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Defects in sensory nerve numbers and growth in mutant Kit and Steel mice

2000· article· en· W2069781806 on OpenAlexaff
Sandra Lourenssen, Benny Motro, Alan Bernstein, Jack Diamond

Bibliographic record

VenueNeuroreport · 2000
Typearticle
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsCanada Research ChairsUniversity of TorontoUniversity of New BrunswickLunenfeld-Tanenbaum Research InstituteQueen's UniversityMcMaster UniversityHotel Dieu Hospital
Fundersnot available
KeywordsMutantSensory systemNeuroscienceBiologyCell biologyNerve growth factorAnatomyGeneticsGeneReceptor

Abstract

fetched live from OpenAlex

The roles in the nervous system of the receptor tyrosine kinase Kit and its ligand, Steel factor, are unclear. We have now found first, that sensory nerve populations are reduced in mutant Kit and Steel mice, implicating Steel-Kit interactions in neuronal development. Second, sensory axonal regeneration (which occurs independently of nerve growth factor, or NGF) is impaired, while collateral sprouting (NGF dependent) is normal. Therefore, there is a selective involvement of Kit signal transduction pathways in nerve growth; supporting this, in wild-type animals Kit was up-regulated in regenerating, but unchanged in sprouting, sensory neurons. The receptor tyrosine kinase Kit thus contrasts with the receptor tyrosine kinase trkA, which is activated by the sprouting stimulus (NGF) but not by the axonal regeneration signal.

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 score0.132
Threshold uncertainty score0.445

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 head0.021
GPT teacher head0.252
Teacher spread0.230 · 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

Citations20
Published2000
Admission routes1
Has abstractyes

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