Stochastic and deterministic models for the kinetic behavior of certain structured enzyme systems II: consecutive two enzyme systems.
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Compartmental models of infectious diseases readily represent known biological and epidemiological processes, are easily understood in flow-chart form by administrators, are simple to adjust to new information, and lend themselves to routine statistical analysis such as parameter estimation and model fitting. Technical results are immediately interpretable in epidemiological and public health terms. Deterministic models are easily stochasticized where this is important for practical purposes. With HIV/AIDS, serial data on both HIV prevalence and AIDS morbidity have been available from San Francisco. Assuming the distribution of the incubation period to be biologically stable, statistical analysis is quite feasible in other regions, even those with no reliable HIV data. Transmission rates must be estimated locally. It is also often possible to estimate the effective size of a population subgroup at risk, from population data on AIDS morbidity only. Computer simulation provides estimates of the evolving pattern of both HIV prevalence and AIDS morbidity. Some public health questions can be answered only by appropriately formulated stochastic models.
There exists a fundamental overall property of the brain which monitors, modulates, and ensures a smoothness of function and which further determines elegance and grace in functioning. This property also imparts a quality of, or a sense of proportion among all other faculties of the brain. It is postulated in this paper that such a property/function, up to now almost taken for granted, is maintained/exercised by a nonlinear deterministic chaotic mode of brain function. If this is the case, borderline psychopathological phenomena, when they flare up, can be explained as resulting from sudden reduction of such a deterministic chaotic mode and the emergence of a pathological order, as the system becomes an oscillating one.
Computer simulations of the supercoiling of DNA, largely limited to stochastic search techniques, can offer important information to complement analytical models and experimental data. Through association of an energy function, minimum-energy supercoiled conformations, fluctuations about these states, and interconversions among forms may be sought. In theory, the observation of such large-scale conformational changes is possible, but modeling and numerical considerations limit the picture obtained in practice. A new computational approach is reported that combines an idealized elastic energy model, a compact B-spline representation of circular duplex DNA, and deterministic minimization and molecular dynamics algorithms. A trefoil knotting result, made possible by a large time-step dynamics scheme, is described. The simulated strand passage supports and details a supercoiled-directed knotting mechanism. This process may be associated with collective bending and twisting motions involved in supercoiling propagation and interwound branching. The results also demonstrate the potential effectiveness of the Langevin/implicit-Euler dynamics scheme for studying biomolecular folding and reactions over biologically interesting time scales.
The relationship between classical demographic deterministic forecasting models, stochastic structural econometric models and time series models is discussed. Final equation autoregressive moving average (ARMA) models for Australian total live-births are constructed. Particular attention is given to the problem of transforming the time series to stationarity (and Gaussianity) and the properties of the forecasts are analyzed. Final form transfer function models linking births to females in the reproductive age groups are also constructed and a comparison of actual forecast performance using the various models is made. Long-run future forecasts are generated and compared with available projections based on the deterministic cohort model after which some policy implications of the analysis are considered.
The authors review a deterministic model proposed for the analysis of two-way contingency tables that arise in counts of pairwise interactions. This model decomposes the table into the sum of two matrices with special forms: in one the contacts are distributed selectively, in the other they are distributed at random. We show that this model has several inherent problems. The decomposition is not unique, which compromises estimation and interpretation of the parameters; the deterministic framework provides no basis for estimation or hypothesis testing; and the assumption of decomposibility is supported by neither empirical evidence nor theoretical considerations. We show that generalized linear models provide a suitable alternative once the probability process is specified and the overparameterization is removed.
The technique of dimension estimation is currently a leading application of nonlinear dynamics (popularly termed "chaos theory") to EEG analysis. A tutorial review of this technique is presented along with some elementary background concepts from nonlinear dynamics. Practical aspects of applying dimension estimation to EEG data are also reviewed, and the possible role of deterministic chaos in brain function is discussed.
Certain macromolecules embedded in the cell membranes of a variety of cells behave as gated ion-selective pores or channels. The length of time that a channel remains open or closed is not deterministic in nature and must be described in terms of relative probabilities. If channels act independently of each other and appropriate experimental conditions can be maintained, the behavior of a channel can be described by a homogeneous Markov process. Using this representation, the relative probability of observing openings (or closings) of various durations can be described by a sum of discrete components which are related to the underlying model of the kinetic behavior of the channel. Generally, these discrete components are taken to be simple decaying exponentials; however, exponentially decaying oscillatory components (as well as certain others which are discussed) are consistent with the Markov process representation. The presence of components other than simple decaying exponentials is shown to imply the violation of detailed balance in the steady-state (which requires energy), and thus, the presence of cyclic pathways in models which accurately represent the kinetic behavior of the channel. Oscillatory components, if present, will in general decay at a faster rate than the slowest decaying component, which, except under a very restricted set of conditions, will be a simple exponential.
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The Clare Bishop Area (CBA) is a retinotopically organized cortical area in the cat brain connected to a great variety of visual areas in a very complex way (Fig. 1). Experimental analysis is difficult because of the following aspects: 1. As the distance from the retina increases, the signal combinations necessary to analyse the system become more and more specific. 2. Feedback loops cannot be opened, so an unequivocal identification of CBA cell properties is impossible. 3. The nonlinear character seems to have a great influence on signal processing. To circumvent these problems, specific signal combinations leading to a separation of input subsystems have been developed (Hoffmann and v. Seelen, 1979). On grounds of practical experience and theoretic considerations, the signal combinations are usually restricted to combinations of deterministic and stochastic signals when analysing the CBA. The different methods of measurement are applied successively, the linearizing ones being used first so that a rough classification is possible. If the nonlinear features of the system have little efect, they can be linearized in the theoretical description, if not, a model consisting of a sequence of a linear dynamic system and a nonlinear one with a static, polynomial feature must be used for analysis by parameter estimation. The experimental part of this publication deals with the determination of a number of cell properties. Some hypotheses on the function of the CBA are tested. THe results lead to the conclusion that further experiments, such as are discussed below, are necessary in the input subsystems, area 18 and 19. The experimental results of some other authors (Hubel and Wiesel, 1969; Turlejski, 1975; Turlejski and Michalski, 1975; Smith and Bauman, 1979; SPera and Bauman, 1979) are confirmed by the implicaions of the present results.
An optimal input of nutrients into the metabolic process of the individual subject so as to effect desired therapeutic results is particularly important for the critically ill. A patient-related, individualized nutrients optimization procedure is proposed here. The procedure is applicable to any time-invariant and deterministic metabolic model that is bound by one or more quantitative limiting criteria. As a case in hand, the procedure is used to optimize the individual metabolic needs of critically ill patients. The results indicate that, given a proper metabolic model, the patient may be treated on an individual appropriateness basis rather than on the traditional statistical intuitive approach.
Different forms of artificial intelligence have been applied to pattern recognition in medicine. Recently, however, a relatively new technique involving software-based neural networks has become more readily available. Deterministic logic is currently applied to rhythm analysis in computer-assisted ECG interpretation methods developed in the University of Glasgow. The aim of the present study is to compare an artificial neural network with deterministic logic for separating sinus rhythm (SR) with supraventricular extrasystoles (SVEs) and/or ventricular extra-systoles (VEs) from atrial fibrillation (AF) at a particular point in the diagnostic logic of the Glasgow Program. A total of 2363 ECGs with 1495 AF and 868 SR + (SVEs and/or VEs) are used for training and testing a variety of neural networks, and the optimum design is selected. Methods for combining the results of the neural-network classification and the deterministic interpretation are also developed. A further 717 ECGs are used to test the selected network. The results show that the use of an artificial neural network can improve the sensitivity of reporting AF from 88.5% using the deterministic approach to 92%, without sacrificing specificity (92.3%).
Fibrillation is more likely to occur in animals showing a high degree of cellular differentiation. Lower species, with cardiac tissue histologically and electrophysiologically more uniform, very rarely, if ever, can fall into this uncoordinated activity. We describe experiments during which two specimens of the South American toad, Bufo paracnemis (body weights, 363 g and 297 g; ventricular weights, 1.8 g and 1.4 g, respectively), were repeatedly fibrillated and defibrillated almost at will. However, we failed when we tried a series of experiments in a given number of animals. Over a total of 16 fibrillation-defibrillation episodes, a fibrillation threshold of about 3.8 mA/g was estimated. The lowest defibrillation values were, respectively, 43 mA/g and 507 mA/g, using rectangular pulses (less than 7 msec pulses width). There were also a few spontaneous reversals before and after defibrillation shocks. These cases point to our still poor understanding of the mechanisms involved in the process. It is suggested that reentry or multiple ectopic foci might not be the basic mechanisms, as traditionally accepted. Rather, it might well be a new behavior of the cells or group of cells like that predicted by the theory of deterministic chaos.
For the cholera epidemic that occurred in the European Mediterranean region in the summer of 1973, a simple deterministic mathematic model is proposed; it consists of a system of two ordinary differential equations which concern the evolution of the human infective population in a town community and of bacteria population in the sea. It is conjectured that the infection process obeys a non linear saturation-type law. A phase space analysis is performed for the system of equations. Conclusions are drawn which concern the evolution of the epidemic and which suggest some indications for the selection of public health policies. The validity of the model is compared with the available data for the town of Bari (Italy).
Non-linear time sequence analysis has been performed on infant sleep measurement data in order to obtain more information about the respiratory processes. As a first step, respiration data during REM sleep were analysed with methods from non-linear dynamics, especially, the correlation integral and the slope of its log-log plot, representing the correlation dimension. Before calculation of the correlation integral, a special kind of filtering has to be applied to the data. This filtering algorithm is a state space and singular value decomposition-based noise reduction method, and it is used to separate the noise and signal subspaces. The dynamics of a signal (in our case data from the respiratory process) and its degrees of freedom can be characterised by the correlation integral and by the correlation dimension, respectively. The main result of this study is that the highly irregular-looking breathing patterns during REM sleep could be described by a deterministic system, and finally the physiological significance of this finding is discussed.
Wright's model for the effects of random fluctuations in gene frequency in a population of fixed size is generalized to randomly fluctuating population size, and treated from the viewpoint of G. Malécot, using a martingale convergence theorem. The gene frequency approaches a limit, whose value depends on the actual realization, or history, of the process; that is, convergence is with probability one (or: almost surely) in statistical language. The limit does not necessarily represent a state of fixation of either allele; in particular, the limiting probability distribution is not necessarily trivial. For the special case of deterministically varying population size, a necessary and sufficient condition for such non-triviality is given.
Cell lengths have been determined at which cycle events occur in the slow-growing Escherichia coli B/r substrains A, K, and F26. The radioautographic and electron microscope analyses allowed determination of the variations in length at birth, initiation and termination of DNA replication, and initiation of the constriction process and of cell separation. In all three substrains the standard deviation increased between cell birth and initiation of DNA replication. From there on, the standard deviation remained relatively constant until cell separation. These observations are consistent with the presence of a deterministic phase during the cell cycle in which the cell sizes at initation of DNA replication and at cell division are correlated.
It is known that a single very large dose of cytotoxic agent administered at once does not result in the same biological consequences as those exerted in the cases where the same dose of the same treatment is distributed with uniformity along a wide interval of time. Moreover its is also clear that at least in some cases, at least with some forms of therapy, at least for some ephemeral time, a beneficial effect may be achieved actually, to some extent at least. In order to achieve reliable indications concerning the optimal time distribution of the antineoplastic treatment however a mathematical model is needed where a realistic balance is drawn for the benefits and harmful outcomes of any form of cancer management. For this purpose a formal representation is introduced in the present paper, that provides a summary description of all processes taking place within the "system" consisting of a population of neoplastic cells and of its natural host under any form of cytotoxic treatment applied with any time-dependent intensity phi (t). The behaviour of the system is depicted in a deterministic way by four linear ordinary differential equations containing ten scalar parameters of 1: demographic, 2: cytokinetic, 3: toxicologic, and 4: clinical meaning.