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Sökning: WFRF:(Law Ian) > Lunds universitet

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2.
  • 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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3.
  • Abolfathi, Bela, et al. (författare)
  • The Fourteenth Data Release of the Sloan Digital Sky Survey : First Spectroscopic Data from the Extended Baryon Oscillation Spectroscopic Survey and from the Second Phase of the Apache Point Observatory Galactic Evolution Experiment
  • 2018
  • Ingår i: Astrophysical Journal Supplement Series. - : IOP Publishing Ltd. - 0067-0049 .- 1538-4365. ; 235:2
  • Tidskriftsartikel (refereegranskat)abstract
    • The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since 2014 July. This paper describes the second data release from this phase, and the 14th from SDSS overall (making this Data Release Fourteen or DR14). This release makes the data taken by SDSS-IV in its first two years of operation (2014-2016 July) public. Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey; the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data-driven machine-learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from the SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS web site (www.sdss.org) has been updated for this release and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020 and will be followed by SDSS-V.
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4.
  • Agn, Mikael, et al. (författare)
  • A modality-adaptive method for segmenting brain tumors and organs-at-risk in radiation therapy planning
  • 2019
  • Ingår i: Medical Image Analysis. - : Elsevier BV. - 1361-8415. ; 54, s. 220-237
  • Tidskriftsartikel (refereegranskat)abstract
    • In this paper we present a method for simultaneously segmenting brain tumors and an extensive set of organs-at-risk for radiation therapy planning of glioblastomas. The method combines a contrast-adaptive generative model for whole-brain segmentation with a new spatial regularization model of tumor shape using convolutional restricted Boltzmann machines. We demonstrate experimentally that the method is able to adapt to image acquisitions that differ substantially from any available training data, ensuring its applicability across treatment sites; that its tumor segmentation accuracy is comparable to that of the current state of the art; and that it captures most organs-at-risk sufficiently well for radiation therapy planning purposes. The proposed method may be a valuable step towards automating the delineation of brain tumors and organs-at-risk in glioblastoma patients undergoing radiation therapy.
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5.
  • Lundemann, Michael, et al. (författare)
  • Feasibility of multi-parametric PET and MRI for prediction of tumour recurrence in patients with glioblastoma
  • 2019
  • Ingår i: European Journal of Nuclear Medicine and Molecular Imaging. - : Springer Science and Business Media LLC. - 1619-7070 .- 1619-7089. ; 46:3, s. 603-613
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Recurrence in glioblastoma patients often occur close to the original tumour and indicates that the current treatment is inadequate for local tumour control. In this study, we explored the feasibility of using multi-modality imaging at the time of radiotherapy planning. Specifically, we aimed to identify parameters from pre-treatment PET and MRI with potential to predict tumour recurrence. Materials and methods: Sixteen patients were prospectively recruited and treated according to established guidelines. Multi-parametric imaging with 18 F-FET PET/CT and 18 F-FDG PET/MR including diffusion and dynamic contrast enhanced perfusion MRI were performed before radiotherapy. Correlations between imaging parameters were calculated. Imaging was related to the voxel-wise outcome at the time of tumour recurrence. Within the radiotherapy target, median differences of imaging parameters in recurring and non-recurring voxels were calculated for contrast-enhancing lesion (CEL), non-enhancing lesion (NEL), and normal appearing grey and white matter. Logistic regression models were created to predict the patient-specific probability of recurrence. The most important parameters were identified using standardized model coefficients. Results: Significant median differences between recurring and non-recurring voxels were observed for FDG, FET, fractional anisotropy, mean diffusivity, mean transit time, extra-vascular, extra-cellular blood volume and permeability derived from scans prior to chemo-radiotherapy. Tissue-specific patterns of voxel-wise correlations were observed. The most pronounced correlations were observed for 18 F-FDG- and 18 F-FET-uptake in CEL and NEL. Voxel-wise modelling of recurrence probability resulted in area under the receiver operating characteristic curve of 0.77 from scans prior to therapy. Overall, FET proved to be the most important parameter for recurrence prediction. Conclusion: Multi-parametric imaging before radiotherapy is feasible and significant differences in imaging parameters between recurring and non-recurring voxels were observed. Combining parameters in a logistic regression model enabled patient-specific maps of recurrence probability, where 18 F-FET proved to be most important. This strategy could enable risk-adapted radiotherapy planning.
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6.
  • Munck af Rosenschöld, Per, et al. (författare)
  • Impact of [18F]-fluoro-ethyl-tyrosine PET imaging on target definition for radiation therapy of high-grade glioma.
  • 2015
  • Ingår i: Neuro-Oncology. - : Oxford University Press (OUP). - 1523-5866 .- 1522-8517. ; 17:5, s. 757-763
  • Tidskriftsartikel (refereegranskat)abstract
    • We sought to assess the impact of amino-acid (18)F-fluoro-ethyl-tyrosine (FET) positron emission tomography (PET) on the volumetric target definition for radiation therapy of high-grade glioma versus the current standard using MRI alone. Specifically, we investigated the influence of tumor grade, MR-defined tumor volume, and the extent of surgical resection on PET positivity.
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7.
  • Vandenberghe, Rik, et al. (författare)
  • F-18-Flutemetamol Amyloid Imaging in Alzheimer Disease and Mild Cognitive Impairment A Phase 2 Trial
  • 2010
  • Ingår i: Annals of Neurology. - : Wiley. - 1531-8249 .- 0364-5134. ; 68:3, s. 319-329
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective: The most widely studied positron emission tomography ligand for in vivo P-amyloid imaging is C-11-Pittsburgh compound B (C-11-PIB). Its availability, however, is limited by the need for an on-site cyclotron. Validation of the F-18-labeled PIB derivative F-18-flutemetamol could significantly enhance access to this novel technology. Methods: Twenty-seven patients with early-stage clinically probable Alzheimer disease (AD), 20 with amnestic mild cognitive impairment (MCI), and 15 cognitively intact healthy volunteers (HVs) above and 10 HVs below 55 years of age participated. The primary endpoint was the efficacy of blinded visual assessments of F-18-flutemetamol scans in assigning subjects to a raised versus normal uptake category, with clinical diagnosis as the standard of truth (SOT). As secondary objectives, we determined the correlation between the regional standardized uptake value ratios (SUVRs) for F-18-flutemetamol and its parent molecule C-11-PIB in 20 of the AD subjects and 20 of the MCI patients. We also determined test-retest variability of F-18-flutemetamol SUVRs in 5 of the AD subjects. Results: Blinded visual assessments of F-18-flutemetamol scans assigned 25 of 27 scans from AD subjects and 1 of 15 scans from the elderly HVs to the raised category, corresponding to a sensitivity of 93.1% and a specificity of 93.3% against the SOT. Correlation coefficients between cortical F-18-flutemetamol SUVRs and C-11-PIB SUVRs ranged from 0.89 to 0.92. Test-retest variabilities of regional SUVRs were 1 to 4%. Interpretation: F-18-Flutemetamol performs similarly to the C-11-PIB parent molecule within the same subjects and provides high test-retest replicability and potentially much wider accessibility for clinical and research use. ANN NEUROL 2010;68:319-329
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