A Weyl-Dirac Cosmological Model with DM and DE

In the Weyl-Dirac (W-D) framework a spatially closed cosmological model is considered. It is assumed that the space-time of the universe has a chaotic Weylian microstructure but is described on a large scale by Riemannian geometry. Locally fields of the Weyl connection vector act as creators of massive bosons having spin 1. It is suggested that these bosons, called weylons, provide most of the dark matter in the universe. At the beginning the universe is a spherically symmetric geometric entity without matter. Primary matter is created by Dirac's gauge function very close to the beginning. In the early epoch, when the temperature of the universe achieves its maximum, chaotically oriented Weyl vector fields being localized in micro-cells create weylons. In the dust dominated period Dirac's gauge function is giving rise to dark energy, the latter causing the cosmic acceleration at present. This oscillatory universe has an initial radius identical to the Plank length = 1.616 exp (-33) cm, at present the cosmic scale factor is 3.21 exp (28) cm, while its maximum value is 8.54 exp (28) cm. All forms of matter are created by geometrically based functions of the W-D theory.Comment: 25 pages. Submitted to GR

The SAMI Galaxy Survey: Data Release One with emission-line physics value-added products

We present the first major release of data from the SAMI Galaxy Survey. This data release focuses on the emission-line physics of galaxies. Data Release One includes data for 772 galaxies, about 20 per cent of the full survey. Galaxies included have the redshift range 0.004 < z < 0.092, a large mass range (7.6 < logM*/M⊙ < 11.6), and star formation rates of ~10-4 to ~101M⊙ yr-1. For each galaxy, we include two spectral cubes and a set of spatially resolved 2D maps: single- and multi-component emission-line fits (with dust-extinction corrections for strong lines), local dust extinction, and star formation rate. Calibration of the fibre throughputs, fluxes, and differential atmospheric refraction has been improved over the Early Data Release. The data have average spatial resolution of 2.16 arcsec (full width at half-maximum) over the 15 arcsec diameter field of view and spectral (kinematic) resolution of R = 4263 (σ = 30 km s-1) around Ha. The relative flux calibration is better than 5 per cent, and absolute flux calibration has an rms of 10 per cent. The data are presented online through the Australian Astronomical Observatory's Data Central

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Association between transcatheter aortic valve replacement and subsequent infective endocarditis and in-hospital death

Importance Limited data exist on clinical characteristics and outcomes of patients who had infective endocarditis after undergoing transcatheter aortic valve replacement (TAVR). Objective To determine the associated factors, clinical characteristics, and outcomes of patients who had infective endocarditis after TAVR. Design, Setting, and Participants The Infectious Endocarditis after TAVR International Registry included patients with definite infective endocarditis after TAVR from 47 centers from Europe, North America, and South America between June 2005 and October 2015. EXPOSURE Transcatheter aortic valve replacement for incidence of infective endocarditis and infective endocarditis for in-hospital mortality. MAIN OUTCOMES AND MEASURES Infective endocarditis and in-hospital mortality after infective endocarditis. Results A total of 250 cases of infective endocarditis occurred in 20 006 patients after TAVR (incidence, 1.1% per person-year; 95% CI, 1.1%-1.4%; median age, 80 years; 64% men). Median time from TAVR to infective endocarditis was 5.3 months (interquartile range [IQR], 1.5-13.4 months). The characteristics associated with higher risk of progressing to infective endocarditis after TAVR was younger age (78.9 years vs 81.8 years; hazard ratio [HR], 0.97 per year; 95% CI, 0.94-0.99), male sex (62.0% vs 49.7%; HR, 1.69; 95% CI, 1.13-2.52), diabetes mellitus (41.7% vs 30.0%; HR, 1.52; 95% CI, 1.02-2.29), and moderate to severe aortic regurgitation (22.4% vs 14.7%; HR, 2.05; 95% CI, 1.28-3.28). Health care?associated infective endocarditis was present in 52.8% (95% CI, 46.6%-59.0%) of patients. Enterococci species and Staphylococcus aureus were the most frequently isolated microorganisms (24.6%; 95% CI, 19.1%-30.1% and 23.3%; 95% CI, 17.9%-28.7%, respectively). The in-hospital mortality rate was 36% (95% CI, 30.0%-41.9%; 90 deaths; 160 survivors), and surgery was performed in 14.8% (95% CI, 10.4%-19.2%) of patients during the infective endocarditis episode. In-hospital mortality was associated with a higher logistic EuroSCORE (23.1% vs 18.6%; odds ratio [OR], 1.03 per 1% increase; 95% CI, 1.00-1.05), heart failure (59.3% vs 23.7%; OR, 3.36; 95% CI, 1.74-6.45), and acute kidney injury (67.4% vs 31.6%; OR, 2.70; 95% CI, 1.42-5.11). The 2-year mortality rate was 66.7% (95% CI, 59.0%-74.2%; 132 deaths; 115 survivors). Conclusions and Relevance Among patients undergoing TAVR, younger age, male sex, history of diabetes mellitus, and moderate to severe residual aortic regurgitation were significantly associated with an increased risk of infective endocarditis. Patients who developed endocarditis had high rates of in-hospital mortality and 2-year mortality

SUGAR-DIP trial: Oral medication strategy versus insulin for diabetes in pregnancy, study protocol for a multicentre, open-label, non-inferiority, randomised controlled trial

Introduction In women with gestational diabetes mellitus (GDM) requiring pharmacotherapy, insulin was the established first-line treatment. More recently, oral glucose lowering drugs (OGLDs) have gained popularity as a patient-friendly, less expensive and safe alternative. Monotherapy with metformin or glibenclamide (glyburide) is incorporated in several international guidelines. In women who do not reach sufficient glucose control with OGLD monotherapy, usually insulin is added, either with or without continuation of OGLDs. No reliable data from clinical trials, however, are available on the effectiveness of a treatment strategy using all three agents, metformin, glibenclamide and insulin, in a stepwise approach, compared with insulin-only therapy for improving pregnancy outcomes. In this trial, we aim to assess the clinical effectiveness, cost-effectiveness and patient experience of a stepwise combined OGLD treatment protocol, compared with conventional insulin-based therapy for GDM. Methods The SUGAR-DIP trial is an open-label, multicentre randomised controlled non-inferiority trial. Participants are women with GDM who do not reach target glycaemic control with modification of diet, between 16 and 34 weeks of gestation. Participants will be randomised to either treatment with OGLDs, starting with metformin and supplemented as needed with glibenclamide, or randomised to treatment with insulin. In women who do not reach target glycaemic control with combined metformin and glibenclamide, glibenclamide will be substituted with insulin, while continuing metformin. The primary outcome will be the incidence of large-for-gestational-age infants (birth weight >90th percentile). Secondary outcome measures are maternal diabetes-related endpoints, obstetric complications, neonatal complications and cost-effectiveness analysis. Outcomes will be analysed according to the intention-to-treat principle. Ethics and dissemination The study protocol was approved by the Ethics Committee of the Utrecht University Medical Centre. Approval by the boards of management for all participating hospitals will be obtained. Trial results will be submitted for publication in peer-reviewed journals

Phylogenomics and the rise of the angiosperms

Angiosperms are the cornerstone of most terrestrial ecosystems and human livelihoods1,2. A robust understanding of angiosperm evolution is required to explain their rise to ecological dominance. So far, the angiosperm tree of life has been determined primarily by means of analyses of the plastid genome3,4. Many studies have drawn on this foundational work, such as classification and first insights into angiosperm diversification since their Mesozoic origins5,6,7. However, the limited and biased sampling of both taxa and genomes undermines confidence in the tree and its implications. Here, we build the tree of life for almost 8,000 (about 60%) angiosperm genera using a standardized set of 353 nuclear genes8. This 15-fold increase in genus-level sampling relative to comparable nuclear studies9 provides a critical test of earlier results and brings notable change to key groups, especially in rosids, while substantiating many previously predicted relationships. Scaling this tree to time using 200 fossils, we discovered that early angiosperm evolution was characterized by high gene tree conflict and explosive diversification, giving rise to more than 80% of extant angiosperm orders. Steady diversification ensued through the remaining Mesozoic Era until rates resurged in the Cenozoic Era, concurrent with decreasing global temperatures and tightly linked with gene tree conflict. Taken together, our extensive sampling combined with advanced phylogenomic methods shows the deep history and full complexity in the evolution of a megadiverse clade

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 7 10 124 ) or temporal stage (p = 3.96 7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine