19,203 research outputs found

    Cell-free DNA and outcome in sepsis.

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    Severe sepsis can be a catastrophic condition that is often associated with poor outcomes. The early diagnosis and management of the condition are vital in order to improve the chances of survival. However, owing to the syndromal nature of its definition and the lack of a biomarker able to accurately confirm the condition, the diagnosis of sepsis is challenging. Even more challenging is the prediction of how these patients will respond to the therapy and whether they will survive the intensive care and the hospital admission

    Identifiability of Large Phylogenetic Mixture Models

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    Phylogenetic mixture models are statistical models of character evolution allowing for heterogeneity. Each of the classes in some unknown partition of the characters may evolve by different processes, or even along different trees. The fundamental question of whether parameters of such a model are identifiable is difficult to address, due to the complexity of the parameterization. We analyze mixture models on large trees, with many mixture components, showing that both numerical and tree parameters are indeed identifiable in these models when all trees are the same. We also explore the extent to which our algebraic techniques can be employed to extend the result to mixtures on different trees.Comment: 15 page

    What role does the right side of the heart play in circulation?

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    Right ventricular failure (RVF) is an underestimated problem in intensive care. This review explores the physiology and pathophysiology of right ventricular function and the pulmonary circulation. When RVF is secondary to an acute increase in afterload, the picture is one of acute cor pulmonale, as occurs in the context of acute respiratory distress syndrome, pulmonary embolism and sepsis. RVF can also be caused by right myocardial dysfunction. Pulmonary arterial catheterization and echocardiography are discussed in terms of their roles in diagnosis and treatment. Treatments include options to reduce right ventricular afterload, specific pulmonary vasodilators and inotropes

    The identifiability of tree topology for phylogenetic models, including covarion and mixture models

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    For a model of molecular evolution to be useful for phylogenetic inference, the topology of evolutionary trees must be identifiable. That is, from a joint distribution the model predicts, it must be possible to recover the tree parameter. We establish tree identifiability for a number of phylogenetic models, including a covarion model and a variety of mixture models with a limited number of classes. The proof is based on the introduction of a more general model, allowing more states at internal nodes of the tree than at leaves, and the study of the algebraic variety formed by the joint distributions to which it gives rise. Tree identifiability is first established for this general model through the use of certain phylogenetic invariants.Comment: 20 pages, 1 figur

    Identifying evolutionary trees and substitution parameters for the general Markov model with invariable sites

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    The general Markov plus invariable sites (GM+I) model of biological sequence evolution is a two-class model in which an unknown proportion of sites are not allowed to change, while the remainder undergo substitutions according to a Markov process on a tree. For statistical use it is important to know if the model is identifiable; can both the tree topology and the numerical parameters be determined from a joint distribution describing sequences only at the leaves of the tree? We establish that for generic parameters both the tree and all numerical parameter values can be recovered, up to clearly understood issues of `label swapping.' The method of analysis is algebraic, using phylogenetic invariants to study the variety defined by the model. Simple rational formulas, expressed in terms of determinantal ratios, are found for recovering numerical parameters describing the invariable sites

    Innovation in the energy sector: advancing or frustrating climate policy goals?

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    The energy sector is well known for the relatively modest level of resource that it devotes to research and development (R&D). However, the incremental pace of energy innovation has speeded up in the last decade as measured by public sector R&D budgets, deployment of alternative technologies and novel institutional arrangements. While much of this effort has been targeted at technologies that promise to reduce carbon dioxide (CO2) emissions, there have also been major innovations that extend the fossil fuel resource base and reduce the cost of extraction. The last decade’s developments can be seen in terms of a challenge to the existing energy paradigm in parallel with a renewed innovative response focusing on conventional fuels and technologies. This paper examines this tension, by exploring the expectations of a variety of organisations in both the public and private sector regarding energy sector developments and by analysing private sector expenditure on energy research and development (R&D) and public sector budgets for energy R&D and demonstration (RD&D). Scenarios and outlook exercises that have been published since 2013 reveal a wide range of beliefs about the future development of the energy system. The contrasting views underpinning the different scenarios are reflected in divergent patterns of R&D investment between the private and public sectors. There appears to be a tension between the drive to transform energy systems, on the part of public bodies, mainly motivated by the need to combat global climate change, and private sector activity, which tends to reinforce and extend existing patterns of energy provision. The paper addresses, but not answer definitively, the key question as to whether technological change is enabling or frustrating ambitious carbon goals
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