GABA Mediates Autoreceptor Feedback Inhibition in the Rat Carotid Body Via Presynaptic GABA<sub>B</sub> Receptors and TASK‐1
Bibliographic record
Abstract
Background K+ channels exert control over neuronal excitability by regulating resting potential and input resistance. Here, we show that GABAB receptor-mediated activation of a background K+ conductance modulates transmission at rat carotid body chemosensory synapses in vitro. Carotid body chemoreceptor (type I) cells expressed GABAB(1) and GABAB(2) subunits as well as endogenous GABA. The GABAB receptor agonist baclofen activated an anandamide- and Ba2+-sensitive TASK-1-like background K+ conductance in chemoreceptor cell clusters, but was without effect on voltage-gated Ca2+ channels. Hydroxysaclofen (50 microM), 5-aminovaleric acid (100 microM) and CGP 55845 (100 nM), selective GABAB receptor blockers, potentiated the hypoxia-induced receptor potential; this effect was abolished by pre-treatment with pertussis toxin (PTX; 500 ng ml-1), an inhibitor of Gi, or by H-89 (50 microM), a selective inhibitor of protein kinase A. The protein kinase C inhibitor chelerythrine chloride (100 microM) was without effect on this potentiation. GABAB receptor blockers also caused depolarisation of type I cells in clusters, and enhanced spike discharge in spontaneously firing cells. In functional co-cultures of type I clusters and petrosal sensory neurones, GABAB receptor blockers potentiated hypoxia-induced postsynaptic chemosensory responses mediated by the fast-acting transmitters ACh and ATP. Thus GABAB receptor-mediated activation of TASK-1 or a related channel provides a presynaptic autoregulatory feedback mechanism that modulates fast synaptic transmission in the rat carotid body.
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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".