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Record W2012237852 · doi:10.1371/journal.pone.0070849

Cannabinoid Receptor CB2 Modulates Axon Guidance

2013· article· en· W2012237852 on OpenAlexafffund
Gabriel Duff, Anteneh Argaw, Bruno Cécyre, Hosni Cherif, Nicolas Tea, Nawal Zabouri, Christian Casanova, Maurice Ptito, Jean‐François Bouchard

Bibliographic record

VenuePLoS ONE · 2013
Typearticle
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsUniversité de Montréal
FundersInstitute of Neurosciences, Mental Health and AddictionCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaBaker Foundation
KeywordsNeuroscienceCannabinoid receptorCannabinoid receptor type 2CannabinoidAxon guidanceReceptorBiologyAxonCell biologyGeneticsAgonist

Abstract

fetched live from OpenAlex

Navigation of retinal projections towards their targets is regulated by guidance molecules and growth cone transduction mechanisms. Here, we present in vitro and in vivo evidences that the cannabinoid receptor 2 (CB2R) is expressed along the retino-thalamic pathway and exerts a modulatory action on axon guidance. These effects are specific to CB2R since no changes were observed in mice where the gene coding for this receptor was altered (cnr2 (-/-)). The CB2R induced morphological changes observed at the growth cone are PKA dependent and require the presence of the netrin-1 receptor, Deleted in Colorectal Cancer. Interfering with endogenous CB2R signalling using pharmacological agents increased retinal axon length and induced aberrant projections. Additionally, cnr2 (-/-) mice showed abnormal eye-specific segregation of retinal projections in the dorsal lateral geniculate nucleus (dLGN) indicating CB2R's implication in retinothalamic development. Overall, this study demonstrates that the contribution of endocannabinoids to brain development is not solely mediated by CB1R, but also involves CB2R.

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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

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

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 head0.053
GPT teacher head0.231
Teacher spread0.178 · 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

Citations63
Published2013
Admission routes2
Has abstractyes

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Same venuePLoS ONESame topicNerve injury and regenerationFrench-language works237,207