The Susceptibility to Diet-Induced Atherosclerosis Is Exacerbated with Aging in C57B1/6 Mice
Bibliographic record
Abstract
The anti-atherogenic activity of HDL is mainly due to their capacity to mediate reverse cholesterol transport (RCT). However, it is not clear to what extent this activity is affected by aging or pro-atherogenic conditions. Three and 24-month-old C57Bl/6 mice were fed an atherogenic diet (high fat, high cholesterol) for 12 weeks. The aged mice displayed a significant reduction in the capacity of HDL to mediate RCT (29.03%, p < 0.0006). Interestingly, the atherogenic diet significantly stimulated the RCT process in both young and aged mice (241% and 201%, respectively, p < 0.01). However, despite this, significant amounts of cholesterol accumulated in the aortas of mice fed an atherogenic diet as compared to regular chow. The accumulation of cholesterol was more marked in the aortas of aged mice (110% increase, p < 0.002). ABCA1 and ABCG1 protein expression on macrophages decreased significantly (52 to 37% reduction, p < 0.002), whereas their expression on hepatic cells increased significantly (up to 590% for ABCA1 and 116% for ABCG1, p < 0.002). On the other hand, SR-BI protein expression on hepatic cells decreased significantly (42.85%, p < 0.0001). ABCG5, ABCG8, and CYP7a protein expression on hepatic cells was also higher in mice fed an atherogenic diet. The increase was age-dependent for both ABCG5 and ABCG8. Our results suggest that the susceptibility to diet-induced atherosclerosis is exacerbated with aging and is a consequence of the dysregulation of the expression levels of membrane cholesterol transporters.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".