Electronic structure of the ferromagnetic superconductor UCoGe from first principles

The superconductor UCoGe is analyzed with electronic structure calculations using Linearized Augmented Plane Wave method based on Density Functional Theory. Ferromagnetic and antiferromagnetic calculations with and without correlations (via LDA+U) were done. In this compound the Fermi level is situated in a region where the main contribution to DOS comes from the U-5f orbital. The magnetic moment is mainly due to the Co-3d orbital with a small contribution from the U-5f orbital. The possibility of fully non-collinear magnetism in this compound seems to be ruled out. These results are compared with the isostructural compound URhGe, in this case the magnetism comes mostly from the U-5f orbital

The loss of anisotropy in MgB2 with Sc substitution and its relationship with the critical temperature

The electrical conductivity anisotropy of the sigma-bands is calculated for the (Mg,Sc)B2 system using a virtual crystal model. Our results reveal that anisotropy drops with relatively little scandium content (< 30%); this behaviour coincides with the lowering of Tc and the reduction of the Kohn anomaly. This anisotropy loss is also found in the Al and C doped systems. In this work it is argued that the anisotropy, or 2D character, of the sigma-bands is an important parameter for the understanding of the high Tc found in MgB2

Uddeling af sølvbægere.

Uddeling af sølvbægere

Erythropoietin Improves Place Learning in an 8-Arm Radial Maze in Fimbria-Fornix Transected Rats

Systemically administered human recombinant erythropoietin (EPO) may have the potential to reduce the cognitive and behavioral symptoms of mechanical brain injury. In a series of studies, we address this possibility. We previously found that EPO given to fimbriafornix transected rats at the moment of injury could substantially improve the posttraumatic acquisition of an allocentric place learning task when such a task is administered in a water maze. Due to the clinical importance of such results, it is important to scrutinize whether the therapeutic effect of EPO is specific to the experimental setup of our original experiments or generalizes across test situations. Consequently, here we studied the effects of similarly administered EPO in fimbria-fornix transected and control operated rats, respectively, evaluating the posttraumatic behavioral/cognitive abilities in an allocentric place learning task administered in an 8-arm radial maze. The administration of EPO to the hippocampally injured rats was associated with a virtually complete elimination of the otherwise severe behavioral impairment caused by fimbria-fornix transection. In contrast, EPO had no detectable effect on the task acquisition of non-lesioned animals. The results of the present study confirm our previous demonstration of EPO's ability to reduce or eliminate the behavioral/cognitive consequences of mechanical injury to the hippocampus, while adding the important observation that such a therapeutic effect is not restricted to the specific experimental setup previously studied

Methods for detecting associations between phenotype and aggregations of rare variants

Although genome-wide association studies have uncovered variants associated with more than 150 traits, the percentage of phenotypic variation explained by these associations remains small. This has led to the search for the dark matter that explains this missing genetic component of heritability. One potential explanation for dark matter is rare variants, and several statistics have been devised to detect associations resulting from aggregations of rare variants in relatively short regions of interest, such as candidate genes. In this paper we investigate the feasibility of extending this approach in an agnostic way, in which we consider all variants within a much broader region of interest, such as an entire chromosome or even the entire exome. Our method searches for subsets of variant sites using either Markov chain Monte Carlo or genetic algorithms. The analysis was performed with knowledge of the Genetic Analysis Workshop 17 answers

Enhancing the discovery of rare disease variants through hierarchical modeling

Advances in next-generation sequencing technology are enabling researchers to capture a comprehensive picture of genomic variation across large numbers of individuals with unprecedented levels of efficiency. The main analytic challenge in disease mapping is how to mine the data for rare causal variants among a sea of neutral variation. To achieve this goal, investigators have proposed a number of methods that exploit biological knowledge. In this paper, I propose applying a Bayesian stochastic search variable selection algorithm in this context. My multivariate method is inspired by the combined multivariate and collapsing method. In this proposed method, however, I allow an arbitrary number of different sources of biological knowledge to inform the model as prior distributions in a two-level hierarchical model. This allows rare variants with similar prior distributions to share evidence of association. Using the 1000 Genomes Project single-nucleotide polymorphism data provided by Genetic Analysis Workshop 17, I show that through biologically informative prior distributions, some power can be gained over noninformative prior distributions

Genome-wide case-control study in GAW17 using coalesced rare variants

Genome-wide association studies have successfully identified numerous loci at which common variants influence disease risks or quantitative traits of interest. Despite these successes, the variants identified by these studies have generally explained only a small fraction of the variations in the phenotype. One explanation may be that many rare variants that are not included in the common genotyping platforms may contribute substantially to the genetic variations of the diseases. Next-generation sequencing, which would better allow for the analysis of rare variants, is now becoming available and affordable; however, the presence of a large number of rare variants challenges the statistical endeavor to stably identify these disease-causing genetic variants. We conduct a genome-wide association study of Genetic Analysis Workshop 17 case-control data produced by the next-generation sequencing technique and propose that collapsing rare variants within each genetic region through a supervised dimension reduction algorithm leads to several macrovariants constructed for rare variants within each genetic region. A simultaneous association of the phenotype to all common variants and macrovariants is undertaken using a linear discriminant analysis using the penalized orthogonal-components regression algorithm. The results suggest that the proposed analysis strategy shows promise but needs further development

Inferring fish escape behaviour in trawls based on catch comparison data: Model development and evaluation based on data from Skagerrak, Denmark

During the fishing process, fish react to a trawl with a series of behaviours that often are species and size specific. Thus, a thorough understanding of fish behaviour in relation to fishing gear and a scientific understanding of the ability of different gear designs to utilize or stimulate various behavioural patterns during the catching process are essential for developing more efficient, selective, and environmentally friendly trawls. Although many behavioural studies using optical and acoustic observation systems have been conducted, harsh observation conditions on the fishing grounds often hamper the ability to directly observe fish behaviour in relation to fishing gear. As an alternative to optical and acoustic methods, we developed and applied a new mathematical model to catch data to extract detailed and quantitative information about species- and size-dependent escape behaviour in towed fishing gear such as trawls. We used catch comparison data collected with a twin trawl setup; the only difference between the two trawls was that a 12 m long upper section was replaced with 800 mm diamond meshes in one of them. We investigated the length-based escape behaviour of cod (Gadus morhua), haddock (Melanogrammus aeglefinus), saithe (Pollachius virens), witch flounder (Glyptocephalus cynoglossus), and lemon sole (Microstomus kitt) and quantified the extent to which behavioural responses set limits for the large mesh panel's selective efficiency. Around 85% of saithe, 80% of haddock, 44% of witch flounder, 55% of lemon sole, and 55% of cod (below 68 cm) contacted the large mesh panel and escaped. We also demonstrated the need to account for potential selectivity in the trawl body, as it can bias the assessment of length-based escape behaviour. Our indirect assessment of fish behaviour was in agreement with the direct observations made for the same species in a similar section of the trawl body reported in the literature

Evaluation of pooled association tests for rare variant identification

Genome-wide association studies have successfully identified many common variants associated with complex human diseases. However, a large portion of the remaining heritability cannot be explained by these common variants. Exploring rare variants associated with diseases is now catching more attention. Several methods have been recently proposed for identification of rare variants. Among them, the fixed-threshold, weighted-sum, and variable-threshold methods are effective in combining the information of multiple variants into a functional unit; these approaches are commonly used. We evaluate the performance of these three methods. Based on our analyses of the Genetic Analysis Workshop 17 data, we find that no method is universally better than the others. Furthermore, adjusting for potential covariates can not only increase the true-positive proportions but also reduce the false-positive proportions. Our study concludes that there is no uniformly most powerful test among the three methods we compared (the fixed-threshold, weighted-sum, and variable-threshold methods), and their performances depend on the underlying genetic architecture of a disease