110 research outputs found
Modelling the spatial distribution of DEM Error
Assessment of a DEM’s quality is usually undertaken by deriving a measure of DEM accuracy – how close the DEM’s elevation values are to the true elevation. Measures such as Root Mean Squared Error and standard deviation of the error are frequently used. These measures summarise elevation errors in a DEM as a single value. A more detailed description of DEM accuracy would allow better understanding of DEM quality and the consequent uncertainty associated with using DEMs in analytical applications. The research presented addresses the limitations of using a single root mean squared error (RMSE) value to represent the uncertainty associated with a DEM by developing a new technique for creating a spatially distributed model of DEM quality – an accuracy surface. The technique is based on the hypothesis that the distribution and scale of elevation error within a DEM are at least partly related to morphometric characteristics of the terrain. The technique involves generating a set of terrain parameters to characterise terrain morphometry and developing regression models to define the relationship between DEM error and morphometric character. The regression models form the basis for creating standard deviation surfaces to represent DEM accuracy. The hypothesis is shown to be true and reliable accuracy surfaces are successfully created. These accuracy surfaces provide more detailed information about DEM accuracy than a single global estimate of RMSE
An open software development-based ecosystem of R packages for metabolomics data analysis
A frequent problem with scientific research software is the lack of support, maintenance and further development. In particular, development by a single researcher can easily result in orphaned software packages, especially if combined with poor documentation or lack of adherence to open software development standards. The RforMassSpectrometry initiative aims to develop an efficient and stable infrastructure for mass spectrometry (MS) data analysis. As part of this initiative, a growing ecosystem of R software packages is being developed covering different aspects of metabolomics and proteomics data analysis. To avoid the aforementioned problems, community contributions are fostered, and open development, documentation and long-term support emphasized. At the heart of the package ecosystem is the Spectra package that provides the core infrastructure to handle and analyze MS data. Its design allows easy expansion to support additional file or data formats including data representations with minimal memory footprint or remote data access. The xcms package for LC-MS data preprocessing was updated to reuse this infrastructure, enabling now also the analysis of very large, or remote, data. This integration simplifies in addition complete analysis workflows which can include the MsFeatures package for compounding, and the MetaboAnnotation package for annotation of untargeted metabolomics experiments. Public annotation resources can be easily accessed through packages such as MsBackendMassbank, MsBackendMgf, MsBackendMsp or CompoundDb, the latter also allowing to create and manage lab-specific compound databases. Finally, the MsCoreUtils and MetaboCoreUtils packages provide efficient implementations of commonly used algorithms, designed to be re-used in other R packages. Ultimately, and in contrast to a monolithic software design, the package ecosystem enables to build customized, modular, and reproducible analysis workflows. Future development will focus on improved data structures and analysis methods for chromatographic data, and better interoperability with other open source softwares including a direct integration with Python MS libraries
Comparison of the Tax System Progressivity Over Time: Theory and Application with Mexican Data
Duration of clopidogrel treatment and risk of mortality and recurrent myocardial infarction among 11 680 patients with myocardial infarction treated with percutaneous coronary intervention: a cohort study
<p>Abstract</p> <p>Background</p> <p>The optimal duration of clopidogrel treatment after percutaneous coronary intervention (PCI) is unclear. We studied the risk of death or recurrent myocardial infarction (MI) in relation to 6- and 12-months clopidogrel treatment among MI patients treated with PCI.</p> <p>Methods</p> <p>Using nationwide registers of hospitalizations and drug dispensing from pharmacies we identified 11 680 patients admitted with MI, treated with PCI and clopidogrel. Clopidogrel treatment was categorized in a 6-months and a 12-months regimen. Rates of death, recurrent MI or a combination of both were analyzed by the Kaplan Meier method and Cox proportional hazards models. Bleedings were compared between treatment regimens.</p> <p>Results</p> <p>The Kaplan Meier analysis indicated no benefit of the 12-months regimen compared with the 6-months in all endpoints. The Cox proportional hazards analysis confirmed these findings with hazard ratios for the 12-months regimen (the 6-months regimen used as reference) for the composite endpoint of 1.01 (confidence intervals 0.81-1.26) and 1.24 (confidence intervals 0.95-1.62) for Day 0-179 and Day 180-540 after discharge. Bleedings occurred in 3.5% and 4.1% of the patients in the 6-months and 12-months regimen (p = 0.06).</p> <p>Conclusions</p> <p>We found comparable rates of death and recurrent MI in patients treated with 6- and 12-months' clopidogrel. The potential benefit of prolonged clopidogrel treatment in a real-life setting remains uncertain.</p
The BET inhibitor JQ1 selectively impairs tumour response to hypoxia and downregulates CA9 and angiogenesis in triple negative breast cancer
The availability of bromodomain and extra-terminal inhibitors (BETi) has enabled translational epigenetic studies in cancer. BET proteins regulate transcription by selectively recognizing acetylated lysine residues on chromatin. BETi compete with this process leading to both downregulation and upregulation of gene expression. Hypoxia enables progression of triple negative breast cancer (TNBC), the most aggressive form of breast cancer, partly by driving metabolic adaptation, angiogenesis and metastasis through upregulation of hypoxia-regulated genes (for example, carbonic anhydrase 9 (CA9) and vascular endothelial growth factor A (VEGF-A). Responses to hypoxia can be mediated epigenetically, thus we investigated whether BETi JQ1 could impair the TNBC response induced by hypoxia and exert anti-tumour effects. JQ1 significantly modulated 44% of hypoxia-induced genes, of which two-thirds were downregulated including CA9 and VEGF-A. JQ1 prevented HIF binding to the hypoxia response element in CA9 promoter, but did not alter HIF expression or activity, suggesting some HIF targets are BET-dependent. JQ1 reduced TNBC growth in vitro and in vivo and inhibited xenograft vascularization. These findings identify that BETi dually targets angiogenesis and the hypoxic response, an effective combination at reducing tumour growth in preclinical studies
Anticoagulant selection in relation to the SAMe-TT2R2 score in patients with atrial fibrillation. the GLORIA-AF registry
Aim: The SAMe-TT2R2 score helps identify patients with atrial fibrillation (AF) likely to have poor anticoagulation control during anticoagulation with vitamin K antagonists (VKA) and those with scores >2 might be better managed with a target-specific oral anticoagulant (NOAC). We hypothesized that in clinical practice, VKAs may be prescribed less frequently to patients with AF and SAMe-TT2R2 scores >2 than to patients with lower scores. Methods and results: We analyzed the Phase III dataset of the Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation (GLORIA-AF), a large, global, prospective global registry of patients with newly diagnosed AF and ≥1 stroke risk factor. We compared baseline clinical characteristics and antithrombotic prescriptions to determine the probability of the VKA prescription among anticoagulated patients with the baseline SAMe-TT2R2 score >2 and ≤ 2. Among 17,465 anticoagulated patients with AF, 4,828 (27.6%) patients were prescribed VKA and 12,637 (72.4%) patients an NOAC: 11,884 (68.0%) patients had SAMe-TT2R2 scores 0-2 and 5,581 (32.0%) patients had scores >2. The proportion of patients prescribed VKA was 28.0% among patients with SAMe-TT2R2 scores >2 and 27.5% in those with scores ≤2. Conclusions: The lack of a clear association between the SAMe-TT2R2 score and anticoagulant selection may be attributed to the relative efficacy and safety profiles between NOACs and VKAs as well as to the absence of trial evidence that an SAMe-TT2R2-guided strategy for the selection of the type of anticoagulation in NVAF patients has an impact on clinical outcomes of efficacy and safety. The latter hypothesis is currently being tested in a randomized controlled trial. Clinical trial registration: URL: https://www.clinicaltrials.gov//Unique identifier: NCT01937377, NCT01468701, and NCT01671007
Comparative effectiveness and safety of non-vitamin K antagonists for atrial fibrillation in clinical practice: GLORIA-AF Registry
Comparative effectiveness and safety of non-vitamin K antagonists for atrial fibrillation in clinical practice: GLORIA-AF Registry
Background and purpose: Prospectively collected data comparing the safety and effectiveness of individual non-vitamin K antagonists (NOACs) are lacking. Our objective was to directly compare the effectiveness and safety of NOACs in patients with newly diagnosed atrial fibrillation (AF). Methods: In GLORIA-AF, a large, prospective, global registry program, consecutive patients with newly diagnosed AF were followed for 3 years. The comparative analyses for (1) dabigatran vs rivaroxaban or apixaban and (2) rivaroxaban vs apixaban were performed on propensity score (PS)-matched patient sets. Proportional hazards regression was used to estimate hazard ratios (HRs) for outcomes of interest. Results: The GLORIA-AF Phase III registry enrolled 21,300 patients between January 2014 and December 2016. Of these, 3839 were prescribed dabigatran, 4015 rivaroxaban and 4505 apixaban, with median ages of 71.0, 71.0, and 73.0 years, respectively. In the PS-matched set, the adjusted HRs and 95% confidence intervals (CIs) for dabigatran vs rivaroxaban were, for stroke: 1.27 (0.79–2.03), major bleeding 0.59 (0.40–0.88), myocardial infarction 0.68 (0.40–1.16), and all-cause death 0.86 (0.67–1.10). For the comparison of dabigatran vs apixaban, in the PS-matched set, the adjusted HRs were, for stroke 1.16 (0.76–1.78), myocardial infarction 0.84 (0.48–1.46), major bleeding 0.98 (0.63–1.52) and all-cause death 1.01 (0.79–1.29). For the comparison of rivaroxaban vs apixaban, in the PS-matched set, the adjusted HRs were, for stroke 0.78 (0.52–1.19), myocardial infarction 0.96 (0.63–1.45), major bleeding 1.54 (1.14–2.08), and all-cause death 0.97 (0.80–1.19). Conclusions: Patients treated with dabigatran had a 41% lower risk of major bleeding compared with rivaroxaban, but similar risks of stroke, MI, and death. Relative to apixaban, patients treated with dabigatran had similar risks of stroke, major bleeding, MI, and death. Rivaroxaban relative to apixaban had increased risk for major bleeding, but similar risks for stroke, MI, and death. Registration: URL: https://www.clinicaltrials.gov. Unique identifiers: NCT01468701, NCT01671007. Date of registration: September 2013
Can patients presenting with acute coronary syndrome be screened for diabetes using glycosylated haemoglobin?
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