Altered Neuronal Nitric Oxide Synthase in the Aging Vascular System: Implications for Estrogens Therapy
Bibliographic record
Abstract
Ovarian dysfunction at any age is associated with increased cardiovascular risk in women; however, therapeutic effects of exogenous estrogens are age dependent. Estradiol (E2) activates neuronal nitric oxide synthase (nNOS) in vascular cells. Because nNOS is prone to uncoupling under unfavorable biochemical conditions (as seen in aging), E2 stimulation of nNOS may lack vascular benefits in aging. Small mesenteric arteries were isolated from female Sprague Dawley rats, 3 or 12 months old, who were ovariectomized (Ovx) and treated with placebo or E2 for 4 wk. Vascular relaxation to exogenous E2 (0.001-100 μmol/liter) ± selective nNOS inhibitor (N-propyl-l-arginine, 2 μmol/liter) or pan-NOS inhibitor [Nω-nitro-l-arginine methyl ester (l-NAME), 100 μmol/liter] was examined on wire myograph. NOS expression was measured by Western blotting in thoracic aortas, in which superoxide generation was detected as dihydroethidium (DHE) fluorescence. E2 relaxations were impaired in Ovx conditions. E2 treatment (4 wk) normalized vascular function in young rats only. Both l-N-propyl-l-arginine and l-NAME blunted E2 relaxation in young controls, but only l-NAME did so in aging controls. NOS inhibition had no effect on acute E2 relaxation in Ovx rats, regardless of age or treatment. nNOS expression was similar in all animal groups. However, nNOS inhibition increased DHE fluorescence in young controls, whereas it reduced it in aging or Ovx animals. In E2-treated animals of either age, superoxide production was NOS independent. In conclusion, nNOS contributed to vascular relaxation in young, but not aging rats, where its enzymatic function shifted toward superoxide production. Thus, nNOS dysfunction may explain a mechanism of impaired E2 signaling in aging conditions.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".