University of Iceland

About: University of Iceland is a education organization based out in Reykjavik, Suðurnes, Iceland. It is known for research contribution in the topics: Population & Genome-wide association study. The organization has 5423 authors who have published 16199 publications receiving 694762 citations. The organization is also known as: Háskóli Íslands.

Swift Identification of Dark Gamma-Ray Bursts

Abstract: We present an optical flux vs. X-ray flux diagram for all known gamma-ray bursts (GRBs) for which an X-ray afterglow has been detected. We propose an operational definition of dark bursts as those bursts that are optically subluminous with respect to the fireball model, i.e., which have an optical-to-X-ray spectral index beta_OX < 0.5. Out of a sample of 52 GRBs we identify 5 dark bursts. The definition and diagram serve as a simple and quick diagnostic tool for identifying dark GRBs based on limited information, particularly useful for early and objective identification of dark GRBs observed with the Swift satellite.

Objective measurements of daily physical activity patterns and sedentary behaviour in older adults: Age, Gene/Environment Susceptibility-Reykjavik Study

Abstract: Background: objectively measured population physical activity (PA) data from older persons is lacking. The aim of this study was to describe free-living PA patterns and sedentary behaviours in Icelandic older men and women using accelerometer. Methods: from April 2009 to June 2010, 579 AGESII-study participants aged 73–98 years wore an accelerometer (Actigraph GT3X) at the right hip for one complete week in the free-living settings. Results: in all subjects, sedentary time was the largest component of the total wear time, 75%, followed by low-light PA, 21%. Moderate-vigorous PA (MVPA) was <1%. Men had slightly higher average total PA (counts × day−1) than women. The women spent more time in low-light PA but less time in sedentary PA and MVPA compared with men (P < 0.001). In persons <75 years of age, 60% of men and 34% of women had at least one bout ≥10 min of MVPA, which decreased with age, with only 25% of men and 9% of women 85 years and older reaching this. Conclusion: sedentary time is high in this Icelandic cohort, which has high life-expectancy and is living north of 60° northern latitude.

Pneumococcal Capsular Switching: A Historical Perspective

Abstract: Background.Changes in serotype prevalence among pneumococcal populations result from both serotype replacement and serotype (capsular) switching. Temporal changes in serotype distributions are well documented, but the contribution of capsular switching to such changes is unknown. Furthermore, it is unclear to what extent vaccine-induced selective pressures drive capsular switching. Methods.Serotype and multilocus sequence typing data for 426 pneumococci dated from 1937 through 2007 were analyzed. Whole-genome sequence data for a subset of isolates were used to investigate capsular switching events. Results.We identified 36 independent capsular switch events, 18 of which were explored in detail with whole-genome sequence data. Recombination fragment lengths were estimated for 11 events and ranged from approximately 19.0 kb to ≥58.2 kb. Two events took place no later than 1960, and the imported DNA included the capsular locus and the nearby penicillin-binding protein genes pbp2x and pbp1a. Conclusions.Capsular switching has been a regular occurrence among pneumococcal populations throughout the past 7 decades. Recombination of large DNA fragments (>30 kb), sometimes including the capsular locus and penicillin-binding protein genes, predated both vaccine introduction and widespread antibiotic use. This type of recombination has likely been an intrinsic feature throughout the history of pneumococcal evolution.

Markers of dysglycaemia and risk of coronary heart disease in people without diabetes: Reykjavik prospective study and systematic review.

Abstract: Background: Associations between circulating markers of dysglycaemia and coronary heart disease (CHD) risk in people without diabetes have not been reliably characterised. We report new data from a prospective study and a systematic review to help quantify these associations. Methods and Findings: Fasting and post-load glucose levels were measured in 18,569 participants in the population-based Reykjavik study, yielding 4,664 incident CHD outcomes during 23.5 y of mean follow-up. In people with no known history of diabetes at the baseline survey, the hazard ratio (HR) for CHD, adjusted for several conventional risk factors, was 2.37 (95% CI 1.79–3.14) in individuals with fasting glucose $7.0 mmol/l compared to those ,7 mmol/l. At fasting glucose values below 7 mmol/l, adjusted HRs were 0.95 (0.89–1.01) per 1 mmol/l higher fasting glucose and 1.03 (1.01–1.05) per 1 mmol/l higher post-load glucose. HRs for CHD risk were generally modest and nonsignificant across tenths of glucose values below 7 mmol/l. We did a meta-analysis of 26 additional relevant prospective studies identified in a systematic review of Western cohort studies that recorded fasting glucose, post-load glucose, or glycated haemoglobin (HbA1c) levels. In this combined analysis, in which participants with a self-reported history of diabetes and/or fasting blood glucose $7 mmol/l at baseline were excluded, relative risks for CHD, adjusted for several conventional risk factors, were: 1.06 (1.00–1.12) per 1 mmol/l higher fasting glucose (23 cohorts, 10,808 cases, 255,171 participants); 1.05 (1.03–1.07) per 1 mmol/l higher post-load glucose (15 cohorts, 12,652 cases, 102,382 participants); and 1.20 (1.10–1.31) per 1% higher HbA1c (9 cohorts, 1639 cases, 49,099 participants). Conclusions: In the Reykjavik Study and a meta-analysis of other Western prospective studies, fasting and post-load glucose levels were modestly associated with CHD risk in people without diabetes. The meta-analysis suggested a somewhat stronger association between HbA1c levels and CHD risk. Please see later in the article for the Editors’ Summary.

Changing Arctic Snow Cover: A Review of Recent Developments and Assessment of Future Needs for Observations, Modelling, and Impacts

Abstract: Snow is a critically important and rapidly changing feature of the Arctic. However, snow-cover and snowpack conditions change through time pose challenges for measuring and prediction of snow. Plausible scenarios of how Arctic snow cover will respond to changing Arctic climate are important for impact assessments and adaptation strategies. Although much progress has been made in understanding and predicting snow-cover changes and their multiple consequences, many uncertainties remain. In this paper, we review advances in snow monitoring and modelling, and the impact of snow changes on ecosystems and society in Arctic regions. Interdisciplinary activities are required to resolve the current limitations on measuring and modelling snow characteristics through the cold season and at different spatial scales to assure human well-being, economic stability, and improve the ability to predict manage and adapt to natural hazards in the Arctic region.