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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".