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Record W2422184525 · doi:10.7554/elife.14653

p21-activated kinase 1 restricts tonic endocannabinoid signaling in the hippocampus

2016· article· en· W2422184525 on OpenAlexafffund
Shuting Xia, Zikai Zhou, Celeste Leung, Yuehua Zhu, Xingxiu Pan, Junxia Qi, Maria Morena, Matthew N. Hill, Wei Xie, Zhengping Jia

Bibliographic record

VenueeLife · 2016
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsOntario Brain InstituteUniversity of CalgaryHospital for Sick ChildrenUniversity of Toronto
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsEndocannabinoid systemPAK1Tonic (physiology)NeuroscienceAnandamideCannabinoid receptorNeurotransmissionBiologyInhibitory postsynaptic potentialSignal transductionReceptorCell biologyBiochemistry

Abstract

fetched live from OpenAlex

PAK1 inhibitors are known to markedly improve social and cognitive function in several animal models of brain disorders, including autism, but the underlying mechanisms remain elusive. We show here that disruption of PAK1 in mice suppresses inhibitory neurotransmission through an increase in tonic, but not phasic, secretion of endocannabinoids (eCB). Consistently, we found elevated levels of anandamide (AEA), but not 2-arachidonoylglycerol (2-AG) following PAK1 disruption. This increased tonic AEA signaling is mediated by reduced cyclooxygenase-2 (COX-2), and COX-2 inhibitors recapitulate the effect of PAK1 deletion on GABAergic transmission in a CB1 receptor-dependent manner. These results establish a novel signaling process whereby PAK1 upregulates COX-2, reduces AEA and restricts tonic eCB-mediated processes. Because PAK1 and eCB are both critically involved in many other organ systems in addition to the brain, our findings may provide a unified mechanism by which PAK1 regulates these systems and their dysfunctions including cancers, inflammations and allergies.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.329
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.298
Teacher spread0.276 · 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 teacher head, 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

Citations21
Published2016
Admission routes2
Has abstractyes

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