A mechanistic simulation of induced DNA damage in a bacterial cell by X- and gamma rays: a parameter study

Mechanistic Monte Carlo simulations calculating DNA damage caused by ionizing radiation are highly dependent on the simulation parameters. In the present study, using the Geant4-DNA toolkit, the impact of different parameters on DNA damage induced in a bacterial cell by X- and gamma-ray irradiation was investigated. Three geometry configurations, including the simple (without DNA details), the random (a random multiplication of identical DNA segments), and the fractal (a regular replication of DNA segments using fractal Hilbert curves), were simulated. Also, three physics constructors implemented in Geant4-DNA, i.e., G4EmDNAPhysics_option2, G4EmDNAPhysics_option4, and G4EmDNAPhysics_option6, with two energy thresholds of 17.5 eV and 5-37.5 eV were compared for direct DNA damage calculations. Finally, a previously developed mathematical model of cell repair called MEDRAS (Mechanistic DNA Repair and Survival) was employed to compare the impact of physics constructors on the cell survival curve. The simple geometry leads to undesirable results compared to the random and fractal ones, highlighting the importance of simulating complex DNA structures in mechanistic simulation studies. Under the same conditions, the DNA damage calculated in the fractal geometry was more consistent with the experimental data. All physics constructors can be used alternatively with the fractal geometry, provided that an energy threshold of 17.5 eV is considered for recording direct DNA damage. All physics constructors represent a similar behavior in generating cell survival curves, although the slopes of the curves are different. Since the inverse of the slope of a bacterial cell survival curve (i.e., the D10-value) is highly sensitive to the simulation parameters, it is not logical to determine an optimal set of parameters for calculating the D10-value by Monte Carlo simulation.

Nitrates in industrial and traditional tomato paste from Arsenjan City, Iran: a health risk assessment study

A comprehensive approach was used for the first time to measure NO3- risk in tomato paste consumption; besides a robust deterministic and probabilistic method was used. The mean levels of NO3- in homemade and industrial tomato paste were 7.36 mg/kg and 43.69 mg/kg, respectively. The Monte Carlo simulation confirmed that these values were below normal levels (HQ less than 1). The sensitivity analysis displayed that FIR was the main factor affecting the risk to human health in both groups. The interactive plot demonstrated the interaction between C and IR for children and adults in both types of tomato paste. This study concludes that NO3- ingestion due to tomato paste consumption poses no significant health risk. However, considering that food and water constitute the primary sources of NO3- intake, continuous monitoring is recommended due to potential health risks associated with excessive NO3- consumption, including certain forms of cancer.

Establishing error bounds for internal calibration of quantitative computed tomography

Opportunistic computed tomography (CT) scans, which can assess relevant osteoporotic bones of interest, offer a potential solution for identifying osteoporotic individuals. CT scans usually do not contain calibration phantoms, so internal calibration methods have been developed to create a voxel-specific density calibration that can be used in opportunistic CT. It remains a challenge, however, to account for potential sources of error in internal calibration, such as beam hardening or heterogeneous internal reference tissues. The purpose of this work was to introduce our internal calibration method that accounts for these variations and to estimate error bounds for the bone mineral density (BMD) measurements taken from internally calibrated scans. The error bounds are derived by incorporating a combination of a Monte Carlo simulation and standard error propagation into our previously established internal calibration method. A cohort of 138 clinical abdominal CT scans were calibrated for BMD assessment with a phantom placed in the field of view and used as the ground truth. Our modified internal calibration method provided error bounds on the same images and was tested to contain the ground truth phantom-calibrated BMD. This was repeated using 10 different internal reference tissue combinations to explore how error bounds are affected by the choice of internal tissue referents. We found that the tissue combination of air, skeletal muscle, and cortical bone yielded the most accurate BMD estimates while maintaining error bounds that were sufficiently conservative to account for sources of error such as beam hardening and heterogeneous tissue samples. The mean difference between the phantom BMD and the BMD resulting from the tissue combination of air, skeletal muscle and cortical bone was 2.12 mg/cc (0.06% BMD error) and 1.13 mg/cc (0.02 % BMD error) for the left and right femur, respectively. Providing error bounds for internal calibration provides a method to explore the influence of internal reference tissues and confidence for BMD estimates.

Tractography passes the test: Results from the diffusion-simulated connectivity (disco) challenge

Estimating structural connectivity from diffusion-weighted magnetic resonance imaging is a challenging task, partly due to the presence of false-positive connections and the misestimation of connection weights. Building on previous efforts, the MICCAI-CDMRI Diffusion-Simulated Connectivity (DiSCo) challenge was carried out to evaluate state-of-the-art connectivity methods using novel large-scale numerical phantoms. The diffusion signal for the phantoms was obtained from Monte Carlo simulations. The results of the challenge suggest that methods selected by the 14 teams participating in the challenge can provide high correlations between estimated and ground-truth connectivity weights, in complex numerical environments. Additionally, the methods used by the participating teams were able to accurately identify the binary connectivity of the numerical dataset. However, specific false positive and false negative connections were consistently estimated across all methods. Although the challenge dataset doesn't capture the complexity of a real brain, it provided unique data with known macrostructure and microstructure ground-truth properties to facilitate the development of connectivity estimation methods.

A probabilistic bias analysis on the magnitude of unmeasured confounding: The impact of driving mileage on road traffic crashes

INTRODUCTION

Unmeasured confounding can lead to biased interpretations of empirical findings. This paper aimed to assess the magnitude of suspected unmeasured confounding due to driving mileage and simulate the statistical power required to detect a discrepancy in the effect of polypharmacy on road traffic crashes (RTCs) among older adults.

METHODS

Based on Monte Carlo Simulation (MCS) approach, we estimated 1) the magnitude of confounding of driving mileage on the association of polypharmacy and RTCs and 2) the statistical power of to detect a discrepancy from no adjusted effect. A total of 1000 studies, each of 500000 observations, were simulated.

RESULTS

Under the assumption of a modest adjusted exposure-outcome odds ratio of 1.35, the magnitude of confounding bias by driving mileage was estimated to be 16% higher with a statistical power of 50%. Only an adjusted odds ratio of at least 1.60 would be associated with a statistical power of about 80% CONCLUSION: This applied probabilistic bias analysis showed that not adjusting for driving mileage as a confounder can lead to an overestimation of the effect of polypharmacy on RTCs in older adults. Even considering a large sample, small to moderate adjusted exposure effects were difficult to be detected.

mvLognCorrEst: an R package for sampling from multivariate lognormal distributions and estimating correlations from uncomplete correlation matrix

BACKGROUND AND OBJECTIVE

Pharmacometrics (PMX) is a quantitative discipline which supports decision-making processes in all stages of drug development. PMX leverages Modeling and Simulations (M&S), which represents a powerful tool to characterize and predict the behavior and the effect of a drug. M&S-based methods, such as Sensitivity Analysis (SA) and Global Sensitivity Analysis (GSA), are gaining interest in PMX as they allow the evaluation of model-informed inference quality. Simulations should be correctly designed to obtain reliable results. Neglecting correlations between model parameters can significantly alter the results of simulations. However, the introduction of a correlation structure between model parameters can cause some issues. Sampling from a multivariate lognormal distribution, which is the typically distribution assumed for PMX model parameters, is not straightforward when a correlation structure is introduced. Indeed, correlations need to respect some constraints which depend by the CVs (i.e., coefficients of variation) of lognormal variables. In addition, when correlation matrices have some unspecified values, they should be properly fixed preserving the positive semi-definiteness of the correlation structure. In this paper, we present mvLognCorrEst, an R package developed to address these issues.

METHODS

The proposed sampling strategy was based on reconducting the extraction from the multivariate lognormal distribution of interest to the underlying Normal distribution. However, with high lognormal CVs, a positive semi-definite Normal covariance matrix cannot be obtained due to the violation of some theoretical constraints. In these cases, the Normal covariance matrix was approximated to its nearest positive definite matrix using Frobenius norm as matrix distance. For the estimation of unknown correlations terms, the graph theory was used to represent the correlation structure as weighed undirected graph. Plausible value ranges for the unspecified correlations were derived considering the paths between variables. Then, their estimation was performed by solving a constrained optimization problem.

RESULTS

Package functions are presented and applied on a real case study, that is the GSA of a PMX model that has been recently developed to support preclinical oncological studies.

CONCLUSIONS

mvLognCorrEst package is an R tool to support simulation-based analysis for which sampling from multivariate lognormal distributions with correlated variables and/or estimation of partially defined correlation matrix are required.

Impact of Climate Variables Change on the Yield of Wheat and Rice Crops in Iran (Application of Stochastic Model Based on Monte Carlo Simulation)

This study aims to predict the yield of two strategic crops in Iran; wheat and rice, under climate scenarios that indicate probable changes in climate variables. It implemented by a stochastic model based on the Monte Carlo method. This model were estimated based on historical data from 1988 to 2019 for precipitation and temperature provided possible changes in the pattern of and their probability of occurrence. The results show that rain-fed wheat, irrigated wheat and rice yields decrease by 42%, 29% and 21% respectively in the average scenario. Therefore, policy makers should try to make the right decisions to increase the production of the country's strategic crops. R&D management to introduce drought-tolerant varieties, use of modern irrigation systems and use of low-volume irrigation methods are some of the proposed solutions to mitigate the effects of climate change.

Progress of triazole antifungal agent posaconazole in individualized therapy

WHAT IS KNOWN AND OBJECTIVE

Posaconazole is the second-generation triazole antifungal agent with widespread clinical application. Posaconazole exposure is influenced by various factors such as drug interactions, disease state and diet, resulting in a high interindividual variability in many patients and failure to ensure therapeutic efficacy. Therefore, it is necessary to conduct individualized therapy on posaconazole to ensure the efficacy and safety of treatment.

METHODS

Articles were identified through PubMed using the keywords such as "posaconazole," "therapeutic drug monitoring" and "Population pharmacokinetics" from 1 January 2001 to 30 April 2022.

RESULTS AND DISCUSSION

In this paper, we review the individualized treatment studies of posaconazole from the three aspects of therapeutic drug monitoring, population pharmacokinetic study and Monte Carlo simulation to provide reference for in-depth individualized posaconazole dosing studies.

WHAT IS NEW AND CONCLUSION

This review suggests that therapeutic drug monitoring should be performed in patients taking posaconazole to adjust the dosage and assess the efficacy and cost-effectiveness of posaconazole under different clinical conditions and different dosing regimens through Monte Carlo simulations. In the future, a more detailed delineation and comprehensive examination of posaconazole PPK for specific populations requires further study.

Human health risk assessment using Monte Carlo simulations for groundwater with uranium in southern India

Uranium naturally occurs in groundwater and its concentration is mostly controlled by the geology of an area. The regular human consumption of groundwater with uranium causes health effects and hence the assessment of radiological and chemical toxicity effects on humans is essential. Hence, the present study was carried out to assess the general hydrochemistry of groundwater in different geological formations of southern India and its relation to uranium as well as to estimate the health risks posed to humans due to consumption of groundwater with uranium using both deterministic and probabilistic approaches. Four river basins representing the major geological formations of southern India were chosen for this study, from where a total of 141 groundwater samples were collected in the year 2016 and analyzed for the concentration of major ions and uranium. The groundwater occurring in granites had high concentration of uranium followed by gneiss and charnockites. Radiological risks to humans were higher in granitic terrain of Bhima basin, where about 1 in 10,000 may get affected due to cancer. The chemical toxicity risks were higher for the people in granite and gneissic terrain of Bhima basin followed by the people in charnockite terrain of Vaniyar basin. The deterministic method has overestimated the actual risk in comparison to the probabilistic risk assessment. The sensitivity analysis indicates that increase of exposure frequency and ingestion rates increases the chemical risks, whereas decrease of body weight increases the chemical risk. Therefore, the probabilistic approach is much superior to deterministic method since it exhibits variability in the values. The current study highlights the risks to humans by consuming groundwater with uranium, emphasizing on the urgent need for supplying treated water to the community.

Health risk assessment and heavy metal accumulation in fish species (Clarias gariepinus and Sarotherodon melanotheron) from industrially polluted Ogun and Eleyele Rivers, Nigeria

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Concentration of Arsenic and Cadmium in the fish tissues exceed the limits set by the European Union.

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THQ values indicated likely adverse effects during a person’s lifetime with continuous exposure to Arsenic and Cadmium.

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As, Cd, and Nickel may pose cancer risk to consumer of fish from the two rivers over longtime exposure.

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Cancer risk due to long time consumption of fish from the rivers can be a major concern.

Ogun and Eleyele Rivers are in the Western part of Nigeria with a potential risk of heavy metal pollution because of many industrial wastes channeling through their courses. Therefore, in this study, the concentration of heavy metals and the possible human health risk of consuming Clarias gariepinus and Sarotherodon melanotheron collected from industrially polluted Ogun and Eleyele Rivers in Nigeria were evaluated.

The concentration of arsenic (As), cadmium (Cd), cobalt (Co), chromium (Cr), manganese (Mn), nickel (Ni), and lead (Pb) in tissues (gill, muscle, and liver) of fish was measured using Atomic Absorption Spectroscopy (AAS) and compared with the maximum permissible. The Estimated Daily Intake (EDI), Targeted Hazard Quotient (THQ), and Carcinogenic Risk (CR) of the metals were estimated for the determination of human health risk. Probabilistic predictions of the health risk were performed with Oracle Crystal Ball software.

Results of this study showed that the dry weight concentrations of the metals in the gills, liver, and muscle of the two fish species from the two sites were well below the permissible limits set by the joint FAO/WHO Expert Committee. Only the EDI for arsenic in gills of C. gariepinus obtained from the Ogun River exceeded the set limit. The THQ was >1 for As in the gills and liver of C. gariepinus and S. melanotheron obtained from the Ogun river suggesting non-carcinogenic risk to the consumers. The carcinogenic risk above 10⁻⁶ obtained for As, Cd, and Ni in the tissues of the two fish species suggested cancer risk to the consumers of fish from the two rivers. Consequent to our observation, consumption of fish from the study site presents some public health concerns. Therefore, this study advises routine heavy metal monitoring of fish along these rivers to implement regulatory standards by the government environmental health management agencies.

Risk Assessment for Oral Bioaccessibility of Lead and Cadmium in the Potato Growing in Smelter-Impacted Soil

Smelting activities are an important source of heavy metals in soil. More seriously, oral ingestion of crops growing in contaminated soil potentially cause harmful effects on human health. The main purpose of this study is to apply the in vitro model (PBET) and Monte Carlo Simulation (MSC) to the health risk assessment process in order to more accurately and realistically evaluate health risks of residents eating contaminated potato. Results indicated in the raw and cooked potato, the bioaccessibility of Pb was 65.9% and 74.5%, and that of Cd was 79.6% and 61.7%, respectively. Additionally, the bioaccessible hazard quotient (BHQ) was less than the permitted level except for the BHQ of Pb for children. This indicated there wasn't potential non-carcinogenic risk for most potato-consumers but the dietary exposure risk for local children cannot be neglected. Sensitivity analysis showed that the bioaccessibility and ingestion rate appeared decisive with respect to potentially deleterious health effects.

Spatial distribution and correlations among elements in smaller than 75 μm street dust: ecological and probabilistic health risk assessment

This study aimed to investigate spatial distribution, correlations among elements and ecological and probabilistic health risk assessment in smaller than 75 μm street dust in Kerman city, Iran. Street dust samples were collected from 35 different points. Elements were detected by ICP-AES. Pollution degree was characterized through Enrichment Factor (EF), Contamination Factor (CF), Geo-accumulation Index (Igeo) and Potential Ecological Risk (PER). The health risk was assessed using the Monte Carlo simulation method. The mean values of elements were in the order of Al > Mn > Zn > Cu > V > Pb > Cr > Ni > Li > As > Co > Mo > Sb > Cd > Ag. The results of Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) showed that Al, As, Co, Li, Mn and V were possibly derived from natural sources (local soil), while traffic and mining activities were proposed as the main source of Cd, Cr, Cu, Mo, Ni, Pb, Sb and Zn. The order of EF and CF mean values decreased as follows: Mn > Ag > Cu > Zn > Pb > Sb > Mo > Li > Co > V > Cd > As > Cr > Ni. In addition, 73% of Cu and 35% of Zn, Ag and Mn had significant enrichment in the street dust samples. Also, Ag and Mn were categorized in the significant and very significant pollution category. In terms of the PER index, all samples could be classified at low-risk category. Ingestion of street dust was the significant route for exposure of residents of Kerman to the elements studied. No significant ecological hazards and health risks were observed from street dust in the study area in the period of the study. The improvement in the fuels quality and development of green spaces can be suggested to control natural and anthropogenic street dust pollution sources in the Kerman city.

Characterization of Gamma Knife Perfexion™ source based on Monte Carlo simulation

This study is aimed at characterizing a single Cobalt-60 source capsule of the Gamma Knife Perfexion™ unit using the BEAMnrc Monte Carlo code. The Gamma Knife Perfexion™ source capsule was modeled using the BEAMnrc user code according to the manufacturer's technical details. The modeled parts include the source, the area around the source, and the capsule. The cylindrical source is 1 mm in diameter and 17 mm in length, with a physical density (ρ) of 8.9 × 10³ kg/m³. The simulation parameters were an electron cutoff energy (ECUT) of 0.7 meV and photon cutoff energy (PCUT) of 0.01 meV. Energy fluence was calculated on a 0.25 cm diameter scoring plane located 3.1 cm from the source. Simulations were performed with and without the encapsulation of the source to investigate its effect on the spectrum and fluence of emitted gamma rays. The results showed that the influence of source encapsulation on the gamma rays is an increase in the relative number of particles in each energy bin of aggregate gamma rays by 92.36% at 0.23 meV energy and 66.12% at 1.10 meV energy. The secondary gamma rays were found to increase by 94.17% at 0.23 meV energy and 63.74% at 1.10 meV energy. The encapsulation of the source attenuated the gamma rays, which altered the spectrum. The mean energy of the beam increased, thereby exhibiting a beam-hardening effect.

Feasibility of using tungsten functional paper as a thin bolus for electron beam radiotherapy

Containing 80% tungsten by weight, tungsten functional paper (TFP) is a radiation-shielding material that is lightweight, flexible, disposable, and easy to cut. Through experimental measurements and Monte Carlo simulations, we investigated the feasibility of using TFP as a bolus in electron beam radiotherapy. Commercial boluses of thickness 5 and 10 mm and from one to nine layers of TFPs (0.3-2.7 mm) were positioned on the surface of water-equivalent phantoms. The percentage depth dose curves and transverse dose profiles were measured using a 9-MeV electron beam from a clinical linear accelerator. Normalized to the value at the depth of maximum dose without bolus, the relative doses at the phantom surface for no bolus, 5-mm bolus, 10-mm bolus, 1 TFP, 3 TFPs, 6 TFPs, and 9 TFPs were 78%, 88%, 92%, 84%, 92%, 102%, and 112%, respectively; the therapeutic depths corresponding to a 90% dose level were 29.1 mm, 22.7 mm, 17.7 mm, 26.6 mm, 23.2 mm, 19.3 mm, and 15.8 mm, respectively. The TFP contributed to increased skin dose and provided dose uniformity within the target volume. However, it also resulted in increased lateral constriction and penumbra width. The results of Monte Carlo simulation produced similar trends as the experimental measurements. Our findings suggest that using TFP as a novel thin and flexible skin bolus for electron beam radiotherapy is feasible.

Dosimetric characteristics of the INTRABEAM ® system with spherical applicators in the presence of air gaps and tissue heterogeneities

The main aim of this study was to investigate the dosimetric characteristics of the INTRABEAM ® system in the presence of air gaps between the surface of applicators (APs) and tumor bed. Additionally, the effect of tissue heterogeneities was another focus. Investigating the dosimetric characteristics of the INTRABEAM® system is essential to deliver the required dose to the tumor bed correctly and reduce the delivered dose to the ribs and lung. Choosing the correct AP size and fitting it to the lumpectomy cavity is essential to remove the effect of air gaps and avoid inaccurate dose delivery. Consequently, the Geant4 toolkit was used to simulate the INTRABEAM ® system with spherical APs of various sizes. The wall effect of the ion chamber (IC) PTW 34013 used in the present study was checked. The simulations were validated in comparison with measurements, and then used to calculate any inaccuracies in dose delivery in the presence of 4- and 10-mm air gaps between the surface of the APs and the tumor bed. Also, the doses received due to tissue heterogeneities were characterized. It turned out that measurements and simulations were approximately in agreement (± 2%) for all sizes of APs. The perturbation factor introduced by the IC due to differences in graphite-coated polyethylene and air as compared to the phantom material was approximately equal to one for all AP. The greatest relative dose delivery difference was observed for an AP with a diameter of 1.5 cm, i.e., 44% and 70% in the presence of 4- and 10-mm air gaps, respectively. In contrast, the lowest relative dose delivery difference was observed for an AP with a diameter of 5 cm, i.e., 24% and 42% in the presence of 4- and 10-mm air gaps, respectively. Increasing APs size showed a decrease in relative dose delivery difference due to the presence of air gaps. In addition, the undesired dose received by the ribs turned out to be higher when a treatment site closer to the ribs was assumed. The undesired dose received by the ribs increased as the AP size increased. The lung dose turned out to be decreased due to the shielding effect of the ribs, small lung density, and long separation distance from the AP surface.

Size-specific dose estimates for various weighting factors of CTDI equation

Size-specific dose estimate (SSDE) was proposed by the American Association of Physicists in Medicine (AAPM) Task Group 204 to consider the effect of patient size in the x-ray CT dose estimation. Size correction factors to calculate SSDE were derived based on the conventional weighted CT dose index (CTDIw) equation. This study aims to investigate the influence of Bakalyar's and the authors' own CTDIw equations on the size correction factors described by the AAPM Task Group 204, using Monte Carlo simulations. The simulations were performed by modeling four types of x-ray CT scanner designs, to compute the dose values in water for cylindrical phantoms with 8-40 cm diameters. CTDI100 method and the AAPM Task Group 111's proposed method were employed as the CT dosimetry models. Size correction factors were obtained for the computed dose values of various phantom diameters for the conventional, Bakalyar's, and the authors' weighting factors. Maximum difference between the size correction factors for the Bakalyar's weighting factor and those of the AAPM Task Group 204 was 27% for a phantom diameter of 11.2 cm. On the other hand, the size correction factors calculated for the authors' weighting factor were in good agreement with those from the AAPM Task Group 204 report with a maximum difference of 17%. The results indicate that the SSDE values obtained with the authors' weighting factor can be evaluated by using the size correction factors reported by the AAPM Task Group 204, which is currently accepted as a standard.

Environmental radionuclides as contaminants of HPGe gamma-ray spectrometers: Monte Carlo simulations for Modane underground laboratory

The main limitation in the high-sensitive HPGe gamma-ray spectrometry has been the detector background, even for detectors placed deep underground. Environmental radionuclides such as ⁴⁰K and decay products in the ²³⁸U and ²³²Th chains have been identified as the most important radioactive contaminants of construction parts of HPGe gamma-ray spectrometers. Monte Carlo simulations have shown that the massive inner and outer lead shields have been the main contributors to the HPGe-detector background, followed by aluminum cryostat, copper cold finger, detector holder and the lead ring with FET. The Monte Carlo simulated cosmic-ray background gamma-ray spectrum has been by about three orders of magnitude lower than the experimental spectrum measured in the Modane underground laboratory (4800 m w.e.), underlying the importance of using radiopure materials for the construction of ultra-low-level HPGe gamma-ray spectrometers.

Examining publication bias-a simulation-based evaluation of statistical tests on publication bias

Background

Publication bias is a form of scientific misconduct. It threatens the validity of research results and the credibility of science. Although several tests on publication bias exist, no in-depth evaluations are available that examine which test performs best for different research settings.

Methods

Four tests on publication bias, Egger’s test (FAT), p-uniform, the test of excess significance (TES), as well as the caliper test, were evaluated in a Monte Carlo simulation. Two different types of publication bias and its degree (0%, 50%, 100%) were simulated. The type of publication bias was defined either as file-drawer, meaning the repeated analysis of new datasets, or p-hacking, meaning the inclusion of covariates in order to obtain a significant result. In addition, the underlying effect (β = 0, 0.5, 1, 1.5), effect heterogeneity, the number of observations in the simulated primary studies (N = 100, 500), and the number of observations for the publication bias tests (K = 100, 1,000) were varied.

Results

All tests evaluated were able to identify publication bias both in the file-drawer and p-hacking condition. The false positive rates were, with the exception of the 15%- and 20%-caliper test, unbiased. The FAT had the largest statistical power in the file-drawer conditions, whereas under p-hacking the TES was, except under effect heterogeneity, slightly better. The CTs were, however, inferior to the other tests under effect homogeneity and had a decent statistical power only in conditions with 1,000 primary studies.

Discussion

The FAT is recommended as a test for publication bias in standard meta-analyses with no or only small effect heterogeneity. If two-sided publication bias is suspected as well as under p-hacking the TES is the first alternative to the FAT. The 5%-caliper test is recommended under conditions of effect heterogeneity and a large number of primary studies, which may be found if publication bias is examined in a discipline-wide setting when primary studies cover different research problems.

Cost-estimate and proposal for a development impact bond for canine rabies elimination by mass vaccination in Chad

Close to 69,000 humans die of rabies each year, most of them in Africa and Asia. Clinical rabies can be prevented by post-exposure prophylaxis (PEP). However, PEP is commonly not available or not affordable in developing countries. Another strategy besides treating exposed humans is the vaccination of vector species. In developing countries, the main vector is the domestic dog, that, once infected, is a serious threat to humans. After a successful mass vaccination of 70% of the dogs in N'Djaména, we report here a cost-estimate for a national rabies elimination campaign for Chad. In a cross-sectional survey in four rural zones, we established the canine : human ratio at the household level. Based on human census data and the prevailing socio-cultural composition of rural zones of Chad, the total canine population was estimated at 1,205,361 dogs (95% Confidence interval 1,128,008-1,736,774 dogs). Cost data were collected from government sources and the recent canine mass vaccination campaign in N'Djaména. A Monte Carlo simulation was used for the simulation of the average cost and its variability, using probability distributions for dog numbers and cost items. Assuming the vaccination of 100 dogs on average per vaccination post and a duration of one year, the total cost for the vaccination of the national Chadian canine population is estimated at 2,716,359 Euros (95% CI 2,417,353-3,035,081) for one vaccination round. A development impact bond (DIB) organizational structure and cash flow scenario were then developed for the elimination of canine rabies in Chad. Cumulative discounted cost of 28.3 million Euros over ten years would be shared between the government of Chad, private investors and institutional donors as outcome funders. In this way, the risk of the investment could be shared and the necessary investment could be made available upfront - a key element for the elimination of canine rabies in Chad.

Prediction of inter-individual variability on the pharmacokinetics of CYP2C8 substrates in human

Inter-individual variability in pharmacokinetics can lead to unexpected side effects and treatment failure, and is therefore an important factor in drug development. CYP2C8 is a major drug-metabolizing enzyme known to be involved in the metabolism of over 100 drugs. In this study, we predicted the inter-individual variability in AUC/Dose of CYP2C8 substrates in healthy volunteers using the Monte Carlo simulation. Inter-individual variability in the hepatic intrinsic clearance of CYP2C8 substrates (CL_int,h,2C8) was estimated from the inter-individual variability in pharmacokinetics of pioglitazone, which is a major CYP2C8 substrate. The coefficient of variation (CV) of CL_int,h,2C8 was estimated to be 40%. Using this value, the CVs of AUC/Dose of other major CYP2C8 substrates, rosiglitazone and amodiaquine, were predicted to validate the estimated CV of CL_int,h,2C8. As a result, the reported CVs of both substrates were within the 2.5-97.5 percentile range of the predicted CVs. Furthermore, the CVs of AUC/Dose of the CYP2C8 substrates loperamide and chloroquine, which are affected by renal clearance, were also successfully predicted. Combining this value with previously reported CVs of other CYPs, we were able to successfully predict the inter-individual variability in pharmacokinetics of various drugs in clinical.

Proximity effects in chromosome aberration induction by low-LET ionizing radiation

Although chromosome aberrations are known to derive from distance-dependent mis-rejoining of chromosome fragments, evaluating whether a certain model describes such "proximity effects" better than another one is complicated by the fact that different approaches have often been tested under different conditions. Herein, a biophysical model ("BIANCA", i.e. BIophysical ANalysis of Cell death and chromosome Aberrations) was upgraded, implementing explicit chromosome-arm domains and two new models for the dependence of the rejoining probability on the fragment initial distance, r. Such probability was described either by an exponential function like exp(-r/r₀), or by a Gaussian function like exp(-r²/2σ²), where r₀ and σ were adjustable parameters. The second, and last, parameters was the yield of "Cluster Lesions" (CL), where "Cluster Lesion" defines a critical DNA damage producing two independent chromosome fragments. The model was applied to low-LET-irradiated lymphocytes (doses: 1-4Gy) and fibroblasts (1-6.1Gy). Good agreement with experimental yields of dicentrics and centric rings, and thus their ratio ("F-ratio"), was found by both the exponential model (with r₀=0.8μm for lymphocytes and 0.7μm for fibroblasts) and the Gaussian model (with σ=1.1μm for lymphocytes and 1.3μm for fibroblasts). While the former also allowed reproducing dose-responses for excess acentric fragments, the latter substantially underestimated the experimental curves. Both models provided G-ratios (ratio of acentric to centric rings) higher than those expected from randomness, although the values calculated by the Gaussian model were lower than those calculated by the exponential one. For lymphocytes the calculated G-ratios were in good agreement with the experimental ones, whereas for fibroblasts both models substantially underestimated the experimental results, which deserves further investigation. This work suggested that, although both models performed better than a step model (which previously allowed reproducing the F-ratio but underestimated the G-ratio), an exponential function describes proximity effects better than a Gaussian one.

The analysis of an effect of seed propagation on defense strategy against pathogen transmission within clonal plant population using lattice model

Many clonal plants have two breeding systems, vegetative and seed propagation. In vegetative propagation, plants reproduce genetically identical offspring that have lower mortality rates. By contrast, the seed propagated offspring has higher mortality rate, however, the seed propagation acts an important role in maintaining the genetic diversity and reproduce widely. According to the experimental studies, the balance between the breeding systems, vegetative and seed propagation, is determined by several functions, such as resource allocation. The infection and spread of systemic pathogen also affect the optimal balance of the breeding systems. Thus, we examine the effect of invasion of systemic pathogen on the optimal balance of the breeding systems of clonal plant using lattice model in two cases, single population and mixed population. In the analysis, the equilibrium and its local stability were derived using approximation method and numerical simulation in single population. Additionally, two situations were assumed in mixed population, infected and uninfected populations, and the efficacy of seed propagation on the suppression of epidemic infections was examined by comparing the results in the two situations. As a result, seed propagation is an effective defensive behavior against systemic pathogens. In the single population, the plants increase their population by increasing the proportion of seed propagation when the epidemic pathogen has highly infective. In mixed population, the increasing proportion of seed propagation is the optimal breeding strategy to defend against the spread of a systemic pathogen.

Is the Rational Addiction model inherently impossible to estimate?

The Rational Addiction (RA) model is increasingly often estimated using individual level panel data with mixed results; in particular, with regard to the implied rate of time discount. This paper suggests that the odd values of the rate of discount frequently found in the literature may in fact be a consequence of the saddle-point dynamics associated with individual level inter-temporal optimization problems. We report the results of Monte Carlo experiments estimating RA-type difference equations that seem to suggest the possibility that the presence of both a stable and an unstable root in the dynamic process may create serious problems for the estimation of RA equations.

Calibration with MCNP of NaI detector for the determination of natural radioactivity levels in the field

In view of assessing natural radioactivity with on-site quantitative gamma spectrometry, efficiency calibration of NaI(Tl) detectors is investigated. A calibration based on Monte Carlo simulation of detector response is proposed, to render reliable quantitative analysis practicable in field campaigns. The method is developed with reference to contact geometry, in which measurements are taken placing the NaI(Tl) probe directly against the solid source to be analyzed. The Monte Carlo code used for the simulations was MCNP. Experimental verification of the calibration goodness is obtained by comparison with appropriate standards, as reported. On-site measurements yield a quick quantitative assessment of natural radioactivity levels present ((40)K, (238)U and (232)Th). On-site gamma spectrometry can prove particularly useful insofar as it provides information on materials from which samples cannot be taken.

Prompt gamma ray evaluation for chlorine analysis in blended cement concrete

Single prompt gamma ray energy has been evaluated to measure chlorine concentration in fly ash (FA), Super-Pozz (SPZ) and blast furnace slag (BFS) cement concrete specimens using a portable neutron generator-based Prompt Gamma Neutron Activation (PGNAA) setup. The gamma ray yield data from chloride concentration measurement in FA, SPZ and BFS cement concretes for 2.86-3.10, 5.72 and 6.11MeV chlorine gamma rays were analyzed to identify a gamma ray with common slope (gamma ray yield/Cl conc. wt%) for the FA, BFS and SPZ cement concretes. The gamma ray yield data for FA and SPZ cement concretes with varying chloride concentration were measured previously using a portable neutron generator-based PGNAA setup. In the current study, new data have been measured for chlorine detection in the BFS cement concrete using a portable neutron generator-based PGNAA setup for 2.86-3.10, 5.72, and 6.11MeV chlorine gamma rays. The minimum detection limit of chlorine in BFS cement concrete (MDC) was found to be 0.034±0.010, 0.032±0.010, 0.033±0.010 for 2.86-3.10, 5.72 and 6.11MeV gamma ray, respectively. The new BFS cement concrete data, along with the previous measurements for FA and SPZ cement concretes, have been utilized to identify a gamma ray with a common slope to analyze the Cl concentration in all of these blended cement concretes. It has been observed that the 6.11MeV chlorine gamma ray has a common slope of 5295±265 gamma rays/wt % Cl concentration for the portable neutron generator-based PGNAA setup. The minimum detectable concentration (MDC) of chlorine in blended cement concrete was measured to be 0.033±0.010wt % for the portable neutron generator-based PGNAA. Thus, the 6.11MeV chlorine gamma ray can be used for chlorine analysis of blended cement concretes.

Generalized canonical correlation analysis of matrices with missing rows: a simulation study

A method is presented for generalized canonical correlation analysis of two or more matrices with missing rows. The method is a combination of Carroll's (1968) method and the missing data approach of the OVERALS technique (Van der Burg, 1988). In a simulation study we assess the performance of the method and compare it to an existing procedure called GENCOM, proposed by Green and Carroll (1988). We find that the proposed method outperforms the GENCOM algorithm both with respect to model fit and recovery of the true structure.