Isospin dependence of electromagnetic transition strengths among an isobaric triplet

Electric quadrupole matrix elements, M, for the J=2→0, ΔT=0, T=1 transitions across the A=46 isobaric multiplet Cr-V-Ti have been measured at GSI with the FRS-LYCCA-AGATA setup. This allows direct insight into the isospin purity of the states of interest by testing the linearity of M with respect to T. Pairs of nuclei in the T=1 triplet were studied using identical reaction mechanisms in order to control systematic errors. The M values were obtained with two different methodologies: (i) a relativistic Coulomb excitation experiment was performed for Cr and Ti; (ii) a “stretched target” technique was adopted here, for the first time, for lifetime measurements in V and Ti. A constant value of M across the triplet has been observed. Shell-model calculations performed within the fp shell fail to reproduce this unexpected trend, pointing towards the need of a wider valence space. This result is confirmed by the good agreement with experimental data achieved with an interaction which allows excitations from the underlying sd shell. A test of the linearity rule for all published data on complete T=1 isospin triplets is presented.Peer Reviewe

Classification of Supernovae

The current classification scheme for supernovae is presented. The main observational features of the supernova types are described and the physical implications briefly addressed. Differences between the homogeneous thermonuclear type Ia and similarities among the heterogeneous core collapse type Ib, Ic and II are highlighted. Transforming type IIb, narrow line type IIn, supernovae associated with GRBs and few peculiar objects are also discussed.Comment: 16 Pages, 4 figures, to be published in "Supernovae and Gamma-Ray Bursters," ed. Kurt W. Weile

A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry

Background Genome-wide studies of gene–environment interactions (G×E) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide G×E analysis of ~ 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer. Methods Analyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene–environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs. Results Assuming a 1 × 10–5 prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability < 15%, we identified two independent SNP-risk factor pairs: rs80018847(9p13)-LINGO2 and adult height in association with overall breast cancer risk (ORint = 0.94, 95% CI 0.92–0.96), and rs4770552(13q12)-SPATA13 and age at menarche for ER + breast cancer risk (ORint = 0.91, 95% CI 0.88–0.94). Conclusions Overall, the contribution of G×E interactions to the heritability of breast cancer is very small. At the population level, multiplicative G×E interactions do not make an important contribution to risk prediction in breast cancer

Breast cancer risk genes: association analysis in more than 113,000 women

BACKGROUNDGenetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking.METHODSWe used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity.RESULTSProtein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D, and TP53) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, and RAD51D, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 were associated with a risk of breast cancer overall with a P value of less than 0.001. For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants.CONCLUSIONSThe results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.)Molecular tumour pathology - and tumour geneticsMTG1 - Moleculaire genetica en pathologie van borstkanke

Numerical modelling of plane strain tests on sands using a particulate approach

This paper describes the results of a series of numerical plane strain test simulations on a particulate material, carried out using the three-dimensional particle flow code PFC-3D. Samples comprised about 10 000 non-spherical particles, each formed by strongly bonding two spheres together. The simulations demonstrate the ability of such a model to capture the essential macro-features of soil behaviour as observed in laboratory tests, including the dependence of peak strengths on the initial void ratio relative to the critical. The development of strain localisations or shear bands associated with the use of rough loading platens, and the sensitivity of the model to the initial sample porosity, particle shape factor and interparticle friction angle, were also investigated.Cet exposé décrit les résultats d'une série de simulations numériques d'essais de déformation plane sur un maté-riau particulaire, essais effectués en utilisant le code de flux de particules en trois dimensions PFC-3D. Les échantillons étaient constitués d'environ 10 000 particules non sphériques, chacune ayant été formée en collant deux sphères ensemble. Les simulations démontrent la faculté d'un tel modèle à saisir les macro-caractéristiques essen-tielles du comportement du sol tel qu'il est observé dans les essais de laboratoire, y compris la dépendance des résistances de pointe sur le taux de pores initial par rapport au taux critique. Nous avons également étudié le développement des localisations de déformation ou de bandes de cisaillement associées à l'utilisation de plateaux de chargement grossiers, ainsi que la sensibilité du modèle à la porosité initiale de l'échantillon, le facteur forme de particule et l'angle de friction entre particules