n-3 Fatty Acids Reduce Arterial LDL-Cholesterol Delivery and Arterial Lipoprotein Lipase Levels and Lipase Distribution
Bibliographic record
Abstract
OBJECTIVE: We previously reported that saturated fat (SAT)-enriched diets increase arterial cholesteryl ester (CE) deposition, especially from LDL-selective uptake (SU), and this was associated with increased arterial lipoprotein lipase (LpL). We now question how n-3 fatty acid rich diets influence arterial cholesterol delivery and arterial LpL levels. METHODS AND RESULTS: C57BL/6 mice were fed chow or eucaloric high-fat diets enriched in SAT or fish oil (n-3) for 12 weeks, and then injected with double radiolabeled or fluorescent-labeled human LDL to separately trace LDL-CE and LDL-apoB uptake. SAT and n-3 diets increased plasma cholesterol levels similarly; n-3 diets lowered plasma triglyceride concentrations. SAT increased arterial LDL-SU with significantly higher CE infiltration into aortic media. In contrast, n-3 markedly reduced total LDL uptake and CE deposition and abolished SU with LDL localized only in aortic intima. Disparate patterns of CE deposition between diets were consistent with distribution of arterial LpL-SAT diets induced higher LpL levels throughout the aorta; n-3 diets decreased LpL levels and limited LpL expression to the aortic intima. CONCLUSIONS: n-3 rich diets decrease arterial total LDL delivery and abrogate LDL-SU in parallel with changing arterial wall LpL expression and distribution.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".