Referral to an Extracorporeal Membrane Oxygenation Center and Mortality Among Patients With Severe 2009 Influenza A(H1N1)

Context Extracorporeal membrane oxygenation (ECMO) can support gas exchange in patients with severe acute respiratory distress syndrome (ARDS), but its role has remained controversial. ECMO was used to treat patients with ARDS during the 2009 influenza A(H1N1) pandemic.

How many dimensions of biodiversity do we need?

Biodiversity is not a commodity, nor a service (ecosystem or otherwise), it is a scientific measure of the complexity of a biological system. Rather than directly valuing biodiversity, economists have tended to value its services, more often the services of 'key' species. This is understandable given the confusion of definitions and measures of biodiversity, but weakly justified if biodiversity is not substitutable. We provide a quantitative and comprehensive definition of biodiversity and propose a framework for examining its substitutability as the first step towards valuation. We define biodiversity as a measure of semiotic information. It is equated with biocomplexity and measured by Algorithmic Information Content (AIC). We argue that the potentially valuable component of this is functional information content (FIC) which determines biological fitness and supports ecosystem services. Inspired by recent extensions to the Noah's Ark problem, we show how FIC/AIC can be calculated to measure the degree of substitutability within an ecological community. From this, we derive a way to rank whole communities by Indirect Use Value, through quantifying the relation between system complexity and production rate of ecosystem services. Understanding biodiversity as information evidently serves as a practical interface between economics and ecological science.

Functional Complexity: The source of value in biodiversity.

Biodiversity may be seen as a scientific measure of the complexity of a biological system, implying an information basis. Complexity cannot be directly valued, so economists have tried to define the services it provides, though often just valuing the services of 'key' species. Here we provide a new definition of biodiversity as a measure of functional information, arguing that complexity embodies meaningful information as Gregory Bateson defined it. We argue that functional information content (FIC) is the potentially valuable component of total (algorithmic) information content (AIC), as it alone determines biological fitness and supports ecosystem services. Inspired by recent extensions to the Noah's Ark problem, we show how FIC/AIC can be calculated to measure the degree of substitutability within an ecological community. Establishing substitutability is an essential foundation for valuation. From it, we derive a way to rank whole communities by Indirect Use Value, through quantifying the relation between system complexity and the production rate of ecosystem services. Understanding biodiversity as information evidently serves as a practical interface between economics and ecological science. © 2012 Elsevier B.V.

Measurements of immune responses for establishing correlates of vaccine protection against HIV

Well-defined correlates of protective immunity are an essential component of rational vaccine development. Despite years of basic science and three HIV vaccine efficacy trials, correlates of immunological protection from HIV infection remain undefined. In December 2010, a meeting of scientists engaged in basic and translational work toward developing HIV-1 vaccines was convened. The goal of this meeting was to discuss current opportunities and optimal approaches for defining correlates of protection, both for ongoing and future HIV-1 vaccine candidates; specific efforts were made to engage young scientists. We discuss here the highlights from the meeting regarding the progress made and the way forward for a protective HIV-1 vaccine.

Independent genomewide screens identify the tumor suppressor VTRNA2-1 as a human epiallele responsive to periconceptional environment

Background: Interindividual epigenetic variation that occurs systemically must be established prior to gastrulation in the very early embryo and, because it is systemic, can be assessed in easily biopsiable tissues. We employ two independent genome-wide approaches to search for such variants.

Results: First, we screen for metastable epialleles by performing genomewide bisulfite sequencing in peripheral blood lymphocyte (PBL) and hair follicle DNA from two Caucasian adults. Second, we conduct a genomewide screen for genomic regions at which PBL DNA methylation is affected by season of conception in rural Gambia. Remarkably, both approaches identify the genomically imprinted VTRNA2-1 as a top environmentally responsive epiallele. We demonstrate systemic and stochastic interindividual variation in DNA methylation at the VTRNA2-1 differentially methylated region in healthy Caucasian and Asian adults and show, in rural Gambians, that periconceptional environment affects offspring VTRNA2-1 epigenotype, which is stable over at least 10 years. This unbiased screen also identifies over 100 additional candidate metastable epialleles, and shows that these are associated with cis genomic features including transposable elements.

Conclusions: The non-coding VTRNA2-1 transcript (also called nc886) is a putative tumor suppressor and modulator of innate immunity. Thus, these data indicating environmentally induced loss of imprinting at VTRNA2-1 constitute a plausible causal pathway linking early embryonic environment, epigenetic alteration, and human disease. More broadly, the list of candidate metastable epialleles provides a resource for future studies of epigenetic variation and human disease.

Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores

Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R(2) increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase.