Synergistic antidyskinetic effects of topiramate and amantadine in animal models of Parkinson's disease
Bibliographic record
Abstract
L-Dopa-induced dyskinesia in patients with Parkinson's disease can be alleviated by amantadine, an antagonist at N-methyl-D-aspartate glutamate receptors. The antiepileptic drug topiramate, which blocks α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors, has also been shown to reduce dyskinesia. The purpose of this study was to examine the behavioral pharmacology of topiramate alone and in combination with amantadine in animal models of PD and L-dopa-induced dyskinesia. The effects of topiramate (5-20 mg/kg) and amantadine (5-20 mg/kg) on abnormal involuntary movements (the rat homologue of dyskinesia) and Rotarod performance were assessed alone and in combination in the 6-hydroxydopamine-lesioned rat following chronic L-dopa treatment. Dyskinesia, parkinsonian disability, and "on-time" were assessed in the MPTP-lesioned nonhuman primate following administration of topiramate (5-20 mg/kg) and amantadine (0.1-1.0 mg/kg) alone and in combination. Topiramate and amantadine dose-dependently reduced dyskinesia in the 6-hydroxydopamine-lesioned rat, whereas topiramate reduced Rotarod performance; there was no effect on parkinsonian disability in the MPTP-lesioned nonhuman primate, in which both drugs reduced dyskinesia. Topiramate and amantadine exhibited differential antidyskinetic effects on dyskinesia elicited by the dopamine D1 receptor agonist SKF 38393 (2 mg/kg). Subthreshold doses of both drugs in combination had a synergistic effect on dyskinesia in the 6-hydroxydopamine-lesioned rat, with no worsening of motor performance; this effect was confirmed in the MPTP-lesioned nonhuman primate, with a selective reduction in "bad on-time." These data confirm the antidyskinetic potential of topiramate and suggest that combination with low-dose amantadine may allow better reduction of dyskinesia with no adverse motor effects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".