PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Monte Carlo Method”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

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

At least 685 records · Page 38Linked to original sources

Conformational transition free energy profiles of an adsorbed, lattice model protein by multicanonical Monte Carlo simulation.

Proteins often undergo changes in internal conformation upon interacting with a surface. We investigate the thermodynamics of surface induced conformational change in a lattice model protein using a multicanonical Monte Carlo method. The protein is a linear heteropolymer of 27 segments (of types A and B) confined to a cubic lattice. The segmental order and nearest neighbor contact energies are chosen to yield, in the absence of an adsorbing surface, a unique 3x3x3 folded structure. The surface is a plane of sites interacting either equally with A and B segments (equal affinity surface) or more strongly with the A segments (A affinity surface). We use a multicanonical Monte Carlo algorithm, with configuration bias and jump walking moves, featuring an iteratively updated sampling function that converges to the reciprocal of the density of states 1/Omega(E), E being the potential energy. We find inflection points in the configurational entropy, S(E)=k ln Omega(E), for all but a strongly adsorbing equal affinity surface, indicating the presence of free energy barriers to transition. When protein-surface interactions are weak, the free energy profiles F(E)=E-TS(E) qualitatively resemble those of a protein in the absence of a surface: a free energy barrier separates a folded, lowest energy state from globular, higher energy states. The surface acts in this case to stabilize the globular states relative to the folded state. When the protein surface interactions are stronger, the situation differs markedly: the folded state no longer occurs at the lowest energy and free energy barriers may be absent altogether.

Adsorption↗

Statistical issues in toxicokinetic modeling: a bayesian perspective.

Determining the relationship between an exposure and the resulting target tissue dose is a critical issue encountered in quantitative risk assessment (QRA). Classical or physiologically based toxicokinetic (PBTK) models can be useful in performing that task. Interest in using these models to improve extrapolations between species, routes, and exposure levels in QRA has therefore grown considerably in recent years. In parallel, PBTK models have become increasingly sophisticated. However, development of a strong statistical foundation to support PBTK model calibration and use has received little attention. There is a critical need for methods that address the uncertainties inherent in toxicokinetic data and the variability in the human populations for which risk predictions are made and to take advantage of a priori information on parameters during the calibration process. Natural solutions to these problems can be found in a Bayesian statistical framework with the help of computational techniques such as Markov chain Monte Carlo methods. Within such a framework, we have developed an approach to toxicokinetic modeling that can be applied to heterogeneous human or animal populations. This approach also expands the possibilities for uncertainty analysis. We present a review of these efforts and other developments in these areas. Appropriate statistical treatment of uncertainty and variability within the modeling process will increase confidence in model results and ultimately contribute to an improved scientific basis for the estimation of occupational and environmental health risks.

Bayes Theorem↗

Binary latent variable modelling and its applicationin the study of air pollution in Hong Kong.

A binary latent variable is constructed to account for the correlation between multiple binary outcomes and is treated as a dependent variable in modelling for covariate effects. This modelling method is similar to the structural equation modelling. Three models are considered: (1) all covariates affecting the binary latent variable directly; (2) some covariates affecting the binary latent variable while other affecting the manifestation of the binary outcomes; and (3) no covariates are included. Gibbs sampling, a special case of the Markov Chain Monte Carlo method, is used to estimate the parameters in the models. Simulation studies show that this method is valid and reliable in estimating covariate effects. But Model (1) fitted the data best with lowest value in the deviance information criteria. The method is illustrated by applying it to the data analysis of an environmental air pollution study. The results show that air pollution (i.e. the most versus the least polluted district) (odds ratio 1.20; 95% confidence interval 0.97-1.49; p=0.102), smoking (relative to not smoking) (2.75; 2.21-3.41; p < 0.001) and mosquito coil use (relative to non-use) (1.27; 0.99-1.62; p=0.058) had an impact on the respiratory health of male adults in Hong Kong.

Air Pollution↗

Estimates of thyroid equivalent dose in Lithuania following the Chernobyl accident.

The volatile radioiodine was detected in Lithuania in the very first days after the Chernobyl accident. The proportion of gaseous 131I species of airborne iodine identified during that period exceeded from 2 to 4 times the aerosol fraction. The radioiodine activity of milk consumed by inhabitants of Lithuania varied over a broad range. 131I activity in milk reached a peak on the fourth day after deposition and then decreased with an effective half-time ranging from 4.2 +/- 0.6 d to 5.2 +/- 0.9 d. Thyroid examinations by dosimetric teams were not available in Lithuania for reasons beyond the control of experimenters. Because of this, thyroid equivalent doses were estimated using the modified ICRP three-compartment cyclic model. These calculations applied Monte Carlo methods and consideration of regional iodine deficiency to generate frequency distributions of equivalent doses to the infant and adult thyroid gland in three areas of Lithuania with different contamination levels.

Adult↗

Bayesian 2-D deconvolution: a model for diffuse ultrasound scattering.

Observed medical ultrasound images are degraded representations of the true acoustic tissue reflectance. The degradation is due to blur and speckle and significantly reduces the diagnostic value of the images. To remove both blur and speckle, we have developed a new statistical model for diffuse scattering in 2-D ultrasound radio frequency images, incorporating both spatial smoothness constraints and a physical model for diffuse scattering. The modeling approach is Bayesian in nature, and we use Markov chain Monte Carlo methods to obtain the restorations. The results from restorations of some real and simulated radio frequency ultrasound images are presented and compared with results produced by Wiener filtering.

Algorithms↗

[Model calculations of the Energy distribution of scattered radiation in a patient (author's transl)].

To obtain quantitative results on scattered radiation produced in a patient by externally applied x-rays or gamma rays, the model of a pencil beam penetrating a water layer is used. By means of the Monte-Carlo method, the energy distribution of scattered photons in a plane parallel to the absorbing layer is calculated for primary photon energies from 60 to 1250 keV. This yields information on the distribution of single-scatter and multiple-scatter photons.

Elementary Particles↗

Dosimetric evaluation of a widely used kilovoltage x-ray unit for endocavitary radiotherapy.

In this paper we present the dosimetric data of a Therapax DTX300 kilovoltage x-ray unit for endocavitary rectal irradiation. The unit if operated at tube voltage of 40-60 kVp (30 mA) with an added filtration of 0.2-0.4 mm Al generates acceptable beam qualities comparable to those of the original Papillon technique. Relative dosimetric measurements were performed at the cone end (37.2 cm SSD) of a 3 cm diameter rectal cone using various detectors to ensure the accuracy. A Monte Carlo method was used to calculate correction factors for the diode used in the percentage depth-dose (PDD) measurement, and to study the effect of the detector size on the beam profile. The PDD data were determined using the diode measurement corrected for its energy and angular response. It was found that the PTW N23342 and Markus parallel-plate chamber can be used directly to measure the PDD for this beam quality with 2% uncertainty. Measurement and Monte Carlo results have shown that the detector size has a significant effect on the penumbral profile. Film and diode detectors have a better spatial resolution compared to ionization chambers, but they may give an incorrect profile tail due to either nonlinear response at low energy or angular dependence. This can be corrected using the ionization-chamber measurement, based on the Monte Carlo analysis. The isodose distributions for this x-ray unit are presented.

Brachytherapy↗

Stability of G,A triple helices.

In this work we selected double-stranded DNA sequences capable of forming stable triplexes at 20 or 50 degrees C with corresponding 13mer purine oligonucleotides. This selection was obtained by a double aptamer approach where both the starting sequences of the oligonucleotides and the target DNA duplex were random. The results of selection were confirmed by a cold exchange method and the influence of the position of a 'mismatch' on the stability of the triplex was documented in several cases. The selected sequences obey two rules: (i) they have a high G content; (ii) for a given G content the stability of the resulting triplex is higher if the G residues lie in stretches. The computer simulation of the Mg2+, Na+and Cl-environment around three triplexes by a density scaled Monte Carlo method provides an interpretation of the experimental observations. The Mg2+cations are statistically close to the G N7 and relatively far from the A N7. The presence of an A repels the Mg2+from adjacent G residues. Therefore, the triplexes are stabilized when the Mg2+can form a continuous spine on G N7.

Base Sequence↗

Calculation of doses in intracavitary therapy.

The computer simulation of the gamma-energy spectrum of four radionuclides usually used in intracavitary therapy was performed. A Monte Carlo method was used for simulation of the decay schemes. The emerging gamma-energy spectra of the radioactive source assemblies were obtained as the result of the interaction of emitted source radiation with the protective stainless steel sheath and the radioactive material itself.

Brachytherapy↗

Depolarization and blurring of optical images by biological tissue.

We present a study of the image blurring and depolarization resulting from the transmission of a narrow beam of light through a continuous random medium. We investigate the dependence of image quality degradation and of depolarization on optical thickness, correlation length of the inhomogeneities, and incident polarization state. This is done numerically with a Monte Carlo method based on a transport equation that takes into account polarization of light. We compare our results with those for transport in media with discrete spherical scatterers. We show that depolarization effects are different in these two models of biological tissue.

Lasers↗

Control of familywise errors in multiple endpoint assessments via stepwise permutation tests.

We describe permutation based sequentially rejective multiple comparison procedures useful in multiple endpoint assessments. We used Monte Carlo methods to compare the power of these newly devised tests to that of tests due to Holm and Rom as well as to the classical Bonferroni method. We illustrate applications of the methods with analysis of visual field data collected from optic neuritis patients. We conclude that the new methods are particularly useful when there are many endpoints involved, the data are significantly correlated, and/or the distributional assumptions are questionable.

Adolescent↗

A Monte Carlo tutorial and the application for radiotherapy treatment planning.

Monte Carlo-based treatment planning algorithms are advancing rapidly and will certainly be implemented as part of conventional treatment planning systems in the near future. This paper was designed as a basic tutorial for using the Monte Carlo method as applied to radiotherapy treatment planning. The tutorial addresses the basic transport differences between photon and electron transport as well as the sampling distributions. The implementation of a virtual linac source model and the conversion from the Monte Carlo source modeling reference plane into the treatment reference plane is discussed. The implementation of a thresholding algorithm for converting CT electron density to patient specific materials is also presented. A 6-field prostate boost treatment is used to compare a conventional treatment planning algorithm (pencil beam model) with a Monte Carlo simulation algorithm. The agreement between the 2 calculation methods is good based upon the qualitative comparison of the isodose distribution and the dose-volume histograms for the prostate and the rectum. The effects of statistical uncertainty on the Monte Carlo calculation are also presented.

Humans↗

Relationship information contained in gamete identity by descent data.

We consider idealized gamete identity by descent (IBD) data which consists of the lengths of IBD and non-IBD regions along the genome for gametes segregating from two related individuals. Information on the relationship between the individuals is contained in the pattern of lengths, with the power of the likelihood ratio test to reject one relationship in favor of another giving a measure of the information contained in the data. We model crossovers with a Poisson process and, under this assumption, present a novel Monte Carlo method for calculating the likelihood of a particular relationship for a given data set. The method provides a way to calculate the information content of data and find the maximum power that tests of relationship can achieve. Simulated data from cousin and greatgrandparent-greatgrandchild relationships is analyzed as an example.

Algorithms↗

A Bayesian approach to net health benefits: an illustration and application to modeling HIV prevention.

PURPOSE: To conduct a cost-effectiveness analysis of HIV prevention when costs and effects cannot be measured directly. To quantify the total estimation of uncertainty due to sampling variability as well as inexact knowledge of HIV transmission parameters. METHODS: The authors focus on estimating the incremental net health benefit (INHB) in a randomized trial of HIV prevention with intervention and control conditions. Using a Bernoulli model of HIV transmission, changes in the participants' risk behaviors are converted into the number of HIV infections averted. A sampling model is used to account for variation in the behavior measurements. Bayes's theorem and Monte Carlo methods are used to attain the stated objectives. RESULTS: The authors obtained a positive mean INHB of 0.0008, indicating that advocacy training is just slightly favored over the control condition for men, assuming a $50,000 per quality-adjusted life year (QALY) threshold. To be confident of a positive INHB, the decision maker would need to spend more than $100,000 per QALY.

Bayes Theorem↗

MASTOS: Mammography Simulation Tool for design Optimization Studies.

Mammography is a high quality imaging technique for the detection of breast lesions, which requires dedicated equipment and optimum operation. The design parameters of a mammography unit have to be decided and evaluated before the construction of such a high cost of apparatus. The optimum operational parameters also must be defined well before the real breast examination. MASTOS is a software package, based on Monte Carlo methods, that is designed to be used as a simulation tool in mammography. The input consists of the parameters that have to be specified when using a mammography unit, and also the parameters specifying the shape and composition of the breast phantom. In addition, the input may specify parameters needed in the design of a new mammographic apparatus. The main output of the simulation is a mammographic image and calculations of various factors that describe the image quality. The Monte Carlo simulation code is PC-based and is driven by an outer shell of a graphical user interface. The entire software package is a simulation tool for mammography and can be applied in basic research and/or in training in the fields of medical physics and biomedical engineering as well as in the performance evaluation of new designs of mammography units and in the determination of optimum standards for the operational parameters of a mammography unit.

Algorithms↗

Combining physiologically based pharmacokinetic modeling with Monte Carlo simulation to derive an acute inhalation guidance value for trichloroethylene.

Using the Monte Carlo method and physiologically based pharmacokinetic modeling, an occupational inhalation exposure to trichloroethylene consisting of 7 h of exposure per day for 5 days was simulated in populations of men and women of 5000 individuals each. The endpoint of concern for occupational exposure was drowsiness. The toxicologic condition leading to drowsiness was assumed to be high levels of both trichloroethanol and trichloroethylene. Therefore, the output of the simulation or dose metric was the maximum value of the sum of the concentration of trichloroethylene in blood and the concentration of trichloroethanol within its volume of distribution occurring within 1 week of exposure. The distributions of the dose metric in the simulated populations were lognormal. To protect 99% of a worker population, a concentration of 30 ppm over a 7-h period of the work day should not be exceeded. Subjecting a susceptible individual (the 99th percentile of the dose metric) to 200 ppm (the ACGIH short-term exposure limit or STEL) for 15 min twice a day over a work week necessitates a 2.5-h rest in fresh air following the STEL exposure to allow the blood concentrations of trichloroethylene and trichloroethanol to drop to levels that would not cause drowsiness. Both the OSHA PEL and the ACGIH TLV are greater than the value of 30 ppm derived here. As well as suggesting a new occupational guidance value, this study provides an example of this method of guidance value derivation.

Administration, Inhalation↗

Computer simulations of protein folding with a small number of distance restraints.

A high coordination lattice model was used to represent the protein chain. Lattice points correspond to amino-acid side groups. A complicated force field was designed in order to reproduce a protein-like behavior of the chain. Long-distance tertiary restraints were also introduced into the model. The Replica Exchange Monte Carlo method was applied to find the lowest energy states of the folded chain and to solve the problem of multiple minima. In this method, a set of replicas of the model chain was simulated independently in different temperatures with the exchanges of replicas allowed. The model chains, which consisted of up to 100 residues, were folded to structures whose root-mean-square deviation (RMSD) from their native state was between 2.5 and 5 A. Introduction of restrain based on the positions of the backbone hydrogen atoms led to an improvement in the number of successful simulation runs. A small improvement (about 0.5 A) was also achieved in the RMSD of the folds. The proposed method can be used for the refinement of structures determined experimentally from NMR data.

Algorithms↗

Bayesian inference for prevalence in longitudinal two-phase studies.

We consider Bayesian inference and model selection for prevalence estimation using a longitudinal two-phase design in which subjects initially receive a low-cost screening test followed by an expensive diagnostic test conducted on several occasions. The change in the subject's diagnostic probability over time is described using four mixed-effects probit models in which the subject-specific effects are captured by latent variables. The computations are performed using Markov chain Monte Carlo methods. These models are then compared using the deviance information criterion. The methodology is illustrated with an analysis of alcohol and drug use in adolescents using data from the Great Smoky Mountains Study.

Adolescent↗