Femtosecond X-Ray Diffraction Studies of the Reversal of the Microstructural Effects of Plastic Deformation during Shock Release of Tantalum

We have used femtosecond x-ray diffraction (XRD) to study laser-shocked fiber-textured polycrystalline tantalum targets as the 37-253 GPa shock waves break out from the free surface. We extract the time and depth-dependent strain profiles within the Ta target as the rarefaction wave travels back into the bulk of the sample. In agreement with molecular dynamics (MD) simulations the lattice rotation and the twins that are formed under shock-compression are observed to be almost fully eliminated by the rarefaction process

Combined strong and weak lensing analysis of 28 clusters from the Sloan Giant Arcs Survey

We study the mass distribution of a sample of 28 galaxy clusters using strong and weak lensing observations. The clusters are selected via their strong lensing properties as part of the Sloan Giant Arcs Survey (SGAS) from the Sloan Digital Sky Survey (SDSS). Mass modelling of the strong lensing information from the giant arcs is combined with weak lensing measurements from deep Subaru/Suprime-cam images to primarily obtain robust constraints on the concentration parameter and the shape of the mass distribution. We find that the concentration c_vir is a steep function of the mass, c_vir \propto M_vir^-0.59\pm0.12, with the value roughly consistent with the lensing-bias-corrected theoretical expectation for high mass (10^15 h^-1 M_sun) clusters. However, the observationally inferred concentration parameters appear to be much higher at lower masses (10^14 h^-1 M_sun), possibly a consequence of the modification to the inner density profiles provided by baryon cooling. The steep mass-concentration relation is also supported from direct stacking analysis of the tangential shear profiles. In addition, we explore the two-dimensional shape of the projected mass distribution by stacking weak lensing shear maps of individual clusters with prior information on the position angle from strong lens modelling, and find significant evidence for a large mean ellipticity with the best-fit value of e = 0.47 \pm 0.06 for the mass distribution of the stacked sample. We find that the luminous cluster member galaxy distribution traces the overall mass distribution very well, although the distribution of fainter cluster galaxies appears to be more extended than the total mass.Comment: 29 pages, 15+9 figures, 7 tables, accepted for publication in MNRA

EUROCarbDB: An open-access platform for glycoinformatics

The EUROCarbDB project is a design study for a technical framework, which provides sophisticated, freely accessible, open-source informatics tools and databases to support glycobiology and glycomic research. EUROCarbDB is a relational database containing glycan structures, their biological context and, when available, primary and interpreted analytical data from high-performance liquid chromatography, mass spectrometry and nuclear magnetic resonance experiments. Database content can be accessed via a web-based user interface. The database is complemented by a suite of glycoinformatics tools, specifically designed to assist the elucidation and submission of glycan structure and experimental data when used in conjunction with contemporary carbohydrate research workflows. All software tools and source code are licensed under the terms of the Lesser General Public License, and publicly contributed structures and data are freely accessible. The public test version of the web interface to the EUROCarbDB can be found at http://www.ebi.ac.uk/eurocar

EUROCarbDB: An open-access platform for glycoinformatics

The EUROCarbDB project is a design study for a technical framework, which provides sophisticated, freely accessible, open-source informatics tools and databases to support glycobiology and glycomic research. EUROCarbDB is a relational database containing glycan structures, their biological context and, when available, primary and interpreted analytical data from high-performance liquid chromatography, mass spectrometry and nuclear magnetic resonance experiments. Database content can be accessed via a web-based user interface. The database is complemented by a suite of glycoinformatics tools, specifically designed to assist the elucidation and submission of glycan structure and experimental data when used in conjunction with contemporary carbohydrate research workflows. All software tools and source code are licensed under the terms of the Lesser General Public License, and publicly contributed structures and data are freely accessible. The public test version of the web interface to the EUROCarbDB can be found at http://www.ebi.ac.uk/eurocarb

A novel design process for selection of attributes for inclusion in discrete choice experiments:Case study exploring variation in clinical decision-making about thrombolysis in the treatment of acute ischaemic stroke

On-line structured prioritisation exercise (SPE). Full survey used to collect data. (DOCX 42 kb

Natural Killer Cell Signal Integration Balances Synapse Symmetry and Migration

Imaging immune surveillance by natural killer (NK) cells has revealed that integration of activating and inhibitory signals determines whether or not NK cells stop to kill the target cell or retain a migratory configuration

Towards a supertree of Arthropoda:a species-level supertree of the spiny, slipper and coral lobsters (Decapoda: Achelata)

While supertrees have been built for many vertebrate groups (notably birds, mammals and dinosaurs), invertebrates have attracted relatively little attention. The paucity of supertrees of arthropods is particularly surprising given their economic and ecological importance, as well as their overwhelming contribution to biodiversity. The absence of comprehensive archives of machine-readable source trees, coupled with the need for software implementing repeatable protocols for managing them, has undoubtedly impeded progress. Here we present a supertree of Achelata (spiny, slipper and coral lobsters) as a proof of concept, constructed using new supertree specific software (the Supertree Toolkit; STK) and following a published protocol. We also introduce a new resource for archiving and managing published source trees. Our supertree of Achelata is synthesised from morphological and molecular source trees, and represents the most complete species-level tree of the group to date. Our findings are consistent with recent taxonomic treatments, confirming the validity of just two families: Palinuridae and Scyllaridae; Synaxidae were resolved within Palinuridae. Monophyletic Silentes and Stridentes lineages are recovered within Palinuridae, and all sub-families within Scyllaridae are found to be monophyletic with the exception of Ibacinae. We demonstrate the feasibility of building larger supertrees of arthropods, with the ultimate objective of building a complete species-level phylogeny for the entire phylum using a divide and conquer strategy

Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans

Abstract: Machine learning methods offer great promise for fast and accurate detection and prognostication of coronavirus disease 2019 (COVID-19) from standard-of-care chest radiographs (CXR) and chest computed tomography (CT) images. Many articles have been published in 2020 describing new machine learning-based models for both of these tasks, but it is unclear which are of potential clinical utility. In this systematic review, we consider all published papers and preprints, for the period from 1 January 2020 to 3 October 2020, which describe new machine learning models for the diagnosis or prognosis of COVID-19 from CXR or CT images. All manuscripts uploaded to bioRxiv, medRxiv and arXiv along with all entries in EMBASE and MEDLINE in this timeframe are considered. Our search identified 2,212 studies, of which 415 were included after initial screening and, after quality screening, 62 studies were included in this systematic review. Our review finds that none of the models identified are of potential clinical use due to methodological flaws and/or underlying biases. This is a major weakness, given the urgency with which validated COVID-19 models are needed. To address this, we give many recommendations which, if followed, will solve these issues and lead to higher-quality model development and well-documented manuscripts

Supplementary File for Capturing wheat phenotypes at the genome level

Supplementary S1: Yield and related traits in bread wheat. Table S1: Examples of genomic regions, candidate and cloned genes for yield and related traits in bread wheat. Supplementary S2: Drought tolerance. Table S2: Examples of genomic regions and candidate genes for drought tolerance. Supplementary S3: Heat tolerance. Table S3. Examples of genomic regions and candidate genes for heat tolerance. Supplementary S4: salinity tolerance in bread wheat. Table S4. Examples of genomic regions and candidate genes for salinity tolerance in bread wheat. Supplementary S5: Frost tolerance. Supplementary S6: Disease resistance. Table S5. Examples of genomic regions, candidate and cloned genes mapped for disease resistance in wheat species. Supplementary S7 insect and mite resistance. Table S6. Examples of genomic regions and candidate genes mapped for insect and mite resistance. Supplementary S8: Quality traits. Table S7. Examples of genomic regions, candidate and cloned genes for quality traits.Recent technological advances in next-generation sequencing (NGS) technologies have dramatically reduced the cost of DNA sequencing, allowing species with large and complex genomes to be sequenced. Although bread wheat (Triticum aestivum L.) is one of the world’s most important food crops, efficient exploitation of molecular marker-assisted breeding approaches has lagged behind that achieved in other crop species, due to its large polyploid genome. However, an international public–private effort spanning 9 years reported over 65% draft genome of bread wheat in 2014, and finally, after more than a decade culminated in the release of a gold-standard, fully annotated reference wheat-genome assembly in 2018. Shortly thereafter, in 2020, the genome of assemblies of additional 15 global wheat accessions was released. As a result, wheat has now entered into the pan-genomic era, where basic resources can be efficiently exploited. Wheat genotyping with a few hundred markers has been replaced by genotyping arrays, capable of characterizing hundreds of wheat lines, using thousands of markers, providing fast, relatively inexpensive, and reliable data for exploitation in wheat breeding. These advances have opened up new opportunities for marker-assisted selection (MAS) and genomic selection (GS) in wheat. Herein, we review the advances and perspectives in wheat genetics and genomics, with a focus on key traits, including grain yield, yield-related traits, end-use quality, and resistance to biotic and abiotic stresses. We also focus on reported candidate genes cloned and linked to traits of interest. Furthermore, we report on the improvement in the aforementioned quantitative traits, through the use of (i) clustered regularly interspaced short-palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated gene-editing and (ii) positional cloning methods, and of genomic selection. Finally, we examine the utilization of genomics for the next-generation wheat breeding, providing a practical example of using in silico bioinformatics tools that are based on the wheat reference-genome sequence.Peer reviewe