640 research outputs found

    A core outcome set for evaluating self-management interventions in people with comorbid diabetes and severe mental illness : study protocol for a modified Delphi study and systematic review

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    BACKGROUND: People with diabetes and comorbid severe mental illness (SMI) form a growing population at risk of increased mortality and morbidity compared to those with diabetes or SMI alone. There is increasing interest in interventions that target diabetes in SMI in order to help to improve physical health and reduce the associated health inequalities. However, there is a lack of consensus about which outcomes are important for this comorbid population, with trials differing in their focus on physical and mental health. A core outcome set, which includes outcomes across both conditions that are relevant to patients and other key stakeholders, is needed. METHODS: This study protocol describes methods to develop a core outcome set for use in effectiveness trials of self-management interventions for adults with comorbid type-2 diabetes and SMI. We will use a modified Delphi method to identify, rank, and agree core outcomes. This will comprise a two-round online survey and multistakeholder workshops involving patients and carers, health and social care professionals, health care commissioners, and other experts (e.g. academic researchers and third sector organisations). We will also select appropriate measurement tools for each outcome in the proposed core set and identify gaps in measures, where these exist. DISCUSSION: The proposed core outcome set will provide clear guidance about what outcomes should be measured, as a minimum, in trials of interventions for people with coexisting type-2 diabetes and SMI, and improve future synthesis of trial evidence in this area. We will also explore the challenges of using online Delphi methods for this hard-to-reach population, and examine differences in opinion about which outcomes matter to diverse stakeholder groups. TRIAL REGISTRATION: COMET registration: http://www.comet-initiative.org/studies/details/911 . Registered on 1 July 2016

    The Quality of Naps in Young Children with Sleeping Difficulties: the Role of Parents and Preschools

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    Minimal research exists in regards to day-time naps in children, and to date no research has examined the architecture of naps in children. The present study examined the quality of naps in the preschool environment compared to the home environment in children with sleeping difficulties. The participants were three children aged 1 year, 8 months to 2 years, 2 months. The naps were digitally recorded in the children’s homes and their preschool. The digital recordings were coded using a sleep coding system, which established the sleep states and patterns of the naps. The results indicated that the naps were individually distinctive and varied across the children and across the environments. The majority of sleep times were spent in quiet sleep compared to active sleep. The most consistent finding was that the mean length of sleep (where sleep occurred during nap time) for each child was longer in the home environment than the preschool environment. Caregiver behaviour across the environments shared similarities. Children with sleeping difficulties were chosen for this study as they represent a more challenging population for parents and teachers. It is possible that the sleeping difficulties may have overridden the differences in sleeping environments. This is an interesting and important area of future research

    Possible Associations of NTRK2 Polymorphisms with Antidepressant Treatment Outcome: Findings from an Extended Tag SNP Approach

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    Background: Data from clinical studies and results from animal models suggest an involvement of the neurotrophin system in the pathology of depression and antidepressant treatment response. Genetic variations within the genes coding for the brain-derived neurotrophic factor (BDNF) and its key receptor Trkb (NTRK2) may therefore influence the response to antidepressant treatment. Methods: We performed a single and multi-marker association study with antidepressant treatment outcome in 398 depressed Caucasian inpatients participating in the Munich Antidepressant Response Signature (MARS) project. Two Caucasian replication samples (N = 249 and N = 247) were investigated, resulting in a total number of 894 patients. 18 tagging SNPs in the BDNF gene region and 64 tagging SNPs in the NTRK2 gene region were genotyped in the discovery sample; 16 nominally associated SNPs were tested in two replication samples. Results: In the discovery analysis, 7 BDNF SNPs and 9 NTRK2 SNPs were nominally associated with treatment response. Three NTRK2 SNPs (rs10868223, rs1659412 and rs11140778) also showed associations in at least one replication sample and in the combined sample with the same direction of effects (PcorrP_{corr} = .018, PcorrP_{corr} = .015 and PcorrP_{corr} = .004, respectively). We observed an across-gene BDNF-NTRK2 SNP interaction for rs4923468 and rs1387926. No robust interaction of associated SNPs was found in an analysis of BDNF serum protein levels as a predictor for treatment outcome in a subset of 93 patients. Conclusions/Limitations: Although not all associations in the discovery analysis could be unambiguously replicated, the findings of the present study identified single nucleotide variations in the BDNF and NTRK2 genes that might be involved in antidepressant treatment outcome and that have not been previously reported in this context. These new variants need further validation in future association studies

    SHREC 2011: robust feature detection and description benchmark

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    Feature-based approaches have recently become very popular in computer vision and image analysis applications, and are becoming a promising direction in shape retrieval. SHREC'11 robust feature detection and description benchmark simulates the feature detection and description stages of feature-based shape retrieval algorithms. The benchmark tests the performance of shape feature detectors and descriptors under a wide variety of transformations. The benchmark allows evaluating how algorithms cope with certain classes of transformations and strength of the transformations that can be dealt with. The present paper is a report of the SHREC'11 robust feature detection and description benchmark results.Comment: This is a full version of the SHREC'11 report published in 3DO

    BepiColombo-Mission Overview and Science Goals

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    BepiColombo is a joint mission between the European Space Agency, ESA, and the Japanese Aerospace Exploration Agency, JAXA, to perform a comprehensive exploration of Mercury. Launched on 20th October 2018 from the European spaceport in Kourou, French Guiana, the spacecraft is now en route to Mercury. Two orbiters have been sent to Mercury and will be put into dedicated, polar orbits around the planet to study the planet and its environment. One orbiter, Mio, is provided by JAXA, and one orbiter, MPO, is provided by ESA. The scientific payload of both spacecraft will provide detailed information necessary to understand the origin and evolution of the planet itself and its surrounding environment. Mercury is the planet closest to the Sun, the only terrestrial planet besides Earth with a self-sustained magnetic field, and the smallest planet in our Solar System. It is a key planet for understanding the evolutionary history of our Solar System and therefore also for the question of how the Earth and our Planetary System were formed. The scientific objectives focus on a global characterization ofMercury through the investigation of its interior, surface, exosphere, and magnetosphere. In addition, instrumentation onboard BepiColombo will be used to test Einstein's theory of general relativity. Major effort was put into optimizing the scientific return of the mission by defining a payload such that individual measurements can be interrelated and complement each other.Peer reviewe
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