Biochemical and pharmacological activities of SSR 146977, a new potent nonpeptide tachykinin NK<sub>3</sub> receptor antagonist
Bibliographic record
Abstract
SSR 146977 is a potent and selective antagonist of the tachykinin NK3 receptor. In Chinese hamster ovary cells expressing the human tachykinin NK3 receptor, SSR 146977 inhibited the binding of radioactive neurokinin B to NK3 receptors (Ki = 0.26 nM), senktide (10 nM) induced inositol monophosphate formation (IC50 = 7.8-13 nM), and intracellular calcium mobilization (IC50 = 10 nM). It antagonized [MePhe7]neurokinin B induced contractions of guinea pig ileum (pA2 = 9.07). Senktide (30 nM) induced firing rate increase of noradrenergic neurons in the guinea pig locus coeruleus and dopaminergic neurons in the guinea pig substantia nigra was also blocked by SSR 146977 (50 and 100 nM, respectively). In vivo, in the respiratory system, SSR 146977 inhibited bronchial hyperresponsiveness to acetylcholine, bronchial microvascular permeability hypersensitivity to histamine (doses of 0.1-1 mg/kg i.p.), and cough (doses of 0.03-1 mg/kg i.p.) provoked by citric acid in guinea pigs. In the central nervous system, SSR 146977 inhibited turning behaviour (ID50 = 0.2 mg/kg i.p. and 0.4 mg/kg p.o.) and prevented the decrease of locomotor activity (10 and 30 mg/kg i.p) mediated by the stimulation of NK3 receptors in gerbils. In guinea pigs, SSR 146977 antagonized senktide-induced acetylcholine release in the hippocampus (0.3 and 1 mg/kg i.p) and norepinephrine release in the prefrontal cortex (0.3 mg/kg i.p.). It also prevented haloperidol-induced increase of the number of spontaneously active dopamine A10 neurons (1 and 3 mg/kg i.p.).
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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) | 0.002 | 0.001 |
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".