Pharmacological evidence that GABA-induced relaxation of rat proximal duodenum longitudinal muscle depends on NKCC cotransporter activity and Ca<sup>2+</sup> influx
Bibliographic record
Abstract
γ-Aminobutyric acid (GABA) is the main inhibitory neurotransmitter in adult central nervous system (CNS) synapses, but it excites immature CNS neurons as well as neurons in the myenteric plexus. The present work aimed to determine whether GABA-induced nonadrenergic, noncholinergic (NANC) neuronal-mediated relaxation of the rat duodenum is dependent on the activity of Na+ K+ Cl- cotransporters (NKCC) and requires calcium influx. In the presence of guanethidine (3 µmol/L), atropine (3 µmol/L), and indomethacin (1 µmol/L), relaxations induced by GABA (100 µmol/L), KCl (5–10 mmol/L) and electrical field stimulation (1–8 Hz, 2 ms, 60 V), but not those induced by bradykinin (10–100 nmol/L) were abolished by lidocaine (300 µmol/L). However, only GABA-induced relaxations were reduced in a concentration-dependent manner by the NKCC1/2 inhibitors bumetanide (0.1–1 µmol/L) and furosemide (1–10 µmol/L). GABA-induced NANC neuronal relaxation was abolished by bicuculline (30 µmol/L) and inhibited by N-nitroarginine methyl ester (l-NAME, 300 µmol/L). The ω-conotoxin GVIA (1 µmol/L), which acts exclusively on neuronal CaV2 channels, but not on smooth muscle voltage-gated Ca2+ CaV1 channels, and nonselective blockers of these channels (verapamil 100 nmol/L and ruthenium red 10 µmol/L), reduced GABA-induced relaxations. These results showed that the activation of GABAA receptors induces NANC nitrergic neuronal relaxations in the rat duodenum, which depend on NKCC activity and CaV2 channel activation, suggesting that this phenomenon results from neuronal depolarization promoted by Cl− efflux through GABAA receptors, with subsequent Ca2+ influx and nitric oxide release.
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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) | 0.002 | 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".