Dicluster Stopping in a Degenerate Electron Gas

In this paper we report on our theoretical studies of various aspects of the correlated stopping power of two point-like ions (a dicluster) moving in close but variable vicinity of each other in some metallic target materials the latter being modelled by a degenerate electron gas with appropriate densities. Within the linear response theory we have made a comprehensive investigation of correlated stopping power, vicinage function and related quantities for a diproton cluster in two metallic targets, aluminum and copper, and present detailed and comparative results for three approximations to the electron gas dielectric function, namely the plasmon-pole approximation without and with dispersion as well as with the random phase approximation. The results are also compared, wherever applicable, with those for an individual projectile.Comment: 29 figures, LaTe

Targeted Next-Generation Sequencing Analysis of 1,000 Individuals with Intellectual Disability.

To identify genetic causes of intellectual disability (ID), we screened a cohort of 986 individuals with moderate to severe ID for variants in 565 known or candidate ID-associated genes using targeted next-generation sequencing. Likely pathogenic rare variants were found in ∼11% of the cases (113 variants in 107/986 individuals: ∼8% of the individuals had a likely pathogenic loss-of-function [LoF] variant, whereas ∼3% had a known pathogenic missense variant). Variants in SETD5, ATRX, CUL4B, MECP2, and ARID1B were the most common causes of ID. This study assessed the value of sequencing a cohort of probands to provide a molecular diagnosis of ID, without the availability of DNA from both parents for de novo sequence analysis. This modeling is clinically relevant as 28% of all UK families with dependent children are single parent households. In conclusion, to diagnose patients with ID in the absence of parental DNA, we recommend investigation of all LoF variants in known genes that cause ID and assessment of a limited list of proven pathogenic missense variants in these genes. This will provide 11% additional diagnostic yield beyond the 10%-15% yield from array CGH alone.Action Medical Research (SP4640); the Birth Defect Foundation (RG45448); the Cambridge National Institute for Health Research Biomedical Research Centre (RG64219); the NIHR Rare Diseases BioResource (RBAG163); Wellcome Trust award WT091310; The Cell lines and DNA bank of Rett Syndrome, X-linked mental retardation and other genetic diseases (member of the Telethon Network of Genetic Biobanks (project no. GTB12001); the Genetic Origins of Congenital Heart Disease Study (GO-CHD)- funded by British Heart Foundation (BHF)This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1002/humu.2290

The SEDs and Host Galaxies of the dustiest GRB afterglows

(Abridged) Until recently the information inferred from gamma-ray burst follow-up observations was mostly limited to optically bright afterglows, biasing all demographic studies against sight-lines that contain large amounts of dust. Here, we present GRB afterglow and host observations for a sample of bursts that are exemplary of previously missed ones because of high visual extinction along the sight-line. This facilitates an investigation of the properties, geometry and location of the absorbing dust of these poorly-explored host galaxies, and a comparison to hosts from optically-selected samples. The hosts of the dustiest afterglows are diverse in their properties, but on average redder, more luminous and massive than the hosts of optically-bright events. We hence probe a different galaxy population, suggesting that previous host samples miss most of the massive, chemically-evolved and metal-rich members. This also indicates that the dust along the sight-line is often related to host properties, and thus probably located in the diffuse ISM or interstellar clouds and not in the immediate GRB environment. Some of the hosts in our sample, are blue, young or of small stellar mass illustrating that even apparently non-extinguished galaxies possess very dusty sight-lines due to a patchy dust distribution. The presented observations establish a population of luminous, massive and correspondingly chemically-evolved GRB hosts. This suggests that GRBs trace the global star-formation rate better than studies based on optically-selected host samples indicate, and the previously-claimed deficiency of high-mass host galaxies was at least partially a selection effect.Comment: 17 pages, 13 figures, resubmitted to A&A after referee repor

Incorporating radiomics into clinical trials: expert consensus on considerations for data-driven compared to biologically-driven quantitative biomarkers

Existing Quantitative Imaging Biomarkers (QIBs) are associated with known biological tissue characteristics and follow a well-understood path of technical, biological and clinical validation before incorporation into clinical trials. In radiomics, novel data-driven processes extract numerous visually imperceptible statistical features from the imaging data with no a priori assumptions on their correlation with biological processes. The selection of relevant features (radiomic signature) and incorporation into clinical trials therefore requires additional considerations to ensure meaningful imaging endpoints. Also, the number of radiomic features tested means that power calculations would result in sample sizes impossible to achieve within clinical trials. This article examines how the process of standardising and validating data-driven imaging biomarkers differs from those based on biological associations. Radiomic signatures are best developed initially on datasets that represent diversity of acquisition protocols as well as diversity of disease and of normal findings, rather than within clinical trials with standardised and optimised protocols as this would risk the selection of radiomic features being linked to the imaging process rather than the pathology. Normalisation through discretisation and feature harmonisation are essential pre-processing steps. Biological correlation may be performed after the technical and clinical validity of a radiomic signature is established, but is not mandatory. Feature selection may be part of discovery within a radiomics-specific trial or represent exploratory endpoints within an established trial; a previously validated radiomic signature may even be used as a primary/secondary endpoint, particularly if associations are demonstrated with specific biological processes and pathways being targeted within clinical trials