469 research outputs found
‘What’s it like to have ME?’ The discursive construction of ME in computer-mediated communication and face-to-face interaction
ME/CFS (chronic fatigue syndrome) is a debilitating illness for which no cause or medical tests have been identified. Debates over its nature have generated interest from qualitative researchers. However, participants are difficult to recruit because of the nature of their condition. Therefore, this study explores the utility of the internet as a means of eliciting accounts. We analyse data from focus groups and the internet in order to ascertain the extent to which previous research findings apply to the internet domain. Interviews were conducted among 49 members of internet (38 chatline, 11 personal) and 7 members of two face-to-face support groups. Discourse analysis of descriptions and accounts of ME/CFS revealed similar devices and interactional concerns in both internet and face-to-face communication. Participants constructed their condition as serious, enigmatic and not psychological. These functioned to deflect problematic assumptions about ME/CFS and to manage their accountability for the illness and its effects
Orthology guided transcriptome assembly of Italian ryegrass and meadow fescue for single-nucleotide polymorphism discovery
Single-nucleotide polymorphisms (SNPs) represent natural DNA sequence variation. They can be used for various applications including the construction of high-density genetic maps, analysis of genetic variability, genome-wide association studies, and mapbased cloning. Here we report on transcriptome sequencing in the two forage grasses, meadow fescue (Festuca pratensis Huds.) and Italian ryegrass (Lolium multiflorum Lam.), and identification of various classes of SNPs. Using the Orthology Guided Assembly (OGA) strategy, we assembled and annotated a total of 18,952 and 19,036 transcripts for Italian ryegrass and meadow fescue, respectively. In addition, we used transcriptome sequence data of perennial ryegrass (L. perenne L.) from a previous study to identify 16,613 transcripts shared across all three species. Large numbers of intraspecific SNPs were identified in all three species: 248,000 in meadow fescue, 715,000 in Italian ryegrass, and 529,000 in perennial ryegrass. Moreover, we identified almost 25,000 interspecific SNPs located in 5343 genes that can distinguish meadow fescue from Italian ryegrass and 15,000 SNPs located in 3976 genes that discriminate meadow fescue from both Lolium species. All identified SNPs were positioned in silico on the seven linkage groups (LGs) of L. perenne using the GenomeZipper approach. With the identification and positioning of interspecific SNPs, our study provides a valuable resource for the grass research and breeding community and will enable detailed characterization of genomic composition and gene expression analysis in prospective Festuca Lolium hybrids
Creation and evaluation of full-text literature-derived, feature-weighted disease models of genetically determined developmental disorders
There are >2500 different genetically determined developmental disorders (DD), which, as a group, show very high levels of both locus and allelic heterogeneity. This has led to the wide-spread use of evidence-based filtering of genome-wide sequence data as a diagnostic tool in DD. Determining whether the association of a filtered variant at a specific locus is a plausible explanation of the phenotype in the proband is crucial and commonly requires extensive manual literature review by both clinical scientists and clinicians. Access to a database of weighted clinical features extracted from rigorously curated literature would increase the efficiency of this process and facilitate the development of robust phenotypic similarity metrics. However, given the large and rapidly increasing volume of published information, conventional biocuration approaches are becoming impractical. Here, we present a scalable, automated method for the extraction of categorical phenotypic descriptors from the full-text literature. Papers identified through literature review were downloaded and parsed using the Cadmus custom retrieval package. Human Phenotype Ontology terms were extracted using MetaMap, with 76–84% precision and 65–73% recall. Mean terms per paper increased from 9 in title + abstract, to 68 using full text. We demonstrate that these literature-derived disease models plausibly reflect true disease expressivity more accurately than widely used manually curated models, through comparison with prospectively gathered data from the Deciphering Developmental Disorders study. The area under the curve for receiver operating characteristic (ROC) curves increased by 5–10% through the use of literature-derived models. This work shows that scalable automated literature curation increases performance and adds weight to the need for this strategy to be integrated into informatic variant analysis pipelines. Database URL: https://doi.org/10.1093/database/baac03
The Dependence of the Superconducting Transition Temperature of Organic Molecular Crystals on Intrinsically Non-Magnetic Disorder: a Signature of either Unconventional Superconductivity or Novel Local Magnetic Moment Formation
We give a theoretical analysis of published experimental studies of the
effects of impurities and disorder on the superconducting transition
temperature, T_c, of the organic molecular crystals kappa-ET_2X and beta-ET_2X
(where ET is bis(ethylenedithio)tetrathiafulvalene and X is an anion eg I_3).
The Abrikosov-Gorkov (AG) formula describes the suppression of T_c both by
magnetic impurities in singlet superconductors, including s-wave
superconductors and by non-magnetic impurities in a non-s-wave superconductor.
We show that various sources of disorder lead to the suppression of T_c as
described by the AG formula. This is confirmed by the excellent fit to the
data, the fact that these materials are in the clean limit and the excellent
agreement between the value of the interlayer hopping integral, t_perp,
calculated from this fit and the value of t_perp found from angular-dependant
magnetoresistance and quantum oscillation experiments. If the disorder is, as
seems most likely, non-magnetic then the pairing state cannot be s-wave. We
show that the cooling rate dependence of the magnetisation is inconsistent with
paramagnetic impurities. Triplet pairing is ruled out by several experiments.
If the disorder is non-magnetic then this implies that l>=2, in which case
Occam's razor suggests that d-wave pairing is realised. Given the proximity of
these materials to an antiferromagnetic Mott transition, it is possible that
the disorder leads to the formation of local magnetic moments via some novel
mechanism. Thus we conclude that either kappa-ET_2X and beta-ET_2X are d-wave
superconductors or else they display a novel mechanism for the formation of
localised moments. We suggest systematic experiments to differentiate between
these scenarios.Comment: 18 pages, 5 figure
Active Brownian Particles. From Individual to Collective Stochastic Dynamics
We review theoretical models of individual motility as well as collective
dynamics and pattern formation of active particles. We focus on simple models
of active dynamics with a particular emphasis on nonlinear and stochastic
dynamics of such self-propelled entities in the framework of statistical
mechanics. Examples of such active units in complex physico-chemical and
biological systems are chemically powered nano-rods, localized patterns in
reaction-diffusion system, motile cells or macroscopic animals. Based on the
description of individual motion of point-like active particles by stochastic
differential equations, we discuss different velocity-dependent friction
functions, the impact of various types of fluctuations and calculate
characteristic observables such as stationary velocity distributions or
diffusion coefficients. Finally, we consider not only the free and confined
individual active dynamics but also different types of interaction between
active particles. The resulting collective dynamical behavior of large
assemblies and aggregates of active units is discussed and an overview over
some recent results on spatiotemporal pattern formation in such systems is
given.Comment: 161 pages, Review, Eur Phys J Special-Topics, accepte
Test beam performance measurements for the Phase I upgrade of the CMS pixel detector
A new pixel detector for the CMS experiment was built in order to cope with the instantaneous luminosities anticipated for the Phase I Upgrade of the LHC. The new CMS pixel detector provides four-hit tracking with a reduced material budget as well as new cooling and powering schemes. A new front-end readout chip mitigates buffering and bandwidth limitations, and allows operation at low comparator thresholds. In this paper, comprehensive test beam studies are presented, which have been conducted to verify the design and to quantify the performance of the new detector assemblies in terms of tracking efficiency and spatial resolution. Under optimal conditions, the tracking efficiency is (99.95 ± 0.05) %, while the intrinsic spatial resolutions are (4.80 ± 0.25) μm and (7.99 ± 0.21) μm along the 100 μm and 150 μm pixel pitch, respectively. The findings are compared to a detailed Monte Carlo simulation of the pixel detector and good agreement is found.Peer reviewe
Search for black holes and other new phenomena in high-multiplicity final states in proton-proton collisions at root s=13 TeV
Peer reviewe
Search for high-mass diphoton resonances in proton-proton collisions at 13 TeV and combination with 8 TeV search
Peer reviewe
Search for heavy resonances decaying into a vector boson and a Higgs boson in final states with charged leptons, neutrinos, and b quarks
Peer reviewe
Search for leptophobic Z ' bosons decaying into four-lepton final states in proton-proton collisions at root s=8 TeV
Peer reviewe
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