Mental health in UK Biobank: development, implementation and results from an online questionnaire completed by 157 366 participants

Background UK Biobank is a well-characterised cohort of over 500 000 participants that offers unique opportunities to investigate multiple diseases and risk factors. Aims An online mental health questionnaire completed by UK Biobank participants was expected to expand the potential for research into mental disorders. Method An expert working group designed the questionnaire, using established measures where possible, and consulting with a patient group regarding acceptability. Case definitions were defined using operational criteria for lifetime depression, mania, anxiety disorder, psychotic-like experiences and self-harm, as well as current post-traumatic stress and alcohol use disorders. Results 157 366 completed online questionnaires were available by August 2017. Comparison of self-reported diagnosed mental disorder with a contemporary study shows a similar prevalence, despite respondents being of higher average socioeconomic status than the general population across a range of indicators. Thirty-five per cent (55 750) of participants had at least one defined syndrome, of which lifetime depression was the most common at 24% (37 434). There was extensive comorbidity among the syndromes. Mental disorders were associated with high neuroticism score, adverse life events and long-term illness; addiction and bipolar affective disorder in particular were associated with measures of deprivation. Conclusions The questionnaire represents a very large mental health survey in itself, and the results presented here show high face validity, although caution is needed owing to selection bias. Built into UK Biobank, these data intersect with other health data to offer unparalleled potential for crosscutting biomedical research involving mental health

Electronic prescribing systems in hospitals to improve medication safety: a multimethods research programme.

Electronic prescribing (ePrescribing) systems allow health-care professionals to enter prescriptions and manage medicines using a computer. We set out to find out how these ePrescribing systems are chosen, set up and used in English hospitals. Given that these systems are designed to improve medication safety, we looked at whether or not these systems affected the number of prescribing errors made (mistakes such as ordering the wrong dose of medication). We also tried to see whether or not the systems were good value for money (or more cost-effective). Finally, we made recommendations to help hospitals choose, set up and use ePrescribing systems. We found that setting up ePrescribing systems was very difficult because there is a need to take into consideration how different pharmacists, nurses and doctors work, and the different work that needs to be carried out for different diseases and medical conditions. We recorded a link between the implementation of ePrescribing systems and a reduction in some high-risk prescribing errors in two out of three study sites. Given that the error reductions corresponded to the warnings triggered by the system, we concluded that the system is likely to have caused the error reduction. Prescribing errors may lead to adverse events that lead to death, impaired quality of life and longer hospital stays. The cost of an ePrescribing system increased in proportion to reduced errors, reaching £4.31 per patient per year for the site that experienced the greatest reduction in prescribing errors (i.e. site S). This estimate is based on assumptions in the model and how much a health service is willing to pay for a unit of health benefit. To help professionals choose, set up and use ePrescribing systems in the future, we produced an online ePrescribing Toolkit (www.eprescribingtoolkit.com/; accessed 21 December 2019) that, with support from NHS England, is becoming widely used internationally

A framework for feature extraction from hospital medical data with applications in risk prediction

Background: Feature engineering is a time consuming component of predictive modeling. We propose a versatile platform to automatically extract features for risk prediction, based on a pre-defined and extensible entity schema. The extraction is independent of disease type or risk prediction task. We contrast auto-extracted features to baselines generated from the Elixhauser comorbidities. Results: Hospital medical records was transformed to event sequences, to which filters were applied to extract feature sets capturing diversity in temporal scales and data types. The features were evaluated on a readmission prediction task, comparing with baseline feature sets generated from the Elixhauser comorbidities. The prediction model was through logistic regression with elastic net regularization. Predictions horizons of 1, 2, 3, 6, 12 months were considered for four diverse diseases: diabetes, COPD, mental disorders and pneumonia, with derivation and validation cohorts defined on non-overlapping data-collection periods. For unplanned readmissions, auto-extracted feature set using socio-demographic information and medical records, outperformed baselines derived from the socio-demographic information and Elixhauser comorbidities, over 20 settings (5 prediction horizons over 4 diseases). In particular over 30-day prediction, the AUCs are: COPD-baseline: 0.60 (95% CI: 0.57, 0.63), auto-extracted: 0.67 (0.64, 0.70); diabetes-baseline: 0.60 (0.58, 0.63), auto-extracted: 0.67 (0.64, 0.69); mental disorders-baseline: 0.57 (0.54, 0.60), auto-extracted: 0.69 (0.64,0.70); pneumonia-baseline: 0.61 (0.59, 0.63), auto-extracted: 0.70 (0.67, 0.72). Conclusions: The advantages of auto-extracted standard features from complex medical records, in a disease and task agnostic manner were demonstrated. Auto-extracted features have good predictive power over multiple time horizons. Such feature sets have potential to form the foundation of complex automated analytic tasks

The Long-Baseline Neutrino Experiment: Exploring Fundamental Symmetries of the Universe

The preponderance of matter over antimatter in the early Universe, the dynamics of the supernova bursts that produced the heavy elements necessary for life and whether protons eventually decay --- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our Universe, its current state and its eventual fate. The Long-Baseline Neutrino Experiment (LBNE) represents an extensively developed plan for a world-class experiment dedicated to addressing these questions. LBNE is conceived around three central components: (1) a new, high-intensity neutrino source generated from a megawatt-class proton accelerator at Fermi National Accelerator Laboratory, (2) a near neutrino detector just downstream of the source, and (3) a massive liquid argon time-projection chamber deployed as a far detector deep underground at the Sanford Underground Research Facility. This facility, located at the site of the former Homestake Mine in Lead, South Dakota, is approximately 1,300 km from the neutrino source at Fermilab -- a distance (baseline) that delivers optimal sensitivity to neutrino charge-parity symmetry violation and mass ordering effects. This ambitious yet cost-effective design incorporates scalability and flexibility and can accommodate a variety of upgrades and contributions. With its exceptional combination of experimental configuration, technical capabilities, and potential for transformative discoveries, LBNE promises to be a vital facility for the field of particle physics worldwide, providing physicists from around the globe with opportunities to collaborate in a twenty to thirty year program of exciting science. In this document we provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess.Comment: Major update of previous version. This is the reference document for LBNE science program and current status. Chapters 1, 3, and 9 provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess. 288 pages, 116 figure

Toward interoperable bioscience data

© The Author(s), 2012. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Nature Genetics 44 (2012): 121-126, doi:10.1038/ng.1054.To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision.The authors also acknowledge the following funding sources in particular: UK Biotechnology and Biological Sciences Research Council (BBSRC) BB/I000771/1 to S.-A.S. and A.T.; UK BBSRC BB/I025840/1 to S.-A.S.; UK BBSRC BB/I000917/1 to D.F.; EU CarcinoGENOMICS (PL037712) to J.K.; US National Institutes of Health (NIH) 1RC2CA148222-01 to W.H. and the HSCI; US MIRADA LTERS DEB-0717390 and Alfred P. Sloan Foundation (ICoMM) to L.A.-Z.; Swiss Federal Government through the Federal Office of Education and Science (FOES) to L.B. and I.X.; EU Innovative Medicines Initiative (IMI) Open PHACTS 115191 to C.T.E.; US Department of Energy (DOE) DE-AC02- 06CH11357 and Arthur P. Sloan Foundation (2011- 6-05) to J.G.; UK BBSRC SysMO-DB2 BB/I004637/1 and BBG0102181 to C.G.; UK BBSRC BB/I000933/1 to C.S. and J.L.G.; UK MRC UD99999906 to J.L.G.; US NIH R21 MH087336 (National Institute of Mental Health) and R00 GM079953 (National Institute of General Medical Science) to A.L.; NIH U54 HG006097 to J.C. and C.E.S.; Australian government through the National Collaborative Research Infrastructure Strategy (NCRIS); BIRN U24-RR025736 and BioScholar RO1-GM083871 to G.B. and the 2009 Super Science initiative to C.A.S

Evolution of the Kangmar Dome, southern Tibet: Structural, petrologic, and thermochronologic constraints

Structural, thermobarometric, and thermochronologic investigations of the Kangmar Dome, southern Tibet, suggest that both extensional and contractional deformational histories are preserved within the dome. The dome is cored by an orthogneiss which is mantled by staurolite + kyanite zone metasedimentary rocks; metamorphic grade dies out up section and is defined by a series of concentric kyanite-in, staurolite-in, garnet-in, and chloritoid-in isograds. Three major deformational events, two older penetrative events and a younger doming event, are preserved. The oldest event, D1, resulted in approximately E-W trending tight to isoclinal folds of bedding with an associated moderately to steeply north dipping axial planar foliation, S1. The second event, D2, resulted in a high strain mylonitic foliation, S2, which defines the domal structure, and an associated approximately N-S trending stretching and mineral alignment lineation. Shear sense during formation of S2 varied from dominantly top S shear on the south dipping flank of the dome to top N shear on the north dipping flank. The central part of the dome exhibits either opposing shear sense indicators or symmetric fabrics. Microtextural relations indicate that peak metamorphism occurred post-D1 and pre- to early D2 deformation. Quantitative thermobarometry yields peak metamorphic conditions of ∼445°C and 370 MPa in garnet zone rocks, increasing to 625°C and 860 MPa in staurolite + kyanite zone rocks. Pressures and temperatures increase with depth and northward within a single structural horizon across the dome and the apparent gradient in pressure is ∼20% of the expected gradient, suggesting that the rocks were subvertically shortened after the pressure gradient was frozen in. Mica 40Ar/39Ar thermochronology yields 15.24 ± 0.05 to 10.94 ± 0.30 Ma cooling ages that increase with depth and young northward within a single structural horizon across the dome. Diffusion modeling of potassium feldspar 40Ar/39Ar spectra yield rapid cooling rates (∼10–30°C/Myr) between ∼11.5 and 10 Ma and apatite fission track ages range from 7.9 ± 3.0 to 4.1 ± 1.9 Ma, with a mean age of ∼5.5 Ma. Both data sets show symmetric cooling across the dome between ∼11 and 5.5 Ma. The S2 mylonitic foliation, peak metamorphic isobars and isotherms, and mica 40Ar/39Ar isochrons are domed, whereas potassium feldspar 40Ar/39Ar and apatite fission track isochrons are not, suggesting that doming occurred at ∼11 Ma. Our data do not support simple, end-member metamorphic core complex-type extension, diapirism, or duplex models for gneiss dome formation. Rather, we suggest that the formation of extensional fabrics occurred within a zone of coaxial strain in the root zone of the Southern Tibetan Detachment System (STDS), implying that normal slip along the STDS and extensional fabrics within the Kangmar Dome were the result of gravitational collapse of overthickened crust. Subsequent doming during the middle Miocene is attributed to thrusting upward and southward over a north dipping ramp above cold Tethyan sediments. Middle Miocene thrust faulting in the Kangmar Dome region is synchronous with continued normal slip along the STDS and thrust motion along the Renbu Zedong thrust fault, suggesting that extension and contraction was occurring simultaneously within southern Tibet

Multi-messenger searches via IceCube’s high-energy neutrinos and gravitational-wave detections of LIGO/Virgo

We summarize initial results for high-energy neutrino counterpart searches coinciding with gravitational-wave events in LIGO/Virgo\u27s GWTC-2 catalog using IceCube\u27s neutrino triggers. We did not find any statistically significant high-energy neutrino counterpart and derived upper limits on the time-integrated neutrino emission on Earth as well as the isotropic equivalent energy emitted in high-energy neutrinos for each event