Do residents’ perceptions of being well-placed and objective presence of local amenities match? A case study in West Central Scotland, UK

Background:<p></p> Recently there has been growing interest in how neighbourhood features, such as the provision of local facilities and amenities, influence residents’ health and well-being. Prior research has measured amenity provision through subjective measures (surveying residents’ perceptions) or objective (GIS mapping of distance) methods. The latter may provide a more accurate measure of physical access, but residents may not use local amenities if they do not perceive them as ‘local’. We believe both subjective and objective measures should be explored, and use West Central Scotland data to investigate correspondence between residents’ subjective assessments of how well-placed they are for everyday amenities (food stores, primary and secondary schools, libraries, pharmacies, public recreation), and objective GIS-modelled measures, and examine correspondence by various sub-groups.<p></p> Methods:<p></p> ArcMap was used to map the postal locations of ‘Transport, Health and Well-being 2010 Study’ respondents (n = 1760), and the six amenities, and the presence/absence of each of them within various straight-line and network buffers around respondents’ homes was recorded. SPSS was used to investigate whether objective presence of an amenity within a specified buffer was perceived by a respondent as being well-placed for that amenity. Kappa statistics were used to test agreement between measures for all respondents, and by sex, age, social class, area deprivation, car ownership, dog ownership, walking in the local area, and years lived in current home.<p></p> Results:<p></p> In general, there was poor agreement (Kappa <0.20) between perceptions of being well-placed for each facility and objective presence, within 800 m and 1000 m straight-line and network buffers, with the exception of pharmacies (at 1000 m straight-line) (Kappa: 0.21). Results varied between respondent sub-groups, with some showing better agreement than others. Amongst sub-groups, at 800 m straight-line buffers, the highest correspondence between subjective and objective measures was for pharmacies and primary schools, and at 1000 m, for pharmacies, primary schools and libraries. For road network buffers under 1000 m, agreement was generally poor.<p></p> Conclusion:<p></p> Respondents did not necessarily regard themselves as well-placed for specific amenities when these amenities were present within specified boundaries around their homes, with some exceptions; the picture is not clear-cut with varying findings between different amenities, buffers, and sub-groups

NEAT: An efficient network enrichment analysis test

Background: Network enrichment analysis is a powerful method, which allows to integrate gene enrichment analysis with the information on relationships between genes that is provided by gene networks. Existing tests for network enrichment analysis deal only with undirected networks, they can be computationally slow and are based on normality assumptions. Results: We propose NEAT, a test for network enrichment analysis. The test is based on the hypergeometric distribution, which naturally arises as the null distribution in this context. NEAT can be applied not only to undirected, but to directed and partially directed networks as well. Our simulations indicate that NEAT is considerably faster than alternative resampling-based methods, and that its capacity to detect enrichments is at least as good as the one of alternative tests. We discuss applications of NEAT to network analyses in yeast by testing for enrichment of the Environmental Stress Response target gene set with GO Slim and KEGG functional gene sets, and also by inspecting associations between functional sets themselves. Conclusions: NEAT is a flexible and efficient test for network enrichment analysis that aims to overcome some limitations of existing resampling-based tests. The method is implemented in the R package neat, which can be freely downloaded from CRAN ( https://cran.r-project.org/package=neat )

Assessing causal relationships in genomics: From Bradford-Hill criteria to complex gene-environment interactions and directed acyclic graphs

Observational studies of human health and disease (basic, clinical and epidemiological) are vulnerable to methodological problems -such as selection bias and confounding- that make causal inferences problematic. Gene-disease associations are no exception, as they are commonly investigated using observational designs. A rich body of knowledge exists in medicine and epidemiology on the assessment of causal relationships involving personal and environmental causes of disease; it includes seminal causal criteria developed by Austin Bradford Hill and more recently applied directed acyclic graphs (DAGs). However, such knowledge has seldom been applied to assess causal relationships in clinical genetics and genomics, even in studies aimed at making inferences relevant for human health. Conversely, incorporating genetic causal knowledge into clinical and epidemiological causal reasoning is still a largely unexplored area

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

ASPM and microcephalin expression in epithelial ovarian cancer correlates with tumour grade and survival

BACKGROUND: The clinico-pathological and molecular heterogeneity of epithelial ovarian cancer (EOC) complicates its early diagnosis and successful treatment. Highly aneuploid tumours and the presence of ascitic fluids are hallmarks of EOC. Two microcephalyassociated proteins, abnormal spindle-like microcephaly-associated protein (ASPM) and microcephalin, are involved in mitosis and DNA damage repair. Their expression is deregulated at the RNA level in EOC. Here, ASPM and microcephalin protein expression in primary cultures established from the ascites of patients with EOC was determined and correlated with clinical data to assess their suitability as biomarkers. METHODS: Five established ovarian cancer cell lines, cells derived from two benign ovarian ascites samples and 40 primary cultures of EOC derived from ovarian ascites samples were analysed by protein slot blotting and/or immunofluorescence to determine ASPM and microcephalin protein levels and their cellular localisation. Results were correlated with clinico-pathological data. RESULTS: A statistically significant correlation was identified for ASPM localisation and tumour grade, with high levels of cytoplasmic ASPM correlating with grade 1 tumours. Conversely, cytoplasmic microcephalin was only identified in high-grade tumours. Furthermore, low levels of nuclear microcephalin correlated with reduced patient survival. CONCLUSION: Our results suggest that ASPM and microcephalin have the potential to be biomarkers in ovarian cance

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

A general method for controlling and resolving rotational orientation of molecules in molecule-surface collisions

Theoretical Chemistr