H-ATLAS/GAMA and HeViCS - dusty early-type galaxies in different environments

NKA acknowledges the support of the Science and Technology Facilities Council. LD, RJI and SJM acknowledge support from the European Research Council Advanced Grant COSMICISM. IDL gratefully acknowledges the support of the Flemish Fund for Scientific Research (FWO-Vlaanderen). KR acknowledges support from the European Research Council Starting Grant SEDmorph (P.I. V. Wild). Date of acceptance: 22/05/2015The Herschel Space Observatory has had a tremendous impact on the study of extragalactic dust. Specifically, early-type galaxies (ETG) have been the focus of several studies. In this paper, we combine results from two Herschel studies -a Virgo cluster study Herschel Virgo Cluster Survey (HeViCS) and a broader, low-redshift Herschel-Astrophysical Terahertz Large Area Survey (H-ATLAS)/Galaxy and Mass Assembly (GAMA) study -and contrast the dust and associated properties for similar mass galaxies. This comparison is motivated by differences in results exhibited between multiple Herschel studies of ETG. A comparison between consistent modified blackbody derived dust mass is carried out, revealing strong differences between the two samples in both dust mass and dust-to-stellar mass ratio. In particular, the HeViCS sample lacks massive ETG with as high a specific dust content as found in H-ATLAS. This is most likely connected with the difference in environment for the two samples. We calculate nearest neighbour environment densities in a consistent way, showing that H-ATLAS ETG occupy sparser regions of the local Universe, whereas HeViCS ETG occupy dense regions. This is also true for ETG that are not Herschel-detected but are in the Virgo and GAMA parent samples. Spectral energy distributions are fit to the panchromatic data. From these, we find that in H-ATLAS the specific star formation rate anticorrelates with stellar mass and reaches values as high as in our Galaxy. On the other hand HeViCS ETG appear to have little star formation. Based on the trends found here, H-ATLAS ETG are thought to have more extended star formation histories and a younger stellar population than HeViCS ETG.Publisher PDFPeer reviewe

Initial combination of linagliptin and metformin compared with linagliptin monotherapy in patients with newly diagnosed type 2 diabetes and marked hyperglycaemia: a randomized, double-blind, active-controlled, parallel group, multinational clinical trial.

Aims To evaluate glucose-lowering treatment strategies with linagliptin and metformin in people with newly diagnosed type 2 diabetes and marked hyperglycaemia, a prevalent population for which few dedicated studies of oral antidiabetes drugs have been conducted. Methods A total of 316 patients, with type 2 diabetes diagnosed for ≤12 months and with glycated haemoglobin (HbA1c) concentration in the range 8.5–12.0%, were randomized 1:1 to double-blind, free-combination treatment with linagliptin 5 mg once daily and metformin twice daily (uptitrated to 2000 mg/day maximum) or to linagliptin monotherapy. The primary endpoint was change in HbA1c concentration from baseline at week 24 (per-protocol completers' cohort: n = 245). Results The mean (standard deviation) age and HbA1c at baseline were 48.8 (11.0) years and 9.8 (1.1)%, respectively. At week 24, the mean ± standard error (s.e.) HbA1c decreased from baseline by –2.8 ± 0.1% with linagliptin/metformin and –2.0 ± 0.1% with linagliptin; a treatment difference of –0.8% (95% confidence interval –1.1 to –0.5; p <0.0001). Similar results were observed in a sensitivity analysis based on intent-to-treat principles: adjusted mean ± s.e. changes in HbA1c of –2.7 ± 0.1% and –1.8 ± 0.1%, respectively; treatment difference of –0.9% (95% CI –1.3 to –0.6; p <0.0001). A treatment response of HbA1c <7.0% was achieved by 61 and 40% of patients in the linagliptin/metformin and linagliptin groups, respectively. Few patients experienced drug-related adverse events (8.8 and 5.7% of patients in the linagliptin/metformin and linagliptin groups, respectively). Hypoglycaemia occurred in 1.9 and 3.2% of patients in the linagliptin/metformin and linagliptin groups, respectively (no severe episodes). Body weight decreased significantly with the combination therapy (–1.3 kg between-group difference; p =0.0033). Conclusions Linagliptin in initial combination with metformin in patients with newly diagnosed type 2 diabetes and marked hyperglycaemia, an understudied group, elicited significant improvements in glycaemic control with a low incidence of hypoglycaemia, weight gain or other adverse effects. These results support early combination treatment strategies and suggest that newly diagnosed patients with marked hyperglycaemia may be effectively managed with oral, non-insulin therapy

Fish heating tolerance scales similarly across individual physiology and populations

Extrapolating patterns from individuals to populations informs climate vulnerability models, yet biological responses to warming are uncertain at both levels. Here we contrast data on the heating tolerances of fishes from laboratory experiments with abundance patterns of wild populations. We find that heating tolerances in terms of individual physiologies in the lab and abundance in the wild decline with increasing temperature at the same rate. However, at a given acclimation temperature or optimum temperature, tropical individuals and populations have broader heating tolerances than temperate ones. These congruent relationships implicate a tight coupling between physiological and demographic processes underpinning macroecological patterns, and identify vulnerability in both temperate and tropical species

Improved numerical stability of stationary black hole evolution calculations

We experiment with modifications of the BSSN form of the Einstein field equations (a reformulation of the ADM equations) and demonstrate how these modifications affect the stability of numerical black hole evolution calculations. We use excision to evolve both non-rotating and rotating Kerr-Schild black holes in octant and equatorial symmetry, and without any symmetry assumptions, and obtain accurate and stable simulations for specific angular momenta J/M of up to about 0.9M.Comment: 13 pages, 11 figures, 1 typo in Eq. (20) correcte

Climate resilience in marine protected areas and the ‘Protection Paradox’

Restricting human activities through Marine Protected Areas (MPAs) is assumed to create more resilient biological communities with a greater capacity to resist and recover following climate events. Here we review the evidence linking protection from local pressures (e.g., fishing and habitat destruction) with increased resilience. Despite strong theoretical underpinnings, studies have only rarely attributed resilience responses to the recovery of food webs and habitats, and increases in the diversity of communities and populations. When detected, resistance to ocean warming and recovery after extreme events in MPAs have small effect sizes against a backdrop of natural variability. By contrast, large die-offs are well described from MPAs following climate stress events. This may be in part because protection from one set of pressures or drivers (such as fishing) can select for species that are highly sensitive to others (such as warming), creating a ‘Protection Paradox’. Given that climate change is overwhelming the resilience capacity of marine ecosystems, the only primary solution is to reduce carbon emissions. High-quality monitoring data in both space and time can also identify emergent resilience signals that do exist, in combination with adequate reference data to quantify the initial system state. This knowledge will allow networks of diverse protected areas to incorporate spatial refugia against climate change, and identify resilient biological components of natural systems. Sufficient spatial replication further offers insurance against losses in any given MPA, and the possibility for many weak signals of resilience to accumulate

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

A review of spatial causal inference methods for environmental and epidemiological applications

The scientific rigor and computational methods of causal inference have had great impacts on many disciplines, but have only recently begun to take hold in spatial applications. Spatial casual inference poses analytic challenges due to complex correlation structures and interference between the treatment at one location and the outcomes at others. In this paper, we review the current literature on spatial causal inference and identify areas of future work. We first discuss methods that exploit spatial structure to account for unmeasured confounding variables. We then discuss causal analysis in the presence of spatial interference including several common assumptions used to reduce the complexity of the interference patterns under consideration. These methods are extended to the spatiotemporal case where we compare and contrast the potential outcomes framework with Granger causality, and to geostatistical analyses involving spatial random fields of treatments and responses. The methods are introduced in the context of observational environmental and epidemiological studies, and are compared using both a simulation study and analysis of the effect of ambient air pollution on COVID-19 mortality rate. Code to implement many of the methods using the popular Bayesian software OpenBUGS is provided

A history of high-power laser research and development in the United Kingdom

The first demonstration of laser action in ruby was made in 1960 by T. H. Maiman of Hughes Research Laboratories, USA. Many laboratories worldwide began the search for lasers using different materials, operating at different wavelengths. In the UK, academia, industry and the central laboratories took up the challenge from the earliest days to develop these systems for a broad range of applications. This historical review looks at the contribution the UK has made to the advancement of the technology, the development of systems and components and their exploitation over the last 60 years

National laboratory-based surveillance system for antimicrobial resistance: a successful tool to support the control of antimicrobial resistance in the Netherlands

An important cornerstone in the control of antimicrobial resistance (AMR) is a well-designed quantitative system for the surveillance of spread and temporal trends in AMR. Since 2008, the Dutch national AMR surveillance system, based on routine data from medical microbiological laboratories (MMLs), has developed into a successful tool to support the control of AMR in the Netherlands. It provides background information for policy making in public health and healthcare services, supports development of empirical antibiotic therapy guidelines and facilitates in-depth research. In addition, participation of the MMLs in the national AMR surveillance network has contributed to sharing of knowledge and quality improvement. A future improvement will be the implementation of a new semantic standard together with standardised data transfer, which will reduce errors in data handling and enable a more real-time surveillance. Furthermore, the