98 research outputs found

    The classification ofseparable simple C*-algebras which are inductive limits of continuous-trace C*-algebraswith spectrum homeomorphic to the closed interval [0,1]

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    A classification is given of certain separable nuclear C*-algebras not necessarily of real rank zero, namely, the class of separable simple C*-algebras which are inductive limits of continuous-trace C*-algebras whose building blocks have spectrum homeomorphic to the closed interval [0,1], or to a disjoint union of copies of this space. Also, the range of the invariant is calculated.Comment: 41 pages, 6figure

    Tourists’ experiences of mega-event cities: Rio’s olympic ‘double bubbles’

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    Rio 2016 sought to connect Olympic-tourists with the city’s local-Cariocan community and culture. Yet the way mega-events are spatially and regulatorily organized, alongside the behavioural tendencies of Olympic-tourists, constrain such ambitions. Using Rio 2016 as a case-study, we offer in-depth, qualitative insights through the lens of 35 individual Olympic-tourists to examine how and why these factors determine behaviour, and thus experiences across host-environments. We detail how concerns over tourists’ safety result in managers designing risk averse experiences, produced by overlaying hyper-securitized and regulatory enforcements inside existing tourist bubbles, creating what we refer to as a ‘double bubble’ – reducing the likelihood of visitors venturing ‘off-the-beaten-track’. Whilst Olympic-bubbles protect tourists from outside threats, they restrict cultural engagement with the wider city, neighbourhoods and locals – side-lining other sides to Rio. We suggest managers adopt a dual-strategy of ‘local infusion’ in and ‘tourist diffusion’ beyond official zones to achieve intended goals

    Measurement Properties of 2 Novel PROs, the Pompe Disease Symptom Scale and Pompe Disease Impact Scale, in the COMET Study

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    Background and Objectives: The Pompe Disease Symptom Scale (PDSS) and Impact Scale (PDIS) were created to measure the severity of symptoms and functional limitations experienced by patients with late-onset Pompe disease (LOPD). The objectives of this analysis were to establish a scoring algorithm and to examine the reliability, validity, and responsiveness of the measures using data from the COMET clinical trial. Methods: The COMET trial was a randomized, double-blind study comparing the efficacy and safety of avalglucosidase alfa and alglucosidase alfa in patients with LOPD aged 16-78 years at baseline. Adult participants (18 years or older) completed the PDSS and PDIS daily for 14 days at baseline and for 2 weeks before quarterly clinic visits for 1 year after randomization using an electronic diary. Data were pooled across treatment groups for the current analyses. Factor analysis and inter-item correlations were used to derive a scoring algorithm. Test-retest and internal consistency analyses examined the reliability of the measures. Correlations with criterion measures were used to evaluate validity and sensitivity to change. Anchor and distribution-based analyses were conducted to estimate thresholds for meaningful change. Results: Five multi-item domain scores were derived from the PDSS (Shortness of Breath, Overall Fatigue, Fatigue/Pain, Upper Extremity Weakness, Pain) and 2 from the PDIS (Mood, Difficulty Performing Activities). Internal consistency (Cronbach α &gt; 0.90) and test-retest reliability (intraclass correlation &gt;0.60) of the scores were supported. Cross-sectional and longitudinal correlations with the criterion measures generally supported the validity of the scores (r &gt; 0.40). Within-patient meaningful change estimates ranging from 1.0 to 1.5 points were generated for the PDSS and PDIS domain scores. Discussion The PDSS and PDIS are reliable and valid measures of LOPD symptoms and functional impacts. The measures can be used to evaluate burden of LOPD and effects of treatments in clinical trials, observational research, and clinical practice.</p

    Modelling subject-specific childhood growth using linear mixed-effect models with cubic regression splines.

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    Childhood growth is a cornerstone of pediatric research. Statistical models need to consider individual trajectories to adequately describe growth outcomes. Specifically, well-defined longitudinal models are essential to characterize both population and subject-specific growth. Linear mixed-effect models with cubic regression splines can account for the nonlinearity of growth curves and provide reasonable estimators of population and subject-specific growth, velocity and acceleration.We provide a stepwise approach that builds from simple to complex models, and account for the intrinsic complexity of the data. We start with standard cubic splines regression models and build up to a model that includes subject-specific random intercepts and slopes and residual autocorrelation. We then compared cubic regression splines vis-à-vis linear piecewise splines, and with varying number of knots and positions. Statistical code is provided to ensure reproducibility and improve dissemination of methods. Models are applied to longitudinal height measurements in a cohort of 215 Peruvian children followed from birth until their fourth year of life.Unexplained variability, as measured by the variance of the regression model, was reduced from 7.34 when using ordinary least squares to 0.81 (p < 0.001) when using a linear mixed-effect models with random slopes and a first order continuous autoregressive error term. There was substantial heterogeneity in both the intercept (p < 0.001) and slopes (p < 0.001) of the individual growth trajectories. We also identified important serial correlation within the structure of the data (ρ = 0.66; 95 % CI 0.64 to 0.68; p < 0.001), which we modeled with a first order continuous autoregressive error term as evidenced by the variogram of the residuals and by a lack of association among residuals. The final model provides a parametric linear regression equation for both estimation and prediction of population- and individual-level growth in height. We show that cubic regression splines are superior to linear regression splines for the case of a small number of knots in both estimation and prediction with the full linear mixed effect model (AIC 19,352 vs. 19,598, respectively). While the regression parameters are more complex to interpret in the former, we argue that inference for any problem depends more on the estimated curve or differences in curves rather than the coefficients. Moreover, use of cubic regression splines provides biological meaningful growth velocity and acceleration curves despite increased complexity in coefficient interpretation.Through this stepwise approach, we provide a set of tools to model longitudinal childhood data for non-statisticians using linear mixed-effect models

    Heart failure pharmacotherapy and cancer:pathways and pre-clinical/clinical evidence

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    Heart failure (HF) patients have a significantly higher risk of new-onset cancer and cancer-associated mortality, compared to subjects free of HF. While both the prevention and treatment of new-onset HF in patients with cancer have been investigated extensively, less is known about the prevention and treatment of new-onset cancer in patients with HF, and whether and how guideline-directed medical therapy (GDMT) for HF should be modified when cancer is diagnosed in HF patients. The purpose of this review is to elaborate and discuss the effects of pillar HF pharmacotherapies, as well as digoxin and diuretics on cancer, and to identify areas for further research and novel therapeutic strategies. To this end, in this review, (i) proposed effects and mechanisms of action of guideline-directed HF drugs on cancer derived from pre-clinical data will be described, (ii) the evidence from both observational studies and randomized controlled trials on the effects of guideline-directed medical therapy on cancer incidence and cancer-related outcomes, as synthetized by meta-analyses will be reviewed, and (iii) considerations for future pre-clinical and clinical investigations will be provided.</p

    Evidence of West Nile virus (WNV) circulation in wild birds and WNV RNA negativity in mosquitoes of the Danube Delta Biosphere Reserve, Romania, 2016

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    West Nile virus (WNV) is a zoonotic flavivirus whose transmission cycle in nature includes wild birds as amplifying hosts and ornithophilic mosquito vectors. Bridge vectors can transmit WNV to mammal species potentially causing West Nile Fever. Wild bird migration is a mode of WNV introduction into new areas. The Danube Delta Biosphere Reserve (DDBR) is a major stopover of wild birds migrating between Europe and Africa. The aim of this study was to investigate the presence of WNV in the DDBR during the 2016 transmission season in wild birds and mosquitoes. Blood from 68 wild birds (nine different species) trapped at four different locations was analyzed by competitive ELISA and Virus Neutralization Test (VNT), revealing positive results in 8/68 (11.8%) of the wild birds by ELISA of which six samples (three from juvenile birds) were confirmed seropositive by VNT. Mosquitoes (n = 6523, 5 genera) were trapped with CDC Mini Light traps at two locations and in one location resting mosquitoes were caught. The presence of WNV RNA was tested in 134 pools by reverse transcription quantitative PCR (RT-qPCR). None of the pools was positive for WNV-specific RNA. Based on the obtained results, WNV was circulating in the DDBR during 2016
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