Quantifying and valuing carbon flows and stores in coastal and shelf ecosystems in the UK

Evidence shows that habitats with potential to mitigate against greenhouse gases emissions, by taking up and storing CO2, are being lost due to the effects of on-going human activities and climate change. The carbon storage by terrestrial habitats (e.g. tropical forests) and the role of coastal habitats (‘Blue Carbon’) as carbon storage sinks is well recognised. Offshore shelf sediments are also a manageable carbon store, covering ∼9% of global marine area, but not currently protected by international agreements to enable their conservation. Through a scenario analysis, we explore the economic value of the damage of human activities and climate change can inflict on UK marine habitats, including shelf sea sediments. In a scenario of increased human and climate pressures over a 25-year period, we estimate damage costs up to US$12.5 billion from carbon release linked to disturbance of coastal and shelf sea sediment carbon stores. It may be possible to manage socio-economic pressure to maintain sedimentary carbon storage, but the trade-offs with other global social welfare benefits such as food security will have to be taken into account. To develop effective incentive mechanisms to preserve these valuable coastal and marine ecosystems within a sustainability governance framework, robust evidence is required

Lesbian and bisexual women's human rights, sexual rights and sexual citizenship: negotiating sexual health in England.

Lesbian and bisexual women's sexual health is neglected in much Government policy and practice in England and Wales. This paper examines lesbian and bisexual women's negotiation of sexual health, drawing on findings from a small research project. Themes explored include invisibility and lack of information, influences on decision-making and sexual activities and experiences of services and barriers to sexual healthcare. Key issues of importance in this respect are homophobic and heterosexist social contexts. Drawing on understandings of lesbian, gay and bisexual human rights, sexual rights and sexual citizenship, it is argued that these are useful lenses through which to examine and address lesbian and bisexual women's sexual health and related inequalities

Using Observational Data to Calibrate Simulation Models

BACKGROUND: Individual-level simulation models are valuable tools for comparing the impact of clinical or public health interventions on population health and cost outcomes over time. However, a key challenge is ensuring that outcome estimates correctly reflect real-world impacts. Calibration to targets obtained from randomized trials may be insufficient if trials do not exist for populations, time periods, or interventions of interest. Observational data can provide a wider range of calibration targets but requires methods to adjust for treatment-confounder feedback. We propose the use of the parametric g-formula to estimate calibration targets and present a case-study to demonstrate its application. METHODS: We used the parametric g-formula applied to data from the HIV-CAUSAL Collaboration to estimate calibration targets for 7-y risks of AIDS and/or death (AIDS/death), as defined by the Center for Disease Control and Prevention under 3 treatment initiation strategies. We compared these targets to projections from the Cost-Effectiveness of Preventing AIDS Complications (CEPAC) model for treatment-naïve individuals presenting to care in the following year ranges: 1996 to 1999, 2000 to 2002, or 2003 onwards. RESULTS: The parametric g-formula estimated a decreased risk of AIDS/death over time and with earlier treatment. The uncalibrated CEPAC model successfully reproduced targets obtained via the g-formula for baseline 1996 to 1999, but over-estimated calibration targets in contemporary populations and failed to reproduce time trends in AIDS/death risk. Calibration to g-formula targets improved CEPAC model fit for contemporary populations. CONCLUSION: Individual-level simulation models are developed based on best available information about disease processes in one or more populations of interest, but these processes can change over time or between populations. The parametric g-formula provides a method for using observational data to obtain valid calibration targets and enables updating of simulation model inputs when randomized trials are not available

Joint care can outweigh costs of nonkin competition in communal breeders

Competition between offspring can greatly influence offspring fitness and parental investment decisions, especially in communal breeders where unrelated competitors have less incentive to concede resources. Given the potential for escalated conflict, it remains unclear what mechanisms facilitate the evolution of communal breeding among unrelated females. Resolving this question requires simultaneous consideration of offspring in noncommunal and communal nurseries, but such comparisons are missing. In the Seychelles warbler Acrocephalus sechellensis, we compare nestling pairs from communal nests (2 mothers) and noncommunal nests (1 mother) with singleton nestlings. Our results indicate that increased provisioning rate can act as a mechanism to mitigate the costs of offspring rivalry among nonkin. Increased provisioning in communal broods, as a consequence of having 2 female parents, mitigates any elevated costs of offspring rivalry among nonkin: per-capita provisioning and survival was equal in communal broods and singletons, but lower in noncommunal broods. Individual offspring costs were also more divergent in noncommunal broods, likely because resource limitation exacerbates differences in competitive ability between nestlings. It is typically assumed that offspring rivalry among nonkin will be more costly because offspring are not driven by kin selection to concede resources to their competitors. Our findings are correlational and require further corroboration, but may help explain the evolutionary maintenance of communal breeding by providing a mechanism by which communal breeders can avoid these costs

Associations between Indigenous Australian oral health literacy and self-reported oral health outcomes

Objectives: To determine oral health literacy (REALD-30) and oral health literacy-related outcome associations, and to calculate if oral health literacy-related outcomes are risk indicators for poor self-reported oral health among rural-dwelling Indigenous Australians. Methods: 468 participants (aged 17-72 years, 63% female) completed a self-report questionnaire. REALD-30 and oral health literacy-related outcome associations were determined through bivariate analysis. Multivariate modelling was used to calculate risk indicators for poor self-reported oral health. Results: REALD-30 scores were lower among those who believed teeth should be infrequently brushed, believed cordial was good for teeth, did not own a toothbrush or owned a toothbrush but brushed irregularly. Tooth removal risk indicators included being older, problem-based dental attendance and believing cordial was good for teeth. Poor self-rated oral health risk indicators included being older, healthcare card ownership, difficulty paying dental bills, problem-based dental attendance, believing teeth should be brushed infrequently and irregular brushing. Perceived need for dental care risk indicators included being female and problem-based dental attendance. Perceived gum disease risk indicators included being older and irregular brushing. Feeling uncomfortable about oro-facial appearance risk indicators included problem-based dental attendance and irregular brushing. Food avoidance risk indicators were being female, difficulty paying dental bills, problem-based dental attendance and irregular brushing. Poor oral health-related quality of life risk indicators included difficulty paying dental bills and problem-based dental attendance. Conclusions: REALD-30 was significantly associated with oral health literacy-related outcomes. Oral health literacy-related outcomes were risk indicators for each of the poor self-reported oral health domains among this marginalised population.Eleanor J. Parker and Lisa M. Jamieso

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Comparing methods to estimate treatment effects on a continuous outcome in multicentre randomized controlled trials: A simulation study

<p>Abstract</p> <p>Background</p> <p>Multicentre randomized controlled trials (RCTs) routinely use randomization and analysis stratified by centre to control for differences between centres and to improve precision. No consensus has been reached on how to best analyze correlated continuous outcomes in such settings. Our objective was to investigate the properties of commonly used statistical models at various levels of clustering in the context of multicentre RCTs.</p> <p>Methods</p> <p>Assuming no treatment by centre interaction, we compared six methods (ignoring centre effects, including centres as fixed effects, including centres as random effects, generalized estimating equation (GEE), and fixed- and random-effects centre-level analysis) to analyze continuous outcomes in multicentre RCTs using simulations over a wide spectrum of intraclass correlation (ICC) values, and varying numbers of centres and centre size. The performance of models was evaluated in terms of bias, precision, mean squared error of the point estimator of treatment effect, empirical coverage of the 95% confidence interval, and statistical power of the procedure.</p> <p>Results</p> <p>While all methods yielded unbiased estimates of treatment effect, ignoring centres led to inflation of standard error and loss of statistical power when within centre correlation was present. Mixed-effects model was most efficient and attained nominal coverage of 95% and 90% power in almost all scenarios. Fixed-effects model was less precise when the number of centres was large and treatment allocation was subject to chance imbalance within centre. GEE approach underestimated standard error of the treatment effect when the number of centres was small. The two centre-level models led to more variable point estimates and relatively low interval coverage or statistical power depending on whether or not heterogeneity of treatment contrasts was considered in the analysis.</p> <p>Conclusions</p> <p>All six models produced unbiased estimates of treatment effect in the context of multicentre trials. Adjusting for centre as a random intercept led to the most efficient treatment effect estimation across all simulations under the normality assumption, when there was no treatment by centre interaction.</p

A horizon scan of issues affecting UK forest management within 50 years

Forests are in the spotlight: they are expected to play a pivotal role in our response to society’s greatest challenges, such as the climate and biodiversity crises. Yet, the forests themselves, and the sector that manages them, face a range of interrelated threats and opportunities. Many of these are well understood, even if the solutions remain elusive. However, there are also emerging trends that are currently less widely appreciated. We report here the results of a horizon scan to identify developing issues likely to affect UK forest management within the next 50 years. These are issues that are presently under-recognized but have potential for significant impact across the sector and beyond. As the forest management sector naturally operates over long timescales, the importance of using good foresight is self-evident. We followed a tried-and-tested horizon scanning methodology involving a diverse Expert Panel to collate and prioritize a longlist of 180 issues. The top 15 issues identified are presented in the Graphical Abstract. The issues represent a diverse range of themes, within a spectrum of influences from environmental shocks and perturbations to changing political and socio-economic drivers, with complex emerging interactions between them. The most highly ranked issue was ‘Catastrophic forest ecosystem collapse’, reflecting agreement that not only is such collapse a likely prospect but it would also have huge implications across the sector and wider society. These and many of the other issues are large scale, with far-reaching implications. We must be careful to avoid inaction through being overwhelmed, or indeed to merely focus on ‘easy wins’ without considering broader ramifications. Our responses to each of the challenges and opportunities highlighted must be synergistic and coherent, involving landscape-scale planning. A more adaptive approach to forest management will be essential, encouraging continual innovation and learning. The 15 horizon scan issues presented here are a starting point on which to build further research, prompt debate and action, and develop evidence-based policy and practice. We hope that this stimulates greater recognition of how our forests and sector may need to change to be fit for the future. In some cases, these changes will need to be fundamental and momentous

Tobacco use induces anti-apoptotic, proliferative patterns of gene expression in circulating leukocytes of Caucasian males

Abstract Background Strong epidemiologic evidence correlates tobacco use with a variety of serious adverse health effects, but the biological mechanisms that produce these effects remain elusive. Results We analyzed gene transcription data to identify expression spectra related to tobacco use in circulating leukocytes of 67 Caucasian male subjects. Levels of cotinine, a nicotine metabolite, were used as a surrogate marker for tobacco exposure. Significance Analysis of Microarray and Gene Set Analysis identified 109 genes in 16 gene sets whose transcription levels were differentially regulated by nicotine exposure. We subsequently analyzed this gene set by hyperclustering, a technique that allows the data to be clustered by both expression ratio and gene annotation (e.g. Gene Ontologies). Conclusion Our results demonstrate that tobacco use affects transcription of groups of genes that are involved in proliferation and apoptosis in circulating leukocytes. These transcriptional effects include a repertoire of transcriptional changes likely to increase the incidence of neoplasia through an altered expression of genes associated with transcription and signaling, interferon responses and repression of apoptotic pathways