Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Stochastic Processes”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,585 records · Page 88Linked to original sources

Medical aspects of the hazardous waste problem.

Although no one knows exactly how much toxic material continues to be released into our environment, most observers believe the amount is substantial. In the last few years, in the state of Massachusetts alone, 22 communities have had their municipal water supplies seriously compromised by chemical contamination, (1) causing alarm and dismay among water users. Nation-wide, public concern has reached the point that in some opinion polls, hazardous waste ranks second only behind inflation as a cause of serious worry. Despite widespread anxiety, shared by public health officials, few studies have shown conclusive evidence of health consequences from toxic materials in the environment. Even in the case of such gross contamination as in the Love Canal area of Niagara Falls, New York, health effects have been difficult to establish. (2) This is partly due to intrusion of the adversary process in cases where liability is involved; it is also a result, however, of inherent technical problems that plague any determination of health hazard. This paper reviews some of these problems, considers some current risk assessment approaches, and touches on medicolegal and regulatory aspects of the hazardous waste problem.

Environmental Exposure↗

A maximum-likelihood estimator for trial-to-trial variations in noisy MEG/EEG data sets.

The standard procedure to determine the brain response from a multitrial evoked magnetoencephalography (MEG) or electroencephalography (EEG) data set is to average the individual trials of these data, time locked to the stimulus onset. When the brain responses vary from trial-to-trial this approach is false. In this paper, a maximum-likelihood estimator is derived for the case that the recorded data contain amplitude variations. The estimator accounts for spatially and temporally correlated background noise that is superimposed on the brain response. The model is applied to a series of 17 MEG data sets of normal subjects, obtained during median nerve stimulation. It appears that the amplitude of late component (30-120 ms) shows a systematic negative trend indicating a weakening response during stimulation time. For the early components (20-35 ms) no such a systematic effect was found. The model is furthermore applied on a MEG data set consisting of epileptic spikes of constant spatial distribution but varying polarity. For these data, the advantage of applying the model is that positive and negative spikes can be processed with a single model, thereby reducing the number of degrees of freedom and increasing the signal-to-noise ratio.

Algorithms↗

Origin and biology of cancer metastasis.

Metastasis, the spread of cells from a primary neoplasm to distant sites where they grow, contributes to the death of most cancer patients. The process of metastasis is not random. Rather, the process consists of a series of linked, sequential steps that must be completed by tumor cells if a metastasis is to develop. Thus, metastatic cells must succeed in invasion and embolization, survive in the circulation, arrest in a distant capillary bed, and extravasate into and multiply in organ parenchyma. Although some of the steps in this process contain stochastic elements, as a whole metastasis favors the survival and growth of a few subpopulations of cells that preexist within the parent neoplasm. Moreover, metastases can have a clonal origin, and different metastases can originate from the proliferation of single cells. The outcome of metastasis depends on the interaction of metastatic cells with different organ environments. Organ-specific metastases have been demonstrated in a variety of experimental tumor systems, and even within one organ, site-specific tumor growth can be found. The conclusion that metastasis is a highly selective process that is influenced by both the intrinsic properties of tumor cells and by host factors is optimistic. A selective process is regulated and therefore can be studied and then manipulated.

Humans↗

Differential neural response to positive and negative feedback in planning and guessing tasks.

The neural mechanisms by which emotional and cognitive processing interact are unknown. Evidence from animal studies and neurological patients suggests that regions of the ventral striatum and orbitofrontal cortex, together with limbic structures such as the amygdala, are critical to such interactions. We used positron emission tomography to study the neural systems engaged by processing performance feedback under two conditions involving either a complex cognitive or a matched guessing task. The main activations associated with the processing of performance feedback under different task conditions involved foci in the medial caudate nucleus and the ventromedial orbitofrontal cortex. A differential modulation of these activations as a function of task type was observed. In particular the orbitofrontal activation associated with the presence of feedback was only seen in the guessing task. These data suggest that the ventral striatum and orbitofrontal cortex are involved in processing of feedback information, findings consistent with animal and neurological studies. We propose that differential activation associated with guessing compared to planning suggests enhanced neural processing of feedback when the outcome of a task is uncontrollable or when information must be assimilated across a number of trials to assess performance.

Adult↗

An off-line strategy for constructing a patient-specific planning target volume in adaptive treatment process for prostate cancer.

PURPOSE: To improve the efficacy of dose delivery and dose escalation for external beam radiotherapy of prostate cancer, an off-line strategy for constructing a patient-specific planning target volume is developed in the adaptive radiotherapy process using image feedback of target location and patient setup position. MATERIALS AND METHODS: We hypothesize that a patient-specific confidence-limited planning target volume (cl-PTV), constructed using an initial sequence of daily measurements of internal target motion and patient setup error, exists and ensures that the clinical target volume (CTV) in the prostate cancer patient receives the prescribed dose within a predefined dose tolerance. A patient-specific bounding volume to correct for target location and compensate for target random motion was first constructed using the convex hull of the first k days of CT measurements. The bounding volume and the initial days of CT measurements were minimized based on a predefined dosimetric criterion. The hypothesis was tested using multiple daily CT images by mimicking the actual treatment of both conventional 4-field-box and intensity-modulated radiotherapy (IMRT) on each of 30 patients with prostate cancer. For each patient, a patient-specific setup margin was also applied to the bounding volume to form the final cl-PTV. This margin was determined using the random setup error predicted from the initial days of portal imaging measurements and the residuals after correcting for the systematic setup error. RESULTS: The bounding volume constructed using daily CT measurements in the first week of treatment are adequate for the conventional beam delivery to achieve maximum dose reduction in the CTV of 2% or less of the prescription dose, for at least 80% of patients (p = 0.08), and 4.5% or less for 95% of patients (p = 0.1). However, for IMRT delivery, 2 weeks of daily CT measurements are required to achieve a similar level of the dosimetric criterion, otherwise the maximum dose reduction of 7%, on average, in the CTV is expected. Furthermore, the patient-specific setup margin required for the IMRT treatment is at least twice larger than that for the conventional treatment, to maintain the same dosimetric criterion. As compared to the conventional PTV, the volume of cl-PTV is significantly reduced, while maintaining the same dosimetric criterion. CONCLUSION: The cl-PTV for prostate treatment can be constructed within the first week of treatment using the feedback of imaging measurements. The cl-PTV has the capability to exclude the systematic variation and compensate for the patient-specific random variation on target location and patient setup position. This implies that in the current off-line image feedback adaptive treatment process, a single plan modification can be performed within the second week of treatment to improve the efficacy of dose delivery and dose escalation for external beam therapy of prostate cancer.

Algorithms↗

Estimating the number of prions in yeast cells.

Certain yeast cells contain proteins that behave like the mammalian prion PrP and are called yeast prions. The yeast prion protein Sup35p can exist in one of two stable forms, giving rise to phenotypes [PSI(+)] and [psi(-)]. If the chemical guanidine hydrochloride (GdnHCl) is added to a culture of growing [PSI(+)] cells, the proportion of [PSI(+)] cells decreases over time. This process is called curing and is due to a failure to propagate the prion form of Sup35p. We describe how curing can be modelled, and improve upon previous models for the underlying processes of cell division and prion segregation; the new model allows for asymmetric cell division and unequal prion segregation. We conclude by outlining plans for future experimentation and modelling.

Cell Division↗

Coupling of conformational folding and disulfide-bond reactions in oxidative folding of proteins.

The oxidative folding of proteins consists of conformational folding and disulfide-bond reactions. These two processes are coupled significantly in folding-coupled regeneration steps, in which a single chemical reaction (the "forward" reaction) converts a conformationally unstable precursor species into a conformationally stable, disulfide-protected successor species. Two limiting-case mechanisms for folding-coupled regeneration steps are described. In the folded-precursor mechanism, the precursor species is preferentially folded at the moment of the forward reaction. The (transient) native structure increases the effective concentrations of the reactive thiol and disulfide groups, thus favoring the forward reaction. By contrast, in the quasi-stochastic mechanism, the forward reaction occurs quasi-stochastically in an unfolded precursor; i.e., reactive groups encounter each other with a probability determined primarily by loop entropy, albeit modified by conformational biases in the unfolded state. The resulting successor species is initially unfolded, and its folding competes with backward chemical reactions to the unfolded precursors. The folded-precursor and quasi-stochastic mechanisms may be distinguished experimentally by the dependence of their kinetics on factors affecting the rates of thiol--disulfide exchange and conformational (un)folding. Experimental data and structural and biochemical arguments suggest that the quasi-stochastic mechanism is more plausible than the folded-precursor mechanism for most proteins.

Disulfides↗

Stochastic properties of gustatory impulse discharges in rat chorda tympani fibers.

1. The present study was intended to elucidate the role of temporal patterns of impulse discharges of the gustatory primary afferents in the coding of taste qualities by the use of simultaneous analyses of the across-neuron patterning (5) and the temporal patterning of impulses. 2. Impulse discharges of 43 rat chorda tympani fibers elicited by gustatory stimulation (0.1 M NaCl, 0.5 M sucrose, 0.01 N HCl, 0.02 M quinine hydrochloride, 0.3 M KCl, and 0.02 M saccharin sodium) were recorded. The temporal patterns of impulse discharges elicited by these stimuli were statistically analyzed both in an initial dynamic phase and a succeeding stationary phase of responses. In the dynamic phase, the time courses of firing frequency were studied; however, these were not clearly associated with the qualities of taste stimuli. In the stationary phase, the stochastic properties of impulse trains were studied regarding the impulse trains as a stochastic point process (30). In this study, interspike interval histograms (ISI histograms), joint interval histograms, serial correlograms, and autocorrelograms were computed. 3. In general, the distribution patterns of ISI histogram were not absolutely specific to the taste qualities. However, the gamma or the exponential distribution occurred most often with 0.1 M NaCl, and the bimodal or the skewed distribution was dominated with 0.5 M sucrose stimulation among the stimuli tested. The rhythmic discharges did not occur exclusively with the sweet taste stimulation, though they occurred more often with the sweet taste stimulation than with other taste stimulations. The joint interval histogram and the serial correlogram were used to examine the stochastic properties of impulse trains with particular reference to the time dependence in the impulse trains. Generally, the time dependence was not concerned with the taste qualities. 4. The chorda tympani fibers were classified into three types according to the magnitude of responses and the temporal patterns of impulse discharges. The neurons predominantly responsive to NaCl and unresponsive to sucrose were classified as type I neurons. The remaining neurons, which moderately responded to both NaCl and sucrose, were further categorized into type II neurons and type III neurons, depending on their temporal patterns of impulse discharge. The type II neurons tended to show the rhythmic or burstlike firing of impulses in response to more than one kind of taste stimuli. 5. The results showed that the taste quality was represented in the characteristic temporal patterning of impulses as well as in the across-neuron patterning of responses. The possible origin of the temporal discharge pattern and its significance in gustatory information processing were discussed on the basis of the neuron types described above.

Afferent Pathways↗

Noise, delays, robustness, canalization and all that.

A biological system such as a developing embryo can withstand many perturbations. What is the basis of this robustness both against noise and mutation? Recent advances in modeling may throw new light on this old problem. First, recent theoretical and experimental work clearly demonstrates the importance of noise and time delays for the proper functioning of genetic networks: noise and delays are simply part of the normal operating constraints. By contrast, sweeping statements have been made recently about a so-called 'robustness' of biological processes, based on work that neglects noise and delays completely. I submit that studying the stability of complex biological systems with such omissions is an unnecessary, inadequate and potentially disastrous simplification. I review the existing alternatives and propose using them to construct a modeling framework that overcomes all serious limitations.

Computational Biology↗

Software sensors for bioprocesses.

State estimation is a significant problem in biotechnological processes, due to the general lack of hardware sensor measurements of the variables describing the process dynamics. The objective of this paper is to review a number of software sensor design methods, including extended Kalman filters, receding-horizon observers, asymptotic observers, and hybrid observers, which can be efficiently applied to bioprocesses. These several methods are illustrated with simulation and real-life case studies.

Algorithms↗

Estimation of vaccine efficacy in outbreaks of acute infectious diseases.

In a previous paper we defined the efficacy of a vaccine as 1-beta 1/beta 0, where beta 0 is the instantaneous probability of transmission of infection to an unvaccinated person exposed to a single infectious person, and beta 1 is similarly defined for a vaccinated person. We showed that under the conditions of an outbreak of an acute, directly transmitted infectious disease in a homogeneous and randomly mixing population, an estimate of this measure of vaccine efficacy is 1-[1n(1-A1)/1n(1-A0)], where A0 and A1 are the observed final attack rates among unvaccinated and vaccinated persons, respectively. In the present work we present an approximation for the standard error of this estimator, accounting for both the sampling and process variation. We extend the results of our previous paper to a stratified population, where the strata correspond to different levels of susceptibility and may have different vaccination coverage. We also consider populations that consist of small units (for example, households) where individuals mix primarily in these units. In this case, definition of vaccine efficacy is in terms of the within-unit transmission probabilities and is estimable by using transmission models for infectious diseases. We apply the estimation methods described above to data from influenza and measles outbreaks. We also examine, via a stochastic simulation study, the robustness of the vaccine efficacy estimators under various population structures and mixing patterns.

Adolescent↗

A model for the interaction of two chemicals.

We describe a method for studying the interaction of two anesthetic agents, Morphine and Midazolam, acting simultaneously in the same individual. Representing the levels of the two chemicals by diffusion processes, we assume their interaction is governed by a linear combination of the separate components. Pharmacological data is used to estimate the model parameters and, in particular, to determine the coefficient in the linear combination. This leads to the conclusion that the two chemicals have a counteractive effect.

Anesthetics↗

Adaptive denoising of event-related functional magnetic resonance imaging data using spectral subtraction.

A new adaptive signal-preserving technique for noise suppression in event-related functional magnetic resonance imaging (fMRI) data is proposed based on spectral subtraction. The proposed technique estimates a parametric model for the power spectrum of random noise from the acquired data based on the characteristics of the Rician statistical model. This model is subsequently used to estimate a noise-suppressed power spectrum for any given pixel time course by simple subtraction of power spectra. The new technique is tested using computer simulations and real data from event-related fMRI experiments. The results show the potential of the new technique in suppressing noise while preserving the other deterministic components in the signal. Moreover, we demonstrate that further analysis using principal component analysis and independent component analysis shows a significant improvement in both convergence and clarity of results when the new technique is used. Given its simple form, the new method does not change the statistical characteristics of the signal or cause correlated noise to be present in the processed signal. This suggests the value of the new technique as a useful preprocessing step for fMRI data analysis.

Algorithms↗

7th Jan Waldenström Lecture. The biology of human cancer metastasis.

The process of cancer metastasis is dynamic and consists of sequential, interrelated steps. Malignant cells that produce metastases have survived a series of potentially lethal interactions that are regulated by both the intrinsic properties of the tumor cells and host factors. Although some of the steps in this process contain stochastic elements, metastases develop from the nonrandom survival of a few subpopulations of cells that preexist within the parent neoplasm. Metastases can have a clonal origin, and different metastases can originate from the proliferation of different cells. The orthotopic implantation of human cancer cells derived from surgical specimens into nude mice provides a biological model of metastasis. Using this model, clonal analysis of a human renal carcinoma, colon carcinoma, and melanoma has revealed that these tumors are heterogeneous for metastatic properties. Damage to an organ's environment is followed by inflammation and repair, and these homeostatic processes facilitate the proliferation of normal (physiology), and in some cases, tumor cells (pathology). Accelerated growth of human colon cancer cells was found in hepatectomized nude mice, whereas accelerated growth of human renal cancer cells was found in nephrectomized nude mice. These data suggest that systemic physiological signals can be usurped by neoplastic cells. Collectively, the factors that regulate metastasis are the intrinsic properties of metastatic cells and host factors involved in homeostasis.

Animals↗

Power spectrum analysis of bursting cells in area MT in the behaving monkey.

It is widely held that visual cortical neurons encode information primarily in their mean firing rates. Some proposals, however, emphasize the information potentially available in the temporal structure of spike trains (Optican and Richmond, 1987; Bialek et al., 1991), in particular with respect to stimulus-related synchronized oscillations in the 30-70 Hz range (Eckhorn et al., 1988; Gray et al., 1989; Kreiter and Singer, 1992) as well as via bursting cells (Cattaneo et al., 1981a; Bonds, 1992). We investigate the temporal fine structure of spike trains recorded in extrastriate area MT of the trained macaque monkey, a region that plays a major role in processing motion information. The data were recorded while the monkey performed a near-threshold direction discrimination task so that both physiological and psychophysical data could be obtained on the same set of trials (Britten et al., 1992). We identify bursting cells and quantify their properties, in particular in relation to the behavior of the animal. We compute the power spectrum and the distribution of interspike intervals (ISIs) associated with individual spike trains from 212 cells, averaging these quantities across similar trials. (1) About 33% of the cells have a relatively flat power spectrum with a dip at low temporal frequencies. We analytically derive the power spectrum of a Poisson process with refractory period and show that it matches the observed spectrum of these cells. (2) About 62% of the cells have a peak in the 20-60 Hz frequency band. In about 10% of all cells, this peak is at least twice the height of its base. The presence of such a peak strongly correlates with a tendency of the cell to respond in bursts, that is, two to four spikes within 2-8 msec. For 93% of cells, the shape of the power spectrum did not change dramatically with stimulus conditions. (3) Both the ISI distribution and the power spectrum of the vast majority of bursting cells are compatible with the notion that these cells fire Poisson-distributed bursts, with a burst-related refractory period. Thus, for our stimulus conditions, no explicitly oscillating neuronal process is required to yield a peak in the power spectrum. (4) We found no statistically significant relationship between the peak in the power spectrum and psychophysical measures of the monkeys' performance on the direction discrimination task.(ABSTRACT TRUNCATED AT 400 WORDS)

Action Potentials↗

A simple kinetic model describes the processivity of myosin-v.

Myosin-V is a motor protein responsible for organelle and vesicle transport in cells. Recent single-molecule experiments have shown that it is an efficient processive motor that walks along actin filaments taking steps of mean size close to 36 nm. A theoretical study of myosin-V motility is presented following an approach used successfully to analyze the dynamics of conventional kinesin but also taking some account of step-size variations. Much of the present experimental data for myosin-V can be well described by a two-state chemical kinetic model with three load-dependent rates. In addition, the analysis predicts the variation of the mean velocity and of the randomness-a quantitative measure of the stochastic deviations from uniform, constant-speed motion-with ATP concentration under both resisting and assisting loads, and indicates a substep of size d(0) approximately 13-14 nm (from the ATP-binding state) that appears to accord with independent observations.

Adenosine Diphosphate↗

Statistical mechanics in biology: how ubiquitous are long-range correlations?

The purpose of this opening talk is to describe examples of recent progress in applying statistical mechanics to biological systems. We first briefly review several biological systems, and then focus on the fractal features characterized by the long-range correlations found recently in DNA sequences containing non-coding material. We discuss the evidence supporting the finding that for sequences containing only coding regions, there are no long-range correlations. We also discuss the recent finding that the exponent alpha characterizing the long-range correlations increases with evolution, and we discuss two related models, the insertion model and the insertion-deletion model, that may account for the presence of long-range correlations. Finally, we summarize the analysis of long-term data on human heartbeats (up to 10(4) heart beats) that supports the possibility that the successive increments in the cardiac beat-to-beat intervals of healthy subjects display scale-invariant, long-range "anti-correlations" (a tendency to beat faster is balanced by a tendency to beat slower later on). In contrast, for a group of subjects with severe heart disease, long-range correlations vanish. This finding suggests that the classical theory of homeostasis, according to which stable physiological processes seek to maintain "constancy," should be extended to account for this type of dynamical, far from equilibrium, behavior.

Base Sequence↗

Evolutionary dynamics of escape from biomedical intervention.

Viruses, bacteria, eukaryotic parasites, cancer cells, agricultural pests and other inconvenient animates have an unfortunate tendency to escape from selection pressures that are meant to control them. Chemotherapy, anti-viral drugs or antibiotics fail because their targets do not hold still, but evolve resistance. A major problem in developing vaccines is that microbes evolve and escape from immune responses. The fundamental question is the following: if a genetically diverse population of replicating organisms is challenged with a selection pressure that has the potential to eradicate it, what is the probability that this population will produce escape mutants? Here, we use multi-type branching processes to describe the accumulation of mutants in independent lineages. We calculate escape dynamics for arbitrary mutation networks and fitness landscapes. Our theory shows how to estimate the probability of success or failure of biomedical intervention, such as drug treatment and vaccination, against rapidly evolving organisms.

Biological Evolution↗