Effects of naloxone benzoylhydrazone on native and recombinant nociceptin/orphanin FQ receptors
Bibliographic record
Abstract
We have studied the effects of naloxone benzoylhydrazone (NalBzoH) at recombinant human OP4 receptors expressed in Chinese hamster ovary (CHO) cells (CHOhOP4) and native OP4 sites in isolated tissues from various species. In CHOhOP4 membranes, nociceptin (NC) and NalBzoH displaced [125I]Tyr14-NC with pKi values of 10.1 and 7.3. In the presence of 100 microM GDP, NC stimulated GTPgamma35S binding (pEC50 = 8.5). NalBzoH was ineffective but antagonized the effects of NC (pA2 = 6.9). At 5 microM GDP, there was an increase in potency (pEC50 = 9.3) and efficacy (4.3-fold) of NC. NalBzOH was a partial agonist (pEC50 = 7.0, Emax = 13% relative to NC). In CHOhOP4 cells, NC and NalBzoH inhibited cAMP formation with pEC50 and Emax values of 9.8 and 100% and 6.0 and 44%, respectively. In the rat vas deferens, NalBzoH (10 microM) did not modify electrically induced twitches but competitively antagonized the inhibitory action of NC (pA2 = 6.2). In the mouse vas deferens (mVD) and guinea pig ileum (gpI), NalBzoH inhibited twitches with pEC50 and Emax values of 7.6 and 78% and 8.5 and 77%, respectively. The effect of 3 microM NalBzoH was fully inhibited by 3 microM naloxone in mVD and 30 microM in gpI. Under these conditions, NalBzoH antagonized the actions of NC in both preparations with pA2 values of 6.3 and 6.8, respectively. Collectively, these data demonstrate that NalBzoH is a nonselective OP4 ligand with system-dependent behaviour.
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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".