Adenosine inhibits calcium channel currents via A<sub>1</sub> receptors on salamander retinal ganglion cells in a mini‐slice preparation
Bibliographic record
Abstract
The effects of adenosine on high-voltage-activated calcium channel currents in tiger salamander retinal ganglion cells were investigated in a mini-slice preparation. Adenosine produced a concentration-dependent decrease in the amplitude of calcium channel current with a maximum inhibition of 26%. The effects of adenosine on calcium channel current were both time- and voltage-dependent. In cells dialyzed with GTP-gamma-s, adenosine caused a sustained and irreversible inhibition of calcium channel current, suggesting involvement of a GTP-binding protein. The inhibitory effect of adenosine on calcium channel current was blocked by the A1 antagonist 8-cyclopentyltheophylline (DPCPX, 1-10 microm), but not by the A2 antagonist 3-7-dimethyl-1-propargylxanthine (DMPX, 10 microm), and was mimicked by the A1 agonist N6-cyclohexyladenosine (CHA, 1 microm) but not by the A2 agonist 5'-(N-cyclopropyl) carbox-amidoadenosine (CPCA, 1 microm). Adenosine's inhibition of calcium channel current was not affected by the L-type calcium channel blocker nifedipine (5 microm). However, adenosine's inhibition of calcium channel current was reduced to approximately 10% after application of omega-conotoxin GVIA (1 microm), suggesting that adenosine inhibits N-type calcium channels. These results show that adenosine acts on an A1 adenosine receptor subtype via a G protein-coupled pathway to inhibit the component of calcium channel current carried in N-type calcium channels.
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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 | 0.001 |
| 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".