The systemic lupus erythematosus IRF5 risk haplotype is associated with systemic sclerosis

Systemic sclerosis (SSc) is a fibrotic autoimmune disease in which the genetic component plays an important role. One of the strongest SSc association signals outside the human leukocyte antigen (HLA) region corresponds to interferon (IFN) regulatory factor 5 (IRF5), a major regulator of the type I IFN pathway. In this study we aimed to evaluate whether three different haplotypic blocks within this locus, which have been shown to alter the protein function influencing systemic lupus erythematosus (SLE) susceptibility, are involved in SSc susceptibility and clinical phenotypes. For that purpose, we genotyped one representative single-nucleotide polymorphism (SNP) of each block (rs10488631, rs2004640, and rs4728142) in a total of 3,361 SSc patients and 4,012 unaffected controls of Caucasian origin from Spain, Germany, The Netherlands, Italy and United Kingdom. A meta-analysis of the allele frequencies was performed to analyse the overall effect of these IRF5 genetic variants on SSc. Allelic combination and dependency tests were also carried out. The three SNPs showed strong associations with the global disease (rs4728142: P = 1.34×10<sup>−8</sup>, OR = 1.22, CI 95% = 1.14–1.30; rs2004640: P = 4.60×10<sup>−7</sup>, OR = 0.84, CI 95% = 0.78–0.90; rs10488631: P = 7.53×10<sup>−20</sup>, OR = 1.63, CI 95% = 1.47–1.81). However, the association of rs2004640 with SSc was not independent of rs4728142 (conditioned P = 0.598). The haplotype containing the risk alleles (rs4728142*A-rs2004640*T-rs10488631*C: P = 9.04×10<sup>−22</sup>, OR = 1.75, CI 95% = 1.56–1.97) better explained the observed association (likelihood P-value = 1.48×10<sup>−4</sup>), suggesting an additive effect of the three haplotypic blocks. No statistical significance was observed in the comparisons amongst SSc patients with and without the main clinical characteristics. Our data clearly indicate that the SLE risk haplotype also influences SSc predisposition, and that this association is not sub-phenotype-specific

Residual sleep disturbance and risk of relapse during the continuation/maintenance phase treatment of major depressive disorder with the selective serotonin reuptake inhibitor fluoxetine

<p>Abstract</p> <p>Background</p> <p>Relapse of major depressive disorder (MDD) is a common clinical problem. This study was designed to determine whether residual sleep disturbance (insomnia and hypersomnia) predict risk of relapse during the continuation and maintenance treatment of MDD.</p> <p>Methods</p> <p>A total of 570 patients with MDD were treated with open-label, flexible dose fluoxetine (range 20 to 60 mg; mean dose = 45.8 mg/day; SD = 15.1) for 12 weeks. Under double blind conditions, 262 patients who achieved clinical response were randomly assigned to continue fluoxetine or to switch to placebo for 52 weeks or until relapse. Residual sleep disturbance during the baseline visit of the double-blind phase was assessed using items 4, 5, 6 (insomnia) and 22, 23, 24 (hypersomnia) of the Hamilton Depression Rating Scale (HDRS). Survival analysis was utilized to determine the effect of residual sleep disturbance on risk of relapse.</p> <p>Results</p> <p>The severities of early (<it>P </it>> 0.05), middle (<it>P </it>> 0.05), late (<it>P </it>> 0.05), or total (<it>P </it>> 0.05) residual insomnia were not found to significantly predict risk of relapse during continuation and maintenance-phase treatment. Similarly, the severities of early bedtime (<it>P </it>> 0.05), oversleeping (<it>P </it>> 0.05), napping (<it>P </it>> 0.05), or total (<it>P </it>> 0.05) residual hypersomnia were not found to significantly predict risk of relapse during continuation and maintenance-phase treatment.</p> <p>Conclusion</p> <p>The present study did not identify the severity of residual sleep disturbance among fluoxetine responders to predict risk of MDD relapse. The size of our sample may have precluded us from identifying more modest effects of residual sleep disturbance on the risk of relapse in MDD patients. Future studies are needed to further explore the relationship between residual sleep disturbance and relapse in MDD.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov Identifier: NCT00427128</p

A statistical approach to quantitative data validation focused on the assessment of students' perceptions about biotechnology

Student awareness levels are frequently used to evaluate the effectiveness of educational policies to promote scientific literacy. Over the last years several studies have been developed to assess students' perceptions towards science and technology, which usually rely on quantitative methods to achieve broad characterizations, and obtain quantifiable and comparable data. Although the usefulness of this information depends on its validity and reliability, validation is frequently neglected by researchers with limited background in statistics. In this context, we propose a guideline to implement a statistical approach to questionnaire validation, combining exploratory factor analysis and reliability analysis. The work focuses on the psychometric analysis of data provided by a questionnaire assessing 1196 elementary and high school students' perceptions about biotechnology. Procedural guidelines to enhance the efficiency of quantitative inquiry surveys are given, by discussing essential methodological aspects and relevant criteria to integrate theory into practice.The authors are grateful to all the participant teachers and students that contributed to gather the data presented and to Catarina L. Santos for useful comments and suggestions on the manuscript. Maria Joao Fonseca was supported by the FCT fellowship SFRH/BD/37389/2007 and this work was sponsored by a research grant (PTDC/AGR-PRO/111857/2009) from Fundacao para a Ciencia e Tecnologia (FCT, Portugal)

Measuring efficiency and productivity in professional football teams: Evidence from the English Premier League

Professional football clubs are unusual businesses, their performance judged on and off the field of play. This study is concerned with measuring the efficiency of clubs in the English Premier League. Information from clubs’ financial statements is used as a measure of corporate performance. To measure changes in efficiency and productivity the Malmquist non-parametric technique has been used. This is derived from the Data Envelopment Analysis (DEA) linear programming approach, with Canonical Correlation Analysis (CCA) being used to ensure the cohesion of the input-output variables. The study concludes that while clubs operate close to efficient levels for the assessed models, there is limited technological advance in their performance in terms of the displacement of the technological frontier

Belediye Müzesi

Taha Toros Arşivi, Dosya No: 114-Müzelerİstanbul Kalkınma Ajansı (TR10/14/YEN/0033) İstanbul Development Agency (TR10/14/YEN/0033

Assessing the queuing process using data envelopment analysis:an application in health centres

Queuing is one of the very important criteria for assessing the performance and efficiency of any service industry, including healthcare. Data Envelopment Analysis (DEA) is one of the most widely-used techniques for performance measurement in healthcare. However, no queue management application has been reported in the health-related DEA literature. Most of the studies regarding patient flow systems had the objective of improving an already existing Appointment System. The current study presents a novel application of DEA for assessing the queuing process at an Outpatients’ department of a large public hospital in a developing country where appointment systems do not exist. The main aim of the current study is to demonstrate the usefulness of DEA modelling in the evaluation of a queue system. The patient flow pathway considered for this study consists of two stages; consultation with a doctor and pharmacy. The DEA results indicated that waiting times and other related queuing variables included need considerable minimisation at both stages

Characterization of a fluvial aquifer at a range of depths and scales: the Triassic St Bees Sandstone Formation, Cumbria, UK

Fluvial sedimentary successions represent porous media that host groundwater and geothermal resources. Additionally, they overlie crystalline rocks hosting nuclear waste repositories in rift settings. The permeability characteristics of an arenaceous fluvial succession, the Triassic St Bees Sandstone Formation in England (UK), are described, from core-plug to well-test scale up to ~1 km depth. Within such lithified successions, dissolution associated with the circulation of meteoric water results in increased permeability (K~10−1–100 m/day) to depths of at least 150 m below ground level (BGL) in aquifer systems that are subject to rapid groundwater circulation. Thus, contaminant transport is likely to occur at relatively high rates. In a deeper investigation (> 150 m depth), where the aquifer has not been subjected to rapid groundwater circulation, well-test-scale hydraulic conductivity is lower, decreasing from K~10−2 m/day at 150–400 m BGL to 10−3 m/day down-dip at ~1 km BGL, where the pore fluid is hypersaline. Here, pore-scale permeability becomes progressively dominant with increasing lithostatic load. Notably, this work investigates a sandstone aquifer of fluvial origin at investigation depths consistent with highly enthalpy geothermal reservoirs (~0.7–1.1 km). At such depths, intergranular flow dominates in unfaulted areas with only minor contribution by bedding plane fractures. However, extensional faults represent preferential flow pathways, due to presence of high connective open fractures. Therefore, such faults may (1) drive nuclear waste contaminants towards the highly permeable shallow (< 150 m BGL) zone of the aquifer, and (2) influence fluid recovery in geothermal fields

Cross-disease Meta-analysis of Genome-wide Association Studies for Systemic Sclerosis and Rheumatoid Arthritis Reveals IRF4 as a New Common Susceptibility Locus

OBJECTIVES: Systemic sclerosis (SSc) and rheumatoid arthritis (RA) are autoimmune diseases that share clinical and immunological characteristics. To date, several shared SSc-RA loci have been identified independently. In this study, we aimed to systematically search for new common SSc-RA loci through an inter-disease meta-GWAS strategy. METHODS: We performed a meta-analysis combining GWAS datasets of SSc and RA using a strategy that allowed identification of loci with both same-direction and opposing-direction allelic effects. The top single-nucleotide polymorphisms (SNPs) were followed-up in independent SSc and RA case-control cohorts. This allowed us to increase the sample size to a total of 8,830 SSc patients, 16,870 RA patients and 43,393 controls. RESULTS: The cross-disease meta-analysis of the GWAS datasets identified several loci with nominal association signals (P-value < 5 x 10(-6) ), which also showed evidence of association in the disease-specific GWAS scan. These loci included several genomic regions not previously reported as shared loci, besides risk factors associated with both diseases in previous studies. The follow-up of the putatively new SSc-RA loci identified IRF4 as a shared risk factor for these two diseases (Pcombined = 3.29 x 10(-12) ). In addition, the analysis of the biological relevance of the known SSc-RA shared loci pointed to the type I interferon and the interleukin 12 signaling pathways as the main common etiopathogenic factors. CONCLUSIONS: Our study has identified a novel shared locus, IRF4, for SSc and RA and highlighted the usefulness of cross-disease GWAS meta-analysis in the identification of common risk loci