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Record W1678034977 · doi:10.1016/j.celrep.2015.07.028

Complete Loss of Netrin-1 Results in Embryonic Lethality and Severe Axon Guidance Defects without Increased Neural Cell Death

2015· article· en· W1678034977 on OpenAlexafffund
Jenea M. Bin, Dong Cho Han, Karen Lai Wing Sun, Louis‐Philippe Croteau, Émilie Dumontier, Jean‐François Cloutier, Artur Kania, Timothy E. Kennedy

Bibliographic record

VenueCell Reports · 2015
Typearticle
Languageen
FieldNeuroscience
TopicAxon Guidance and Neuronal Signaling
Canadian institutionsUniversité de MontréalMontreal Clinical Research InstituteMcGill UniversityMontreal Neurological Institute and Hospital
FundersCanadian Institutes of Health Research
KeywordsNetrinAxon guidanceBiologyLoss functionReceptorCell biologyEmbryonic stem cellAxonPhenotypeGeneticsGene

Abstract

fetched live from OpenAlex

Netrin-1 regulates cell migration and adhesion during the development of the nervous system, vasculature, lung, pancreas, muscle, and mammary gland. It is also proposed to function as a dependence ligand that inhibits apoptosis; however, studies disagree regarding whether netrin-1 loss-of-function mice exhibit increased cell death. Furthermore, previously studied netrin-1 loss-of-function gene-trap mice express a netrin-1-β-galactosidase protein chimera with potential for toxic gain-of-function effects, as well as a small amount of wild-type netrin-1 protein. To unambiguously assess loss of function, we generated netrin-1 floxed and netrin-1 null mouse lines. Netrin-1(-/-) mice die earlier and exhibit more severe axon guidance defects than netrin-1 gene-trap mice, revealing that complete loss of function is more severe than previously reported. Netrin-1(-/-) embryos also exhibit increased expression of the netrin receptors DCC and neogenin that are proposed dependence receptors; however, increased apoptosis was not detected, inconsistent with netrin-1 being an essential dependence receptor ligand in the embryonic spinal cord.

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 score0.205
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.062
GPT teacher head0.278
Teacher spread0.216 · 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

Citations104
Published2015
Admission routes2
Has abstractyes

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