Receptors subtypes involved in adenosine-mediated modulation of norepinephrine release from cardiac nerve terminals
Bibliographic record
Abstract
The objective of this study was to determine which adenosine receptor subtypes were involved in the modulation of norepinephrine release from cardiac nerve terminals. In addition, the persistence of adenosine-mediated effects was evaluated. Rat hearts attached to the stellate ganglion were isolated and perfused. The ganglion was electrically stimulated twice (S1 and S2), allowing 10 min between the stimulations. To determine adenosine receptor subtypes, selective and nonselective adenosine agonists and antagonists were infused following S1 and until the end of S2. To evaluate the persistence of adenosine-mediated effect on norepinephrine release, the stellate ganglion was stimulated a third (S3) and fourth (S4) time. Coronary effluents were collected to determine norepinephrine content. Adenosine and a selective A1 receptor agonist, CCPA, inhibited norepinephrine release by 49% and 54%, respectively. This effect was reversed by simultaneous infusion of nonspecific (8-SPT) and specific (DPCPX) A1 receptor antagonists. Selective A2A (CGS 21680) and A3 (AB-MECA) receptor agonists had no discernible effect on norepinephrine release. Similarly, adenosine A2A receptor antagonists CSC and DMPX did not alter the dose-response relation between norepinephrine release and adenosine. Finally, the inhibitory effects of adenosine on norepinephrine release did not persist 10 min subsequent to the removal of adenosine. Adenosine inhibited norepinephrine release primarily via the adenosine A1 receptor. This effect of adenosine was of short duration. Adenosine A2A and A3 receptors were either absent or functionally insignificant in the regulation of norepinephrine release in the rat heart.
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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".