Effects of dopamine, SKF-38393 and R(-)-NPA on ATP-activated currents in rat DRG neurons
Bibliographic record
Abstract
This study aimed to investigate the effect of the activation of dopamine (DA) receptors on ATP-activated currents (IATP) in freshly isolated dorsal root ganglion (DRG) neurons of rats using whole-cell patch clamp technique in combination with intracellular dialysis. Extracellular application of DA inhibited IATP in half of the neurons tested (39/77, 50.6%), enhanced IATP in a small subset of the neurons (22/77, 28.6%), and had no effect on IATP in the rest (16/77, 20.8%). To investigate the DA receptor subtypes that mediate these modulations, the effects of R(-)-NPA, a D2 receptor agonist, and SKF-38393, a D1 receptor agonist, were examined. Preapplication of R(-)-NPA inhibited IATP in most of the cells tested (53/57, 93.0%) and had no effect in the rest (4/57, 7.0%); no potentiating effect was observed. Preapplication of SKF-38393 inhibited IATP in a majority of the cells tested (57/77, 74.0%), potentiated IATP in some cells (12/77, 15.6%), and had no effect in the remainder (8/77, 10.4%). Further study of the inhibitory effect of R(-)-NPA and SKF-38393 revealed that both of them acted in a noncompetitive manner, shifting the concentration-response curve for IATP downwards with the maximal response markedly reduced and EC50 basically unchanged; and the inhibition was independent of the holding potential. Intracellular dialysis of GDP-beta-S and H-7 abolished R(-)-NPA inhibition of IATP completely, and SKF-38393 inhibition of IATP was removed by intracellular application of H-7 but not by H-9. These results suggest that the activation of DA receptors dominantly inhibits IATP in dorsal root ganglion cells, and this inhibition may be involved in the modulation of afferent information by the diencephalon-derived DA in the primary sensory neurons.
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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) | 0.001 | 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".