Effect of atorvastatin on plasma apoE metabolism in patients with combined hyperlipidemia
Bibliographic record
Abstract
Atorvastatin, a synthetic HMG-CoA reductase inhibitor used for the treatment of hyperlipidemia and the prevention of coronary artery disease, significantly lowers plasma cholesterol and low-density lipoprotein cholesterol (LDL-C) levels. It also reduces total plasma triglyceride and apoE concentrations. In view of the direct involvement of apoE in the pathogenesis of atherosclerosis, we have investigated the effect of atorvastatin treatment (40 mg/day) on in vivo rates of plasma apoE production and catabolism in six patients with combined hyperlipidemia using a primed constant infusion of deuterated leucine. Atorvastatin treatment resulted in a significant decrease (i.e., 30-37%) in levels of total triglyceride, cholesterol, LDL-C, and apoB in all six patients. Total plasma apoE concentration was reduced from 7.4 +/- 0.9 to 4.3 +/- 0.2 mg/dl (-38 +/- 8%, P < 0.05), predominantly due to a decrease in VLDL apoE (3.4 +/- 0.8 vs. 1.7 +/- 0.2 mg/dl; -42 +/- 11%) and IDL/LDL apoE (1.9 +/- 0.3 vs. 0.8 +/- 0.1 mg/dl; -57 +/- 6%). Total plasma lipoprotein apoE transport (i.e., production) was significantly reduced from 4.67 +/- 0.39 to 3.04 +/- 0.51 mg/kg/day (-34 +/- 10%, P < 0.05) and VLDL apoE transport was reduced from 3.82 +/- 0.67 to 2.26 +/- 0.42 mg/kg/day (-36 +/- 10%, P = 0.057). Plasma and VLDL apoE residence times and HDL apoE kinetic parameters were not significantly affected by drug treatment. Percentage decreases in VLDL apoE concentration and VLDL apoE production were significantly correlated with drug-induced reductions in VLDL triglyceride concentration (r = 0.99, P < 0.001; r = 0.88, P < 0.05, respectively, n = 6). Our results demonstrate that atorvastatin causes a pronounced decrease in total plasma and VLDL apoE concentrations and a significant decrease in plasma and VLDL apoE rates of production in patients with combined hyperlipidemia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".