953 research outputs found

    The Rx for Change database: a first-in-class tool for optimal prescribing and medicines use

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    <p>Abstract</p> <p>Background</p> <p>Globally, suboptimal prescribing practices and medication errors are common. Guidance to health professionals and consumers alone is not sufficient to optimise behaviours, therefore strategies to promote evidence-based decision making and practice, such as decision support tools or reminders, are important. The literature in this area is growing, but is of variable quality and dispersed across sources, which makes it difficult to identify, access, and assess. To overcome these problems, by synthesizing and evaluating the data from systematic reviews, we have developed <it>Rx for Change </it>to provide a comprehensive, online database of the evidence for strategies to improve drug prescribing and use.</p> <p>Methods</p> <p>We use reliable and valid methods to search and screen the literature, and to appraise and analyse the evidence from relevant systematic reviews. We then present the findings in an online format which allows users to easily access pertinent information related to prescribing and medicines use. The database is a result of the collaboration between the Canadian Agency for Drugs and Technologies in Health (CADTH) and two Cochrane review groups.</p> <p>Results</p> <p>To capture the body of evidence on interventions to improve prescribing and medicines use, we conduct comprehensive and regular searches in multiple databases, and hand-searches of relevant journals. We screen articles to identify relevant systematic reviews, and include them if they are of moderate or high methodological quality. Two researchers screen, assess quality, and extract data on demographic details, intervention characteristics, and outcome data. We report the results of our analysis of each systematic review using a standardised quantitative and qualitative format. <it>Rx for Change </it>currently contains over 200 summarised reviews, structured in a multi-level format. The reviews included in the database are diverse, covering various settings, conditions, or diseases and targeting a range of professional and consumer behaviors.</p> <p>Conclusions</p> <p><it>Rx for Change </it>is a novel database that synthesizes current research evidence about the effects of interventions to improve drug prescribing practices and medicines use.</p

    Nonlinear and delayed impacts of climate on dengue risk in Barbados: A modelling study

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    Background: Over the last 5 years (2013–2017), the Caribbean region has faced an unprecedented crisis of co-occurring epidemics of febrile illness due to arboviruses transmitted by the Aedes sp. mosquito (dengue, chikungunya, and Zika). Since 2013, the Caribbean island of Barbados has experienced 3 dengue outbreaks, 1 chikungunya outbreak, and 1 Zika fever outbreak. Prior studies have demonstrated that climate variability influences arbovirus transmission and vector population dynamics in the region, indicating the potential to develop public health interventions using climate information. The aim of this study is to quantify the nonlinear and delayed effects of climate indicators, such as drought and extreme rainfall, on dengue risk in Barbados from 1999 to 2016. Methods and findings: Distributed lag nonlinear models (DLNMs) coupled with a hierarchal mixed-model framework were used to understand the exposure–lag–response association between dengue relative risk and key climate indicators, including the standardised precipitation index (SPI) and minimum temperature (Tmin). The model parameters were estimated in a Bayesian framework to produce probabilistic predictions of exceeding an island-specific outbreak threshold. The ability of the model to successfully detect outbreaks was assessed and compared to a baseline model, representative of standard dengue surveillance practice. Drought conditions were found to positively influence dengue relative risk at long lead times of up to 5 months, while excess rainfall increased the risk at shorter lead times between 1 and 2 months. The SPI averaged over a 6-month period (SPI-6), designed to monitor drought and extreme rainfall, better explained variations in dengue risk than monthly precipitation data measured in millimetres. Tmin was found to be a better predictor than mean and maximum temperature. Furthermore, including bidimensional exposure–lag–response functions of these indicators—rather than linear effects for individual lags—more appropriately described the climate–disease associations than traditional modelling approaches. In prediction mode, the model was successfully able to distinguish outbreaks from nonoutbreaks for most years, with an overall proportion of correct predictions (hits and correct rejections) of 86% (81%:91%) compared with 64% (58%:71%) for the baseline model. The ability of the model to predict dengue outbreaks in recent years was complicated by the lack of data on the emergence of new arboviruses, including chikungunya and Zika. Conclusion: We present a modelling approach to infer the risk of dengue outbreaks given the cumulative effect of climate variations in the months leading up to an outbreak. By combining the dengue prediction model with climate indicators, which are routinely monitored and forecasted by the Regional Climate Centre (RCC) at the Caribbean Institute for Meteorology and Hydrology (CIMH), probabilistic dengue outlooks could be included in the Caribbean Health-Climatic Bulletin, issued on a quarterly basis to provide climate-smart decision-making guidance for Caribbean health practitioners. This flexible modelling approach could be extended to model the risk of dengue and other arboviruses in the Caribbean region

    Germline heterozygous DDX41 variants in a subset of familial myelodysplasia and acute myeloid leukemia

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    The Brazilian National Council for Scientific and Technological Development), Bloodwise, Children with Cancer and MRC (Medical Research Council, UK)

    Duplication of amyloid precursor protein (APP), but not prion protein (PRNP) gene is a significant cause of early onset dementia in a large UK series.

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    Amyloid precursor protein gene (APP) duplications have been identified in screens of selected probands with early onset familial Alzheimer's disease (FAD). A causal role for copy number variation (CNV) in the prion protein gene (PRNP) in prion dementias is not known. We aimed to determine the prevalence of copy number variation in APP and PRNP in a large referral series, test a screening method for detection of the same, and expand knowledge of clinical phenotype. We used a 3-tiered screening assay for APP and PRNP duplication (exonic real-time quantitative polymerase chain reaction [exon-qPCR], fluorescent microsatellite quantitative PCR [fm-q-PCR], and Illumina array [Illumina Inc., San Diego, CA, USA]) for analysis of a heterogeneous referral series comprising 1531 probands. Five of 1531 probands screened showed APP duplication, a similar prevalence to APP missense mutation. Real-time quantitative PCR and fluorescent microsatellite quantitative PCR were similar individually but are theoretically complementary; we used Illumina arrays as our reference assay. Two of 5 probands were from an autosomal dominant early onset Alzheimer's disease (familial Alzheimer's disease) pedigree. One extensive, noncontiguous duplication on chromosome 21 was consistent with an unbalanced translocation not including the Down's syndrome critical region. Seizures were prominent in the other typical APP duplications. A range of imaging, neuropsychological, cerebrospinal fluid, and pathological findings are reported that extend the known phenotype. APP but not PRNP duplication is a significant cause of early onset dementia in the UK. The recognized phenotype may be expanded to include the possibility of early seizures and apparently sporadic disease which, in part, may be due to different mutational mechanisms. The pros and cons of our screening method are discussed

    A Study of Cosmic Ray Composition in the Knee Region using Multiple Muon Events in the Soudan 2 Detector

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    Deep underground muon events recorded by the Soudan 2 detector, located at a depth of 2100 meters of water equivalent, have been used to infer the nuclear composition of cosmic rays in the "knee" region of the cosmic ray energy spectrum. The observed muon multiplicity distribution favors a composition model with a substantial proton content in the energy region 800,000 - 13,000,000 GeV/nucleus.Comment: 38 pages including 11 figures, Latex, submitted to Physical Review

    A Dynamic Pathway for Calcium-Independent Activation of CaMKII by Methionine Oxidation

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    SummaryCalcium/calmodulin (Ca2+/CaM)-dependent protein kinase II (CaMKII) couples increases in cellular Ca2+ to fundamental responses in excitable cells. CaMKII was identified over 20 years ago by activation dependence on Ca2+/CaM, but recent evidence shows that CaMKII activity is also enhanced by pro-oxidant conditions. Here we show that oxidation of paired regulatory domain methionine residues sustains CaMKII activity in the absence of Ca2+/CaM. CaMKII is activated by angiotensin II (AngII)-induced oxidation, leading to apoptosis in cardiomyocytes both in vitro and in vivo. CaMKII oxidation is reversed by methionine sulfoxide reductase A (MsrA), and MsrA−/− mice show exaggerated CaMKII oxidation and myocardial apoptosis, impaired cardiac function, and increased mortality after myocardial infarction. Our data demonstrate a dynamic mechanism for CaMKII activation by oxidation and highlight the critical importance of oxidation-dependent CaMKII activation to AngII and ischemic myocardial apoptosis
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