Arterial Retention of Remnant Lipoproteins Ex Vivo Is Increased in Insulin Resistance Because of Increased Arterial Biglycan and Production of Cholesterol‐Rich Atherogenic Particles That Can Be Improved by Ezetimibe in the JCR:LA‐ <i>cp</i> Rat
Bibliographic record
Abstract
BACKGROUND: Literature supports the "response-to-retention" hypothesis-that during insulin resistance, impaired metabolism of remnant lipoproteins can contribute to accelerated cardiovascular disease progression. We used the JCR:LA-cp rat model of metabolic syndrome (MetS) to determine the extent of arterial accumulation of intestinal-derived remnants ex vivo and potential mechanisms that contribute to exacerbated cholesterol deposition in insulin resistance. METHODS AND RESULTS: Arteries from control and MetS (insulin-resistant) JCR:LA-cp rats were perfused ex vivo with Cy5-labeled remnant lipoproteins, and their arterial retention was quantified by confocal microscopy. Arterial proteoglycans were isolated from control and MetS rats at 6, 12, and 32 weeks of age. There was a significant increase in the arterial retention of remnants and in associated cholesterol accumulation in MetS rats as compared to control rats. Mechanistic studies reveal that increased cholesterol deposition is a result of greater arterial biglycan content; longer glycosaminoglycans and increased production of cholesterol-rich intestinal-derived remnants, as compared to controls. Additionally, perfusion of vessels treated with ezetimibe, alone or in combination with simvastatin, with remnants isolated from the respective treatment group reduced ex vivo arterial retention of remnant-derived cholesterol ex vivo as compared to untreated controls. CONCLUSIONS: Increased progression of atherosclerotic cardiovascular disease in MetS and type 2 diabetes mellitus might be explained in part by an increase in the arterial retention of cholesterol-rich remnants. Furthermore, ezetimibe alone or in combination treatment with simvastatin could be beneficial in ameliorating atherosclerotic cardiovascular disease in insulin resistance and MetS.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".