Elastic geobarometry for anisotropic inclusions in cubic hosts

Mineral inclusions entrapped in other minerals may record the local stresses at the moment of their entrapment in the deep Earth. When rocks are exhumed to the surface of the Earth, residual stresses and strains may still be preserved in the inclusion. If measured and interpreted correctly through elastic geobarometry, they give us invaluable information on the pressures (P) and temperatures (T) of metamorphism. Current estimates of P and T of entrapment rely on simplified models that assumes that the inclusion is spherical and embedded in an infinite host, and that their elastic properties are isotropic. We report a new method for elastic geobarometry for anisotropic inclusions in quasi-isotropic hosts. The change of strain in the inclusion is modelled with the axial equations of state of the host and the inclusion. Their elastic interaction is accounted for by introducing a 4th rank tensor, the relaxation tensor, that can be evaluated numerically for any symmetry of the host and the inclusion and for any geometry of the system. This approach can be used to predict the residual strain/stress state developed in an inclusion after exhumation from known entrapment conditions, or to estimate the entrapment conditions from the residual strain measured in real inclusions. In general, anisotropic strain and stress states are developed in non-cubic mineral inclusions such as quartz and zircon, with deviatoric stresses typically limited to few kbars. For garnet hosts, the effect of the mutual crystallographic orientation between the host and the inclusion on the residual strain and stress is negligible when the inclusion is spherical and isolated. Assuming external hydrostatic conditions, our results suggest that the isotropic and the new anisotropic models give estimations of entrapment conditions within 2%

Novel Synthesis and High Pressure Behavior of Na0.3CoO2 x 1.3 H2O and Related Phases

We have prepared powder samples of NaxCoO2 x yH2O using a new synthesis route. Superconductivity was observed in Na0.3CoO2 x 1.3H2O between 4 and 5K as indicated by the magnetic susceptibility. The bulk compressibilities of Na0.3CoO2 x 1.3H2O, Na0.3CoO2 x 0.6H2O and Na0.3CoO2 were determined using a diamond anvil cell and synchrotron powder diffraction. Chemical changes occurring under pressure when using different pressure transmitting media are discussed and further transport measurements are advocated.Comment: 7 pages, 4 figures, PRrapid submitte

Thermodynamics of pyrope-majorite, Mg3Al2Si3O12-Mg4Si4O12, solid solution from atomistic model calculations

Static lattice energy calculations, based on empirical pair potentials have been performed for a large set of different structures with compositions between pyrope and majorite, and with different states of order of octahedral cations. The energies have been cluster expanded using pair and quaternary terms. The derived ordering constants have been used to constrain Monte Carlo simulations of temperature-dependent properties in the ranges of 1073 3673K and 0 20 GPa. The free energies of mixing have been calculated using the method of thermodynamic integration. At zero pressure the cubic/tetragonal transition is predicted for pure majorite at 3300 K. The transition temperature decreases with the increase of the pyrope mole fraction. A miscibility gap associated with the transition starts to develop at about 2000K and xmaj 0.8, and widens with the decrease in temperature and the increase in pressure. Activity composition relations in the range of 0 20 GPa and 1073 2673K are described with the help of a high-order Redlich Kister polynomial

Cloning and regional localization of the mouse faciogenital dysplasia ( Fgd1 ) gene

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47027/1/335_2004_Article_BF00352375.pd

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Peer reviewe