Docosahexaenoic acid reduces levodopa‐induced dyskinesias in 1‐methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine monkeys
Bibliographic record
Abstract
OBJECTIVE: The objective of the present study was to investigate the effect of docosahexaenoic acid (DHA), a polyunsaturated fatty acid (omega-3), on levodopa-induced dyskinesias (LIDs) in parkinsonian 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated monkeys. METHODS: We explored the effect of DHA in two paradigms. First, a group of MPTP monkeys was primed with levodopa for several months before introducing DHA. A second group of MPTP monkeys (de novo) was exposed to DHA before levodopa therapy. RESULTS: DHA administration reduced LIDs in both paradigms without alteration of the anti-parkinsonian effect of levodopa indicating that DHA can reduce the severity or delay the development of LIDs in a nonhuman primate model of Parkinson's disease. INTERPRETATION: These results suggest that DHA can reduce the severity or delay the development of LIDs in a nonhuman primate model of Parkinson's disease. DHA may represent a new approach to improve the quality of life of Parkinson's disease patients.
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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) | 0.001 | 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".