MicroRNAs and obesity-induced endothelial dysfunction: key paradigms in molecular therapy
Bibliographic record
Abstract
The endothelium plays a pivotal role in maintaining vascular health. Obesity is a global epidemic that has seen dramatic increases in both adult and pediatric populations. Obesity perturbs the integrity of normal endothelium, leading to endothelial dysfunction which predisposes the patient to cardiovascular diseases. MicroRNAs (miRNAs) are short, single-stranded, non-coding RNA molecules that play important roles in a variety of cellular processes such as differentiation, proliferation, apoptosis, and stress response; their alteration contributes to the development of many pathologies including obesity. Mediators of obesity-induced endothelial dysfunction include altered endothelial nitric oxide synthase (eNOS), Sirtuin 1 (SIRT1), oxidative stress, autophagy machinery and endoplasmic reticulum (ER) stress. All of these factors have been shown to be either directly or indirectly caused by gene regulatory mechanisms of miRNAs. In this review, we aim to provide a comprehensive description of the therapeutic potential of miRNAs to treat obesity-induced endothelial dysfunction. This may lead to the identification of new targets for interventions that may prevent or delay the development of obesity-related cardiovascular disease.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".