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Neurofilament Transport<i>In Vivo</i>Minimally Requires Hetero-Oligomer Formation

2003· article· en· W2137878828 on OpenAlexaff
Aidong Yuan, Mala V. Rao, Asok Kumar, Jean‐Pierre Julien, Ralph A. Nixon

Bibliographic record

VenueJournal of Neuroscience · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSkin and Cellular Biology Research
Canadian institutionsMcGill University
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute on Aging
KeywordsNeurofilamentOligomerAxoplasmic transportProtein subunitCell biologyChemistryIn vivoBiophysicsAxonBiochemistryBiologyGenePolymer chemistryImmunology

Abstract

fetched live from OpenAlex

Neurofilament assembly requires at minimum the polymerization of neurofilament light chain (NF-L) with either neurofilament medium chain (NF-M) or neurofilament heavy chain (NF-H) subunits, but requirements for their axonal transport have long been controversial. Using a gene deletion approach, we generated mice containing only NF-L or NF-M. In vivo pulse radiolabeling analyses in retinal ganglion cell neurons revealed that NF-L alone is incapable of efficient transport, whereas nearly one-half of the normal level of NF-M is transported along optic axons in the absence of the other triplet subunits. Under these conditions, however, NF-M transport is completely abolished by deleting alpha-internexin. Our results strongly suggest that efficient neurofilament protein transport in vivo minimally requires hetero-oligomer formation. They also show that NF-M can partner with intermediate filament proteins other than the NF-H and NF-L subunits in neurons to support slow transport and possibly other functions of neuronal intermediate filaments.

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 score0.044
Threshold uncertainty score0.287

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 head0.023
GPT teacher head0.284
Teacher spread0.261 · 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

Citations52
Published2003
Admission routes1
Has abstractyes

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