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Träfflista för sökning "(WFRF:(Luo L.)) srt2:(2015-2019) hsvcat:3 srt2:(2015)"

Sökning: (WFRF:(Luo L.)) srt2:(2015-2019) hsvcat:3 > (2015)

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1.
  • Freitag, Daniel F., et al. (författare)
  • Cardiometabolic effects of genetic upregulation of the interleukin 1 receptor antagonist: a Mendelian randomisation analysis
  • 2015
  • Ingår i: The Lancet Diabetes & Endocrinology. - 2213-8595. ; 3:4, s. 243-253
  • Tidskriftsartikel (refereegranskat)abstract
    • Background To investigate potential cardiovascular and other effects of long-term pharmacological interleukin 1 (IL-1) inhibition, we studied genetic variants that produce inhibition of IL-1, a master regulator of inflammation. Methods We created a genetic score combining the effects of alleles of two common variants (rs6743376 and rs1542176) that are located upstream of IL1RN, the gene encoding the IL-1 receptor antagonist (IL-1Ra; an endogenous inhibitor of both IL-1 alpha and IL-1 beta); both alleles increase soluble IL-1Ra protein concentration. We compared effects on inflammation biomarkers of this genetic score with those of anakinra, the recombinant form of IL-1Ra, which has previously been studied in randomised trials of rheumatoid arthritis and other inflammatory disorders. In primary analyses, we investigated the score in relation to rheumatoid arthritis and four cardiometabolic diseases (type 2 diabetes, coronary heart disease, ischaemic stroke, and abdominal aortic aneurysm; 453 411 total participants). In exploratory analyses, we studied the relation of the score to many disease traits and to 24 other disorders of proposed relevance to IL-1 signalling (746 171 total participants). Findings For each IL1RN minor allele inherited, serum concentrations of IL-1Ra increased by 0.22 SD (95% CI 0.18-0.25; 12.5%; p=9.3 x 10(-33)), concentrations of interleukin 6 decreased by 0.02 SD (-0.04 to -0.01; -1,7%; p=3.5 x 10(-3)), and concentrations of C-reactive protein decreased by 0.03 SD (-0.04 to -0.02; -3.4%; p=7.7 x 10(-14)). We noted the effects of the genetic score on these inflammation biomarkers to be directionally concordant with those of anakinra. The allele count of the genetic score had roughly log-linear, dose-dependent associations with both IL-1Ra concentration and risk of coronary heart disease. For people who carried four IL-1Ra-raising alleles, the odds ratio for coronary heart disease was 1.15 (1.08-1.22; p=1.8 x 10(-6)) compared with people who carried no IL-1Ra-raising alleles; the per-allele odds ratio for coronary heart disease was 1.03 (1.02-1.04; p=3.9 x 10(-10)). Perallele odds ratios were 0.97 (0.95-0.99; p=9.9 x 10(-4)) for rheumatoid arthritis, 0.99 (0.97-1.01; p=0.47) for type 2 diabetes, 1.00 (0.98-1.02; p=0.92) for ischaemic stroke, and 1.08 (1.04-1.12; p=1.8 x 10(-5)) for abdominal aortic aneurysm. In exploratory analyses, we observed per-allele increases in concentrations of proatherogenic lipids, including LDL-cholesterol, but no clear evidence of association for blood pressure, glycaemic traits, or any of the 24 other disorders studied. Modelling suggested that the observed increase in LDL-cholesterol could account for about a third of the association observed between the genetic score and increased coronary risk. Interpretation Human genetic data suggest that long-term dual IL-1 alpha/beta inhibition could increase cardiovascular risk and, conversely, reduce the risk of development of rheumatoid arthritis. The cardiovascular risk might, in part, be mediated through an increase in proatherogenic lipid concentrations. Copyright (C) The Interleukin 1 Genetics Consortium. Open Access article distributed under the terms of CC-BY-NC-ND.
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2.
  • Kristan, Matej, et al. (författare)
  • The Visual Object Tracking VOT2015 challenge results
  • 2015
  • Ingår i: Proceedings 2015 IEEE International Conference on Computer Vision Workshops ICCVW 2015. - : IEEE. - 9780769557205 ; , s. 564-586
  • Konferensbidrag (refereegranskat)abstract
    • The Visual Object Tracking challenge 2015, VOT2015, aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 62 trackers are presented. The number of tested trackers makes VOT 2015 the largest benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the appendix. Features of the VOT2015 challenge that go beyond its VOT2014 predecessor are: (i) a new VOT2015 dataset twice as large as in VOT2014 with full annotation of targets by rotated bounding boxes and per-frame attribute, (ii) extensions of the VOT2014 evaluation methodology by introduction of a new performance measure. The dataset, the evaluation kit as well as the results are publicly available at the challenge website(1).
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3.
  • Yu, Xue Qin, et al. (författare)
  • Prostate cancer prevalence in New South Wales Australia : A population-based study
  • 2015
  • Ingår i: Cancer Epidemiology. - : Elsevier BV. - 1877-7821 .- 1877-783X. ; 39:1, s. 29-36
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Information on the current and future numbers of Australian men living with prostate cancer is limited. We describe a method for estimating complete prevalence of prostate cancer to provide a measure of the burden of prostate cancer in Australia. Methods: Prostate cancer data from the New South Wales (NSW) Central Cancer Registry were used with PIAMOD (Prevalence and Incidence Analysis MODel) software to estimate future prostate cancer prevalence in NSW. We first fitted parametric incidence and survival models then used the modelled incidence and survival estimates to calculate complete prevalence. The estimated and projected prevalence incorporate past observed trends and take into account different assumptions about future survival trends. These models were validated against observed prevalence from the counting method. Results: Based on data for 1996-2007, the number of men living with prostate cancer in NSW was estimated to rise by 59% to 73%, from 38,322 in 2007 to 60,910-66,160 in 2017. The increasing incidence rates and the ageing population were the major contributors to this estimated increase. Validation suggested that these projections were reasonable, as the estimated prevalence in 1996-2007 was in good agreement with the corresponding prevalence calculated using the direct counting method, and the incidence models were supported by the recent data on prostate-specific antigen testing. Conclusions: As the number of men living with prostate cancer is expected to increase dramatically in the next decade in Australia, representing a significant challenge to the health system, careful planning and development of a healthcare system able to respond to this increased demand is required. These projections are useful for addressing the challenge in meeting the cancer care needs of men with prostate cancer.
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