Comparison of the effects of escitalopram and atorvastatin on diet-induced atherosclerosis in rats
Bibliographic record
Abstract
Atherosclerosis is one of the most common disorders among the elderly. Depression may be associated with the development of atherosclerosis. Thus, the aim of this study is to evaluate and compare the effects of escitalopram (a selective serotonin reuptake inhibitor) with atorvastatin (a well known antihyperlipidemic drug) on high fat diet induced atherosclerosis in rats. The results of this study showed that the administration of either escitalopram or atorvastatin for 6 weeks was associated with a significant decrease in serum levels of total cholesterol, triglycerides, low density lipoproteins, very low density lipoproteins, and serum malondialdehyde, and a significant increase in high density lipoproteins when compared with the atherosclerosis model group. Histopathological examination of the aortas from the test rats revealed significant regression of atherosclerotic changes, together with a significant decrease in vascular cell adhesion molecule-1 (VCAM-1) expression in the media of both the escitalopram group and the atorvastatin group when compared with the atherosclerosis model group. This study has shown that escitalopram reduced atherosclerotic changes, thus its use as an antidepressant in elderly patients should be considered.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".