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Record W1995737033 · doi:10.1002/jnr.10289

Alterations in myelination in the central nervous system of dystonia musculorum mice

2002· article· en· W1995737033 on OpenAlexaff
Ron Saulnier, Yves De Repentigny, V. Wee Yong, Rashmi Kothary

Bibliographic record

VenueJournal of Neuroscience Research · 2002
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsUniversity of CalgaryUniversity of Ottawa
FundersMultiple Sclerosis Society
KeywordsMyelinCentral nervous systemBiologyPeripheral nervous systemAnatomyPathologyOptic nerveNervous systemNeuroscienceSciatic nerveMedicine

Abstract

fetched live from OpenAlex

Dystonia musculorum (dt) is an autosomal recessive sensory neuropathy in mice resulting from a mutation in the gene encoding the cytoskeletal linker protein Bpag1. In addition to neurodegeneration, dt mice display myelination abnormalities in the peripheral nervous system. In this report we investigated whether myelination abnormalities are also present in the central nervous system of dt(Tg4) mice. Transcripts for both neural isoforms of Bpag1 (a1 and a2) were detected in optic nerves and spinal cords of wild-type mice. Light microscopy of resin-embedded thin sections revealed a reduction in myelinated axons in both optic nerves and spinal cords in dt(Tg4) mice. As well, hypermyelinated axons were detected in these tissues. Ultrastructural analysis of optic nerves and spinal cords from dt(Tg4) mice revealed an increase in the number of amyelinated axons, the presence of hypo- and hypermyelinated axons, and redundant myelin that course away from axons. Changes in the level of myelin proteins accompanied the morphological alterations. Myelin-associated glycoprotein levels were reduced in optic nerves of dt(Tg4) mice, and myelin basic protein levels were altered in optic nerves, sciatic nerves, and spinal cords of affected mice. Short-term cultures of oligodendrocytes derived from dt(Tg4) mice did not show morphological alterations.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.562
Threshold uncertainty score0.436

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.152
GPT teacher head0.378
Teacher spread0.227 · 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

Citations16
Published2002
Admission routes1
Has abstractyes

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