Pretreatment with the nitric oxide donor SNAP or nerve transection blocks humoral preconditioning by remote limb ischemia or intra-arterial adenosine
Bibliographic record
Abstract
We have previously shown that remote ischemic preconditioning (rIPC) by transient limb ischemia leads to the release of a circulating factor(s) that induces potent myocardial protection. Intra-arterial injection of adenosine into a limb also leads to cardioprotection, but the mechanism of its signal transduction is poorly understood. Eleven groups of rabbits received saline control or rIPC or adenosine administration with additional pretreatment with the nitric oxide (NO) synthase blocker N(G)-nitro-l-arginine methyl ester, the NO donor S-nitroso-N-acetylpenicillamine, its non-NO-donating derivative N-acetylpenicillamine, or femoral nerve section. Blood was then drawn from each animal, and the dialysate of the plasma was used to perfuse a naïve heart from an untreated donor. Infarct size was measured after 30 min of global ischemia and 120 min reperfusion. When compared with that of the control, mean infarct size was significantly smaller in groups treated with rIPC alone (P < 0.01) and intra-arterial adenosine (P < 0.01). Pretreatment with N(G)-nitro-l-arginine methyl ester or N-acetylpenicillamine did not affect the level of protection induced by rIPC (P = not significant, compared with rIPC alone) or intra-arterial adenosine (P = not significant, compared with intra-arterial adenosine alone), but prior femoral nerve transection or pretreatment with S-nitroso-N-acetylpenicillamine abolished the cardioprotective effect of intra-arterial adenosine and rIPC. Intra-arterial adenosine, like rIPC, releases a blood-borne cardioprotective factor(s) that is dependent on an intact femoral nerve and is inhibited by pretreatment with a NO donor. These results may be important when designing or assessing the results of clinical trials of adenosine or rIPC cardioprotection, where NO donors are used as part of therapy.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".