High-Accuracy X-Ray Diffraction Analysis of Phase Evolution Sequence During Devitrification of Cu50Zr50 Metallic Glass

Real-time high-energy X-ray diffraction (HEXRD) was used to investigate the crystallization kinetics and phase selection sequence for constant-heating-rate devitrification of fully amorphous Cu50Zr50, using heating rates from 10 K/min to 60 K/min (10 °C/min to 60 °C/min). In situ HEXRD patterns were obtained by the constant-rate heating of melt-spun ribbons under synchrotron radiation. High-accuracy phase identification and quantitative assessment of phase fraction evolution though the duration of the observed transformations were performed using a Rietveld refinement method. Results for 10 K/min (10 °C/min) heating show the apparent simultaneous formation of three phases, orthorhombic Cu10Zr7, tetragonal CuZr2 (C11b), and cubic CuZr (B2), at 706 K (433 °C), followed immediately by the dissolution of the CuZr (B2) phase upon continued heating to 789 K (516 °C). Continued heating results in reprecipitation of the CuZr (B2) phase at 1002 K (729 °C), with the material transforming completely to CuZr (B2) by 1045 K (772 °C). The Cu5Zr8 phase, previously reported to be a devitrification product in C50Zr50, was not observed in the present study

No evidence that protein truncating variants in BRIP1 are associated with breast cancer risk: implications for gene panel testing.

BACKGROUND: BRCA1 interacting protein C-terminal helicase 1 (BRIP1) is one of the Fanconi Anaemia Complementation (FANC) group family of DNA repair proteins. Biallelic mutations in BRIP1 are responsible for FANC group J, and previous studies have also suggested that rare protein truncating variants in BRIP1 are associated with an increased risk of breast cancer. These studies have led to inclusion of BRIP1 on targeted sequencing panels for breast cancer risk prediction. METHODS: We evaluated a truncating variant, p.Arg798Ter (rs137852986), and 10 missense variants of BRIP1, in 48 144 cases and 43 607 controls of European origin, drawn from 41 studies participating in the Breast Cancer Association Consortium (BCAC). Additionally, we sequenced the coding regions of BRIP1 in 13 213 cases and 5242 controls from the UK, 1313 cases and 1123 controls from three population-based studies as part of the Breast Cancer Family Registry, and 1853 familial cases and 2001 controls from Australia. RESULTS: The rare truncating allele of rs137852986 was observed in 23 cases and 18 controls in Europeans in BCAC (OR 1.09, 95% CI 0.58 to 2.03, p=0.79). Truncating variants were found in the sequencing studies in 34 cases (0.21%) and 19 controls (0.23%) (combined OR 0.90, 95% CI 0.48 to 1.70, p=0.75). CONCLUSIONS: These results suggest that truncating variants in BRIP1, and in particular p.Arg798Ter, are not associated with a substantial increase in breast cancer risk. Such observations have important implications for the reporting of results from breast cancer screening panels.The COGS project is funded through a European Commission's Seventh Framework Programme grant (agreement number 223175 - HEALTH-F2-2009-223175). BCAC is funded by Cancer Research UK [C1287/A10118, C1287/A12014] and by the European Community´s Seventh Framework Programme under grant agreement number 223175 (grant number HEALTH-F2-2009-223175) (COGS). Funding for the iCOGS infrastructure came from: the European Community's Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, C8197/A16565), the National Institutes of Health (CA128978) and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 16 CA148065 and 1U19 CA148112 - the GAME-ON initiative), the Department of Defense (W81XWH-10-1- 0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. This study made use of data generated by the Wellcome Trust Case Control consortium. Funding for the project was provided by the Wellcome Trust under award 076113. The results published here are in part based upon data generated by The Cancer Genome Atlas Project established by the National Cancer Institute and National Human Genome Research Institute.This is the author accepted manuscript. The final version is available from BMJ Group at http://dx.doi.org/10.1136/jmedgenet-2015-103529

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives