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Record W4377140274 · doi:10.1101/2023.05.19.541431

Importin 13-dependent Axon Diameter Growth Regulates Conduction Speeds along Myelinated CNS Axons

2023· preprint· en· W4377140274 on OpenAlexfundno aff
Jenea M. Bin, Daumante Šuminaite, Linde Kegel, Maria Rubio-Brotons, Jason J. Early, Daniel Soong, Matthew R. Livesey, Richard J. Poole, David A. Lyons

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSignaling Pathways in Disease
Canadian institutionsnot available
FundersWellcome TrustMultiple Sclerosis SocietyLister Institute of Preventive MedicineUniversity of EdinburghBiotechnology and Biological Sciences Research CouncilMultiple Sclerosis Society of Canada
KeywordsAxonNerve conduction velocityNeuroscienceGrowth coneNervous systemSomaBiologyAnatomyBiophysics

Abstract

fetched live from OpenAlex

Summary Central nervous system neurons have axons that vary over 100-fold in diameter. This diversity contributes to the regulation of myelination and conduction velocity along axons, which is critical for proper nervous system function. Despite this importance, technical challenges have limited our understanding of mechanisms controlling axon diameter growth, preventing systematic dissection of how manipulating diameter affects conduction along individual axons. Here, we establish zebrafish as system to investigate the regulation of axon diameter and axonal conduction in vivo . We identify a role for importin 13b specifically in axon diameter growth, that is independent of axonal length and overall cell size. Impairment of diameter growth along individual myelinated axons reduced conduction velocity in proportion to the diameter, but had no effect on the precision of action potential propagation or ability to fire at high frequencies. This work highlights an axon diameter-specific mechanism of growth that regulates conduction speeds along myelinated axons.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.029
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.022
GPT teacher head0.236
Teacher spread0.214 · 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.

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
Published2023
Admission routes1
Has abstractyes

Explore more

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