Effect of DETA-NONOate and papaverine on vasodilation of human internal mammary artery
Bibliographic record
Abstract
In this study, the relaxatory effect of DETA-NONOate is compared with that of papaverine on isolated human internal mammary artery. We investigated the inhibitory effects of DETA-NONOate and papaverine on phenylephrine-induced contractile response in internal mammary artery segments. The internal mammary artery segments, taken from methodologically matched patients who underwent coronary artery bypass grafting, were prepared, placed in an organ bath, and contracted with phenylephrine (10(-9) to 10(-4) mol/L) to investigate their relaxatory response to DETA-NONOate or papaverine. Phenylephrine dose-response contraction was obtained after 1, 2, and 3 h in segments pre-incubated with DETA-NONOate or papaverine for 30 min. The EC50 that presented for internal mammary artery segments incubated with DETA-NONOate was 3.523 ± 1.2696 × 10(-7) mol/L, and for papaverine was 3.467 ± 1.2145 × 10(-6) mol/L. In segments pre-incubated with DETA-NONOate, the contractile response to phenylephrine was suppressed in the first 2 h post-incubation, compared with control responsive groups (p < 0.05), but this inhibition was revoked after 3 h post-incubation. We showed that DETA-NONOate has a more significant relaxative effect by comparison with papaverine; moreover, continuous and long-lasting nitric oxide production by DETA-NONOate might be of great importance for the outcome from coronary artery bypass grafting, when internal mammary artery is used as a conduit.
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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) | 0.000 | 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".