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Record W2338677800 · doi:10.1002/acn3.303

<i>α</i> 5GABA <sub>A</sub> receptor deficiency causes autism‐like behaviors

2016· article· en· W2338677800 on OpenAlexafffund
Agnieszka A. Zurek, Stephen W.P. Kemp, Zeenia Aga, Susan Walker, Marija Milenković, Amy J. Ramsey, Etienne Sibille, Stephen W. Scherer, Beverley A. Orser

Bibliographic record

VenueAnnals of Clinical and Translational Neurology · 2016
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsSunnybrook Health Science CentreHealth Sciences CentreMental Health Research CanadaHospital for Sick ChildrenUniversity of Toronto
FundersNational Institute of Mental HealthCanadian Institutes of Health Research
KeywordsAutismMissense mutationGABAA receptorMedicineExome sequencingAutism spectrum disorderReceptorPopulationNeuroimagingNeuroscienceGeneticsGeneBioinformaticsMutationPsychiatryInternal medicineBiology

Abstract

fetched live from OpenAlex

The prevalence of autism spectrum disorders (ASDs), which affect over 1% of the population, has increased twofold in recent years. Reduced expression of GABAA receptors has been observed in postmortem brain tissue and neuroimaging of individuals with ASDs. We found that deletion of the gene for the α5 subunit of the GABAA receptor caused robust autism-like behaviors in mice, including reduced social contacts and vocalizations. Screening of human exome sequencing data from 396 ASD subjects revealed potential missense mutations in GABRA5 and in RDX, the gene for the α5GABAA receptor-anchoring protein radixin, further supporting a α5GABAA receptor deficiency in ASDs.

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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.130
GPT teacher head0.398
Teacher spread0.268 · 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

Citations53
Published2016
Admission routes2
Has abstractyes

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