Combined use of metformin and atorvastatin attenuates atherosclerosis in rabbits fed a high-cholesterol diet
Bibliographic record
Abstract
Statins are widely used to reduce cardiovascular risk. Unfortunately, some patients still experience cardiovascular events though prescribed with high-intensity statins. Metformin, an anti-diabetic drug, was reported to possess anti-atherosclerotic effects. Therefore, the experiments were designed to evaluate whether combined use of metformin and atorvastatin can achieve additional benefits. In rabbits fed a high-cholesterol diet, we evaluated the effects of the combination therapy on atherosclerotic plaques, lipid profiles, blood glucose levels, liver and kidney functions. Effects of combination therapy on cholesterol efflux and the expression of related transporters were studied in vitro. Our results showed that the combination therapy induced a more significant decrease in atherosclerotic lesion area than atorvastatin without additional lipid-lowering effect. The combination therapy significantly increased the percentage of large high-density lipoprotein subfraction. The intravenous glucose tolerance test showed that atorvastatin-treated rabbits had an increased area under the curve for time-dependent glucose levels after a bolus injection of glucose, which was completely reversed by metformin treatment. In cultured macrophages, co-treatment with metformin and atorvastatin promoted cholesterol efflux and up-regulated expression of ATP-binding cassette transporters A1 and G1. Taken together, our results suggest that atorvastatin/metformin combination therapy may achieve additional anti-atherosclerotic benefits likely through increasing cholesterol efflux in macrophages.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".