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Record W2608502625 · doi:10.1186/s13041-017-0293-z

Targeting metabotropic glutamate receptors for novel treatments of schizophrenia

2017· review· en· W2608502625 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMolecular Brain · 2017
Typereview
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Neurological Disorders and StrokeNational Institute of Mental HealthCanadian Institutes of Health ResearchVanderbilt University
KeywordsMetabotropic glutamate receptorNeuroscienceMetabotropic receptorGlutamatergicAllosteric regulationNeuroprotectionGlutamate receptorAllosteric modulatorPharmacologySchizophrenia (object-oriented programming)Metabotropic glutamate receptor 2Metabotropic glutamate receptor 5ReceptorBiologyMedicineInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Support for the N-methyl-d-aspartate receptor (NMDAR) hypofunction hypothesis of schizophrenia has led to increasing focus on restoring proper glutamatergic signaling as an approach for treatment of this devastating disease. The ability of metabotropic glutamate (mGlu) receptors to modulate glutamatergic neurotransmission has thus attracted considerable attention for the development of novel antipsychotics. Consisting of eight subtypes classified into three groups based on sequence homology, signal transduction, and pharmacology, the mGlu receptors provide a wide range of targets to modulate NMDAR function as well as glutamate release. Recently, allosteric modulators of mGlu receptors have been developed that allow unprecedented selectivity among subtypes, not just groups, facilitating the investigation of the effects of subtype-specific modulation. In preclinical animal models, positive allosteric modulators (PAMs) of the group I mGlu receptor mGlu5 have efficacy across all three symptom domains of schizophrenia (positive, negative, and cognitive). The discovery and development of mGlu5 PAMs that display unique signal bias suggests that efficacy can be retained while avoiding the neurotoxic effects of earlier compounds. Interestingly, mGlu1 negative allosteric modulators (NAMs) appear efficacious in positive symptom models of the disease but are still in early preclinical development. While selective group II mGlu receptor (mGlu2/3) agonists have reached clinical trials but were unsuccessful, specific mGlu2 or mGlu3 receptor targeting still hold great promise. Genetic studies implicated mGlu2 in the antipsychotic effects of group II agonists and mGlu2 PAMs have since entered into clinical trials. Additionally, mGlu3 appears to play an important role in cognition, may confer neuroprotective effects, and thus is a promising target to alleviate cognitive deficits in schizophrenia. Although group III mGlu receptors (mGlu4/6/7/8) have attracted less attention, mGlu4 agonists and PAMs appear to have efficacy across all three symptoms domains in preclinical models. The recent discovery of heterodimers comprising mGlu2 and mGlu4 may explain the efficacy of mGlu4 selective compounds but this remains to be determined. Taken together, compounds targeting mGlu receptors, specifically subtype-selective allosteric modulators, provide a compelling alternative approach to fill the unmet clinical needs for patients with schizophrenia.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.823
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.182
GPT teacher head0.446
Teacher spread0.264 · 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