Molecular toxicity of nitrobenzene derivatives to tetrahymena pyriformis based on SMILES descriptors using Monte Carlo, docking, and MD simulations

It is challenging to model the toxicity of nitroaromatic compounds due to limited experimental data. Nitrobenzene derivatives are commonly used in industry and can lead to environmental contamination. Extensive research, including several QSPR studies, has been conducted to understand their toxicity. Predictive QSPR models can help improve chemical safety, but their limitations must be considered, and the molecular factors affecting toxicity should be carefully investigated. The latest QSPR methods, molecular modeling techniques, machine learning algorithms, and computational chemistry tools are essential for developing accurate and robust models. In this work, we used these methods to study a series of fifty compounds derived from nitrobenzene. The Monte Carlo approach was used for QSPR modeling by applying the SMILES molecular structure representation and optimal molecular descriptors. The correlation ideality index (CII) and correlation contradiction index (CCI) were further introduced as validation parameters to estimate the developed models' predictive ability. The statistical quality of the CII models was better than those without CII. The best QSPR model with the following statistical parameters (Split-3): (R2 = 0.968, CCC = 0.984, IIC = 0.861, CII = 0.979, Q2 = 0.954, QF12 = 0.946, QF22 = 0.938, QF32 = 0.947, Rm2 = 0.878, RMSE = 0.187, MAE = 0.151, FTraining = 390, FInvisible = 218, FCalibration = 240, RTest2 = 0.905) was selected to generate the studied promoters with increasing and decreasing activity.

Reduction of Magnetic Interaction Due to Clustering in Doped Transition-Metal Dichalcogenides: A Case Study of Mn-, V-, and Fe-Doped WSe2

Using Hubbard-U-corrected density functional theory calculations, lattice Monte Carlo simulations, and spin Monte Carlo simulations, we investigate the impact of dopant clustering on the magnetic properties of WSe2 doped with period four transition metals. We use manganese (Mn) and iron (Fe) as candidate n-type dopants and vanadium (V) as the candidate p-type dopant, substituting the tungsten (W) atom in WSe2. Specifically, we determine the strength of the exchange interaction in Fe-, Mn-, and V-doped WSe2 in the presence of clustering. We show that the clusters of dopants are energetically more stable than discretely doped systems. Further, we show that in the presence of dopant clustering, the magnetic exchange interaction significantly reduces because the magnetic order in clustered WSe2 becomes more itinerant. Finally, we show that the clustering of the dopant atoms has a detrimental effect on the magnetic interaction, and to obtain an optimal Curie temperature, it is important to control the distribution of the dopant atoms.

Spectrally refined unbiased Monte Carlo estimate of the Earth's global radiative cooling

The Earth's radiative cooling is a key driver of climate. Determining how it is affected by greenhouse gas concentration is a core question in climate-change sciences. Due to the complexity of radiative transfer processes, current practices to estimate this cooling require the development and use of a suite of radiative transfer models whose accuracy diminishes as we move from local, instantaneous estimates to global estimates over the whole globe and over long periods of time (decades). Here, we show that recent advances in nonlinear Monte Carlo methods allow a paradigm shift: a completely unbiased estimate of the Earth's infrared cooling to space can be produced using a single model, integrating the most refined spectroscopic models of molecular gas energy transitions over a global scale and over years, all at a very low computational cost (a few seconds).

Monte Carlo simulation of the Varian TrueBeam flattened-filtered beams using a surrogate geometry in PRIMO

BACKGROUND

Monte Carlo simulation of radiation transport for medical linear accelerators (linacs) requires accurate knowledge of the geometrical description of the linac head. Since the geometry of Varian TrueBeam machines has not been disclosed, the manufacturer distributes phase-space files of the linac patient-independent part to allow researchers to compute absorbed dose distributions using the Monte Carlo method. This approach limits the possibility of achieving an arbitrarily small statistical uncertainty. This work investigates the use of the geometry of the Varian Clinac 2100, which is included in the Monte Carlo system PRIMO, as a surrogate.

METHODS

Energy, radial and angular distributions extracted from the TrueBeam phase space files published by the manufacturer and from phase spaces tallied with PRIMO for the Clinac 2100 were compared for the 6, 8, 10 and 15 MV flattened-filtered beams. Dose distributions in water computed for the two sets of PSFs were compared with the Varian Representative Beam Data (RBD) for square fields with sides ranging from 3 to 30 cm. Output factors were calculated for square fields with sides ranging from 2 to 40 cm.

RESULTS

Excellent agreement with the RBD was obtained for the simulations that employed the phase spaces distributed by Varian as well as for those that used the surrogate geometry, reaching in both cases Gamma ([Formula: see text], 2 mm) pass rates larger than [Formula: see text], except for the 15 MV surrogate. This result supports previous investigations that suggest a change in the material composition of the TrueBeam 15 MV flattening filter. In order to get the said agreement, PRIMO simulations were run using enlarged transport parameters to compensate the discrepancies between the actual and surrogate geometries.

CONCLUSIONS

This work sustains the claim that the simulation of the 6, 8 and 10 MV flattening-filtered beams of the TrueBeam linac can be performed using the Clinac 2100 model of PRIMO without significant loss of accuracy.

3D printed non-uniform anthropomorphic phantoms for quantitative SPECT

BACKGROUND

A 3D printing grid-based method was developed to construct anthropomorphic phantoms with non-uniform activity distributions, to be used for evaluation of quantitative SPECT images. The aims were to characterize the grid-based method and to evaluate its capability to provide realistically shaped phantoms with non-uniform activity distributions.

METHODS

Characterization of the grid structures was performed by printing grid-filled spheres. Evaluation was performed by micro-CT imaging to investigate the printing accuracy and by studying the modulation contrast ([Formula: see text]) in SPECT images for 177Lu and 99mTc as a function of the grid fillable-volume fraction (FVF) determined from weighing. The grid-based technique was applied for the construction of two kidney phantoms and two thyroid phantoms, designed using templates from the XCAT digital phantoms. The kidneys were constructed with a hollow outer container shaped as cortex, an inner grid-based structure representing medulla and a solid section representing pelvis. The thyroids consisted of two lobes printed as grid-based structures, with void hot spots within the lobes. The phantoms were filled with solutions of 177Lu (kidneys) or 99mTc (thyroids) and imaged with SPECT. For verification, Monte Carlo simulations of SPECT imaging were performed for activity distributions corresponding to those of the printed phantoms. Measured and simulated SPECT images were compared qualitatively and quantitatively.

RESULTS

Micro-CT images showed that printing inaccuracies were mainly uniform across the grid. The relationships between the FVF from weighing and [Formula: see text] were found to be linear (r = 0.9995 and r = 0.9993 for 177Lu and 99mTc, respectively). The FVF-deviations from the design were up to 15% for thyroids and 4% for kidneys, mainly related to possibilities of cleaning after printing. Measured and simulated SPECT images of kidneys and thyroids exhibited similar activity distributions and quantitative comparisons agreed well, thus verifying the grid-based method.

CONCLUSIONS

We find the grid-based technique useful for the provision of 3D printed, realistically shaped, phantoms with non-uniform activity distributions, which can be used for evaluation of different quantitative methods in SPECT imaging.

Measurement uncertainty for < 905 > Uniformity of Dosage Units tests using Monte Carlo and bootstrapping methods - Uncertainties arising from sampling and analytical steps

Uniformity of dosage unit (UDU) test is widely used to assess the quality, safety, and effectiveness of dosage forms in unit doses. An increased variability of the amount of drug (API - Active Pharmaceutical Ingredient) in each dose unit may lead to low quality, unsafety, and ineffective medicines. The aim of this work was to evaluate the measurement uncertainty associated with the acceptance value (AV) using the Monte Carlo and Bootstrapping methods, as well as to estimate the risk of false decisions regarding compliance/non-compliance due to uncertainty. Haloperidon 5 mg tablets and ofloxacin 200 mg tablets were subject to content uniformity (CU) and weight variation (WV) tests, respectively. Measurement uncertainty evaluation of UDU tests considered both uncertainties arising from sampling analytical steps. Uncertainty values were quantified using Monte Carlo (sampling) or bootstrapping (resampling) methods. Confidence intervals at 95% confidence level (CI95%) for AV value obtained for haloperidol 5 mg tablets were found to between 8.1 and15.8 and between 8.1 and 16.9 for Boostrapping and Monte Carlo methods, respectively. There is an increased risk of false conformity assessment for haloperidol UDU test (6.5% and 12.1% risk values for Bootstrapping and Monte Carlo methods). Considering the ofloxacin 200 mg tablets, the CI95% for AV value were found to be between 4.0 and 11.3 and between 4.9 and 11.4 for Bootstrapping and Monte Carlo methods, respectively. Uncertainty arising from sampling and analytical steps were both relevant to the overall uncertainty of AV values. Measurement uncertainty evaluation provided relevant information to support conformity assessments with a reduced risk of false decision making.

Ecological and Health Risks Attributed to Rare Earth Elements in Coal Fly Ash

The occurrence and distribution of yttrium and rare earth elements (REYs), along with major elements and heavy metal(loid)s (HMs) in coal fly ash (CFA) from five coal-fired power plants (CFPPs), were analyzed, and the REY-associated ecological and health risks were assessed. The individual REYs in CFA were abundant in the following order: Ce > La > Nd > Y > Pr > Gd > Sm > Dy > Er > Yb > Eu > Ho > Tb > Tm > Lu. The total REY content ranged from 135 to 362 mg/kg, averaging 302 mg/kg. The mean light-to-heavy REY ratio was 4.1, indicating prevalent light REY enrichment in CFA. Significantly positive correlations between the REYs suggested that they coexist and share similar origins in CFA. REYs were estimated to pose low to moderate ecological risks, with risk index (RI) values ranging from 66 to 245. The hazard index (HI) and target cancer risk (TCR) of REYs from CFA, estimated to be higher for children (HIc = 0.15, TCRc = 8.4 × 10-16) than for adults (HIa = 0.017, TCRa = 3.6 × 10-16), were well below the safety limits (HI = 1, TCR = 1.0 × 10-6). However, the danger to human health posed by HMs in the same CFA samples (HIc = 5.74, TCRc = 2.6 × 10-4, TCRa = 1.1 × 10-4) exceeded the safe thresholds (excl. HIa = 0.63). The mean RI and HI attributed to REYs in CFA were 14% and 2.6%, respectively, of the total risks that include HMs.

Predicting the Elastic Modulus of Recycled Concrete Considering Material Nonuniformity: Mesoscale Numerical Method

The evaluation of the elastic modulus of recycled concrete is one of the focuses of civil engineering and structural engineering, which is not only related to the stability of building structures but also related to the resource utilization of concrete. Therefore, based on the IRSM method in mesoscale, a novel model for predicting the elastic modulus of recycled concrete is proposed which has the advantages of being low-cost and high-precision, amongst others, compared to theoretical and experimental methods. Then, the influence of coarse aggregate, contact surface, gelling material, and air bubbles on the elastic modulus of recycled concrete is studied. The IRSM model includes four processes: Identification, Reconstruction, Simulation, and Monte Carlo, which can accurately reconstruct the geometric characteristics of coarse aggregate, efficiently reconstruct the coarse aggregate accumulation model, and quickly analyze the elastic modulus of concrete, as well as fully consider the nonuniform characteristics of coarse aggregate distribution and shape. Compared with the experimental results, the error is less than 5%, which verifies the rationality of the IRSM method. The results of the parametric analysis show that the influence of each factor on the elastic modulus of concrete in descending order is elastic modulus of cement, elastic modulus of coarse aggregate, content of coarse aggregate, content of air voids, elastic modulus of contacting surface, and thickness of contacting surface, and the corresponding Pearson's Coefficients are 0.688, 0.427, 0.412, -0.269, 0.188, and -0.061, respectively, in which the content of air voids and thickness of contact surface have a negative effect on the elastic modulus of concrete. These influences mainly affect the deformation resistance (elastic modulus) of concrete through "force chain" adjustment, including the force transfer effect, number of paths, and integrity.

Lifetime attributable risks (LARs) of cancer in the fetus associated with maternal radiography examinations

PURPOSE

For various reasons, pregnant women are occasionally exposed to ionizing radiation during radiology examinations. In these situations, it is essential to determine the radiation dose to the fetus and any associated risks. The present study attempts to calculate the mean dose for the fetus to estimate the possible cancer induction and cancer mortality risks resulting from maternal radiography exams.

MATERIAL AND METHODS

The GATE Monte Carlo platform and a standard voxelized pregnant phantom were employed to calculate fetal radiation dose during maternal radiography exams. The data published in Biological Effects of Ionizing Radiation VII were used to convert fetal dose to lifetime attributable risks (LARs) of cancer incidence and cancer-related mortality.

RESULTS

The fetal doses and LARs of cancer incidence and cancer-related mortality for the radiographs of the chest and skull were negligible. The maximum LAR values for the lateral view of the abdomen in computed and digital radiography are 5598.29 and 2238.95 per 100,000 individuals, respectively. The computed radiography of the lateral view of the abdomen revealed the highest LAR of cancer-related mortality (2074.30 deaths for every 100,000 people).

CONCLUSION

The radiation dose incurred by the fetus due to chest and skull radiographs was minimal and unlikely to cause any abnormalities in the fetus. The discernible elevation in the lifetime attributable risk associated with cancer incidence and mortality arising from lateral computed radiography examinations of the abdomen warrants careful consideration within the realm of maternal radiography examinations.

Comparison of Otsu and an adapted Chan-Vese method to determine thyroid active volume using Monte Carlo generated SPECT images

BACKGROUND

The Otsu method and the Chan-Vese model are two methods proven to perform well in determining volumes of different organs and specific tissue fractions. This study aimed to compare the performance of the two methods regarding segmentation of active thyroid gland volumes, reflecting different clinical settings by varying the parameters: gland size, gland activity concentration, background activity concentration and gland activity concentration heterogeneity.

METHODS

A computed tomography was performed on three playdough thyroid phantoms with volumes 20, 35 and 50 ml. The image data were separated into playdough and water based on Hounsfield values. Sixty single photon emission computed tomography (SPECT) projections were simulated by Monte Carlo method with isotope Technetium-99 m ([Formula: see text]Tc). Linear combinations of SPECT images were made, generating 12 different combinations of volume and background: each with both homogeneous thyroid activity concentration and three hotspots of different relative activity concentrations (48 SPECT images in total). The relative background levels chosen were 5 %, 10 %, 15 % and 20 % of the phantom activity concentration and the hotspot activities were 100 % (homogeneous case) 150 %, 200 % and 250 %. Poisson noise, (coefficient of variation of 0.8 at a 20 % background level, scattering excluded), was added before reconstruction was done with the Monte Carlo-based SPECT reconstruction algorithm Sahlgrenska Academy reconstruction code (SARec). Two different segmentation algorithms were applied: Otsu's threshold selection method and an adaptation of the Chan-Vese model for active contours without edges; the results were evaluated concerning relative volume, mean absolute error and standard deviation per thyroid volume, as well as dice similarity coefficient.

RESULTS

Both methods segment the images well and deviate similarly from the true volumes. They seem to slightly overestimate small volumes and underestimate large ones. Different background levels affect the two methods similarly as well. However, the Chan-Vese model deviates less and paired t-testing showed significant difference between distributions of dice similarity coefficients (p-value [Formula: see text]).

CONCLUSIONS

The investigations indicate that the Chan-Vese model performs better and is slightly more robust, while being more challenging to implement and use clinically. There is a trade-off between performance and user-friendliness.

Optically stimulated luminescence dosimeters for simultaneous measurement of point dose and dose-weighted LET in an adaptive proton therapy workflow

Purpose

To demonstrate the suitability of optically stimulated luminescence detectors (OSLDs) for accurate simultaneous measurement of the absolute point dose and dose-weighted linear energy transfer (LETD) in an anthropomorphic phantom for experimental validation of daily adaptive proton therapy.

Methods

A clinically realistic intensity-modulated proton therapy (IMPT) treatment plan was created based on a CT of an anthropomorphic head-and-neck phantom made of tissue-equivalent material. The IMPT plan was optimized with three fields to deliver a uniform dose to the target volume covering the OSLDs. Different scenarios representing inter-fractional anatomical changes were created by modifying the phantom. An online adaptive proton therapy workflow was used to recover the daily dose distribution and account for the applied geometry changes. To validate the adaptive workflow, measurements were performed by irradiating Al2O3:C OSLDs inside the phantom. In addition to the measurements, retrospective Monte Carlo simulations were performed to compare the absolute dose and dose-averaged LET (LETD) delivered to the OSLDs.

Results

The online adaptive proton therapy workflow was shown to recover significant degradation in dose conformity resulting from large anatomical and positioning deviations from the reference plan. The Monte Carlo simulations were in close agreement with the OSLD measurements, with an average relative error of 1.4% for doses and 3.2% for LETD. The use of OSLDs for LET determination allowed for a correction for the ionization quenched response.

Conclusion

The OSLDs appear to be an excellent detector for simultaneously assessing dose and LET distributions in proton irradiation of an anthropomorphic phantom. The OSLDs can be cut to almost any size and shape, making them ideal for in-phantom measurements to probe the radiation quality and dose in a predefined region of interest. Although we have presented the results obtained in the experimental validation of an adaptive proton therapy workflow, the same approach can be generalized and used for a variety of clinical innovations and workflow developments that require accurate assessment of point dose and/or average LET.

[Health Risk Assessment and Priority Control Factors Analysis of Heavy Metals in Agricultural Soils Based on Source-oriented]

To analyze the source apportionment and health risk of heavy metals in agricultural soils of major producing areas of agricultural products in Chongqing, a positive matrix factorization (PMF) model and health risk assessment (HRA) model based on Monte Carlo simulation were used. Meanwhile, both the PMF and HRA model were combined to explore health risks of heavy metals in agricultural soils by different pollution sources in order to determine the priority control factors. The results showed that the average values of Cd concentration were higher than its corresponding background value; the average values of Cr concentration were lower than its corresponding background value; and the average values of As, Pb, Cu, Ni, and Zn concentration were basically consistent with their corresponding background values. Using PMF model analysis, natural sources, industrial sources, and agricultural sources were identified as the determinants for the accumulation of heavy metals in agricultural soils, with the contribution rates of 35%, 24%, and 41%, respectively. Using the HRA model based on Monte Carlo simulation analysis, carcinogenic risks of adult and children were tolerable (1.00E-6 < TCR ≤ 1.00E-4), whereas non-carcinogenic risks were acceptable (HI ≤ 1). Oral ingestion was the main exposure pathway. The analysis results of the relationship among heavy metals, pollution sources, and health risks showed that industrial pollution and As were identified as priority control factors, and agricultural pollution and Cd were identified as secondary control factors. Our findings provide scientific support for decision makers to control soil pollution and reduce the management costs of soil pollution.

High-density polyethylene (HDPE)-incorporated boron carbide and boric acid nanoparticles as a nanoshield of photoneutrons from medical linear accelerators

PURPOSE

The current study aimed to investigate boron carbide and boric acid nanoparticles (NPs) as absorbents for thermal neutrons and high-density polyethylene (HDPE) as a substrate and neutron moderator for fast neutrons. The goal was to assess the performance of boron carbide and boric acid NPs based on HDPE as a nanoshield of photoneutrons from medical linear accelerators.

MATERIALS AND METHODS

This study was conducted in two parts of simulation and practice. The Monte Carlo (MC) simulation involved modeling and verification of the single-layer, double-layer, and combined nanoshields by selecting nanomaterials and substrates and, finally, calculating the macroscopic cross-sections. The practical part involved manufacturing nanoshields based on the simulation results and evaluating the manufactured nanocomposites via experimental measurements.

RESULTS

MC simulation results with an uncertainty of less than 1% showed that for the monolayer samples, the best result belonged to boron carbide at a concentration of 10% and a macroscopic cross-section of 0.933 cm-1. At a concentration of 20%, the highest value among the double-layer samples was 0.936 cm-1 and for the combined samples, this value was 0.928 cm-1. Boron carbide single-layer nanocomposites at a 10% concentration, as well as the bilayer nanoshield of 10% boron carbide and 20% boric acid performed well; however, the best performance belonged to the nanoshield with a macroscopic cross-section of 0.960 and the combination containing 5% boron carbide and 10% boric acid.

CONCLUSIONS

The research suggests that utilizing boron carbide and boric acid nanoshields in combination with HDPE holds promise as a viable approach to protecting from the photoneutrons. Further exploration of these nanocomposite shields and their practical applications is warranted, with the potential to yield significant advancements in radiation therapy safety and efficacy.

Non-coplanar lung SABR treatments delivered with a gantry-mounted x-ray tube

Objective.To create two non-coplanar, stereotactic ablative radiotherapy (SABR) lung patient treatment plans compliant with the radiation therapy oncology group (RTOG) 0813 dosimetric criteria using a simple, isocentric, therapy with kilovoltage arcs (SITKA) system designed to provide low cost external radiotherapy treatments for low- and middle-income countries (LMICs).Approach.A treatment machine design has been proposed featuring a 320 kVp x-ray tube mounted on a gantry. A deep learning cone-beam CT (CBCT) to synthetic CT (sCT) method was employed to remove the additional cost of planning CTs. A novel inverse treatment planning approach using GPU backprojection was used to create a highly non-coplanar treatment plan with circular beam shapes generated by an iris collimator. Treatments were planned and simulated using the TOPAS Monte Carlo (MC) code for two lung patients. Dose distributions were compared to 6 MV volumetric modulated arc therapy (VMAT) planned in Eclipse on the same cases for a Truebeam linac as well as obeying the RTOG 0813 protocols for lung SABR treatments with a prescribed dose of 50 Gy.Main results.The low-cost SITKA treatments were compliant with all RTOG 0813 dosimetric criteria. SITKA treatments showed, on average, a 6.7 and 4.9 Gy reduction of the maximum dose in soft tissue organs at risk (OARs) as compared to VMAT, for the two patients respectively. This was accompanied by a small increase in the mean dose of 0.17 and 0.30 Gy in soft tissue OARs.Significance.The proposed SITKA system offers a maximally low-cost, effective alternative to conventional radiotherapy systems for lung cancer patients, particularly in low-income countries. The system's non-coplanar, isocentric approach, coupled with the deep learning CBCT to sCT and GPU backprojection-based inverse treatment planning, offers lower maximum doses in OARs and comparable conformity to VMAT plans at a fraction of the cost of conventional radiotherapy.

Evaluation of RADIANCE Monte Carlo algorithm for treatment planning in electron based Intraoperative Radiotherapy (IOERT)

PURPOSE

To perform experimental as well as independent Monte Carlo (MC) evaluation of the MC algorithm implemented in RADIANCE version 4.0.8, a dedicated treatment planning system (TPS) for 3D electron dose calculations in intraoperative radiation therapy (IOERT).

METHODS AND MATERIALS

The MOBETRON 2000 (IntraOp Medical Corporation, Sunnyvale, CA) IOERT accelerator was employed. PDD and profiles for five cylindrical plastic applicators with 50-90 mm diameter and 0°, 30° beveling were measured in a water phantom, at nominal energies of 6, 9 and 12 MeV. Additional PDD measurements were performed for all the energies without applicator. MC modeling of the MOBETRON was performed with the user code BEAMnrc and egs_chamber of the MC simulation toolkit EGSnrc. The generated phase space files of the two 0°-bevel applicators (50 mm, 80 mm) and three energies in both RADIANCE and BEAMnrc, were used to determine PDD and profiles in various set-ups of virtual water phantoms with air and bone inhomogeneities. 3D dose distributions were also calculated in image data sets of an anthropomorphic tissue-equivalent pelvis phantom. Image acquisitions were realized with a CT scanner (Philips Big Bore CT, Netherlands). Gamma analysis was applied to quantify the deviations of the RADIANCE calculations to the measurements and EGSnrc calculations. Gamma criteria normalized to the global maximum were investigated between 2%, 2 mm and 3%, 3 mm.

RESULTS

RADIANCE MC calculations satisfied the gamma criteria of 3%, 3 mm with a tolerance limit of 85% passing rate compared to in- water phantom measurements, except for the dose profiles of the 30° beveled applicators. Mismatches lay in surface doses, in umbra regions and in the beveled end of the 30° applicators. A very good agreement to the EGSnrc calculations in heterogeneous media was observed. Deviations were more pronounced for the larger applicator diameter and higher electron energy. In 3D dose comparisons in the anthropomorphic phantom, gamma passing rates were higher than 96 % for both simulated applicators.

CONCLUSIONS

RADIANCE MC algorithm agrees within 3%, 3 mm criteria with in-water phantom measurements and EGSnrc MC dose distributions in heterogeneous media for 0°-bevel applicators. The user should be aware of missing scattering components and the 30° beveled applicators should be used with attention.

SAXS/MC studies of the mixed-folded protein Cdt1 reveal monomeric, folded over conformations

Cdt1 is a protein critical for DNA replication licensing and is well-established to be a binding partner of the minichromosome maintenance (MCM) complex. Cdt1 has also been demonstrated to have an emerging, "moonlighting" role at the kinetochore via direct binding to microtubules and to the Ndc80 complex. However, it is not known how the structure and conformations of Cdt1 could allow for these multiple, completely unique sets of protein complexes. And while there exist multiple robust methods to study entirely folded or entirely unfolded proteins, structure-function studies of combined, mixed folded/disordered proteins remain challenging. It this work, we employ multiple orthogonal biophysical and computational techniques to provide a detailed structural characterization of human Cdt1 92-546. DSF and DSCD show both folded winged helix (WH) domains of Cdt1 are relatively unstable. CD and NMR show the N-terminal and the linker regions are intrinsically disordered. Using DLS and SEC-MALS, we show that Cdt1 is polydisperse, monomeric at high concentrations, and without any apparent inter-molecular self-association. SEC-SAXS of the monomer in solution enabled computational modeling of the protein in silico. Using the program SASSIE, we performed rigid body Monte Carlo simulations to generate a conformational ensemble. Using experimental SAXS data, we filtered for conformations which did and did not fit our data. We observe that neither fully extended nor extremely compact Cdt1 conformations are consistent with our SAXS data. The best fit models have the N-terminal and linker regions extended into solution and the two folded domains close to each other in apparent "folded over" conformations. The best fit Cdt1 conformations are consistent with a function as a scaffold protein which may be sterically blocked without the presence of binding partners. Our studies also provide a template for combining experimental and computational biophysical techniques to study mixed-folded proteins.

Computational model of radiation oxygen effect with Monte Carlo simulation: effects of antioxidants and peroxyl radicals

PURPOSE

Oxygen plays a crucial role in radiation biology. Antioxidants and peroxyl radicals affect the oxygen effect greatly. This study aims to establish a computational model of the oxygen effect and explore the effect attributed to antioxidants and peroxyl radicals.

MATERIALS AND METHODS

Oxygen-related reactions are added to our track-structure Monte Carlo code NASIC, including oxygen fixation, chemical repair by antioxidants and damage migration from base-derived peroxyl radicals. Then the code is used to simulate the DNA damage under various oxygen, antioxidant and damage migration rate conditions. The oxygen enhancement ratio(OER) is calculated quantifying by the number of double-strand breaks for each condition. The roles of antioxidants and peroxyl radicals are examined by manipulating the relevant parameters.

RESULTS AND CONCLUSIONS

Our results indicate that antioxidants are capable of rapidly restoring DNA radicals through chemical reactions, which compete with natural and oxygen fixation processes. Additionally, antioxidants can react with peroxyl radicals derived from bases, thereby preventing the damage from migrating to DNA strands. By quantitatively accounting for the impact of peroxyl radicals and antioxidants on the OER curves, our study establishes a more precise and comprehensive model of the radiation oxygen effect.

Proof-of-concept for a thin conical X-ray target optimized for intensity and directionality for use in a carbon nanotube-based compact X-ray tube

BACKGROUND

Carbon nanotube-based cold cathode technology has revolutionized the miniaturization of X-ray tubes. However, current applications of these devices required optimization for large, uniform fields with low intensity.

PURPOSE

This work investigated the feasibility and radiological characteristics of a novel conical X-ray target optimized for high intensity and high directionality to be used in a compact X-ray tube.

METHODS

The proposed device uses an ultrathin, conical tungsten-diamond target that exhibits significant heat loading while maintaining a small focal spot size and promoting forward-directedness of the X-ray field through preferential attenuation of oblique-angled photons. The electrostatic and thermal properties of the theoretical tube were calculated and analyzed using COMSOL Multiphysics software. The production, transport, and calculation of radiological properties associated with the resultant X-ray field were performed using the Geant4 toolkit via its wrapper, TOPAS.

RESULTS

Heat transfer analysis of this X-ray tube demonstrated the feasibility of a 200-kV electron beam bombarding the proposed target at a maximum current of 100 mA using a 1-ms symmetric duty cycle. The cathode of the X-ray tube was designed to be segmented into nine switchable electrical segments for modulation of the focal spot size from 0.4- to 10.8-mm. After importing the COMSOL-derived electron beam into TOPAS for X-ray production simulations, radiological analysis of the resultant field demonstrated high levels of intrinsic beam collimation while maintaining high intensity. A maximum dose rate of 17,887 cGy/min was calculated for 1-mm depth in water at 7-cm distance.

CONCLUSIONS

The proposed X-ray tube design can create highly directional X-ray fields with superior fluence compared to that of current commercial X-ray tubes of comparable size.

Effect of tin spectral filtration on organ and effective dose in CT colonography and CT lung cancer screening

BACKGROUND

Studies of tin spectral filtration have demonstrated potential in reducing radiation dose while maintaining image quality for unenhanced computed tomography (CT) scans. The extent of dose reduction, however, was commonly measured using the change in the scanner's reported CTDIvol . This method does not account for how tin filtration affects patient organ and effective dose.

PURPOSE

To investigate the effect of tin filtration on patient organ and effective dose for CT Lung Cancer Screening (LCS) and CT Colonography (CTC).

METHODS

A previously-developed Monte Carlo program was adapted to model a 96-row CT scanner (Somatom Force, Siemens Healthineers) with tin filtration capabilities at 100 kV (100Sn) and 150 kV (150Sn). The program was then validated using experimental CTDIvol measurements at all available kV (70-150 kV) and tin-filtered kV options (100Sn and 150Sn). After validation, the program simulated LCS scans of the chest and CTC scan of the abdomen-pelvis for a population of 53 computational patient models from the extended cardiac-torso family. Each scan was performed using three different spectra: 120 kV, 100Sn, and 150Sn. CTDIvol -normalized organ doses and DLP-normalized effective doses, commonly referred to as dose conversion factors, were compared between the different spectra.

RESULTS

For all LCS and CTC scans, CTDIvol -normalized organ doses and DLP-normalized effective doses increased with increasing beam hardness (120 kV, 100Sn, 150 Sn). For LCS, relative for 120 kV, conversion factors for 100Sn produced a median increase in effective dose of 9%, with organ dose increases of 8% to lung, 5% to breast, 15% to thyroid, and 3% to skin. Conversion factors for 150Sn produced a median increase in effective dose of 20%, with organ dose increases of 16%, 18%, 26%, and 12% to these same organs, respectively. For CTC, relative for 120 kV, conversion factors for 100Sn produced a median increase in effective dose of 12%, with organ dose increases of 9% to colon, 10% to liver, 11% to stomach, and 4% to skin. Conversion factors for 150Sn produced a median increase in effective dose of 21%, with organ dose increases of 16%, 17%, 19%, and 10% to these same organs, respectively.

CONCLUSIONS

Results show that dose conversion factors are greater when using tin filtration and should be considered when evaluating tin's potential for dose reduction.

A dose calculation algorithm for boron neutron capture therapy using convolution/superposition method

The convolution/superposition (C/S) method originally designed for photon dose calculation was first applied for developing a treatment planning system for boron neutron capture therapy. The original concept of TEGMA (total energy generated per unit mass) was proposed to represent distinctive dose components from neutron reactions with the elements in the patient's tissue. First, neutron fluence distributions in a homogeneous brain phantom irradiated with an energy-groupwise pencil beam of 2.5 × 2.5 mm2 were calculated using the MCNP6.2 code. Then, a library of energy-groupwise TEGMA and KERMA were generated and stored in the developed C/S code. As a benchmark, dose distributions in a cuboid phantom and a human head phantom were calculated using the developed C/S and PHITS Monte Carlo codes. A neutron beam having a continuous epithermal spectrum and a square field of 22.5 × 22.5 mm2 or a circle field of 22.5 mm in diameter was assumed to be incident on the phantoms. The human head phantom was created by the pre-processing including the voxelization and transformation of test DICOM CT images. The differences in boron doses between C/S and MC ranged from 2% to 6%. In nitrogen doses, the differences were from 4% to 9%. A large discrepancy observed in hydrogen lateral dose profiles could be explained by the differences in cross-section data and recoil-proton transport algorithms of MCNP6.2 and PHITS. With isodose curves normalized at the center of the tumor in the human head phantom, they were almost identical in the range of 60%-110% for both cases. The C/S have underestimated the backscattering neutron and showed a larger absorbed dose gradient around 40% region. The calculation time of C/S using Intel i7-10700 processor was less than 1 min for both phantoms. The calculation time of PHITS using three Intel Xeon E5-2640 v4 processors was 15.5 min for the cuboid phantom and ∼380 min for the human head phantom. The proposed algorithm has the advantages of high speed while promising fair accuracy in BNCT dose calculations.

A fully automated machine learning-based methodology for personalized radiation dose assessment in thoracic and abdomen CT

PURPOSE

To develop a machine learning-based methodology for patient-specific radiation dosimetry in thoracic and abdomen CT.

METHODS

Three hundred and thirty-one thoracoabdominal radiotherapy-planning CT examinations with the respective organ/patient contours were collected retrospectively for the development and validation of segmentation 3D-UNets. Moreover, 97 diagnostic thoracic and 89 diagnostic abdomen CT examinations were collected retrospectively. For each of the diagnostic CT examinations, personalized MC dosimetry was performed. The data derived from MC simulations along with the respective CT data were used for the training and validation of a dose prediction deep neural network (DNN). An algorithm was developed to utilize the trained models and perform patient-specific organ dose estimates for thoracic and abdomen CT examinations. The doses estimated with the DNN were compared with the respective doses derived from MC simulations. A paired t-test was conducted between the DNN and MC results. Furthermore, the time efficiency of the proposed methodology was assessed.

RESULTS

The mean percentage differences (range) between DNN and MC dose estimates for the lungs, liver, spleen, stomach, and kidneys were 7.2 % (0.2-24.1 %), 5.5 % (0.4-23.0 %), 7.9 % (0.6-22.3 %), 6.9 % (0.0-23.0 %) and 6.7 % (0.3-22.6 %) respectively. The differences between DNN and MC dose estimates were not significant (p-value = 0.12). Moreover, the mean processing time of the proposed workflow was 99 % lower than the respective time needed for MC-based dosimetry.

CONCLUSIONS

The proposed methodology can be used for rapid and accurate patient-specific dosimetry in chest and abdomen CT.

Estimating how contouring differences affect normal tissue complication probability modelling

Background and purpose

Normal tissue complication probability (NTCP) models are developed from large retrospective datasets where automatic contouring is often used to contour the organs at risk. This study proposes a methodology to estimate how discrepancies between two sets of contours are reflected on NTCP model performance. We apply this methodology to heart contours within a dataset of non-small cell lung cancer (NSCLC) patients.

Materials and methods

One of the contour sets is designated the ground truth and a dosimetric parameter derived from it is used to simulate outcomes via a predefined NTCP relationship. For each simulated outcome, the selected dosimetric parameters associated with each contour set are individually used to fit a toxicity model and their performance is compared. Our dataset comprised 605 stage IIA-IIIB NSCLC patients. Manual, deep learning, and atlas-based heart contours were available.

Results

How contour differences were reflected in NTCP model performance depended on the slope of the predefined model, the dosimetric parameter utilized, and the size of the cohort. The impact of contour differences on NTCP model performance increased with steeper NTCP curves. In our dataset, parameters on the low range of the dose-volume histogram were more robust to contour differences.

Conclusions

Our methodology can be used to estimate whether a given contouring model is fit for NTCP model development. For the heart in comparable datasets, average Dice should be at least as high as between our manual and deep learning contours for shallow NTCP relationships (88.5 ± 4.5 %) and higher for steep relationships.

A cooperative construction strategy for multi-parameter spatial variant random fields and its application in groundwater pollution risk assessment

The spatial variability of hydrogeological parameters is a significant source of uncertainty in groundwater numerical modeling and has a certain risk impact on the prediction of pollutant migration and transformation. Current research has focused on the effects of single-parameter spatial variant random fields or utilizing random sampling methods to randomly combine multiple-parameter spatial variant random fields while ignoring the correlation between parameters. This paper proposes an innovative concept of associated random variables to construct multi-parameter synergistic spatial variant random fields, ensuring both the spatial variability and inherent correlation of the parameters. A hypothetical case was constructed, and the Monte Carlo sampling experiment based on computer simulation was used to assess groundwater pollution risks with multiple associated parameters. The results show that hydraulic conductivity and porosity are the main sensitive parameters. The associated random variable allows for the representation of positive correlation, negative correlation, and no correlation between the hydraulic conductivity and porosity. The pollutant mass concentrations in each observation well conform to the generalized extreme value distribution, and the pollution risks of each water well as well as the concentration distribution intervals of pollutants with different probabilities can be obtained. The influence of associated parameters on the cumulative risk of contaminants in observation wells and pollution degree range is only related to their mathematical distribution and is independent of correlations between parameters. This study addresses the issues of spatial variability and inherent correlation of hydrogeological parameters, which are of great significance for groundwater pollution risk assessment and the promotion of sustainable water quality management of groundwater resources.

Multiple energy X-ray imaging of metal oxide particles inside gingival tissues

BACKGROUND

Periodontal disease affects over 50% of the global population and is characterized by gingivitis as the initial sign. One dental health issue that may contribute to the development of periodontal disease is foreign body gingivitis (FBG), which can result from exposure to some kinds of foreign metal particles from dental products or food.

OBJECTIVE

We design a novel, portable, affordable, multispectral X-ray and fluorescence optical microscopic imaging system dedicated to detecting and differentiating metal oxide particles in dental pathological tissues. A novel denoising algorithm is applied. We verify the feasibility and optimize the performance of the imaging system with numerical simulations.

METHODS

The designed imaging system has a focused X-ray tube with tunable energy spectra and thin scintillator coupled with an optical microscope as detector. A simulated soft tissue phantom is embedded with 2-micron thick metal oxide discs as the imaged object. GATE software is used to optimize the systematic parameters such as energy bandwidth and X-ray photon number. We have also applied a novel denoising method, Noise2Sim with a two-layer UNet structure, to improve the simulated image quality.

RESULTS

The use of an X-ray source operating with an energy bandwidth of 5 keV, X-ray photon number of 108, and an X-ray detector with a 0.5 micrometer pixel size in a 100 by 100-pixel array allowed for the detection of particles as small as 0.5 micrometer. With the Noise2Sim algorithm, the CNR has improved substantially. A typical example is that the Aluminum (Al) target's CNR is improved from 6.78 to 9.72 for the case of 108 X-ray photons with the Chromium (Cr) source of 5 keV bandwidth.

CONCLUSIONS

Different metal oxide particles were differentiated using Contrast-to-Noise ratio (CNR) by utilizing four different X-ray spectra.

Heterogeneous physical phantom for I-125 dose measurements and dose-to-medium determination

PURPOSE

In this paper we present a further step in the implementation of a physical phantom designed to generate sets of "true" independent reference data as requested by TG-186, intending to address and mitigate the scarcity of experimental studies on brachytherapy (BT) validation in heterogeneous media. To achieve this, we incorporated well-known heterogeneous materials into the phantom in order to perform measurements of 125I dose distribution. The work aims to experimentally validate Monte Carlo (MC) calculations based on MBDCA and determine the conversion factors from LiF response to absorbed dose in different media, using cavity theory.

METHODS AND MATERIALS

The physical phantom was adjusted to incorporate tissue equivalent materials, such as: adipose tissue, bone, breast and lung with varying thickness. MC calculations were performed using MCNP6.2 code to calculate the absorbed dose in the LiF and the dose conversion factors (DCF).

RESULTS

The proposed heterogeneous phantom associated with the experimental procedure carried out in this work yielded accurate dose data that enabled the conversion of the LiF responses into absorbed dose to medium. The results showed a maximum uncertainty of 6.92 % (k = 1), which may be considered excellent for dosimetry with low-energy BT sources.

CONCLUSIONS

The presented heterogeneous phantom achieves the required precision in dose evaluations due to its easy reproducibility in the experimental setup. The obtained results support the dose conversion methodology for all evaluated media. The experimental validation of the DCF in different media holds great significance for clinical procedures, as it can be applied to other tissues, including water, which remains a widely utilized reference medium in clinical practice.