Orexin receptor subtype activation and locomotor behaviour in the rat
Bibliographic record
Abstract
AIM: Orexin-producing neurones, located primarily in the perifornical region of the lateral hypothalamus, project to a wide spectrum of brain sites where they influence numerous behaviours as well as modulating the neuroendocrine and autonomic responses to stress. While some of the actions of orexin appear to be mediated via the type 1 receptor, some are not, including its action on the release of one stress hormone, prolactin. We describe here the ability of orexin to increase locomotor behaviours and identify the importance of both receptor subtypes in these actions. METHODS: Rats were tested for their behavioural responses to the central activation of both the type 1 (OX(1)R) and type 2 (OX(2)R) receptor (ICV orexin A), compared to OX(2)R activation using a relatively selective OX(2)R agonist in the absence or presence of an orexin receptor antagonist that possesses highest affinity for OX(1)R. RESULTS: Increases in locomotor activity were observed, effects which were expressed by not only orexin A, which binds to both the OX(1)R and the OX(2)R receptors, but also by the relatively selective OX(2)R agonist [(Ala(11), Leu(15))-orexin B]. Furthermore, the OX(1)R selective antagonist only partially blocked the action of orexin A on most locomotor behaviours and did not block the actions of [(Ala(11), Leu(15))-orexin B]. CONCLUSION: We conclude that orexin A exerts its effects on locomotor behaviour via both the OX(1)R and OX(2)R and that agonism or antagonism of only one of these receptors for therapeutic purposes (i.e. sleep disorders) would not provide selectivity in terms of associated behavioural side effects.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".