University of Alberta

About: University of Alberta is a education organization based out in Edmonton, Alberta, Canada. It is known for research contribution in the topics: Population & Health care. The organization has 65403 authors who have published 154847 publications receiving 5358338 citations. The organization is also known as: Ualberta & UAlberta.

Thrombin-Receptor Antagonist Vorapaxar in Acute Coronary Syndromes

Abstract: In patients with acute coronary syndromes, the addition of vorapaxar to standard therapy did not significantly reduce the primary composite end point but significantly increased the risk of major bleeding, including intracranial hemorrhage. (Funded by Merck; TRACER ClinicalTrials.gov number, NCT00527943.).

Relation Between Red Blood Cell Distribution Width and Cardiovascular Event Rate in People With Coronary Disease

Abstract: Background— Higher levels of red blood cell distribution width (RDW) may be associated with adverse outcomes in patients with heart failure. We examined the association between RDW and the risk of all-cause mortality and adverse cardiovascular outcomes in a population of people with coronary disease who were free of heart failure at baseline. Methods and Results— We performed a post hoc analysis of data from the Cholesterol and Recurrent Events study. Baseline RDW was measured in 4111 participants who were randomized to receive pravastatin 40 mg daily or placebo and followed for a median of 59.7 months. We used Cox proportional hazards models to examine the association between RDW and adverse clinical outcomes. During nearly 60 months of follow-up, 376 participants died. A significant association was noted between baseline RDW level and the adjusted risk of all-cause mortality (hazard ratio per percent increase in RDW, 1.14; 95% confidence interval, 1.05 to 1.24). After categorization based on quartile of...

Peanut shell hybrid sodium ion capacitor with extreme energy–power rivals lithium ion capacitors

Abstract: This is the first report of a hybrid sodium ion capacitor (NIC) with the active materials in both the anode and the cathode being derived entirely from a single precursor: peanut shells, which are a green and highly economical waste globally generated at over 6 million tons per year. The electrodes push the envelope of performance, delivering among the most promising sodiation capacity–rate capability–cycling retention combinations reported in the literature for each materials class. Hence the resultant NIC also offers a state-of-the-art cyclically stable combination of energy and power, not only in respect to previously but also as compared to Li ion capacitors (LICs). The ion adsorption cathode based on Peanut Shell Nanosheet Carbon (PSNC) displays a hierarchically porous architecture, a sheet-like morphology down to 15 nm in thickness, a surface area on par with graphene materials (up to 2396 m2 g−1) and high levels of oxygen doping (up to 13.51 wt%). Scanned from 1.5–4.2 V vs. Na/Na+ PSNC delivers a specific capacity of 161 mA h g−1 at 0.1 A g−1 and 73 mA h g−1 at 25.6 A g−1. A low surface area Peanut Shell Ordered Carbon (PSOC) is employed as an ion intercalation anode. PSOC delivers a total capacity of 315 mA h g−1 with a flat plateau of 181 mA h g−1 occurring below 0.1 V (tested at 0.1 A g−1), and is stable at 10 000 cycles (tested at 3.2 A g−1). The assembled NIC operates within a wide temperature range (0–65 °C), yielding at room temperature (by active mass) 201, 76 and 50 W h kg−1 at 285, 8500 and 16 500 W kg−1, respectively. At 1.5–3.5 V, the hybrid device achieved 72% capacity retention after 10 000 cycles tested at 6.4 A g−1, and 88% after 100 000 cycles at 51.2 A g−1.

A full genome search in multiple sclerosis

Abstract: The aetiology of multiple sclerosis (MS) is uncertain. There is strong circumstantial evidence to indicate it is an autoimmune complex trait. Risks for first degree relatives are increased some 20 fold over the general population. Twin studies have shown monozygotic concordance rates of 25-30% compared to 4% for dizygotic twins and siblings. Studies of adoptees and half sibs show that familial risk is determined by genes, but environmental factors strongly influence observed geographic differences. Studies of candidate genes have been largely unrewarding. We report a genome search using 257 microsatellite markers with average spacing of 15.2 cM in 100 sibling pairs (Table 1, data set 1 - DS1). A locus of lambda>3 was excluded from 88% of the genome. Five loci with maximum lod scores (MLS) of >1 were identified on chromosomes 2, 3, 5, 11 and X. Two additional data sets containing 44 (Table 1, DS2) and 78 sib pairs (Table 1, DS3) respectively, were used to further evaluate the HLA region on 6p21 and a locus on chromosome 5 with an MLS of 4.24. Markers within 6p21 gave MLS of 0.65 (non-significant, NS). However, D6S461, just outside the HLA region, showed significant evidence for linkage disequilibrium by the transmission disequilibrium test (TDT), in all three data sets (for DS1 chi2 = 10.8, adjusted P < 0.01)(DS2 and DS3 chi2 = 10.9, P < 0.0005), suggesting a modest susceptibility locus in this region. On chromosome 5p results from all three data sets (222 sib pairs) yielded a multipoint MLS of 1.6. The results support genetic epidemiological evidence that several genes interact epistatically to determine heritable susceptibility.

A comparative analysis of the efficiency of change metrics and static code attributes for defect prediction

Abstract: In this paper we present a comparative analysis of the predictive power of two different sets of metrics for defect prediction. We choose one set of product related and one set of process related software metrics and use them for classifying Java files of the Eclipse project as defective respective defect-free. Classification models are built using three common machine learners: logistic regression, naive Bayes, and decision trees. To allow different costs for prediction errors we perform cost-sensitive classification, which proves to be very successful: >75% percentage of correctly classified files, a recall of >80%, and a false positive rate <30%. Results indicate that for the Eclipse data, process metrics are more efficient defect predictors than code metrics.