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Results for “Monte Carlo Method”

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At least 703 records · Page 39Linked to original sources

PubMed2001

Corrections for inhomogeneities in biological tissue caused by blood vessels.

In tissue optics, the assumption that blood is homogeneously distributed in tissue can give rise to miscalculations because blood is found only in blood vessels. In our paper randomly oriented blood vessels are treated as particles for which we obtained apparent absorption and scattering coefficients by means of the Monte Carlo method. Apart from this correction for the contribution of blood properties in tissue, a correction for the contribution of the surrounding tissue proved to be needed as well. The results found with our model were compared with available results from the literature.

Blood Vessels↗

PubMed1993

Refinement of the F-actin model against X-ray fiber diffraction data by the use of a directed mutation algorithm.

The F-actin model has been refined by a Directed Mutation Algorithm, a reiterative procedure which combines a Monte-Carlo method of selecting subdomains to be refined at each cycle with a non-linear least-squares routine to get the best fit for the particular selected domains. The G-actin crystal structure was used as a starting model. The experimental data were obtained by X-ray fiber diffraction patterns from oriented F-actin gels. After 250 cycles we were able to obtain an almost perfect fit of the calculated diffraction pattern to the experimental diffraction pattern as well as a reasonable stereochemistry including intermolecular interactions of the actin monomers with an r.m.s. shift in the C alpha-positions of 3.2 A from the crystal coordinates. The stereochemistry of the intersubunit packing was calculated by molecular dynamics using the program X-PLOR. In addition, the binding site of phalloidin, a cyclic heptapeptide from the mushroom Amanita phalloides, could be determined. Furthermore, we were able to determine differences in the structures of F-actin with and without phalloidin. The method proved itself robust and showed a high degree of convergence.

Actins↗

PubMed1998

Study of dosimetry consistency for kilovoltage x-ray beams.

In this paper, the consistency of kilovoltage (tube potentials between 40 and 300 kV) x-ray beam dosimetry using the "in-air" method and the in-phantom measurement has been studied. The procedures for the measurement of the central-axis depth-dose curve, which serve as a link between the dose at the reference depth to the dose elsewhere in a phantom, were examined. The uncertainties on the measured dose distributions were analyzed with the emphasis on the surface dose measurement. The Monte Carlo method was used to calculate the perturbation correction factors for a photon diode and a NACP plane-parallel ionization chamber at different depths in a water phantom irradiated by 100-300 kV (2.43 mm Al-3.67 mm Cu half-value layer) x-ray beams. The depth-dose curves measured with these two detectors, after correcting for the perturbation effect (up to 15% corrections), agreed with each other to within 1.5%. Comparisons of the doses at the phantom surface and at 2 cm depth in water for photon beams of 100-300 kV tube potential obtained using the "backscatter" method and those using the "in-phantom" measurement have shown that the "in-air" method can be equally applied to this energy range if the depth-dose curve can be measured accurately. To this end, measured depth ionization curves require depth-dependent correction factors.

Humans↗

PubMed2000

Genetic analysis of the age at menopause by using estimating equations and Bayesian random effects models.

Multi-wave self-report data on age at menopause in 2182 female twin pairs (1355 monozygotic and 827 dizygotic pairs), were analysed to estimate the genetic, common and unique environmental contribution to variation in age at menopause. Two complementary approaches for analysing correlated time-to-onset twin data are considered: the generalized estimating equations (GEE) method in which one can estimate zygosity-specific dependence simultaneously with regression coefficients that describe the average population response to changing covariates; and a subject-specific Bayesian mixed model in which heterogeneity in regression parameters is explicitly modelled and the different components of variation may be estimated directly. The proportional hazards and Weibull models were utilized, as both produce natural frameworks for estimating relative risks while adjusting for simultaneous effects of other covariates. A simple Markov chain Monte Carlo method for covariate imputation of missing data was used and the actual implementation of the Bayesian model was based on Gibbs sampling using the freeware package BUGS.

Adult↗

PubMed2005

A configuration space of homologous proteins conserving mutual information and allowing a phylogeny inference based on pair-wise Z-score probabilities.

BACKGROUND: Popular methods to reconstruct molecular phylogenies are based on multiple sequence alignments, in which addition or removal of data may change the resulting tree topology. We have sought a representation of homologous proteins that would conserve the information of pair-wise sequence alignments, respect probabilistic properties of Z-scores (Monte Carlo methods applied to pair-wise comparisons) and be the basis for a novel method of consistent and stable phylogenetic reconstruction. RESULTS: We have built up a spatial representation of protein sequences using concepts from particle physics (configuration space) and respecting a frame of constraints deduced from pair-wise alignment score properties in information theory. The obtained configuration space of homologous proteins (CSHP) allows the representation of real and shuffled sequences, and thereupon an expression of the TULIP theorem for Z-score probabilities. Based on the CSHP, we propose a phylogeny reconstruction using Z-scores. Deduced trees, called TULIP trees, are consistent with multiple-alignment based trees. Furthermore, the TULIP tree reconstruction method provides a solution for some previously reported incongruent results, such as the apicomplexan enolase phylogeny. CONCLUSION: The CSHP is a unified model that conserves mutual information between proteins in the way physical models conserve energy. Applications include the reconstruction of evolutionary consistent and robust trees, the topology of which is based on a spatial representation that is not reordered after addition or removal of sequences. The CSHP and its assigned phylogenetic topology, provide a powerful and easily updated representation for massive pair-wise genome comparisons based on Z-score computations.

Algorithms↗

PubMed2003

[Population pharmacokinetics of phenytoin in pediatric patients].

OBJECTIVE: To study population pharmacokinetics of phenytoin in pediatric patients by using sparse data. METHODS: We used routinely collected therapeutic drug monitoring data, derived from the steady state serum concentrations of phenytoin in 42 pediatric outpatients with epilepsy. Depending on whether the patients were administered with phenytoin alone or coadministered with phenobabital or clonazepam, the subjects were divided into two groups: phenytoin group and coadministration group. The population parameter and individual parameter of phenytoin in children were estimated using Monte Carlo method. RESULTS: The children's phenytoin population pharmacokinetic parameters Vm and Km were 9.8 mg.kg(-1).d(-1) and 2.73 mg/L in phenytoin group; and 9.2 mg.kg(-1).d(-1) and 3.24 mg/L in coadministration group. There were good relationship between predicted and determined concentrations with correlation coefficient of 0.999 and 0.984, respectively. CONCLUSION: The coadministration of phenobarbital or clonazepam obviously affected the pharmacokinetics of phenytoin. The population pharmacokinetics of phenytoin in children may provide a usefull index for individualization of dosage regimen.

Adolescent↗

PubMed2006

Dynamic survival models with spatial frailty.

In many survival studies, covariates effects are time-varying and there is presence of spatial effects. Dynamic models can be used to cope with the variations of the effects and spatial components are introduced to handle spatial variation. This paper proposes a methodology to simultaneously introduce these components into the model. A number of specifications for the spatial components are considered. Estimation is performed via a Bayesian approach through Markov chain Monte Carlo methods. Models are compared to assess relevance of their components. Analysis of a real data set is performed, showing the relevance of both time-varying covariate effects and spatial components. Extensions to the methodology are proposed along with concluding remarks.

Bayes Theorem↗

PubMed1997

Monte Carlo simulation of depth-dose distributions in TLD-100 under 90Sr-90Y irradiation.

In this work the depth-dose distribution in TLD-100 dosimeters under beta irradiation from a 90Sr-90Y source was investigated using the Monte Carlo method. Comparisons between the simulated data and experimental results showed that the depth-dose distribution is strongly affected by the different components of both the source and dosimeter holders due to the large number of electron scattering events.

Beta Particles↗

PubMed2002

Growth of a virtual tumour using probabilistic methods of cell generation.

A study into treatment enhancement in combined chemo-radiotherapy for unresectable head and neck cancer has initiated the development of a computer model of tumour growth. The model is based on biological parameters, and characterises tumour growth prior to chemo-radiotherapy. Tumour growth starting from a single stem cell is modelled using the Monte Carlo method. The type of the cell function, their relative proportions on mitosis, their proliferative capacity, the duration of the four phases of the cell cycle, the mean cell cycle time, and the cell loss due to natural causes are the main parameters of the basic model. A Gaussian distribution function operates in establishing the cell cycle time, with a mean value of 33 hours, while the cell type is sampled from a uniform distribution. With the established model, the sensitivity of the developed tumour's cell population to the stem, proliferative and nonproliferative ratio at mitosis was assessed. The present model accurately reflects the exponential distribution of cells along the cell cycle (70% cells in GI phase, 15% in S, 10% in G2, 5% in M) of a developed tumour as described in the literature. The proportion of stem, finitely proliferating and resting cells during tumour growth is maintained within their biological limits (2% stem, 13% finitely proliferating, 85% nonproliferating cells). The ratio (R = 3) between the time necessary to develop a clinically detectable tumour (10(9) cells) and the further time to grow to its lethal size (10(12) cells) is in accordance with the biological data when tumour volume is compared for the two periods (30 doublings and 10 doublings respectively). In conclusion, computer simulation can illustrate the biological growth of a tumour and the cell distribution along the cell cycle. These distributions may then be used in the assessment of tumour response to radiotherapy and to specific chemotherapeutic agents.

Cell Count↗

PubMed1990

Confidence intervals for the parameters of psychometric functions.

A Monte Carlo method for computing the bias and standard deviation of estimates of the parameters of a psychometric function such as the Weibull/Quick is described. The method, based on Efron's parametric bootstrap, can also be used to estimate confidence intervals for these parameters. The method's ability to predict bias, standard deviation, and confidence intervals is evaluated in two ways. First, its predictions are compared to the outcomes of Monte Carlo simulations of psychophysical experiments. Second, its predicted confidence intervals were compared with the actual variability of human observers in a psychophysical task. Computer programs implementing the method are available from the author.

Discrimination Learning↗

PubMed1987

Electron tunneling paths in proteins.

One of the crucial issues in biological electron transfer is the determination of the role of spatially intermediate amino acid residues in controlling or directing the electronic tunneling interaction between redox sites. A quantum path integral Monte Carlo method is developed for the analysis of electronic tunneling pathways in a highly structured environment. This path integral method is applied to intramolecular electron transfer in a ruthenium-modified myoglobin that contains a tryptophan in the "line-of-flight." A principal result is the identification of the relevant cylindrical zone swept out by the tunneling electron.

Electron Transport↗

PubMed2004

Quality assurance of patient dosimetry in boron neutron capture therapy.

The verification of the correctness of planned and executed treatments is imperative for safety in radiotherapy. The purpose of the present work is to describe and evaluate the quality assurance (QA) procedures for patient dosimetry implemented at the boron neutron capture therapy (BNCT) facility at Studsvik, Sweden. The dosimetric complexity of the mixed neutron-photon field during BNCT suggests a careful verification of routine procedures, specifically the treatment planning calculations. In the present study, two methods for QA of patient dosimetry are presented. The first is executed prior to radiotherapy and involves an independent check of the planned absorbed dose to be delivered to a point in the patient for each treatment field. The second QA procedure involves in vivo dosimetry measurements using post-treatment activation analysis. Absorbed dose conversion factors taking the difference in material composition and geometry of the patient and the PMMA phantom used for reference dosimetry were determined using the Monte Carlo method. The agreement of the QA procedure prior to radiotherapy reveals an acceptably small deviation for 60 treatment fields of +/-4.2% (1 SD), while the in vivo dosimetry method presented may benefit from improvements, as the deviations observed were quite substantial (+/- 12%, 1 SD), and were unlikely to be due to actual errors in the clinical dosimetry

Boron Neutron Capture Therapy↗

PubMed2001

Highly potent side-chain to side-chain cyclized enkephalin analogues containing a carbonyl bridge: synthesis, biology and conformation.

Six novel cyclic enkephalin analogues have been synthesized. Cyclization of the linear peptides containing basic amino acid residues in position 2 and 5 was achieved by treatment with bis(4-nitrophenyl)carbonate. It was found that some of the compounds exibit unusually high mu-opioid activity in the guinea pig ileum (GPI) assay. The 18-membered analogue cyclo(N(epsilon),N(beta)-carbonyl-D-Lys2,Dap5)-enkephalinamide turned out to be one of the most potent mu-agonists reported so far. NMR spectra of the peptides were recorded and structural parameters were determined. The conformational space was exhaustively examined for each of them using the electrostatically driven Monte Carlo method. Each peptide was finally described as an ensemble of conformations. A model of the bioactive conformation of this class of opioid peptides was proposed.

Animals↗

PubMed1992

The role of cell death in the growth of preneoplastic lesions: a Monte Carlo simulation model.

A variety of experimental and clinical examples of preneoplasia demonstrate that regression of early lesions is common. This paper examines the hypothesis that early lesions operate under the identical growth kinetics of 'late' lesions (neoplasms), but that kinetic features favouring continuous growth in established lesions tend to favour extinction of lesions composed of small numbers of cells. Growth simulations of early lesions were produced using the Monte Carlo method, a technique demanding intensive computations. With the advent of powerful personal computers, this technique is now widely available to biologists. Simulating growth under conditions of cell loss similar to those observed in established tumours, the model predicts that the great majority of initiated cell clusters are expected to reach extinction within a few cell doubling times, and most early (promoted) lesions would not likely progress to the size of a clinically detectable lesion within the life span of the host organism. These Monte Carlo simulations provide a model of initiated cell growth consistent with the recently demonstrated role of early lesion cell death in the development of human lymphomas and in transgenic mice expressing the bcl-2 oncogene. The model demonstrates that small increments in the intrinsic cell loss probability in even the earliest progenitors of malignancy can strongly influence the subsequent development of neoplasia from initiated foci.

Apoptosis↗

PubMedDate not supplied

Image feature analysis and computer-aided diagnosis in digital radiography. I. Automated detection of microcalcifications in mammography.

We have investigated the application of computer-based methods to the detection of microcalcifications in digital mammograms. The computer detection system is based on a difference-image technique in which a signal-suppressed image is subtracted from a signal-enhanced image to remove the structured background in a mammogram. Signal-extraction techniques adapted to the known physical characteristics of microcalcifications are then used to isolate microcalcifications from the remaining noise background. We employ Monte Carlo methods to generate simulated clusters of microcalcifications that are superimposed on normal mammographic backgrounds. This allows quantitative evaluation of detection accuracy of the computer method and the dependence of this accuracy on the physical characteristics of the microcalcifications. Our present computer method can achieve a true-positive cluster detection rate of approximately 80% at a false-positive detection rate of one cluster per image. The potential application of such a computer-aided system to mammographic interpretation is demonstrated by its ability to detect microcalcifications in clinical mammograms.

Algorithms↗

PubMed2004

Understanding actin organization in cell structure through lattice based Monte Carlo simulations.

Understanding the connection between mechanics and cell structure requires the exploration of the key molecular constituents responsible for cell shape and motility. One of these molecular bridges is the cytoskeleton, which is involved with intracellular organization and mechanotransduction. In order to examine the structure in cells, we have developed a computational technique that is able to probe the self-assembly of actin filaments through a lattice based Monte Carlo method. We have modeled the polymerization of these filaments based upon the interactions of globular actin through a probabilistic model encompassing both inert and active proteins. The results show similar response to classic ordinary differential equations at low molecular concentrations, but a bi-phasic divergence at realistic concentrations for living mammalian cells. Further, by introducing localized mobility parameters, we are able to simulate molecular gradients that are observed in nonhomogeneous protein distributions in vivo. The method and results have potential applications in cell and molecular biology as well as self-assembly for organic and inorganic systems.

Actins↗

PubMed1987

The Monte Carlo simulation of pearl chain formation.

The phenomenon of pearl chain formation (PCF) is investigated by means of a statistical model using the Monte Carlo method. Fifteen particles (cells) interacting with simple dipole-dipole potential are shown to form chains under the influence of an external field with a threshold potential significantly lower than the two particle estimate. A possible overlap between PCF and the thermal effects of an electric field is suggested.

Algorithms↗

PubMed2000

Effective dose equivalent and effective dose: comparison for common projections in oral and maxillofacial radiology.

OBJECTIVES: Effective dose equivalents (H(E)) and effective doses (E) for radiographic projections common in dentistry, calculated from the same organ dose distributions, are presented to determine whether the 2 quantities can be directly compared. STUDY DESIGN: Doses to all organs and tissues in the head, neck, trunk, and proximal extremities were determined for each projection (intraoral full-mouth radiographic survey, panoramic, cephalometric, temporomandibular tomograms, and submentovertex view) by computer simulation with Monte Carlo methods. H(E) and E were calculated from these complete distributions and by methods prescribed by the International Commission on Radiological Protection (ICRP). RESULTS: H(E) and E computed from complete dose distributions were found comparable within a few percentage points. However, those computed by strict application of ICRP methods were not. CONCLUSION: For radiographic projections with highly localized dose distributions, such as those common in dentistry, direct comparison of H(E) and E may not be meaningful, unless both computation algorithms are known.

Algorithms↗