mGlu5, Dopamine D<sub>2</sub>and Adenosine A<sub>2A</sub>Receptors in L-DOPA-induced Dyskinesias
Bibliographic record
Abstract
Patients with Parkinson's disease (PD) receiving L-3,4-dihydroxyphenylalanine (L-DOPA, the gold-standard treatment for this disease) frequently develop abnormal involuntary movements, termed L-DOPA-induced dyskinesias (LID). Glutamate overactivity is well documented in PD and LID. An approach to manage LID is to add to L-DOPA specific agents to reduce dyskinesias such as metabotropic glutamate receptor (mGlu receptor) drugs. This article reviews the contribution of mGlu type 5 (mGlu5) receptors in animal models of PD. Several mGlu5 negative allosteric modulators acutely attenuate LID in 1-methyl-4-phenyl-1,2,3,6- tetrahydropyridine (MPTP) monkeys and 6-hydroxydopamine(6-OHDA)-lesioned rats. Chronic administration of mGlu5 negative allosteric modulators to MPTP monkeys and 6-OHDA rats also attenuates LID while maintaining the antiparkinsonian effect of L-DOPA. Radioligand autoradiography shows an elevation of striatal mGlu5 receptors of dyskinetic L-DOPA-treated MPTP monkeys but not in those without LID. The brain molecular correlates of the long-term effect of mGlu5 negative allosteric modulators treatments with L-DOPA attenuating development of LID was shown to extend beyond mGlu5 receptors with normalization of glutamate activity in the basal ganglia of L-DOPA-induced changes of NMDA, AMPA, mGlu2/3 receptors and VGlut2 transporter. In the basal ganglia, mGlu5 receptor negative allosteric modulators also normalize the L-DOPA-induced changes of dopamine D2receptors, their associated signaling proteins (ERK1/2 and Akt/GSK3β) and neuropeptides (preproenkephalin, preprodynorphin) as well as the adenosine A2A receptors expression. These results show in animal models of PD reduction of LID with mGlu5 negative allosteric modulation associated with normalization of glutamate, dopamine and adenosine receptors suggesting a functional link of these receptors in chronic treatment with L-DOPA.
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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 | 0.000 |
| 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 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".