Effective dose of A-bomb radiation in Hiroshima and Nagasaki as assessed by chromosomal effectiveness of spectrum energy photons and neutrons

The effective dose of combined spectrum energy neutrons and high energy spectrum γ-rays in A-bomb survivors in Hiroshima and Nagasaki has long been a matter of discussion. The reason is largely due to the paucity of biological data for high energy photons, particularly for those with an energy of tens of MeV. To circumvent this problem, a mathematical formalism was developed for the photon energy dependency of chromosomal effectiveness by reviewing a large number of data sets published in the literature on dicentric chromosome formation in human lymphocytes. The chromosomal effectiveness was expressed by a simple multiparametric function of photon energy, which made it possible to estimate the effective dose of spectrum energy photons and differential evaluation in the field of mixed neutron and γ-ray exposure with an internal reference radiation. The effective dose of reactor-produced spectrum energy neutrons was insensitive to the fine structure of the energy distribution and was accessible by a generalized formula applicable to the A-bomb neutrons. Energy spectra of all sources of A-bomb γ-rays at different tissue depths were simulated by a Monte Carlo calculation applied on an ICRU sphere. Using kerma-weighted chromosomal effectiveness of A-bomb spectrum energy photons, the effective dose of A-bomb neutrons was determined, where the relative biological effectiveness (RBE) of neutrons was expressed by a dose-dependent variable RBE, RBE(γ, D _n), against A-bomb γ-rays as an internal reference radiation. When the newly estimated variable RBE(γ, D _n) was applied to the chromosome data of A-bomb survivors in Hiroshima and Nagasaki, the city difference was completely eliminated. The revised effective dose was about 35% larger in Hiroshima, 19% larger in Nagasaki and 26% larger for the combined cohort compared with that based on a constant RBE of 10. Since the differences are significantly large, the proposed effective dose might have an impact on the magnitude of the risk estimates deduced from the A-bomb survivor cohort.     

Measurement of the unstained biological sample by a novel scanning electron generation X-ray microscope based on SEM

We introduced a novel X-ray microscope system based on scanning electron microscopy using thin film, which enables the measurement of unstained biological samples without damage. An unstained yeast sample was adsorbed under a titanium (Ti)-coated silicon nitride (Si₃N₄) film 90 nm thick. The X-ray signal from the film was detected by an X-ray photodiode (PD) placed below the sample. With an electron beam at 2.6 kV acceleration and 6.75 nA current, the yeast image is obtained using the X-ray PD. The image is created by soft X-rays from the Ti layer. The Ti layer is effective in generating the characteristic 2.7-nm wavelength X-rays by the irradiation of electrons. Furthermore, we investigated the electron trajectory and the generation of the characteristic X-rays within the Ti-coated Si₃N₄ film by Monte Carlo simulation. Our system can be easily utilized to observe various unstained biological samples of cells, bacteria, and viruses.     

Monte carlo study of the percolation in two-dimensional polymer systems

The structure of a two-dimensional film formed by adsorbed polymer chains was studied by means of Monte Carlo simulations. The polymer chains were represented by linear sequences of lattice beads and positions of these beads were restricted to vertices of a two-dimensional square lattice. Two different Monte Carlo methods were employed to determine the properties of the model system. The first was the random sequential adsorption (RSA) and the second one was based on Monte Carlo simulations with a Verdier-Stockmayer sampling algorithm. The methodology concerning the determination of the percolation thresholds for an infinite chain system was discussed. The influence of the chain length on both thresholds was presented and discussed. It was shown that the RSA method gave considerably lower thresholds for longer chains. This behavior can be explained by a different pool of chain conformations used in the calculations in both methods under consideration.

Integrated Terahertz Surface Plasmon Resonance on Polyvinylidene Fluoride Layer for the Profiling of Fluid Reflectance Spectra

We design terahertz (THz) surface-plasmon-resonance (SPR) sensors using a ferroelectric polyvinylidene fluoride (PVDF) thin layer for biological sensing. The reflectivity properties based on SPR are described using transfer matrix method (TMM) and numerically simulated using finite-difference time domain (FDTD) method. The sensing characteristics of the structure are systematically analyzed through the examination of the reflectivity spectrum. The results reveal that the pronounced SPR resonance peak has quasi-linear relationship with the refractive index variation of the material under investigation. Through analyzing and optimizing the structural parameters of the THz SPR sensor, we achieved the theoretical value of the refractive index detection sensitivity as high as 0.393 THz/unit change of refractive index (RIU) for a 20-μm-thick liquid sample with a 10-μm PVDF layer. This work shows great promise toward realizing a THz SPR sensor with high sensitivity for identifying the signatures of biological fluid sample.     

Using matrix summation method for three dimensional dose calculation in brachytherapy

AimThe purpose of this study is to calculate radiation dose around a brachytherapy source in a water phantom for different seed locations or rotation the sources by the matrix summation method.BackgroundMonte Carlo based codes like MCNP are widely used for performing radiation transport calculations and dose evaluation in brachytherapy. But for complicated situations, like using more than one source, moving or rotating the source, the routine Monte Carlo method for dose calculation needs a long time running.Materials and methodsThe MCNPX code has been used to calculate radiation dose around a ¹⁹²Ir brachytherapy source and saved in a 3D matrix. Then, we used this matrix to evaluate the absorbed dose in any point due to some sources or a source which shifted or rotated in some places by the matrix summation method.ResultsThree dimensional (3D) dose results and isodose curves were presented for ¹⁹²Ir source in a water cube phantom shifted for 10 steps and rotated for 45 and 90° based on the matrix summation method. Also, we applied this method for some arrays of sources.ConclusionThe matrix summation method can be used for 3D dose calculations for any brachytherapy source which has moved or rotated. This simple method is very fast compared to routine Monte Carlo based methods. In addition, it can be applied for dose optimization study.     

Low-energy electrons inside active DNA models: A tool to elucidate the radiation action mechanisms

To postulate radiation action mechanisms and to test them by Monte Carlo simulation, a complex computer model was developed consisting of major components for the generation of a radiation spectrum, biomolecular structures, and electron track structures in liquid water. As the radiation source¹²⁵I is employed here; it is an excellent test radiation due to its exactly localized position in the DNA molecule and high biological toxicity as a consequence of the emission of short-ranging Auger electrons. A linear DNA plasmid model (Pomplun 1991) which can actively respond to radical attack (Terrissol and Pomplun 1994) has been modified into a nucleosome model representing the double-helix of DNA with 146 basepairs and more than 9000 atoms surrounding the histones. The introduction of this new target structure allows a more realistic simulation of cellular conditions. Using the model's decay accumulation aspect, the situation of many break and survival experiments can be approximated and the influence of several cellular parameters tested. As a first step, a correlation between the size of energy depositions and strand-break patterns was sought.     

Dose-rate dependent stochastic effects in radiation cell-survival models

Summary When cells are subjected to ionizing radiation the specific energy rate (microscopic analog of dose-rate) varies from cell to cell. Within one cell, this rate fluctuates during the course of time; a crossing of a sensitive cellular site by a high energy charged particle produces many ionizations almost simultaneously, but during the interval between events no ionizations occur. In any cell-survival model one can incorporate the effect of such fluctuations without changing the basic biological assumptions. Using stochastic differential equations and Monte Carlo methods to take into account stochastic effects we calculated the dose-survival relationships in a number of current cell survival models. Some of the models assume quadratic misrepair; others assume saturable repair enzyme systems. It was found that a significant effect of random fluctuations is to decrease the theoretically predicted amount of dose-rate sparing. In the limit of low dose-rates neglecting the stochastic nature of specific energy rates often leads to qualitatively misleading results by overestimating the surviving fraction drastically. In the opposite limit of acute irradiation, analyzing the fluctuations in rates merely amounts to analyzing fluctuations in total specific energyvia the usual microdosimetric specific energy distribution function, and neglecting fluctuations usually underestimates the surviving fraction. The Monte Carlo methods interpolate systematically between the low dose-rate and high dose-rate limits. As in other approaches, the slope of the survival curve at low dose-rates is virtually independent of dose and equals the initial slope of the survival curve for acute radiation.     

单木生物量模型估计区域尺度生物量的不确定性

采用系统抽样体系江西省固定样地杉木连续观测数据和生物量数据,通过Monte Carlo法反复模拟由单木生物量模型推算区域尺度地上生物量的过程,估计了江西省杉木地上总生物量。基于不同水平建模样本量n及不同决定系数R~2的设计,分别研究了单木生物量模型参数变异性及模型残差变异性对区域尺度生物量估计不确定性的影响。研究结果表明:2009年江西省杉木地上生物量估计值为(19.84±1.27)t/hm~2,不确定性占生物量估计值约6.41%。生物量估计值和不确定性值达到平稳状态所需的运算时间随建模样本量及决定系数R~2的增大而减小;相对于模型参数变异性,残差变异性对不确定性的影响更小。     

Detection of dispersed short tandem repeats using reversible jump Markov chain Monte Carlo

Tandem repeats occur frequently in biological sequences. They are important for studying genome evolution and human disease. A number of methods have been designed to detect a single tandem repeat in a sliding window. In this article, we focus on the case that an unknown number of tandem repeat segments of the same pattern are dispersively distributed in a sequence. We construct a probabilistic generative model for the tandem repeats, where the sequence pattern is represented by a motif matrix. A Bayesian approach is adopted to compute this model. Markov chain Monte Carlo (MCMC) algorithms are used to explore the posterior distribution as an effort to infer both the motif matrix of tandem repeats and the location of repeat segments. Reversible jump Markov chain Monte Carlo (RJMCMC) algorithms are used to address the transdimensional model selection problem raised by the variable number of repeat segments. Experiments on both synthetic data and real data show that this new approach is powerful in detecting dispersed short tandem repeats. As far as we know, it is the first work to adopt RJMCMC algorithms in the detection of tandem repeats.     

The effect of the β-emitting yttrium-90 citrate on the dose–response of dicentric chromosomes in human lymphocytes: a basis for biological dosimetry after radiosynoviorthesis

The production of dicentric chromosomes in human lymphocytes by β-particles of yttrium-90 (Y-90) was studied in vitro to provide a basis of biological dosimetry after radiosynoviorthesis (RSO) of persistent synovitis by intra-articular administration of yttrium-90 citrate colloid. Since the injected colloid may leak into the lymphatic drainage exposing other parts of the body to radiation, the measurement of biological damage induced by β-particles of Y-90 is important for the assessment of radiation risk to the patients. A linear dose–response relationship (α = 0.0229 ± 0.0028 dicentric chromosomes per cell per gray) was found over the dose range of 0.2176–2.176 Gy. The absorbed doses were calculated for exposure of blood samples to Y-90 activities from 40 to 400 kBq using both Monte Carlo simulation and an analytical model. The maximum low-dose RBE, the RBE_M which is equivalent to the ratio of the α coefficients of the dose–response curves, is well in line with published results obtained earlier for irradiation of blood of the same donor with heavily filtered 220 kV X-rays (3.35 mm copper), but half of the RBE_M relative to weakly filtered 220 kV X-rays. Therefore, it can be concluded that for estimating an absorbed dose during RSO by the technique of biological dosimetry, in vitro and in vivo data for the same radiation quality are necessary.     

Analyzing indirect secondary electron contrast of unstained bacteriophage T4 based on SEM images and Monte Carlo simulations

The indirect secondary electron contrast (ISEC) condition of the scanning electron microscopy (SEM) produces high contrast detection with minimal damage of unstained biological samples mounted under a thin carbon film. The high contrast image is created by a secondary electron signal produced under the carbon film by a low acceleration voltage. Here, we show that ISEC condition is clearly able to detect unstained bacteriophage T4 under a thin carbon film (10-15 nm) by using high-resolution field emission (FE) SEM. The results show that FE-SEM provides higher resolution than thermionic emission SEM. Furthermore, we investigated the scattered electron area within the carbon film under ISEC conditions using Monte Carlo simulation. The simulations indicated that the image resolution difference is related to the scattering width in the carbon film and the electron beam spot size. Using ISEC conditions on unstained virus samples would produce low electronic damage, because the electron beam does not directly irradiate the sample. In addition to the routine analysis, this method can be utilized for structural analysis of various biological samples like viruses, bacteria, and protein complexes.     

Density guided importance sampling: application to a reduced model of protein folding

MOTIVATION: Monte Carlo methods are the most effective means of exploring the energy landscapes of protein folding. The rugged topography of folding energy landscapes causes sampling inefficiencies however, particularly at low, physiological temperatures. RESULTS: A hybrid Monte Carlo method, termed density guided importance sampling (DGIS), is presented that overcomes these sampling inefficiencies. The method is shown to be highly accurate and efficient in determining Boltzmann weighted structural metrics of a discrete off-lattice protein model. In comparison to the Metropolis Monte Carlo method, and the hybrid Monte Carlo methods, jump-walking, smart-walking and replica-exchange, the DGIS method is shown to be more efficient, requiring no parameter optimization. The method guides the simulation towards under-sampled regions of the energy spectrum and recognizes when equilibrium has been reached, avoiding arbitrary and excessively long simulation times. AVAILABILITY: Fortran code available from authors upon request. CONTACT: m.j.parker@leeds.ac.uk.     

A validation of SpekPy: A software toolkit for modelling X-ray tube spectra

PurposeTo validate the SpekPy software toolkit that has been developed to estimate the spectra emitted from tungsten anode X-ray tubes. The model underlying the toolkit introduces improvements upon a well-known semi-empirical model of X-ray emission.Materials and methodsUsing the same theoretical framework as the widely-used SpekCalc software, new electron penetration data was simulated using the Monte Carlo (MC) method, alternative bremsstrahlung cross-sections were applied, L-line characteristic emissions were included, and improvements to numerical methods implemented. The SpekPy toolkit was developed with the Python programming language. The toolkit was validated against other popular X-ray spectrum models (50 to 120 kVp), X-ray spectra estimated with MC (30 to 150 kVp) as well as reference half value layers (HVL) associated with numerous radiation qualities from standard laboratories (20 to 300 kVp).ResultsThe toolkit can be used to estimate X-ray spectra that agree with other popular X-ray spectrum models for typical configurations in diagnostic radiology as well as with MC spectra over a wider range of conditions. The improvements over SpekCalc are most evident at lower incident electron energies for lightly and moderately filtered radiation qualities. Using the toolkit, estimations of the HVL over a large range of standard radiation qualities closely match reference values.ConclusionsA toolkit to estimate X-ray spectra has been developed and extensively validated for central-axis spectra. This toolkit can provide those working in Medical Physics and beyond with a powerful and user-friendly way of estimating spectra from X-ray tubes.     

Track structures, DNA targets and radiation effects in the biophysical Monte Carlo simulation code PARTRAC

This review describes the PARTRAC suite of comprehensive Monte Carlo simulation tools for calculations of track structures of a variety of ionizing radiation qualities and their biological effects. A multi-scale target model characterizes essential structures of the whole genomic DNA within human fibroblasts and lymphocytes in atomic resolution. Calculation methods and essential results are recapitulated regarding the physical, physico-chemical and chemical stage of track structure development of radiation damage induction. Recent model extension towards DNA repair processes extends the time dimension by about 12 orders of magnitude and paves the way for superior predictions of radiation risks.     

Model for radial dependence of frequency distributions for energy imparted in nanometer volumes from HZE particles

This paper develops a deterministic model of frequency distributions for energy imparted (total energy deposition) in small volumes similar to DNA molecules from high-energy ions of interest for space radiation protection and cancer therapy. Frequency distributions for energy imparted are useful for considering radiation quality and for modeling biological damage produced by ionizing radiation. For high-energy ions, secondary electron (delta-ray) tracks originating from a primary ion track make dominant contributions to energy deposition events in small volumes. Our method uses the distribution of electrons produced about an ion's path and incorporates results from Monte Carlo simulation of electron tracks to predict frequency distributions for ions, including their dependence on radial distance. The contribution from primary ion events is treated using an impact parameter formalism of spatially restricted linear energy transfer (LET) and energy-transfer straggling. We validate our model by comparing it directly to results from Monte Carlo simulations for proton and alpha-particle tracks. We show for the first time frequency distributions of energy imparted in DNA structures by several high-energy ions such as cosmic-ray iron ions. Our comparison with results from Monte Carlo simulations at low energies indicates the accuracy of the method.     

Bayesian analysis of matrix normal graphical models

We present Bayesian analyses of matrix-variate normal data with conditional independencies induced by graphical model structuring of the characterizing covariance matrix parameters. This framework of matrix normal graphical models includes prior specifications, posterior computation using Markov chain Monte Carlo methods, evaluation of graphical model uncertainty and model structure search. Extensions to matrix-variate time series embed matrix normal graphs in dynamic models. Examples highlight questions of graphical model uncertainty, search and comparison in matrix data contexts. These models may be applied in a number of areas of multivariate analysis, time series and also spatial modelling.     

Generating Correlated Binary Variables with Complete Specification of the Joint Distribution

Most statistical methods for the analysis of correlated binary data are based on asymptotic theory. Therefore it is important to generate correlated binary data efficiently for Monte Carlo simulation studies to investigate the finite sample performance of these methods. This article provides a simple method for generating correlated binary data with a given joint distribution. The key idea is to consider k‐variate binary data as a multinomial distribution with 2^k possible outcomes.     

Biofilm model calibration and microbial diversity study using Monte Carlo simulations

Mathematical models are useful tools for studying and exploring biological conversion processes as well as microbial competition in biological treatment processes. A single‐species biofilm model was used to describe biofilm reactor operation at three different hydraulic retention times (HRT). The single‐species biofilm model was calibrated with sparse experimental data using the Monte Carlo filtering method. This calibrated single‐species biofilm model was then extended to a multi‐species model considering 10 different heterotrophic bacteria. The aim was to study microbial diversity in bulk phase biomass and biofilm, as well as the competition between suspended and attached biomass. At steady state and independently of the HRT, Monte Carlo simulations resulted only in one unique dominating bacterial species for suspended and attached biomass. The dominating bacterial species was determined by the highest specific substrate affinity (ratio of µ/K_S). At a short HRT of 20 min, the structure of the microbial community in the bulk liquid was determined by biomass detached from the biofilm. At a long HRT of 8 h, both biofilm detachment and microbial growth in the bulk liquid influenced the microbial community distribution. Biotechnol. Bioeng. 2013; 110: 1323–1332. © 2012 Wiley Periodicals, Inc.     

Development of PARMA: PHITS-based analytical radiation model in the atmosphere

Estimation of cosmic-ray spectra in the atmosphere has been essential for the evaluation of aviation doses. We therefore calculated these spectra by performing Monte Carlo simulation of cosmic-ray propagation in the atmosphere using the PHITS code. The accuracy of the simulation was well verified by experimental data taken under various conditions, even near sea level. Based on a comprehensive analysis of the simulation results, we proposed an analytical model for estimating the cosmic-ray spectra of neutrons, protons, helium ions, muons, electrons, positrons and photons applicable to any location in the atmosphere at altitudes below 20 km. Our model, named PARMA, enables us to calculate the cosmic radiation doses rapidly with a precision equivalent to that of the Monte Carlo simulation, which requires much more computational time. With these properties, PARMA is capable of improving the accuracy and efficiency of the cosmic-ray exposure dose estimations not only for aircrews but also for the public on the ground.