NYX‐458 Improves Cognitive Performance in a Primate Parkinson's Disease Model
Bibliographic record
Abstract
BACKGROUND: NYX-458 is a N-methyl-d-aspartate receptor (NMDAR) modulator that enhances synaptic plasticity. Dopaminergic cell loss in Parkinson's disease (PD) leads to NMDAR dysregulation in the cortico-striato-pallidal-thalmo-cortical network and altered plasticity in brain regions important to cognitive function. We hypothesize that targeting the NMDAR may be an efficacious approach to treating cognitive impairment in PD. OBJECTIVES: NYX-458 was evaluated in 2 nonhuman primate models of PD. The first, a chronic low-dose 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-administration model, was used to assess the effects of NYX-458 on cognitive domains impacted early in PD including attention, working memory, executive function, and visuospatial learning. The second, a high-dose MPTP-administration model, was used to assess potential for NYX-458 induced change in motor symptoms. METHODS: NYX-458 was evaluated in the chronic low-dose MPTP model using the variable delayed response measure to assess attention and working memory and simple discrimination reversal to assess executive function. NYX-458 was also assessed in the high-dose MPTP model as a monotherapy and in combination with low-dose or high-dose levodopa to assess potential impact on motor symptoms. RESULTS: NYX-458 administration resulted in rapid and long-lasting improvement in cognitive function across the domains of attention, working memory, and executive function. Dose levels effective in improving cognitive performance had no effect on PD motor symptoms, the antiparkinsonian benefit of levodopa, or dyskinesia. CONCLUSIONS: NYX-458 provides benefit in specific domains known to be impaired in PD in a dopamine depletion model of PD-like cognitive impairment. These data support the continued evaluation of NYX-458 as a potential therapeutic for cognitive decline in PD. © 2020 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".