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Netrin-1 Attracts Axons through FAK-Dependent Mechanotransduction

2012· article· en· W2006695366 on OpenAlexfundno aff
Simon W. Moore, Xian Zhang, Christopher D. Lynch, Michael P. Sheetz

Bibliographic record

VenueJournal of Neuroscience · 2012
Typearticle
Languageen
FieldNeuroscience
TopicAxon Guidance and Neuronal Signaling
Canadian institutionsnot available
FundersNational Institute of General Medical SciencesNational Institute of Neurological Disorders and StrokeCommon FundNational Eye InstituteCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsNetrinGrowth coneMechanotransductionFocal adhesionAxon guidanceCell biologyAxonPhosphorylationNeuroscienceBiologyKinase

Abstract

fetched live from OpenAlex

The mechanism by which extracellular cues influence intracellular biochemical cascades that guide axons is important, yet poorly understood. Because of the mechanical nature of axon extension, we explored whether the physical interactions of growth cones with their guidance cues might be involved. In the context of mouse spinal commissural neuron axon attraction to netrin-1, we found that mechanical attachment of netrin-1 to the substrate was required for axon outgrowth, growth cone expansion, axon attraction and phosphorylation of focal adhesion kinase (FAK) and Crk-associated substrate (CAS). Myosin II activity was necessary for traction forces >30 pN on netrin-1. Interestingly, while these myosin II-dependent forces on netrin-1 substrates or beads were needed to increase the kinase activity and phosphorylation of FAK, they were not necessary for netrin-1 to increase CAS phosphorylation. When FAK kinase activity was inhibited, the growth cone's ability to recruit additional adhesions and to generate forces >60 pN on netrin-1 was disrupted. Together, these findings demonstrate an important role for mechanotransduction during chemoattraction to netrin-1 and that mechanical activation of FAK reinforces interactions with netrin-1 allowing greater forces to be exerted.

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 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 score0.024
Threshold uncertainty score0.635

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.003
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 head0.125
GPT teacher head0.325
Teacher spread0.200 · 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

Citations91
Published2012
Admission routes1
Has abstractyes

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