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Development of a mathematical model of the human circulatory system.

A mathematical lumped parameter model of the human circulatory system (HCS) has been developed to complement in vitro testing of ventricular assist devices. Components included in this model represent the major parts of the systemic HCS loop, with all component parameters based on physiological data available in the literature. Two model configurations are presented in this paper, the first featuring elements with purely linear constitutive relations, and the second featuring nonlinear constitutive relations for the larger vessels. Three different aortic compliance functions are presented, and a pressure-dependent venous flow resistance is used to simulate venous collapse. The mathematical model produces reasonable systemic pressure and flow behaviour, and graphs of this data are included.

Cardiovascular Physiological Phenomena↗

A mathematical model of integrin-mediated haptotactic cell migration.

Haptotactic cell migration, a directed response to gradients of cell-extracellular matrix adhesion, is an important process in a number of biological phenomena such as wound healing and tumour cell invasion. Previously, mathematical models of haptotaxis have been developed on the premise that cells migrate in response to gradients in the density of the extracellular matrix. In this paper, we develop a novel mathematical model of haptotaxis which includes the adhesion receptors known as integrins and a description of their functional activation, local recruitment and protrusion as part of lamellipodia. Through the inclusion of integrins, the modelled cell matter is able to respond to a true gradient of cell-matrix adhesion, represented by functionally active integrins. We also show that previous matrix-mediated models are in fact a subset of the novel integrin-mediated models, characterised by specific choices of diffusion and haptotaxis coefficients in their model equations. Numerical solutions suggest the existence of travelling waves of cell migration that are confirmed via a phase plane analysis of a simplified model.

Algorithms↗

A mathematical framework for modeling axon guidance.

In this paper, a simulation tool for modeling axon guidance is presented. A mathematical framework in which a wide range of models can been implemented has been developed together with efficient numerical algorithms. In our framework, models can be defined that consist of concentration fields of guidance molecules in combination with finite-dimensional state vectors. These vectors can characterize migrating growth cones, target neurons that release guidance molecules, or other cells that act as sources of membrane-bound or diffusible guidance molecules. The underlying mathematical framework is presented as well as the numerical methods to solve them. The potential applications of our simulation tool are illustrated with a number of examples, including a model of topographic mapping.

Algorithms↗

On the use of mathematical models of malaria transmission.

The key conclusions of several mathematical models of malaria are reviewed with emphasis on their relevance for control. The Ross-Macdonald model of malaria transmission has had major influence on malaria control. One of its main conclusions is that endemicity of malaria is most sensitive to changes in mosquito imago survival rate. Thus malaria can be controlled more efficiently with imagicides than with larvicides. An extension of this model shows that the amount of variability in transmission parameters strongly affects the outcome of control measures and that predictions of the outcome can be misleading. Models that describe the immune response and simulate vaccination programs suggest that one of the most important determinants of the outcome of a vaccine campaign is the duration of vaccine efficacy. Apparently malaria can be controlled only if the duration of efficacy is in the order of a human life-span. The models further predict that asexual stage vaccines are more efficient than transmission-blocking vaccines. Directions for further applications of mathematical models are discussed.

Animals↗

An application of mathematical programming concepts to behavioural research design.

More and more frequently, human factors specialists are being asked to design behavioural research and evaluation techniques that will be applied many times to many different systems, and not always by behavioural scientists. One way to meet the repeatability requirement is to base evaluation technique design on the concepts of mathematical optimisation (eg, linear programming). This paper presents a general model for the application of mathematical programming concepts to behavioural research design, and an example of the use of this approach to design a simulator certification programme for the Strategic Air Command (SAC).

Journal Article↗

Mlab--a mathematical modeling tool.

An interactive interpreter called Mlab is described. One uses Mlab by typing commands. In this sense, Mlab is a programming language. It has various mathematical and graphical facilities which make it a useful tool for mathematical modeling. The curve fitting capabilities of Mlab are augmented with differential-equation-handling and matrix-manipulation capabilities which provide a powerful and civilized facility for curve fitting. Many people are engaged in this activity, and, in general, they use programs which are neither sufficiently general nor easy to use. (Some conventional programming is usually required, for example.) Mlab purports to be easier than alternate approaches. The nature of Mlab is discussed with accompanying examples. The main example is the use of curve fitting to determine molecular weight from ultracentrifuge data. This example was chosen because it exhibits a special feature of Mlab, namely the root operator, which appears in the definition of the model function.

Computers↗

A computer program for mathematical treatment of data in radioimmunoassay.

A mathematical analysis of counting data obtained in hormone plasmatic radioimmunoassay is presented. A log-normal Galton distribution of the dose-effect type is assumed for the fitting of the experimental data. The special adopted procedure makes it possible to reproduce the total range of the sigmoid curve and not only the rectilinear part of it. Experimental data with iterations and the proper weights of the iterated counting rates are automatically taken into account and the statistical errors of the standard curve and of the sample's dose evaluated from it are given by the code. A large number of analyses have been performed in order to test the affidability of the method and to explain the validity of the chemical-physical parameters of the calculated distribution. Some selected results are presented and a full description of the mathematical formalism is given.

Animals↗

A mathematical simulation of the AIDS patient and extracorporeal detoxification.

A simple numerical simulation of AIDS patient detoxification by a hypothetical extracorporeal device for the removal of viruses, infected white cells, and syncytia has been designed. The mathematical model accounts for healthy blood white cells attacking and destroying the viruses, while at the same time the viruses attack and infect certain white cells. The infected white cells serve as a site for viral growth; eventually the cells lyse, releasing a large number of viruses into the blood stream. The healthy white cells and infected white cells combine to form syncytia, where the virus multiplies, and finally the syncytium ruptures releasing all the virus. This model can be used to predict concentrations over a specified period for the patient. This is a mathematical model to be used as a research and design tool only.

AIDS-Related Complex↗

Empirical and mathematical models on the relationship between patient age and nosocomial infection.

This paper proposes two models, one a purely empirical one and the other a mathematical one, which depict the relationship between patient age and nosocomial infection rate. The empirical model is based on the two age-specific phenomena, the acquisition of resistance to infection with age mainly in the early years of life and the deterioration of existing resistance mechanisms with ageing predominantly in the later years of life. The net effect of these two factors is shown to approximate into a quadratic relationship between age and nosocomial infection rate, like the type demonstrated in earlier experimental studies. The second mathematical model is derived from studies on cancer research and here the relationship between age and nosocomial infection rate for patients in the age group 30-70 years is represented by a log linear model. The model was tested against experimental data derived from large surveys on nosocomial infection and the resulting correlation coefficient was 0.98. The model was an extremely good fit when tested against postoperative wound infection rates as well as nasal carriage rate of antibiotic resistant Staph. aureus. Furthermore, when patients in the survey were subdivided into groups of male patients and female patients and into two groups based on the type of operative wound, the model was still found to be a very good fit to the experimental data. This confirmed the validity of the model even in the presence of other patient-related parameters. Finally, the model was tested against the results of a totally different experimental study conducted elsewhere and the resulting correlation coefficient was 0.999, which confirmed the validity of the model in a universal context.

Adult↗

Building intelligent alarm systems by combining mathematical models and inductive machine learning techniques.

In this article a technique is described to develop knowledge-based alarm systems for ventilator therapy, using mathematical modeling and machine learning. With a mathematical model airway pressure, expiratory gas flow and CO2 concentration at the endotracheal tube are simulated for patients, undergoing volume-controlled ventilation with constant ventilator settings, during normal functioning of the breathing circuit and during breathing circuit mishaps (leaks and obstructions). Simulations were performed for 94 physiologically different 'patients', by varying airway resistance and lung/thorax compliance values in the model. Each simulated breath was described by a set of derived signal features and a label that constituted during which event (normal function or mishap) the breath was recorded. With an inductive machine learning algorithm rules, linking signal feature values to breathing circuit events, were created from data of 54 of the simulated patients. The resulting set of rules was able to classify 99% of events in the data of the remaining 40 patients correctly. Of signals, measured at a ventilated lung simulator, 100% of events were classified correctly.

Airway Resistance↗

Mathematical modelling of flow through an irregular arterial stenosis.

A mathematical model of flow through an irregular arterial stenosis is developed. The model is two-dimensional and axi-symmetric with the stenosis outline obtained from a three-dimensional casting of a mildly stenosed artery. Agreement between modelled and experimental pressure drops (obtained from an axi-symmetric machined stenosis with the same profile) is excellent. Results are also obtained for a smooth stenosis model, similar to that used for most mathematical modelling studies. This model overestimates the pressure drop across the stenosis, as well as the wall shear stress and separation Reynolds number. Also, the smooth model predicts one instead of three recirculation zones present in the irregular model. The original stenosis is modified to increase the severity from 48 and 87% areal occlusion, while maintaining the same general shape. This has the effect of increasing the pressure drop by an order of magnitude and decreasing the number of recirculation zones to one, with a lower separation Reynolds number.

Arterial Occlusive Diseases↗

Experimental and mathematical methods for representing relative surface elongation of the ACL.

The common approach to assess the stabilizing role of the ACL in the knee has been to measure the elongation of a few marked fibers in the ligament. A comparison of the relative elongation (RE) of these marked fibers between different specimens and studies is delicate due to the difficulty of marking the same fibers. More consistent comparisons would be achieved if the RE of the whole ligament surface was presented. Hence, we developed a mathematical method leading to a continuous description of the relative elongation of the ligament's surface based on experimental measurements of the RE of five fibers. The ligament fibers of two knee specimens were marked by radiopaque markers and a Roentgen Stereophotogrammetric Analysis system was used to reconstruct the three-dimensional positions of these artificial landmarks. The mathematical procedure used isoparametric cubic splines to interpolate the contours of the insertion sites. The results showed that the general pattern of the RE for both specimens was similar, characterized by an undulation near full flexion. In fact, close to full flexion all the RE of the fibers increased. Such a representation describes the changes in the RE for a given fiber during knee flexion and at the same time characterizes the RE distribution at a given flexion angle.

Aged↗

A mathematical model of atrioventricular conduction block using the excitability recovery curve of the myocardial cell.

A simple mathematical model of AV conduction block was constructed on the basis of single-cell electrophysiological experiments concerning the rate-dependent property of excitability of the AV nodal cells (the excitability recovery curve, ERC). This ERC was analogous to the phase response curve (PRC) of cardiac pacemaker cells, which the authors had previously used to construct a model of modulated parasystole. Computer simulation was used to reproduce the ERC. The single-cell ERC was then extended to the entire AV node, and this curve was used to formulate a mathematical model of AV conduction block as a nonlinear, first-order difference equation of the successive PR intervals of the ECG. This model predicted a variety of ECG patterns of AV conduction block: normal rhythm, first-degree block, and several second-degree blocks of complex Wenckebach periodicity in relation to the sinus rate and the shape of the ERC. By assuming this model it was possible to identify the underlying ERC of actual ECGs with complex Wenckebach periodicity.

Animals↗

Mathematical analysis of antiserum titre and affinity in rabbits injected with 11 alpha OH-progesterone-hemisuccinate-BSA.

A mathematical procedure is presented here to determine the behaviour of antiserum titre in rabbits, after repeated injections of 11 alpha OH-Progesterone-hemisuccinate-BSA. By means of methods recently applied to the time series, the peaks of maximum response were determined. A common behaviour of rabbits was revealed for the delay times in the response after each booster injection. The titre and affinity of antiserum were determined by means of a special method for mathematical treatment of data in RIA analysis, which gives directly such parameters with a statistical interpretation.

Animals↗

Use of mathematical models for understanding the dynamics of gene amplification.

Recently it has been suggested that high levels of cancer drug resistance and poor prognosis are strongly associated with gene or oncogene amplification (GA). It has been further suggested that the molecular mechanisms underlying GA may be different for different genes, and that different amplification mechanisms may function concurrently or sequentially in the same gene. The aim of this review is to demonstrate the use of mathematical models in studying these intricate dynamics. We have provided mathematical models for the generation of extrachromosomal elements, their autonomous replication and equal or unequal mitotic segregation, the integration of the extrachromosomal elements within the chromosomes, and chromosomal GA in one or many unlinked genes. Using this formal description one can examine the potential role of each GA mechanism in the generation of specific distributions of gene-copy number in a cell population, under various levels of selection stringency. Thus one can specify the conditions for the emergence of drug-resistant mutants prior to selection, as well as the relationships between the stringency of the selecting environment and the characteristics of the resultant cellular phenotype.

Animals↗

Mathematics of predictive food microbiology.

Commonly encountered problems related to modelling bacterial growth in food are analysed from a mathematical point of view. Modelling techniques and terms, some misused, are discussed and an attempt is made to clarify how, and under what conditions, they may be used. A theoretical framework is given to provide a basis in which mathematical models having been used in predictive microbiology can be embedded. By using several simplifying idealizations as a compromise between the complexity of the biological system and the available data, a practically usable model becomes available.

Bacteria↗

PANSYM: a symbolic equation generator for mathematical modelling, analysis and control of metabolic and pharmacokinetic systems.

Software is presented for automatic generation of first-order ordinary differential equations (ODE) that arise from lumped parameter representations of metabolic and pharmacokinetic systems. The definition of system structures is accomplished by fractional transfer rates between state variables, together with input/output equations and initial conditions of state variables. General non-linear mathematical expressions can be assigned to all structure definition items. The software parses and interprets the system definitions and generates symbolically the mathematical expression of the model's set of ODE. In addition, symbolic derivatives of state equations are determined with respect to model parameters, state variables and external inputs. These derivatives represent the constituents of systems of sensitivity-differential and adjoint-differential equations that arise in identification and optimal control problems. Finally, output routines generate source code that, once compiled and linked to simulation programs, allows efficient numerical integration of the system of ODE. This software has been developed in PROLOG on Macintosh computers and has been extensively used with the programming environment MATLAB. Possible applications of this software include model building, sensitivity analysis, identification, optimal experiment design and numerical solution of optimal control problems.

Computer Simulation↗

Mathematical models of insulin secretion in physiological and clinical investigations.

The discovery of the radioimmunoassay for the measurement of insulin concentration stimulated several clever studies which showed, both in vitro and in vivo, the peculiar biphasic pattern of the beta-cell response to glucose stimulation. Physiologists took the challenge to describe with mathematical models those data, introducing tools that provided medical and biological research scientists with further knowledge of the nature of the complex processes involved in insulin secretion. Simulation models were therefore developed to account for the dependence on each other of the different features of the system behaviour to better understand them and to formulate hypotheses for further investigations. The disadvantages of these models (rather complex mathematical structure, unidentifiability, etc.) limited their use to a few applications, mostly as teaching tools. The use of models in the clinical setting required the individualization of the parameter set for a single subject from an experimental test as simple as possible. This led to the development of the minimal model of insulin appearance and kinetics. This model, fully identifiable, thus enables the furnishing of a personalized picture of insulin behaviour, providing insights on hormone secretion during a (frequently sampled) intravenous glucose tolerance test. However, this model analyzed systemic insulin concentration data and gave information only on post-hepatic insulin delivery. Since the liver takes up more than 50% of the released hormone, a further step was necessary to evaluate insulin secretion, i.e. the analysis of the behaviour of C-peptide, which is released equimolarly with insulin, but is not extracted by the liver. The last generation models are in fact descriptors of the systemic C-peptide dynamics, and are used to reconstruct its secretion which is assumed to be molarly equal to that of insulin. Mainly three models of pre-hepatic insulin appearance, based on this principle, have been developed and used in clinical studies.

C-Peptide↗