Catechin prevents severe dyslipidemia-associated changes in wall biomechanics of cerebral arteries in LDLr<sup>−/−</sup>:hApoB<sup>+/+</sup> mice and improves cerebral blood flow
Bibliographic record
Abstract
Endothelial dysfunction and oxidative stress contribute to the atherosclerotic process that includes stiffening of large peripheral arteries. In contrast, our laboratory previously reported a paradoxical increase in cerebrovascular compliance in LDLr(-/-):hApoB(+/+) atherosclerotic (ATX) mice (7). We hypothesized that prevention of cerebral artery endothelial dysfunction with a chronic dietary antioxidant intake would normalize the changes in cerebral artery wall structure and biomechanics and prevent the decline in basal cerebral blood flow associated with atherosclerosis. Three-month-old ATX mice were treated, or not, for 3 mo with the polyphenol (+)-catechin (CAT; 30 mg·kg(-1)·day(-1)) and compared with wild-type controls. In isolated, pressurized cerebral arteries from ATX mice, CAT prevented endothelial dysfunction (deterioration of endothelium-dependent, flow-mediated dilations; P < 0.05), the inward hypertrophic structural remodeling (increase in the wall-to-lumen ratio; P < 0.05), and the rise in cerebrovascular compliance (rightward shift of the stress-strain curve measured in passive conditions, reflecting mechanical properties of the arterial wall; P < 0.05). Doppler optical coherence tomography imaging in vivo confirmed these findings, showing that cerebral compliance was higher in ATX mice and normalized by CAT (P < 0.05). CAT also prevented basal cerebral hypoperfusion in ATX mice (P < 0.05). Active remodeling of the cerebrovascular wall in ATX mice was further suggested by the increase (P < 0.05) in pro-metalloproteinase-9 activity, which was normalized by CAT. We conclude that, by preserving the endothelial function, a chronic treatment with CAT prevents the deleterious effect of severe dyslipidemia on cerebral artery wall structure and biomechanical properties, contributing to preserving resting cerebral blood flow.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".