147 research outputs found

    Improving quality indicator report cards through Bayesian modeling

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    <p>Abstract</p> <p>Background</p> <p>The National Database for Nursing Quality Indicators<sup>® </sup>(NDNQI<sup>®</sup>) was established in 1998 to assist hospitals in monitoring indicators of nursing quality (eg, falls and pressure ulcers). Hospitals participating in NDNQI transmit data from nursing units to an NDNQI data repository. Data are summarized and published in reports that allow participating facilities to compare the results for their units with those from other units across the nation. A disadvantage of this reporting scheme is that the sampling variability is not explicit. For example, suppose a small nursing unit that has 2 out of 10 (rate of 20%) patients with pressure ulcers. Should the nursing unit immediately undertake a quality improvement plan because of the rate difference from the national average (7%)?</p> <p>Methods</p> <p>In this paper, we propose approximating 95% credible intervals (CrIs) for unit-level data using statistical models that account for the variability in unit rates for report cards.</p> <p>Results</p> <p>Bayesian CrIs communicate the level of uncertainty of estimates more clearly to decision makers than other significance tests.</p> <p>Conclusion</p> <p>A benefit of this approach is that nursing units would be better able to distinguish problematic or beneficial trends from fluctuations likely due to chance.</p

    Model-based learning from preference data

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    International audiencePreference data occurs when assessors express comparative opinions about a set of items, by rating, ranking, pair comparing, liking or clicking. The purpose of preference learning is to (i) infer on the shared consensus preference of a group of users, sometimes called rank aggregation; or (ii) estimate for each user her individual ranking of the items, when the user indicates only incomplete preferences; this is an important part of recom-mender systems. We provide an overview of probabilistic approaches to preference learning, including the Mallows, Plackett-Luce, Bradley-Terry models and collaborative filtering, and some of their variations. We illustrate , compare and discuss the use of these models by means of an experiment in which assessors rank potatoes, and with a simulation. The purpose of this paper is not to recommend the use of one best method, but to present a palette of different possibilities for different questions and different types of data

    Diversification and Specialization of Plant RBR Ubiquitin Ligases

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    Background: RBR ubiquitin ligases are components of the ubiquitin-proteasome system present in all eukaryotes. They are characterized by having the RBR (RING – IBR – RING) supradomain. In this study, the patterns of emergence of RBR genes in plants are described. Methodology/Principal Findings: Phylogenetic and structural data confirm that just four RBR subfamilies (Ariadne, ARA54, Plant I/Helicase and Plant II) exist in viridiplantae. All of them originated before the split that separated green algae from the rest of plants. Multiple genes of two of these subfamilies (Ariadne and Plant II) appeared in early plant evolution. It is deduced that the common ancestor of all plants contained at least five RBR genes and the available data suggest that this number has been increasing slowly along streptophyta evolution, although losses, especially of Helicase RBR genes, have also occurred in several lineages. Some higher plants (e. g. Arabidopsis thaliana, Oryza sativa) contain a very large number of RBR genes and many of them were recently generated by tandem duplications. Microarray data indicate that most of these new genes have low-level and sometimes specific expression patterns. On the contrary, and as occurs in animals, a small set of older genes are broadly expressed at higher levels. Conclusions/Significance: The available data suggests that the dynamics of appearance and conservation of RBR genes is quite different in plants from what has been described in animals. In animals, an abrupt emergence of many structurall

    Comparative Genomics of Cell Envelope Components in Mycobacteria

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    Mycobacterial cell envelope components have been a major focus of research due to their unique features that confer intrinsic resistance to antibiotics and chemicals apart from serving as a low-permeability barrier. The complex lipids secreted by Mycobacteria are known to evoke/repress host-immune response and thus contribute to its pathogenicity. This study focuses on the comparative genomics of the biosynthetic machinery of cell wall components across 21-mycobacterial genomes available in GenBank release 179.0. An insight into survival in varied environments could be attributed to its variation in the biosynthetic machinery. Gene-specific motifs like ‘DLLAQPTPAW’ of ufaA1 gene, novel functional linkages such as involvement of Rv0227c in mycolate biosynthesis; Rv2613c in LAM biosynthesis and Rv1209 in arabinogalactan peptidoglycan biosynthesis were detected in this study. These predictions correlate well with the available mutant and coexpression data from TBDB. It also helped to arrive at a minimal functional gene set for these biosynthetic pathways that complements findings using TraSH

    Diversity in the Architecture of ATLs, a Family of Plant Ubiquitin-Ligases, Leads to Recognition and Targeting of Substrates in Different Cellular Environments

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    Ubiquitin-ligases or E3s are components of the ubiquitin proteasome system (UPS) that coordinate the transfer of ubiquitin to the target protein. A major class of ubiquitin-ligases consists of RING-finger domain proteins that include the substrate recognition sequences in the same polypeptide; these are known as single-subunit RING finger E3s. We are studying a particular family of RING finger E3s, named ATL, that contain a transmembrane domain and the RING-H2 finger domain; none of the member of the family contains any other previously described domain. Although the study of a few members in A. thaliana and O. sativa has been reported, the role of this family in the life cycle of a plant is still vague. To provide tools to advance on the functional analysis of this family we have undertaken a phylogenetic analysis of ATLs in twenty-four plant genomes. ATLs were found in all the 24 plant species analyzed, in numbers ranging from 20–28 in two basal species to 162 in soybean. Analysis of ATLs arrayed in tandem indicates that sets of genes are expanding in a species-specific manner. To get insights into the domain architecture of ATLs we generated 75 pHMM LOGOs from 1815 ATLs, and unraveled potential protein-protein interaction regions by means of yeast two-hybrid assays. Several ATLs were found to interact with DSK2a/ubiquilin through a region at the amino-terminal end, suggesting that this is a widespread interaction that may assist in the mode of action of ATLs; the region was traced to a distinct sequence LOGO. Our analysis provides significant observations on the evolution and expansion of the ATL family in addition to information on the domain structure of this class of ubiquitin-ligases that may be involved in plant adaptation to environmental stress

    The equilibria that allow bacterial persistence in human hosts

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    We propose that microbes that have developed persistent relationships with human hosts have evolved cross-signalling mechanisms that permit homeostasis that conforms to Nash equilibria and, more specifically, to evolutionarily stable strategies. This implies that a group of highly diverse organisms has evolved within the changing contexts of variation in effective human population size and lifespan, shaping the equilibria achieved, and creating relationships resembling climax communities. We propose that such ecosystems contain nested communities in which equilibrium at one level contributes to homeostasis at another. The model can aid prediction of equilibrium states in the context of further change: widespread immunodeficiency, changing population densities, or extinctions.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62883/1/nature06198.pd

    Incorporating concepts of inequality and inequity into health benefits analysis

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    BACKGROUND: Although environmental policy decisions are often based in part on both risk assessment information and environmental justice concerns, formalized approaches for addressing inequality or inequity when estimating the health benefits of pollution control have been lacking. Inequality indicators that fulfill basic axioms and agree with relevant definitions and concepts in health benefits analysis and environmental justice analysis can allow for quantitative examination of efficiency-equality tradeoffs in pollution control policies. METHODS: To develop appropriate inequality indicators for health benefits analysis, we provide relevant definitions from the fields of risk assessment and environmental justice and consider the implications. We evaluate axioms proposed in past studies of inequality indicators and develop additional axioms relevant to this context. We survey the literature on previous applications of inequality indicators and evaluate five candidate indicators in reference to our proposed axioms. We present an illustrative pollution control example to determine whether our selected indicators provide interpretable information. RESULTS AND CONCLUSIONS: We conclude that an inequality indicator for health benefits analysis should not decrease when risk is transferred from a low-risk to high-risk person, and that it should decrease when risk is transferred from a high-risk to low-risk person (Pigou-Dalton transfer principle), and that it should be able to have total inequality divided into its constituent parts (subgroup decomposability). We additionally propose that an ideal indicator should avoid value judgments about the relative importance of transfers at different percentiles of the risk distribution, incorporate health risk with evidence about differential susceptibility, include baseline distributions of risk, use appropriate geographic resolution and scope, and consider multiple competing policy alternatives. Given these criteria, we select the Atkinson index as the single indicator most appropriate for health benefits analysis, with other indicators useful for sensitivity analysis. Our illustrative pollution control example demonstrates how these indices can help a policy maker determine control strategies that are dominated from an efficiency and equality standpoint, those that are dominated for some but not all societal viewpoints on inequality averseness, and those that are on the optimal efficiency-equality frontier, allowing for more informed pollution control policies
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