[Nphe<sup>1</sup>]‐Nociceptin (1‐13)‐NH<sub>2</sub>, a nociceptin receptor antagonist, reverses nociceptin‐induced spatial memory impairments in the Morris water maze task in rats
Bibliographic record
Abstract
1. The present study was undertaken to investigate the effects of the novel nociceptin receptor antagonist, [Nphe(1)]-Nociceptin (1-13)-NH(2) (bilateral intrahippocampal injection, 50 nmole rat(-1)) on purported nociceptin-induced (bilateral intrahippocampal injection, 5 nmole rat(-1)) deficits in spatial learning in the rat Morris water maze task. In addition, experiments were performed in an 'open field' to investigate possible peptide-induced changes in exploratory behaviour. 2. Nociceptin significantly impaired the ability of the animal to locate the hidden platform throughout training (P<0.001 versus control group). 3. Pretreatment with [Nphe(1)]-Nociceptin (1-13)-NH(2) significantly blocked nociceptin-induced impairment of spatial learning (P<0.001 versus nociceptin group). 4. A probe trial revealed that vehicle-treated animals spent more time in the quadrant that had previously contained the hidden platform, whereas nociceptin-treated animals did not spend more time in any one quadrant. 5. Learning impairments were not attributable to non-specific deficits in motor performance or change in exploratory behaviour. 6. Taken together, our results reveal that [Nphe(1)]-Nociceptin (1-13)-NH(2) represents an effective and useful in vivo antagonist at the nociceptin receptors involved in learning and memory.
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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) | 0.001 | 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".