Enhancement of haloperidol-induced catalepsy by nicotine: an investigation of possible mechanisms
Bibliographic record
Abstract
Nicotine has been reported to potentiate the cataleptic effect of the dopamine receptor antagonist haloperidol in rats. This effect is paradoxical, since nicotine alone tends to increase nigrostriatal dopamine release. In the present experiments, a pro-cataleptic effect of nicotine was confirmed statistically but was small and variable. Three potential mechanisms underlying this effect were investigated. (i) Desensitization of brain nicotinic receptors appears to make little if any contribution to the pro-cataleptic effect of nicotine, insofar as the latter was not mimicked by two centrally active nicotinic antagonists (mecamylamine and chlorisondamine). (ii) Depolarization inactivation resulting from combined treatment with haloperidol and nicotine does not appear to be critical, since the pro-cataleptic effect of nicotine was not enhanced by chronic haloperidol administration, a treatment designed to enhance depolarization inactivation. (iii) The slow emergence and persistence of the acute pro-cataleptic effect of nicotine suggested possible mediation by a nicotine metabolite. However, neither cotinine nor nornicotine, the principal pharmacologically-active metabolites of nicotine, exerted a significant pro-cataleptic effect. In conclusion, the pro-cataleptic effect of nicotine was weak and variable in the present study, and its mechanism remains obscure.Key words: catalepsy, nicotine, haloperidol, Tourette's Syndrome, dopamine, nornicotine.
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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".