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PubMed1981

Interactions among ventilation, the circulation, and the uptake and distribution of halothane--use of a hybrid computer multiple model: I. The basic model.

The authors describe an 18-compartment hybrid computer multiple model of the uptake and distribution of halothane. This model uses 88 equations and 124 parameter settings. Three submodels are incorporated into the basic model: 1) The mass transport of halothane is simulated on the digital portion of the hybrid computer. 2) A breath-by-breath pulmonary model with two compartments describes air pressure-flow relations in the airway system. 3) A beat-to-beat cardiovascular model with 15 compartments describes in detail blood pressure-flow relations. In addition, a baroreceptor-heart rate loop is included: an increase in arterial pressure causes a decrease in heart rate. The slope of the baroreceptor response is progressively decreased by halothane until at 2 per cent there is no response. The model of halothane uptake and distribution is separate from the blood and air pressure-flow models, but is, in effect, driven by them. Myocardial "contractility" (stroke volume) and certain regional vascular resistances can be affected by the concentration of halothane in one or any proportion of any combination of three compartments: arterial blood (arteriolar concentrations), cerebral gray matter, or myocardial. In turn, these factors significantly affect the uptake and distribution of halothane. The responses to three steady-state concentration, as well as to a step change in concentration from 0 to 2 per cent, were examined. Twenty-four outputs were recorded, including halothane concentrations in ten compartments; myocardial "contractility"; left and right ventricular and right atrial pressures; cardiac output; stroke volume, R-R interval; and blood flows in six regions. Two variables--alveolar concentration of halothane and arterial blood pressure--were recorded during a step change of 0 to 5 per cent. The model describes the appropriate steady-state and dynamic cardiovascular responses to halothane. It also demonstrates the complex interrelationships among caridac output, regional blood flow distribution, and the uptake and distribution of halothane. During step change in halothane concentration, most of the responses occur early, a phenomenon also seen in man and goats. Thus, the model is useful not only for representing organ and tissue halothane concentrations, but also for gaining new insights into cardiovascular alterations produced by rapidly changing concentrations of halothane and into the complex interactions between the circulation and the uptake and distribution of halothane.

Anesthesia, Inhalation↗

PubMed1995

Testing the conservativeness of a screening model in a model validation exercise.

Although models for calculating derived emission limits have been around for many years, the opportunity to test them against independent data sets did not arise until the Biospheric Model Validation Study (BIOMOVS) was organized in 1985. Within BIOMOVS, two scenarios tested predictions of the movement of 131I and 137Cs from air to soil, pasture, milk, and beef. One of these scenarios was a model intercomparison of a chronic release over 30 y. The second scenario, using data gathered world-wide after the Chernobyl accident, allowed predictions to be compared directly with observations. The Canadian Standards Association's Guidelines for Calculating Derived Release Limits for Radioactive Material in Airborne and Liquid Effluents for Normal Operation of Nuclear Facilities was tested in both these scenarios to see whether its predictions were suitably conservative, as they should be for a screening model. A comparison was made between results of the Canadian Standards Association's model and those of other screening models on the one hand and results of models attempting to predict best estimates on the other hand. This analysis shows that often screening models are not conservative, and thus there should be much more effort to test the models against observations.

Air Pollutants, Radioactive↗

PubMed1998

Effect of conductivity uncertainties and modeling errors on EEG source localization using a 2-D model.

This paper presents a sensitivity study of electroencephalography-based source localization due to errors in the head-tissue conductivities and to errors in modeling the conductivity variation inside the brain and scalp. The study is conducted using a two-dimensional (2-D) finite element model obtained from a magnetic resonance imaging (MRI) scan of a head cross section. The effect of uncertainty in the following tissues is studied: white matter, gray matter, cerebrospinal fluid (CSF), skull, and fat. The distribution of source location errors, assuming a single-dipole source model, is examined in detail for different dipole locations over the entire brain region. We also present a detailed analysis of the effect of conductivity on source localization for a four-layer cylinder model and a four-layer sphere model. These two simple models provide insight into how the effect of conductivity on boundary potential translates into source location errors, and also how errors in a 2-D model compare to errors in a three-dimensional model. Results presented in this paper clearly point to the following conclusion: unless the conductivities of the head tissues and the distribution of these tissues throughout the head are modeled accurately, the goal of achieving localization accuracy to within a few millimeters is unattainable.

Brain↗

PubMed1998

A model for binaural response properties of inferior colliculus neurons. I. A model with interaural time difference-sensitive excitatory and inhibitory inputs.

A model was developed that simulates the binaural response properties of low-frequency inferior colliculus (IC) neurons in response to several types of stimuli. The model incorporates existing models for auditory-nerve fibers, bushy cells in the cochlear nucleus, and cells in medial superior olive (MSO). The IC model neuron receives two inputs, one excitatory from an ipsilateral MSO model cell and one inhibitory from a contralateral MSO model cell. The membrane potential of the IC model neuron (and the other model neurons) is described by Hodgkin-Huxley type equations. Responses of IC neurons are simulated for pure-tone stimuli, binaural beat stimuli, interaural phase-modulated tones, single binaural clicks, and pairs of binaural clicks. The simulation results show most of the observed properties of IC discharge patterns, including the bimodal and unimodal interaural time difference (ITD) functions, sensitivities to direction and rate of change of ITD, ITD-dependent echo suppression, and early and late inhibitions in response to clicks. This study demonstrates that these response properties can be generated by a simple model incorporating ITD-dependent excitation and inhibition from binaural neurons.

Acoustic Stimulation↗

PubMed1998

A model for binaural response properties of inferior colliculus neurons. II. A model with interaural time difference-sensitive excitatory and inhibitory inputs and an adaptation mechanism.

The inferior colliculus (IC) model of Cai et al. [J. Acoust. Soc. Am. 103, 475-493 (1998)] simulated the binaural response properties of low-frequency IC neurons in response to various acoustic stimuli. This model, however, failed to simulate the sensitivities of IC neurons to dynamically changing temporal features, such as the sharpened dynamic interaural phase difference (IPD) functions. In this paper, the Cai et al. (1998) model is modified such that an adaptation mechanism, viz., an additional channel simulating a calcium-activated, voltage-independent potassium channel which is responsible for afterhyperpolarization, is incorporated in the IC membrane model. Simulations were repeated with this modified model, including the responses to pure tones, binaural beat stimuli, interaural phase-modulated stimuli, binaural clicks, and pairs of binaural clicks. The discharge patterns of the model in response to current injection were also studied and compared with physiological data. It was demonstrated that this model showed all the properties that were simulated by the Cai et al. (1998) model. In addition, it showed some properties that were not simulated by that model, such as the sharpened dynamic IPD functions and adapting discharge patterns in response to current injection.

Acoustic Stimulation↗

PubMedDate not supplied

Application of multiple modelling to hyperthermia estimation: reducing the effects of model mismatch.

Multiple model estimation is a viable technique for dealing with the spatial perfusion model mismatch associated with hyperthermia dosimetry. Using multiple models, spatial discrimination can be obtained without increasing the number of unknown perfusion zones. Two multiple model estimators based on the extended Kalman filter (EKF) are designed and compared with two EKFs based on single models having greater perfusion zone segmentation. Results given here indicate that multiple modelling is advantageous when the number of thermal sensors is insufficient for convergence of single model estimators having greater perfusion zone segmentation. In situations where sufficient measured outputs exist for greater unknown perfusion parameter estimation, the multiple model estimators and the single model estimators yield equivalent results.

Body Temperature↗

PubMed1999

On the dangers of averaging across observers when comparing decision bound models and generalized context models of categorization.

Averaging across observers is common in psychological research. Often, averaging reduces the measurement error and, thus, does not affect the inference drawn about the behavior of individuals. However, in other situations, averaging alters the structure of the data qualitatively, leading to an incorrect inference about the behavior of individuals. In this research, the influence of averaging across observers on the fits of decision bound models (Ashby, 1992a) and generalized context models (GCM; Nosofsky, 1986) was investigated through Monte Carlo simulation of a variety of categorization conditions, perceptual representations, and individual difference assumptions and in an experiment. The results suggest that (1) averaging has little effect when the GCM is the correct model, (2) averaging often improves the fit of the GCM and worsens the fit of the decision bound model when the decision bound model is the correct model, (3) the GCM is quite flexible and, under many conditions, can mimic the predictions of the decision bound model, whereas the decision bound model is generally unable to mimic the predictions of the GCM, (4) the validity of the decision bound model's perceptual representation assumption can have a large effect on the inference drawn about the form of the decision bound, and (5) the experiment supported the claim that averaging improves the fit of the GCM. These results underscore the importance of performing single-observer analysis if one is interested in understanding the categorization performance of individuals.

Bias↗

PubMed1985

Stochastic model of human granulocyte-macrophage progenitor cell proliferation and differentiation. I. Setting up the model.

A mathematical model is constructed for the proliferation and differentiation of granulocyte-macrophage progenitor cells in response to the specific proliferation/differentiation stimulus granulocyte-macrophage colony stimulating activity (gm-CSA). The major objective of this model was to test an earlier conceptual model in which we proposed that clone size potential and sensitivity to gm-CSA are functional properties of granulocyte-macrophage progenitor cells, properties that gradually change as the cells differentiate down the granulocyte-monocyte pathway. Another aim was to provide a tool for further analysis of the regulation of granulopoiesis and granulocyte-macrophage progenitor cell proliferation and differentiation. To formulate and then test the mathematical model, available experimental data were divided, one part being used to construct the model, and the other, the results of different and independent experiments, being used for model validation. This report describes the mathematical model and the estimation of model parameters using in vitro experimental results on the relationship between clone number and gm-CSA concentration and on the clone size distributions obtained under conditions of maximal stimulation by gm-CSA. The accompanying article shows how the model was then tested using data from three other types of experiment.

Cell Differentiation↗

PubMed1996

Risk modeling in acute renal failure requiring dialysis: the introduction of a new model.

Predicting patient outcome in acute renal failure has become increasingly important as technology advances and ethical questions arise concerning life supporting therapies. We propose a new model which uses mortality as an endpoint and may be applied to the acute renal failure patient in the ICU setting who requires dialysis. This model is based on our ICU acute renal failure registry and has been prospectively validated for our institution. Our registry for the purposes of developing this model consists of data from 512 ICU patients requiring acute dialysis from 1988 until 1992. The model was developed by testing a variety of potential risk factors for mortality in a univariate analysis (Student's t-test and Chi square), and those factors found to be significant (p < 0.05) were subsequently tested in a multivariate fashion. The factors found significant included male gender, respiratory failure requiring intubation, hematologic dysfunction (platelet count < 50,000, leukocyte count < 2,500, or bleeding diathesis), bilirubin < 2.0 mg/dl, the absence of surgery, serum creatinine on the first dialysis treatment day, an increasing number of failed organ systems, and an increased BUN from the time of admission. Weights are assigned to each variable based on the odds ratio, and a score is generated with a range of 0 to 20. The initial data for the registry demonstrates good fit using the Hosmer and Lemeshow goodness-of-fit table. The model is next validated in 88 patients from 1993 through February 1994, then prospectively tested in 35 additional patients using a standard data collection form, and the model continues to demonstrate good fit. Although this model has been prospectively validated at our institution, this model or any such predictive model should be used with caution if not independently validated at any institution which proposes its use.

Acute Kidney Injury↗

PubMed1997

Large scale protein modelling and model repository.

Knowledge-based molecular modelling of proteins has proven useful in many instances including the rational design of mutagenesis experiments, but it has been generally limited by the availability of expensive computer hardware and software. To overcome these limitations, we have developed the SWISS-MODEL server for automated knowledge-based protein modelling. The SWISS-MODEL server uses the Brookhaven Protein Data Bank as a source of structural information and automatically generates protein models for sequences which share significant similarities with at least one protein of known 3D-structure. We now use the software framework of the server to generate large collections of protein models. To store these models, we have established the SWISS-MODEL Repository, a new database for protein models generated by theoretical approaches. This repository is directly integrated with SWISS-PROT and other databases through the ExPASy World-Wide Web server (URL is http:(/)/www.expasy.ch).

Amino Acid Sequence↗

PubMed1998

Anticonvulsant drug effects in the direct cortical ramp-stimulation model in rats: comparison with conventional seizure models.

A modified cortical ramp stimulation (CRS) model has been developed allowing repeated determinations of seizure threshold at short time intervals in individual rats without inducing postictal threshold increases. Anticonvulsant potency of the standard antiepileptic drugs carbamazepine, phenytoin, phenobarbital, valproate, diazepam and ethosuximide in the CRS model was compared with respective drug potencies in two more traditional seizure models with transcorneal stimulus application, i.e., the minimal electroshock seizure threshold (minEST) and the maximal electroshock seizure threshold (maxEST). In the CRS model, two different types of threshold were determined, the threshold for localized seizures (TLS) and the threshold for generalized seizures (TGS). When screw electrodes were implanted over the primary motor cortex, TLS was characterized by unilateral forelimb clonus, tonic abduction of contralateral forelimb, and head adversion. When ramp-shaped stimulation was continued above the TLS current, bilateral clonic forelimb seizures with loss of posture developed, which was defined as TGS. In contrast to TLS, TGS could not be repeatedly determined at short time intervals because of postictal threshold increase. TLS was dose-dependently increased by carbamazepine, phenobarbital, valproate and diazepam, although phenytoin showed a truncated dose-response, and ethosuximide was ineffective. In comparison to TLS, drug-induced increases in TGS were more marked. All drugs dose-dependently increased minEST and, except ethosuximide, maxEST. For comparison of drug potencies, doses increasing seizure thresholds by 20 or 50% were calculated from dose-response curves. Respective comparisons showed marked differences in drug potencies between models, indicating that the CRS method presents a model of another, more pharmacoresistant seizure type than seizure types induced in traditional models, such as transcorneal electroshock. Based on the location of electrodes in the frontal neocortex, the characteristic seizure pattern, and the low pharmacological sensitivity of the seizures to standard antiepileptics, the modified CRS model most likely represents a new model of localization-related seizures occurring in frontal lobe epilepsy and may thus be used in the search for novel drugs with higher efficacy against this difficult-to-treat type of epilepsy.

Animals↗

PubMed1995

Simulation of micropopulations in epidemiology: tutorial. 4. Evaluations of simulation models. A series of tutorials illustrated by coronary heart disease models.

The first tutorial in this series (Ackerman E: Simulation of micropopulations in epidemiology: Tutorial 1. Simulation: an introduction, Int J Biomed Comput, 36 (1994) 229-238) introduces the general approach of simulation of micropopulation models of coronary disease using Monte Carlo techniques. The modeling process includes the selection of functional forms to represent the probability of state transfers. Alternative functional forms are described in the second tutorial (Ackerman E: Simulation of micropopulations in epidemiology: Tutorial 2. Analytic forms of event probabilities, Int J Biomed Comput, 37 (1994) 139-149). The third tutorial (Ackerman E: Simulation of micropopulations in epidemiology: Tutorial 3. Simulation model evaluation methods, Int J Biomed Comput, 37 (1994) 195-204) considers the actual risk factors used in the models and the compartmentalization of the population. However, that tutorial emphasizes the methods of evaluating different models of coronary heart disease. In the current tutorial, the evaluation methods are applied to the models previously introduced. Essential to this is the concept of degrees of freedom. Limitations of that concept are discussed with specific reference to models of coronary heart disease. The estimation of optimal values for the risk coefficients is considered further. The various tests of appropriateness are applied to specific models and the role of sensitivity analysis is further illustrated. Discussions of intervention strategies and their simulation is deferred to the following tutorial.

Adult↗

PubMedDate not supplied