Association of different lipid measures for atherogenic lipid fractions and risk of coronary events in patients receiving combination antiretroviral therapy: the Swiss HIV Cohort Study

Background: Evidence for a better performance of different highly atherogenic versus traditional lipid parameters for coronary heart disease (CHD) risk prediction is conflicting. We investigated the association of the ratios of sma11 dense low density lipoprotein(LDL)/apoplipoprotein A, aolipoprotein B/apolipoprotein A-I and total cholesterol! HDL-cholesterol and CHD events in patients on combination antiretroviral therapy (cART).Methods: Case control study nested into the Swiss HIV Cohort Study: for each cART-treated patient with a first coronary event between April 1, 2000 and July 31, 2008 (case) we selected four control patients (1) that were without coronary events until the date of the event of the index case, (2) had a plasma sample within ±30 days of the sample date of the respective case, (3) received cART and (4) were then matched for age, gender and smoking status. Lipoproteins were measured by ultracentrifugation. Conditional logistic regression models were used to estimate the independent effects of different lipid ratios and the occurrence of coronary events.Results: In total, 98 cases (19 fatal myocardial infarctions [MI] and 79 non-fatal coronary events [53 definite MIs, 15 possible MIs and 11 coronary angioplasties or bypassesJ) were matched with 392 controls. Cases were more often injecting drug users, less likely to be virologically suppressed and more often on abacavir-containing regimens. In separa te multivariable models of total cholesterol, triglycerides, HDL-cholesterol, systolic blood pressure, abdominal obesity, diabetes and family history of CHD, small dense-LDL and apolipoprotein B were each statistically significantly associated with CHD events (for 1 mg/dl increase: odds ratio [OR] 1.05, 95% CI 1.00-1.11 and 1.15, 95% CI 1.01-1.31, respectively), but the ratiosof small dense-LDLlapolipoprotein A-I (OR 1.26, 95% CI 0.95-1.67), apolipoprotein B/apolipoprotein A-I (OR 1.02, 95% CI 0.97-1.07) and HDL-cholesterol! total cholesterol (OR 0.99 95% CI 0.98-1.00) were not. Following adjustment for HIV related and cART variables these associations were weakened in each model: apolipoprotein B (OR 1.27, 95% CI 1.00-1.30), sd-LDL (OR 1.04, 95% CI 0.99-1.20), small dense-LDLlapolipoprotein A-I (OR 1.17, 95% CI 0.87-1.58), apolipoprotein B/apolipoprotein A-I (OR 1.02, 95% CI 0.97-1.07) and total cholesterolJHDL- cholesterol (OR 0.99, 95% CI 0.99-1.00).Conclusions: In patients receiving cART, small dense-LDL and apolipoprotein B showed the strongest associations with CHD events in models controlling for traditional CHD risk factors including total cholesterol and triglycerides. Adding small dense LDLlapoplipoprotein A-l, apolipoprotein B/apolipoprotein A-I and total cholesterol! HDL-cholesterol ratios did not further improve models of lipid parameters and associations of increased risk for CHD events.

BAFF-R, a newly identified TNF receptor that specifically interacts with BAFF.

B cell homeostasis has been shown to critically depend on BAFF, the B cell activation factor from the tumor necrosis factor (TNF) family. Although BAFF is already known to bind two receptors, BCMA and TACI, we have identified a third receptor for BAFF that we have termed BAFF-R. BAFF-R binding appears to be highly specific for BAFF, suggesting a unique role for this ligand-receptor interaction. Consistent with this, the BAFF-R locus is disrupted in A/WySnJ mice, which display a B cell phenotype qualitatively similar to that of the BAFF-deficient mice. Thus, BAFF-R appears to be the principal receptor for BAFF-mediated mature B cell survival.

Computation of multiple correspondence analysis, with code in R

The generalization of simple correspondence analysis, for two categorical variables, to multiple correspondence analysis where they may be three or more variables, is not straighforward, both from a mathematical and computational point of view. In this paper we detail the exact computational steps involved in performing a multiple correspondence analysis, including the special aspects of adjusting the principal inertias to correct the percentages of inertia, supplementary points and subset analysis. Furthermore, we give the algorithm for joint correspondence analysis where the cross-tabulations of all unique pairs of variables are analysed jointly. The code in the R language for every step of the computations is given, as well as the results of each computation.

Research joint ventures and optimal R&D policy with asymmetric information

When to allow Research Joint Ventures (RJVs) or not is an importantinstrument in the development of an optimal R&D policy. Theregulator, however, is unlikely to know all the relevant informationto regulate R&D optimally. The extent to which there existappropriability problems between the firms is one such variable thatis private information to the firms in the industry. In a duopolysetting we analyze the characteristics of a second-best R&D policywhere the government can either allow RJVs or not and give lump-sumsubsidies to the parties involved. The second-best R&D policy withoutsubsidies will either block some welfare improving RJVs or allow somewelfare reducing ones. With lump-sum subsidies, the second-best policytrades off the expected subsidy cost with allowing welfare decreasingRJVs or blocking welfare increasing ones.

Pääministeri R. v. Fieandt 15/3 1958

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