MiR-652-3p inhibition enhances endothelial repair and reduces atherosclerosis by promoting Cyclin D2 expression
Bibliographic record
Abstract
Background: Atherosclerosis is a hyperlipidemia-induced condition affecting the arterial wall that damages healthy endothelial cell (EC) function, leading to enhanced risk of atherothrombotic events. Certain microRNAs regulate EC dysfunction in response to hyperlipidemia and may be suitable therapeutic targets to combat atherosclerosis. Methods: miRNA expression in human ECs was analyzed under various conditions to identify key microRNAs. High-cholesterol diet (HCD)-fed Mir652 -/-Apoe -/-(Mir652 -/-) mice and matching Mir652 +/+ Apoe -/- (Mir652 +/+ ) mice were subjected to carotid injury to analyze the effects of miR-652 knockdown on endothelial repair. In silico analysis followed by in vitro and in vivo experiments were applied to identify miR-652's target gene Ccnd2 and investigate the pair's effects on ECs. miR-652-5p and miR-652-3p antagomir therapies were tested in Mir652 +/+ mice under normal and HCD diet to assess their effect on endothelial repair. Findings: miR-652-3p, which is upregulated in human and murine atherosclerotic plaques, suppresses expression of the endothelial repair gene Ccnd2, thereby enhancing atherosclerotic lesion formation. Post-denudation recovery of ECs was promoted in Mir652 -/-mice due to enhanced EC proliferation attributable to de-repression of miR-652-3p's (but not miR-652-5p's) regulation of Ccnd2 expression. Under hyperlipidemic conditions at non-predilection sites, miR-652-3p produces anti-proliferative effects in ECs, such that Mir652 -/-mice display reduced atherosclerotic progression. In contrast, neither miR-652-3p nor Ccnd2 displayed significant effects on the endothelium at predilection sites or under disturbed flow conditions. Administration of a miR-652-3p antagomir rescued the proliferation of ECs in vivo, thereby limiting atherosclerotic development. Interpretation: miR-652-3p blockade may be a potential therapeutic strategy against atherosclerosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".