Effect of the mGlu <sub>2</sub> positive allosteric modulator biphenyl‐indanone A as a monotherapy and as adjunct to a low dose of L‐DOPA in the MPTP‐lesioned marmoset
Bibliographic record
Abstract
Abstract Activation of metabotropic glutamate 2 (mGlu 2 ) receptors is a potential novel therapeutic approach for the treatment of parkinsonism. Thus, when administered as monotherapy or as adjunct to a low dose of L‐3,4‐dihydroxyphenylalanine (L‐DOPA), the mGlu 2 positive allosteric modulator (PAM) LY‐487,379 alleviated parkinsonism in 1‐methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine (MPTP)‐lesioned primates. Here, we sought to investigate the effect of biphenyl‐indanone A (BINA), a highly selective mGlu 2 PAM whose chemical scaffold is unrelated to LY‐487,379, to determine if a structurally different mGlu 2 PAM would also confer anti‐parkinsonian benefit. In monotherapy experiments, MPTP‐lesioned marmosets were injected with either vehicle, L‐DOPA/benserazide (15/3.75 mg/kg, positive control) or BINA (0.1, 1, 10 mg/kg). In adjunct to a low L‐DOPA dose experiments, MPTP‐lesioned marmosets were injected with L‐DOPA/benserazide (7.5/1.875 mg/kg) in combination with vehicle or BINA (0.1, 1, 10 mg/kg). Parkinsonism, dyskinesia and psychosis‐like behaviours (PLBs) were then quantified. When administered alone, BINA 1 and 10 mg/kg decreased parkinsonism severity by ~22% ( p < 0.01) and ~47% ( p < 0.001), when compared with vehicle, which was comparable with the global effect of a high L‐DOPA dose. When administered in combination with a low L‐DOPA dose, BINA 1 and 10 mg/kg decreased global parkinsonism by ~38% ( p < 0.001) and ~53% ( p < 0.001). BINA 10 mg/kg decreased global dyskinesia by ~94% ( p < 0.01) and global PLBs by ~92% ( p < 0.01). Our results provide additional evidence that mGlu 2 positive allosteric modulation elicits anti‐parkinsonian effects. That this benefit is not related to a particular chemical scaffold suggests that it may be a class effect rather than the effect of a specific molecule.
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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) | 0.001 | 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 | 0.001 | 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".