non-parametric framework for estimating threshold limit values.

BACKGROUND: To estimate a threshold limit value for a compound known to have harmful health effects, an 'elbow' threshold model is usually applied. We are interested on non-parametric flexible alternatives. METHODS: We describe how a step function model fitted by isotonic regression can be used to estimate threshold limit values. This method returns a set of candidate locations, and we discuss two algorithms to select the threshold among them: the reduced isotonic regression and an algorithm considering the closed family of hypotheses. We assess the performance of these two alternative approaches under different scenarios in a simulation study. We illustrate the framework by analysing the data from a study conducted by the German Research Foundation aiming to set a threshold limit value in the exposure to total dust at workplace, as a causal agent for developing chronic bronchitis. RESULTS: In the paper we demonstrate the use and the properties of the proposed methodology along with the results from an application. The method appears to detect the threshold with satisfactory success. However, its performance can be compromised by the low power to reject the constant risk assumption when the true dose-response relationship is weak. CONCLUSION: The estimation of thresholds based on isotonic framework is conceptually simple and sufficiently powerful. Given that in threshold value estimation context there is not a gold standard method, the proposed model provides a useful non-parametric alternative to the standard approaches and can corroborate or challenge their findings.

Air Pollutants, Occupational↗

PubMed1997

The use of likelihood-based confidence intervals in genetic models.

This article describes the computation and relative merits of likelihood-based confidence intervals, compared to other measures of error in parameter estimates. Likelihood-based confidence intervals have the advantage of being asymmetric, which is often the case with structural equation models for genetically informative studies. We show how the package Mx provides confidence intervals for parameters and functions of parameters in the context of a simple additive genetic, common, and specific environment threshold model for binary data. Previously published contingency tables for major depression in adult female twins are used for illustration. The support for the model shows a marked skew as the additive genetic parameter is systematically varied from zero to one. The impact of allowing different prevalence rates in MZ vs. DZ twins is explored by fitting a model with separate threshold parameters and comparing the confidence intervals. Despite the improvement in fit of the different prevalence model, the confidence intervals on all parameters broaden, owing to their covariance.

Adult↗

PubMed1983

Demodulation methods for an adaptive neural encoder model.

An adaptive version of the integrate and fire-at-threshold model for the neural coding process is presented. The encoder transforms stimulus intensity information into sequences of identical membrane depolarization spikes, their times of occurrence defining a modulated point process. Several theoretical decoding schemes are then introduced and their performance analyzed. These implement simple, recursive parameter estimation algorithms and their output reproduces reliably; the encoded time-varying stimulus level.

Animals↗

PubMed2003

Parametric stability evaluation in computer experiments on the mathematical model of Drosophila control gene subnetwork.

Using the method of generalized threshold models, the problem is formulated and solved to evaluate the parametric stability of the model of a gene subnetwork controlling the early ontogenesis of the fruit fly Drosophila melanogaster. Computer experiments have been performed to test the parametric stability of the model. Quantitative evaluations have been obtained for parametric stability of the Drosophila gene subnetwork in nuclei along the embryo's anterior-posterior axis. The results of computer experiments have been compared with the previous research data on "sensitivity" of functioning regimes to random changes of the parameters in the models of prokaryotic and eukaryotic systems, namely the system controlling the lambda-phage development and the subsystem controlling the flower morphogenesis of Arabidopsis thaliana. The obtained results confirm high parametric stability of gene networks that control the development of organisms.

Animals↗

PubMed2003

Sparks and waves in a stochastic fire-diffuse-fire model of Ca2+ release.

Calcium ions are an important second messenger in living cells. Indeed, calcium signals in the form of waves have been the subject of much recent experimental interest. It is now well established that these waves are composed of elementary stochastic release events (calcium puffs or sparks) from spatially localized calcium stores. Here we develop a computationally inexpensive model of calcium release, based upon a stochastic generalization of the fire-diffuse-fire threshold model. Our model retains the discrete nature of calcium stores, but also incorporates a notion of release probability via the introduction of threshold noise. Numerical simulations of the model illustrate that stochastic calcium release leads to the spontaneous production of calcium sparks that may merge to form saltatory waves. In the parameter regime where deterministic waves exist, it is possible to identify a critical level of noise, defining a nonequilibrium phase transition between propagating and abortive structures. A statistical analysis shows that this transition is the same as for models in the directed percolation universality class. Moreover, in the regime where no initial structure can survive deterministically, threshold noise is shown to generate a form of array enhanced coherence resonance, whereby all calcium stores release periodically and simultaneously.

Biophysical Phenomena↗