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PubMed1999

Breeding biology of muscovy duck (Cairina moschata) under natural incubation: the use of the weibull function and a beta-binomial model to predict nest hatchability

In this paper we tested the Weibull function and beta-binomial distribution to analyse and predict nest hatchability, using empirical data on hatchability in Muscovy duck (Cairina moschata) eggs under natural incubation (932 successfully incubated nests and 11 822 eggs). The estimated parameters of the Weibull function and beta-binomial model were compared with the logistic regression analysis. The maximum likelihood estimation of the parameters was used to quantify simultaneously the influence of the nesting behaviour and the duration of the reproduction cycle on hatchability. The estimated parameters showed that the hatchability was not affected in natural dump nests, but in artificial dump nests and in nests with non-term eggs the hatchability was reduced by 10 and 25%, respectively. Similar results were obtained using logistic regression. Both models provided a satisfactory description of the observed data set, but the beta-binomial model proved to have more parameters with practical and biological meaningful interpretations, because this model is able to quantify and incorporate the unexplained variation in a single parameter theta (which is a variance measure). Copyright 1999 Academic Press.

Journal Article↗
PubMed1998

Seizure detection of newborn EEG using a model-based approach.

Seizures are often the first sign of neurological disease or dysfunction in the newborn. However, their clinical manifestation is often subtle, which tends to hinder their diagnosis at the earliest possible time. This represents an undesirable situation since the failure to quickly and accurately diagnose seizure can lead to longer-term brain injury or even death. In this paper we consider the problem of automatic seizure detection in the neonate based on electroencephalogram (EEG) data. We propose a new approach based on a model for the generation of the EEG, which is derived from the histology and biophysics of a localized portion of the brain. We show that by using this approach, good detection performance of electrographic seizure is possible. The model for seizure is first presented along with an estimator for the model parameters. Then we present a seizure-detection scheme based on the model parameter estimates. This scheme is compared with the quadratic detection filter (QDF), and is shown to give superior performance over the latter. This is due to the ability of the model-based detector to account for the variability (nonstationarity) of the EEG by adjusting its parameters appropriately.

Algorithms↗
PubMed2003

A physiologically based approach for the estimation of recirculatory parameters.

Indicator dilution studies are used to provide estimates for several physiological parameters such as cardiac output as well as intra- and extravascular volumes. This study introduces a novel technique for the estimation of recirculatory parameters. A mathematical model based on a dispersion-convection partial differential equation (PDE), derived from the fractal geometry of the vascular tree and the hydrodynamics of the blood flow, is used to describe the spatiotemporal profile of tracers in the circulatory system. Initially, the equation is fitted to concentration-time (C,t) data of a tracer to derive the parameter estimates of the model equation; in a subsequent step, these estimates along with appropriate changes of the parameters of the PDE are used to generate the early concentration-time profile of a hypothetical appropriate tracer without recirculation. Thus, the area under the concentration-time curve of the first passage of the tracer is calculated and used for the estimation of various physiological parameters, including cardiac output, miscellaneous partial blood volumes, and the corresponding mean transit times. The procedure was applied successfully to literature data of various tracers from humans and dogs.

Animals↗
PubMedDate not supplied

Modelling of age-related bone loss using cross-sectional data.

BACKGROUND: Current applications of bone mineral density (BMD) data in age studies are not free of certain drawbacks. Since it is well established that age-related patterns of BMD changes involve three distinct periods (bone acquisition in youth, stabilization at maturity, and decrease with ageing), adjusting for age via an inappropriate mathematical function may lead to inconsistencies and wrong conclusions. HYPOTHESIS: The piecewise model, which encompasses the above three periods, will accurately describe the BMD dependence on age. OBJECTIVE: To examine age-related patterns of BMD changes using a number of possible mathematical functions and to find among them the best-fitting function. Next, to test whether the chosen function is universally applicable or if there are diverse population-specific functions. MATERIAL AND METHODS: Thirteen ethnic samples from various regions of Europe and Asia, assigned into five ethnic-geographic groups, were examined. The total sample included 2430 males and 2515 females. Compact BMD of hand phalanges was measured by photodensitometry from plain radiographs of each individual studied. Statistical software was developed for the purposes of the present study; this software gave a maximum likelihood of the parameter estimates for various statistical models (functions). RESULTS: In all samples of sufficient size and representative age range, a two-interval function was found as the best fitting and most parsimonious model to describe the BMD age-related changes. This two-interval function was characterized by age-related bone mass increase, positive slope beta(1s) in young age or a plateau (beta(1s) = 0, i.e. no age-related changes) until a sex-specific age threshold, T(0), after which annual bone loss ensued with a slope coefficient beta(2s). Threshold of BMD loss in women of different ethnic groups ranged between 37.85 and 47.77 years, and roughly coincided with perimenopausal age. In males, the age T(0) varied between 27.85 and 49.07 years. The ensuing cortical bone loss appeared to be linear in both sexes, averaging between 0.51% and 1.15% in men and between 0.74% and 1.77% per year of young age BMD value in females. CONCLUSIONS: The change of phalangeal BMD with age may be best described by a two-interval function, regardless of sex and ethnic background. However, specific parameter estimates depend both on gender and ethnic affiliation. This study has yielded a well-fitted model of BMD dependence on age suitable for further use in population studies.

Adolescent↗
PubMed2004

The use of Markov chain Monte Carlo for analysis of correlated binary data: patterns of somatic cells in milk and the risk of clinical mastitis in dairy cows.

Two analytical approaches were used to investigate the relationship between somatic cell concentrations in monthly quarter milk samples and subsequent, naturally occurring clinical mastitis in three dairy herds. Firstly, cows with clinical mastitis were selected and a conventional matched analysis was used to compare affected and unaffected quarters of the same cow. The second analysis included all cows, and in order to overcome potential bias associated with the correlation structure, a hierarchical Bayesian generalised linear mixed model was specified. A Markov chain Monte Carlo (MCMC) approach, that is Gibbs sampling, was used to estimate parameters. The results of both the matched analysis and the hierarchical modelling suggested that quarters with a somatic cell count (SCC) in the range 41,000-100,000 cells/ml had a lower risk of clinical mastitis during the next month than quarters <41,000 cell/ml. Quarters with an SCC >200,000 cells/ml were at the greatest risk of clinical mastitis in the next month. There was a reduced risk of clinical mastitis between 1 and 2 months later in quarters with an SCC of 81,000-150,000 cells/ml compared with quarters below this level. The hierarchical modelling analysis identified a further reduced risk of clinical mastitis between 2 and 3 months later in quarters with an SCC 61,000-150,000 cells/ml, compared to other quarters. We conclude that low concentrations of somatic cells in milk are associated with increased risk of clinical mastitis, and that high concentrations are indicative of pre-existing immunological mobilisation against infection. The variation in risk between quarters of affected cows suggests that local quarter immunological events, rather than solely whole cow factors, have an important influence on the risk of clinical mastitis. MCMC proved a useful tool for estimating parameters in a hierarchical Bernoulli model. Model construction and an approach to assessing goodness of model fit are described.

Animals↗
PubMed1986

Quantitative investigations of different vaccination policies for the control of congenital rubella syndrome (CRS) in the United Kingdom.

The paper examines predictions of the impact of various one-, two- and three-stage vaccination policies on the incidence of congenital rubella syndrome (CRS) in the United Kingdom with the aid of a mathematical model of the transmission dynamics of rubella virus. Parameter estimates for the model are derived from either serological data or case notifications, and special attention is given to the significance of age-related changes in the rate of exposure to rubella infection and heterogeneous mixing between age groups. Where possible, model predictions are compared with observed epidemiological trends. The principal conclusion of the analyses is that benefit is to be gained in the UK, both in the short and long term, by the introduction of a multiple-stage vaccination policy involving high levels of vaccination coverage of young male and female children (at around two years of age) and teenage girls (between the ages of 10-15 years), plus continued surveillance and vaccination of adult women in the child-bearing age classes. Model predictions suggest that to reduce the incidence of CRS in future years, below the level generated by a continuation of the current UK policy (the vaccination of teenage girls), would require high rates of vaccination (greater than 60%) of both boys and girls at around two years of age. Numerical studies also suggest that uniform vaccination coverage levels of greater than 80-85% of young male and female children could, in the long term (40 years or more), eradicate rubella virus from the population. The robustness of these conclusions with respect to the accuracy of parameter estimates and various assumptions concerning the pattern of age-related change in exposure to infections and 'who acquires infection from whom' is discussed.

Adolescent↗
PubMed2004

Trading variance reduction with unbiasedness: the regularized subspace information criterion for robust model selection in kernel regression.

A well-known result by Stein (1956) shows that in particular situations, biased estimators can yield better parameter estimates than their generally preferred unbiased counterparts. This letter follows the same spirit, as we will stabilize the unbiased generalization error estimates by regularization and finally obtain more robust model selection criteria for learning. We trade a small bias against a larger variance reduction, which has the beneficial effect of being more precise on a single training set. We focus on the subspace information criterion (SIC), which is an unbiased estimator of the expected generalization error measured by the reproducing kernel Hilbert space norm. SIC can be applied to the kernel regression, and it was shown in earlier experiments that a small regularization of SIC has a stabilization effect. However, it remained open how to appropriately determine the degree of regularization in SIC. In this article, we derive an unbiased estimator of the expected squared error, between SIC and the expected generalization error and propose determining the degree of regularization of SIC such that the estimator of the expected squared error is minimized. Computer simulations with artificial and real data sets illustrate that the proposed method works effectively for improving the precision of SIC, especially in the high-noise-level cases. We furthermore compare the proposed method to the original SIC, the cross-validation, and an empirical Bayesian method in ridge parameter selection, with good results.

Bayes Theorem↗
PubMed2005

The effect of synchronization on genetic parameters of reproductive traits in dairy cattle.

Genetic evaluation and selection is one strategy for improving female reproductive performance. Many producers use synchronization of ovulation or estrus to manage reproduction. The objective of this study was to examine the effects of reproductive synchronization on genetic parameter estimates of days to first breeding (DFB), days open (DO), and pregnancy rate at 120 d postpartum (PR120). Data were collected from 64 producers participating in an artificial insemination progeny testing program and using Dairy Comp 305 herd management software to record reproductive treatments and events. Data included 18,359 records for DFB and 16,379 records for DO and PR120. Synchronization was classified by breeding codes at time of insemination. The traits DFB and DO were analyzed using a linear model with age at calving, herd-year-season, and parity as fixed effects and sire and residual as random effects. For PR120, a threshold sire model was used with fixed effects as in the DFB and DO models. Three models were applied to the complete data sets of all traits; a base model with no synchronization effect, an expanded model with a fixed synchronization effect, and an interaction model with a random sire by herd management interaction. Herd management categories were based on an individual herd's use of synchronization protocols. Also, data subsets were analyzed separately based on cow synchronization treatment and herd management categories. Synchronized records for DFB had on average 40% higher sire variance and 60% lower residual variance than nonsynchronized records. Heritability for DFB ranged from 0.01 to 0.09. Sire variance was 40% lower for DO and 25% lower for PR120 in first synchronized records than either later-synchronized or nonsynchronized records. Residual variances for DO varied by 3% among cow treatment categories and 14% for herd management categories. Heritabilities ranged from 0.03 to 0.07 for DO and 0.10 to 0.26 for PR120. Including a fixed effect for synchronization in the DO model reduced sire variance by 33% and residual variance by 10%. Sire by herd management interactions were less than 2% of the total variance for all traits. Accounting for synchronization, especially for DFB, may improve accuracy of genetic parameter estimates and animal evaluations.

Analysis of Variance↗
PubMed2006

Neuropsychological outcomes of army personnel following deployment to the Iraq war.

CONTEXT: The effects of war-zone deployment on neuropsychological health remain poorly understood. Neuropsychological performance deficits serve as sensitive measures of neural dysfunction and are often associated with psychosocial and occupational problems. Previous studies have not conducted objective neuropsychological assessments both before and after a major war-zone deployment. OBJECTIVE: To examine objective neuropsychological outcomes of Iraq War deployment in a large military cohort. DESIGN, SETTING, AND PARTICIPANTS: The Neurocognition Deployment Health Study, a prospective, cohort-controlled study conducted at military installations. This report centers on 961 male and female active-duty Army soldiers drawn from the larger cohort. Deploying Army soldiers (n = 654) were examined prior to deployment to Iraq (April-December 2003) and shortly after return (within a mean of 73 days [median, 75 days]; January-May 2005) from Iraq deployment. A comparison group of soldiers (n = 307) similar in military characteristics but not deploying overseas during the study was assessed in sessions timed to be as close as possible to the assessment of deployers. Military unit sampling procedures facilitated representation of combat, combat support, and combat service support functions among both deployers and nondeployers. MAIN OUTCOME MEASURES: Individually administered, performance-based neuropsychological tasks. Estimates (beta; the unstandardized parameter estimate) for the absolute differences in adjusted mean outcome scores between deployed and nondeployed groups were determined using generalized estimating equations. RESULTS: Multiple linear regression analyses adjusted for battalion membership revealed that Iraq deployment, compared with nondeployment, was associated with neuropsychological compromise on tasks of sustained attention (beta = 0.11; P<.001), verbal learning (beta = -1.51; P = .003), and visual-spatial memory (beta = -3.82; P<.001). Iraq deployment was also associated with increased negative state affect on measures of confusion (beta = 1.40; P<.001) and tension (beta = 1.24; P<.001). In contrast, deployment was associated with improved simple reaction time (beta = 4.30; P = .003). Deployment effects remained statistically significant after taking into account deployment-related head injury and stress and depression symptoms. CONCLUSIONS: Deployment to Iraq is associated with increased risk of neuropsychological compromise. Findings point to the need to investigate further the impact of deployment on neural functioning. Public health implications include consideration of neuropsychological compromise in health prevention and postdeployment clinical and occupational management.

Adult↗
PubMed1998

Longitudinal analysis of deciduous tooth emergence: II. Parametric survival analysis in Bangladeshi, Guatemalan, Japanese, and Javanese children.

We present a form of parametric survival analysis that incorporates exact, interval-censored, and right-censored times to deciduous tooth emergence. The method is an extension of common cross-sectional procedures such as logit and probit analysis, so that data arising from mixed longitudinal and cross-sectional studies can be properly combined. We extended the method to incorporate and estimate a proportion of agenic teeth. While we concentrate on deciduous tooth emergence, the method is relevant to studies of permanent tooth emergence and other developmental events. Deciduous tooth emergence data were analyzed from four longitudinal studies. The samples are 1,271 rural Guatemalan children examined every three months up to age two and every six months thereafter as part of the INCAP study; 397 rural Bangladeshi children examined monthly to age one and quarterly thereafter as part of the Meheran Growth and Development Study; 468 rural Indonesian children examined monthly as part of the Ngaglik study; and 114 urban Japanese children examined monthly in studies from 1910 and 1920. Although all four studies were longitudinal, many observations from the Guatemala and Bangladesh studies were effectively cross-sectionally observed. Three different parametric forms were used to model the eruption process: a normal distribution, a lognormal distribution, and a lognormal distribution with age shifted to shortly after conception. All three distributions produced reliable estimates of central tendencies, but the shifted lognormal distribution produced the best overall estimates of shape (variance) parameters. Estimates of emergence were compared to other studies that used similar methods. Japanese children showed relatively fast emergence times for all teeth. Bangladeshi and Javanese children showed emergence times that were slower than are found in most previous studies. Estimates of agenesis were not significantly different from zero for most teeth. One or two central incisors showed significant agenesis that ranged from 0.1 to 0.8% in three of the samples; even so, failure to model the agenic proportion did not seriously bias the estimates.

Bangladesh↗
PubMed2006

A kinetic study of lipase-catalyzed reversible kinetic resolution involving verification at miniplant-scale.

Lipase-catalyzed kinetic resolution of racemates is a popular method for synthesis of chiral synthons. Most of these resolutions are reversible equilibrium limited reactions. For the first time, an extensive kinetic model is proposed for kinetic resolution reactions, which takes into account the full reversibility of the reaction, substrate inhibition by an acyl donor and an acyl acceptor as well as alternative substrate inhibition by each enantiomer. For this purpose, the reversible enantioselective transesterification of (R/S)-1-methoxy-2-propanol with ethyl acetate catalyzed by Candida antarctica lipase B (CAL-B) is investigated. The detailed model presented here is valid for a wide range of substrate and product concentrations. Following model discrimination and the application of Haldane equations to reduce the degree of freedom in parameter estimation, the 11 free parameters are successfully identified. All parameters are fitted to the complete data set simultaneously. Six types of independent initial rate studies provide a solid data basis for the model. The effect of changes in substrate and product concentration on reaction kinetics is discussed. The developed model is used for simulations to study the behavior of reaction kinetics in a fixed bed reactor. The typical plot of enantiomeric excess versus conversion of substrate and product is evaluated at various initial substrate mixtures. The model is validated by comparison with experimental results obtained with a fixed bed reactor, which is part of a fully automated state-of-the-art miniplant.

Enzymes, Immobilized↗
PubMed2007

Estimating the predictive quality of dose-response after model selection.

Prediction of dose-response is important in dose selection in drug development. As the true dose-response shape is generally unknown, model selection is frequently used, and predictions based on the final selected model. Correctly assessing the quality of the predictions requires accounting for the uncertainties caused by the model selection process, which has been difficult. Recently, a new approach called data perturbation has emerged. It allows important predictive characteristics be computed while taking model selection into consideration. We study, through simulation, the performance of data perturbation in estimating standard error of parameter estimates and prediction errors. Data perturbation was found to give excellent prediction error estimates, although at times large Monte Carlo sizes were needed to obtain good standard error estimates. Overall, it is a useful tool to characterize uncertainties in dose-response predictions, with the potential of allowing more accurate dose selection in drug development. We also look at the influence of model selection on estimation bias. This leads to insights into candidate model choices that enable good dose-response prediction.

Bias↗
PubMed1985

Estimation of parameters affecting the uptake of 99mTc-methylenediphosphonate in rat femur with model simulation.

The uptake of 99mTc-methylenediphosphonate (MDP) in different parts of rat femur was simulated using a local three-space model for tracer transfer. The model consisted of bone blood, bone ECF-space and space for tracer deposition. The measured 99mTc-MDP concentration in the systemic blood and the local bone blood flow measured by 131I-macroaggregated albumin microspheres were used as input parameters. The measured blood flow values were 6.3, 3.1 and 15.3 ml/100 g/min for proximal, middle and distal femur, respectively. The model parameters that gave the best fit to measured 99mTc-MDP uptake curves in computer simulation showed that bone blood flow, volume of ECF-space, permeability surface area product and accretion constant from ECF-space to space for tracer deposition were highest in distal and lowest in middle femur. The values corresponded to peak extraction fractions of 0.38, 0.62, and 0.31 for proximal, middle and distal femur, respectively. We conclude that the simulation gives acceptable model parameters, and indicates applicability of a similar model into clinical quantitative bone scintigraphy.

Animals↗
PubMed1992

Evaluation of two unstructured mathematical models for the penicillin G fed-batch fermentation.

The mathematical model for the penicillin G fed-batch fermentation proposed by Heijnen et al. (1979) is compared with the model of Bajpai & Reuss (1980). Although the general structure of these models is similar, the difference in metabolic assumptions and specific growth and production kinetics results in a completely different behaviour towards product optimization. A detailed analysis of both models reveals some physical and biochemical shortcomings. It is shown that it is impossible to make a reliable estimation of the model parameters, only using experimental data of simple constant glucose feed rate fermentations with low initial substrate amount. However, it is demonstrated that some model parameters might be key factors in concluding whether or not altering the substrate feeding strategy has an important influence on the final amount of product. It is illustrated that feeding strategy optimization studies can be a tool in designing experiments for parameter estimation purposes.

Fermentation↗
PubMed1994

Genetic and environmental influences on early childhood behavior.

The Child Behavior Checklist for Ages 2-3 (Adelbach et al., J. Abnorm. Child Psychol. 15;629-650; 1987) was completed by mothers of 229 pairs of twins (mean age = 33 months). Using the two broad-band groupings of Internalizing and Externalizing described by Achenbach et al. (1987), various models to estimate genetic and environmental parameters were fitted using LISREL 7. Model-fitting results showed that the genetic components to the observed phenotypical variation were small and not necessary in the model. Influences from the shared environment, however, could not be dropped from the model without a deterioration in fit. Parameter estimates were not significantly different in boys and girls.

Child Behavior↗