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Patients lacking classical poor prognostic markers might also benefit from a step-down glucocorticoid bridging scheme in early rheumatoid arthritis: week 16 results from the randomized multicenter CareRA trial
No full textINTRODUCTION: Considering a lack of efficacy data in patients with early rheumatoid arthritis (eRA) presenting without classical markers of poor prognosis, we compared methotrexate (MTX) with or without step-down glucocorticoids in the CareRA trial. METHODS: Disease-modifying antirheumatic drug-naive patients with eRA were stratified into a low-risk group based on prognostic markers that included non-erosiveness, anti-citrullinated protein antibodies and rheumatoid factor negativity and low disease activity (Disease Activity Score in 28 joints based on C-reactive protein (DAS28(CRP)
Summary of the ATLAS experiment???s sensitivity to supersymmetry after LHC Run 1 ??? interpreted in the phenomenological MSSM
No full textTools for assessing outcomes in studies of chronic cough: CHEST guideline and expert panel report.
No full textBACKGROUND: Since the publication of the 2006 American College of Chest Physicians (CHEST) cough guidelines, a variety of tools has been developed or further refined for assessing cough. The purpose of the present committee was to evaluate instruments used by investigators performing clinical research on chronic cough. The specific aims were to (1) assess the performance of tools designed to measure cough frequency, severity, and impact in adults, adolescents, and children with chronic cough and (2) make recommendations or suggestions related to these findings. METHODS: By following the CHEST methodologic guidelines, the CHEST Expert Cough Panel based its recommendations and suggestions on a recently published comparative effectiveness review commissioned by the US Agency for Healthcare Research and Quality, a corresponding summary published in CHEST, and an updated systematic review through November 2013. Recommendations or suggestions based on these data were discussed, graded, and voted on during a meeting of the Expert Cough Panel. RESULTS: We recommend for adults, adolescents (≥ 14 years of age), and children complaining of chronic cough that validated and reliable health-related quality-of-life (QoL) questionnaires be used as the measurement of choice to assess the impact of cough, such as the Leicester Cough Questionnaire and the Cough-Specific Quality-of-Life Questionnaire in adult and adolescent patients and the Parent Cough-Specific Quality of Life Questionnaire in children. We recommend acoustic cough counting to assess cough frequency but not cough severity. Limited data exist regarding the performance of visual analog scales, numeric rating scales, and tussigenic challenges. CONCLUSIONS: Validated and reliable cough-specific health-related QoL questionnaires are recommended as the measurement of choice to assess the impact of cough on patients. How they compare is yet to be determined. When used, the reporting of cough severity by visual analog or numeric rating scales should be standardized. Previously validated QoL questionnaires or other cough assessments should not be modified unless the new version has been shown to be reliable and valid. Finally, in research settings, tussigenic challenges play a role in understanding mechanisms of cough
Selective gas adsorption in microporous metal-organic frameworks incorporating urotropine basic sites: An experimental and theoretical study
No full textThe feasibility phase of a community antenatal lifestyle programme (the lifestyle course [tlc]) for women with a body mass index (bmi)≥30kg/m2.
No full textPlanck intermediate results. XX. Comparison of polarized thermal emission from Galactic dust with simulations of MHD turbulence
No full textPolarized emission observed by Planck HFI at 353 GHz towards a sample of nearby fields is presented, focusing on the statistics of polarization fractions p and angles œà. The polarization fractions and column densities in these nearby fields are representative of the range of values obtained over the whole sky. We find that: (i) the largest polarization fractions are reached in the most diffuse fields; (ii) the maximum polarization fraction pmax decreases with column density NH in the more opaque fields with NH> 1021 cm-2; and (iii) the polarization fraction along a given line of sight is correlated with the local spatial coherence of the polarization angle. These observations are compared to polarized emission maps computed in simulations of anisotropic magnetohydrodynamical turbulence in which we assume a uniform intrinsic polarization fraction of the dust grains. We find that an estimate of this parameter may be recovered from the maximum polarization fraction pmax in diffuse regions where the magnetic field is ordered on large scales and perpendicular to the line of sight. This emphasizes the impact of anisotropies of the magnetic field on the emerging polarization signal. The decrease of the maximum polarization fraction with column density in nearby molecular clouds is well reproduced in the simulations, indicating that it is essentially due to the turbulent structure of the magnetic field: an accumulation of variously polarized structures along the line of sight leads to such an anti-correlation. In the simulations, polarization fractions are also found to anti-correlate with the angle dispersion function ùíÆ. However, the dispersion of the polarization angle for a given polarization fraction is found to be larger in the simulations than in the observations, suggesting a shortcoming in the physical content of these numerical models. In summary, we find that the turbulent structure of the magnetic field is able to reproduce the main statistical properties of the dust polarization as observed in a variety of nearby clouds, dense cores excluded, and that the large-scale field orientation with respect to the line of sight plays a major role in the quantitative analysis of these statistical properties. Appendices are available in electronic form at http://www.aanda.org</a
The relationship between personality traits and psychotic like experiences in a large non-clinical adolescent sample
No full textHidden behavior prediction of complex systems under testing influence based on semi-quantitative information and belief rule base
No full textCompared with the observable behavior, it is difficult to predict the hidden behavior of a complex system. In the existing methods for predicting the hidden behavior, a lot of testing data (usually quantitative information) are needed to be sampled. However, some complex engineering systems have the following characteristics: 1) The systems cannot be tested periodically, and the observable information is incomplete; 2) the change process of hidden behavior may be affected by the test; and 3) only part of quantitative information and qualitative knowledge (i.e., semiquantitative information) may be obtained. These characteristics all related to the test are named as testing influence for simplicity. Although a model and a corresponding optimal algorithm for training the model parameters have been proposed to predict the hidden behavior on the basis of semiquantitative information and belief rule base (BRB), the testing influence has not been considered. In order to solve the above problems, a new BRB-based model, which can use the semiquantitative information, is proposed under testing influence in this paper. In the newly proposed forecasting model, there are some parameters of which the initial values are usually assigned by experts and may not be accurate, which can lead to the inaccurate prediction results. As such, an improved optimal algorithm for training the parameters of the forecasting model is further developed on the basis of the expectation-maximization idea and the covariance matrix adaption evolution strategy (CMA-ES). By using the semiquantitative information, the proposed BRB-based model and the improved CMA-ES algorithm can operate together in an integrated manner so as to improve the forecasting precision. A case study is examined to demonstrate the ability and applicability of the newly proposed BRB-based forecasting model and the improved CMA-ES algorithm
Measurement of the and production cross sections in pp collisions at TeV with the ATLAS detector
No full textAmbiguity and variability of database and software names in bioinformatics
No full textBackground: There are numerous options available to achieve various tasks in bioinformatics, but until recently, there were no tools that could systematically identify mentions of databases and tools within the literature. In this paper we explore the variability and ambiguity of database and software name mentions and compare dictionary and machine learning approaches to their identification. Results: Through the development and analysis of a corpus of 60 full-text documents manually annotated at the mention level, we report high variability and ambiguity in database and software mentions. On a test set of 25 full-text documents, a baseline dictionary look-up achieved an F-score of 46 %, highlighting not only variability and ambiguity but also the extensive number of new resources introduced. A machine learning approach achieved an F-score of 63 % (with precision of 74 %) and 70 % (with precision of 83 %) for strict and lenient matching respectively. We characterise the issues with various mention types and propose potential ways of capturing additional database and software mentions in the literature. Conclusions: Our analyses show that identification of mentions of databases and tools is a challenging task that cannot be achieved by relying on current manually-curated resource repositories. Although machine learning shows improvement and promise (primarily in precision), more contextual information needs to be taken into account to achieve a good degree of accuracy.There are numerous options available to achieve various tasks in bioinformatics, but until recently, there were no tools that could systematically identify mentions of databases and tools within the literature. In this paper we explore the variability and ambiguity of database and software name mentions and compare dictionary and machine learning approaches to their identification