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Mathematical modelling of tumour-induced angiogenesis: network growth and structure.

Angiogenesis, the formation of blood vessels from a pre-existing vasculature, is a process whereby capillary sprouts are formed in response to externally supplied chemical stimuli. The sprouts then grow and develop, driven initially by endothelial cell migration, and organise themselves into a branched, connected network. Subsequent cell proliferation near the sprout-tips permits further extension of the capillaries and ultimately completes the process. Angiogenesis occurs during embryogenesis, wound healing, arthritis and during the growth of solid tumours. In this chapter we first of all present a review of a variety of mathematical models which have been used to describe the formation of capillary networks and then focus on a specific recent model which uses novel mathematical modelling techniques to generate both 2 and 3 dimensional vascular structures. The modelling focusses on key events of angiogenesis such as the migratory response of endothelial cells to exogenous cytokines (tumour angiogenic factors, TAF) secreted by a solid tumour; endothelial cell proliferation; endothelial cell interactions with extracellular matrix macromolecules such as fibronectin; matrix degradation; capillary sprout branching and anastomosis. Numerical simulations of the model, using parameter values based on experimental data, are presented and the theoretical structures generated by the model are compared with the morphology of actual capillary networks observed in in vivo experiments. A final section discusses the use of the mathematical model as a possible angiogenesis assay and implications for chemotherapy regimes.

Animals↗

Use of Adair four-step kinetics in mathematical simulation of oxygen transport in the microcirculation.

The Adair four-step kinetic model for the reactions of haemoglobin and oxygen recognizes five haemoglobin species, corresponding to deoxyhaemoglobin and one species for each level of oxygenation of the four haem groups. Thus, an oxygen transport problem involves a system of five simultaneous non-linear partial differential equations for diffusion with chemical reaction. This mathematical complexity has impeded application of the Adair model despite its theoretical advantages over the one-step model often used in practice. The Adair kinetic model has been incorporated into a simulation of microcirculatory oxygen transport. The results show that the usual one-step kinetic model is inaccurate in comparison with the Adair model. However, an empirical modification can be made to the one-step model to ensure compatibility with the equilibrium curve. This modified one-step kinetic model (the VRC model) is much more tractable mathematically than the Adair model. In the physiological range of fluxes, the VRC kinetic model appears to be of sufficient accuracy for most purposes, and the mathematical complexity of the Adair model is not required.

Biological Transport, Active↗

Mathematical model of the metabolism of 123I-16-iodo-9-hexadecenoic acid in an isolated rat heart. Validation by comparison with experimental measurements.

The aim of the present study was to demonstrate that it is possible to estimate the intracellular metabolism of a fatty acid labelled with iodine using external radioactivity measurements. 123I-16-iodo-9-hexadecenoic acid (IHA) was injected close to the coronary arteries of isolated rat hearts perfused according to the Langendorff technique. The time course of the cardiac radioactivity was measured using an INa crystal coupled to an analyser. The obtained curves were analysed using a four-compartment mathematical model, with the compartments corresponding to the vascular-IHA (O), intramyocardial free-IHA (1), esterified-IHA (2) and iodide (3) pools. Curve analysis using this model demonstrated that, as compared to substrate-free perfusion, the presence of glucose (11 mM) increased IHA storage and decreased its oxidation. These changes were enhanced by the presence of insulin. A comparison of these results with measurements of the radioactivity levels within the various cellular fractions validated our proposed mathematical model. Thus, using only a mathematical analysis of a cardiac time-activity curve, it is possible to obtain quantitative information about IHA distribution in the different intracellular metabolic pathways. This technique is potentially useful for the study of metabolic effects of ischaemia or anoxia, as well as for the study of the influence of various substrates or drugs on IHA metabolism in isolated rat hearts.

Animals↗

A mathematical model representing the extraneuronal O-methylating system of the perfused rat heart.

1. A mathematical model was developed to mimic the function of the extraneuronal O-methylating system of the rat heart. Its essential features are: a saturable uptake process (uptake 2), a saturable, intracompartmental enzyme (COMT), the ability of the catecholamine to penetrate the membrane of the model compartment by a diffusional flux obeying first-order kinetics, and the ability of the metabolite to leave the compartment by an efflux obeying first-order kinetics. 2. Of the six kinetic constants of the model compartment five are known from experiments with hearts perfused with 3H-isoprenaline (Kmuptake, Vmaxuptake, Vmaxenzyme, k for amine, k for metabolite); only one constant is unknown (Kmenzyme) for the intact heart cells. 3. Results calculated with the help of the mathematical model were compared with results obtained from rat hearts perfused with 3H-isoprenaline. Although full congruency of results cannot be expected, there was satisfactory agreement between the two sets of results. Apparently, the mathematical model is able to simulate the function of the O-methylating system of the rat heart. 4. Comparison of the two sets of results leads to a definition of the function of the O-methylating system of the perfused rat heart. if all cells of the rat heart participate in the O-methylating system, the Km of the COMT of intact heart cells must be very low (i.e., somewhere between 2 and 5 microM isoprenaline). However, if the O-methylating system comprises only a small fraction of all cells, the COMT of the intact heart cells may well have a correspondingly higher Km.

Animals↗

[A mathematical model of the biomechanics of respiration during artificial ventilation of the lungs].

The authors review a mathematic model of the respiratory biomechanics during artificial lung ventilation, presenting a subsystem of the mathematic model of respiration designed at the All-Union Research Surgery Center of the USSR AMS and used in the medical information diagnostic system elaborated for the Department of Resuscitation and Intensive Care, provide differential equations of the mathematic model, the results of the numerical solution of the model and an example of using the model for solving a private problem of selecting an adequate mode of artificial lung ventilation.

Biomechanical Phenomena↗

Mathematical modelling in nuclear medicine.

Modern imaging techniques can provide sequences of images giving signals proportional to the concentrations of tracers (by emission tomography), of X-ray-absorbing contrast materials (fast CT or perhaps NMR contrast), or of native chemical substances (NMR) in tissue regions at identifiable locations in 3D space. Methods for the analysis of the concentration-time curves with mathematical models describing the physiological processes and the appropriate anatomy are now available to give a quantitative portrayal of both structure and function: such is the approach to metabolic or functional imaging. One formulates a model first by defining what it should represent: this is the hypothesis. When translated into a self-consistent set of differential equations, the model becomes a mathematical model, a quantitative version of the hypothesis. This is what one would like to test against data. However, the next step is to reduce the mathematical model to a computable form; anatomically and physiologically realistic models account of the spatial gradients in concentrations within blood-tissue exchange units, while compartmental models simplify the equations by using the average concentrations. The former are known as distributed models and the latter as lumped compartmental or mixing chamber models. Since both are derived from the same ideas, the parameters are usually the same; their differences are in their ability to represent the hypothesis correctly, quantitatively, and sometimes in their computability. In this essay we review the philosophical and practical aspects of such modelling analysis for translating image sequences into physiological terms.

Computer Simulation↗

On the mathematical modelling of pain.

In this review a case is presented for the use of mathematical modelling in the study of pain. The philosophy of mathematical modelling is outlined and a recommendation is made for the use of modern nonlinear techniques and computational neuroscience in the modelling of pain. Classic and more recent examples of modelling in neurobiology in general and pain in particular, at three different levels-molecular, cellular and neural networks-are described and evaluated. Directions for further progress are indicated, particularly in plasticity and in modelling brain mechanisms. Major advantages of mathematical modelling are that it can handle extremely complex theories and it is non-invasive, and so is particularly valuable in the investigation of chronic pain.

Analgesia↗

Mathematical elegance with biochemical realism: the covarion model of molecular evolution.

There is an apparent paradox in our understanding of molecular evolution. Current biochemically based models predict that evolutionary trees should not be recoverable for divergences beyond a few hundred million years. In practice, however, trees often appear to be recovered from much older times. Mathematical models, such as those assuming that sites evolve at different rates [including a Gamma distribution of rates across sites (RAS)] may in theory allow the recovery of some ancient divergences. However, such models require that each site maintain its characteristic rate over the whole evolutionary period. This assumption, however, contradicts the knowledge that tertiary structures diverge with time, invalidating the rate-constancy assumption of purely mathematical models. We report here that a hidden Markov version of the covarion model can meet both biochemical and statistical requirements for the analysis of sequence data. The model was proposed on biochemical grounds and can be implemented with only two additional parameters. The two hidden parts of this model are the proportion of sites free to vary (covarions) and the rate of interchange between fixed sites and these variable sites. Simulation results are consistent with this approach, providing a better framework for understanding anciently diverged sequences than the standard RAS models. However, a Gamma distribution of rates may approximate a covarion model and may possibly be justified on these grounds. The accurate reconstruction of older divergences from sequence data is still a major problem, and molecular evolution still requires mathematical models that also have a sound biochemical basis.

Evolution, Molecular↗

Spatially-explicit matrix models. A mathematical analysis of stage-structured integrodifference equations.

This paper is concerned with mathematical analysis of the 'critical domain-size' problem for structured populations. Space is introduced explicitly into matrix models for stage-structured populations. Movement of individuals is described by means of a dispersal kernel. The mathematical analysis investigates conditions for existence, stability and uniqueness of equilibrium solutions as well as some bifurcation behaviors. These mathematical results are linked to species persistence or extinction in connected habitats of different sizes or fragmented habitats; hence the framework is given for application of such models to ecology. Several approximations which reduce the complexity of integrodifference equations are given. A simple example is worked out to illustrate the analytical results and to compare the behavior of the integrodifference model to that of the approximations.

Algorithms↗

Mathematical models and their application in body composition research.

Mathematical models are a means of formalizing the knowledge on living systems obtained in clinical physiology and theoretical biophysics. They allow the actual processes in living systems to be described and the mechanisms of these systems to be evaluated. The study of body composition strives to quantitatively evaluate intrinsic body compartments and to obtain important information on the nutritional and energy requirements of healthy persons and those with various pathologies. Although there has been great progress in the development of sophisticated instruments for body composition research, it is not always possible to directly measure certain body compartments (e. g. intracellular water and fat mass) because of either technical difficulties or for ethical reasons. Therefore, mathematical models, which can potentially estimate these compartments indirectly, may be a viable alternative. In this paper, we describe the various advances in the use of mathematical models for body composition research.

Body Composition↗

A new mathematical model based on clinical and laboratory variables for the diagnosis of Sjögren's syndrome.

Sjögren's syndrome (SS) is a systemic autoimmune disease that mainly affects exocrine glands. A diagnosis of SS in its early stages has a potential clinical relevance, but it is difficult and cannot be made solely on clinical grounds. Several sets of diagnostic criteria have been proposed, but none has met with a general consensus. Minor salivary gland has been judged to be the "gold standard" for the diagnosis of SS. However, it is a painful procedure and has a small but significant proportion of both false positive and false negative results. The aim of our study was to develop a simple mathematical score that uses clinical and laboratory variables for diagnosing SS, thereby reducing the need of minor salivary gland. The following variables were included in the model: ANA, SS-A/SS-B, Schirmer's Test/BUT, C3/C4, serum gammaglobulin levels. One hundred consecutive individuals reporting clinical syndromes consistent with a sicca syndrome were included in the study. The application of our multifactorial mathematical model has shown a high predictive value for SS vs controls or vs patients with other autoimmune disorders (Sensitivity 93%, Specificity 100%), with an estimated minor salivary gland reduction of 77%. We conclude that our mathematical model can be considered a useful non-invasive approach for diagnosing Sjogren's Syndrome and recommend its validation on a larger scale.

Adult↗

Simple stochastic fingerprints towards mathematical modeling in biology and medicine 2. Unifying Markov model for drugs side effects.

Most of present mathematical models for biological activity consider just the molecular structure. In the present article we pretend extending the use of Markov chain models to define novel molecular descriptors, which consider in addition other parameters like target site or biological effect. Specifically, this mathematical model takes into consideration not only the molecular structure but the specific biological system the drug affects too. Herein, a general Markov model is developed that describes 19 different drugs side effects grouped in eight affected biological systems for 178 drugs, being 270 cases finally. The data was processed by linear discriminant analysis (LDA) classifying drugs according to their specific side effects, forward stepwise was fixed as strategy for variables selection. The average percentage of good classification and number of compounds used in the training/predicting sets were 100/95.8% for endocrine manifestations, (18 out of 18)/(13 out of 14); 90.5/92.3% for gastrointestinal manifestations, (38 out of 42)/(30 out of 32); 88.5/86.5% for systemic phenomena, (23 out of 26)/(17 out of 20); 81.8/77.3% for neurological manifestations, (27 out of 33)/(19 out of 25); 81.6/86.2% for dermal manifestations, (31 out of 38)/(25 out of 29); 78.4/85.1% for cardiovascular manifestation, (29 out of 37)/(24 out of 28); 77.1/75.7% for breathing manifestations, (27 out of 35)/(20 out of 26) and 75.6/75% for psychiatric manifestations, (31 out of 41)/(23 out of 31). Additionally a back-projection analysis (BPA) was carried out for two ulcerogenic drugs to prove in structural terms the physical interpretation of the models obtained. This article develops a mathematical model that encompasses a large number of drugs side effects grouped in specifics biological systems using stochastic absolute probabilities of interaction ((A)pi(k)(j)) by the first time.

Drug-Related Side Effects and Adverse Reactions↗

Regional myocardial stress distribution from magnetic resonance image-based mathematical models.

The instantaneous regional stress distribution within the myocardium, which cannot be directly measured, has been estimated using improved numerical methods and nonaxisymmetric biventricular geometry. To do this, we have employed computer-aided solid mathematical modeling to generate a three-dimensional representation for an ex vivo canine biventricular unit using magnetic resonance imaging. A two-dimensional transverse section was isolated from the solid mathematical model for regional stress analysis using p-version finite element analysis. Loading conditions and material property descriptions were taken from published reports. Analyses showed the maximum principal stresses to range from -1.76 X 10(5) to 8.52 X 10(5) dynes/cm2 during systolic loading, and from -3.85 X 10(4) to 1.13 X 10(5) dynes/cm2 during diastolic loading. This study demonstrates that magnetic resonance image-based solid mathematical biventricular models are suitable for regional stress analysis using p-version finite element analysis. p-Version finite element analysis using magnetic resonance image-based cardiac representations facilitates in vivo stress-strain analyses and may allow the clinical estimation of regional myocardial stress.

Animals↗

Mathematical modeling of dendritic growth in vitro.

The dendritic branching pattern of cultured hippocampal neurons was analyzed to obtain mathematical parameters that fit the time-dependent growth of dendrites under limited extrinsic influence. Cultured neurons were stained with a non-toxic carbocyanine dye (diO) and pyramidal-shaped neurons that were physically separated from one another were analyzed at post-plating days 1, 2, 3, 4, 6 and 7. The geometric branching pattern of the dendrites was analyzed using a mathematical model that incorporates random effects in the form of a Galton-Watson branching process where splitting of one branch is statistically independent of the splitting of all other branches, and deterministic effects in the form of a parameter that measures the extent to which dense patterns (clusters) or sparse patterns (elongated trees) are formed. The geometric branching pattern of the dendrites was analyzed using a mathematical model that incorporates random and deterministic effects. The model parameters were estimated via the method of maximum likelihood. The data suggest that in vitro basal dendrites grow according to a purely random branching process without pronounced dense or sparse patterns, while apical dendrites tend to form elongated trees with fewer secondary bifurcations. This trend is quantified, and it depends on the culture conditions in which the neurons are grown. The quantitative assessment of various influences on dendritic growth patterns are discussed.

Animals↗

Evaluation of a mathematical model analysing the relation between intradental nerve impulse activity and perceived pain in man.

In this investigation the usefulness and accuracy of the parameters of a mathematical model for the analysis of the effectiveness of different pain relieving procedures on pulpal pain were studied. The investigation was carried out using a previously developed mathematical/biological model on data from original subject recordings of Intradental Nerve Impulse Activity (INA) and pain estimations. Computer simulated INA and pain estimation curves were also used to enable calculation of the mathematical and biological conditions that are essential for the actual mathematical/biological model, and to facilitate the interpretation of the parameters of the model. It was shown by means of both real and simulated data that the mathematical model is well suited for the analysis of the effectiveness of some pain relieving procedures on pulpal pain. It was also shown that, by means of three new variables, the model could be made even more accurate and useful for this application.

Computer Simulation↗

A mathematical model of physiological processes and its application to the study of aging.

The behavior of a physiological system which, after displacement, returns by homeostatic mechanisms to its original condition can be described by a simple differential equation in which the "recovery time" is a parameter. Two such systems, which influence one another, can be linked mathematically by the use of "coupling" or "feedback" coefficients. These concepts are the basis for many mathematical models of physiological behavior, and we describe the general nature of such models. Next, we introduce the concept of a "fatal limit" for the displacement of a physiological system, and show how measures of such limits can be included in mathematical models. We show how the numerical values of such limits depend on the values of other system parameters, i.e., recovery times and coupling coefficients, and suggest ways of measuring all these parameters experimentally, for example by monitoring changes induced by X-irradiation. Next, we discuss age-related changes in these parameters, and show how the parameters of mortality statistics, such as the famous Gompertz parameters, can be derived from experimentally measurable changes. Concepts of onset-of-aging, critical or fatal limits, equilibrium value (homeostasis), recovery times and coupling constants are involved. Illustrations are given using published data from mouse and rat populations. We believe that this method of deriving survival patterns from model that is experimentally testable is unique.

Aging↗

Quantitative analysis of cytosolic free calcium oscillations in neutrophils by mathematical modelling.

Mathematical models are often used to elucidate mechanisms behind cytosolic Ca2+ oscillations. We have evaluated the use of mathematical modelling to analyse and quantify Ca2+ signal patterns, in single, adherent human neutrophils (PMN) after stimulation by the bacterial peptide N-formyl-methionyl-leucyl-phenylalanine (fMLP). The cells were loaded with Fura-2 and fluctuations in cytosolic Ca2+ recorded with a video based digital imaging system. A new indirect intracellular calibration method was introduced to avoid the uncertainty in obtaining an equilibrium between the extracellular and intracellular calcium concentrations. Two different approaches to mathematical modelling were used. First, we applied a sensitivity analysis with a two-pool model by assuming an optimal situation using reliable a priori estimates of all structural parameters (e.g. Hill coefficients and dissociation constants). We found that the a priori estimates of the other 5 more variable parameters must lie within the range of 25-400% of the postulated true parameter values to be reliable in a parameter estimation method. Small changes (less than 5%) in those variable parameter values induced very different types of signal patterns which may have some relevance in evaluating a possible functional significance to the oscillatory signals. Second, we employed a one-pool, non oscillatory model integrated with a power spectrum method as a tool to quantify the dose dependency between fMLP (1-1000 nM) and parameters describing the biphasic process of calcium signalling and parameters describing only the oscillatory components. We conclude that the frequency of the observed oscillations assembled around one characteristic frequency independent of fMLP concentration, and sinusoidal oscillations were observed most frequently in PMN stimulated to a moderate peak [Ca2+]i level.

Biological Assay↗

Application of a mathematical model to describe the behaviour of the Lactobacillus spp. during the ripening of a Spanish dry fermented sausage (Chorizo).

The evolution of Lactobacillus spp. during the curing process of dry fermented sausage (Chorizo), has been studied under natural climatic conditions and in a controlled drying chamber, with regulated temperature and relative humidity. In order to fully understand the development of the microorganisms in each of these two cases, it applied a mathematical model based on a modified Gompertz equation. The proposed mathematical function is easy to use and statistically appropriate. Furthermore, it allows the distinction to be made between the four phases which characterise the behaviour of these microorganisms during the curing of the sausage (a) latency from an initial threshold level; (b) exponential growth; (c) stationary state; (d) depletion to a residual level. The mathematical analysis of this function has highlighted certain differences in the behaviour of the microbial flora depending on the technological conditions to which the drying of the sausages is subjected. Under the climatically controlled conditions of the drying process, a better development of the lactobacillus spp. is observed, but conversely the final stage of the exponential growth is brought forward, the length of the stationary phase is shortened and is reached before the end of the drying period, at which point the marginal decline of the microorganisms becomes ever more reduced.

Fermentation↗