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At least 649 records · Page 36Linked to original sources

PubMed1999

Modelling concentric contraction of muscle using an improved cross-bridge model.

Despite its overwhelming acceptance in muscle research, the cross-bridge theory does not account for all phenomena observed during muscular contractions. A phenomenon which has received much attention in the biomechanics literature, but has evaded convincing explanation and is not accounted for in the formulation of the classic cross-bridge theory, is the persistent aftereffects of muscular length changes on force production. For example, following muscle shortening, the isometric force of a muscle is depressed for a long time period ( > 5 s) compared to the corresponding isometric force following no length change. In the present study, the classic cross-bridge model was modified in two ways in an attempt to account for the force depressions following muscle shortening. First, the steady-state force depressions following shortening were described by a single scalar variable: the work performed by the muscle during shortening; and second, the dynamic, history-dependent cross-bridge properties were described using a fading memory function. The proposed model was developed and tested for shortening of the cat soleus at constant speeds ranging from 4 to 32 mm/s, for shortening at changing speeds, and for shortening of different magnitudes ranging from 2 to 10 mm. The history-dependent forces during shortening and the steady-state force depressions following shortening were well captured with the modified cross-bridge model. The present model contains two mathematically simple adaptations to the classic cross-bridge model, and is the first such model to account for the long-lasting force depressions following muscle shortening using a single scalar variable.

Actins↗

PubMed1991

Biophysical models of protein denaturation. I. An improvement of the model of two states.

The model of two states (native and denatured), frequently used for the description of protein denaturation, has been complemented by relations defining, on theoretical grounds, the temperature dependence of the relevant thermodynamic functions. In essence, this was achieved by assuming that the temperature dependence of Gibbs free energies of the native protein and of denaturation can be approximated, within the interval (0 degree C, 100 degrees C), by second-order partial sums of Taylor series. The improved model operates with four parameters: the temperature of denaturation, the heat capacities of the native and denatured protein at the temperature of denaturation, and the entropy of denaturation at that temperature. A theoretical treatment is included of the temperature dependence of total heat capacity, the variable recorded in the form of continuous thermograms by means of differential scanning calorimetry. Our model correctly reproduces experimental thermograms of proteins and provides for the biophysical interpretation of a number of their geometric components. Fitting procedures were complemented by a newly devised method for estimating starting values of model parameters from calorimetric data. The phenomenon of cold denaturation was also reproduced quantitatively by our model, which supplies explicit proof of the exothermal nature of this phenomenon. Finally, the relationship between temperature profiles of thermodynamic functions describing denaturation has been defined by sequences of profile magnitudes at points where the profiles intersect the temperature axis and/or cross each other. Model-derived sequences of profile magnitudes, representative of cross-point temperatures and of intervals in between, together constitute a general characteristics of denaturation, uninfluenced by differences in thermodynamic stability between protein species.

Mathematics↗

PubMedDate not supplied

Models-of-data and models-of-processes in the post-genomic era.

As we are entering the post-genomic era, models-of-data, such as mining and filtering methods for gene sequences and microarrays and the clustering of co-expressed genes, must be complemented with models-of-processes that explain relationships between genomic information and phenomena at biochemical and physiological levels. Many of these models will have the structure of compartment models, whose conceptualization, identification and analysis will fundamentally benefit from the seminal work of John Jacquez. The article indicates with three vignettes that non-linear compartment models in the formulation of biochemical systems theory are viable candidates for post-genomic models-of-processes.

Animals↗

PubMed2003

Modeling of phosphorus dynamics in aquatic sediments: I--model development.

A model is developed to study the phosphorus dynamics in aquatic sediments and to conduct dynamic predictions of phosphorus release across a sediment-water interface. The model focuses on the sediment active layer below the sediment-water interface and is based on primary mechanisms regulating phosphorus behavior in sediments, including effective diffusion, bioturbation mixing and burial processes (transport), organic decomposition, sorption kinetic processes and non-linear partitioning (mobilization). The effects of environmental factors such as dissolved oxygen and temperature are taken into account. The model is solved by numerical integration. The primary difference from models in the literature is that the model directly describes the dynamic behavior of dissolved, particulate exchangeable ortho-phosphorus and organic phosphorus in sediments, and incorporates dynamic sorption and non-linear partitioning processes. These improve model mechanisms and allow regulation of phosphorus flux through the sediment reservoir that acts as both a source and sink of phosphorus.

Biological Availability↗

PubMed2003

Modeling of phosphorus dynamics in aquatic sediments: II--examination of model performance.

A sediment phosphorus model, describing dynamics of organic phosphorus, dissolved reactive phosphorus and exchangeable particulate phosphorus, is applied to five monitoring stations in Chesapeake Bay, USA, to examine model performance in predicting sediment-water phosphorus exchange. The model was fit to 1 year of field measurements, and verified over 3 years at five sampling stations. The results show that the simulated concentrations of phosphorus reasonably correspond to model mechanisms and field observations in both spatial and temporal variations. Predicted release fluxes of phosphorus are consistent with field measurements and improved over those obtained by existing sediment phosphorus models. The model incorporates the effects of dissolved oxygen and non-linear, non-equilibrium sediment sorption in phosphorus dynamics. A sensitivity analysis indicates the importance of the non-linear, non-equilibrium sorption processes to accurate prediction of sediment-water phosphorus flux.

Environmental Monitoring↗

PubMed1999

A pharmacokinetic modeling of inorganic arsenic: a short-term oral exposure model for humans.

This study presents a pharmacokinetic modeling of inorganic arsenic disposition in human body for short-term oral exposures. Effort on the development of the model is directed toward the prediction of the kinetic behavior of inorganic arsenic and its metabolites in the body. The current model considers the 4 circulating species; AsIII, AsV, and two metabolites such as monomethylarsenic (MMA) and dimethylarsenic (DMA) in the blood and tissue groups. While it is difficult to estimate some parameters used in the models at this time, the current model assumptions and predictions seem to be consistent with the experimental observations found in the literature. Hence, the current model, when more fully developed, is expected to provide insight into the behavior of inorganic arsenic and its methylated metabolites within the body, and may help increase the understanding of risk assessment issues associated with inorganic arsenic in drinking water.

Administration, Oral↗

PubMed2001

Numerical modeling of humic colloid borne americium (III) migration in column experiments using the transport/speciation code K1D and the KICAM model.

The humic colloid borne Am(III) transport was investigated in column experiments for Gorleben groundwater/sand systems. It was found that the interaction of Am with humic colloids is kinetically controlled, which strongly influences the migration behavior of Am(III). These kinetic effects have to be taken into account for transport/speciation modeling. The kinetically controlled availability model (KICAM) was developed to describe actinide sorption and transport in laboratory batch and column experiments. Application of the KICAM requires a chemical transport/speciation code, which simultaneously models both kinetically controlled processes and equilibrium reactions. Therefore, the code K1D was developed as a flexible research code that allows the inclusion of kinetic data in addition to transport features and chemical equilibrium. This paper presents the verification of K1D and its application to model column experiments investigating unimpeded humic colloid borne Am migration. Parmeters for reactive transport simulations were determined for a Gorleben groundwater system of high humic colloid concentration (GoHy 2227). A single set of parameters was used to model a series of column experiments. Model results correspond well to experimental data for the unretarded humic borne Am breakthrough.

Americium↗

PubMed2001

Validation of a digital color Doppler flow measurement method for pulmonary regurgitant volumes and regurgitant fractions in an in vitro model and in a chronic animal model of postoperative repaired tetralogy of Fallot.

OBJECTIVES: The purpose of this study was to validate a digital color Doppler (DCD) automated cardiac flow measurement method for quantifying pulmonary regurgitation (PR) in an in vitro and a chronic animal model of the right ventricular outflow tract of postoperative tetralogy of Fallot (TOF). BACKGROUND: There has been no reliable ultrasound method that can accurately quantitate PR. METHODS: We developed an in vitro model of mild pulmonary stenosis and wide-open PR that mimics the patterns of flow seen in patients with postoperative TOF. Thirteen different forward and regurgitant stroke volumes (RSVs) across the noncircular shaped cross-sectional outflow tract flow area were estimated using the DCD method in two orthogonal planes. In six sheep with surgically created PR, 24 different hemodynamic states with PR strictly quantified by electromagnetic probes were also studied. RESULTS: The RSVs and regurgitant fractions (RFs) obtained by the DCD method using average values from two orthogonal planes correlated well with reference values (RSV: r = 0.99, mean difference = 0.02 +/- 0.39 ml/beat for in vitro model; r = 0.97, mean differences = 1.79 +/- 1.84 ml/beat for animal model, RF: r = 0.98, mean difference = -1.10 +/- 4.34% for in vitro model; r = 0.94, mean difference = 2.73 +/- 6.75% for animal model). However, the DCD method using a single plane had limited accuracy for estimating pulmonary RFs and RSVs. CONCLUSIONS: The DCD method using average values from two orthogonal planes provides accurate estimation of RSVs and RFs and should have clinical importance for serially quantifying PR in patients with postoperative TOF.

Animals↗

PubMedDate not supplied

E-state modeling of corticosteroids binding affinity validation of model for small data set.

Data for 31 steroids binding to the corticosteroid binding globulin (CBG) were modeled using E-state molecular structure descriptors and a kappa shape index. Both E-state and hydrogen E-state descriptors appear in the model in atom-level and atom-type descriptors. A four-variable model is obtained that is statistically satisfactory: r (2) = 0.81, s = 0.51; r (2)(press) = 0.72; s(press) = 0.62. Structure interpretation is given for each variable in the model. A leave-group-out (LGO) approach to model-validation is presented in which each observation is removed from the data set three times in random groups of 20% of the whole data set. The average of the resulting predicted values constitutes consensus predictions for these data for which r (2)(LOO) = 0.70. These collective results support the claim that the E-state model may be useful for prediction of pK binding values for new compounds.

Adrenal Cortex Hormones↗

PubMed2001

Effects of pH on protein association: modification of the proton-linkage model and experimental verification of the modified model in the case of cytochrome c and plastocyanin.

Effects of pH on protein association are not well understood. To understand them better, we combine kinetic experiments, calculations of electrostatic properties, and a new theoretical treatment of pH effects. The familiar proton-linkage model, when used to analyze the dependence of the association constant K on pH, reveals little about the individual proteins. We modified this model to allow determination not only of the numbers of the H+ ions involved in the association but also of the pK(a) values, in both the separate and the associated proteins, of the side chains that are responsible for the dependence of K on pH. Some of these side chains have very similar pK(a) values, and we treat them as a group having a composite pK(a) value. Use of these composite pK(a) values greatly reduces the number of parameters and allows meaningful interpretation of the experimental results. We experimentally determined the variation of K in the interval 5.4 < or = pH < or = 9.0 for four diprotein complexes, those that the wild-type cytochrome c forms with the wild-type plastocyanin and its mutants Asp42Asn, Glu59Gln, and Glu60Gln. The excellent fittings of the experimental results to the modified model verified this model and revealed some unexpected and important properties of these prototypical redox metalloproteins. Protein association causes a decrease in the pK(a) values of the acidic side chains and an increase in the pK(a) values of the basic side chains. Upon association, three carboxylic side chains in wild-type plastocyanin each release a H+ ion. These side chains in free plastocyanin have an anomalously high composite pK(a) value, approximately 6.3. Upon association, five or six side chains in cytochrome c, likely those of lysine, each take up a H+ ion. Some of these side chains have anomalously low pK(a) values, less than 7.0. The unusual pK(a) values of the residues in the recognition patches of plastocyanin and cytochrome c may be significant for the biological functions of these proteins. Although each mutation in plastocyanin markedly, and differently, changed the dependence of K on pH, the model consistently gave excellent fittings. They showed decreased numbers of H+ ions released or taken up upon protein association and altered composite pK(a) values of the relevant side chains. Comparisons of the fitted composite pK(a) values with the theoretically calculated pK(a) values for plastocyanin indicated that Glu59 and Asp61 in the wild-type plastocyanin each release a H+ ion upon association with cytochrome c. Information of this kind cannot readily be obtained by spectroscopic methods. Our modification of the proton-linkage model is a general one, applicable also to ligands other than H+ ion and to processes other than association.

Cytochrome c Group↗

PubMed2001

Development of a pharmacophore model for histamine H3 receptor antagonists, using the newly developed molecular modeling program SLATE.

New molecular modeling tools were developed to construct a qualitative pharmacophore model for histamine H3 receptor antagonists. The program SLATE superposes ligands assuming optimum hydrogen bond geometry. One or two ligands are allowed to flex in the procedure, thereby enabling the determination of the bioactive conformation of flexible H3 antagonists. In the derived model, four hydrogen-bonding site points and two hydrophobic pockets available for binding antagonists are revealed. The model results in a better understanding of the structure-activity relationships of H3 antagonists. To validate the model, a series of new antagonists was synthesized. The compounds were designed to interact with all four hydrogen-bonding site points and the two hydrophobic pockets simultaneously. These ligands have high H3 receptor affinity, thereby illustrating how the model can be used in the design of new classes of H3 antagonists.

Animals↗

PubMed1996

Preliminary physiologically based pharmacokinetic model for cocaine in the rat: model development and scale-up to humans.

A physiologically based multicompartmental model has been developed to describe the concentration-time course of cocaine in plasma and tissues in the rat. The compartments included in the model were brain, heart, gut, liver, muscle, fat, venous blood, arterial blood, and a mass-balance compartment. Drug delivery to the tissues was assumed to be flow limited. The model incorporated a nonsaturable binding site for cocaine in the liver. Elimination occurred via both blood and hepatic elimination. The model was validated using independently derived data. The model was scaled to humans and accurately predicted the cocaine levels following intranasal and inhalation administration. However, a poor fit was observed following intravenous administration. Future models incorporating non-constant blood flow and pharmacodynamics need to be developed.

Animals↗

PubMed2002

Molecular modeling of four stereoisomers of the major B[a]PDE adduct (at N(2)-dG) in five cases where the structure is known from NMR studies: molecular modeling is consistent with NMR results.

The potent mutagen/carcinogen benzo[a]pyrene (B[a]P) is metabolically activated to (+)-anti-B[a]PDE, which is known to induce a variety of mutations (e.g., GC --> TA, GC --> AT, etc.). One hypothesis for this complexity is that different mutations are induced by different conformations of its major adduct [+ta]-B[a]P-N(2)-dG when bypassed during DNA replication (perhaps by different DNA polymerases). Our previous molecular modeling studies have suggested that conformational complexity might be extensive in that B[a]P-N(2)-dG adducts appeared capable of adopting at least sixteen potential conformational classes in ds-DNA [e.g., Kozack and Loechler (1999) Carcinogenesis 21, 1953], although only eight seemed likely to be relevant to base substitution mutagenesis. Such molecular modeling studies are only likely to be valuable for the interpretation of mutagenesis results if global minimum energy conformations for adducts are found and if the differences in the energies of these different conformations can be computed reasonably accurately. One approach to assessing the reliability of our molecular modeling techniques is considered herein. Using a five-step molecular modeling protocol, which importantly included a molecular dynamics version of simulated annealing, eight conformations are studied in each of five cases. (The five cases are listed below, and were chosen because in each case the preferred solution conformation is known from a NMR study.) Of the eight conformations studied, the one computed to be lowest in energy is the same conformation as the one observed by NMR in four of the five cases: 5'-CGC sequence with [+ta]-, [-ta]-, and [+ca]-B[a]P-N(2)-dG, and 5'-TGC sequence with [+ta]-B[a]P-N(2)-dG. In the fifth case (5'-CGC sequence with [-ca]-B[a]P-N(2)-dG), the known NMR conformation is computed to be second lowest in energy, but it is within approximately 1.7 kcal of the computed lowest energy conformation. These results suggest that molecular modeling is surprisingly accurate in computing lowest energy conformations and that it should be useful in assessing the relative energies of different conformations. This is especially important given that currently molecular modeling is the only means available to study the energetics of minor conformations of DNA adducts.

Benzo(a)pyrene↗

PubMedDate not supplied

Mathematical models of cochlear nucleus onset neurons: II. model with dynamic spike-blocking state.

Onset (On) neurons in the cochlear nucleus (CN), characterized by their prominent response to the onset followed by little or no response to the steady-state of sustained stimuli, have a remarkable ability to entrain (firing 1 spike per cycle of a periodic stimulus) to low-frequency tones up to 1000 Hz. In this article, we present a point-neuron model with independent, excitatory auditory-nerve (AN) inputs that accounts for the ability of On neurons to both produce onset responses for high-frequency tone bursts and entrain to a wide range of low-frequency tones. With a fixed-duration spike-blocking state after a spike (an absolute refractory period), the model produces entrainment to a broad range of low-frequency tones and an On response with short interspike intervals (chopping) for high-frequency tone bursts. To produce On response patterns with no chopping, we introduce a novel, more complex, active membrane model in which the spike-blocking state is maintained until the instantaneous membrane voltage falls below a transition voltage. During the sustained depolarization for a high-frequency tone burst, the new model does not chop because it enters a spike-blocking state after the first spike and fails to leave this state until the membrane voltage returns toward rest at the end of the stimulus. The model entrains to low-frequency tones because the membrane voltage falls below the transition voltage on every cycle when the AN inputs are phase-locked. With the complex membrane model, On response patterns having moderate steady-state activity for high-frequency tone bursts (On-L) are distinguished from those having no steady-state activity (On-I) by requiring fewer AN inputs. Voltage-gated ion channels found in On-responding neurons of the CN may underlie the hypothesized dynamic spike-blocking state. These results provide a mechanistic rationale for distinguishing between the different physiological classes of CN On neurons.

Acoustic Stimulation↗

PubMed2003

The potential synergy between cognitive models and modern psychometric models.

Analyses of cognitive aspects of survey methodology (CASM) and psychometric analysis are two methods that are able to complement each other. We use concrete examples to illustrate how psychometric analyses can test hypotheses from CASM. The psychometrics framework recognizes that survey responses are affected by other factors than the concept being assessed, for example by cognitive factors and processes. Such factors are subsumed under the concept of measurement error. Possible sources of measurement error can be tested, e.g. by randomized experiments. A standard way to reduce measurement error is to ask several questions about the same concept and combine the answers into a multi-item scale that is more precise than the individual items. Techniques like structural equation models use the item correlations to assess the magnitude of measurement error and to test the assumptions behind the multi-item scale, e.g. the effect of common response choices and item time frames. A central problem in modern psychometrics is how to model the mapping of the continuous latent variable onto the item response choice categories. This is achieved by threshold models (e.g. item response models and structural equation models for categorical data). These models can, for example, analyze the impact of mode of administration, test whether the items function in the same way for all people (measurement invariance/differential item functioning) and examine the consistency of responses from any single person. Such analyses provide new possibilities for combining psychometrics and cognitive methods.

Attitude to Health↗

PubMed1987

Structural-equation models of current drug use: are appropriate models so simple(x)?

The simplex and common-factor models of drug use were compared using maximum-likelihood estimation of latent variable structural models in two samples: a sample of 226 high school students, using ratio-scale measures of current drug use, and a sample of 310 industrial workers and 811 college students, using ordinal-scale measures of current drug use. Latent variables of alcohol, marijuana, enhancer hard drugs, and dampener hard drugs were specified in a series of structural models. Contrary to previous findings with cumulative drug-use data, the common-factor model provided a more acceptable representation of the observed current-use data than did the simplex model in both samples. In addition, the similarity of results across both of these samples supports recent contentions by Huba and Bentler (1982) that quantitatively measured variables are not necessarily superior to qualitative, ordinal indicators in latent variable models of drug use.

Adolescent↗

PubMed1993

A queue-series model for reaction time, with discrete-stage and continuous-flow models as special cases.

This article presents a new reaction time model that includes both sequential-stage (discrete) and overlapping-stage (continuous-flow) models as special cases. In the new model, task performance is carried out by a series of distinct processing stages, each of which functions as a queue. A stimulus conveys 1 or more distinct components of information (e.g., features), and each stage can begin processing as soon as it receives 1 component from its predecessor. If a stimulus activates only 1 component, successive stages operate in strict sequence; if it activates multiple components, successive stages operate with temporal overlap. Within this class of models, experimental factors affecting different processing stages always have additive effects on reaction time with sequential stages but rarely do so with overlapping stages. Within this class of models, then, observations of factor additivity support discrete-stage models.

Attention↗

PubMed2002

Analysis of multivariate frequency data by graphical models and generalizations of the multidimensional row-column association model.

Models used to analyze cross-classifications of counts from psychological experiments must represent associations between multiple discrete variables and take into account attributes of stimuli, experimental conditions, or characteristics of subjects. The models must also lend themselves to psychological interpretations about underlying structures mediating the relationship between stimuli and responses. To meet these needs, the author extends the graphical latent variable models for nominal and/or ordinal data proposed by C. J. Anderson and J. K. Vermunt (2000) to situations in which dependencies between observed variables are not fully accounted for by the latent variables. The graphical models provide a unified framework for studying multivariate associations that include log-linear models and log-multiplicative association models as special cases.

Humans↗