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At least 217 records · Page 12Linked to original sources
PubMed1988

Relationships among growth hormone and prolactin secretory parameter estimates in Holstein bulls and their predicted differences for lactational traits.

Selection of dairy sires is based on the production records of their female ancestors, half-sibs and daughters. No trait expressed by the sire is used. Concentrations of growth hormone (GH) and prolactin (PRL), hormones produced in both males and females that are fundamental in lactation, may be correlated with production. A study was conducted to determine whether measures of these hormones in the sire would be useful predictors of lactational ability of daughters. Blood samples were collected at 15-min intervals for 8 h from 26 Holstein bulls (5.5 yr of age) that had one progeny summary available. Plasma concentrations of GH and PRL were quantified and the mean and baseline concentrations and the frequency and mean amplitude of the secretory peaks were determined for each bull. Concentrations among these values and bulls' predicted differences (PD) were determined. Significant negative correlations were detected for frequency of GH peaks and PD for yield of milk, fat and protein; correlations were positive for PRL baseline concentrations and PD for fat and protein (P less than .10), and correlations were negative for frequency of PRL peaks and PD for milk, fat and protein (P less than .10). Addition of estimates of bull hormone secretory parameters to breeding values based on performance of relatives considerably improved the accuracy (R2) for predicting progeny performance from sire information. Certain characteristics of the patterns of GH and PRL secretion may be heritable and aid in identification of superior dairy animals.

Animals↗
PubMed1990

Transducer characterization from pressure amplitude distribution measurements using a Kalman filter as parameter estimation algorithm.

The amplitude and frequency contents of a received ultrasound pulse depends on the spatial pressure amplitude distribution of the sound field, as produced by the transducer in the medium, and on the position and orientation of the reflecting surface in this field. Often, the geometry of the reflecting surface and the acoustical properties of the medium are known or can be estimated. Then it is practical to determine the transducer parameters in order to calculate the distortion of a reflected ultrasound pulse. Apart from geometrical parameters such as size and mechanical focusing, the surface velocity amplitude distribution (SVAD) of a transducer is of major importance. For some transducer configurations this SVAD may be described with a limited number of parameters. This paper presents a method, based on a Kalman filter algorithm, to assess the transducer parameters by measurement of the spatial sound field pressure amplitude distribution in various planes for different emission frequencies. Comparison of the measured pressure amplitudes with those calculated using the estimated values of the parameters shows that this method yields reliable results.

Acoustics↗
PubMedDate not supplied

Identifiability and parameter estimation.

In experiments on biological systems one often cannot measure all state variables (compartments). Given a particular experiment of that type, a basic kinetic parameter may have no effect on the observations; such a parameter is an insensible parameter for that experiment. A parameter may influence the observations and not be uniquely determinable; such a parameter is nonidentifiable for that experiment. Only identifiable parameters can be estimated uniquely, by that experiment. I review the basic theory to check identifiability for a nominal value of a parameter (local identifiability), and present some examples of problems that may arise in estimation.

Kinetics↗
PubMed1983

Simulation of calcium homeostasis: modeling and parameter estimation.

The system that regulates plasma calcium in the bird has been formalized into a model based on a series of differential equations and solved by computer simulation. Bone, kidney, and intestine have been considered as the control subsystems, with parathyroid hormone and 1,25-dihydroxycholecalciferol as the regulating hormones. The parameters used in the simulation model have been computed either from published results or by specifically designed experiments described here. For the estimation of parameters, an iterative procedure has been developed that was designed to minimize the sum of square errors between observed and system-simulated values. Parameters of 1,25-dihydroxycholecalciferol metabolism were experimentally obtained from the kinetic behavior of the 3H-labeled hormone in rachitic birds after a single dose. Model parameters have been adjusted using the results of in vivo calcium loading and validated by an EDTA infusion experiment. The simulation model has been used to study the hierarchy of the activities of the three control subsystems and of the regulating hormones, at different calcium intakes. Positive or negative errors in plasma calcium resulted in an asymmetry in the activities of the controlling systems, bone and kidney, whereas the intestine is characterized by its relatively long response time.

Animals↗
PubMed2000

Lumped parameter estimation for the embryonic chick vascular system: a time-domain approach using MLAB.

We have evaluated several lumped parameter analog models for the early chick embryonic vascular system that may be used to infer loading characteristics of the developing heart. We measured dorsal aortic pressure and flow simultaneously with a servo-null pressure system and a pulsed Doppler velocimeter. Four different analog circuit models were chosen for comparisons. We formulated the time-domain differential equations specifying the relations between pressure and flow in the models, and then estimated the lumped parameters that produced the best fit. The MLAB mathematical modeling software was used for solving differential equations, and for minimizing the difference between model-predicted values and experimental data. The traditional three-element Windkessel model with an added inductance term was most often the best-fitting model. This is compatible with the previous study using a frequency-domain approach. The procedures developed for the current study are adaptable for the study of a variety of nonlinear models, and distributed parameter models for mammalian cardiovascular development with mechanically, pharmacologically, or genetically altered conditions.

Analog-Digital Conversion↗
PubMed1998

Simulation and parameter estimation study of a simple neuronal model of rhythm generation: role of NMDA and non-NMDA receptors.

Simple neural network models of the Xenopus embryo swimming CPG, based on the one originally developed by Roberts and Tunstall (1990), were used to investigate the role of the voltage-dependent N-methyl-D-aspartate (NMDA) receptor channels, in conjunction with faster non-NMDA components of synaptic excitation, in rhythm generation. The voltage-dependent NMDA current "follows" the membrane potential, leading to a postinhibitory rebound that is more efficient than one without voltage dependency and allows neurons to fire more than one action potential per cycle. Furthermore, the model demonstrated limited rhythmic activity in the absence of synaptic inhibition, supporting the hypothesis that the NMDA channels provide a basic mechanism for rhythmicity. However, the rhythmic properties induced by the NMDA current were observed only when there was moderate activation of the non-NMDA synaptic channels, suggesting a modulatory role for this component. The simulations also show that the voltage dependency of the NMDA conductance, as well as the fast non-NMDA current, stabilizes the alternation pattern versus synchrony. To verify that these effects and their implications on the mechanism of swimming and transition to other types of activity take place in the real preparation, constraints on parameter values have to be specified. A method to estimate synaptic parameters was tested with generated data. It is shown that a global analysis, based on multiple iterations of the optimization process (Foster et al., 1993), gives a better understanding of the parameter subspace describing network activity than a standard fit with a sensitivity analysis for an individual solution.

Animals↗
PubMedDate not supplied

Kinetic parameters estimation for ascorbic acid degradation in fruit nectar using the Partial Equivalent Isothermal Exposures (PEIE) method under non-isothermal continuous heating conditions.

With the purpose of testing the Paired Equivalent Isothermal Exposures (PEIE) method to determine reaction kinetic parameters under non-isothermal conditions, continuous pasteurizations were carried out with a tropical fruit nectar [25% cupuaçu (Theobroma grandiflorum) pulp and 15% sugar] to estimate the ascorbic acid thermal degradation kinetic parameters. Fifteen continuous thermal exposures were studied, with seven being cycled. The experimental ascorbic acid thermal degradation kinetic parameters were estimated by the PEIE method (E(a) = 73 +/- 9 kJ/mol, k(8)(0)( degrees )(C) = 0.017 +/- 0.001 min(-)(1)). These values compared very well to the previously determined values for the same product under isothermal conditions (E(a) = 73 +/- 7 kJ/mol, k(8)(0)( degrees )(C) = 0.020 +/- 0.001 min(-)(1)). The predicted extents of reaction presented a good fit to the experimental data, although the cycled thermal treatments presented some deviation. In addition to being easier and faster than the Isothermal method, the PEIE method can be a more reliable method to estimate first-order reaction kinetic parameters when continuous heating is considered.

Ascorbic Acid↗
PubMed1984

A model of intestinal iron absorption and plasma iron kinetics: optimal parameter estimates for normal dogs.

A multicompartment model describing the physiological processes of intestinal iron absorption has been developed. The model accounts for uptake by the intestinal mucosa of iron in the lumen, followed by either iron incorporation into a mucosal storage pool (presumably ferritin) or direct iron transfer to the plasma. To enable analysis of iron absorption from noninvasive measurements, plasma iron kinetics were also analyzed. The model was validated in studies of three beagle dogs given oral 59Fe-citrate and intravenous 55Fe-transferrin simultaneously. Model parameters were estimated from the best (least-squares) fit of the model outputs to the tracer iron activity in venous blood samples and in the whole body. The parameter values show that both incorporation of iron into the mucosal storage pool and transfer of iron from the mucosa to the plasma occur at rates approximately 100 times greater than mucosal uptake of iron from the gut lumen. Further, release of iron from mucosal storage, while measurable, occurs at a slow rate. The study demonstrates the practicality of this noninvasive approach for the simultaneous study of iron absorption and plasma iron kinetics.

Animals↗
PubMed1995

Hemodynamic parameter estimation from ocular fluorescein angiograms.

BACKGROUND: A method is proposed for parameterizing choroidal blood flow from fluorescein angiograms. METHODS: After digitizing and aligning the angiographic sequence, the intensity build-up curves of fluorescence are analysed per pixel (approx. 10 microns in fundo). Two models are compared. A one-compartment model predicts an exponential build-up curve, from which the following parameters are estimated: maximum fluorescence, dye appearance time and local perfusion rate (reciprocal of the time constant of the exponential). To account for the contribution of the systemic circulation to the shape of the build-up curve, a two-compartment model is used which predicts a bi-exponential curve. RESULTS: Introduction of the second (systemic) compartment resulted in a significant improvement of fit in 37 of 48 patients studied. The rate constants of the systemic compartment found were mainly in the range of 0.30-1.00 s-1. CONCLUSION: For the individual patient, the local perfusion rates may vary strongly, with lower perfusion rates possibly being of prognostic value for ocular diseases such as glaucoma or diabetic retinopathy.

Blood Flow Velocity↗
PubMed1999

Modelling and parameter estimation of the enzymatic synthesis of oligosaccharides by beta-galactosidase from bacillus circulans

The aim of this research is to develop a model to describe oligosaccharide synthesis and simultaneously lactose hydrolysis. Model A (engineering approach) and model B (biochemical approach) were used to describe the data obtained in batch experiments with beta-galactosidase from Bacillus circulans at various initial lactose concentrations (from 0.19 to 0.59 mol.kg(-1)). A procedure was developed to fit the model parameters and to select the most suitable model. The procedure can also be used for other kinetically controlled reactions. Each experiment was considered as an independent estimation of the model parameters, and consequently, model parameters were fitted to each experiment separately. Estimation of the parameters per experiment preserved the time dependence of the measurements and yielded independent sets of parameters. The next step was to study by ordinary regression methods whether parameters were constant under the altering conditions examined. Throughout all experiments, the parameters of model B did not show a trend upon the initial lactose concentration when inhibition was included. Therefore model B, a galactosyl-enzyme complex-based model, was chosen to describe the oligosaccharide synthesis, and one parameter set was determined for various initial lactose concentrations. Copyright 1999 John Wiley & Sons, Inc.

Journal Article↗
PubMed1981

HPLC-analysis and preliminary pharmacokinetic parameter estimations of chloroquine.

An HPLC method for the separate determination of chloroquine and its major metabolites has been developed. Separation was on an octadecyl RP column. Fluorimetric detection followed after on-line post-column buffering of the mobile phase to pH = 9.25. The method is highly selective for the compounds of interest with a detection limit down to 1 ng/ml. Preliminary data on the pharmacokinetics of chloroquine are reported, as obtained with this method. Kinetic parameters were estimated with the aid of the non-linear regression computer programme NON-LIN.

Chloroquine↗
PubMed1986

Logistic curve fitting and parameter estimation using nonlinear noniterative least-squares regression analysis.

A microcomputer program has been developed for the fitting of the logistic curve to biological, medical, and other experimental data. In addition to supplying estimates for all of the logistic curve parameters, the program provides the fitted result for each input datum thus allowing for the immediate assessment of the logistic curve and detection of possible outliers.

Biometry↗
PubMed1990

Parameter estimation in a three-compartment model for blood alcohol curves.

Models of alcohol input and absorption are crucial to the description and understanding of the effects of alcohol in the human body. In this paper, the pharmacokinetics of alcohol after oral administration are described by a three-compartment model with a supposed concentration-dependent absorption and elimination. The absorption of alcohol from the small intestine into the blood is represented by a first-order rate constant ka. To describe the delay in peak concentration of alcohol the gastric emptying rate is represented as a first-order parameter with a feedback control depending on the amount of alcohol remaining in the stomach. The alcohol ingestion can then be represented as a bolus input. The elimination process is described by a model similar to the Michaelis-Menten model for enzyme kinetics. Parameters are estimated by means of an iterative algorithm minimizing a non-linear function. A good fit of the model was obtained for blood alcohol curves from six men and six women who each had received an alcohol dose of 28.5 g on three consecutive days. It is concluded that the model can be recommended to describe adequately the absorption and elimination of alcohol.

Adult↗
PubMed1998

Predicting the radiation control probability of heterogeneous tumour ensembles: data analysis and parameter estimation using a closed-form expression.

A closed-form formula describing the tumour control probability (tcp) of a heterogeneous collection of tumours has been obtained by analytically averaging the homogeneous double-exponential tcp formula over inter-tumour distributions of clonogen radiosensitivity, density and repopulation rate, tumour volume and dose. The formula can be straightforwardly and relatively quickly fitted to clinical data, yielding radiobiological parameter values for use in tcp modelling. The formula was fitted to published tcp data which catalogued tumour control records grouped by dose and tumour volume, and treatment duration. Fitted parameter values, confidence intervals and goodness-of-fit statistics were determined. The sets of parameter values obtained are unique only to within a scaling factor. The formula provides non-rejectable fits to data which grouped tcp by dose and volume when radiosensitivity parameters take values close to laboratory estimates, the fitted volume dependence parameter, however, taking rather high values. Good fits are obtainable with the intuitively reasonable volume parameter value of one, but with radiosensitivity values around one-third of their laboratory estimates. Non-rejectable fits to data which grouped tcp by dose and treatment duration may be obtained with radiosensitivity and repopulation rate parameters lying close to laboratory estimates.

Breast Neoplasms↗
PubMed1993

On the covariance between parameter estimates in models of twin data.

We study the covariance between estimates of additive genetic variance and either dominance genetic variance or common environmental variance in likelihood-based twin analyses. The central tools used in these investigations are the asymptotic covariances of variance component estimates, which we present for several commonly used twin models. We first illustrate the use of the asymptotic covariance terms for determining the optimal ratio of monozygotic to dizygotic group sample sizes for a twin study. We then focus attention on the asymptotic correlations between estimates of additive genetic variance, and either dominance genetic variance or common environmental variance, and their use in understanding when parameters are efficiently estimable from twin data. The results of this investigation are confirmed by simulation studies, and highlight inherent limitations of the twin model, in the sense that having only twin data limits the ability to detect individual variance components. Finally, remarks on possible alternative statistical methods are given, and results are presented to illustrate the improvements in efficiency that are possible with additional family data. In particular, the results provide insight into the limitations of inference from twin data.

Analysis of Variance↗
PubMed1995

Accuracy of noncompartmental pharmacokinetic parameters estimated from bolus injection and steady-state infusion data.

A Monte Carlo simulation study was carried out to examine the accuracy of parameters derived from curve moments. Impulse response (IR) and washout (WO) concentration-time curves, based on a triexponential model, were analyzed by numerical integration and regression analysis. Both designs were tested according to their robustness to measurement error and model misspecification. Performance of the methods was judged using the median error (ME) and the median absolute error (MAE) of 1000 simulations. The WO design provided better estimates of mean disposition residence time and worse estimates of the normalized variance of disposition residence times (CVD2) than its rival. At 20% measurement noise, the MAE of CVD2 was less than 13%. The WO design was much more robust to model misspecification. Numerical integration performed as good as, or better than, regression analysis. Both methods are very sensitive to tail-area error, meaning that special attention needs to be paid to this aspect of experimental design. This study demonstrates that it is possible to obtain good estimates of higher moment parameters in a well-designed experiment.

Models, Theoretical↗
PubMedDate not supplied

Robust nonlinear autoregressive moving average model parameter estimation using stochastic recurrent artificial neural networks.

In this study, we introduce a new approach for estimating linear and nonlinear stochastic autoregressive moving average (ARMA) model parameters, given a corrupt signal, using artificial recurrent neural networks. This new approach is a two-step approach in which the parameters of the deterministic part of the stochastic ARMA model are first estimated via a three-layer artificial neural network (deterministic estimation step) and then reestimated using the prediction error as one of the inputs to the artificial neural networks in an iterative algorithm (stochastic estimation step). The prediction error is obtained by subtracting the corrupt signal of the estimated ARMA model obtained via the deterministic estimation step from the system output response. We present computer simulation examples to show the efficacy of the proposed stochastic recurrent neural network approach in obtaining accurate model predictions. Furthermore, we compare the performance of the new approach to that of the deterministic recurrent neural network approach. Using this simple two-step procedure, we obtain more robust model predictions than with the deterministic recurrent neural network approach despite the presence of significant amounts of either dynamic or measurement noise in the output signal. The comparison between the deterministic and stochastic recurrent neural network approaches is furthered by applying both approaches to experimentally obtained renal blood pressure and flow signals.

Algorithms↗
PubMed1986

Kinetic model of glucose-6-phosphate dehydrogenase from red blood cells. Parameter estimation from progress curves and simulation of regulatory properties.

A kinetic model of human and mouse glucose-6-phosphate dehydrogenase is presented which takes into account the substrates and all inhibitors of significant importance in the red cell. The parameter values were estimated by analysis of progress curves. The applicability of a new method based on non-linear regression to complex enzyme kinetics was proved. The in vivo-regulation of glucose-6-phosphate dehydrogenase is examined by determining elasticity coefficients and by using simple simulation experiments. The model is convenient to describe the behaviour of enzyme activity under physiological conditions.

Adenosine Triphosphate↗