Sustained Cabergoline Treatment Reverses Levodopa-Induced Dyskinesias in Parkinsonian Monkeys
Bibliographic record
Abstract
The pathophysiology of L-Dopa-induced dyskinesias (LID), a common problem after long-term use of L-dopa in the treatment of Parkinson's disease (PD), is not completely understood. Oscillations in L-Dopa concentrations in the brain are believed to be responsible, at least in part, for their pathogenesis. This study was aimed at verifying whether chronic administration of cabergoline, a long-acting dopamine D2-like receptor agonist, can reverse established LID. Four MPTP-treated cynomolgus monkeys with long-standing and stable parkinsonian syndrome and reproducible dyskinesias to L-Dopa, were used in this study. We compared the antiparkinsonian and dyskinetic responses of L-Dopa methyl ester (62.5 mg and 125 mg), given with benserazide (50 mg) (L-Dopa/benserazide), administered before and after a 6-week period during which the animals were treated only by daily administration of cabergoline (doses ranging from 0.125 to 0.185 mg/kg, subcutaneous). During cabergoline treatment, the monkeys initially showed marked dyskinesias, which were reduced significantly after 4 weeks of treatment. However, there was no tolerance to its antiparkinsonian effect. L-Dopa/benserazide given 4 days after cabergoline withdrawal produced a significant antiparkinsonian effect, but dyskinesias were dramatically reduced compared to what had been seen before chronic cabergoline treatment. The duration of the L-Dopa response was not increased after chronic administration of cabergoline. Our data suggest that sustained dopamine D2 receptor stimulation could be of value when trying to reduce or to reverse LID in patients with fluctuating advanced PD.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".