MétaCan
Menu
← Back to cohort

Allosteric and orthosteric activation of mGlu <sub>2</sub> receptors to alleviate dyskinesia and psychosis in the parkinsonian marmoset

2019· article· en· W3174463003 on OpenAlexafffundabout
Adjia Hamadjida, Stephen G. Nuara, Jim C. Gourdon, Philippe Huot

Bibliographic record

VenueThe FASEB Journal · 2019
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaWeston Brain Institute
KeywordsDyskinesiaAllosteric regulationMPTPBenserazideParkinsonismPharmacologyParkinson's diseaseMedicineNeurosciencePsychologyReceptorChemistryLevodopaInternal medicineDisease

Abstract

fetched live from OpenAlex

Objective To determine the effect of combined allosteric and orthosteric activation of metabotropic glutamate 2 (mGlu 2 ) receptors on L‐3,4‐dihydroxyphenylalanine (L‐DOPA)‐induced psychosis‐like behaviours (PLBs) and dyskinesia in the 1‐methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine (MPTP)‐lesioned marmoset model of Parkinson's disease (PD). Background We have previously demonstrated that activation of mGlu 2 receptors via positive allosteric modulation with LY‐487,379 or orthosteric stimulation with LY‐354,740 alleviates PLBs and dyskinesia in experimental parkinsonism. Here, we seek to determine if synergy ensues when mGlu 2 positive allosteric modulation and orthosteric stimulation are combined, in the MPTP‐lesioned marmoset. Methods Six common marmosets were rendered parkinsonian by MPTP injection. Following repeated administration of L‐DOPA/benserazide (L‐DOPA) to elicit stable PLBs and dyskinesia, they were administered acute challenges of LY‐487,379 (1 mg/kg), LY‐354,740 (1 mg/kg), LY‐487,379/LY‐354,740 (each 1 mg/kg) or vehicle, in combination with L‐DOPA, after which the severity of each of PLBs, dyskinesia and parkinsonian disability was rated. Results LY‐487,379, LY‐354,740 and LY‐487,379/LY‐354,740 each significantly reduced the severity of the global dyskinesia score, by ≈ 42%, 55% and 64% (each P < 0.001), when compared to L‐DOPA/vehicle. The combination LY‐487,379/LY‐354,740 was significantly more effective than either treatment alone (both P < 0.05). The severity of the global PLB score was also significantly reduced by each of LY‐487,379, LY‐354,740 and LY‐487,379/LY‐354,740, by ≈ 51%, 44% and 56% (each P < 0.001), when compared to L‐DOPA/vehicle. The combination LY‐487,379/LY‐354,740 was significantly more effective than LY‐487,379 ( P < 0.01), but not LY‐354,740 ( P > 0.05). The benefits on dyskinesia and PLBs were achieved without compromising the therapeutic effect of L‐DOPA on parkinsonism. Conclusions Our results confirm mGlu 2 activation, via both positive allosteric modulation and orthosteric stimulation, is a promising strategy to reduce dyskinesia and psychosis in PD. Moreover, they suggest that the combination of a positive allosteric modulator and an orthosteric agonist may lead to a synergistic effect, thereby providing greater anti‐dyskinetic and anti‐psychotic effects. Support or Funding Information Fonds de Recherche Québec ‐ Santé, Natural Sciences and Engineering Research Council of Canada, Parkinson Canada, Weston Brain Institute, Michael J Fox Foundation for Parkinson's Research, Healthy Brains for Healthy Lives. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.034
GPT teacher head0.299
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2019
Admission routes3
Has abstractyes

Explore more

Same venueThe FASEB Journal→Same topicNeuroscience and Neuropharmacology Research→French-language works237,207→