MétaCan
Menu
Back to cohort

Septin 7: Actin cross-organization is required for axonal association of Schwann cells

2013· article· en· W2019583868 on OpenAlexaff
Alejandro D. Roth, Dalinda Liazoghli, Felipe Perez De Arce, David Colman

Bibliographic record

VenueBiological Research · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsSeptinCell biologyCytoskeletonBiologyMicrotubuleMyelinCytoplasmDorsal root ganglionMicrofilamentActinGTPaseCytoplasmic streamingCytokinesisNeuriteCell polarityCell divisionActin cytoskeletonNeuroscienceAnatomyCellGeneticsDorsumCentral nervous system

Abstract

fetched live from OpenAlex

Myelin sheaths present two distinct domains: compacted myelin spirals and flanking non-compacted cytoplasmic channels, where lipid and protein segregation is established by unknown mechanisms. Septins, a conserved family of membrane and cytoskeletal interacting GTPases, form intracellular diffusion barriers during cell division and neurite extension and are expressed in myelinating cells. Septins, particularly septin 7 (Sept7), the central constituent of septin polymers, are associated with the cytoplasmic channels of myelinating cells. Here we show that Schwann cells deprived of Sept7 fail to wrap around axons from dorsal root ganglion neurons and exhibit disorganization of the actin cytoskeleton. Likewise, Sept7 distribution is dependent on microfilament but not microtubule organization.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.001

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 head0.084
GPT teacher head0.391
Teacher spread0.307 · 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 source (direct Gemma or distilled Codex), 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

Citations8
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueBiological ResearchSame topicCellular Mechanics and InteractionsFrench-language works237,207