Resilience of the Internal Mammary Artery to Atherogenesis: Shifting From Risk to Resistance to Address Unmet Needs
Bibliographic record
Abstract
Fueled by the global surge in aging, atherosclerotic cardiovascular disease reached pandemic dimensions putting affected individuals at enhanced risk of myocardial infarction, stroke, and premature death. Atherosclerosis is a systemic disease driven by a wide spectrum of factors, including cholesterol, pressure, and disturbed flow. Although all arterial beds encounter a similar atherogenic milieu, the development of atheromatous lesions occurs discontinuously across the vascular system. Indeed, the internal mammary artery possesses unique biological properties that confer protection to intimal growth and atherosclerotic plaque formation, thus making it a conduit of choice for coronary artery bypass grafting. Its endothelium abundantly expresses nitric oxide synthase and shows accentuated nitric oxide release, while its vascular smooth muscle cells exhibit reduced tissue factor expression, high tPA (tissue-type plasminogen activator) production and blunted migration and proliferation, which may collectively mitigate intimal thickening and ultimately the evolution of atheromatous plaques. We aim here to provide insights into the anatomy, physiology, cellular, and molecular aspects of the internal mammary artery thereby elucidating its remarkable resistance to atherogenesis. We propose a change in perspective from risk to resilience to decipher mechanisms of atheroresistance and eventually identification of novel therapeutic targets presently not addressed by currently available remedies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".