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At least 1,621 records · Page 90Linked to original sources
PubMed2000

Pharmacokinetic variability and therapeutic drug monitoring actions at steady state.

PURPOSE: To develop a mathematical model for therapeutic drug monitoring and to assess the kinetic relationships between the intensity of corrective action and the approach of drug concentrations to target values. METHODS: A mathematical model that succinctly accounts for the corrective actions and the variability inherent in the pharmacokinetics was used. RESULTS: The validity of the variability term was tested using experimental data for steady state concentrations of the drug procainamide. The approach of the monitored process to the target value followed exponential kinetics and an analytical expression for dependence the variance with time and various dosing parameters was derived. The variance of the drug concentration depends critically on a single non-dimensional parameter containing the rate constant for the therapeutic corrective actions and a coefficient describing the variance rate. When the rate constant for the therapeutic corrective actions was less than this critical value, the variance increased indefinitely. CONCLUSIONS: From a dosing standpoint, large variances in drug concentrations are undesirable because some patients will be overdosed or underdosed. Since deterministic models cannot provide analytical solutions for the moments of drug concentration distribution functions, stochastic models can be used to provide useful insights into the design of therapeutic regimens.

Algorithms↗
PubMed1994

Synapses on axon collaterals of pyramidal cells are spaced at random intervals: a Golgi study in the mouse cerebral cortex.

In this study we investigated the arrangement of synapses on local axon collaterals of Golgi-stained pyramidal neurons in the mouse cerebral cortex. As synaptic markers we considered axonal swellings visible at high magnification under the light microscope. Such axonal swellings coincide with synaptic boutons, as has been demonstrated in a number of combined light and electron microscopic studies. These studies also indicated that, in most cases, one bouton corresponds precisely to one synapse. Golgi-impregnated axonal trees of 20 neocortical pyramidal neurons were drawn with a camera lucida. Axonal swellings were marked on the drawings. Most swellings were 'en passant'; occasionally, they were situated at the tip of short, spine-like processes. On axon collaterals, the average interval between swellings was 4.5 microns. On the axonal main stem, the swellings were always less densely packed than on the collaterals. Statistical analysis of the spatial distribution of the swellings did not reveal any special patterns. Instead, the arrangement of swellings on individual collaterals follows a Poisson distribution. Moreover, the same holds to a large extent for the entire collection of pyramidal cell collaterals. This suggests that a single Poisson process, characterized by only one rate parameter (number of synapses per unit length), describes most of the spatial distribution of synapses along pyramidal cell collaterals. These findings do not speak in favour of a pronounced target specificity of pyramidal neurons at the synaptic level. Instead, our results support a probabilistic model of cortical connectivity.

Animals↗
PubMed2001

Stepwise lineage restriction of progenitors in lympho-myelopoiesis.

It has long been controversial whether hematopoiesis progresses through ordered stages of determination as in embryonic development. This is due to the absence of a methodology capable of exactly determining the developmental potential of hematopoietic stem/progenitor cells. The multilineage progenitor (MLP) assay enabled us to discriminate among seven types of hematopoietic progenitors, which are multipotent progenitor p-MTB (capable of generating myeloid, T and B cells), bipotent progenitors p-MT, p-MB and p-TB, and unipotent progenitors p-M, p-T and p-B. Among these seven types, the p-TB type progenitor was found to be absent. These findings indicate that the process of lineage commitment proceeds through an ordered but not random process. By extending the area of investigation to include the erythroid lineage, more convincing evidence for the ordered process was obtained. Detailed and exact illustration of the process of hematopoiesis will provide an opportunity to revive hematopoiesis as one of the most fascinating targets of research in developmental biology.

Animals↗
PubMed2005

Automated microscope system for determining factors that predict neuronal fate.

Unraveling cause-and-effect relationships in the nervous system is challenging because some biological processes begin stochastically, take a significant amount of time to unfold, and affect small neuronal subpopulations that can be difficult to isolate and measure. Single-cell approaches are slow, subject to user bias, and sometimes too laborious to achieve sample sizes large enough to detect important effects. Here, we describe an automated imaging and analysis system that enables us to follow the fates of individual cells and intracellular proteins over time. Observations can be quantified in a high-throughput manner with minimal user bias. We have adapted survival analysis methods to determine whether and how factors measured during longitudinal analysis predict a particular biological outcome. The ability to monitor complex processes at single-cell resolution quickly, quantitatively, and over long intervals should have wide applications for biology.

Animals↗
PubMed1976

On the absorption probabilities and absorption times of finite homogeneous birth-death processes.

This paper provides some formulas for the absorption probabilities, the mean absorption times and the variances of first absorption times in finite homogeneous absorbing birth-death processes. The results are then applied to a genetic model of Moran [1958] for computing the absorption probability densities, the mean absorption times and the variances of first absorption times. Specifically, it is shown that the probability distribution of the first absorption time is the matrix analog of exponential distribution or a mixture of exponential distributions if the transition matrix is diagonable.

Alleles↗
PubMed2001

Mutated mtDNA distribution in exponentially growing cell cultures and how the segregation rate is increased by the mitochondrial compartments.

A cell contains many copies of mitochondrial DNA. The distribution of a mitochondrial gene mutation in a cell culture is governed by the way in which the mtDNA molecules of a cell are replicated and partitioned between the two daughter cells during mitosis. Assuming that this partition process is random, we describe the evolution of the mitochondrial genetic state of a cell culture. The mutated mtDNA is ultimately segregated and the rate of the trend to segregation is relatively slow. It is nevertheless greatly accelerated if the model takes into account the spatial mtDNA partition by the mitochondrial compartments.

Cell Division↗
PubMedDate not supplied

[The network mechanisms of physiological regulation].

A review of connectionist or network approach to describe and understand regulatory processes in organism is presented. Network models of neural, genetic, immune and endocrine regulation are considered and a conception of organism as an integrative network system is introduced. A new approach to the problem of organism state control, called associative control, is proposed and its possible medical applications, in particular, in psychotherapy, psychoanalysis and alternative medicines are discussed.

Animals↗
PubMed2001

SCOPE: a probabilistic model for scoring tandem mass spectra against a peptide database.

Proteomics, or the direct analysis of the expressed protein components of a cell, is critical to our understanding of cellular biological processes in normal and diseased tissue. A key requirement for its success is the ability to identify proteins in complex mixtures. Recent technological advances in tandem mass spectrometry has made it the method of choice for high-throughput identification of proteins. Unfortunately, the software for unambiguously identifying peptide sequences has not kept pace with the recent hardware improvements in mass spectrometry instruments. Critical for reliable high-throughput protein identification, scoring functions evaluate the quality of a match between experimental spectra and a database peptide. Current scoring function technology relies heavily on ad-hoc parameterization and manual curation by experienced mass spectrometrists. In this work, we propose a two-stage stochastic model for the observed MS/MS spectrum, given a peptide. Our model explicitly incorporates fragment ion probabilities, noisy spectra, and instrument measurement error. We describe how to compute this probability based score efficiently, using a dynamic programming technique. A prototype implementation demonstrates the effectiveness of the model.

Amino Acid Sequence↗
PubMed2006

T-cell motility in the early stages of the immune response modeled as a random walk amongst targets.

The transport process by which a T cell makes high-frequency encounters with antigen-presenting cells following infection is an important element of adaptive immunity. Recent experimental work has allowed in vivo cell motility to be characterized in detail. On the basis of experimental data we develop a quantitative model for encounters between T cells and antigen-presenting cells. We model this as a transport-limited chemical reaction with the dynamics dependent on physical contact between randomly moving reactants. We use asymptotic methods to calculate a time distribution which characterizes the delay before a T cell is activated and use Monte Carlo simulations to verify the analysis. We find that the density of antigen-primed dendritic cells within the lymph node paracortex must be greater than 35 cells/mm3 for a T cell to have a more than 50% chance of encountering a dendritic cell within 24 h. This density is much larger than existing estimates based on calculations which neglect the transport process. We also use simulations to compare a T cell which re-orients isotropically with a T cell which turns according to an experimentally observed distribution and find that the effects of anisotropy on the solution are small.

Animals↗
PubMedDate not supplied

Tristate markov model for the firing statistics of rapidly-adapting mechanoreceptive fibers.

Rapidly-adapting (RA) mechanoreceptive fibers, which are associated with Meissner corpuscles, mediate one component of the neural information that contributes to the sense of touch. Responses of cat RA fibers subject to 40-Hz sinusoidal stimulation were modeled as a Markov process. Since an RA fiber generates one, two or no spikes in each cycle of the stimulus, the fiber's activity was considered to exist in one of these three possible states. By analyzing empirically generated spike trains, the probability of each state and the probabilities of transitions between the three states were found as a function of the average firing rate of the fiber. The average firing rate depends on the stimulus amplitude. In addition, the phase of each spike with respect to the stimulus cycle was represented by a Laplace distribution. Based on empirical data, the mean and the standard deviation of this distribution decrease as the stimulus amplitude is increased. The entire stochastic model was implemented on a computer to simulate the responses of RA fibers. The post-stimulus time, inter-spike interval and period histograms generated from the simulations match the histograms obtained from the empirical data well as quantified by relative errors. This temporal model can be combined with a population model for average rate to derive a spatio-temporal description of the responses of somatosensory afferents. The effects of changing the stimulation frequency are discussed.

Action Potentials↗
PubMed1989

Evolution of plant mitochondrial genomes via substoichiometric intermediates.

Comparison of the modern fertile maize mitochondrial genome (N) with an ancestral maize mitochondrial genome (RU) reveals a 12 kb duplication (containing the atpA gene) in the modern genome that is absent from the ancestor. Cloning, mapping, and sequencing of the relevant portions of the ancestral genome shows that this duplication probably arose via a three-stage recombination process involving substoichiometric intermediates. Comparison with analogous observations on yeast mitochondrial genomes suggests that this three-stage model of genome reorganization can be generally applied to plant mitochondrial genomes to explain both deletions and the creation of novel repeats, common features of plant mitochondrial genome evolution.

Base Sequence↗
PubMed1988

Internal motions in proteins and gating kinetics of ionic channels.

Single-channel current recordings have revealed a complex kinetic behavior of ionic channels. Many channels exhibit closed-time distributions in which long waiting times occur with a much higher frequency than predicted by a simple exponential decay function. In this paper a model for opening-closing transitions that accounts for internal motions in the protein matrix is discussed. The model is based on the notion that the transition between a conductive and a nonconductive state of the channel represents a local process in the protein, such as the movement of a small segment of a peptide chain or the rotation of a single amino-acid residue. When the blocking group moves into the ion pathway, a structural defect is created consisting in a region of loose packing and/or poor hydrogen bonding. By rearrangements of neighboring groups, the defect may migrate within the protein matrix, carrying out a kind of random walk. Once the defect has moved away from the site where it was formed, a transition back to the open state of the channel is possible only when the defect has returned by chance to the original position. The kinetic properties of this model are analyzed by stochastic simulation of defect diffusion in a small domain of the protein. With a suitable choice of domain size and diffusion rate, the model is found to predict closed-time distributions that agree with experimental observations.

Animals↗
PubMed2002

Statistical process control for large scale microarray experiments.

MOTIVATION: Maintaining and controlling data quality is a key problem in large scale microarray studies. In particular systematic changes in experimental conditions across multiple chips can seriously affect quality and even lead to false biological conclusions. Traditionally the influence of these effects can be minimized only by expensive repeated measurements, because a detailed understanding of all process relevant parameters seems impossible. RESULTS: We introduce a novel method for microarray process control that estimates quality based solely on the distribution of the actual measurements without requiring repeated experiments. A robust version of principle component analysis detects single outlier microarrays and thereby enables the use of techniques from multivariate statistical process control. In particular, the T(2) control chart reliably tracks undesired changes in process relevant parameters. This can be used to improve the microarray process itself, limits necessary repetitions to only affected samples and therefore maintains quality in a cost effective way. We prove the power of the approach on 3 large sets of DNA methylation microarray data.

Algorithms↗
PubMed1987

Prediction of thresholds and latency on the basis of experimentally determined impulse responses.

As was shown before (Roufs and Blommaert 1981), temporal impulse responses and step responses can be obtained psychophysically using a drift-correcting perturbation technique. In this paper, experimentally determined impulse responses are given for eight subjects using different experimental conditions, i.e. a 1 deg stimulus field at background luminances of 1200 Td and 100 Td, and a point source superimposed on an extended background of the same luminances, which is a possibility to separate transient and sustained processing. For a large class of stimuli, predictions of threshold curves and latency of different time functions are calculated on the basis of these measured impulse responses. Predictions are tested against experimental data. It will be shown that a simple model, only consisting of a linear filter followed by a noisy peak detector, suffices for a fair quantitative description of the available data.

Humans↗
PubMed2005

Random activation energy model and disordered kinetics, from static to dynamic disorder.

We suggest a unified path integral approach for random rate processes with random energy barriers, which includes systems with static and dynamic disorder as particular cases. We assume that the random component of the activation energy barrier can be described by a generalized Zubarev-McLennan nonequilibrum statistical ensemble that can be derived from the maximum information entropy approach by assuming that the time history of the fluctuations of the random components of the energy barrier are known. We show that the average survival function, which is an experimental observable in disorderd kinetics, can be computed exactly in terms of the characteristic functional of this generalized Zubarev-McLennan nonequilibrium statistical ensemble. We investigate different types of disorder described by our approach, ranging from static disorder with infinite memory to random processes with long or short memory, and finally to rapidly fluctuating independent random processes with no memory. We derive expressions of the average survival function for all these types of disorder and discuss their implications in the evaluation of kinetic parameters from experimental data. We illustrate our approach by studying a simple model of dynamic disorder of the renewal type. Finally we discuss briefly the implications of our approach in molecular biology and genetics.

Entropy↗
PubMed2006

B cell ligand discrimination through a spreading and contraction response.

B cells recognize foreign antigens by virtue of cell surface immunoglobulin receptors and are most effectively activated by membrane-bound ligands. Here, we show that in the early stages of this process, B cells exhibit a two-phase response in which they first spread over the antigen-bearing membrane and then contract, thereby collecting bound antigen into a central aggregate. The extent of this response, which is both signaling- and actin-dependent, determines the quantity of antigen accumulated and hence the degree of B cell activation. Brownian dynamic simulations reproduce essential features of the antigen collection process and suggest a possible basis for affinity discrimination. We propose that dynamic spreading is an important step of the immune response.

Actins↗
PubMed1997

A mathematical model for intracellular effects of toxins on DNA adduction and repair.

The process by which certain classes of toxins compounds or their metabolites may react with DNA to alter the genetic information contained in subsequent generations of cells or organisms are a major component of hazard associated with exposure to chemicals in the environment. Many classes of chemicals may form DNA adducts and there may or may not be a defined mechanism to remove a particular adduct from DNA independent of replication. Many compounds and metabolites that bind DNA also readily bind existing proteins; some classes of toxins and DNA adducts have the capacity to inactivate a repair enzyme and divert the repair process competitively. This paper formulates an intracellular dynamic model for one aspect of the action of toxins that form DNA adducts, recognizing a capacity for removal of those adducts by a repair enzyme combined with reaction of the toxin and/or the DNA adduct to inactivate the repair enzyme. This paper model illustrates the possible saturation of repair enzyme capacity by the toxin dosage and shows that bistable behavior can occur, with the potential to induce abrupt shifts away from steady state equilibria. The model suggests that bistable behavior, dose and variation between individuals or tissues may combine under certain conditions to amplify the biological effect of dose observed as DNA adduction and its consequences as mutation. A model recognizing stochastic phenomena also indicates that variation in within-cell toxin concentration may promote jumps between stable equilibria.

DNA Adducts↗
PubMed1992

Computational behavior dynamics: an alternative description of Nevin (1969).

A computational processing behavior-dynamic model was instantiated in the form of a computer program that "behaved" on the task developed by Nevin (1969). In this classic discrete-trials experiment, the relative frequency of choosing a response alternative matched the relative frequency of reinforcement for that alternative, the local structure of responding was opposite that predicted by momentary maximizing (i.e., the probability of a changeover decreased with run length), and absolute and relative response rates varied independently. The behavior-dynamic model developed here qualitatively reproduced these three results (but not in quantitative and specific detail) and also generated some interesting, as-yet-untested predictions about performance in Nevin's task. The model was discussed as an example of a stochastic behavior-dynamic alternative to algebraic behavior theory.

Animals↗