Heterogeneous Vasodilator Pathways Underlying Flow Mediated Dilation are Preserved in Healthy Aging
Bibliographic record
Abstract
Blocking nitric oxide (NO) and prostaglandin (PG) formation does not uniformly reduce radial artery (RA) flow mediated dilation (FMD) in young adults. We hypothesized that aging would alter these pathways such that blocking NO and PG would reduce RA FMD in older adults (n = 10 (5 men), 65±3 y). RA FMD was measured after brachial artery infusions of saline, N(G)‐ monomethyl‐L‐arginine (L‐NMMA), and ketorolac (KETO) + L‐NMMA. Data were compared to published data in young adults (n = 16 (8 men), 28±5 y). No sex differences were observed in either age group. L‐NMMA reduced FMD in older adults (8.9±3.6 to 5.9±3.7%) although this was not statistically significant (p = 0.08) and did not differ (p = 0.74) from the reduction observed in young adults (10.0±3.8 to 7.6±4.7%; p = 0.03). Shear stimulus normalization abolished the effect of L‐NMMA in both groups. No main or interaction effects of blocking PG on FMD were observed in young or older adults (p >; 0.11). Heterogeneity was observed in dilatory responses to blockade in older adults. L‐NMMA reduced (n = 6; range = 36–123% decrease) or augmented FMD (n = 4; range = 0.4–122% increase). After PG blockade, reduced (48–103% decrease) and augmented (72–118% increase) FMD responses were observed. Contrary to our hypothesis, NO is not obligatory for RA FMD in older adults. Similar to young adults, redundant vasodilatory phenotypes exist in healthy, older humans. Funded by a HH Open Competition Grant
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) | 0.000 | 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 | 0.000 |
| 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".