Oxygen impurities in NiAl: Relaxation effects

We have used a full-potential linear muffin-tin orbital method to calculate the effects of oxygen impurities on the electronic structure of NiAl. Using the supercell method with a 16-atom supercell we have investigated the cases where an oxygen atom is substitutionally placed at either a nickel or an aluminum site. Full relaxation of the atoms within the supercell was allowed. We found that oxygen prefers to occupy a nickel site over an aluminum site with a site selection energy of 138 mRy (21,370 K). An oxygen atom placed at an aluminum site is found to cause a substantial relaxation of its nickel neighbors away from it. In contrast, this steric repulsion is hardly present when the oxygen atom occupies the nickel site and is surrounded by aluminum neighbors. We comment on the possible relation of this effect to the pesting degradation phenomenon (essentially spontaneous disintegration in air) in nickel aluminides.Comment: To appear in Phys. Rev. B (Aug. 15, 2001

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

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

The challenge of separating signatures of local adaptation from those of isolation by distance and colonization history: The case of two white pines

Accurately detecting signatures of local adaptation using genetic-environment associations (GEAs) requires controlling for neutral patterns of population structure to reduce the risk of false positives. However, a high degree of collinearity between climatic gradients and neutral population structure can greatly reduce power, and the performance of GEA methods in such case is rarely evaluated in empirical studies. In this study, we attempted to disentangle the effects of local adaptation and isolation by environment (IBE) from those of isolation by distance (IBD) and isolation by colonization from glacial refugia (IBC) using range-wide samples in two white pine species. For this, SNPs from 168 genes, including 52 candidate genes for growth and phenology, were genotyped in 133 and 61 populations of Pinus strobus and P. monticola, respectively. For P. strobus and using all 153 SNPs, climate (IBE) did not significantly explained among-population variation when controlling for IBD and IBC in redundancy analyses (RDAs). However, 26 SNPs were significantly associated with climate in single-locus GEA analyses (Bayenv2 and LFMM), suggesting that local adaptation took place in the presence of high gene flow. For P. monticola, we found no evidence of IBE using RDAs and weaker signatures of local adaptation using GEA and FST outlier tests, consistent with adaptation via phenotypic plasticity. In both species, the majority of the explained among-population variation (69 to 96%) could not be partitioned between the effects of IBE, IBD, and IBC. GEA methods can account differently for this confounded variation, and this could explain the small overlap of SNPs detected between Bayenv2 and LFMM. Our study illustrates the inherent difficulty of taking into account neutral structure in natural populations and the importance of sampling designs that maximize climatic variation, while minimizing collinearity between climatic gradients and neutral structure