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At least 487 records · Page 27Linked to original sources

PubMed2005

Modelling a spontaneously reported side effect by use of a Markov mixed-effects model.

AIMS: To present a method for analyzing side-effect data where change in severity is spontaneously reported during the experiment. METHODS: A clinical study in 12 healthy volunteers aimed to investigate the concentration-response characteristics of a CNS-specific side-effect was conducted. After an open session where the subjects experienced the side-effect and where the individual pharmacokinetic parameters were evaluated they were randomized to a sequence of three different infusion rates of the drug in a double-blinded crossover way. The infusion rates were individualized to achieve the same target concentration in all subjects and different drug input rates were selected to mimic absorption profiles from different formulations. The occurrence of the specific side-effect and any subsequent change in severity was self-reported by the subjects. Severity was recorded as 0 = no side-effect, 1 = mild side-effect and 2 = moderate or severe side-effect. RESULTS: The side-effect data were analyzed using a mixed-effects model for ordered categorical data with and without Markov elements. The former model estimated the probability of having a certain side-effect score conditioned on the preceding observation and drug exposure. The observed numbers of transitions between scores were from 0 -> 1: 24, from 0- > 2: 11, from 1 - >, 2: 23, from 2- > 1: 1, from 2- > 0: 32 and from 1 - >0: 2. The side-effect model consisted of an effect-compartment model with a tolerance compartment. The predictive performance of the Markov model was investigated by a posterior predictive check (PPC), where 100 datasets were simulated from the final model. Average number of the different transitions from the PPC was from 0 - > 1: 26, from 0 - > 2: 11, from 1 - > 2: 25, from 2 - >1: 1, from 2 - >0: 35 and from 1 - > 0: 1. A similar PPC for the model without Markov elements was at considerable disparity with the data. CONCLUSION: This approach of incorporating Markov elements in an analysis of spontaneously reported categorical side-effect data could adequately predict the observed side-effect time course and could be considered in analyses of categorical data where dependence between observations is an issue.

Adult↗

PubMed1993

Models for computer simulation studies of input functions for tracer kinetic modeling with positron emission tomography.

In tracer kinetic modeling with Positron Emission Tomography (PET), the direct measurement (piecewise linear approximation) of plasma time-activity curve of tracer (PTAC) is often used as the input function to estimate regional physiological parameters. However, no explicit general model is available for PTAC itself, which limits the further study of the effects of PTAC, such as PTAC measurement noise or PTAC sampling schedules, on the physiological parameters estimation. A PTAC model is proposed in this paper and compared with other four possible candidates. Eight sets of [18F]-fluoro-2-deoxy-D-glucose (FDG) experimental data were used to test the models and several statistical criteria were used to validate their adequacy. An application of the model to improve the estimation of local cerebral metabolic rate of glucose (LCMRGlc) is presented. This model is also expected to be useful for generating realistic PTAC curves in computer simulation studies of other tracers and their kinetic modeling characteristics.

Animals↗

PubMed1991

Domain of validity of classical models of leucine metabolism assessed by compartmental modeling.

Whole-body modeling of in vivo leucine (an essential amino acid) metabolism is fundamentally difficult due to the complexity of the system. This has favored the use of two simple kinetic models, the so-called primary and reciprocal pool models, to interpret tracer data, but their domain of validity is uncertain. We define here the error of these two approaches by using comprehensive compartmental models of leucine metabolism as true representations of the leucine system. Of particular interest is the comparison of the two simple models with an 11-compartment model characterized by a rich intracellular compartmentation that has recently been proposed as a sound physiological description of the system. Formulas are derived that define in structural terms the error of the primary and reciprocal pool models.

Humans↗

PubMed1992

Sexual mixing models: a comparison of analogue deterministic and stochastic models.

Models for sexual partner choice are discussed for the case of highly variable sexual activity in the population. It is demonstrated that the variances in the number of infected persons may be extremely large. For the random mixing model, higher order cumulants are also evaluated. On the basis of these results the applicability of deterministic models and models for expectations only are questioned. A general model is proposed for handling nonrandom, or correlated, mixing. The problem of inconsistency is overcome by considering the couples having sex as the natural unit in the model. In the case of s discrete homogeneous groups it is shown that only (s2) parameters defining the interaction between the groups can be chosen freely. Finally, the effect of correlation in partner choice is demonstrated by a bivariate lognormal model for partner choice.

Female↗

PubMed1989

Animal models of human immunodeficiency virus infection. Public Health Service Animal Models Committee.

The search for a model of HIV infection continues. While much of the initial work focussed on animal models of AIDS, more recent efforts have sought animal models of HIV infection in which one or more signs of AIDS may be reproduced. Most initial small animal modelling efforts were negative and many such efforts remain unpublished. In 1988, the Public Health Service (PHS) AIDS Animal Model Committee conducted a survey among PHS agencies to identify published and unpublished data on animal models of HIV. To date, the chimpanzee is the only animal to be reliably infected with HIV albeit without development of signs and symptoms normally associated with human AIDS. One recent study has shown the gibbon to be similarly susceptible to infection with HIV. Mice carrying a chimera of elements of the human immune system have been shown to support the growth of HIV and F1 progeny of transgenic mice containing intact copies of HIV proviral DNA, have developed a disease that resembles some aspects of human AIDS. Rabbits, baboons and rhesus monkeys have also been shown to be infected under certain conditions and/or with selected strains of HIV but again without the development of AIDS symptomatology. This report briefly summarizes published and available unpublished data on these efforts to develop an animal model of HIV infection.

Acquired Immunodeficiency Syndrome↗

PubMed1996

The human/sheep xenograft model: a large animal model of human hematopoiesis.

Although not 'ideal', xenograft models of human hematopoiesis have proved to be extremely useful experimental systems for the study of the in vivo engraftment/proliferation potential of human hematopoietic stem/progenitor cells (HSC). Among these, the human/sheep xenograft model is unique in several respects. This model takes advantage of fetal immunologic immaturity and developing 'homing' spaces in the fetal bone marrow to obtain donor HSC engraftment in normal recipients without marrow conditioning. This avoids both the possible stromal abnormalities associated with irradiation- and/or chemotherapy-induced immunodeficiency which may limit human HSC engraftment or long-term maintenance of human hematopoiesis, and the use of genetically deficient hosts which may result in restricted donor cell expression. In the human/sheep xenograft model, human HSC (1) colonizes the bone marrow, (2) persists for many years, (3) is capable of multilineage differentiation, (4) retains its ability to respond to human cytokines, and (5) retains its ability to engraft/differentiate in secondary recipients. Another unique aspect of the sheep model is its large size; this permits repeated evaluation of human cell activity in the same chimeric sheep over long periods. The model appears to discriminate between the different populations of human HSC and exhibits a degree of sensitivity that suggests this in utero approach may serve as a biologically relevant model for the identification, characterization, and study of the in vivo potential of human HSC from available sources.

Animals↗

PubMed2004

Band splitting in overloaded isocratic elution chromatography III. Modeling of adsorbate-adsorbate interactions by a two-component extension of a BET kinetic isotherm model.

A new two-component competitive adsorption model was derived to account for the competitive adsorption data of mixtures of ethylbenzoate and 4-tert-butylphenol, on a C18-Kromasil column under RPLC conditions (mobile phase, methanol/water, 62/38, v/v). The derivation is based on kinetic arguments and is an extension to multicomponent systems of the single-component BET isotherm. The model assumes that the molecules of the first compound (A) can adsorb on layers made of molecules of either A or B, while molecules of B can only adsorb on layers made of molecules of A. This makes the competitive isotherm consistent with the single-component isotherms of ethylbenzoate and 4-tert-butylphenol, the multilayer BET and the monolayer Langmuir isotherm models, respectively. The competitive adsorption data were acquired by frontal analysis (FA) with equimolar mixtures of eight different concentrations. For the seven lowest concentrations, these data were derived from the retention times of the shocks of the two compounds and the concentration of the intermediate plateau of the less retained compound. At the highest concentration (25 g/l), the individual band profiles were measured by collecting and analyzing twenty fractions. The low concentration data (C < or = 10 g/l) are well accounted for by the two competitive isotherm models derived previously but these models fail to describe the experimental data of 4-tert-butylphenol at high concentrations. By contrast, the new model predicts very well the experimental adsorption data for mixtures of ethylbenzoate and 4-tert-butylphenol in the whole range of concentration studied. Our results suggest that the adsorption constant of 4-tert-butylphenol onto layers made of ethylbenzoate (b(B,A) = 0.0120 l/g) is intermediate between those of ethylbenzoate on layers made of 4-tert-butylphenol (b(A,B) = 0.0105 l/g) and of ethylbenzoate on itself (b(A,A) = 0.0145 l/g). This new model should give an improved description of the band splitting observed for 4-tert-butylphenol in the presence of ethylbenzoate.

Adsorption↗

PubMed2006

Theoretical foundation to estimate the relative efficiencies of the Jukes-Cantor+gamma model and the Jukes-Cantor model in obtaining the correct phylogenetic tree.

This paper deals with the theoretical foundation to estimate the relative efficiency (probability of inferring the true tree) of different nucleotide substitution models. A novel theoretical approach has been developed to estimate the relative efficiency of nucleotide substitution models based on the neighbor-relation method. The theory was developed directly by using the four-point condition. Initially theoretical formulas for the Jukes-Cantor+gamma (JC+Gamma) model and the Jukes-Cantor (JC) model were developed to estimate their relative efficiencies. Theoretical formulas were used on several model topologies for both models to obtain a true tree. Extensive simulations were performed on the same set of trees to test the strength of the theoretical approach. Simulation results demonstrated a good agreement with results obtained by the theoretical estimation. Overall the theoretical foundation for estimating model efficiencies is very accurate.

Algorithms↗

PubMed2005

Conventional models overestimate the statistical significance of volume-outcome associations, compared with multilevel models.

OBJECTIVE: To compare the use of conventional statistical models with multilevel regression models in volume-outcome analyses of surgical procedures in an empirical case study. STUDY DESIGN AND SETTING: Using conventional regression models and multilevel regression models, we estimated the effect of hospital volume and surgeon volume on 30-day mortality and length of postoperative hospital stay in persons who had an esophagectomy, pancreaticoduodenectomy, or major lung resection for cancer in Ontario, Canada, from 1994 to 1999. RESULTS: The point estimates of volume-outcome associations were similar using either method; however, the 95% confidence intervals estimated by multilevel models were wider than those estimated by conventional models. A significant association between volume and mortality was identified in 2 of 18 (11%) comparisons using conventional analysis but in none of the 18 (0%) comparisons using multilevel analysis, and between volume and length of stay in 15 of 18 (83%) comparisons using conventional analysis and in 1 of 18 (6%) comparisons using multilevel analysis. CONCLUSION: Conventional and multilevel statistical models can yield substantially different results in the analysis of volume-outcome associations for surgical procedures.

Age Factors↗

PubMed2005

Linking a one-dimensional pesticide fate model to a three-dimensional groundwater model to simulate pollution risks of shallow and deep groundwater underlying fractured till.

The one-dimensional pesticide fate model MACRO was loose-linked to the three-dimensional discrete fracture/matrix diffusion model FRAC3DVS to describe transport of the pesticide mecoprop in a fractured moraine till and local sand aquifer (5-5.5 m depth) overlying a regional limestone aquifer (16 m depth) at Havdrup, Denmark. Alternative approaches to describe the upper boundary in the groundwater model were examined. Field-scale simulations were run to compare a uniform upper boundary condition with a spatially variable upper boundary derived from Monte-Carlo simulations with MACRO. Plot-scale simulations were run to investigate the influence of the temporal resolution of the upper boundary conditions for fluxes in the groundwater model and the effects of different assumptions concerning the macropore/fracture connectivity between the two models. The influence of within-field variability of leaching on simulated mecoprop concentrations in the local aquifer was relatively small. A fully transient simulation with FRAC3DVS gave 20 times larger leaching to the regional aquifer compared to the case with steady-state water flow, assuming full connectivity with respect to macropores/fractures across the boundary between the two models. For fully transient simulations 'disconnecting' the macropores/fractures at the interface between the two models reduced leaching by a factor 24. A fully connected, transient simulation with FRAC3DVS, with spatially uniform upper boundary fluxes derived from a MACRO simulation with 'effective' parameters is therefore recommended for assessing leaching risks to the regional aquifer, at this, and similar sites.

Agriculture↗

PubMed2005

Parameterization of individual-based models: comparisons with deterministic mean-field models.

The relating of deterministic, mean-field models into network models, where epidemic spread occurs between interconnected susceptible and infectious individuals or populations, requires careful consideration. Here, we discuss models that consider differently the manner in which contact rate and infectiousness change over time, with different algorithms suitable for different underlying processes. Though these models give coincidental results to the mean-field in the case of large, highly connected networks, the results when sparsely connected networks are considered may differ. Different subsets of the parameters from the mean-field epidemic (R(0), generation time, infectiousness, etc.) are preserved in each case. Despite these differences, simulated epidemics generated under some model architectures are insensitive to the average degree of contact amongst nodes, k. Model-based estimates of k may be model dependent, and must therefore be viewed with caution.

Algorithms↗

PubMedDate not supplied

Development of models of active ion transport for whole-cell modelling: cardiac sodium-potassium pump as a case study.

This study presents a method for the reduction of biophysically-based kinetic models for the active transport of ions. A lumping scheme is presented which exploits the differences in timescales associated with fast and slow transitions between model states, while maintaining the thermodynamic properties of the model. The goal of this approach is to contribute to modelling of the effects of disturbances to metabolism, associated with ischaemic heart disease, on cardiac cell function. The approach is illustrated for the sodium-potassium pump in the myocyte. The lumping scheme is applied to produce a 4-state representation from the detailed 15-state model of Läuger and Apell, Eur. Biophys. J. 13 (1986) 309, for which the principles of free energy transduction are used to link the free energy released from ATP hydrolysis (deltaGATP) to the transition rates between states of the model. An iterative minimisation algorithm is implemented to determine the transition rate parameters based on the model fit to experimental data. Finally, the relationship between deltaGATP and pump cycling direction is investigated and compared with recent experimental findings.

Adenosine Triphosphate↗

PubMed2001

Modeling pO(2) distributions in the bone marrow hematopoietic compartment. II. Modified Kroghian models.

Hematopoietic cells of various lineages are organized in distinct cellular architectures in the bone marrow hematopoietic compartment (BMHC). The homogeneous Kroghian model, which deals only with a single cell type, may not be sufficient to accurately describe oxygen transfer in the BMHC. Thus, for cellular architectures of physiological significance, more complex biophysical-transport models were considered and compared against simulations using the homogeneous Kroghian model. The effects of the heterogeneity of model parameters on the oxygen tension (pO(2)) distribution were examined using the multilayer Kroghian model. We have also developed two-dimensional Kroghian models to simulate several cellular architectures in which a cell cluster (erythroid cluster) or an individual cell (megakaryocyte or adipocyte) is located in the BMHC predominantly occupied by mature granulocytes. pO(2) distributions in colony-type cellular arrangements (erythroblastic islets, granulopoietic loci, and lymphocytic nodules) in the BMHC were also evaluated by modifying the multilayer Kroghian model. The simulated results indicate that most hematopoietic progenitors experience low pO(2) values, which agrees with the finding that low pO(2) promotes the expansion of various hematopoietic progenitors. These results suggest that the most primitive stem cells, which are located even further away from BM sinuses, are likely located in a very low pO(2) environment.

Erythrocytes↗

PubMed2003

Quantitative analysis of aspartate receptor signaling complex reveals that the homogeneous two-state model is inadequate: development of a heterogeneous two-state model.

The two-state model of receptor activation, in which a receptor population exists in equilibrium between a single on-state and a single off-state, has long been considered a viable model for the signaling behavior of bacterial chemoreceptors. Here, we show that this simple, homogeneous two-state model is adequate for a pure receptor population with just one adaptation state, but fails to account quantitatively for the observed linear relationship between the apparent attractant affinity (K(1/2)) and kinase activity (V(obs)(apo)) as the adaptation state is varied. Further analysis reveals that the available data are instead consistent with a heterogeneous two-state model in which covalent modification of receptor adaptation sites changes the microscopic properties of the on-state or off-state. In such a system, each receptor molecule retains a single on-state and off-state, but covalent adaptation generates a heterogeneous population of receptors exhibiting a range of different on-states or off-states with different microscopic parameters and conformations. It follows that covalent adaptation transforms the receptor from a simple, two-state toggle switch into a variable switch. In order to identify the microscopic parameters most sensitive to covalent adaptation, six modified, two-state models were examined in which covalent adaptation alters a different microscopic parameter. The analysis suggests that covalent adaptation primarily alters the ligand-binding affinity of the receptor off-state (K(D1)). By contrast, models in which covalent adaptation alters the ligand-binding affinity of the receptor on-state, the maximal kinase stimulation of the on-state or off-state, cooperative interactions between receptors, or the assembly of the receptor-kinase signaling complex are inconsistent with the available evidence. Overall, the findings support a heterogeneous two-state model in which modification of the receptor adaptation sites generates a population of receptors with heterogeneous off-states differing in their attractant affinities. In the process of testing the effects of covalent adaptation on the assembly of the receptor-kinase signaling complex, a new method for estimating the stoichiometric ratio of receptor and CheA in the ternary signaling complex was devised. This method suggests that the ratio of receptor dimers to CheA dimers in the assembled complex is 6:1 or less.

Bacterial Proteins↗

PubMed2002

The Tripartite Influence model of body image and eating disturbance: a covariance structure modeling investigation testing the mediational role of appearance comparison.

Recent theoretical approaches to the etiology of eating disorders and body image disturbances have begun to focus on multifactorial models. In the current study, the Tripartite Influence model was examined in a large sample of college females (ages 18-22). This model proposes that three primary core sources of influence--parents, peers and media--contribute to the development of body image and eating disturbances. Additionally, the model suggests that at least two factors mediate the relationship between influences and disturbance-appearance comparison and internalization of media information. In this study, appearance comparison was examined as a mediational link between peer, family and media influence variables and the outcome disturbance measures of eating dysfunction and body image dissatisfaction. Covariance structure modeling (CSM) was used to test the proposed pathways. The results indicated that appearance comparison mediated the effects of family and media influences on body dissatisfaction, which in turn influenced restrictive and bulimic behaviors. In addition, peer influences had a direct influence on restriction. Perfectionism was hypothesized to relate to body dissatisfaction, but was in fact found to influence appearance comparison. The findings were limited by the necessity of several modifications to the originally proposed models, yet offer replication and extension of previous work with appearance comparison and support for further testing of the Tripartite Influence model.

Adolescent↗

PubMed1983

Rate theory models for ion transport through rigid pores. III. Continuum vs discrete models in single file diffusion.

In studying the single file model in its discrete as well as in its continuum form the relationship between the phenomenological continuum theory of diffusion and the rate theory approach is analyzed. The single file model in its original form is discrete and represents the most general rate theory model for ion transport through rigid pores in biological membranes. In neglecting the interionic interactions which the single file model takes into account, the Nernst-Planck equation of macroscopic free diffusion can be derived from single file by means of the procedure n leads to infinity (where n is the number of binding sites within a pore) and the classical diffusion theory can thereby be integrated into the more general concept of single filing transport. Moreover, the single file model has been transformed in the limit n leads to infinity into the corresponding continuum form involving interionic interactions. The essential differences between the two derived continuum forms are: In the macroscopic diffusion model, the interionic interactions are regarded in the form of a "mean field". Thus we only get one equation of motion (Nernst-Planck equation) for the ionic concentration c(x, t) within the membrane. In the continuum version of the single file model, however, we obtain a hierarchy of Fokker-Planck equations for the probability density functions Pm(x1, . . . , xm, t) (where m is the number of ions within a pore). The interactions of the single file system are incorporated in detail into the Fokker-Planck equation as well as into the corresponding boundary conditions. As a consequence, the boundary conditions are highly complex in comparison with periodic conditions or Dirichlet conditions often used for the Nernst-Planck equation in electrophysiology. Two types of boundary conditions have been found which are principally different: The first one is to regulate the entry and exit of the ions at the pore mouth by a negative feedback mechanism, the second one describes the collisions of the ions within multiply occupied pores. In this context the question is discussed of whether the continuum version of single file has advantages over the discrete one.

Binding Sites↗

PubMed2003

Statistical models for analyzing repeated quality measurements of horticultural products. Model evaluations and practical example.

In the field of postharvest quality assessment of horticultural products, research on the development of non-destructive quality sensors, replacing destructive and often time consuming sensors, has spurred in the last decennium offering the possibility of taking repeated quality measures on the same product. Repeated measures analysis is gaining importance during recent years and several software packages offer a broad class of routines. A dataset dealing with the postharvest quality evolution of different tomato cultivars serves as practical example for the comparison and discussion of four different statistical model types. Starting from an analysis at each time point and an ordinary least squares regression model as standard and widely used methods, this contribution aims at comparing these two methods to a repeated measures analysis and a longitudinal mixed model. It is shown that the flexibility of such a mixed model, both towards the repeated measures design of the experiments as towards the large product variability inherent to these horticultural products, is an important advantage over classical techniques. This research shows that different conclusions could be drawn depending on which technique is used due to the basic assumptions of each model and which are not always fulfilled. The results further demonstrate the flexibility of the mixed model concept. Using a mixed model for repeated measures, the different sources of variability, being inter-tomato variability, intra-tomato variability and measurement error were characterized being of great benefit to the researcher.

Computer Simulation↗

PubMed2002

Calibration of model constants in a biological reaction model for sewage treatment plants.

Various biological reaction models have been proposed which estimate concentrations of soluble and insoluble components in effluent of sewage treatment plants. These models should be effective to develop a better operation system and plant design, but their formulas consist of nonlinear equations, and there are many model constants, which are not easy to calibrate. A technique has been proposed to decide the model constants by precise experiments, but it is not practical for design engineers or process operators to perform these experiments regularly. Other approaches which calibrate the model constants by mathematical techniques should be used. In this paper, the optimal regulator method of modern control theory is applied as a mathematical technique to calibrate the model constants. This method is applied in a small sewage treatment testing facility. Calibration of the model constants is examined to decrease the deviations between calculated and measured concentrations. Results show that calculated values of component concentrations approach measured values and the method is useful for actual plants.

Calibration↗