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Record W2791950417 · doi:10.1111/brv.12398

Integrins promote axonal regeneration after injury of the nervous system

2018· review· en· W2791950417 on OpenAlexfundno aff
Bart Nieuwenhuis, Barbara Haenzi, Melissa R. Andrews, Joost Verhaagen, James W. Fawcett

Bibliographic record

VenueBiological reviews/Biological reviews of the Cambridge Philosophical Society · 2018
Typereview
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsnot available
FundersBiotechnology and Biological Sciences Research CouncilMedical Research CouncilMedical Research Council CanadaNederlandse Organisatie voor Wetenschappelijk OnderzoekHersenstichtingInternational Spinal Research Trust
KeywordsIntegrinRegeneration (biology)Cell biologyCell adhesion moleculeExtracellular matrixNervous systemCentral nervous systemNeuroscienceBiologyPeripheral nervous systemCytoskeletonCell adhesionReceptorCellBiochemistry

Abstract

fetched live from OpenAlex

Integrins are cell surface receptors that form the link between extracellular matrix molecules of the cell environment and internal cell signalling and the cytoskeleton. They are involved in several processes, e.g. adhesion and migration during development and repair. This review focuses on the role of integrins in axonal regeneration. Integrins participate in spontaneous axonal regeneration in the peripheral nervous system through binding to various ligands that either inhibit or enhance their activation and signalling. Integrin biology is more complex in the central nervous system. Integrins receptors are transported into growing axons during development, but selective polarised transport of integrins limits the regenerative response in adult neurons. Manipulation of integrins and related molecules to control their activation state and localisation within axons is a promising route towards stimulating effective regeneration in the central nervous system.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.195
GPT teacher head0.349
Teacher spread0.154 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations103
Published2018
Admission routes1
Has abstractyes

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Same venueBiological reviews/Biological reviews of the Cambridge Philosophical SocietySame topicNerve injury and regenerationFrench-language works237,207