Variability in COVID-19 in-hospital mortality rates between national health service trusts and regions in England: A national observational study for the Getting It Right First Time Programme

Background A key first step in optimising COVID-19 patient outcomes during future case-surges is to learn from the experience within individual hospitals during the early stages of the pandemic. The aim of this study was to investigate the extent of variation in COVID-19 outcomes between National Health Service (NHS) hospital trusts and regions in England using data from March–July 2020. Methods This was a retrospective observational study using the Hospital Episode Statistics administrative dataset. Patients aged ≥ 18 years who had a diagnosis of COVID-19 during a hospital stay in England that was completed between March 1st and July 31st, 2020 were included. In-hospital mortality was the primary outcome of interest. In secondary analysis, critical care admission, length of stay and mortality within 30 days of discharge were also investigated. Multilevel logistic regression was used to adjust for covariates. Findings There were 86,356 patients with a confirmed diagnosis of COVID-19 included in the study, of whom 22,944 (26.6%) died in hospital with COVID-19 as the primary cause of death. After adjusting for covariates, the extent of the variation in-hospital mortality rates between hospital trusts and regions was relatively modest. Trusts with the largest baseline number of beds and a greater proportion of patients admitted to critical care had the lowest in-hospital mortality rates. Interpretation There is little evidence of clustering of deaths within hospital trusts. There may be opportunities to learn from the experience of individual trusts to help prepare hospitals for future case-surges

Weather and Financial Risk-Taking: Is Happiness the Channel?

Weather variables, and sunshine in particular, are found to be strongly correlated with financial variables. I consider self-reported happiness as a channel through which sunshine affects financial variables. I examine the influence of happiness on risk-taking behavior by instrumenting individual happiness with regional sunshine, and I find that happy people appear to be more risk-averse in financial decisions, and accordingly choose safer investments. Happy people take more time for making decisions and have more self-control. Happy people also expect to live longer and accordingly seem more concerned about the future than the present, and expect less inflation

The Inner-Shelf Dynamics Experiment

17 USC 105 interim-entered record; under review.The article of record as published may be found at http://dx.doi.org/10.1175/BAMS-D-19-0281.1The inner shelf, the transition zone between the surfzone and the midshelf, is a dynamically complex region with the evolution of circulation and stratification driven by multiple physical processes. Cross-shelf exchange through the inner shelf has important implications for coastal water quality, ecological connectivity, and lateral movement of sediment and heat. The Inner-Shelf Dynamics Experiment (ISDE) was an intensive, coordinated, multi-institution field experiment from September–October 2017, conducted from the midshelf, through the inner shelf, and into the surfzone near Point Sal, California. Satellite, airborne, shore- and ship-based remote sensing, in-water moorings and ship-based sampling, and numerical ocean circulation models forced by winds, waves, and tides were used to investigate the dynamics governing the circulation and transport in the inner shelf and the role of coastline variability on regional circulation dynamics. Here, the following physical processes are highlighted: internal wave dynamics from the midshelf to the inner shelf; flow separation and eddy shedding off Point Sal; offshore ejection of surfzone waters from rip currents; and wind-driven subtidal circulation dynamics. The extensive dataset from ISDE allows for unprecedented investigations into the role of physical processes in creating spatial heterogeneity, and nonlinear interactions between various inner-shelf physical processes. Overall, the highly spatially and temporally resolved oceanographic measurements and numerical simulations of ISDE provide a central framework for studies exploring this complex and fascinating region of the ocean.U.S. Office of Naval Research (ONR)ONR Departmental Research Initiative (DRI)Inner-Shelf Dynamics Experiment (ISDE

Refining transcriptional programs in kidney development by integration of deep RNA-sequencing and array-based spatial profiling

<p>Abstract</p> <p>Background</p> <p>The developing mouse kidney is currently the best-characterized model of organogenesis at a transcriptional level. Detailed spatial maps have been generated for gene expression profiling combined with systematic <it>in situ </it>screening. These studies, however, fall short of capturing the transcriptional complexity arising from each locus due to the limited scope of microarray-based technology, which is largely based on "gene-centric" models.</p> <p>Results</p> <p>To address this, the polyadenylated RNA and microRNA transcriptomes of the 15.5 dpc mouse kidney were profiled using strand-specific RNA-sequencing (RNA-Seq) to a depth sufficient to complement spatial maps from pre-existing microarray datasets. The transcriptional complexity of RNAs arising from mouse RefSeq loci was catalogued; including 3568 alternatively spliced transcripts and 532 uncharacterized alternate 3' UTRs. Antisense expressions for 60% of RefSeq genes was also detected including uncharacterized non-coding transcripts overlapping kidney progenitor markers, Six2 and Sall1, and were validated by section <it>in situ </it>hybridization. Analysis of genes known to be involved in kidney development, particularly during mesenchymal-to-epithelial transition, showed an enrichment of non-coding antisense transcripts extended along protein-coding RNAs.</p> <p>Conclusion</p> <p>The resulting resource further refines the transcriptomic cartography of kidney organogenesis by integrating deep RNA sequencing data with locus-based information from previously published expression atlases. The added resolution of RNA-Seq has provided the basis for a transition from classical gene-centric models of kidney development towards more accurate and detailed "transcript-centric" representations, which highlights the extent of transcriptional complexity of genes that direct complex development events.</p

Global Patterns and Controls of Nutrient Immobilization On Decomposing Cellulose In Riverine Ecosystems

Microbes play a critical role in plant litter decomposition and influence the fate of carbon in rivers and riparian zones. When decomposing low-nutrient plant litter, microbes acquire nitrogen (N) and phosphorus (P) from the environment (i.e., nutrient immobilization), and this process is potentially sensitive to nutrient loading and changing climate. Nonetheless, environmental controls on immobilization are poorly understood because rates are also influenced by plant litter chemistry, which is coupled to the same environmental factors. Here we used a standardized, low-nutrient organic matter substrate (cotton strips) to quantify nutrient immobilization at 100 paired stream and riparian sites representing 11 biomes worldwide. Immobilization rates varied by three orders of magnitude, were greater in rivers than riparian zones, and were strongly correlated to decomposition rates. In rivers, P immobilization rates were controlled by surface water phosphate concentrations, but N immobilization rates were not related to inorganic N. The N:P of immobilized nutrients was tightly constrained to a molar ratio of 10:1 despite wide variation in surface water N:P. Immobilization rates were temperature-dependent in riparian zones but not related to temperature in rivers. However, in rivers nutrient supply ultimately controlled whether microbes could achieve the maximum expected decomposition rate at a given temperature

An Experimental Component Index for the CPI: From Annual Computer Data to Monthly Data on Other Goods

The CPI component indices are obtained from comparing price quotes at a given store in different periods. If we omit comparisons from goods in the store in the initial, but not in the comparison, period we generate a selection bias: goods that exit are disproportionately obsolete goods that have falling prices. Building on Pakes (2003), we explain why standard hedonic predictions for second-period prices of exiting goods do not account for this bias. New hedonic methods are derived, shown to have desirable properties, and are applied to three CPI samples where they generate significant selection corrections. (JEL C43, E31)