Sustained differential effects of a transient antioxidant diet and voluntary exercise training on vascular functions in aging mice
Bibliographic record
Abstract
A healthy diet and regular exercise delay cardiovascular diseases in aging, but little is known about the mechanisms. We tested the effects of an early transient antioxidant diet and voluntary exercise on the vascular function of aging mice. One month old C57/Bl6 mice were split into 3 groups: one was supplemented with the antioxidant catechin (30mg/kg/d; CAT), a second was given access to an exercise wheel (EX) and a third remained sedentary (S), all until 9 months (9m). Mice were then aged for another 3 months in sedentary conditions with no treatment (12m). Femoral artery reactivity and compliance were assessed in a pressure myograph (80 mm Hg). At 9m, arterial compliance, represented by the Young's elastic modulus (β), did not differ between S (0.08±0.01) and CAT (0.08±0.01) mice, while it was greater in the EX group (0.05±0.01, p<0.05); 12m mice retained their elastic properties except for the EX group (0.07±0.01, p<0.05). The wall media‐tolumen ratio was similar in all groups. Endothelium‐dependent dilations to acetylcholine were similar in all groups at 9 and 12m. This dilatory response was, however, reduced by 60% (p<0.05) after inhibition of NO production in S mice, but not in the other groups at both ages. In conclusion, both CAT and EX improved vascular endothelial function by preserving NO‐independent vasodilator mechanisms, while only EX improved arterial compliance. Supported by CIHR MOP14496 .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.001 |
| 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".