The impact of solvents on the efficiency of cationic dye adsorption from a solution onto protonated Faujasite-type zeolite (FAU-Y) was investigated in the prospect of supporting potential applications in wastewater treatment or in the preparation of building blocks for optical devices. The adsorption isotherms were experimentally determined for methylene blue (MB) and auramine O (AO) from single-component solutions in water and in ethanol. The limiting dye uptake (saturation capacity) was evaluated for each adsorption system, and it decreased in the order of MB-water > AO-water > AO-ethanol > MB-ethanol. The mutual distances and orientations of the adsorbed dye species, and their interactions with the oxygen sites of the FAU-Y framework, with the solvent molecules, and among themselves were inferred from Monte Carlo simulations and subsequently utilized to rationalize the observed differences in the saturation capacity. The dye-solvent competition and the propensity of the dyes to form compact pi-stacked dimers were shown to play an important role in establishing a non-uniform distribution of the adsorbed species throughout the porous space. The two effects appeared particularly strong in the case of the MB-water system. The necessity of including solvent effects in modeling studies is emphasized.

Mobile applications offer a wide range of opportunities for psychological data collection, such as increased ecological validity and greater acceptance by participants compared to traditional laboratory studies. However, app-based psychological data also pose data-analytic challenges because of the complexities introduced by missingness and interdependence of observations. Consequently, researchers must weigh the advantages and disadvantages of app-based data collection to decide on the scientific utility of their proposed app study. For instance, some studies might only be worthwhile if they provide adequate statistical power. However, the complexity of app data forestalls the use of simple analytic formulas to estimate properties such as power. In this paper, we demonstrate how Monte Carlo simulations can be used to investigate the impact of app usage behavior on the utility of app-based psychological data. We introduce a set of questions to guide simulation implementation and showcase how we answered them for the simulation in the context of the guessing game app Who Knows (Rau et al., 2023). Finally, we give a brief overview of the simulation results and the conclusions we have drawn from them for real-world data generation. Our results can serve as an example of how to use a simulation approach for planning real-world app-based data collection.

OBJECTIVE: The purpose of this study is to investigate the dosimetric characteristics of a collimator for minibeam radiotherapy (MBRT) with film dosimetry and Monte Carlo (MC) simulations. The outcome of MBRT with respect to conventional RT using a glioma preclinical model was also evaluated.
METHODS: A multi-slit collimator was designed to be used with commercial small animal irradiator. The collimator was built by aligning 0.6 mm wide and 5 mm thick parallel lead leaves at 0.4 mm intervals. Dosimetry characteristics were evaluated by Gafchromic (CG) films and TOPAS Monte Carlo (MC) code. An in vivo experiment was performed using a glioma preclinical model by injecting two million GL261cells subcutaneously and treating with 25 Gy, single fraction, with MBRT and conventional RT. Survival curves and acute radiation damage were measured to compare both treatments.
RESULTS: A satisfactory agreement between experimental results and MC simulations were obtained, the measured FWHM and distance between the peaks were respectively 0.431 and 1.098 mm. In vivo results show that MBRT can provide local tumor control for three weeks after RT treatment and a similar survival fraction of open beam radiotherapy. No severe acute effects were seen for the MBRT group.
CONCLUSIONS: We developed a minibeam collimator and presented its dosimetric features. Satisfactory agreement between MC and GC films was found with differences consistent with uncertainties due to fabrication and set-up errors. The survival curves of MBRT and open field RT are similar while atoxicity is dramatically lower with MBRT, preliminarily confirming the expected effect.

This study conducted a comprehensive analysis of trace element concentrations in the Upper Indus River Basin (UIRB), a glacier-fed region in the Western Himalayas (WH), aiming to discern their environmental and anthropogenic sources and implications. Despite limited prior data, 69 samples were collected in 2019 from diverse sources within the UIRB, including mainstream, tributaries, and groundwater, to assess trace element concentrations. Enrichment factor (EF) results and comparisons with regional and global averages suggest that rising levels of Zn, Cd, and As may pose safety concerns for drinking water quality. Advanced multivariate statistical techniques such as principal component analysis (PCA), absolute principal component scores (APCS-MLR), Monte Carlo simulation (MCS), etc were applied to estimate the associated human health hazards and also identified key sources of trace elements. The 95th percentile of the MCS results indicates that the estimated total cancer risk for children is significantly greater than (>1000 times) the USEPA\'s acceptable risk threshold of 1.0 × 10-6. The results classified most of the trace elements into two distinct groups: Group A (Li, Rb, Sr, U, Cs, V, Ni, TI, Sb, Mo, Ge), linked to geogenic sources, showed lower concentrations in the lower-middle river reaches, including tributaries and downstream regions. Group B (Pb, Nb, Cr, Zn, Be, Al, Th, Ga, Cu, Co), influenced by both geogenic and anthropogenic activities, exhibited higher concentrations near urban centers and midstream areas, aligning with increased municipal waste and agricultural activities. Furthermore, APCS-MLR source apportionment indicated that trace elements originated from natural geogenic processes, including rock-water interactions and mineral dissolution, as well as anthropogenic activities. These findings underscore the need for targeted measures to mitigate anthropogenic impacts and safeguard water resources for communities along the IRB and WH.

A Monte Carlo study of the compatibilization of A/B polymer blends has been performed using the bond fluctuation model. The considered compatibilizers are copolymer molecules composed of A and B blocks. Different types of copolymer structures have been included, namely, linear diblock and 4-block alternating copolymers, star block copolymers, miktoarm stars, and zipper stars. Zipper stars are composed of two arms of diblock copolymers arranged in alternate order (AB and BA) from the central unit, along with two homogeneous arms of A and B units. The compatibilization performance has been characterized by analyzing the equilibration of repulsion energy, the simulated scattering intensity obtained with opposite refractive indices for A and B, the profiles along a coordinate axis, the radial distribution functions, and the compatibilizer aggregation numbers. According to the results, linear alternate block copolymers, star block copolymers, and zipper stars exhibit significantly better compatibilization, with zipper stars showing slightly but consistently better performance.

BACKGROUND: Dosimetry-based personalized therapy was shown to have clinical benefits e.g. in liver selective internal radiation therapy (SIRT). Yet, there is no consensus about its introduction into clinical practice, mainly as Monte Carlo simulations (gold standard for dosimetry) involve massive computation time. We addressed the problem of computation time and tested a patch-based approach for Monte Carlo simulations for internal dosimetry to improve parallelization. We introduce a physics-inspired cropping layout for patch-based MC dosimetry, and compare it to cropping layouts of the literature as well as dosimetry using organ-S-values, and dose kernels, taking whole-body Monte Carlo simulations as ground truth. This was evaluated in five patients receiving Yttrium-90 liver SIRT.
RESULTS: The patch-based Monte Carlo approach yielded the closest results to the ground truth, making it a valid alternative to the conventional approach. Our physics-inspired cropping layout and mosaicking scheme yielded a voxel-wise error of < 2% compared to whole-body Monte Carlo in soft tissue, while requiring only ≈  10% of the time.
CONCLUSIONS: This work demonstrates the feasibility and accuracy of physics-inspired cropping layouts for patch-based Monte Carlo simulations.

Tacrolimus (TAC) has high pharmacokinetic (PK) variability during the early transplantation period. The relationships between whole-blood and intracellular TAC concentrations and clinical outcomes remain controversial. This study identifies the factors affecting the PK variability of TAC and characterizes the relationships between whole-blood and intracellular TAC concentrations. Data regarding whole-blood TAC concentrations of 1,787 samples from 215 renal transplant recipients (<90 days postoperative) across two centers and intracellular TAC concentrations (648 samples) digitized from previous studies were analyzed using nonlinear mixed-effects modeling. The effects of potential covariates were screened, and the distribution of whole-blood to intracellular TAC concentration ratios (RWB:IC) was estimated. The final model was evaluated using bootstrap, goodness of fit, and prediction-corrected visual predictive checks. The optimal dosing regimens and target ranges for each type of immune cell subsets were determined using Monte Carlo simulations. A two-compartment model adequately described the data, and the estimated mean TAC CL/F was 23.6 L·h-1 (relative standard error: 11.5 %). The hematocrit level, CYP3A5*3 carrier status, co-administration with Wuzhi capsules, and tapering prednisolone dose may contribute to the high variability of TAC PK variability during the early post-transplant period. The estimated RWB:IC of all TAC concentrations in peripheral blood mononuclear cells (PBMCs) was 4940, and inter-center variability of PBMCs was observed. The simulated TAC target range in PBMCs was 20.2-85.9 pg·million cells-1. Inter-center variability in intracellular concentrations should be taken into account in further analyses. TAC dosage adjustments can be guided based on PK/PD variability and simulated intracellular concentrations.

Phase behavior of nanoconfined fluids adsorbed in metal-organic frameworks is of paramount importance for the design of advanced materials for energy and gas storage, separations, electrochemical devices, sensors, and drug delivery, as well as for the pore structure characterization. Phase transformations in adsorbed fluids often involve long-lasting metastable states and hysteresis that has been well-documented in gas adsorption-desorption and nonwetting fluid intrusion-extrusion experiments. However, theoretical prediction of the observed nanophase behavior remains a challenging problem. The mesoscopic canonical, or mesocanonical, ensemble (MCE) is devised to study the nanophase behavior under conditions of controlled fluctuations to stabilize metastable and labile states. Here, we implement and apply the MCE Monte Carlo (MCEMC) simulation scheme to predict the origins of reversible and hysteric adsorption phase transitions in a series of practical MOF materials, including IRMOF-1, ZIF-412, UiO-66, Cu-BTC, IRMOF-74-V, VII, and IX. The MCEMC method, called the gauge cell method, allows to produce Van der Waals type isotherms with distinctive swings around the phase transition regions. The constructed isotherms determine the positions of phase equilibrium and spinodals, as well as the nucleation barriers separating metastable states. We demonstrate the unique capabilities of the MCEMC method in quantitative predictions of experimental observations compared with the conventional grand canonical and canonical ensemble simulations. The MCEMC method is implemented in the open-source RASPA and LAMMPS software packages and recommended for studies of adsorption behavior and pore structure characterization of MOFs and other nanoporous materials.

OBJECTIVE: This study aimed to assess the accuracy of patient-specific absorbed dose calculations for tumours and organs at risk in radiopharmaceutical therapy planning, utilizing hybrid planar-SPECT/CT imaging.
METHODS: Three Monte Carlo (MC) simulated digital patient phantoms were created, with time-activity data for mIBG labelled to I-123 (LEHR and ME collimators) and I-131 (HE collimator). The study assessed the accuracy of the mean absorbed doses for I-131-mIBG therapy treatment planning. Multiple planar whole-body (WB) images were simulated (between 1 to 72 h post-injection (p.i)). The geometric-mean image of the anterior and posterior WB images was calculated, with scatter and attenuation corrections applied. Time-activity curves were created for regions of interest over the liver and two tumours (diameters: 3.0 cm and 5.0 cm) in the WB images. A corresponding SPECT study was simulated at 24 h p.i and reconstructed using the OS-EM algorithm, incorporating scatter, attenuation, collimator-detector response, septal scatter and penetration corrections. MC voxel-based absorbed dose rate calculations used two image sets, (i) the activity distribution represented by the SPECT images and (ii) the activity distribution from the SPECT images distributed uniformly within the volume of interest. Mean absorbed doses were calculated considering photon and charged particle emissions, and beta emissions only. True absorbed doses were calculated by MC voxel-based dosimetry of the known activity distributions for reference.
RESULTS: Considering photon and charged particle emissions, mean absorbed dose accuracies across all three radionuclide-collimator combinations of 3.8 ± 5.5% and 0.1 ± 0.9% (liver), 5.2 ± 10.0% and 4.3 ± 1.7% (3.0 cm tumour) and 15.0 ± 5.8% and 2.6 ± 0.6% (5.0 cm tumour) were obtained for image set (i) and (ii) respectively. Considering charged particle emissions, accuracies of 2.7 ± 4.1% and 5.7 ± 0.7% (liver), 3.2 ± 10.2% and 9.1 ± 1.7% (3.0 cm tumour) and 13.6 ± 5.7% and 7.0 ± 0.6% (5.0 cm tumour) were obtained for image set (i) and (ii) respectively.
CONCLUSIONS: The hybrid WB planar-SPECT/CT method proved accurate for I-131-mIBG dosimetry, suggesting its potential for personalized treatment planning.

Singlet-to-triplet intersystem crossing (ISC) in organic molecules is intimately connected with their geometries: by modifying the molecular shape, symmetry selection rules pertaining to spin-orbit coupling can be partially relieved, leading to extra matrix elements for increased ISC. As an analog to this molecular design concept, the study finds that the lattice symmetry of supramolecular polymers also defines their triplet formation efficiencies. A supramolecular polymer self-assembled from weakly interacting molecules is considered. Its 2D oblique unit cell effectively renders it as a coplanar array of 1D molecular columns weakly bound to each other. Using momentum-resolved photoluminescence imaging in combination with Monte Carlo simulations, the study found that photogenerated charge carriers in the supramolecular polymer predominantly recombine as spin-uncorrelated carrier pairs through inter-column charge transfer states. This lattice-defined recombination pathway leads to a substantial triplet formation efficiency (≈60%) in the supramolecular polymer. These findings suggest that lattice symmetry of micro-/macroscopic structures relying on intermolecular interactions can be strategized for controlled triplet formation.