Effects of OPC-14523, a combined sigma and 5-HT <sub>1a</sub> ligand, on pre- and post-synaptic 5-HT <sub>1a</sub> receptors
Bibliographic record
Abstract
OPC-14523 (OPC) is a novel compound with high affinity for sigma and 5-HT1A receptors that shows 'antidepressant-like' effects in animal models of depression. We have previously demonstrated that OPC produces an increase in 5-HT neurotransmission and a decreased response of 5-HT neurons to the acute administration of paroxetine in the DRN, an effect that appears to be mediated by OPC's 5-HT1A receptor affinity. The current study sets out to investigate more specifically the effects of OPC on 5-HT1A pre- and post-synaptic receptors, to assess whether it acts as an agonist or antagonist. Using an electrophysiological model of in vivo extracellular recordings in anaesthetized rats, the effects of OPC was assessed on pre-synaptic DRN 5-HT1A autoreceptors and post-synaptically on hippocampal 5-HT1A receptors of CA3 pyramidal neurons. OPC applied by microiontophoresis, produced a significant decrease in the firing activity of 5-HT neurons of the DRN and of quisqualate-activated CA3 pyramidal neurons of the dorsal hippocampus. The effects of OPC on 5-HT1A receptors were significantly reduced by the co-application of the 5-HT1A antagonist WAY-100635. In addition, the effects of OPC were not blocked by the injection of the sigma antagonists NE-100 or haloperidol. Therefore, OPC is acting as an agonist on both pre- and post-synaptic 5-HT1A receptors. The current findings combined with previous data on OPC suggest a pharmacological profile that warrants further investigation.
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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 | 0.000 |
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".