Prediction of responsibility for drivers and riders involved in injury road crashes

Responsibility analysis allows the evaluation of crash risk factors from crash data only, but requires a reliable responsibility assessment. The aim of the present study is to predict expert responsibility attribution (considered as a gold-standard) from explanatory variables available in crash data routinely recorded by the police, according to a data-driven process with explicit rules. Method: Driver responsibility was assessed by experts using all information contained in police reports for a sample of about 5000 injury crashes that occurred in France in 2011. Three statistical methods were used to predict expert responsibility attribution: logistic regression with L1 penalty, random forests, and boosting. Potential predictors of expert attribution referred to inappropriate driver actions and to external conditions at the time of the crash. Logistic regression was chosen to construct a score to assess responsibility for drivers and riders in crashes involving one or more motor vehicles, or involving a cyclist or pedestrian. Results: Cross-validation showed that our tool can predict expert responsibility assessments on new data sets. In addition, responsibility analyses performed using either the expert responsibility or our predicted responsibility return similar odds ratios. Our scoring process can then be used to reliably assess responsibility based on national police report databases, provided that they include the information needed to construct the score

Radiation doses and risks to neonates undergoing radiographic examinations in intensive care units in Tunisia

Purpose: To assess the radiation doses to neonates from diagnostic radiography in order to derive the local diagnostic reference levels (LDRLs) for optimisation purposes.Methods: This study was carried out in the neonatal intensive care units (NICU) of  two hospitals in Tunis. 134 babies, with weights ranging from 635 g to 6680 g, performed chest-abdomen X-ray examinations. Neonates were categorized into groups of birth weight. For each X-ray examination, patient data and exposure parameters were recorded. Dose area product (DAP) was measured and entrance surface dose (ESD) was estimated. Effective dose was calculated from the Monte Carlo simulation software PCXMC.Results: DAP values increased with neonatal weight and demonstrated a wide variation (5.0 - 43.0 mGy.cm2, mean 23.4 mGy.cm2) for patient weight from 600 g to 4000 g. A wide variation was also observed for ESD (14 - 93 μGy, mean 55.2 μGy). The LDRLs expressed in term of DAP were estimated to be 17.6 mGy.cm2 and 29.1 mGy.cm2 for the first and the second NICU, respectively. In terms of effective dose, the average value was about 31.6 μSv per single radiological examination. The results show the necessity to use a standardized protocol with high voltage technique combined to lower current time product (mAs) values and an adapted collimation which could lead to further reductions in the neonatal doses. Conclusion: This study presents the LDRLs and the effective doses for neonates in two NICUs and demonstrates the necessity to optimize patient protection for this category of patient

REPAS : Responsabilité estimée par apprentissage statistique - Rapport final

Responsibility analysis makes it possible to estimate crash risk factors from crash data only. One necessary condition to achieve this objective is to dispose of a reliable responsibility assessment. The aim of the present study was to predict expert responsibility attribution (considered as gold-standard) from crash data routinely recorded by the police. The final objective was to estimate driver responsibility in crashes according to a data-driven process with explicit rules. Driver responsibility was attributed by experts in the light of all information contained in the police reports, including accident diagrams and photographs for a sample of 5,000 injury crashes that occurred in France in 2011. This expert responsibility was transformed into a binary variable (1 if totally or rather responsible, 0 if totally or rather not responsible). Explanatory variables were found in the database which yearly includes computerized information from police reports for all of France. As potential predictors of expert attribution, we considered variables referring to inappropriate actions, such as driving the wrong way, speeding, failure to give way, making a half-turn or overtaking, etc. We also included as potential predictors some variables referring to external conditions at the time of the accident such as weather or road condition. As the set of explanatory variables could vary according to the type of accident, the three most frequent accident configurations were considered separately: (1) accident involving only motor vehicles, 2 or more; (2) accident involving a motor vehicle and a pedestrian or a cyclist; (3) accident involving only 1 motor vehicle. Three different statistical methods for each accident configuration were implemented to predict expert responsibility attribution: logistic regression with L1 penalty, random forests, and boosting. After cross-validation for logistic regression and boosting and out-of-bag estimation for random forests, the three statistical methods showed similar performance in terms of accuracy, sensitivity, specificity and reliability for accident configurations 1 and 2. We therefore chose logistic regression, which is suitable for predictions based on a risk/prediction score. The prediction score was also validated by estimating and comparing odds ratios (ORs) obtained for certain risk factors, using the predictions and expert responsibility assessments. The ORs for predictions and expert attributions were very close, except in case of high blood alcohol content, where they were lower using predictions. Based on expert decisions for a fairly large number of police accident reports, we constructed a score to assess responsibility for drivers and riders in accidents involving one or more motor vehicles, or involving a cyclist or pedestrian. The score could directly be applicable to French police data. The methodology could be adapted for other police data, and R scripts are available from the authors upon request. Further work is needed to validate this responsibility assessment, notably using similar police data such as those in the European CARE database.L'analyse de responsabilité permet d'estimer les facteurs de risque d'accident à partir des données d'accident uniquement. Une condition nécessaire pour atteindre cet objectif est de disposer d'une évaluation fiable de la responsabilité. L'objectif de la présente étude était de prédire l'attribution de la responsabilité des experts (considérée comme l'étalon-or) à partir des données d'accidents régulièrement enregistrées par la police. L'objectif final était d'estimer la responsabilité du conducteur en cas d'accident selon un processus guidé par des données et des règles explicites. La responsabilité du conducteur a été attribuée par les experts à la lumière de l'ensemble des informations contenues dans les rapports de police, y compris les schémas d'accidents et les photographies pour un échantillon de 5 000 accidents corporels survenus en France en 2011. Cette responsabilité d'expert a été transformée en variable binaire (1 si totalement ou plutôt responsable, 0 si totalement ou plutôt non responsable). Des variables explicatives ont été trouvées dans la base de données qui inclut chaque année des informations informatisées issues des rapports de police pour l'ensemble de la France. En tant que prédicteurs potentiels de l'attribution par des experts, nous avons pris en compte des variables se référant à des actions inappropriées, telles que conduire dans le mauvais sens, excès de vitesse, ne pas céder le passage, faire un demi-tour ou un dépassement, etc. Nous avons également inclus comme prédicteurs potentiels certaines variables se rapportant aux conditions externes au moment de l'accident, comme les conditions météorologiques ou l'état de la route. L'ensemble des variables explicatives pouvant varier selon le type d'accident, les trois configurations d'accident les plus fréquentes ont été considérées séparément : (1) accident impliquant uniquement des véhicules à moteur, 2 ou plus ; (2) accident impliquant un véhicule à moteur et un piéton ou un cycliste ; (3) accident impliquant un seul véhicule à moteur. Trois méthodes statistiques différentes ont été mises en oeuvre pour chaque configuration d'accident afin de prédire l'attribution de la responsabilité des experts : régression logistique avec pénalité L1, forêts aléatoires et boosting. Après validation croisée pour la régression logistique et le boosting, et l'estimation "out-of-bag" pour les forêts aléatoires, les trois méthodes statistiques ont montré des performances similaires en termes de précision, de sensibilité, de spécificité et de fiabilité pour les configurations 1 et 2 des accidents. Nous avons donc choisi la régression logistique, qui convient aux prédictions basées sur un score risque/prévision. Le score de prédiction a également été validé en estimant et en comparant les odds-ratios (OR) obtenus pour certains facteurs de risque, en utilisant les prédictions et les évaluations de responsabilité des experts. Les ORs pour les prédictions et les attributions d'experts étaient très proches, sauf en cas d'alcoolémie élevée, où ils étaient plus faibles en utilisant les prédictions. En nous fondant sur les décisions d'experts d'un assez grand nombre de rapports d'accident de la police, nous avons établi un score pour évaluer la responsabilité des conducteurs et des conducteurs dans les accidents impliquant un ou plusieurs véhicules automobiles, un cycliste ou un piéton. Le score pourrait être directement applicable aux données des forces de l'ordre françaises. La méthodologie pourrait être adaptée à d'autres données policières, et des scripts R sont disponibles sur demande auprès des auteurs. Des travaux supplémentaires sont nécessaires pour valider cette évaluation de la responsabilité, notamment en utilisant des données policières similaires telles que celles de la base de données européenne CARE

Epigenetic remodelling of enhancers in response to estrogen deprivation and re-stimulation

Estrogen hormones are implicated in a majority of breast cancers and estrogen receptor alpha (ER), the main nuclear factor mediating estrogen signaling, orchestrates a complex molecular circuitry that is not yet fully elucidated. Here, we investigated genome-wide DNA methylation, histone acetylation and transcription after estradiol (E2) deprivation and re-stimulation to better characterize the ability of ER to coordinate gene regulation. We found that E2 deprivation mostly resulted in DNA hypermethylation and histone deacetylation in enhancers. Transcriptome analysis revealed that E2 deprivation leads to a global down-regulation in gene expression, and more specifically of TET2 demethylase that may be involved in the DNA hypermethylation following short-term E2 deprivation. Further enrichment analysis of transcription factor (TF) binding and motif occurrence highlights the importance of ER connection mainly with two partner TF families, AP-1 and FOX. Theseinteractions takeplace in the proximity of E2 deprivation-mediated differentially methylated and histone acetylated enhancers. Finally, while most deprivation-dependent epigenetic changes were reversed following E2 re-stimulation, DNA hypermethylation and H3K27 deacetylation at certain enhancers were partially retained. Overall, these results show that inactivation of ER mediates rapid and mostly reversible epigenetic changes at enhancers, and bring new insight into early events, which may ultimately lead to endocrine resistance.Institut National du Cancer (INCa, France, in part); European Commission (EC) Seventh Framework Programme (FP7) Translational Cancer Research (TRANSCAN) Framework; Fondation ARC pour la Recherche sur le Cancer (France) (to Z.H.); Fonds National de la Recherche, Luxembourg [10100060 to A.S.]; IARC Fellowship (Marie Curie actions – People – COFUND to N.F.J., in part); PoSTDoctoral Fellowship of the Basque Government; Swiss National Science Foundation (SNSF) (to L.V., V.Y., R.M.). Funding for open access charge: IARC regular budge

Traffic Safety Basic Facts 2012 : Single vehicle accidents

The CARE database brings together the disaggregate details of road accidents and casualties across Europe, by combining the national accident databases that are maintained by all EU member states. Access to the CARE database is restricted, however, so it is important that a comprehensive range of publications based on these data be accessible to the general public. This process was begun in the SafetyNet project that was carried out between 2004 and 2008, and the concept of the Basic Fact Sheet (BFS) Basic Fact Sheets and Annual Statistical Report (ASR) was developed. By 2008, twelve Fact Sheets were being prepared annually by researchers at five institutes. This Fact Sheet presents an overview highlighting the main facts for Single vehicle accidents. Wherever possible, measures of risk are calculated by relating the number of fatalities from CARE to exposure data available from other sources. Most Fact Sheets examined trends over the period 2001-2010, with more detailed analyses of data from 2010

Aflatoxin Exposure during Early Life Is Associated with Differential DNA Methylation in Two-Year-Old Gambian Children

Background: DNA methylation is an epigenetic control mechanism that may be altered by environmental exposures. We have previously reported that in utero exposure to the mycotoxin and liver carcinogen aflatoxin B1 from the maternal diet, as measured using biomarkers in the mothers’ blood, was associated with differential DNA methylation in white blood cells of 6-month-old infants from The Gambia. Methods: Here we examined aflatoxin B1-associated differential DNA methylation in white blood cells of 24-month-old children from the same population (n = 244), in relation to the child’s dietary exposure assessed using aflatoxin albumin biomarkers in blood samples collected at 6, 12 and 18 months of age. HM450 BeadChip arrays were used to assess DNA methylation, with data compared to aflatoxin albumin adduct levels using two approaches; a continuous model comparing aflatoxin adducts measured in samples collected at 18 months to DNA methylation at 24 months, and a categorical time-dose model that took into account aflatoxin adduct levels at 6, 12 and 18 months, for comparison to DNA methylation at 24 months. Results: Geometric mean (95% confidence intervals) for aflatoxin albumin levels were 3.78 (3.29, 4.34) at 6 months, 25.1 (21.67, 29.13) at 12 months and 49.48 (43.34, 56.49) at 18 months of age. A number of differentially methylated CpG positions and regions were associated with aflatoxin exposure, some of which affected gene expression. Pathway analysis highlighted effects on genes involved with with inflammatory, signalling and growth pathways. Conclusions: This study provides further evidence that exposure to aflatoxin in early childhood may impact on DNA methylation

CADD: predicting the deleteriousness of variants throughout the human genome

Combined Annotation-Dependent Depletion (CADD) is a widely used measure of variant deleteriousness that can effectively prioritize causal variants in genetic analyses, particularly highly penetrant contributors to severe Mendelian disorders. CADD is an integrative annotation built from more than 60 genomic features, and can score human single nucleotide variants and short insertion and deletions anywhere in the reference assembly. CADD uses a machine learning model trained on a binary distinction between simulated de novo variants and variants that have arisen and become fixed in human populations since the split between humans and chimpanzees; the former are free of selective pressure and may thus include both neutral and deleterious alleles, while the latter are overwhelmingly neutral (or, at most, weakly deleterious) by virtue of having survived millions of years of purifying selection. Here we review the latest updates to CADD, including the most recent version, 1.4, which supports the human genome build GRCh38. We also present updates to our website that include simplified variant lookup, extended documentation, an Application Program Interface and improved mechanisms for integrating CADD scores into other tools or applications. CADD scores, software and documentation are available at https://cadd.gs.washington.edu

Lung cancer risk in relation to jobs held in a nationwide case-control study in Iran

Background: Globally, lung cancer is the most frequent occupational cancer, but the risk associated with the occupations or occupational environment in Iran is not clear. We aimed to assess occupations with the risk of lung cancer. Methods: We used the IROPICAN nationwide case-control study data including 658 incident lung cancer cases and 3477 controls. We assessed the risk of lung cancer in relation to ever working in major groups of International Standard Classification of Occupations, high-risk occupations for lung cancer and duration of employment and lung cancer subtype among construction workers and farmers while controlling for cigarette smoking and opium consumption. We used unconditional regression logistic models to estimate ORs for the association between increased lung cancer risk and occupations. Results: We observed elevated ORs for lung cancer in male construction workers (OR=1.4; 95% CI: 1.0 to 1.8), petroleum industry workers (OR=3.2; 95% CI: 1.1 to 9.8), female farmers (OR=2.6; 95% CI: 1.3 to 5.3) and female bakers (OR=5.5; 95% CI: 1.0 to 29.8). A positive trend by the duration of employment was observed for male construction workers (p< 0.001). Increased risk of squamous cell carcinoma was observed in male construction workers (OR=1.9; 95% CI: 1.2 to 3.0) and female farmers (OR=4.3; 95% CI: 1.1 to 17.2), who also experienced an increased risk of adenocarcinoma (OR=3.8; 95% CI: 1.4 to 9.9). Discussion: Although we observed associations between some occupations and lung cancer consistent with the literature, further studies with larger samples focusing on exposures are needed to better understand the occupational lung cancer burden in Iran.publishedVersionPeer reviewe

DNA methylome analysis identifies accelerated epigenetic aging associated with postmenopausal breast cancer susceptibility

Aim of the study A vast majority of human malignancies are associated with ageing, and age is a strong predictor of cancer risk. Recently, DNA methylation-based marker of ageing, known as ‘epigenetic clock’, has been linked with cancer risk factors. This study aimed to evaluate whether the epigenetic clock is associated with breast cancer risk susceptibility and to identify potential epigenetics-based biomarkers for risk stratification. Methods Here, we profiled DNA methylation changes in a nested case–control study embedded in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (n = 960) using the Illumina HumanMethylation 450K BeadChip arrays and used the Horvath age estimation method to calculate epigenetic age for these samples. Intrinsic epigenetic age acceleration (IEAA) was estimated as the residuals by regressing epigenetic age on chronological age. Results We observed an association between IEAA and breast cancer risk (OR, 1.04; 95% CI, 1.007–1.076, P = 0.016). One unit increase in IEAA was associated with a 4% increased odds of developing breast cancer (OR, 1.04; 95% CI, 1.007–1.076). Stratified analysis based on menopausal status revealed that IEAA was associated with development of postmenopausal breast cancers (OR, 1.07; 95% CI, 1.020–1.11, P = 0.003). In addition, methylome-wide analyses revealed that a higher mean DNA methylation at cytosine-phosphate-guanine (CpG) islands was associated with increased risk of breast cancer development (OR per 1 SD = 1.20; 95 %CI: 1.03–1.40, P = 0.02) whereas mean methylation levels at non-island CpGs were indistinguishable between cancer cases and controls. Conclusion Epigenetic age acceleration and CpG island methylation have a weak, but statistically significant, association with breast cancer susceptibility