Heart rate-associated mechanical stress impairs carotid but not cerebral artery compliance in dyslipidemic atherosclerotic mice
Bibliographic record
Abstract
The cardiac cycle imposes a mechanical stress that dilates elastic carotid arteries, while shear stress largely contributes to the endothelium-dependent dilation of downstream cerebral arteries. In the presence of dyslipidemia, carotid arteries stiffen while the endothelial function declines. We reasoned that stiffening of carotid arteries would be prevented by reducing resting heart rate (HR), while improving the endothelial function would regulate cerebral artery compliance and function. Thus we treated or not 3-mo-old male atherosclerotic mice (ATX; LDLr(-/-):hApoB(+/+)) for 3 mo with the sinoatrial pacemaker current inhibitor ivabradine (IVA), the β-blocker metoprolol (METO), or subjected mice to voluntary physical training (PT). Arterial (carotid and cerebral artery) compliance and endothelium-dependent flow-mediated cerebral dilation were measured in isolated pressurized arteries. IVA and METO similarly reduced (P < 0.05) 24-h HR by ≈15%, while PT had no impact. As expected, carotid artery stiffness increased (P < 0.05) in ATX mice compared with wild-type mice, while cerebral artery stiffness decreased (P < 0.05); this paradoxical increase in cerebrovascular compliance was associated with endothelial dysfunction and an augmented metalloproteinase-9 (MMP-9) activity (P < 0.05), without changing the lipid composition of the wall. Reducing HR (IVA and METO) limited carotid artery stiffening, but plaque progression was prevented by IVA only. In contrast, IVA maintained and PT improved cerebral endothelial nitric oxide synthase-dependent flow-mediated dilation and wall compliance, and both interventions reduced MMP-9 activity (P < 0.05); METO worsened endothelial dysfunction and compliance and did not reduce MMP-9 activity. In conclusion, HR-dependent mechanical stress contributes to carotid artery wall stiffening in severely dyslipidemic mice while cerebrovascular compliance is mostly regulated by the endothelium.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".