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Galectin‐1 in regenerating motoneurons

2004· article· en· W2129849654 on OpenAlexaff
John McGraw, Lowell T. McPhail, Loren W. Oschipok, Hidenori Horie, Françoise Poirier, J. D. Steeves, Matt S. Ramer, Wolfram Tetzlaff

Bibliographic record

VenueEuropean Journal of Neuroscience · 2004
Typearticle
Languageen
FieldImmunology and Microbiology
TopicGalectins and Cancer Biology
Canadian institutionsInternational Collaboration On Repair DiscoveriesUniversity of British Columbia
Fundersnot available
KeywordsAxotomyWhisking in animalsEndogenyRegeneration (biology)AplysiaGalectinNeuroscienceNeurotrophic factorsFacial nerveNeurotrophinBiologyNerve growth factorCell biologyInternal medicineEndocrinologyAnatomyMedicineReceptorSomatosensory system

Abstract

fetched live from OpenAlex

The exogenous application of recombinant galectin-1 has recently been shown to promote the rate of peripheral nerve regeneration. Endogenous neuronal galectin-1 expression has recently been demonstrated to increase after axotomy. Here we demonstrate a significant increase in the endogenous neuronal expression of galectin-1 mRNA in facial motoneurons after either a nerve resection or crush injury in mice. This increase in galectin-1 expression was due in part to the loss of target-derived factor(s) as indicated by both the return of galectin-1 expression to control levels following target re-innervation and the increase in galectin-1 expression after blockade of axonal transport by an interneuronal colchicine injection. Furthermore, interneuronal injections of glial-derived neurotrophic factor into the uninjured nerve also increased galectin-1 mRNA expression within facial motoneurons suggesting that positive signals may also be involved in the regulation of galectin-1 expression. Galectin-1 null mutant mice showed an attenuated rate of functional recovery of whisking movement after a facial nerve crush.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.756
Threshold uncertainty score0.309

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.247
Teacher spread0.224 · 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

Citations39
Published2004
Admission routes1
Has abstractyes

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