Cholesteryl Ester Transfer Protein (CETP) Expression Protects Against Diet Induced Atherosclerosis in SR-BI Deficient Mice
Bibliographic record
Abstract
OBJECTIVE: To determine whether expression of the human CETP transgene protects against diet-induced atherosclerosis in SR-BI deficient mice. METHODS AND RESULTS: SR-BI deficient (-/-) mice were crossed with CETP transgenic (CETPtg) mice to produce a colony of SR-BI(-/-) x CETPtg mice in a C57Bl/6 background. Age and sex matched groups of genetically modified and wild-type C57Bl/6 mice were fed a high fat, high cholesterol diet for 22 weeks. In both wild-type and SR-BI(-/-) mice, expression of the CETP transgene reduced the cholesterol content and increased the density of lipoprotein particles in the HDL density range. In SR-BI(-/-) x CETPtg mice, CETP activity inversely correlated with total plasma cholesterol levels and shifted the buoyant HDL typical of SR-BI deficiency toward a more normal density HDL particle. Atherosclerosis at the level of the aortic arch was evident in both male and female SR-BI deficient mice but occurred to a greater extent in the females. Expression of CETP markedly attenuated the development of atherosclerosis in SR-BI deficient mice fed an atherogenic diet (P<0.003). CONCLUSIONS: Expression of the human CETP transgene protects SR-BI deficient mice from atherosclerosis, consistent with a role for CETP in remodeling HDL and providing an alternative pathway for the selective uptake of HDL-CE by the liver.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".