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- Axelsson, Magnus, et al.
(författare)
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GRB110721A : AN EXTREME PEAK ENERGY AND SIGNATURES OF THE PHOTOSPHERE
- 2012
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Ingår i: Astrophysical Journal Letters. - 2041-8205. ; 757:2
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Tidskriftsartikel (refereegranskat)abstract
- GRB110721A was observed by the Fermi Gamma-ray Space Telescope using its two instruments, the Large Area Telescope (LAT) and the Gamma-ray Burst Monitor (GBM). The burst consisted of one major emission episode which lasted for similar to 24.5 s (in the GBM) and had a peak flux of (5.7 +/- 0.2) x 10(-5) erg s(-1) cm(-2). The time-resolved emission spectrum is best modeled with a combination of a Band function and a blackbody spectrum. The peak energy of the Band component was initially 15 +/- 2 MeV, which is the highest value ever detected in a GRB. This measurement was made possible by combining GBM/BGO data with LAT Low Energy events to achieve continuous 10-100 MeV coverage. The peak energy later decreased as a power law in time with an index of -1.89 +/- 0.10. The temperature of the blackbody component also decreased, starting from similar to 80 keV, and the decay showed a significant break after similar to 2 s. The spectrum provides strong constraints on the standard synchrotron model, indicating that alternative mechanisms may give rise to the emission at these energies.
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- Palmer, M. K., et al.
(författare)
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Comparing a novel equation for calculating low-density lipoprotein cholesterol with the Friedewald equation: A VOYAGER analysis
- 2019
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Ingår i: Clinical Biochemistry. - : Elsevier BV. - 0009-9120 .- 1873-2933. ; 64, s. 24-29
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Tidskriftsartikel (refereegranskat)abstract
- Treating elevated low-density lipoprotein cholesterol (LDL-C) to risk-stratified target levels is recommended in several guidelines. Thus, accurate estimation of LDL-C is required. LDL-C is typically calculated using the Friedewald equation: (total cholesterol) - (non-high-density lipoprotein cholesterol [non-HDL-C]) - (triglycerides [TGs]/5). As the equation uses a fixed value equal to 5 as a divisor for TGs, it does not account for inter-individual variability, often resulting in underestimation of risk and potentially undertreatment. It is specifically inapplicable in patients with fasting triglycerides >= 400 mg/dL. A novel method of LDL-C calculation was derived and validated by Martin et al.: (non-HDL-C) - (triglycerides/adjustable factor). This equation uses an adjustable factor, the median TG:very-low-density lipoprotein cholesterol ratio in strata defined by levels of TG and non-HDLC, as divisor for TGs, and the adjustable factor ranging from 3 to 12 has been shown to provide more accurate estimates of LDL-C compared with the Friedewald equation using a direct assay as the gold standard. We used 70,209 baseline and on-treatment lipid values from the VOYAGER meta-analysis database to determine the difference in calculated LDL-C values using the Friedewald and novel equations. In patients with TGs < 400 mg/dL, LDL-C values calculated using the novel equation were plotted against those calculated using the Friedewald equation. The novel equation generally resulted in LDL-C values greater than the Friedewald calculation, with differences increasing with decreasing LDL-C levels; 23% of individuals who reached a LDL-C target of 70 mg/dL with the Friedewald equation did not achieve this target when the novel equation was used to calculate LDL-C; these figures were 8% and 2% for < 100 mg/dL and < 130 mg/dL targets, respectively. In patients with triglycerides >= 400 mg/dL, in whom the Friedewald equation is not valid, lipid values calculated using the novel equation were compared with those obtained by beta-quantification. Values calculated with the novel equation did not appear to be closely related with those calculated by beta-quantification in these patients. In conclusion, the novel equation provides a higher estimation of exact LDL-C values than the Friedewald equation, particularly in patients with low LDL-C levels, which may result in undertreatment of some patients whose LDL-C was calculated using the Friedewald method. However, neither may be suitable for patients with TG >= 400 mg/dL.
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- Cederstrom, S., et al.
(författare)
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New candidate genes for ST-elevation myocardial infarction
- 2020
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Ingår i: Journal of Internal Medicine. - : Wiley. - 0954-6820 .- 1365-2796. ; 287:1, s. 66-77
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Tidskriftsartikel (refereegranskat)abstract
- Background Despite extensive research in atherosclerosis, the mechanisms of coronary atherothrombosis in ST-elevation myocardial infarction (STEMI) patients are undetermined. Objectives Our aim was to find candidate genes involved in STEMI by analysing leucocyte gene expression in STEMI patients, without the influence of secondary inflammation from innate immunity, which was assumed to be a consequence rather than the cause of coronary atherothrombosis. Methods Fifty-one patients were included at coronary angiography because of STEMI. Arterial blood was sampled in the acute phase (P1), at 24-48 h (P2) and at 3 months (P3). Leucocyte RNA was isolated and gene expression analysis was performed by Affymetrix Human Transcriptome Array 2.0. By omission of up- or downregulated genes at P2, secondary changes from innate immunity were excluded. Genes differentially expressed in P1 when compared to the convalescent sample in P3 were determined as genes involved in STEMI. Results Three genes were upregulated at P1 compared to P3; ABCG1 (P = 5.81 x 10(-5)), RAB20 (P = 3.69 x 10(-5)) and TMEM2 (P = 7.75 x 10(-6)) whilst four were downregulated; ACVR1 (P = 9.01 x 10(-5)), NFATC2IP (P = 8.86 x 10(-5)), SUN1 (P = 3.87 x 10(-5)) and TTC9C (P = 7.18 x 10(-6)). These genes were also highly expressed in carotid atherosclerotic plaques. Conclusions We found seven genes involved in STEMI. The study is unique regarding the blood sampling in the acute phase and omission of secondary expressed genes from innate immunity. However, the results need to be replicated by future studies.
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- Edfors, R., et al.
(författare)
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Use of proteomics to identify biomarkers associated with chronic kidney disease and long-term outcomes in patients with myocardial infarction
- 2020
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Ingår i: Journal of Internal Medicine. - : Wiley. - 0954-6820 .- 1365-2796. ; 288:5, s. 581-592
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Tidskriftsartikel (refereegranskat)abstract
- Background Patients with chronic kidney disease (CKD) have poor outcomes following myocardial infarction (MI). We performed an untargeted examination of 175 biomarkers to identify those with the strongest association with CKD and to examine the association of those biomarkers with long-term outcomes. Methods A total of 175 different biomarkers from MI patients enrolled in the Swedish Web-System for Enhancement and Development of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies (SWEDEHEART) registry were analysed either by a multiple reaction monitoring mass spectrometry assay or by a multiplex assay (proximity extension assay). Random forests statistical models were used to assess the predictor importance of biomarkers, CKD and outcomes. Results A total of 1098 MI patients with a median estimated glomerular filtration rate of 85 mL min(-1)/1.73 m(2)were followed for a median of 3.2 years. The random forests analyses, without and with adjustment for differences in demography, comorbidities and severity of disease, identified six biomarkers (adrenomedullin, TNF receptor-1, adipocyte fatty acid-binding protein-4, TNF-related apoptosis-inducing ligand receptor 2, growth differentiation factor-15 and TNF receptor-2) to be strongly associated with CKD. All six biomarkers were also amongst the 15 strongest predictors for death, and four of them were amongst the strongest predictors of subsequent MI and heart failure hospitalization. Conclusion In patients with MI, a proteomic approach could identify six biomarkers that best predicted CKD. These biomarkers were also amongst the most important predictors of long-term outcomes. Thus, these biomarkers indicate underlying mechanisms that may contribute to the poor prognosis seen in patients with MI and CKD.
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