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PubMed2004

Agent-based computational modeling of wounded epithelial cell monolayers.

Computational modeling of biological systems, or in silico biology, is an emerging tool for understanding structure and order in biological tissues. Computational models of the behavior of epithelial cells in monolayer cell culture have been developed and used to predict the healing characteristics of scratch wounds made to urothelial cell cultures maintained in low- and physiological [Ca2+] environments. Both computational models and in vitro experiments demonstrated that in low exogenous [Ca2+], the closure of 500-microm scratch wounds was achieved primarily by cell migration into the denuded area. The wound healing rate in low (0.09 mM) [Ca2+] was approximately twice as rapid as in physiological (2 mM) [Ca2+]. Computational modeling predicted that in cell cultures that are actively proliferating, no increase in the fraction of cells in the S-phase would be expected, and this conclusion was supported experimentally in vitro by bromodeoxyuridine incorporation assay. We have demonstrated that a simple rule-based model of cell behavior, incorporating rules relating to contact inhibition of proliferation and migration, is sufficient to qualitatively predict the calcium-dependent pattern of wound closure observed in vitro. Differences between the in vitro and in silico models suggest a role for wound-induced signaling events in urothelial cell cultures.

Algorithms↗
PubMed2005

Computational modeling of dendrites.

Computational methods have been part of neuroscience for many years. For example, models developed with these methods have provided a theory that helps explain the action potential. More recently, as experimental patch-electrode techniques have revealed new biophysics related to dendritic function and synaptic integration, computational models of dendrites have been developed to explain and further illuminate these results, and to predict possible additional behavior. Here, a collection of computational models of dendrites is reviewed. The goal is to help explain how such computational techniques work, some of their limitations, and what one can hope to learn about dendrites by modeling them.

Action Potentials↗
PubMed2001

A computer model of human atria with reasonable computation load and realistic anatomical properties.

Atrial fibrillation is the most frequent arrhythmia, provoking discomfort, heart failure and arterial embolisms. The aim of this work is to develop a simplified anatomical computer model of human atria for the study of atrial arrhythmias and the understanding of electrical propagation mechanisms. With the model we propose, up to 40 s of real-time propagation have been simulated on a single-processor computer. The size and the electrophysiological properties of the simulated atria are within realistic values and information about anatomy has been taken into account in a three-dimensional structure. Besides normal sinus beat, pathological phenomena such as flutter and fibrillation have been induced using a programmed stimulation protocol. One important observation in our model is that atrial arrhythmias are a combination of functional and anatomical reentries and that the geometry plays an important role. This virtual atrium can reproduce electrophysiological observations made in humans but with the advantage of showing in great detail how arrhythmias are initiated and sustained. Such details are difficult or impossible to study in humans. This model will serve us as a tool to evaluate the impact of new therapeutic strategies and to improve them.

Atrial Fibrillation↗
PubMed1996

Dynamic relationships of trabecular bone density, architecture, and strength in a computational model of osteopenia.

A computational model was developed to study the effects of short- and long-term periods of disuse osteopenia and repair to elucidate the interrelationships between bone mass, architecture, and strength. The model is one in which the sequence of structural change events is followed in time. This temporal feature contrasts with studies of real trabecular tissue which are necessarily cross-sectional in nature and do not lend themselves to insights into the dynamic nature of the structural changes with time. In the model it was assumed that the stimulus for bone adaptation to mechanical load is the local mechanical strain rate, according to which the trabecular surfaces are differentially formed and resorbed. The effects of mechanical loading and unloading (disuse) on the cancelous bone properties were studied. The bone mass, architecture, and elastic stiffness were shown to be strongly dependent upon the period of the unloading phase, as well as the period of the reloading phase. Mechanical stiffness is demonstrated computationally to be a multivalued function of bone mass, if architecture is not accounted for. The model shows how the same value of trabecular bone mass can be associated with two or more distinct values of biomechanical stiffness. This result is the first explicit demonstration of how bone mass, architecture, and strength are related under dynamical load-bearing conditions. The results explain the empirical observation that bone mass can account for about 65% of the observed variation in bone strength, but that by incorporating measures of bony architecture into the analysis, the predictability is increased to 94%. The computational model may be used to explore the effects of different loading regimes on mass, architecture, and strength, and potentially for assistance in designing both animal and clinical bone loss studies.

Adaptation, Physiological↗
PubMed1997

Comparing breastfeeding and breast pumps using a computer model.

There is a role for computer models in increasing the understanding of milk extraction from the human teat. A computer model can be used to investigate aspects of extracting milk from the human teat which are not feasible using clinical experiments. In this paper, the behavior of the human teat during an infant suckling and with the use of a breast pump is modeled. The model is used to (1) identify the role of suction and the peristaltic motion of the tongue during suckling and (2) compare the volume of milk extracted by an infant breastfeeding with that obtained using a breast pump. Infants use a peristaltic motion of the tongue, along with some suction, to extract milk. Breast pumps use a cyclic pattern of suction only. In the model, the human teat is represented as a cylindrical porous elastic material saturated with fluid. We mimic an infant suckling by imposing both suction and a peristaltic force in the computer model of the human teat. This is compared to the effect of suction only, which models the action of breast pumps. The results demonstrate that there is an optimal time to apply the peristaltic force during the suction cycle which will increase the milk volume. The model and results may be of use in the future design of effective breast pumps.

Breast Feeding↗
PubMed1976

Influence of vessel distension and myogenic tone on pulmonary arterial input impedance. A study using a computer model of rabbit lung.

A computer model of the pulmonary arterial (PA) bed of rabbit lungs was designed in order to test experimental observations of changes in PA input impedance and pulsatile hydraulic power (cap.) during increased PA pressure. The computer model was based on a simple 3-component analog representation of single vessels (i.e. resistance, inertance and compliance). 16 generations of arterial vessels, from PA to 60 mum diameter, were combined to calculate PA input impedance. Input impedance was found to mimic closely that observed experimentally. Both venous pressure elevation and arteriolar constriction was found to reduce input impedance and Wp. By combining arteriolar constriction with increased myogenic tone of the larger arteries, Wp was found to show a minimum level at a certain PA pressure, dependent on the degree of arterial stiffening. Wp was found to follow changes in arterial volume and resistance during stimulated vasoconstriction. Wp dissipation in arterial vessels was calculated to approx. 50% of total imput Wp at physiological pressure conditions, and could be reduced by one half after PA pressure increase from 20 to 50 cm H2O, despite a concurrent halving of arterial compliance. Arterial vessels smaller than 200 mum diameter were found to have negligible direct influence on PA input impedance.

Animals↗
PubMed2006

Applying computational modeling to drug discovery and development.

Computational models of cells, tissues and organisms are necessary for increased understanding of biological systems. In particular, modeling approaches will be crucial for moving biology from a descriptive to a predictive science. Pharmaceutical companies identify molecular interventions that they predict will lead to therapies at the organism level, suggesting that computational biology can play a key role in the pharmaceutical industry. We discuss pharmaceutically-relevant computational modeling approaches currently used as predictive tools. Specific examples demonstrate how companies can employ these computational models to improve the efficiency of transforming targets into therapies.

Animals↗
PubMed1976

[Computer models of personality: implications for measurement].

Computer models of human behavior have long existed in the world of science fiction; however, in reality, progress has been slow. Research has concentrated, in recent years, on the simulation of memory and cognition. Computer models of personality, although fascinating and potentially useful, have been neglected. This paper reviewed the research done to date, categorizing it under five headings: (a) models of belief systems; (b) models of interpersonal behavior; (c) models of decision-making processes; (d) prediction models; and (e) theory-based simulations of specific processes. One practical application was then explored in depth, that of using the computer models in personality measurement. Although some practical development of the working simulations would have to precede their application to personality measurement, it was felt that such an application would be feasible and useful.

Attitude↗
PubMed2005

Mathematical and computational modelling of spatio-temporal signalling in rod phototransduction.

Rod photoreceptors are activated by light through activation of a cascade that includes the G protein-coupled receptor rhodopsin, the G protein transducin, its effector cyclic guanosine monophosphate (cGMP) phosphodiesterase and the second messengers cGMP and Ca2+. Signalling is localised to the particular rod outer segment disc, which is activated by absorption of a single photon. Modelling of this cascade has previously been performed mostly by assumption of a well-stirred cytoplasm. We recently published the first fully spatially resolved model that captures the local nature of light activation. The model reduces the complex geometry of the cell to a simpler one using the mathematical theories of homogenisation and concentrated capacity. The model shows that, upon activation of a single rhodopsin, changes of the second messengers cGMP and Ca2+ are local about the particular activated disc. In the current work, the homogenised model is computationally compared with the full, non-homogenised one, set in the original geometry of the rod outer segment. It is found to have an accuracy of 0.03% compared with the full model in computing the integral response and a 5200-fold reduction in computation time. The model can reconstruct the radial time-profiles of cGMP and Ca2+ in the interdiscal spaces adjacent to the activated discs. Cellular electrical responses are localised near the activation sites, and multiple photons sufficiently far apart produce essentially independent responses. This leads to a computational analysis of the notion and estimate of 'spread' and the optimum distribution of activated sites that maximises the response. Biological insights arising from the spatio-temporal model include a quantification of how variability in the response to dim light is affected by the distance between the outer segment discs capturing photons. The model is thus a simulation tool for biologists to predict the effect of various factors influencing the timing, spread and control mechanisms of this G protein-coupled, receptor-mediated cascade. It permits ease of simulation experiments across a range of conditions, for example, clamping the concentration of calcium, with results matching analogous experimental results. In addition, the model accommodates differing geometries of rod outer segments from different vertebrate species. Thus it represents a building block towards a predictive model of visual transduction.

Animals↗
PubMedDate not supplied

Model reduction in the computational modeling of reaction systems.

The underlying assumption for most lumping techniques is that the reduced models must be valid for the entire composition space. This is a harsh requirement that often limits the models that are generated. The scheme that is presented here uses the inherent structure of reaction systems to divide the composition space into regions. Within each region, the order-of-magnitude relationships that exist between terms in the rate equations are used to systematically reduce the order and coupling of the model. The full system is then described through piecewise combination of these simpler, region-specific models. Although these reduced models are based on assumptions that make them invalid globally, they are accurate within the regions for which they have been crafted.

Algorithms↗
PubMed2001

Optimization of background electrolytes for capillary electrophoresis I. Mathematical and computational model.

A mathematical and computational model is introduced for optimization of background electrolyte systems for capillary zone electrophoresis of anions. The model takes into account mono- or di- or trivalent ions and allows also for modeling of highly acidic or alkaline electrolytes, where a presence of hydrogen and hydroxide ions is significant. At maximum, the electrolyte can contain two co-anions and two counter-cations. The mathematical relations of the model are formulated to enable an easy algorithmization and programming in a computer language. The model assesses the composition of the background electrolyte in the analyte zone, which enables prediction of the parameters of the system that are experimentally available, like the transfer ratio, which is a measure of the sensitivity in the indirect photometric detection or the molar conductivity detection response, which expresses the sensitivity of the conductivity detection. Furthermore, the model also enables the evaluation of a tendency of the analyte to undergo electromigration dispersion and allows the optimization of the composition of the background electrolyte to reach a good sensitivity of detection while still having the dispersion properties in the acceptable range. Although the model presented is aimed towards the separation of anions, it can be straightforwardly rearranged to serve for simulation of electromigration of cationic analytes. The suitability of the model is checked by inspecting the behavior of a phosphate buffer for analysis of anions. It is shown that parameters of the phosphate buffer when used at neutral and alkaline pH values possess singularities that indicate a possible occurrence of system peaks. Moreover, if the mobility of any analyte of the sample is close to the mobilities of the system peaks, the indirect detector signals following the background electrolyte properties will be heavily amplified and distorted. When a specific detector sensitive on presence of the analyte were used, the signal would be almost lost due to the excessive dispersion of the peak.

Electrolytes↗
PubMed1989

Clinical application of electrocardiographic computer model.

A three-dimensional computer model was developed to stimulate the ventricular depolarization and repolarization in a clinical setting. The ventricle is composed of approximately 50,000 units arranged in a cubic close-packed structure and the specialized conduction system is distributed so as to obtain the excitation sequence resembling normal ventricular depolarization. The normal distribution of action potential waveforms with the longest duration on the endocardium and the shortest on the epicardium is used in the model. The heart model is mounted in a homogeneous torso model, and the body surface potential distribution generated by the electric dipoles is calculated using the boundary element method. The QRST waveforms corresponding to the normal and some abnormal heart conditions, such as bundle branch block, myocardial infarction, apical hypertrophic cardiomyopathy, and Wolff-Parkinson-White syndrome, is obtained by assuming the abnormal area with altered electrical properties. Thus the three-dimensional computer model may provide further insight into the genesis of the clinical electrocardiogram.

Bundle-Branch Block↗
PubMed1997

Diagnosing congenital heart defects using the Fallot computational model.

This paper describes a computational model developed for the diagnosis of multiple defects. If multiple defects interact, meaning that the cues observable for multiple defects are not a sum of the cues observable for the component defects, diagnosis is particularly difficult. We developed a description and classification of the ways cues change when defects interact. A computational model (named Fallot) was implemented and a knowledge-base was constructed for the diagnosis of congenital heart defects. On each case, Fallot performs recognition-based reasoning followed by solution construction and evaluation with the cue combination methods. Fallot was tested on cases from hospital files and correctly diagnoses cases with multiple interacting defects for which conventional methods are not applicable or fail.

Abnormalities, Multiple↗
PubMed2006

A biological approach to computational models of proteomic networks.

Computational modeling is useful as a means to assemble and test what we know about proteins and networks. Models can help address key questions about the measurement, definition and function of proteomic networks. Here, we place these biological questions at the forefront in reviewing the computational strategies that are available to analyze proteomic networks. Recent examples illustrate how models can extract more information from proteomic data, test possible interactions between network proteins and link networks to cellular behavior. No single model can achieve all these goals, however, which is why it is critical to prioritize biological questions before specifying a particular modeling approach.

Computer Simulation↗
PubMed2000

Computational model of intracellular pharmacokinetics of paclitaxel.

The intracellular pharmacokinetics of paclitaxel is closely related to its pharmacodynamics. Although drug transport across the cell membrane and extracellular and intracellular drug binding have been shown to affect intracellular drug accumulation, their quantitative relationship is unknown. This study was designed to establish a mathematical model for computing the intracellular paclitaxel pharmacokinetics. As a starting point, the model assumes drug transport into and out of cells via passive diffusion. Experimental data on the intracellular pharmacokinetics of [(3)H]paclitaxel were obtained using monolayer cultures of human breast MCF7 tumor cells, which have negligible expression of the mdr1 P-glycoprotein. The results indicate that, in addition to drug binding and microtubule concentration, changes in cell number due to cell growth and drug effects also affected intracellular drug accumulation. A kinetic model was developed to describe several concomitant processes: 1) saturable drug binding to extracellular proteins, 2) saturable and nonsaturable drug binding to intracellular components, 3) time- and concentration-dependent drug depletion from culture medium, 4) cell density-dependent drug accumulation, and 5) time- and drug concentration-dependent enhancement of tubulin concentration. The model was validated by the close prediction (<7% deviation) of the effects of extracellular-to-intracellular concentration gradient and cell density on the kinetics of drug accumulation and efflux. This model was used to predict the effects of changing several parameters (number and binding affinity of intracellular binding sites, free fraction, and concentration of drug in extracellular fluid) on intracellular drug accumulation. In conclusion, the computational model of intracellular paclitaxel pharmacokinetics provides the means to predict drug concentration in cells.

Antineoplastic Agents, Phytogenic↗
PubMed2004

Functionally and structurally integrated computational modeling of ventricular physiology.

Computational biology is integrative in several ways. Functionally, computational models are valuable for integrating the many interacting processes within biochemical networks and the many interacting physiological subsystems within the cell. Structurally detailed models provide a way of integrating across scales of biological organization from molecule to organism. Data integration across diverse laboratory and clinical measurements is another unique strength of computational biology. We describe examples of all three categories of integration by using recent advances in modeling cardiac excitation-contraction coupling and whole-heart electromechanics in health and disease.

Animals↗
PubMed1992

Three-dimensional structure for the beta 2 adrenergic receptor protein based on computer modeling studies.

Computer-aided model building techniques have been used to construct three-dimensional model structures for hamster beta 2 adrenergic receptor. Experimental data were used as constraints to guide the model building procedure, and a number of rather strict criteria were applied to assess the physical plausibility of model structures. We present details of our best model structure to date, which is consistent with a large body of experimental data. We also discuss in detail our model building procedures and evaluation criteria, which we believe may be of general utility in modeling projects.

Amino Acid Sequence↗
PubMed1990

Termination of macro-reentrant tachycardia by a single extrastimulus delivered during the 'effective' refractory period: a computer modeled 'case report'.

A computer model of cardiac excitation sequences was used to reproduce atrioventricular (AV) reentrant tachycardia (AVRT) and its termination by a single 'on-circuit' extrastimulus. The model simulated activation waves revolving along a one-dimensional circular pathway, the portions of which represented the atrial, AV nodal, His-Purkinje, ventricular, and accessory pathway sections of the tachycardia circuit. The modeled pathway was composed of 289 elements. The model distinguished only the depolarised and resting states of constituent elements, but introduced differential refractoriness and conduction velocity for each element. These values approximated the natural situation established in a patient suffering from AVRT associated with the right bundle branch block. The results of the study suggest that: (A) the usual impression of a regular recovery wave and of a regular excitable window moving uniformly along the macro-reentrant circular path is incorrect; (B) during the tachycardia, islands of repolarized cells appear which are surrounded by tissue that is still refractory; (C) an extrastimulus which captures the island of early repolarized tissue may cause an excitation restricted to a small part of the myocardium but the local refractoriness following such an extrastimulus may be sufficient to terminate the tachycardia.

Atrioventricular Node↗