Effect of GABA‐ergic mechanisms on synaptosomal NO synthesis and the nitrergic component of NANC relaxation in rat ileum
Bibliographic record
Abstract
BACKGROUND: γ-Aminobutyric acid (GABA) acts on specific neural receptors [A, B and C(Aρ)] to modulate gastrointestinal function. The precise role of GABA receptor activation in the regulation of presynaptic nitric oxide (NO) synthesis in nerve terminals is unknown. METHODS: Rat ileal nerve terminals were isolated by differential centrifugation. Nitric oxide synthesis was analysed using a L-[(3) H]arginine assay. In vitro studies were performed under non-adrenergic non-cholinergic (NANC) conditions on isolated ileal segments. KEY RESULTS: γ-Aminobutyric acid inhibited NO synthesis significantly (n = 6, P < 0.05) [(fmol mg(-1) min(-1)) control: 27.7 ± 1.5, 10(-6) mol L(-1): 19.7 ± 1.3; 10(-5) mol L(-1): 17.5 ± 3.0]. This effect was antagonized by the GABA A receptor antagonist bicuculline and the GABA C receptor antagonist (1,2,5,6-tetrahydropyridin-4-yl)methylphosphinic acid (TPMPA), but not by the GABA B receptor antagonist SCH 50911. The GABA A receptor agonist muscimol [(fmol mg(-1) min(-1)) control: 27.6 ± 1.0, 10(-6) mol L(-1): 19.1 ± 1.7, n = 5, P < 0.05] and the GABA C receptor agonist cis-4-aminocrotonic acid (CACA) [(fmol mg(-1) min(-1)) control: 29.5 ± 3.2, 10(-3) mol L(-1): 20.3 ± 2.5, n = 6, P < 0.05], mimicked the GABA-effect, whereas the GABA B agonist baclofen was ineffective. Bicuculline reversed the inhibitory effect of muscimol, TPMPA antagonized the effect of CACA. In functional experiments the GABA A and C receptor agonists reduced the NANC relaxation induced by electrical field stimulation in rat ileum by about 40%. After NOS-inhibition by Nε-nitro-L-arginine methyl ester (L-NAME) the GABA A receptor agonist had no effect, whereas the GABA C receptor agonist still showed a residual response. CONCLUSIONS & INFERENCES: γ-Aminobutyric acid inhibits neural NO synthesis in rat ileum by GABA A and GABA C(Aρ) receptor-mediated mechanisms.
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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 | 0.001 |
| 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".