800 resultados para utility preserving


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Rationale: Nonadherence to inhaled corticosteroid therapy (ICS) is a major contributor to poor control in difficult asthma, yet it is challenging to ascertain. Objectives: Identify a test for nonadherence using fractional exhaled nitric oxide (FENO) suppression after directly observed inhaled corticosteroid (DOICS) treatment. Methods: Difficult asthma patients with an elevated FENO (>45 ppb) were recruited as adherent (ICS prescription filling >80%) or nonadherent (filling <50%). They received 7 days of DOICS (budesonide 1,600 µg) and a test for nonadherence based on changes in FENO was developed. Using this test, clinic patients were prospectively classified as adherent or nonadherent and this was then validated against prescription filling records, prednisolone assay, and concordance interview. Measurements and Main Results: After 7 days of DOICS nonadherent (n = 9) compared with adherent subjects (n = 13) had a greater reduction in FENO to 47 ± 21% versus 79 ± 26% of baseline measurement (P = 0.003), which was also evident after 5 days (P = 0.02) and a FENO test for nonadherence (area under the curve = 0.86; 95% confidence interval, 0.68-1.00) was defined. Prospective validation in 40 subjects found the test identified 13 as nonadherent; eight confirmed nonadherence during interview (three of whom had excellent prescription filling but did not take medication), five denied nonadherence, two had poor inhaler technique (unintentional nonadherence), and one also denied nonadherence to prednisolone despite nonadherent blood level. Twenty-seven participants were adherent on testing, which was confirmed in 21. Five admitted poor ICS adherence but of these, four were adherent with oral steroids and one with omalizumab. Conclusions: FENO suppression after DOICS provides an objective test to distinguish adherent from nonadherent patients with difficult asthma. Clinical trial registered with www.clinicaltrials.gov (NCT 01219036). Copyright © 2012 by the American Thoracic Society.

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Aims: The objectives of this study were to produce Salmonella-specific peptide ligands by phage display biopanning and evaluate their use for magnetic separation (MS).
Methods and Results: Four phage display biopanning rounds were performed and the peptides expressed by the two most Salmonella-specific (on the basis of phage binding ELISA results) phage clones, MSal020401 and MSal020417, were chemically synthesized and coupled to MyOne™ tosylactivated Dynabeads®. Peptide capture capability for whole Salmonella cells from non-enriched broth cultures was quantified by MS + plate counts and MS + Greenlight™ detection, and compared to capture capability of anti-Salmonella (antibody-coated) Dynabeads®. MS + Greenlight™ gave a more comprehensive picture of capture capability than MS + plate counts and showed that Peptide MSal020417-coated beads exhibited at least similar, if not better, capture capability to anti-Salmonella Dynabeads® (mean capture values of 36.0 ± 18.2 % and 31.2 ± 20.1 %, respectively, over Salmonella spp. concentration range 3 x 101 - 3 x 106 cfu ml-1) with minimal cross-reactivity (= 1.9 %) to three other foodborne bacteria.
Conclusions: One of the phage display-derived peptide ligands was demonstrated by MS + Greenlight™ to be a viable antibody-alternative for MS of Salmonella spp.
Significance and Impact of Study: This study demonstrates an antibody-free approach to Salmonella detection and opens substantial possibilities for more rapid tests for this bacterium.

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In this paper, we characterize surjective completely bounded disjointness preserving linear operators on Fourier algebras of locally compact amenable groups. We show that such operators are given by weighted homomorphisms induced by piecewise affine proper maps. © 2011 Elsevier Inc.

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Let T be a compact disjointness preserving linear operator from C0(X) into C0(Y), where X and Y are locally compact Hausdorff spaces. We show that T can be represented as a norm convergent countable sum of disjoint rank one operators. More precisely, T = Snd ?hn for a (possibly finite) sequence {xn }n of distinct points in X and a norm null sequence {hn }n of mutually disjoint functions in C0(Y). Moreover, we develop a graph theoretic method to describe the spectrum of such an operator

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Determination of HER2 protein expression by immunohistochemistry (IHC) and genomic status by fluorescent in situ hybridisation (FISH) are important in identifying a subset of high HER2-expressing gastric cancers that might respond to trastuzumab. Although FISH is considered the standard for determination of HER2 genomic status, brightfield ISH is being increasingly recognised as a viable alternative. Also, the impact of HER2 protein expression/genomic heterogeneity on the accuracy of HER2 testing has not been well studied in the context of gastric biopsy samples.

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Healing algorithms play a crucial part in distributed peer-to-peer networks where failures occur continuously and frequently. Whereas there are approaches for robustness that rely largely on built-in redundancy, we adopt a responsive approach that is more akin to that of biological networks e.g. the brain. The general goal of self-healing distributed graphs is to maintain certain network properties while recovering from failure quickly and making bounded alterations locally. Several self-healing algorithms have been suggested in the recent literature [IPDPS'08, PODC'08, PODC'09, PODC'11]; they heal various network properties while fulfilling competing requirements such as having low degree increase while maintaining connectivity, expansion and low stretch of the network. In this work, we augment the previous algorithms by adding the notion of edge-preserving self-healing which requires the healing algorithm to not delete any edges originally present or adversarialy inserted. This reflects the cost of adding additional edges but more importantly it immediately follows that edge preservation helps maintain any subgraph induced property that is monotonic, in particular important properties such as graph and subgraph densities. Density is an important network property and in certain distributed networks, maintaining it preserves high connectivity among certain subgraphs and backbones. We introduce a general model of self-healing, and introduce xheal+, an edge-preserving version of xheal[PODC'11]. © 2012 IEEE.

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This paper proposes a discrete mixture model which assigns individuals, up to a probability, to either a class of random utility (RU) maximizers or a class of random regret (RR) minimizers, on the basis of their sequence of observed choices. Our proposed model advances the state of the art of RU-RR mixture models by (i) adding and simultaneously estimating a membership model which predicts the probability of belonging to a RU or RR class; (ii) adding a layer of random taste heterogeneity within each behavioural class; and (iii) deriving a welfare measure associated with the RU-RR mixture model and consistent with referendum-voting, which is the adequate mechanism of provision for such local public goods. The context of our empirical application is a stated choice experiment concerning traffic calming schemes. We find that the random parameter RU-RR mixture model not only outperforms its fixed coefficient counterpart in terms of fit-as expected-but also in terms of plausibility of membership determinants of behavioural class. In line with psychological theories of regret, we find that, compared to respondents who are familiar with the choice context (i.e. the traffic calming scheme), unfamiliar respondents are more likely to be regret minimizers than utility maximizers. © 2014 Elsevier Ltd.