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Background Rheumatoid arthritis (RA) diagnosis requires interpretation of a combination of clinical, laboratory and imaging investigations. In RA, the consequences of incorrect serology test results are particularly important: patients with False Positive results (FPs) are initially managed as RA patients, bringing about extra costs until a correct diagnosis is made. Objectives The first aim of the study was to evaluate the diagnostic performance of RF-IgA, RF-IgM, and CCP, used alone or in multi-testing parallel or sequential combinations. The secondary goal focused on the economic consequences of serology FPs in selected European countries. Methods 190 established RA patients and 197 controls (either affected by other conditions or healthy donors) were used to assess the diagnostic performance of mono- and multi-serology testing in PC; both testing in Primary Care (PC) and in Secondary Care (SC) settings were considered. For the secondary objective, a 12 month Markov model simulated, from the National Health Services perspective, 1.000 RA-suspected individuals tested in PC and SC with mono- or multi-testing. Costs come from the published literature. The European countries included in the analysis were the United Kingdom, Austria, Belgium, Denmark, France, Germany, Italy, the Netherlands, Portugal, Spain and Sweden. Uncertainty was addressed with sensitivity analysis. Results The mono-testing diagnostic performance was: - RF-IgA: sensitivity [95% CI]=40.5% [33.5%, 47.9%], specificity=92.4% [87.8%, 95.7%]; - RF-IgM: sensitivity=59.0% [51.6%, 66.0%], specificity=89.3% [84.2%, 93.3%]; - CCP: sensitivity=59.5% [52.1%, 66.5%], specificity=96.5% [92.8%, 98.6%]. In multi-testing, defining a “positive result” as “positivity to at least one test” increased sensitivity; “positivity to all the tests” increased specificity. In a PC scenario: - parallel testing: - o using CCP and RF-IgM increased specificity to 99.5% [97.2%, 100.0%]; - o the three tests used simultaneously maximised specificity (100.0% [98.1%, 100.0%]), but reduced sensitivity to 35.8% [29.0%, 43.1%]; - sequential testing: testing positive to both RF-IgA and RF-IgM followed by CCP testing led to 90.7% [81.7%, 96.2%] sensitivity and to 100.0% [54.1%, 100.0%] specificity. With respect to mono-testing, multi-testing options reduced the number of FPs. Therefore, in each of the countries considered, multi-testing allowed for important cost savings due to reduced clinical procedures and resource utilisation of FPs. Conclusions Multi-serology testing improve the diagnostic accuracy of the individual RF-IgA, RF-IgM and CCP tests. Optimal multi-testing combinations minimise the number of FPs, thus reducing avoidable costs to the National Health Services. Consequently, multi-testing for RA demonstrates superior value from patient and payer perspective. References [1] Hallert E, et al. Rheumatology2006;45(3):325–331. [2] Lajas C, et al. Arthritis Rheum2003;49(1):64–70. [3] Lundkvist J, et al. Eur J Health Econ 2008;(Suppl 2):S49–60. [4] Verstappen SM, et al. Ann Rheum Dis2004;63(7):817–24. Disclosure of Interest B. Mascialino Employee of: Thermo Fisher Scientific, S. Swiniarski Employee of: Thermo Fisher Scientific, I. Gehring Employee of: Thermo Fisher Scientific, M. Poorafshar Employee of: Thermo Fisher Scientific

Aims: To quantify and model mathematically the effects on the subjectssleepwake cycle, alertness, and performance of the sleep phase shift due to working at times of the day when sleep propensity is high. Methodologi es: Thirty-seven police officers working on a fast counterclockwise schedule, filled for 25 consecutive days a self -administered questionnaire about the previous night sleep, subjective fatigue, sleep attacks, errors. For each subject, the hom eostatic process was computed according to the BorbEly -Achermann model. Night sleep decreased progressively during the shift schedule, with effects on sleep pressure Original ResearchArticle

Statistical methods play a significant role throughout the life-cycle of physics experiments, being an essential component of physics analysis. The present project in progress aims to develop an object-oriented software Toolkit for statistical data analysis. The Toolkit contains a variety of Goodness-of-Fit (GoF) tests, from Chi-squared to Kolmogorov-Smirnov, to less known, but generally much more powerful tests such as Anderson-Darling, Goodman, Fisz-Cramer-von Mises, Kuiper. Thanks to the component-based design and the usage of the standard abstract interfaces for data analysis, this tool can be used by other data analysis systems or integrated in experimental software frameworks. In this paper we describe the statistical details of the algorithms and the computational features of the Toolkit. With the aim of showing the consistency between the code and the mathematical features of the algorithms, we describe the results we obtained reproducing by means of the Toolkit a couple of Goodness-of-Fit testing examples of relevance in statistics literature.

Objective The aims of this study were: to evaluate a homogeneous sample of truck drivers of dangerous goods (TDDGs) in order to assess the prevalence of obstructive sleep apnea (OSA), and to verify the secondary risk of motor vehicle accidents (MVAs) and near miss accidents (NMAs) in this population. Methods A sample of 283 male TDDGs was evaluated. None of the subjects reported OSA symptoms before screening. Clinical and physical evaluation, Epworth Sleepiness Scale (ESS), and the items on OSA from the Sleep Disorder Score (SDS) questionnaire were used to select subjects with suspicion of OSA. Polysomnography (PSG) was performed to confirm the diagnosis of OSA. The frequency of MVAs and NMAs was assessed at baseline for the whole sample, and also for the drivers with severe OSA after two years of continuous positive airway pressure (CPAP) treatment. Results The mean age of the sample was 42.3 ± 8.3 years. A total of 139 (49.1%) subjects had suspected OSA, and the PSG study confirmed the diagnosis in 35.7%. A significant association between OSA severity and NMAs was observed, and subjects with severe OSA showed a near five-fold increased risk of NMAs (OR = 4.745, 95% CI 1.292–17.424, p = 0.019). After two years of CPAP treatment, the rate of NMAs was comparable with drivers without OSA, showing the efficacy of therapy. Conclusion This study showed an unexpected high prevalence of OSA in TDDGs. Untreated subjects with severe OSA had a significantly increased risk of NMAs. In professional drivers, screening, treatment, and management of OSA are mandatory for reducing road accident risk and improving road safety.

Introduction Specific IgE antibodies to peanut and hazelnut allergen components can help distinguish between symptomatic and clinically irrelevant sensitizations. We investigated the utility of peanut and hazelnut components in allergy diagnosis through a systematic approach, analyzing the diagnostic accuracy of sIgE to storage proteins and pollen cross-reactive PR-10 proteins. Methods Seven databases were searched for studies involving the diagnosis of patients suspected of peanut or hazelnut allergy and employing oral food challenges as reference standard. Study quality was assessed with QUADAS-2 tool. Diagnostic parameters of component-sIgE at several pre-defined cut-offs were calculated by meta-regression analysis of the data extracted. Results In total, 11/23 studies (peanut =17, hazelnut = 7) presented data suitable for meta-regression analysis, and were judged to have no concerns of applicability. The pooled sensitivity and specificity of Ara h 2-sIgE in single-gate pediatric studies was 85.8% and 83.6%, respectively at 0.35 kUA/L. The corresponding values of sIgE to hazelnut Cor a 14 and Cor a 9 were 81.7% / 77.9% and 77.6 / 67.3%, respectively. The diagnostic accuracy of peanut Ara h 2- sIgE and hazelnut Cor a 14-sIgE was found to be highest at 0.35 kUA/L threshold, while the optimal cut-off for hazelnut Cor a 9-sIgE was 1.0 kUA/L. Specific IgE to Ara h 8 and Cor a 1 PR-10 proteins had low diagnostic accuracy. Conclusions sIgE to storage proteins confer high specificity in diagnosing peanut and hazelnut allergy in children and may help in reducing the need for oral food challenges in diagnosing these allergies.

Introduction Food allergies can substantially burden patients and families by negatively affecting finances, social relationships and personal perceptions of health. This study was performed under the Finnish Allergy Programme aimed at reducing avoidance diets to foods in schoolchildren by 50%. The goal of this study was to investigate how many children could be freed from diet restrictions in a school district through a diagnostic algorithm including Component-Resolved Diagnostics and food challenge. The secondary aim was to provide a crude estimate of the burden of the elimination food diets and the savings associated to the proposed intervention. Methods 205 children with food avoidance diet according to the school register because of food allergy, were invited into the study. 157 children were interviewed, tested for IgE to extracts and allergen components and food challenged in respective order. Results After two years, 12 children still had an avoidance diet and three of them were treated successfully with OIT; the rest suspended their avoidance diet (n=134) or dropped out of the study (n=11). The cost of the elimination diets was estimated in 172700€ per year at start, 13200€ per year at the end of the study; total savings were 128080€ yearly. Equivalent cost savings for the US will be presented. Conclusions The results demonstrate a 65% reduction of avoidance diets to foods in school-aged children, exceeding the 50% aim of the Finnish Allergy Programme. Therefore, it is possible to actively reduce the number of food allergy diagnoses that remain unmonitored in the society through a tailored diagnostic work-up.

Purpose: TheGEANT4 general-purpose Monte Carlo simulation toolkit is able to simulate physical interaction processes of electrons, hydrogen and helium atoms with charge states ( H 0 , H + ) and ( He 0 , He + , He 2 + ), respectively, in liquid water, the main component of biological systems, down to the electron volt regime and the submicrometer scale, providing GEANT4 users with the so-called “GEANT4-DNA” physics models suitable for microdosimetry simulation applications. The corresponding software has been recently re-engineered in order to provide GEANT4 users with a coherent and unique approach to the simulation of electromagnetic interactions within the GEANT4 toolkit framework (since GEANT4 version 9.3 beta). This work presents a quantitative comparison of these physics models with a collection of experimental data in water collected from the literature. Methods: An evaluation of the closeness between the total and differential cross section models available in theGEANT4 toolkit for microdosimetry and experimental reference data is performed using a dedicated statistical toolkit that includes the Kolmogorov–Smirnov statistical test. The authors used experimental data acquired in water vapor as direct measurements in the liquid phase are not yet available in the literature. Comparisons with several recommendations are also presented. Results: The authors have assessed the compatibility of experimental data withGEANT4microdosimetry models by means of quantitative methods. The results show that microdosimetric measurements in liquid water are necessary to assess quantitatively the validity of the software implementation for the liquid water phase. Nevertheless, a comparison with existing experimental data in water vapor provides a qualitative appreciation of the plausibility of the simulation models. The existing reference data themselves should undergo a critical interpretation and selection, as some of the series exhibit significant deviations from each other. Conclusions: TheGEANT4-DNA physics models available in the GEANT4 toolkit have been compared in this article to available experimental data in the water vapor phase as well as to several published recommendations on the mass stopping power. These models represent a first step in the extension of the GEANT4 Monte Carlo toolkit to the simulation of biological effects of ionizing radiation.

The tissue equivalence of solid state silicon detectors in proton radiation fields was determined to improve the radiation protection applications of silicon detectors in aviation and space missions. The study was performed by means of Geant4 simulations. Results are presented showing that a simple c( ~ 0.56) of linear dimensions is adequate to convert experimentally obtained microdosimetric energy deposition spectra in silicon to equivalent microdosimetric energy deposition spectra in water.

New physical processes specific for microdosimetry simulation are under development in the Geant4 Low Energy Electromagnetic package. The first set of models implemented for this purpose cover the interactions of electrons, protons and light ions in liquid water; they address a physics domain relevant to the simulation of radiation effects in biological systems, where water represents an important component. The design developed for effectively handling particle interactions down to a low energy scale and the physics models implemented in the first public release of the software are described.

The Low Energy Electromagnetic package of the Geant4 toolkit incorporates a component for the simulation of atomic relaxation of elements with atomic number between 6 and 100. This process is triggered by the creation of a vacancy in the atomic shell occupancy as a result of an incident particle interaction with an atom of the target material. X-ray fluorescence and Auger electron emission result from the relaxation cascade. The availability of a model handling the atomic relaxation in Geant4 extends the applicability of the simulation toolkit to experimental use cases concerning the investigation of material properties through their characteristic X-ray or Auger emission. It is also relevant to precise simulation applications, like microdosimetry or the design and optimization of detectors based on nanotechnology. The key features of the software development process, the software architecture and design, and the implementation details of the physics model are described.

The accuracy of the Geant4 component for the simulation of atomic relaxation has been evaluated against the experimental measurements of the NIST Standard Reference Data. The validation study concerns X-ray and Auger transition energies. The comparison of the simulated and experimental data with rigorous statistical methods demonstrates the excellent accuracy of the simulation of atomic de-excitation in Geant4.

Geant 4 is an object-oriented toolkit for simulating the passage of particles through matter. At the very heart of Geant 4 there is a wide set of complementary, and sometimes alternative, physics models which describe the basic interaction of particles with matter. After a review of the main characteristics of the toolkit and a status report of the current activities, the results of a series of detailed tests for the quantitative validation of the electromagnetic models of Geant 4 are presented. Such precision tests demonstrate the reliability of the physics models provided in Geant 4 and are hence particularly relevant for critical applications of simulation models.

Using the Monte Carlo simulation tool GEANT4, we simulated the hadron-therapy beam line of the Centro di AdroTerapia ed Applicazioni Nucleari Avanzate (CATANA) center. This is the unique Italian hadron-therapy facility in which 62-MeV proton beams are used for the radiotherapeutic treatment of choroidal and iris melanomas. All the elements, such as diffusers, range shifters, collimators, and detectors, typical of a proton-therapy line were modeled. The beam line provides an ideal environment for the experimental testing and validation of the software developed. The software architecture was developed, and the validation of the software is in its final stage. Simulated ranges, energy distribution, depth and lateral dose distributions for full energy proton beams will be compared to the experimental results obtained at Laboratori Nazionali del Sud (LNS) with different detectors.

International audience; Modeling the radio-induced effects in biological medium still requires accurate physics models to describe the interactions induced by all the charged particles present in the irradiated medium in detail. These interactions include inelastic as well as elastic processes. To check the accuracy of the very low energy models recently implemented into the GEANT4 toolkit for modeling the electron slowing-down in liquid water, the simulation of electron dose point kernels remains the preferential test. In this context, we here report normalized radial dose profiles, for mono-energetic point sources, computed in liquid water by using the very low energy "GEANT4-DNA" physics processes available in the GEANT4 toolkit. In the present study, we report an extensive intra-comparison of profiles obtained by a large selection of existing and well-documented Monte-Carlo codes, namely, EGSnrc, PENELOPE, CPA100, FLUKA and MCNPX.

Monte Carlo simulations of S-values have been carried out with the Geant4-DNA extension of the Geant4 toolkit. The S-values have been simulated for monoenergetic electrons with energies ranging from 0.1 keV up to 20 keV, in liquid water spheres (for four radii, chosen between 10 nm and 1 μm), and for electrons emitted by five isotopes of iodine (131, 132, 133, 134 and 135), in liquid water spheres of varying radius (from 15 μm up to 250 μm). The results have been compared to those obtained from other Monte Carlo codes and from other published data. The use of the Kolmogorov–Smirnov test has allowed confirming the statistical compatibility of all simulation results.

A comprehensive study has been performed to provide general guidelines for the practical choice of the most suitable goodness-of-fit test in real data analysis. Quantitative comparisons among the goodness-of-fit tests contained in the Statistical Toolkit are presented; the case of samples drawn from smooth theoretical functions is taken into account. This study is the most complete and general approach so far available to characterize the power of goodness-of-fit tests for the comparison of two data distributions. The results provide guidance to the user to identify the most appropriate test for his/her analysis on an objective basis.

Geant4 is a software toolkit for the simulation of the passage of particles through matter. It is used by a large number of experiments and projects in a variety of application domains, including high energy physics, astrophysics and space science, medical physics and radiation protection. Its functionality and modeling capabilities continue to be extended, while its performance is enhanced. An overview of recent developments in diverse areas of the toolkit is presented. These include performance optimization for complex setups; improvements for the propagation in fields; new options for event biasing; and additions and improvements in geometry, physics processes and interactive capabilities.

The present project aims to develop an open-source and object-oriented software Toolkit for statistical data analysis. Its statistical testing component contains a variety of Goodness-of-Fit tests, from Chi-squared to Kolmogorov-Smirnov, to less known, but generally much more powerful tests such as Anderson-Darling, Goodman, Fisz-Cramer-von Mises, Kuiper, Tiku. Thanks to the component-based design and the usage of the standard abstract interfaces for data analysis, this tool can be used by other data analysis systems or integrated in experimental software frameworks. This Toolkit has been released and is downloadable from the web. In this paper we describe the statistical details of the algorithms, the computational features of the Toolkit and describe the code validation.

The Statistical Toolkit is a project for the development of open source software tools for statistical data analysis in experimental particle and nuclear physics. The second development cycle encompassed an extension of the software functionality and new tools to facilitate its usage in experimental environments. The new developments include additional goodness-of-fit tests, new implementations of existing tests to improve their statistical precision or computational performance, a new component to extend the usability of the toolkit with other data analysis systems, and new tools for an easier configuration and build of the system in the user's computing environment. The computational performance of all the algorithms implemented has been studied.

The present project in progress develops an object-oriented software toolkit for statistical data analysis. The Goodness-of-Fit (GoF) Statistical Comparison component of the toolkit provides algorithms for the comparison of data distributions in a variety of use cases typical of physics experiments. The system contains a variety of two-sample GoF tests, from chi-squared to tests based on the maximum distance between the two empirical distribution functions (Kolmogorov-Smirnov, Kuiper, Goodman), to tests based on the weighted quadratic distance between the two empirical distribution functions (Cramer-von Mises, Anderson-Darling). Thanks to its flexible design the GoF Statistical Toolkit has been recently extended, implementing other less known GoF tests (weighted formulations of Kolmogorov-Smirnov and Cramer-von Mises tests, Watson and Tiku tests).

Lo scopo di questo lavoro è fornire uno strumento di software sofisticato per la validazione statistica delle distribuzioni isodosi calcolate da un toolkit adottato per la simulazione del passaggio delle particelle nella materia (Geant4). Tale validazione si basa sul confronto dei risultati delle simulazioni con set di misure sperimentali, con dati di riferimento disponibili in letteratura o con dati ottenuti da calcoli teorici o da fit.

Statistical methods play a significant role throughout the life-cycle of HEP experiments, being an essential component of physics analysis. Only a few basic tools for statistical analysis were available in the public domain FORTRAN libraries for HEP. Nowadays the situation is hardly unchanged even among the libraries of the new generation. The present project in progress aims to develop an object-oriented software toolkit for statistical data analysis. More in particular, the Statistical Comparison component of the toolkit provides algorithms for the comparison of data distributions in a variety of use cases typical of HEP experiments, as regression testing (in various phases of the software life-cycle), validation of simulation through comparison to experimental data, comparison of expected versus reconstructed distributions, comparison of data from different sources - such as different sets of experimental data, or experimental with respect to theoretical distributions. The toolkit contains a variety of goodness-of-fit tests, from chi-squared to Kolmogorov-Smirnov, to less known, but generally much more powerful tests such as Anderson-Darling, Lilliefors, Cramer-von Mises, Kuiper. Thanks to the component-based design and the usage of the standard AIDA interfaces, this tool can be used by other data analysis systems or integrated in experimental software frameworks. We present the architecture of the system, the statistics methods implemented and the results of its first applications to the validation of the Geant4 Simulation Toolkit and to experimental data analysis.

In this note we discuss in general how to test the implementation code of statistical tests, and then we treat in detail the case of the Kolmogorov-Smirnov test. It will be shown that some 'obvious' expected properties, like the flatness distributions of p-values from repeating drawings from the same parent distribution, are not indeed reproduced even in absence of bugs in the code, due to either asymptotic approximations in the formulas used to compute the p-value, or to the discreteness of the distance distribution in the case of direct Monte Carlo evaluation of the p-value. This makes the code-testing more complicated. Some practical advice is presented anyhow.

Purpose A meta-analysis was conducted to estimate the prevalence of patients with molecularly confirmed Leber hereditary optic neuropathy (LHON) carrying any of the 3 primary mtDNA mutations (m.11778G>A, m.14484T>C, m.3460G>A) which cause this inherited form of blindness. Methods A literature search was conducted to identify primary reports with LHON prevalence data reported for Europe. The overall prevalence of LHON with molecularly confirmed diagnosis was evaluated by weighting the prevalence estimates of the individual studies by the inverse of their variance. Results Based on this meta-analysis of 5 European studies providing appropriate information, the estimated prevalence of LHON disease associated with the combined m.11778G>A, m.14484T>C, m.3460G>A mutations was ∼1:45,000 (2.23×10-5; 95% confidence interval [CI] 2.01-2.44×10–5). Patients with LHON carrying either the m.11778G>A or the m.3460G>A mutation have a more severe clinical presentation and a much lower chance of spontaneous recovery from vision loss compared to patients with the m.14484T>C mutation. The estimated prevalence for patients with LHON in Europe carrying either of these severe mutations (m.11778G>A or m.3460G>A) was ∼1:65,000 (1.54×10–5; 95% CI 1.33-1.74×10–5). Conclusions Although this meta-analysis summarizes the existing prevalence data for the primary, disease-causing mitochondrial DNA mutations of LHON in Europe, there is still a clear lack of reliable primary epidemiologic data for this devastating ophthalmologic disease.

This paper presents a study of energy deposits induced by ionising particles in liquid water at the molecular scale. Particles track structures were generated using the Geant4-DNA processes of the Geant4 Monte-Carlo toolkit. These processes cover electrons (0.025 eV–1 MeV), protons (1 keV–100 MeV), hydrogen atoms (1 keV–100 MeV) and alpha particles (10 keV–40 MeV) including their different charge states. Electron ranges and lineal energies for protons were calculated in nanometric and micrometric volumes.

International audience; An overview of the electromagnetic (EM) physics of the Geant4 toolkit is presented. Two sets of EM models are available: the "Standard" initially focused on high energy physics (HEP) while the "Low-energy" was developed for medical, space and other applications. The "Standard" models provide a faster computation but are less accurate for keV energies, the "Low-energy" models are more CPU time consuming. A common interface to EM physics models has been developed allowing a natural combination of ultra-relativistic, relativistic and low-energy models for the same run providing both precision and CPU performance. Due to this migration additional capabilities become available. The new developments include relativistic models for bremsstrahlung and e+e- pair production, models of multiple and single scattering, hadron/ion ionization, microdosimetry for very low energies and also improvements in existing Geant4 models. In parallel, validation suites and benchmarks have been intensively developed.

The Geant4-DNA project proposes to develop an open-source simulation software based and fully included in the general-purpose Geant4 Monte-Carlo simulation toolkit. The main objective of this software is to simulate biological damages induced by ionizing radiations at the cellular and sub-cellular scale. This project was originally initiated by the European Space Agency for the prediction of the deleterious effects of radiations that may affect astronauts during future long duration space exploration missions. In this paper, the Geant4-DNA collaboration presents an overview of the whole on-going project, including its most recent developments that are available in the Geant4 toolkit since December 2009 (release 9.3), as well as an illustration example simulating the direct irradiation of a biological chromatin fiber. Expected extensions involving several research domains, such as particle physics, chemistry and cellular and molecular biology, within a fully interdisciplinary activity of the Geant4 collaboration are also discussed.

Motivation: In searching for differentially expressed (DE) genes in microarray data, we often observe a fraction of the genes to have unequal variability between groups. This is not an issue in large samples, where a valid test exists that uses individual variances separately. The problem arises in the small-sample setting, where the approximately valid Welch test lacks sensitivity, while the more sensitive moderated t-test assumes equal variance. Methods: We introduce a moderated Welch test (MWT) that allows unequal variance between groups. It is based on (i) weighting of pooled and unpooled standard errors and (ii) improved estimation of the gene-level variance that exploits the information from across the genes. Results: When a non-trivial proportion of genes has unequal variability, false discovery rate (FDR) estimates based on the standard t and moderated t-tests are often too optimistic, while the standard Welch test has low sensitivity. The MWT is shown to (i) perform better than the standard t, the standard Welch and the moderated t-tests when the variances are unequal between groups and (ii) perform similarly to the moderated t, and better than the standard t and Welch tests when the group variances are equal. These results mean that MWT is more reliable than other existing tests over wider range of data conditions. Availability: R package to perform MWT is available at http://www.meb.ki.se/~yudpaw Contact: yudi.pawitan@ki.se Supplementary information: Supplementary data are available at Bioinformatics online.

A project is in progress for a systematic, rigorous validation of Geant4 electromagnetic physics. This paper presents the first results concerning the validation of Geant4 bremsstrahlung models against experimental data.

AVIRM, présenté par Mascialino B., soumis aux proceedings; International audience; A project, named Geant4-DNA, is in progress to extend the Geant4 simulation toolkit to model the effects of radiation with biological systems at cellular and DNA level. The first component implemented in the first development cycle of the project describes the fractional survival of a population of cells irradiated with photons or charged particles. The software system developed provides the user the option to choose among a small set of alternative models for the calculation of mammalian cell survival after irradiation. The flexible design adopted makes the system open to further extension to implement other cell survival models available in literature. The preliminary design of a prototype of the cell survival models implemented and preliminary results in some selected cell lines are described.

A novel architectural approach to the design of human phantom software models is presented. A detailed design has been developed to enable the adoption of this approach in Geant4-based simulation applications. A few preliminary implementations and application demonstrations are described.

A comprehensive, rigorous validation of Geant4 electromagnetic and hadronic models pertinent to the simulation of the proton Bragg peak in water is presented. Geant4 simulation results are validated against high precision experimental data taken in the CATANA hadrontherapy facility.

AVIRM, présenté par Z. Francis, soumis aux proceedings; International audience; A set of processes specialized for the simulation of particle interactions with water has been developed in the Geant4 Low Energy Electromagnetic package. The models cover the interactions of electrons, protons and light ions down to the electronVolt energy scale. They address a physics domain relevant to the simulation of radiation effects in biological systems, where water represents an important component. The software design, the physics models implemented and an overview of their tests are described.

The validation of Geant4 with respect to authoritative reference data is a critical issue, fundamental to establish the predictive capabilities of Geant4-based simulations. We present the results of a series of comparisons for the evaluation of Geant4 atomic relaxation package with respect to the National Institute of Standards and Technologies (NIST) reference data.

Monitoring radiation background is a crucial task for the operation of LHC experiments. A project is in progress at CERN for the optimisation of the radiation monitors for LHC experiments. A simulation system based on Geant4, designed to assist the engineering optimisation of LHC radiation monitor detectors, is presented. Various detector packaging configurations are studied through their Geant4-based simulation, and their behaviour is compared.

We present a Geant4-based simulation, this Monte Carlo program has been developed in order to simulate the absorbed dose distribution given by a medical linac used for intensity modulated radiation therapy (IMRT). The linac geometry was input into the Monte Carlo code using the accelerator's manufacturer's specifications. We made assumptions about some parameters such as the energy and the electron radial distributions that were assumed to be Gaussian in shape. The capability of the program in evaluating dose distribution has been verified by comparison with measurements in water phantom; the comparisons were performed for percent depth dose (PDD) and for flatness at 15, 50 and 100 mm depth for various field size, for a 6 MV electron beam. The source-surface distance (SSD) was 100 cm. We show the comparisons between simulation results and experimental measurements and the software architecture.

Using the Monte Carlo simulation tool GEANT4 we simulated the hadron-therapy beam line of the CATANA (Centro di AdroTerapia ed Applicazioni Nucleari Avanzate) center. This is the unique italian hadron-therapy facility in which 62 MeV proton beams are used for the radiotherapeutic treatment of choroidal and iris melanomas. All the elements, such as diffusers, range shifters, collimators and detectors, typical of a proton-therapy line were modelled. The beam line provides an ideal environment for the experimental testing and validation of the software developed. The software architecture was developed, and the validation of the software is in its final stage. Simulated ranges, energy distribution, depth and lateral dose distributions for full energy proton beams will be compared tothe experimental results obtained at LNS (Laboratori Nazionali del Sud) with different detectors.

The Geant4 Simulation Toolkit provides an ample set of physics models describing electromagnetic interactions of particles with matter. This paper presents the results of a series of comparisons for the evaluation of Geant4 electromagnetic processes with respect to United States National Institute of Standards and Technologies (NIST) reference data. A statistical analysis was performed to estimate quantitatively the compatibility of Geant4 electromagnetic models with NIST data; the statistical analysis also highlighted the respective strengths of the different Geant4 models.

STUDY OBJECTIVES: Night work can be dangerous because both circadian sleep propensity (process C) and sleep pressure due to the prolonged wakefulness (process S) contribute to the reduction of vigilance levels. As naps are a countermeasure to sleepiness, this study evaluates the role they play in preventing sleep-related accidents in Italian shift-working police drivers. DESIGN/SETTING/PARTICIPANTS: The study concerns highway car accidents that occurred to Italian shift-working police drivers; it was performed in 2 steps: a retrospective analysis of the overall number of accidents that occurred during the years 1993--1997 (n, 1195), followed by a validation analysis of a smaller cohort of accidents prospectively collected during 2003 (n, 84). INTERVENTIONS: N/A. MEASUREMENTS AND RESULTS: RETROSPECTIVE ANALYSIS: The influence of process S, process C, driver characteristics, and context conditions on accident risk, estimated by means of Cox hazard regression, revealed that nighttime accident risk was mainly influenced by process S levels. Consequently, an experimental mathematical model linking the hourly observed number of accidents to process S levels was designed. Its generalization to the theoretical case of drivers omitting naps showed an increase of about 38% of accidents. PROSPECTIVE ANALYSIS: In order to validate our results, we compared retrospective and prospective sleep patterns: no statistical difference was found. Again, the hourly number of accidents increased with homeostatic sleep pressure; the theoretical efficacy of napping was quantified in 48% accidents decrease. CONCLUSIONS: Our data seem to confirm that napping before working a night shift is an effective countermeasure to alertness and performance deterioration associated with night work. Moreover, this self-initiated behavior could have a prophylactic efficacy in reducing the number of car accidents.

Data analysis is an essential section of all physics experiments; in spite of this only a few analysis standard toolkits are available. Concerning the comparison between distributions, almost all these toolkits are limited to the Chi-squared test. Statistics provides a whole chapter of Goodness-of-Fit tests, from the Chi-squared to tests based on maximum distance (Kolmogorov-Smirnov, Kuiper, Goodman), to tests based on quadratic distance (Fisz-Cramer-von Mises, Anderson-Darling, Tiku). All of these Goodness-of-Fit tests have been collected in a new open-source Statistical Toolkit. This Toolkit matches a sophisticated statistical data treatment with the most advanced computing techniques, such as object-oriented technology with the use of design patterns and generic programming. None of the Goodness-of-Fit tests included in the system is optimum for every case. Unfortunately, statistics does not provide a universal recipe for specific distributions and furthermore the only rare available guidelines refer to the comparison between smooth theoretical distributions. With the aim of helping the user in the algorithm choice, we present the results of an intrinsic statistical comparison among many of the Goodness-of-Fit tests contained in the Statistical Toolkit in terms of relative efficiency.