Involvement of Cholinergic System in Hyperactivity in Dopamine-Deficient Mice
Bibliographic record
Abstract
Dopaminergic systems have been known to be involved in the regulation of locomotor activity and development of psychosis. However, the observations that some Parkinson's disease patients can move effectively under appropriate conditions despite low dopamine levels (eg, kinesia paradoxia) and that several psychotic symptoms are typical antipsychotic resistant and atypical antipsychotic sensitive indicate that other systems beyond the dopaminergic system may also affect locomotor activity and psychosis. The present study showed that dopamine-deficient (DD) mice, which had received daily L-DOPA injections, could move effectively and even be hyperactive 72 h after the last L-DOPA injection when dopamine was almost completely depleted. Such hyperactivity was ameliorated by clozapine but not haloperidol or ziprasidone. Among multiple actions of clozapine, muscarinic acetylcholine (ACh) activation markedly reduced locomotor activity in DD mice. Furthermore, the expression of choline acetyltransferase, an ACh synthase, was reduced and extracellular ACh levels were significantly reduced in DD mice. These results suggest that the cholinergic system, in addition to the dopaminergic system, may be involved in motor control, including hyperactivity and psychosis. The present findings provide additional evidence that the cholinergic system may be targeted for the treatment of Parkinson's disease and psychosis.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".