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Search: WFRF:(Ehrenborg A)

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  • Saliba-Gustafsson, P., et al. (author)
  • Subclinical atherosclerosis and its progression are modulated by PLIN2 through a feed-forward loop between LXR and autophagy
  • 2019
  • In: Journal of Internal Medicine. - : Wiley. - 0954-6820 .- 1365-2796. ; 286:6, s. 660-675
  • Journal article (peer-reviewed)abstract
    • Background Hyperlipidaemia is a major risk factor for cardiovascular disease, and atherosclerosis is the underlying cause of both myocardial infarction and stroke. We have previously shown that the Pro251 variant of perilipin-2 reduces plasma triglycerides and may therefore be beneficial to reduce atherosclerosis development. Objective We sought to delineate putative beneficial effects of the Pro251 variant of perlipin-2 on subclinical atherosclerosis and the mechanism by which it acts. Methods A pan-European cohort of high-risk individuals where carotid intima-media thickness has been assessed was adopted. Human primary monocyte-derived macrophages were prepared from whole blood from individuals recruited by perilipin-2 genotype or from buffy coats from the Karolinska University hospital blood central. Results The Pro251 variant of perilipin-2 is associated with decreased intima-media thickness at baseline and over 30 months of follow-up. Using human primary monocyte-derived macrophages from carriers of the beneficial Pro251 variant, we show that this variant increases autophagy activity, cholesterol efflux and a controlled inflammatory response. Through extensive mechanistic studies, we demonstrate that increase in autophagy activity is accompanied with an increase in liver-X-receptor (LXR) activity and that LXR and autophagy reciprocally activate each other in a feed-forward loop, regulated by CYP27A1 and 27OH-cholesterol. Conclusions For the first time, we show that perilipin-2 affects susceptibility to human atherosclerosis through activation of autophagy and stimulation of cholesterol efflux. We demonstrate that perilipin-2 modulates levels of the LXR ligand 27OH-cholesterol and initiates a feed-forward loop where LXR and autophagy reciprocally activate each other; the mechanism by which perilipin-2 exerts its beneficial effects on subclinical atherosclerosis.
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  • Aminoff, A, et al. (author)
  • Allele-specific regulation of MTTP expression influences the risk of ischemic heart disease.
  • 2010
  • In: Journal of lipid research. - 0022-2275 .- 1539-7262. ; 51:1, s. 103-11
  • Journal article (peer-reviewed)abstract
    • Promoter polymorphisms in microsomal triglyceride transfer protein (MTTP) have been associated with decreased plasma lipids but an increased risk for ischemic heart disease (IHD), indicating that MTTP influences the susceptibility for IHD independent of plasma lipids. The objective of this study was to characterize the functional promoter polymorphism in MTTP predisposing to IHD and its underlying mechanism. Use of pyrosequencing technology revealed that presence of the minor alleles of the promoter polymorphisms -493G>T and -164T>C result in lower transcription of MTTP in vivo in the heart, liver, and macrophages. In vitro experiments indicated that the minor -164C allele mediates the lower gene expression and that C/EBP binds to the polymorphic region in an allele-specific manner. Furthermore, homozygous carriers of the -164C were found to have increased risk for IHD as shown in a case-control study including a total of 544 IHD patients and 544 healthy control subjects. We concluded that carriers of the minor -164C allele have lower expression of MTTP in the heart, mediated at least partly by the transcription factor CCAAT/enhancer binding protein, and that reduced concentration of MTTP in the myocardium may contribute to IHD upon ischemic damage.
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  • Gonzales, Ricardo A., et al. (author)
  • MVnet : automated time-resolved tracking of the mitral valve plane in CMR long-axis cine images with residual neural networks: a multi-center, multi-vendor study
  • 2021
  • In: Journal of Cardiovascular Magnetic Resonance. - : Springer Science and Business Media LLC. - 1097-6647 .- 1532-429X. ; 23, s. 1-15
  • Journal article (peer-reviewed)abstract
    • Background: Mitral annular plane systolic excursion (MAPSE) and left ventricular (LV) early diastolic velocity (e’) are key metrics of systolic and diastolic function, but not often measured by cardiovascular magnetic resonance (CMR). Its derivation is possible with manual, precise annotation of the mitral valve (MV) insertion points along the cardiac cycle in both two and four-chamber long-axis cines, but this process is highly time-consuming, laborious, and prone to errors. A fully automated, consistent, fast, and accurate method for MV plane tracking is lacking. In this study, we propose MVnet, a deep learning approach for MV point localization and tracking capable of deriving such clinical metrics comparable to human expert-level performance, and validated it in a multi-vendor, multi-center clinical population. Methods: The proposed pipeline first performs a coarse MV point annotation in a given cine accurately enough to apply an automated linear transformation task, which standardizes the size, cropping, resolution, and heart orientation, and second, tracks the MV points with high accuracy. The model was trained and evaluated on 38,854 cine images from 703 patients with diverse cardiovascular conditions, scanned on equipment from 3 main vendors, 16 centers, and 7 countries, and manually annotated by 10 observers. Agreement was assessed by the intra-class correlation coefficient (ICC) for both clinical metrics and by the distance error in the MV plane displacement. For inter-observer variability analysis, an additional pair of observers performed manual annotations in a randomly chosen set of 50 patients. Results: MVnet achieved a fast segmentation (<1 s/cine) with excellent ICCs of 0.94 (MAPSE) and 0.93 (LV e’) and a MV plane tracking error of −0.10 ± 0.97 mm. In a similar manner, the inter-observer variability analysis yielded ICCs of 0.95 and 0.89 and a tracking error of −0.15 ± 1.18 mm, respectively. Conclusion: A dual-stage deep learning approach for automated annotation of MV points for systolic and diastolic evaluation in CMR long-axis cine images was developed. The method is able to carefully track these points with high accuracy and in a timely manner. This will improve the feasibility of CMR methods which rely on valve tracking and increase their utility in a clinical setting.
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