An m<scp>G</scp>lu4‐<scp>P</scp>ositive <scp>A</scp>llosteric <scp>M</scp>odulator <scp>A</scp>lleviates <scp>P</scp>arkinsonism in <scp>P</scp>rimates
Bibliographic record
Abstract
BACKGROUND: Levodopa remains the gold-standard treatment for PD. However, it becomes less effective as the disease progresses and produces debilitating side effects, such as motor fluctuations and l-dopa-induced dyskinesia. Modulation of metabotropic glutamate receptor 4 represents a promising antiparkinsonian approach in combination with l-dopa, but it has not been demonstrated in primates. OBJECTIVE: We studied whether a novel positive allosteric modulator of the metabotropic glutamate receptor 4, PXT002331 (foliglurax), could reduce parkinsonism in primate models. METHODS: We assessed the therapeutic potential of PXT002331 in three models of MPTP-induced parkinsonism in macaques. These models represent three different stages of disease evolution: early stage and advanced stage with and without l-dopa-induced dyskinesia. RESULTS: As an adjunct to l-dopa, PXT002331 induced a robust and dose-dependent reversal of parkinsonian motor symptoms in macaques, including bradykinesia, tremor, posture, and mobility. Moreover, PXT002331 strongly decreased dyskinesia severity, thus having therapeutic efficacy on both parkinsonian motor impairment and l-dopa-induced dyskinesia. PXT002331 brain penetration was also assessed using PET imaging in macaques, and pharmacodynamic analyses support target engagement in the therapeutic effects of PXT002331. CONCLUSIONS: This work provides a demonstration that a positive allosteric modulator of metabotropic glutamate receptor 4 can alleviate the motor symptoms of PD and the motor complications induced by l-dopa in primates. PXT002331 is the first compound of its class to enter phase IIa clinical trials. © 2018 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 | 0.000 | 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) | 0.007 | 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".