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Record W2693135060 · doi:10.1186/s13229-017-0138-8

Neuroanatomy in mouse models of Rett syndrome is related to the severity of Mecp2 mutation and behavioral phenotypes

2017· article· en· W2693135060 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMolecular Autism · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Neurodevelopmental Disorders
Canadian institutionsHospital for Sick ChildrenInstitute of Cancer ResearchOntario Institute for Cancer ResearchUniversity of TorontoCentre for Addiction and Mental Health
FundersSimons Foundation Autism Research InitiativeSimons FoundationAutism Speaks
KeywordsMECP2Rett syndromeNeuroanatomyNeuroscienceMutationPhenotypeMutantBiologyCerebellumGeneticsGene

Abstract

fetched live from OpenAlex

BACKGROUND: Rett syndrome (RTT) is a neurodevelopmental disorder that predominantly affects girls. The majority of RTT cases are caused by de novo mutations in methyl-CpG-binding protein 2 (MECP2), and several mouse models have been created to further understand the disorder. In the current literature, many studies have focused their analyses on the behavioral abnormalities and cellular and molecular impairments that arise from Mecp2 mutations. However, limited efforts have been placed on understanding how Mecp2 mutations disrupt the neuroanatomy and networks of the brain. METHODS: mouse lines using high-resolution magnetic resonance imaging (MRI) paired with deformation-based morphometry to determine the brain regions susceptible to Mecp2 disruptions. RESULTS: lines. CONCLUSIONS: Our findings demonstrate that the direction and magnitude of the neuroanatomical differences between control and mutant mice carrying Mecp2 mutations are driven by the severity of the mutation and the stage of behavioral impairments.

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)0.000
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 score0.580
Threshold uncertainty score0.372

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.010
GPT teacher head0.253
Teacher spread0.243 · 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