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Record W2140961802 · doi:10.1371/journal.pone.0133848

Dissociation of Axonal Neurofilament Content from Its Transport Rate

2015· article· en· W2140961802 on OpenAlexaff
Aidong Yuan, Linda Hassinger, Mala V. Rao, Jean-Pierre Julien, Christopher C.J. Miller, Ralph A. Nixon

Bibliographic record

VenuePLoS ONE · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSkin and Cellular Biology Research
Canadian institutionsCentre hospitalier de l'Université Laval
FundersNational Institute on AgingMedical Research CouncilWellcome Trust
KeywordsNeurofilamentCytoskeletonAxonAxoplasmic transportCell biologyBiologyChemistryBiophysicsBiochemistryImmunohistochemistryImmunologyCell

Abstract

fetched live from OpenAlex

The axonal cytoskeleton of neurofilament (NF) is a long-lived network of fibrous elements believed to be a stationary structure maintained by a small pool of transported cytoskeletal precursors. Accordingly, it may be predicted that NF content in axons can vary independently from the transport rate of NF. In the present report, we confirm this prediction by showing that human NFH transgenic mice and transgenic mice expressing human NFL Ser55 (Asp) develop nearly identical abnormal patterns of NF accumulation and distribution in association with opposite changes in NF slow transport rates. We also show that the rate of NF transport in wild-type mice remains constant along a length of the optic axon where NF content varies 3-fold. Moreover, knockout mice lacking NFH develop even more extreme (6-fold) proximal to distal variation in NF number, which is associated with a normal wild-type rate of NF transport. The independence of regional NF content and NF transport is consistent with previous evidence suggesting that the rate of incorporation of transported NF precursors into a metabolically stable stationary cytoskeletal network is the major determinant of axonal NF content, enabling the generation of the striking local variations in NF number seen along 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)0.000
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 score0.010
Threshold uncertainty score0.260

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 head0.131
GPT teacher head0.263
Teacher spread0.132 · 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

Citations13
Published2015
Admission routes1
Has abstractyes

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