75 research outputs found

    Effectiveness of Biodiversity Surrogates for Conservation Planning: Different Measures of Effectiveness Generate a Kaleidoscope of Variation

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    Conservation planners represent many aspects of biodiversity by using surrogates with spatial distributions readily observed or quantified, but tests of their effectiveness have produced varied and conflicting results. We identified four factors likely to have a strong influence on the apparent effectiveness of surrogates: (1) the choice of surrogate; (2) differences among study regions, which might be large and unquantified (3) the test method, that is, how effectiveness is quantified, and (4) the test features that the surrogates are intended to represent. Analysis of an unusually rich dataset enabled us, for the first time, to disentangle these factors and to compare their individual and interacting influences. Using two data-rich regions, we estimated effectiveness using five alternative methods: two forms of incidental representation, two forms of species accumulation index and irreplaceability correlation, to assess the performance of ‘forest ecosystems’ and ‘environmental units’ as surrogates for six groups of threatened species—the test features—mammals, birds, reptiles, frogs, plants and all of these combined. Four methods tested the effectiveness of the surrogates by selecting areas for conservation of the surrogates then estimating how effective those areas were at representing test features. One method measured the spatial match between conservation priorities for surrogates and test features. For methods that selected conservation areas, we measured effectiveness using two analytical approaches: (1) when representation targets for the surrogates were achieved (incidental representation), or (2) progressively as areas were selected (species accumulation index). We estimated the spatial correlation of conservation priorities using an index known as summed irreplaceability. In general, the effectiveness of surrogates for our taxa (mostly threatened species) was low, although environmental units tended to be more effective than forest ecosystems. The surrogates were most effective for plants and mammals and least effective for frogs and reptiles. The five testing methods differed in their rankings of effectiveness of the two surrogates in relation to different groups of test features. There were differences between study areas in terms of the effectiveness of surrogates for different test feature groups. Overall, the effectiveness of the surrogates was sensitive to all four factors. This indicates the need for caution in generalizing surrogacy tests

    Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

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    The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

    Comparative genomics of Cluster O mycobacteriophages

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    Mycobacteriophages - viruses of mycobacterial hosts - are genetically diverse but morphologically are all classified in the Caudovirales with double-stranded DNA and tails. We describe here a group of five closely related mycobacteriophages - Corndog, Catdawg, Dylan, Firecracker, and YungJamal - designated as Cluster O with long flexible tails but with unusual prolate capsids. Proteomic analysis of phage Corndog particles, Catdawg particles, and Corndog-infected cells confirms expression of half of the predicted gene products and indicates a non-canonical mechanism for translation of the Corndog tape measure protein. Bioinformatic analysis identifies 8-9 strongly predicted SigA promoters and all five Cluster O genomes contain more than 30 copies of a 17 bp repeat sequence with dyad symmetry located throughout the genomes. Comparison of the Cluster O phages provides insights into phage genome evolution including the processes of gene flux by horizontal genetic exchange

    Partner randomized controlled trial: study protocol and coaching intervention

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    <p>Abstract</p> <p>Background</p> <p>Many children with asthma live with frequent symptoms and activity limitations, and visits for urgent care are common. Many pediatricians do not regularly meet with families to monitor asthma control, identify concerns or problems with management, or provide self-management education. Effective interventions to improve asthma care such as small group training and care redesign have been difficult to disseminate into office practice.</p> <p>Methods and design</p> <p>This paper describes the protocol for a randomized controlled trial (RCT) to evaluate a 12-month telephone-coaching program designed to support primary care management of children with persistent asthma and subsequently to improve asthma control and disease-related quality of life and reduce urgent care events for asthma care. Randomization occurred at the practice level with eligible families within a practice having access to the coaching program or to usual care. The coaching intervention was based on the transtheoretical model of behavior change. Targeted behaviors included 1) effective use of controller medications, 2) effective use of rescue medications and 3) monitoring to ensure optimal control. Trained lay coaches provided parents with education and support for asthma care, tailoring the information provided and frequency of contact to the parent's readiness to change their child's day-to-day asthma management. Coaching calls varied in frequency from weekly to monthly. For each participating family, follow-up measurements were obtained at 12- and 24-months after enrollment in the study during a telephone interview.</p> <p>The primary outcomes were the mean change in 1) the child's asthma control score, 2) the parent's quality of life score, and 3) the number of urgent care events assessed at 12 and 24 months. Secondary outcomes reflected adherence to guideline recommendations by the primary care pediatricians and included the proportion of children prescribed controller medications, having maintenance care visits at least twice a year, and an asthma action plan. Cost-effectiveness of the intervention was also measured.</p> <p>Discussion</p> <p>Twenty-two practices (66 physicians) were randomized (11 per treatment group), and 950 families with a child 3-12 years old with persistent asthma were enrolled. A description of the coaching intervention is presented.</p> <p>Trial registration</p> <p>ClinicalTrials.gov identifier <a href="http://www.clinicaltrials.gov/ct2/show/NCT00860834">NCT00860834</a>.</p

    Loss of a Conserved tRNA Anticodon Modification Perturbs Plant Immunity

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    [EN] tRNA is the most highly modified class of RNA species, and modifications are found in tRNAs from all organisms that have been examined. Despite their vastly different chemical structures and their presence in different tRNAs, occurring in different locations in tRNA, the biosynthetic pathways of the majority of tRNA modifications include a methylation step(s). Recent discoveries have revealed unprecedented complexity in the modification patterns of tRNA, their regulation and function, suggesting that each modified nucleoside in tRNA may have its own specific function. However, in plants, our knowledge on the role of individual tRNA modifications and how they are regulated is very limited. In a genetic screen designed to identify factors regulating disease resistance and activation of defenses in Arabidopsis, we identified SUPPRESSOR OF CSB3 9 (SCS9). Our results reveal SCS9 encodes a tRNA methyltransferase that mediates the 2'-O-ribose methylation of selected tRNA species in the anticodon loop. These SCS9-mediated tRNA modifications enhance during the course of infection with the bacterial pathogen Pseudomonas syringae DC3000, and lack of such tRNA modification, as observed in scs9 mutants, severely compromise plant immunity against the same pathogen without affecting the salicylic acid (SA) signaling pathway which regulates plant immune responses. Our results support a model that gives importance to the control of certain tRNA modifications for mounting an effective immune response in Arabidopsis, and therefore expands the repertoire of molecular components essential for an efficient disease resistance response.This work was supported by the National Science Foundation of China (grant 31100268 to PC) and the Spanish MINECO (BFU2012 to PV) and Generalitat Valenciana (Prometeo2014/020 to PV). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ramirez Garcia, V.; González-García, B.; López Sánchez, A.; Castelló Llopis, MJ.; Gil, M.; Zheng, B.; Cheng, P.... (2015). Loss of a Conserved tRNA Anticodon Modification Perturbs Plant Immunity. PLoS Genetics. 11(10):1-27. https://doi.org/10.1371/journal.pgen.1005586S127111
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