The insignificant evolution of the richness-mass relation of galaxy clusters

We analysed the richness--mass scaling of 23 very massive clusters at $0.15<z<0.55$ with homogenously measured weak-lensing masses and richnesses within a fixed aperture of $0.5$ Mpc radius. We found that the richness--mass scaling is very tight (the scatter is $<0.09$ dex with 90 \% probability) and independent of cluster evolutionary status and morphology. This implies a close association between infall and evolution of dark matter and galaxies in the central region of clusters. We also found that the evolution of the richness-mass intercept is minor at most, and, given the minor mass evolution across the studied redshift range, the richness evolution of individual massive clusters also turns out to be very small. Finally, it was paramount to account for the cluster mass function and the selection function. Ignoring them would led to biases larger than the (otherwise quoted) errors. Our study benefits from: a) weak-lensing masses instead of proxy-based masses thereby removing the ambiguity between a real trend and one induced by an accounted evolution of the used mass proxy; b) the use of projected masses that simplify the statistical analysis thereby not requiring consideration of the unknown covariance induced by the cluster orientation/triaxiality; c) the use of aperture masses as they are free of the pseudo-evolution of mass definitions anchored to the evolving density of the Universe; d) a proper accounting of the sample selection function and of the Malmquist-like effect induced by the cluster mass function; e) cosmological simulations for the computation of the cluster mass function, its evolution, and the mass growth of each individual cluster.Comment: A&A, in press. Fixed pdf generation proble

Assessing Impacts on Unplanned Hospitalisations of Care Quality and Access Using a Structural Equation Method: With a Case Study of Diabetes

Background: Enhanced quality of care and improved access are central to effective primary care management of long term conditions. However, research evidence is inconclusive in establishing a link between quality of primary care, or access, and adverse outcomes, such as unplanned hospitalisation. Methods: This paper proposes a structural equation model for quality and access as latent variables affecting adverse outcomes, such as unplanned hospitalisations. In a case study application, quality of care (QOC) is defined in relation to diabetes, and the aim is to assess impacts of care quality and access on unplanned hospital admissions for diabetes, while allowing also for socio-economic deprivation, diabetes morbidity, and supply effects. The study involves 90 general practitioner (GP) practices in two London Clinical Commissioning Groups, using clinical quality of care indicators, and patient survey data on perceived access. Results: As a single predictor, quality of care has a significant negative impact on emergency admissions, and this significant effect remains when socio-economic deprivation and morbidity are allowed. In a full structural equation model including access, the probability that QOC negatively impacts on unplanned admissions exceeds 0.9. Furthermore, poor access is linked to deprivation, diminished QOC, and larger list sizes. Conclusions: Using a Bayesian inference methodology, the evidence from the analysis is weighted towards negative impacts of higher primary care quality and improved access on unplanned admissions. The methodology of the paper is potentially applicable to other long term conditions, and relevant when care quality and access cannot be measured directly and are better regarded as latent variables

Spatially Interpolated Disease Prevalence Estimation Using Collateral Indicators of Morbidity and Ecological Risk

This paper considers estimation of disease prevalence for small areas (neighbourhoods) when the available observations on prevalence are for an alternative partition of a region, such as service areas. Interpolation to neighbourhoods uses a kernel method extended to take account of two types of collateral information. The first is morbidity and service use data, such as hospital admissions, observed for neighbourhoods. Variations in morbidity and service use are expected to reflect prevalence. The second type of collateral information is ecological risk factors (e.g., pollution indices) that are expected to explain variability in prevalence in service areas, but are typically observed only for neighbourhoods. An application involves estimating neighbourhood asthma prevalence in a London health region involving 562 neighbourhoods and 189 service (primary care) areas

Time Course of Changes in Peripheral Blood Gene Expression During Medication Treatment for Major Depressive Disorder.

Changes in gene expression (GE) during antidepressant treatment may increase understanding of the action of antidepressant medications and serve as biomarkers of efficacy. GE changes in peripheral blood are desirable because they can be assessed easily on multiple occasions during treatment. We report here on GE changes in 68 individuals who were treated for 8 weeks with either escitalopram alone, or escitalopram followed by bupropion. GE changes were assessed after 1, 2, and 8 weeks of treatment, with significant changes observed in 156, 121, and 585 peripheral blood gene transcripts, respectively. Thirty-one transcript changes were shared between the 1- and 8-week time points (seven upregulated, 24 downregulated). Differences were detected between the escitalopram- and bupropion-treated subjects, although there was no significant association between GE changes and clinical outcome. A subset of 18 genes overlapped with those previously identified as differentially expressed in subjects with MDD compared with healthy control subjects. There was statistically significant overlap between genes differentially expressed in the current and previous studies, with 10 genes overlapping in at least two previous studies. There was no enrichment for genes overexpressed in nervous system cell types, but there was a trend toward enrichment for genes in the WNT/β-catenin pathway in the anterior thalamus; three genes in this pathway showed differential expression in the present and in three previous studies. Our dataset and other similar studies will provide an important source of information about potential biomarkers of recovery and for potential dysregulation of GE in MDD

Chapter 14: Vulnerability of seabirds on the Great Barrier Reef to climate change

Seabirds are highly visible, charismatic predators in marine ecosystems that are defined as feeding exclusively at sea, in either nearshore, offshore or pelagic waters. At a conservative estimate there are approximately 0.7 billion individuals of 309 species of seabirds globally. Such high population abundance means that in all ecosystems where seabirds occur the levels of marine resources they consume are significant. Such high consumption rates also mean that seabirds play a number of important functional roles in marine ecosystems, including the transfer of nutrients from offshore and pelagic areas to islands and reefs, seed dispersal and the distribution of organic matter into lower parts of the developing soil profile (eg burrow-nesting species such as shearwaters).This is Chapter 14 of Climate change and the Great Barrier Reef: a vulnerability assessment. The entire book can be found at http://hdl.handle.net/11017/13

Bayes linear kinematics in the analysis of failure rates and failure time distributions

Collections of related Poisson or binomial counts arise, for example, from a number of different failures in similar machines or neighbouring time periods. A conventional Bayesian analysis requires a rather indirect prior specification and intensive numerical methods for posterior evaluations. An alternative approach using Bayes linear kinematics in which simple conjugate specifications for individual counts are linked through a Bayes linear belief structure is presented. Intensive numerical methods are not required. The use of transformations of the binomial and Poisson parameters is proposed. The approach is illustrated in two examples, one involving a Poisson count of failures, the other involving a binomial count in an analysis of failure times

Suicide variations between English neighbourhoods over 2017-21: The role of spatial scale.

Geographic studies of suicide variation typically focus on predictors at the same level as the event rates, and the possible interplay between different spatial scales does not generally figure. In this paper we focus on suicide variations between 6856 small area census units in England, but against a background provided by nine regions, broad urban-rural categories, and 155 local labour markets. Suicide death totals vary considerably between the small areas, with more areas than expected having no deaths, so we apply zero inflated regression. With this framework, we consider the relative contribution of factors at higher and lower spatial scales in explaining small area suicide contrasts, and why some areas have unduly elevated or unduly low suicide rates. We find significantly lower suicide levels in English metropolitan regions, after allowing for neighbourhood influences, but considerable heterogeneity in risks within broader spatial units. Varying incidence in general is associated significantly with all observed neighbourhood risk factors (social fragmentation, socioeconomic status, mental ill-health, ethnic mix), but low fragmentation and low psychiatric morbidity are the only significant influences on unduly low incidence