Effect of Ezetimibe on the In Vivo Kinetics of ApoB-48 and ApoB-100 in Men With Primary Hypercholesterolemia
Bibliographic record
Abstract
OBJECTIVE: To examine the impact of ezetimibe, a selective inhibitor of intestinal cholesterol absorption, on the in vivo kinetics of apolipoproteins (apo) B-48 and B-100 in humans. METHODS AND RESULTS: Kinetics of triglyceride-rich lipoprotein (TRL) apoB-48 and very-low-density lipoprotein (VLDL), intermediate-density lipoprotein (IDL), and low-density lipoprotein (LDL) apoB-100 labeled with a stable isotope were assessed at baseline and at the end of 8 weeks of treatment with 10 mg/d of ezetimibe in 8 men with moderate primary hypercholesterolemia. Data were fit to a multicompartmental model using SAAMII to calculate fractional catabolic rate (FCR) and production rate (PR). Ezetimibe significantly decreased total and LDL cholesterol concentrations by -14.5% and -22.0% (P=0.004), respectively, with no significant change in plasma triglyceride and high-density lipoprotein (HDL) cholesterol levels. Ezetimibe had no significant effect on TRL apoB-48 kinetics and pool size (PS). However, VLDL and IDL apoB-100 FCRs were significantly increased (+31.2%, P=0.02 and +20.8%, P=0.04, respectively) with a concomitant elevation of VLDL apoB-100 PR (+20.9%, P=0.04). Furthermore, LDL apoB-100 PS was significantly reduced by -23.2% (P=0.004), caused by a significant increase in FCR of this lipoprotein fraction (+24.0%, P=0.04). CONCLUSIONS: These results indicate that reduction of plasma LDL cholesterol concentration after treatment with ezetimibe is associated with an increase in FCR of apoB-100-containing lipoproteins.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".