MétaCan
Menu
Back to cohort
Record W4400723406 · doi:10.1016/j.neulet.2024.137904

Rock2 heterozygosity improves recognition memory and endothelial function in a mouse model of 16p11.2 deletion autism syndrome

2024· article· en· W4400723406 on OpenAlexafffund
Julie Ouellette, Baptiste Lacoste

Bibliographic record

VenueNeuroscience Letters · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCongenital heart defects research
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsHaploinsufficiencyROCK2AutismBiologyMECP2Loss of heterozygosityNeuroscienceGeneticsGeneMedicineKinaseRho-associated protein kinasePhenotypePsychiatryAllele

Abstract

fetched live from OpenAlex

Rho-associated protein kinase-2 (ROCK2) is a critical player in many cellular processes and was incriminated in cardiovascular and neurological disorders. Recent evidence has shown that non-selective pharmacological blockage of ROCKs ameliorates behavioral alterations in a mouse model of 16p11.2 haploinsufficiency. We had revealed that 16p11.2-deficient mice also display cerebrovascular abnormalities, including endothelial dysfunction. To investigate whether genetic blockage of ROCK2 also exerts beneficial effects on cognition and angiogenesis, we generated mice with both 16p11.2 and Rock2 haploinsufficiency (16p11.2df/+;Rock2+/−). We find that Rock2 heterozygosity on a 16p11.2df/+ background significantly improved recognition memory. Furthermore, brain endothelial cells from 16p11.2df/+;Rock2+/− mice display improved angiogenic capacity compared to cells from 16p11.2df/+ littermates. Overall, this study implicates Rock2 gene as a modulator of 16p11.2-associated alterations, highlighting its potential as a target for treatment of autism spectrum disorders.

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.252
Teacher spread0.232 · 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

Citations2
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueNeuroscience LettersSame topicCongenital heart defects researchFrench-language works237,207