Dosimetry at cellular level for the alpha-emitting radionuclides actinium-225, astatine-211 and radium-223 for bone metastasis cells from castration resistant prostate cancer.

Objectives.The aim of this work is to evaluate energy deposition in the nucleus and cytoplasm in targeted alpha therapy of metastatic castration-resistant prostate cancer by modeling two cell lines, PC3 (osteolytic) and LNCaP C4-2 (osteoblastic), for actinium-225, astatine-211, and radium-223 and their progeny, using Monte Carlo simulations with the GATE/Geant4 code.Approach.We developed single cell and cell clusters models to Monte Carlo simulations, performed on the GATE platform version 9.3, with the GEANT4-DNA physics list emstandard_opt3_mixed_dna for At-211, Ac-225 and Ra-223 progenies. We considered three radionuclide distributions as a sources: the nucleus, the cytoplasm and the whole cell.Main results.When the nucleus was considered as a target, theS-values (N←N) calculated for At-211, Ac-225 and Ra-223 progenies were significantly higher, within 60%-90%, thanS-values (N←Cy), demonstrating less influence of cytoplasm only internalization. When the cytoplasm was considering as a target, theS-values (Cy←Cy) calculated for At-211, Ac-225 and Ra-223 progeny were significantly higher, within 30%-90%, than theS-values (Cy←N). When no progeny migration occurs and for target nucleus , the cumulativeS-values (N←N) calculated for At-211, Ac-225 and Ra-223 were significantly higher, within 50%-70%, than theS-values (N←N) computed for At-211, Ac-225, and Ra-223. Comparing the cumulativeS-values, Ac-225 and Ra-223 therapies is more effective, in terms of deposited energy in a target, than that with At-211.Significance.The data presented in this research indicates that Ac-225 therapy may be the optimum choice due to the energy deposited in the nucleus, as long as the recoil effects and redistribution of progeny are understood. In contrast, At-211 is an alternative to avoid progeny migration. However, to completely analyze the efficacy of radionuclide therapy, other parameters must be considered, such as biological half-life, stability of the transport molecule, progeny migration, excretion pathways, and uptake in different organs.

Mathematical Modeling of Mating Probability and Fertile Egg Production in Helminth Parasites.

In this work, we obtained a general formulation for the mating probability and fertile egg production in helminth parasites, focusing on the reproductive behavior of polygamous parasites and its implications for transmission dynamics. By exploring various reproductive variables in parasites with density-dependent fecundity, such as helminth parasites, we departed from the traditional assumptions of Poisson and negative binomial distributions to adopt an arbitrary distribution model. Our analysis considered critical factors such as mating probability, fertile egg production, and the distribution of female and male parasites among hosts, whether they are distributed together or separately. We show that the distribution of parasites within hosts significantly influences transmission dynamics, with implications for parasite persistence and, therefore, with implications in parasite control. Using statistical models and empirical data from Monte Carlo simulations, we provide insights into the complex interplay of reproductive variables in helminth parasites, enhancing our understanding of parasite dynamics and the transmission of parasitic diseases.

TOPAS-Tissue: A Framework for the Simulation of the Biological Response to Ionizing Radiation at the Multi-Cellular Level.

This work aims to develop and validate a framework for the multiscale simulation of the biological response to ionizing radiation in a population of cells forming a tissue. We present TOPAS-Tissue, a framework to allow coupling two Monte Carlo (MC) codes: TOPAS with the TOPAS-nBio extension, capable of handling the track-structure simulation and subsequent chemistry, and CompuCell3D, an agent-based model simulator for biological and environmental behavior of a population of cells. We verified the implementation by simulating the experimental conditions for a clonogenic survival assay of a 2-D PC-3 cell culture model (10 cells in 10,000 µm2) irradiated by MV X-rays at several absorbed dose values from 0-8 Gy. The simulation considered cell growth and division, irradiation, DSB induction, DNA repair, and cellular response. The survival was obtained by counting the number of colonies, defined as a surviving primary (or seeded) cell with progeny, at 2.7 simulated days after irradiation. DNA repair was simulated with an MC implementation of the two-lesion kinetic model and the cell response with a p53 protein-pulse model. The simulated survival curve followed the theoretical linear-quadratic response with dose. The fitted coefficients α = 0.280 ± 0.025/Gy and ß = 0.042 ± 0.006/Gy2 agreed with published experimental data within two standard deviations. TOPAS-Tissue extends previous works by simulating in an end-to-end way the effects of radiation in a cell population, from irradiation and DNA damage leading to the cell fate. In conclusion, TOPAS-Tissue offers an extensible all-in-one simulation framework that successfully couples Compucell3D and TOPAS for multiscale simulation of the biological response to radiation.

Hybrid organic monolithic column containing MIL-68(Al) for the separation of small molecules by capillary HPLC.

A hybrid organic monolithic column made of poly(lauryl methacrylate-co-1,6-hexanediol dimethacrylate) and the metal-organic framework MIL-68(Al) was prepared for the first time. The column was used in capillary liquid chromatography, both in isocratic and gradient elution modes. Separation performance towards small molecules of different chemical nature (polycyclic aromatic hydrocarbons, alkylbenzenes, phenols, etc.) was studied. Monte Carlo simulations were made to both select the proper precursors to obtain empty metal-organic framework micropores in the monolithic polymer and also, to analyze the potential free access of the studied analytes into the micropores (necessary to improve mass transfer and column efficiency). The hereby synthesized metal-organic framework microcrystals allowed obtaining homogeneous hybrid monolithic columns. Adding of MIL-68(Al) (1030 m2 g-1 BET specific surface area) increased the surface area from 3.9 m2 g-1 for the parent monolith to 18.2 m2 g-1 for the hybrid column containing 8 mg mL-1 of the microcrystals. Chromatographic performance of this new column was evaluated by studying retention factors, resolution, and plate counts at room temperature. Different compounds, not completely resolved in the parent monolith, were partially or completely separated after metal-organic framework addition. Using the monolithic column with only 2 mg mL-1 of MIL-68(Al), five alkylbenzenes were completely separated with very symmetrical peak shapes, resolution factors up to 3.60 and plate counts of 4300 plates m-1 for n-hexylbenzene. This value is higher than those obtained by other authors who used organic monolithic columns with embedded metal-organic frameworks to perform separations at room temperature. Additionally, nine polycyclic aromatic hydrocarbons were partially or completely resolved in gradient elution mode. The hybrid monolithic columns exhibited very good intra-day (%RSD=1.9), inter-day (%RSD=2.6), and column-to-column (%RSD=4.3) reproducibility values. Easy and fast column preparation, and versatility to efficiently separate several compounds of different chemical nature in isocratic and gradient mode, makes this new hybrid column a very good option for the analysis of small molecules in capillary (or nano) HPLC.

Unlocking the power of tobacco taxation to mitigate the social costs of smoking in Mexico: a microsimulation model.

Despite being the most cost-effective tobacco control policy, tobacco taxation is the least implemented component of the World Health Organization MPOWER package to reduce smoking worldwide. In Mexico, both smoking prevalence and taxation have remained stable for more than a decade. This study aims to provide evidence about the potential effects of taxation to reduce the burden of tobacco-related diseases and the main attributable social costs in Mexico, including informal (unpaid) care costs, which are frequently ignored. We employ a first-order Monte Carlo microsimulation model that follows hypothetical population cohorts considering the risks of an adverse health event and death. First, we estimate tobacco-attributable morbidity and mortality, direct medical costs and indirect costs, such as labour productivity losses and informal care costs. Then, we assess the potential effects of a 50% cigarette price increase through taxation and two alternative scenarios of 25% and 75%. The inputs come from several sources, including national surveys and vital statistics. Each year, 63 000 premature deaths and 427 000 disease events are attributable to tobacco in Mexico, while social costs amount to MX$194.6 billion (US$8.5)-MX$116.2 (US$5.1) direct medical costs and MX$78.5 (US$3.4) indirect costs-representing 0.8% of gross domestic product. Current tobacco tax revenue barely covers 23.3% of these costs. Increasing cigarette prices through taxation by 50% could reduce premature deaths by 49 000 over the next decade, while direct and indirect costs averted would amount to MX$87.9 billion (US$3.8) and MX$67.6 billion (US$2.9), respectively. The benefits would far outweigh any potential loss even in a pessimistic scenario of increased illicit trade. Tobacco use imposes high social costs on the Mexican population, but tobacco taxation is a win-win policy for both gaining population health and reducing tobacco societal costs.

Bolus Effect Caused by Use of Thermoplastic Masks in Head and Neck Radiotherapy Treatments.

This paper examines the dosimetric uncertainty arising from the use of thermoplastic masks in the treatment of head and neck cancer through radiotherapy. This study was conducted through Monte Carlo simulations using the Monte Carlo N-Particle eXtended (MCNPX code), and the theoretical results are compared with radiochromic films. Using material characterization techniques, the compounds of the thermoplastic mask were identified, confirming that most of the material corresponds to the polymer C10H16O4. The theoretical results show increases ranging from 42% to 57.4% in the surface absorbed dose for 6 and 15 MV photon beams, respectively, compared to the absorbed dose without the mask. The experimental data corroborate these findings, showing dose increases ranging from 18.4% to 52.1% compared to the expected surface absorbed dose without the mask. These results highlight the need to consider the bolus effect induced by thermoplastic masks during the precise and safe planning and application of radiotherapy treatment in order to ensure its therapeutic efficacy and minimize the associated risks to patients.

A New Mixture Model With Cure Rate Applied to Breast Cancer Data.

We introduce a new modelling for long-term survival models, assuming that the number of competing causes follows a mixture of Poisson and the Birnbaum-Saunders distribution. In this context, we present some statistical properties of our model and demonstrate that the promotion time model emerges as a limiting case. We delve into detailed discussions of specific models within this class. Notably, we examine the expected number of competing causes, which depends on covariates. This allows for direct modeling of the cure rate as a function of covariates. We present an Expectation-Maximization (EM) algorithm for parameter estimation, to discuss the estimation via maximum likelihood (ML) and provide insights into parameter inference for this model. Additionally, we outline sufficient conditions for ensuring the consistency and asymptotic normal distribution of ML estimators. To evaluate the performance of our estimation method, we conduct a Monte Carlo simulation to provide asymptotic properties and a power study of LR test by contrasting our methodology against the promotion time model. To demonstrate the practical applicability of our model, we apply it to a real medical dataset from a population-based study of incidence of breast cancer in São Paulo, Brazil. Our results illustrate that the proposed model can outperform traditional approaches in terms of model fitting, highlighting its potential utility in real-world scenarios.

Diclofenac sodium adsorption on activated carbon: experimental, modeling and bayesian statistics.

The present study modeled the adsorption process of the drug diclofenac sodium on activated charcoal. For this purpose, a mass balance-based model was used considering a fixed bed column. The mass transfer rate in the solid phase was represented by a driving force model proposed in this study, and a gamma exponent with a range of 0 > γ ≤ 2 was assigned to the model. Different isotherms were adopted to represent the equilibrium at the solid/liquid interface: the Langmuir, Freundlich, Sips and Redlich-Peterson isotherms. The modeling was approached from the perspective of Bayesian statistics, and the Markov chain Monte Carlo method was used for parameter estimation. Model validation was performed with experimental data obtained under different operating conditions of initial concentration ($C_{0.

Where do we invest money to implement active learning on caries detection? An economic evaluation.

This trial-based economic evaluation aimed to estimate the incremental cost of implementing an active learning strategy (theoretical-practical workshop) to substitute the didactic lecture as the sole method for students training in caries detection. We also provided a budget impact analysis and explored the composition of costs related to the activity. Data from the coordinating centre of a multicentre randomized and controlled study (IuSTC01) was analyzed as the first part of our main economic analysis plan. The perspective of the educational provider (the institution implementing the activity) was considered, and an immediate time horizon was adopted. All used resources were valued in Brazilian Real by adopting a microcosting strategy. Costs for each strategy were estimated and converted into international dollars. The incremental Cost per student and the total cost of implementing the complete teaching strategy for 80 students were calculated. Monte Carlo simulations were used to estimate the uncertainties. The incremental Cost estimated for the workshop implementation would be $7.93 per student (interquartile range (IQR): $7.8-8.1), and the total cost of the teaching activity would be $684 (IQR:672-696). The laboratory training comprised more than 50% of the total amount spent, and a higher percentage of this value was related to human resources costs (72%). Saving 40% of the costs could be expected for the next rounds of activities in the institution, assuming no need for additional preparation of didactic materials and tutor training. A modest incremental cost per student and an acceptable organizational budget impact should be expected for the institution when including active learning training in caries detection for undergraduate students, mainly related to the human resources involved.

Simplified and Detailed Evaluations of the Uncertainty of the Measurement of Microbiological Contamination of Pharmaceutical Products.

BACKGROUND: The control of the microbial contamination of pharmaceutical products (PP) is crucial to ensure their safety and efficacy. The validity of the monitoring of such contamination depends on the uncertainty of this quantification. Highly uncertain quantifications due to the variability of determinations or the magnitude of systematic effects affecting microbial growth or other analytical operations make analysis unfit for the intended use. The quantification of the measurement uncertainty expressing the combined effects of all random and systematic effects affecting the analysis allows for a sound decision about quantification adequacy for their intended use. The complexity of the quantification of microbial analysis uncertainty led to the development of simplified ways of performing this evaluation. OBJECTIVE: This work assesses the adequacy of the simplified quantification of the uncertainty of the determination of the microbial contamination of PP by log transforming microbial count and dilution factor of the test sample whose uncertainty is combined in a log scale using the uncertainty propagation law. METHODS: This assessment is performed by a parallel novel bottom-up and accurate evaluation of microbial analysis uncertainty involving the Monte Carlo method simulation of the Poisson log-normal distribution of counts and of the normally distributed measured volumes involved in the analysis. Systematic effects are assessed and corrected on results to compensate for their impact on the determinations. Poisson regression is used to predict precision affecting determinations on unknown test samples. RESULT: Simplified and detailed models of the uncertainty of the measurement of the microbial contamination of PP are provided, allowing objective comparisons of several determinations and those with a maximum contamination level. CONCLUSIONS: This work concludes that triplicate determinations are required to produce results with adequately low uncertainty and that simplified uncertainty quantification underevaluates or overevaluates the uncertainty from determinations based on low or high colony numbers, respectively. Therefore, detailed uncertainty evaluations are advised for determinations between 50 and 200% of PP's maximum admissible contamination value. HIGHLIGHT: User-friendly tools for detailed and simplified evaluations of the uncertainty of the measurement of microbial contamination of PP are provided together with the understanding of when simplifications are adequate.

Bayesian inverse problem for a fractional diffusion model of cell migration.

In the present work, both direct and inverse problems are considered for a Fisher-type fractional diffusion equation, which is proposed to describe the phenomenon of cell migration. For the direct problem, a solution is given via the Fourier method and the Laplace transform. On the other hand, we solved the inverse problem from a Bayesian statistical framework using a set of data that are the result of a cell migration experiment on a wound closure assay. We estimated the parameters of the mathematical model via Markov Chain Monte Carlo methods.

Economic and financial viability of a pig farm in central semi-tropical Mexico: 2022-2026 prospective.

To estimate the economic and financial viability of a pig farm in central sub-tropical Mexico within a 5-year planning horizon, a Monte Carlo simulation model was utilized. Net returns were projected using simulated values for the distribution of input and product processes, establishing 2021 as base scenario. A stochastic modelling approach was employed to determine the economic and financial outlook. The findings reveal a panorama of economic and financial viability. Net income increased by 555%, return on assets rose from 3.36% in 2022 to 11.34% in 2026, and the probability of decapitalization dropped from 58% to 13%, respectively in the aforesaid periods. Similarly, the probability of obtaining negative net income decreased from 40% in 2022 to 18% in 2026. The technological, productive, and economic management of the production unit allowed for a favorable scenario within the planning horizon. There is a growing interest in predicting the economic sectors worth investing in and supporting, considering their economic and development performance. This research offers both methodological and scientific evidence to demonstrate the feasibility of establishing a planning schedule and validating the suitability of the pork sector for public investment and support.

Arsenic and fluoride in groundwater triggering a high risk: Probabilistic results using Monte Carlo simulation and species sensitivity distribution.

The widespread presence of arsenic (As) and fluoride (F-) in groundwater poses substantial risks to human health on a global scale. These elements have been identified as the most prevalent geogenic contaminants in groundwater in northern Mexico. Consequently, this study aimed to evaluate the human health and ecological risks associated with the content of As and F- in the Meoqui-Delicias aquifer, which is in one of Mexico's most emblematic irrigation districts. Concentrations of As and F- were measured in 38 groundwater samples using ICP-MS and ion chromatography, respectively. Overall, these elements showed a similar trend across the aquifer, revealing a positive correlation between them and pH. The concentration of As and F- in the groundwater ranged from 5.3 µg/L to 303 µg/L and from 0.5 mg/L to 8.8 mg/L, respectively. Additionally, the levels of As and F- surpassed the established national standards for safe drinking water in 92% and 97% of samples, respectively. Given that groundwater is used for both agricultural purposes and human activities, this study also assessed the associated human health and ecological risks posed by these elements using Monte Carlo simulation and Species Sensitivity Distribution. The findings disclosed a significant noncarcinogenic health risk associated with exposure to As and F-, as well as an unacceptable carcinogenic health risk to As through water consumption for both adults and children. Furthermore, a high ecological risk to aquatic species was identified for F- and high to medium risks for As in the sampling sites. Therefore, the findings in this study provide valuable information for Mexican authorities and international organizations (e.g., WHO) about the adverse effects that any exposure without treatment to groundwater from this region represents for human health.

Monte Carlo simulation for photon energy response from the RADOS dosemeter.

Ionizing radiation interaction models are commonly included in Monte Carlo codes. However, as there are different models and different output quantities available, it is important to understand the physical phenomena used. So, the aim of this study is to analyze the photon interaction model called Simple Physical Treatment of the Monte Carlo code MCNPX to estimate the energy dependence of photons from the RADOS dosemeter and to validate this calculation method by comparing it with experimental results found in the literature. The energy deposition in the MTS-N detector and the air kerma were obtained accompanied by their uncertainties, which varied between 1.5% and 3.0%. The RADOS dosemeter simulation and the calculation methodology applied in this study have been validated. Therefore, when using the Simple Physical Treatment model, the effective dose can be corrected by a correction factor calculated from the simulated results.

Cost-effectiveness of restorative treatments for permanent molars with severe molar incisor hypomineralization: perspectives for the Brazilian public health system.

OBJECTIVES: To undertake a cost-effectiveness analysis of restorative treatments for a first permanent molar with severe molar incisor hypomineralization from the perspective of the Brazilian public system. MATERIALS AND METHODS: Two models were constructed: a one-year decision tree and a ten-year Markov model, each based on a hypothetical cohort of one thousand individuals through Monte Carlo simulation. Eight restorative strategies were evaluated: high viscosity glass ionomer cement (HVGIC); encapsulated GIC; etch and rinse adhesive + composite; self-etch adhesive + composite; preformed stainless steel crown; HVGIC + etch and rinse adhesive + composite; HVGIC + self-etch adhesive + composite, and encapsulated GIC + etch and rinse adhesive + composite. Effectiveness data were sourced from the literature. Micro-costing was applied using 2022 USD market averages with a 5% variation. Incremental cost-effectiveness ratio (ICER), net monetary benefit (%NMB), and the budgetary impact were obtained. RESULTS: Cost-effective treatments included HVGIC (%NMB = 0%/ 0%), encapsulated GIC (%NMB = 19.4%/ 19.7%), and encapsulated GIC + etch and rinse adhesive + composite (%NMB = 23.4%/ 24.5%) at 1 year and 10 years, respectively. The benefit gain of encapsulated GIC + etch and rinse adhesive + composite in relation to encapsulated GIC was small when compared to the cost increase at 1 year (gain of 3.28% and increase of USD 24.26) and 10 years (gain of 4% and increase of USD 15.54). CONCLUSION: Within the horizon and perspective analyzed, the most cost-effective treatment was encapsulated GIC restoration. CLINICAL RELEVANCE: This study can provide information for decision-making.

A Mathematical Model for the Impact of 3HP and Social Programme Implementation on the Incidence and Mortality of Tuberculosis: Study in Brazil.

In this paper, we presented a mathematical model for tuberculosis with treatment for latent tuberculosis cases and incorporated social implementations based on the impact they will have on tuberculosis incidence, cure, and recovery. We incorporated two variables containing the accumulated deaths and active cases into the model in order to study the incidence and mortality rate per year with the data reported by the model. Our objective is to study the impact of social program implementations and therapies on latent tuberculosis in particular the use of once-weekly isoniazid-rifapentine for 12 weeks (3HP). The computational experimentation was performed with data from Brazil and for model calibration, we used the Markov Chain Monte Carlo method (MCMC) with a Bayesian approach. We studied the effect of increasing the coverage of social programs, the Bolsa Familia Programme (BFP) and the Family Health Strategy (FHS) and the implementation of the 3HP as a substitution therapy for two rates of diagnosis and treatment of latent at 1% and 5%. Based of the data obtained by the model in the period 2023-2035, the FHS reported better results than BFP in the case of social implementations and 3HP with a higher rate of diagnosis and treatment of latent in the reduction of incidence and mortality rate and in cases and deaths avoided. With the objective of linking the social and biomedical implementations, we constructed two different scenarios with the rate of diagnosis and treatment. We verified with results reported by the model that with the social implementations studied and the 3HP with the highest rate of diagnosis and treatment of latent, the best results were obtained in comparison with the other independent and joint implementations. A reduction of the incidence by 36.54% with respect to the model with the current strategies and coverage was achieved, and a greater number of cases and deaths from tuberculosis was avoided.

Age and growth of the blue shark Prionace glauca (Linnaeus, 1758) in the Ecuadorian Pacific: Bayesian multi-models.

The blue shark Prionace glauca plays a critical role as a predator in marine ecosystems but is threatened by by-catch. To obtain more precise biological data, a Bayesian approach was used, and 536 vertebrae samples collected during 1 year at the landing stage called "Playita Mía" Manta, Ecuador, were analysed. The objective was to estimate the age and growth parameters of the species. The size of the specimens varied between 116 and 310 cm in total length (TL). Using a Bayesian approach based on the Markov Chain Monte Carlo (MCMC) method, growth parameters were evaluated. The von Bertalanffy model was the one that best fitted the data and provided more adequate estimates (females: L ∞ = 325.50 cm, L 0 = 53.23 cm, and k = 0.12 years; males: L ∞ = 331.47 cm, L 0 = 51.59 cm, k = 0.12 years -1; combined sexes: L ∞ = 329.65 cm, L 0 = 53.64 cm, k = 0.11 year-1). The results indicated that females and males have a similar growth, and that the species has a slow growth. Further studies using multi-model Bayesian approaches and covering a broader range of sizes in the Pacific Ocean are suggested. These studies will provide crucial information for the management and conservation of this species.

Calibration system correction factor for measuring the reference air kerma rate (RAKR) applied to high dose rate192Ir sources (HDR).

The aim of this study was to use computer simulation to analyze the impact of the aluminum fixing support on the Reference Air Kerma (RAK), a physical quantity obtained in a calibration system that was experimentally developed in the Laboratory of Radiological Sciences of the University of the State of Rio de Janeiro (LCR-UERJ). Correction factors due to scattered radiation and the geometry of the192Ir sources were also sought to be determined. The computational simulation was validated by comparing some parameters of the experimental results with the computational results. These parameters were: verification of the inverse square law of distance, determination of (RAKR), analysis of the source spectrum with and without encapsulation, and the sensitivity curve of the Sourcecheck 4PI ionization chamber response, as a function of the distance from the source along the axial axis, using the microSelectron-v2 (mSv2) and GammaMedplus (GMp) sources. Kerma was determined by activity in the Reference air, with calculated values of 1.725 × 10-3U. Bq-1and 1.710 × 10-3U. Bq-1for the ionization chamber NE 2571 and TN 30001, respectively. The expanded uncertainty for these values was 0.932% and 0.919%, respectively, for a coverage factor (k = 2). The correction factor due to the influence of the aluminum fixing support for measurements at 1 cm and 10 cm from the source was 0.978 and 0.969, respectively. The geometric correction factor of the sources was ksg= 1.005 with an expanded uncertainty of 0.7% for a coverage factor (k = 2). This value has a difference of approximately 0.2% compared to the experimental values.

Dosimetry of Large Field Valencia applicators for Cobalt-60-based brachytherapy.

BACKGROUND: Non-melanoma skin cancer is one of the most common types of cancer and one of the main approaches is brachytherapy. For small lesions, the treatment of this cancer with brachytherapy can be done with two commercial applicators, one of these is the Large Field Valencia Applicators (LFVA). PURPOSE: The aim of this study is to test the capabilities of the LFVA to use clinically 60Co sources instead of the 192Ir ones. This study was designed for the same dwell positions and weights for both sources. METHODS: The Penelope Monte Carlo code was used to evaluate dose distribution in a water phantom when a 60Co source is considered. The LFVA design and the optimized dwell weights reported for the case of 192Ir are maintained with the only exception of the dwell weight of the central position, that was increased. 2D dose distributions, field flatness, symmetry and the leakage dose distribution around the applicator were calculated. RESULTS: When comparing the dose distributions of both sources, field flatness and symmetry remain unchanged. The only evident difference is an increase of the penumbra regions for all depths when using the 60Co source. Regarding leakage, the maximum dose within the air volume surrounding the applicator is in the order of 20% of the prescription dose for the 60Co source, but it decreases to less than 5% at about 1 cm distance. CONCLUSIONS: Flatness and symmetry remains unaltered as compared with 192Ir sources, while an increase in leakage has been observed. This proves the feasibility of using the LFVA in a larger range of clinical applications.

Statistical analysis of parameters and adsorption isotherm models.

The present work intends to discuss parameter estimation and statistical analysis in adsorption. The Langmuir and Tóth isotherm models are compared for a set of carbon dioxide adsorption data on 13X zeolite from literature at different temperatures: 303, 323, 373, and 423 K. Statistical analyses were performed under frequentist and Bayesian perspectives. Under the frequentist statistical view, parameters were estimated using Maximum Likelihood estimation (MLE). Statistical analyses of parameters were performed by confidence regions in terms of elliptical approximation and likelihood region, while the evaluation of models was performed by chi-square statistics. The results showed that, for these nonlinear models, the elliptical region offers a poor approximation of the parameter estimates' confidence region, especially for the most correlated parameter pairs. Additionally, the four-parameter Tóth's equation yields less correlated parameters than the three-parameter Langmuir model. From a Bayesian perspective, the Markov chain Monte Carlo (MCMC) technique facilitated the reconstruction of the probability density functions of parameters as well as enabled the propagation of parametric uncertainties in the model responses. Finally, the accurate assessment of experimental uncertainty significantly influences the evaluation of models and their respective parameters.