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Impaired fast axonal transport in neurons of the sciatic nerves from <i>dystonia musculorum</i> mice

2003· article· en· W1603565354 on OpenAlexafffund
Yves De Repentigny, Julie Deschênes‐Furry, Bernard J. Jasmin, Rashmi Kothary

Bibliographic record

VenueJournal of Neurochemistry · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSkin and Cellular Biology Research
Canadian institutionsUniversity of Ottawa
FundersOntario Neurotrauma FoundationCanadian Institutes of Health ResearchUniversity of Ottawa
KeywordsAxoplasmic transportSciatic nerveNeurofilamentCytoskeletonNeuroscienceBiologyAnatomyMicrotubuleNeuritePathologyCell biologyMedicineImmunohistochemistry

Abstract

fetched live from OpenAlex

Dystonia musculorum (dt) mice suffer from a severe sensory neuropathy caused by mutations in the gene encoding the cytoskeletal cross-linker protein dystonin/bullous pemphigoid antigen 1 (Bpag1). Loss of function of dystonin/Bpag1 within neurons leads to a loss in the maintenance of cytoskeletal organization and to the development of focal axonal swellings prior to death of the neuron. In the present study, we demonstrate that neurons within the sciatic nerves of dt27J mice undergo axonal degeneration as has been previously reported for the dorsal roots. Furthermore, ultrastructural studies reveal a perturbed organization of the neurofilament and microtubule networks within the axons of sciatic nerves in dt27J mice. The disrupted cytoskeletal organization suggested that axonal transport is affected in dt mice. To address this, we assessed fast axonal transport by measuring the rate of accumulation of acetylcholinesterase (AChE) proximal and distal to a surgically introduced ligature on the sciatic nerves of normal and dt27J mice. Our findings demonstrate that axonal transport of AChE in both orthograde and retrograde directions is markedly affected, and allow us to conclude that axonal transport defects do exist in the sciatic nerves of dt27J mice.

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 score0.074
Threshold uncertainty score0.451

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 head0.009
GPT teacher head0.234
Teacher spread0.225 · 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

Citations32
Published2003
Admission routes2
Has abstractyes

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