Using Monte Carlo experiments to select meta-analytic estimators

The purpose of this study is to show how Monte Carlo analysis of meta‐analytic estimators can be used to select estimators for specific research situations. Our analysis conducts 1620 individual experiments, where each experiment is defined by a unique combination of sample size, effect size, effect size heterogeneity, publication selection mechanism, and other research characteristics. We compare 11 estimators commonly used in medicine, psychology, and the social sciences. These are evaluated on the basis of bias, mean squared error (MSE), and coverage rates. For our experimental design, we reproduce simulation environments from four recent studies. We demonstrate that relative estimator performance differs across performance measures. Estimator performance is a complex interaction of performance indicator and aspects of the application. An estimator that may be especially good with respect to MSE may perform relatively poorly with respect to coverage rates. We also show that the size of the meta‐analyst's sample and effect heterogeneity are important determinants of relative estimator performance. We use these results to demonstrate how these observable characteristics can guide the meta‐analyst to choose the most appropriate estimator for their research circumstances.

Effect of pH on the Supramolecular Structure of Helicobacter pylori Urease by Molecular Dynamics Simulations

The effect of pH on the supramolecular structure of Helicobacter pylori urease was studied by means of molecular dynamics simulations at seven different pHs. Appropriate urease charge distributions were calculated using a semi-grand canonical Monte Carlo (SGCMC) procedure that assigns each residue’s charge state depending on the assigned individual pKa obtained by PROPKA. The effect of pH on protein stability has been analyzed through root-mean-square deviation (RMSD), radius of gyration (RG), solvent-accessible surface area (SASA), hydrogen bonds (HB) and salt bridges (SB). Urease catalyses the hydrolysis of urea in 12 active sites that are covered by mobile regions that act like flaps. The mobility of these flaps is increased at acidic pHs. However, extreme acidic conditions cause urease to have the least number of stabilizing interactions. This initiates the process of denaturalization, wherein the four (αβ)3 subunits of the global structure ((αβ)3)4 of urease start to separate.

Body-size-dependent Iodine-131Svalues

In a recent epidemiologic risk assessment on late health effects of patients treated with radioactive iodine (RAI), organ/tissue doses of the patients were estimated based on iodine-131Svalues derived from the reference computational phantoms of the International Commission on Radiological Protection (ICRP). However, the use of theSvalues based on the reference phantoms may lead to significant biases in the estimated doses of patients whose body sizes (height and weight) are significantly different from the reference body sizes. To fill this critical gap, we established a comprehensive dataset of body-size-dependent iodine-131Svalues (r_T← thyroid) for 30 radiosensitive target organs/tissues by performing Monte Carlo dose calculations coupled with a total of 212 adult male and female computational phantoms in different heights and weights. We observed that theSvalues tend to decrease with increasing body height; for example, theSvalue (gonads ← thyroid) of the 160 cm male phantom is about 3 times higher than that of the 190 cm male phantom at the 70 kg weight. We also observed that theSvalues tend to decrease with increasing body weight for some organs/tissues; for example, theSvalue (skin ← thyroid) of the 45 kg female phantom is about two times higher than that of the 130 kg female phantom at the 160 cm height. For other organs/tissues, which are relatively far from the thyroid, in contrast, theSvalues tend to increase with increasing body weight; for example, theSvalue (bladder ← thyroid) of the 45 kg female phantom is about 2 times lower than that of the 130 kg female phantom. Overall, the majority of the body-size-dependentSvalues deviated to within 25% from those of the reference phantoms. We believe that the use of body-size-dependentSvalues in dose reconstructions should help quantify the dosimetric uncertainty in epidemiologic investigations of RAI-treated patients.

EyeDose: An open-source tool for using published Monte Carlo results to estimate the radiation dose delivered to the tumor and critical ocular structures for 125I Collaborative Ocular Melanoma Study eye plaques

PURPOSE

Radiation side effects and visual outcome for uveal melanoma patients managed with plaque radiotherapy are dependent on the radiation dose administered to the tumor and nearby healthy tissues. We have developed an open-source software tool, EyeDose, to simplify and standardize tumor and critical structure dose reporting for Collaborative Ocular Melanoma Study eye plaques.

METHODS AND MATERIALS

EyeDose is a MATLAB-based program that calculates point dose and volume dose metrics for standard models of the tumor and critical ocular structures. It uses published three-dimensional dose distributions for eye plaques, calculated with Monte Carlo methods, which are oriented with respect to the eye using the tumor's position on a fundus diagram. A standard model for the ocular structures was created using published measurements and patient CT scans. EyeDose reports radiation statistics for the fovea, optic disc, lens, lacrimal gland, retina, and tumor. The dosimetric margin for implant placement uncertainty is also calculated.

RESULTS

EyeDose calculations were validated against previously published Monte Carlo results for eight different tumor positions, including the dose to the fovea, optic disc, lacrimal gland, lens, and along the central axis. EyeDose accepts a spreadsheet input for rapidly processing large retrospective patient data sets, with an average run time of <40 s per patient. EyeDose is published as an open-source tool for easy adaptation at different institutions.

CONCLUSIONS

EyeDose calculates radiation statistics for Collaborative Ocular Melanoma Study eye plaque patients with Monte Carlo accuracy and without a treatment planning system. EyeDose streamlines data collection for large retrospective studies and can also be used prospectively to assess plaque applicability.

Development of a Predictive Monte Carlo Radiative Transfer Model for Ablative Fractional Skin Lasers

It is possible to enhance topical drug delivery by pretreatment of the skin with ablative fractional lasers (AFLs). However, the parameters to use for a given AFL to achieve the desired depth of ablation or the desired therapeutic or cosmetic outcome are hard to predict. This leaves open the real possibility of overapplication or underapplication of laser energy to the skin. In this study, we developed a numerical model consisting of a Monte Carlo radiative transfer (MCRT) code coupled to a heat transfer and tissue damage algorithm. The simulation is designed to predict the depth effects of AFL on the skin, verified with in vitro experiments in porcine skin via optical coherence tomography (OCT) imaging. Ex vivo porcine skin is irradiated with increasing energies (50-400 mJ/pixel) from a CO₂ AFL. The depth of microscopic treatment zones is measured and compared with our numerical model. The data from the OCT images and MCRT model complement each other well. Nonablative thermal effects on surrounding tissue are also discussed. This model, therefore, provides an initial step toward a predictive determination of the effects of AFL on the skin. Lasers Surg. Med. © 2020 The Authors. Lasers in Surgery and Medicine published by Wiley Periodicals LLC.

Oxygen depletion in FLASH ultra-high-dose-rate radiotherapy: A molecular dynamics simulation

PURPOSE

We present a first-principles molecular dynamics (MD) simulation and expound upon a mechanism of oxygen depletion hypothesis to explain the mitigation of normal tissue injury observed in ultra-high-dose-rate (UHDR) FLASH radiotherapy.

METHODS

We simulated damage to a segment of DNA (also representing other biomolecules such as RNA and proteins) in a simulation box filled with H 2 O and O 2 molecules. Attoseconds physical interactions (ionizations, electronic, and vibrational excitations) were simulated by using the Monte Carlo track structure code Geant4-DNA. Immediately after ionization, ab initio Car-Parrinello molecular dynamics (CPMD) simulation was used to identify which H 2 O and O 2 molecules surrounding the DNA molecule were converted into reactive oxygen species (ROS). Subsequently, the femto- to nanosecond reactions of ROS were simulated by using MD with reactive force field (ReaxFF), to illustrate ROS merging into new types of non-reactive oxygen species (NROS) due to strong coupling among ROS. A coarse-grained model was constructed to describe the relevant collective phenomenon at the macroscopic level on ROS aggregation and formation of NROS agglomerates consistent with the underlying microscopic pathways obtained from MD simulations.

RESULTS

Time-dependent molecular simulations revealed the formation of metastable and transient spaghetti-like complexes among ROS generated at UHDR. At the higher ROS densities produced under UHDR, stranded chains (i.e., NROS) are produced, mediated through attractive electric polarity forces, hydrogen bonds, and magnetic dipole-dipole interactions among hydroxyl ( . OH ) radicals. NROS tend to be less mobile than cellular biomolecules as opposed to the isolated and sparsely dense ROS generated at conventional dose rates (CDR). We attribute this effect to the suppression of biomolecular damage induced per particle track. At a given oxygen level, as the dose rate increases, the size and number of NROS chains increase, and correspondingly the population of toxic ROS components decreases. Similarly, at a given high dose rate, as the oxygen level increases, so do the size and number of NROS chains until an optimum level of oxygen is reached. Beyond that level, the amount of oxygen present may be sufficient to saturate the production of NROS chains, thereby reversing the sparing effects of UHDRs.

CONCLUSIONS

We showed that oxygen depletion, hypothesized to lead to lower normal-tissue toxicity at FLASH dose rates, takes place within femto- to nanoseconds after irradiation. The mechanism is governed by the slow dynamics of chains of ROS complexes (NROS). Under physoxic (≈ 4-5% oxygen) conditions (i.e., in normal tissues), NROS are more abundant than in hypoxic conditions (e.g., <0.3% in parts of tumors), suggesting that biomolecular damage would be reduced in an environment with physoxic oxygen levels. Hence irradiation at UHDRs would be more effective for sparing physoxic normal tissues but not tumors containing regions of hypoxia. At much higher levels of oxygen (e.g., >10-15%), oxygen depletion by UHDRs may not be sufficient for tissue sparing.

Modeling the Device Behavior of Biological and Synthetic Nanopores with Reduced Models

Biological ion channels and synthetic nanopores are responsible for passive transport of ions through a membrane between two compartments. Modeling these ionic currents is especially amenable to reduced models because the device functions of these pores, the relation of input parameters (e.g., applied voltage, bath concentrations) and output parameters (e.g., current, rectification, selectivity), are well defined. Reduced models focus on the physics that produces the device functions (i.e., the physics of how inputs become outputs) rather than the atomic/molecular-scale physics inside the pore. Here, we propose four rules of thumb for constructing good reduced models of ion channels and nanopores. They are about (1) the importance of the axial concentration profiles, (2) the importance of the pore charges, (3) choosing the right explicit degrees of freedom, and (4) creating the proper response functions. We provide examples for how each rule of thumb helps in creating a reduced model of device behavior.

Using Monte Carlo methods for Hp(0.07) values assessment during the handling of 18F-FDG

The dose limit for the skin of the hand is typically converted to a surface of 1 cm², which means that one needs to measure point doses in different places on the hand. However, the commonly used method of measuring doses on the hand, i.e., using a dosimetric ring including one or several thermoluminescent detectors worn at the base of a finger, is not adequate for manual procedures such as labeling or radiopharmaceutical injection. Consequently, the purpose of this study was to create and conduct a series of computer simulations that, by recreating the actual working conditions, would provide information on the values of ionizing radiation doses received by the most exposed parts of the hands of employees of radiopharmaceutical production facilities, as well as those of nurses during the injection of radiopharmaceuticals. The simulations were carried out using Monte Carlo radiation transport calculations. The H_p(0.07) personal dose equivalent values obtained for the fingertips of the index and middle fingers of nursing staff and chemists were within the range limited by the minimum and maximum H_p(0.07) values obtained as a result of dosimetric measurements carried out in diagnostic and production centers. Only in the case of the nurse's fingertip, the simulated value of H_p(0.07 slightly exceeded the measured maximum H_p(0.07) value. The comparison of measured and simulated dose values showed that the largest differences in H_p(0.07) values occurred at the thumb tip, and for ring finger and middle finger of some of the nurses investigated.

Risk assessment of phthalates based on aggregated exposure from foods and personal care products and comparison with biomonitoring data

Phthalates are a group of diesters of phthalic acid and have been widely used by the industry as plasticisers giving flexibility and durability to polyvinyl chloride (PVC) plastics. Commonly their uses vary from plasticisers in food contact materials and toys to emulsifying agents in personal care products. Phthalates are not covalently bound to PVC, thus they can migrate into the air, skin, water, food and the environment. The omnipresence of phthalates results in human exposure via multiple pathways such as dermal, oral and inhalation for prolonged periods. There is evidence that phthalates can induce disruption in oestrogenic activity, reproductive, developmental and liver toxicity both in experimental animals and potentially in humans. The aim of this technical report is to summarise the activities of the fellow performed at the Norwegian Institute of Public Health (NIPH). The goals of the work programme were collecting concentration levels on five specific phthalates from the scientific literature and combining them with consumption/use data reported in a biomonitoring study part of a Horizon 2020 project (EuroMix), and finally, estimate the aggregate phthalate exposure from food and personal care products and compare them with the measured phthalate levels in urine samples collected in the biomonitoring study.

Recommended dose voxel size and statistical uncertainty parameters for precision of Monte Carlo dose calculation in stereotactic radiotherapy

Monte Carlo (MC)‐based treatment planning requires a choice of dose voxel size (DVS) and statistical uncertainty (SU). These parameters effect both the precision of displayed dose distribution and time taken to complete a calculation. For efficient, accurate, and precise treatment planning in a clinical setting, optimal values should be selected. In this investigation, 30 volumetric modulated arc therapy (VMAT) stereotactic radiotherapy (SRT) treatment plans, 10 brain, 10 lung, and 10 spine were calculated in the Monaco 5.11.02 treatment planning system (TPS). Each plan was calculated with a DVS of 0.1 and 0.2 cm using SU values of 0.50%, 0.75%, 1.00%, 1.50%, and 2.00%, along with a ground truth calculation using a DVS of 0.1 cm and SU of 0.15%. The variance at each relative dose level was calculated for all SU settings to assess their relationship. The variation from the ground truth calculation for each DVS and SU combination was determined for a range of DVH metrics and plan quality indices along with the time taken to complete the calculations. Finally, the effect of defining the maximum dose using a volume of 0.035 cc was compared to 0.100 cc when considering DVS and SU settings. Changes in the DVS produced greater variations from the ground truth calculation than changes in SU across the values tested. Plan quality metrics and mean dose values showed less sensitivity to changes in SU than DVH metrics. From this study, it was concluded that while maintaining an average calculation time of <10 min, 75% of plans could be calculated with variations of <2.0% from their ground truth values when using an SU setting of 1.50% and a DVS of 0.1 cm in the case of brain or spine plans, and a 0.2 cm DVS in the case of lung plans.

Monte Carlo Computation of Dose-Volume Histograms in Structures at Risk of an Eye Irradiated with Heterogeneous Ruthenium-106 Plaques

Background/Aims

The aim of this work is to compare Monte Carlo simulated absorbed dose distributions obtained from ¹⁰⁶Ru eye plaques, whose heterogeneous emitter distribution is known, with the common homogeneous approximation. The effect of these heterogeneities on segmented structures at risk is analyzed using an anthropomorphic phantom.

Methods

The generic CCA and CCB, with a homogeneous emitter map, and the specific CCA1364 and CCB1256 ¹⁰⁶Ru eye plaques are modeled with the Monte Carlo code PENELOPE. To compare the effect of the heterogeneities in the segmented volumes, cumulative dose-volume histograms are calculated for different rotations of the aforementioned plaques.

Results

For the cornea, the CCA with the equatorial placement yields the lowest absorbed dose rate while for the CCA1364 in the same placement the absorbed dose rate is 33% higher. The CCB1256 with the hot spot oriented towards the cornea yields the maximum dose rate per unit of activity while it is 44% lower for the CCB.

Conclusions

Dose calculations based on a homogeneous distribution of the emitter substance yield the lowest absorbed dose in the analyzed structures for all plaque placements. Treatment planning based on such calculations may result in an overdose of the structures at risk.

Pharmacokinetics of doxycycline after oral administration of multiple doses in dogs

The aim of this study was to determine the pharmacokinetic parameters of doxycycline in dogs and assess the efficacy of an oral drug dosage regimen of 10 mg/kg daily for 28 days through Pharmacokinetic/Pharmacodynamic (PK/PD) target analysis based on Monte Carlo simulation, using previously published data for the zoonotic pathogen Staphylococcus pseudintermedius. After a multiple-dosage regimen, the accumulation index was 1.88 ± 0.82. The Cmax_ss and Cmin_ss values were 5.18 ± 1.81 µg/ml and 1.91 ± 1.35 µg/ml, respectively. There were statistically significant differences for Cmax, Cmin at 24 hr, MRTt, AUCt and AUC∞ between days 1 and 28. The Cmin_ss value was over the MIC of the principal pathogens, and Cmax_ss was higher than the resistance values (>2 μg/ml). For AUC/MIC indices of 12, 25 and 40, the cumulative fraction responses (CFR) were 94.01%, 69.55% and 60.86%, respectively; for an MIC value of 2 µg/ml, the corresponding probability of target attainment (PTA) was 99.94%, 84.78% and 45.16%, respectively. Doxycycline was used against numerous localized infections in different organs and tissues. For the strains with MIC < 1 μg/mL, PTA was close to 100%, even for the most demanding ones, specifically 94.98% for an index of 40% and 99.9% for an index of 25.

A novel and fast methodology to calculate doses in LDR brachytherapy

We present the concept of a new methodology for faster simulation of the doses in brachytherapy with permanent implants, based on the knowledge of the seeds arrangement, adding previously simulated doses in an equivalent medium in terms of the atomic composition of the organ in question. To perform the doses calculations we use Monte Carlo simulations. We simulated a cylindrical I-125 seed and compared our results against published data. Our proposal is to have the doses simulated previously in different arrangement of seed-absorbents, and then, considering the spacial positions of the seeds after the implants, these doses can be directly added, obtaining a very fast computation of the total dose. Two phantoms of prostates with permanent implant seeds in 2D and 3D arrangements were simulated. The results of the proposed methodology were compared with two complete Monte Carlo simulations in 2D and 3D designs. Differences in doses were analysed, obtaining statistical discrepancies of less than 1% and reducing the simulation time by more than 4 orders of magnitude. With the proposed methodology, it is possible to perform rapid dose calculations in brachytherapy, using laptop or desktop computers.

Performance analysis method for model-based irrigation strategies under uncertainty

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A Richards equation-based soil water model was combined with an evapotranspiration model to compute drainage and crop water stress resulting from irrigation within a MATLAB programming environment.

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Monte Carlo sampling was used to simulate how uncertainty in soil parameters and evapotranspiration propagates into predictions of drainage, water use and crop water stress.

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Soil water pressure head was used as a threshold value to indicate crop water stress based on soil profile interactions with the crop root zone.

There is a necessity to increase the performance of food production in agriculture, this means, that precise management support in farming systems is required to reduce water use and drainage while avoiding crop stress. Management support based on model predictions is used to increase the performance of food production. However, sources of uncertainty affect the model predictions. Uncertainty in soil properties and uncertain evapotranspiration translate into uncertain predictions, and consequently in risk of performance loss. This paper presents the code and method to analyze performance uncertainty (and risk of performance loss) due to uncertain circumstances. The method is based on using the De Graaf evapotranspiration model and the EMMAN3G model, a Richards equation-based soil water model, as modules to conduct a performance uncertainty study.

Enhanced optimization of volumetric modulated arc therapy plans using Monte Carlo generated beamlets

PURPOSE

A treatment planning system (TPS) produces volumetric modulated arc therapy (VMAT) plans by applying an optimization process to an objective function, followed by an accurate calculation of the final, deliverable dose. However, during the optimization step, a rapid dose calculation algorithm is required, which reduces its accuracy and its representation of the objective function space. Monte Carlo (MC) routines, considered the gold standard in accuracy, are currently too slow for practical comprehensive VMAT optimization. Therefore, we propose a novel approach called enhanced optimization (EO), which employs the TPS VMAT plan as a starting point, and applies small perturbations to nudge the solution closer to a true objective minimum. The perturbations consist of beamlet dose matrices, calculated using MC routines on a distributed-computing framework.

METHODS

DICOM files for clinical VMAT plans files are exported from the TPS and used to generate input files for the EGSnrc MC toolkit. Beamlet doses are calculated using the MC routines, each corresponding to a single multileaf collimator leaf from a single control point traveling 0.5 cm in or out of the field. A typical VMAT plan requires 5000 to 10 000 beamlets, which may be calculated overnight. This results in a ternary-valued objective function, which may use the same clinical objectives as the original VMAT plan. A simple greedy search algorithm is applied to minimize this function and determine the optimal set of ternary variables. The resulting modified control point parameters are imported into the TPS to calculate the final, deliverable dose, and to compare the EO plan with the original. EO was evaluated retrospectively on seven VMAT plans (two adult brain, one pediatric brain, two head and neck, and two prostate). Additionally, the use of stricter objectives was investigated for two of the cases: the left cochlea planning organ at risk (OAR) volume objective for the pediatric brain case, and the rectum objective for a prostate case.

RESULTS

EO produced improved objective scores (by 6% to 60%) and dose-volume histograms (DVH) for the brain plans and the head and neck plans. For each of these plans, the target dose minimum and homogeneity were preserved, while one or more of the OAR DVH's was reduced. Although EO also reduced the objective scores for the prostate plans (by 46% and 79%), their absolute score and DVH improvements were not substantial. The stricter objective on the pediatric brain case resulted in lower dose to the OAR without compromising the target dose. However, the rectum dose in the prostate case could not be improved without reducing dose homogeneity to the planning target volume, suggesting that VMAT prostate cases may already be highly optimized by the TPS.

CONCLUSION

We have developed a novel approach to improving the dose distribution of VMAT plans, which relies on MC calculations to provide small modifications to the control points. This method may be particularly useful for complex treatments in which a certain OAR is of concern and it is difficult for the treatment planner to obtain an acceptable solution with the TPS. Further development will reduce the beamlet computation time and result in more sophisticated EO treatment planning methods.

Production of the next-generation positron nuclide zirconium-89 (89 Zr) guided by Monte Carlo simulation and its good quality for antibody labeling

The next-generation positron zirconium-89 (⁸⁹ Zr, T_1/2 = 3.27 days) is a novel nuclide for immunological positron emission tomography because of its favorite longer half-life. The aim of this work is to develop optimized methods for routine production and purification of ⁸⁹ Zr through Monte Carlo (MC) simulation and laboratory experiments. ⁸⁹ Y(p,n)⁸⁹ Zr reaction was used for ⁸⁹ Zr production. Optimized thicknesses of Al degrader (0.11 cm) and ⁸⁹ Y foil (0.064 cm) were simulated through MC method. ⁸⁹ Zr (15.0-40.7 mCi) with an average production rate of 0.92 ± 0.12 mCi/μA·h was produced after 1- to 2-h bombardment at the proton beam energy of 20 MeV and current of 20 μA. High radio-purity ⁸⁹ Zr (6.14-26.8 mCi) obtained eluted from hydroxamate resin using 1-mol/L oxalic acid solution, with the concentration of 2.7 × 10⁴ mCi/L. The gamma spectrum showed that the characteristic peak of ⁸⁹ Zr was 511 and 909 keV, and no impurities were found. [⁸⁹ Zr]Zr-DFO-trastuzumab was successfully labeled and performed good radiochemical purity (>95%) and stability that showed potential application in tumor molecular imaging.

Comparison of actual and simulated tumoricidal effects induced by photodynamic therapy

OBJECTIVES

Numerous studies employ mathematical methods, such as Monte Carlo simulation, to predict the tumor killing effects of photodynamic therapy (PDT) by simulating optical propagation, photosensitizer distribution, and oxygen distribution. Whether these models faithfully reflect tumor killing is unknown, and model validation using tumor cross sections in these studies is usually insufficient to answer this question. To fill this gap in our knowledge, we employed a mouse model of breast cancer to determine the spatiotemporal effects of PDT using direct histopathological and biochemical analyses of whole tumors.

METHODS

We prepared approximately 700 5-μm-thick serial sections of breast tumors of syngeneic mice treated with PDT employing the photosensitizer photocarcinorin (PsD-007, a second-generation photosensitizer developed in China). Three adjoining sections were subjected to hematoxylin and eosin staining to assess necrosis, the TUNEL assay to evaluate apoptosis, and CD31 staining to detect angiogenesis, respectively. We then generated a three-dimensional (3D) reconstruction of the tumor to evaluate these processes. We simultaneously used the Monte Carlo method to develop a model of light distribution throughout the tumor to evaluate the actual and simulated tumor killing effects induced by PDT.

RESULTS

Tumor necrosis decreased exponentially as a function of distance from the source of illumination, while the distributions of apoptosis and neovascularization were independent of light distribution. Most apoptosis occurred in the lower layers (3000-4000 μm) of the tumor where the light intensity was too low to excite the photosensitizer. Neovascularization occurred at depths ranging from 2500 to 3500 μm. These analyses provided a 3D view of how a tumor is destroyed using PDT.

CONCLUSIONS

Although the optical distribution model predicted tumor necrosis caused by PDT, it was ineffective in predicting the sites of apoptosis and vascular destruction. Mathematical modeling is limited in its capabilities required to gain a comprehensive understanding of the spatiotemporal events associated with PDT. The mouse model developed here will serve as a platform for detailed direct histopathological, biochemical, and molecular genetic analyses of the effects of PDT, which will facilitate the development of optimized treatment strategies.

A Monte Carlo method for in silico modeling and visualization of Waddington's epigenetic landscape with intermediate details

Waddington's epigenetic landscape is a classic metaphor for describing the cellular dynamics during the development modulated by gene regulation. Quantifying Waddington's epigenetic landscape by mathematical modeling would be useful for understanding the mechanisms of cell fate determination. A few computational methods have been proposed for quantitative modeling of landscape; however, to model and visualize the landscape of a high dimensional gene regulatory system with realistic details is still challenging. Here, we propose a Monte Carlo method for modeling the Waddington's epigenetic landscape of a gene regulatory network (GRN). The method estimates the probability distribution of cellular states by collecting a large number of time-course simulations with random initial conditions. By projecting all the trajectories into a 2-dimensional plane of dimensions i and j, we can approximately calculate the quasi-potential U(x_i,x_j,∗)=-ln P(x_i,x_j,∗), where P(x_i,x_j,∗) is the estimated probability of an equilibrium steady state or a non-equilibrium state. Compared to the state-of-the-art methods, our Monte Carlo method can quantify the global potential landscape (or emergence behavior) of GRN for a high dimensional system. The potential landscapes show that not only attractors represent stability, but the paths between attractors are also part of the stability or robustness of biological systems. We demonstrate the novelty and reliability of our method by plotting the potential landscapes of a few published models of GRN.

Independent reaction times method in Geant4-DNA: Implementation and performance

PURPOSE

The simulation of individual particle tracks and the chemical stage following water radiolysis in biological tissue is an effective means of improving our knowledge of the physico-chemical contribution to the biological effect of ionizing radiation. However, the step-by-step simulation of the reaction kinetics of radiolytic species is the most time-consuming task in Monte Carlo track-structure simulations, with long simulation times that are an impediment to research. In this work, we present the implementation of the independent reaction times (IRT) method in Geant4-DNA Monte Carlo toolkit to improve the computational efficiency of calculating G-values, defined as the number of chemical species created or lost per 100 eV of deposited energy.

METHODS

The computational efficiency of IRT, as implemented, is compared to that from available Geant4-DNA step-by-step simulations for electrons, protons and alpha particles covering a wide range of linear energy transfer (LET). The accuracy of both methods is verified using published measured data from fast electron irradiations for ^• OH and e aq - for time-dependent G-values. For IRT, simulations in the presence of scavengers irradiated by cobalt-60 γ-ray and 2 MeV protons are compared with measured data for different scavenging capacities. In addition, a qualitative assessment comparing measured LET-dependent G-values with Geant4-DNA calculations in pure liquid water is presented.

RESULTS

The IRT improved the computational efficiency by three orders of magnitude relative to the step-by-step method while differences in G-values by 3.9% at 1 μs were found. At 7 ps, ^• OH and e aq - yields calculated with IRT differed from recent published measured data by 5% ± 4% and 2% ± 4%, respectively. At 1 μs, differences were 9% ± 5% and 6% ± 7% for ^• OH and e aq - , respectively. Uncertainties are one standard deviation. Finally, G-values at different scavenging capacities and LET-dependent G-values reproduced the behavior of measurements for all radiation qualities.

CONCLUSION

The comprehensive validation of the Geant4-DNA capabilities to accurately simulate the chemistry following water radiolysis is an ongoing work. The implementation presented in this work is a necessary step to facilitate performing such a task.

Automated Searching and Identification of Self-Organized Nanostructures

Currently, researchers spend significant time manually searching through large volumes of data produced during scanning probe imaging to identify specific patterns and motifs formed via self-assembly and self-organization. Here, we use a combination of Monte Carlo simulations, general statistics, and machine learning to automatically distinguish several spatially correlated patterns in a mixed, highly varied data set of real AFM images of self-organized nanoparticles. We do this regardless of feature-scale and without the need for manually labeled training data. Provided that the structures of interest can be simulated, the strategy and protocols we describe can be easily adapted to other self-organized systems and data sets.

Monte Carlo calculations of radiotherapy dose in "homogeneous" anatomy

Given the substantial literature on the use of Monte Carlo (MC) simulations to verify treatment planning system (TPS) calculations of radiotherapy dose in heterogeneous regions, such as head and neck and lung, this study investigated the potential value of running MC simulations of radiotherapy treatments of nominally homogeneous pelvic anatomy. A pre-existing in-house MC job submission and analysis system, built around BEAMnrc and DOSXYZnrc, was used to evaluate the dosimetric accuracy of a sample of 12 pelvic volumetric arc therapy (VMAT) treatments, planned using the Varian Eclipse TPS, where dose was calculated with both the Analytical Anisotropic Algorithm (AAA) and the Acuros (AXB) algorithm. In-house TADA (Treatment And Dose Assessor) software was used to evaluate treatment plan complexity, in terms of the small aperture score (SAS), modulation index (MI) and a novel exposed leaf score (ELS/ELA). Results showed that the TPS generally achieved closer agreement with the MC dose distribution when treatments were planned for smaller (single-organ) targets rather than larger targets that included nodes or metastases. Analysis of these MC results with reference to the complexity metrics indicated that while AXB was useful for reducing dosimetric uncertainties associated with density heterogeneity, the residual TPS dose calculation uncertainties resulted from treatment plan complexity and TPS model simplicity. The results of this study demonstrate the value of using MC methods to recalculate and check the dose calculations provided by commercial radiotherapy TPSs, even when the treated anatomy is assumed to be comparatively homogeneous, such as in the pelvic region.

Structural fluctuations and mechanical stabilities of the metamorphic protein RfaH

RfaH is a compact two-domain bacterial transcription factor that functions both as a regulator of transcription and an enhancer of translation. Underpinning the dual functional roles of RfaH is a partial but dramatic fold switch, which completely transforms the ~50-amino acid C-terminal domain (CTD) from an all-α state to an all-β state. The fold switch of the CTD occurs when RfaH binds to RNA polymerase (RNAP), however, the details of how this structural transformation is triggered is not well understood. Here we use all-atom Monte Carlo simulations to characterize structural fluctuations and mechanical stability properties of the full-length RfaH and the CTD as an isolated fragment. In agreement with experiments, we find that interdomain contacts are crucial for maintaining a stable, all-α CTD in free RfaH. To probe mechanical properties, we use pulling simulations to measure the work required to inflict local deformations at different positions along the chain. The resulting mechanical stability profile reveals that free RfaH can be divided into a "rigid" part and a "soft" part, with a boundary that nearly coincides with the boundary between the two domains. We discuss the potential role of this feature for how fold switching may be triggered by interaction with RNAP.

A Parametric Study of the Effects of Critical Design Parameters on the Performance of Nanoscale Silicon Devices

The current electronics industry has used the aggressive miniaturization of solid-state devices to meet future technological demands. The downscaling of characteristic device dimensions into the sub-10 nm regime causes them to fall below the electron-phonon scattering length, thereby resulting in a transition from quasi-ballistic to ballistic carrier transport. In this study, a well-established Monte Carlo model is employed to systematically investigate the effects of various parameters such as applied voltage, channel length, electrode lengths, electrode doping and initial temperature on the performance of nanoscale silicon devices. Interestingly, from the obtained results, the short channel devices are found to exhibit smaller heat generation, with a 2 nm channel device having roughly two-thirds the heat generation rate observed in an 8 nm channel device, which is attributed to reduced carrier scattering in the ballistic transport regime. Furthermore, the drain contacts of the devices are identified as critical design areas to ensure safe and efficient performance. The heat generation rate is observed to increase linearly with an increase in the applied electric field strength but does not change significantly with an increase in the initial temperature, despite a marked reduction in the electric current flowing through the device.

A detailed model and Monte Carlo simulation for predicting DIP genome length distribution in baculovirus infection of insect cells

Baculoviruses have enormous potential for use as biopesticides to control insect pest populations without the adverse environmental effects posed by the widespread use of chemical pesticides. However, continuous baculovirus production is susceptible to DNA mutation and the subsequent production of defective interfering particles (DIPs). The amount of DIPs produced and their genome length distribution are of great interest not only for baculoviruses but for many other DNA and RNA viruses. In this study, we elucidate this aspect of virus replication using baculovirus as an example system and both experimental and modeling studies. The existing mathematical models for the virus replication process consider DIPs as a lumped quantity and do not consider the genome length distribution of the DIPs. In this study, a detailed population balance model for the cell-virus culture is presented, which predicts the genome length distribution of the DIP population along with their relative proportion. The model is simulated using the kinetic Monte Carlo algorithm, and the results agree well with the experimental results. Using this model, a practical strategy to maintain the DIP fraction to near to its maximum and minimum limits has been demonstrated.

Ratios of internal doses deposited in different organs to the whole body when such organ is adopted as source of 18F-fluorodeoxyglucose, a Monte Carlo Geant4 study on a male medical internal radiation dose phantom

In the present study, the last stable version of Monte Carlo Geant4 code known as Geant4.10.3 has been used for measuring internal dose ratios to the whole body for about 40 organs. This, by performing a Monte Carlo model of 18F-fluorodeoxyglucose (18F-FDG) inside different organs of medical internal radiation dose male phantom, mimics a human male adult of 70 kg. A dedicated Geant4 user code has been developed in the top of one offered by Geant4 Monte Carlo toolkit and so-called human phantom. Several Monte Carlo simulations have been carried out, and in each of them, we have taken up such organ as source of 18F-FDG with a small amount of radioactivity, evenly distributed across its volume, and we measure ratios of absorbed doses deposited in organs to the whole body. The results have shown that there are radiation dose contributions from surrounding organs and their gravities are so variable; some organs have near-local character; thus, almost all radiations are locally deposited, which generally do not affect surrounding ones mainly including adrenals, thyroid, clavicles, thymus, testes, bladder, pancreas, scapula and upper spine; whereas, it is not the case for many other organs in which radiation doses are deposited outside of their parent volumes. In addition, absorbed doses in some organs that have high-tissue weighting factors, namely colon, lungs, stomach, bladder, thyroid, and liver are seriously affected by radioactivity of surrounding muscle organs, the gravity of such affectation is mainly growth when a patient is identified as having hyperglycemia or undergoing a hard physical activity.