Presynaptic vesicular accumulation is required for antipsychotic efficacy in psychotic-like rats
Bibliographic record
Abstract
BACKGROUND: The therapeutic effects of antipsychotic drugs (APDs) are mainly attributed to their postsynaptic inhibitory functions on the dopamine D2 receptor, which, however, cannot explain the delayed onset of full therapeutic efficacy. It was previously shown that APDs accumulate in presynaptic vesicles during chronic treatment and are released like neurotransmitters in an activity-dependent manner triggering an auto-inhibitory feedback mechanism. Although closely mirroring therapeutic action onset, the functional consequence of the APD accumulation process remained unclear. AIMS: Here we tested whether the accumulation of the APD haloperidol (HAL) is required for full therapeutic action in psychotic-like rats. METHODS: We designed a HAL analog compound (HAL-F), which lacks the accumulation property of HAL, but retains its postsynaptic inhibitory action on dopamine D2 receptors. RESULTS/OUTCOMES: By perfusing LysoTracker fluorophore-stained cultured hippocampal neurons, we confirmed the accumulation of HAL and the non-accumulation of HAL-F. In an amphetamine hypersensitization psychosis-like model in rats, we found that subchronic intracerebroventricularly delivered HAL (0.1 mg/kg/day), but not HAL-F (0.3-1.5 mg/kg/day), attenuates psychotic-like behavior in rats. CONCLUSIONS/INTERPRETATION: These findings suggest the presynaptic accumulation of HAL may serve as an essential prerequisite for its full antipsychotic action and may explain the time course of APD action. Targeting accumulation properties of APDs may, thus, become a new strategy to improve APD action.
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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".