Pregnenolone Reduces L‐Dopa‐Induced Dyskinesias in Female Parkinsonian Monkeys
Bibliographic record
Abstract
BACKGROUND: Pregnenolone is the first neurosteroid synthesized from cholesterol in the brain. Previous studies showed that it reduces the development of levodopa (L-dopa)-induced dyskinesias (LIDs) in rat models of Parkinson's disease (PD). OBJECTIVE: To examine whether pregnenolone mitigates established LIDs in a non-human primate model. METHODS: Ovariectomized female macaques, modeling the postmenopausal hormonal status of most women with PD, were lesioned with MPTP and treated with L-dopa to induce LIDs. Pregnenolone was administered subcutaneously (SC) at 6 or 18 mg/kg or orally (36 mg/kg). RESULTS: Pregnenolone reduced established LIDs in MPTP-lesioned monkeys while preserving L-dopa's antiparkinsonian effects. The antidyskinetic effect was dose-dependent, with the greatest reduction observed at 18 mg/kg SC, followed by 6 mg/kg SC, and a lesser effect at 36 mg/kg orally, likely due to first-pass metabolism. CONCLUSIONS: Pregnenolone reduces established LIDs in parkinsonian monkeys and may represent a safe, novel therapeutic candidate for dyskinesia treatment in PD. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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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 | 0.001 | 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) | 0.003 | 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".