Canakinumab for acute gouty arthritis in patients with limited treatment options: results from two randomised, multicentre, active-controlled, double-blind trials and their initial extensions.

OBJECTIVES: Gouty arthritis patients for whom non-steroidal anti-inflammatory drugs and colchicine are inappropriate have limited treatment options. Canakinumab, an anti-interleukin-1β monoclonal antibody, may be an option for such patients. The authors assessed the efficacy/safety of one dose of canakinumab 150 mg (n=230) or triamcinolone acetonide (TA) 40 mg (n=226) at baseline and upon a new flare in frequently flaring patients contraindicated for, intolerant of, or unresponsive to non-steroidal anti-inflammatory drugs and/or colchicine. Core study co-primary endpoints were pain intensity 72 h postdose (0-100 mm visual analogue scale and time to first new flare. METHODS: Two 12-week randomised, multicentre, active-controlled, double-blind, parallel-group core studies with double-blind 12-week extensions (response in acute flare and in prevention of episodes of re-flare in gout (β-RELIEVED and β-RELIEVED-II)). RESULTS: 82.6% patients had comorbidities. Mean 72-h visual analogue scale pain score was lower with canakinumab (25.0 mm vs 35.7 mm; difference, -10.7 mm; 95% CI -15.4 to -6.0; p<0.0001), with significantly less physician-assessed tenderness and swelling (ORs=2.16 and 2.74; both p≤0.01) versus TA. Canakinumab significantly delayed time to first new flare, reduced the risk of new flares by 62% versus TA (HR: 0.38; 95% CI 0.26 to 0.57) in the core studies and by 56% (HR: 0.44; 95% CI 0.32 to 0.60; both p≤0.0001) over the entire 24-week period, and decreased median C-reactive protein levels (p≤0.0001 at 72 h and 7 days). Over the 24-week period, adverse events were reported in 66.2% (canakinumab) and 52.8% (TA) and serious adverse events were reported in 8.0% (canakinumab) and 3.5% (TA) of patients. Adverse events reported more frequently with canakinumab included infections, low neutrophil count and low platelet count. CONCLUSION: Canakinumab provided significant pain and inflammation relief and reduced the risk of new flares in these patients with acute gouty arthritis.

An Automatic Approach for Learning and Tuning Gaussian Interval Type-2 Fuzzy Membership Functions Applied to Lung CAD Classification System

The potential of type-2 fuzzy sets for managing high levels of uncertainty in the subjective knowledge of experts or of numerical information has focused on control and pattern classification systems in recent years. One of the main challenges in designing a type-2 fuzzy logic system is how to estimate the parameters of type-2 fuzzy membership function (T2MF) and the Footprint of Uncertainty (FOU) from imperfect and noisy datasets. This paper presents an automatic approach for learning and tuning Gaussian interval type-2 membership functions (IT2MFs) with application to multi-dimensional pattern classification problems. T2MFs and their FOUs are tuned according to the uncertainties in the training dataset by a combination of genetic algorithm (GA) and crossvalidation techniques. In our GA-based approach, the structure of the chromosome has fewer genes than other GA methods and chromosome initialization is more precise. The proposed approach addresses the application of the interval type-2 fuzzy logic system (IT2FLS) for the problem of nodule classification in a lung Computer Aided Detection (CAD) system. The designed IT2FLS is compared with its type-1 fuzzy logic system (T1FLS) counterpart. The results demonstrate that the IT2FLS outperforms the T1FLS by more than 30% in terms of classification accuracy.

Identification of different heart tissues from MRI C-SENC images using an unsupervised multi-stage fuzzy clustering technique.

PURPOSE: To objectively characterize different heart tissues from functional and viability images provided by composite-strain-encoding (C-SENC) MRI. MATERIALS AND METHODS: C-SENC is a new MRI technique for simultaneously acquiring cardiac functional and viability images. In this work, an unsupervised multi-stage fuzzy clustering method is proposed to identify different heart tissues in the C-SENC images. The method is based on sequential application of the fuzzy c-means (FCM) and iterative self-organizing data (ISODATA) clustering algorithms. The proposed method is tested on simulated heart images and on images from nine patients with and without myocardial infarction (MI). The resulting clustered images are compared with MRI delayed-enhancement (DE) viability images for determining MI. Also, Bland-Altman analysis is conducted between the two methods. RESULTS: Normal myocardium, infarcted myocardium, and blood are correctly identified using the proposed method. The clustered images correctly identified 90 +/- 4% of the pixels defined as infarct in the DE images. In addition, 89 +/- 5% of the pixels defined as infarct in the clustered images were also defined as infarct in DE images. The Bland-Altman results show no bias between the two methods in identifying MI. CONCLUSION: The proposed technique allows for objectively identifying divergent heart tissues, which would be potentially important for clinical decision-making in patients with MI.

The Gene Ontology in 2010: extensions and refinements.

The Gene Ontology (GO) Consortium (http://www.geneontology.org) (GOC) continues to develop, maintain and use a set of structured, controlled vocabularies for the annotation of genes, gene products and sequences. The GO ontologies are expanding both in content and in structure. Several new relationship types have been introduced and used, along with existing relationships, to create links between and within the GO domains. These improve the representation of biology, facilitate querying, and allow GO developers to systematically check for and correct inconsistencies within the GO. Gene product annotation using GO continues to increase both in the number of total annotations and in species coverage. GO tools, such as OBO-Edit, an ontology-editing tool, and AmiGO, the GOC ontology browser, have seen major improvements in functionality, speed and ease of use.

Fuzzy logic algorithm to extract specific interaction forces from atomic force microscopy data

The atomic force microscope is not only a very convenient tool for studying the topography of different samples, but it can also be used to measure specific binding forces between molecules. For this purpose, one type of molecule is attached to the tip and the other one to the substrate. Approaching the tip to the substrate allows the molecules to bind together. Retracting the tip breaks the newly formed bond. The rupture of a specific bond appears in the force-distance curves as a spike from which the binding force can be deduced. In this article we present an algorithm to automatically process force-distance curves in order to obtain bond strength histograms. The algorithm is based on a fuzzy logic approach that permits an evaluation of "quality" for every event and makes the detection procedure much faster compared to a manual selection. In this article, the software has been applied to measure the binding strength between tubuline and microtubuline associated proteins.

THE USEFUL SIDE OF AMBIVALENCE: Ambivalent attitudes can be adaptive and socially valued

En s'inspirant de la littérature récente qui a dépeint l'ambivalence comme étant adaptative et en lien avec des comportements stratégiques, cette thèse examine le versant utile des attitudes ambivalentes. Elle met tout d'abord en évidence que son expression peut-être sciemment contrôlée et mise en avant pour des raisons d'auto-présentation. De plus, elle démontre que les individus peuvent présenter une attitude ambivalente afin de gagner l'approbation sociale sur un objet d'attitude controversé alors que l'inverse a été observé sur des objets consensuels (Première ligne de recherche). Cette thèse a également révélé que l'expression d'attitudes ambivalentes pouvait amener à être valorisé socialement. En effet, contrairement à des attitudes plus tranchées (pro-normatives ou contre-normatives), les attitudes ambivalentes ont été évaluées de façon plus importante sur la dimension de l'utilité sociale (une dimension qui indique la compétence d'autrui ou encore la propension à évoluer dans la hiérarchie sociale). La valorisation de l'ambivalence n'est apparue que sur la dimension de l'utilité sociale et non sur la dimension de la désirabilité sociale (une dimension qui indique la sympathie d'autrui ainsi que la propension à être apprécié socialement). De plus, ce résultat a été observé sur des thèmes controversés et non sur des thèmes consensuels (Seconde ligne de recherche). Dans l'ensemble cette thèse soutient une approche de l'ambivalence comme donnant lieu à des bénéfices. Elle peut également ouvrir la voie à l'étude de l'ambivalence en lien avec la pensée critique. - Drawing on the recent literature that portrayed ambivalence as being adaptive and linked with strategic behaviors, this thesis examines the useful side of ambivalent attitudes. It first revealed that the expression of ambivalent attitudes could be controlled and purposely displayed for self-presentational concerns. Furthermore, it demonstrated that people could put ambivalence forward to gain social approval when expressing it on controversial social issues, whereas the opposite was true on consensual social issues (First line of research). The thesis also revealed that the expression of ambivalent attitudes could lead to be socially valued. Indeed, contrary to clear-cut attitudes (either pro-normative or counter-normative attitudes), ambivalent attitudes have been evaluated the highest on the social utility dimension (a dimension indicating people's competence as well as the extent to which they are likely to climb in social hierarchy). The valorization of ambivalent attitudes only appeared on social utility and not on social desirability (a dimension indicating people's niceness as well as the extent to which they are likely to be socially appreciated). This effect was true on controversial social issues but not on consensual ones (Second line of research). Overall, this thesis provides support for an approach that conceives attitudinal ambivalence as leading to benefits. It also may open avenues for the study of ambivalence in relation with critical thinking.

Ground-state order and spin-lattice coupling in tetrahedral spin systems Cu2Te2O5X2 (X = Br or Cl)

High-resolution ac susceptibility and thermal conductivity measurement on Cu2Te2O5X2 (X=Br,Cl) single crystals are reported. For Br-sample, sample dependence prevents one from distinguishing between possibilities of magnetically ordered and spin-singlet ground states. In Cl-sample a three-dimensional transition at 18.5 K is accompanied by almost isotropic behavior of susceptibility and almost switching behavior of thermal conductivity. Thermal conductivity studies suggest the presence of a tremendous spin-lattice coupling characterizing Cl- but not Br-sample. Below the transition Cl-sample is in a complex magnetic state involving AF order but also the elements consistent with the presence of a gap in the excitation spectrum.

Change points detection in crime-related time series: an on-line fuzzy approach based on a shape space representation

The extension of traditional data mining methods to time series has been effectively applied to a wide range of domains such as finance, econometrics, biology, security, and medicine. Many existing mining methods deal with the task of change points detection, but very few provide a flexible approach. Querying specific change points with linguistic variables is particularly useful in crime analysis, where intuitive, understandable, and appropriate detection of changes can significantly improve the allocation of resources for timely and concise operations. In this paper, we propose an on-line method for detecting and querying change points in crime-related time series with the use of a meaningful representation and a fuzzy inference system. Change points detection is based on a shape space representation, and linguistic terms describing geometric properties of the change points are used to express queries, offering the advantage of intuitiveness and flexibility. An empirical evaluation is first conducted on a crime data set to confirm the validity of the proposed method and then on a financial data set to test its general applicability. A comparison to a similar change-point detection algorithm and a sensitivity analysis are also conducted. Results show that the method is able to accurately detect change points at very low computational costs. More broadly, the detection of specific change points within time series of virtually any domain is made more intuitive and more understandable, even for experts not related to data mining.