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Modest loss of peripheral axons, muscle atrophy and formation of brain inclusions in mice with targeted deletion of gigaxonin exon 1

2008· article· en· W2049832848 on OpenAlexafffund
Florence Dequen, Pascale Bomont, Genevíève Gowing, Don W. Cleveland, Jean‐Pierre Julien

Bibliographic record

VenueJournal of Neurochemistry · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSkin and Cellular Biology Research
Canadian institutionsCentre hospitalier de l'Université LavalUniversité Laval
FundersCanadian Institutes of Health ResearchNational Institutes of HealthNational Institute of Neurological Disorders and StrokeFondation pour la Recherche MédicaleCanada Research Chairs
KeywordsExonBiologyMuscle atrophyUbiquitin ligaseAtrophyPhenotypeUbiquitinMutationCell biologyInclusion bodiesGeneGenetics

Abstract

fetched live from OpenAlex

Mutations in the gigaxonin gene are responsible for giant axonal neuropathy (GAN), a progressive neurodegenerative disorder associated with abnormal accumulations of Intermediate Filaments (IFs). Gigaxonin is the substrate-specific adaptor for a new Cul3-E3-ubiquitin ligase family that promotes the proteasome dependent degradation of its partners MAP1B, MAP8 and tubulin cofactor B. Here, we report the generation of a mouse model with targeted deletion of Gan exon 1 (Gan(Deltaexon1;Deltaexon1)). Analyses of the Gan(Deltaexon1;Deltaexon1) mice revealed increased levels of various IFs proteins in the nervous system and the presence of IFs inclusion bodies in the brain. Despite deficiency of full length gigaxonin, the Gan(Deltaexon1;Deltaexon1) mice do not develop overt neurological phenotypes and giant axons reminiscent of the human GAN disease. Nonetheless, at 6 months of age the Gan(Deltaexon1;Deltaexon1) mice exhibit a modest hind limb muscle atrophy, a 10% decrease of muscle innervation and a 27% axonal loss in the L5 ventral roots. This new mouse model should provide a useful tool to test potential therapeutic approaches for GAN disease.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.303

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 head0.236
Teacher spread0.226 · 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

Citations58
Published2008
Admission routes2
Has abstractyes

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