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Record W2089627499 · doi:10.1002/dvdy.22215

Examining the combinatorial model of motor neuron survival by expression profiling of trophic factors and their receptors in the embryonic <i>Gallus gallus</i>

2010· article· en· W2089627499 on OpenAlexafffund
Wendy Gu, Artur Kania

Bibliographic record

VenueDevelopmental Dynamics · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicZebrafish Biomedical Research Applications
Canadian institutionsMcGill UniversityUniversité de MontréalMontreal Clinical Research Institute
FundersCanadian Institutes of Health ResearchMuscular Dystrophy Association
KeywordsBiologyMotor neuronReceptorSpinal cordNeuroscienceEmbryoNeuronEmbryonic stem cellAmyotrophic lateral sclerosisCell biologyGeneGeneticsInternal medicine

Abstract

fetched live from OpenAlex

During embryogenesis, limb-innervating lateral motor column (LMC) spinal motor neurons (MN) are generated in excess and subsequently nearly half of them die. Many motor neuron survival factors (MnSFs) have been shown to suppress this default programmed cell death (PCD) program through their receptors (MnSFRs), raising the possibility that they are involved in matching specific MNs with their target muscles. Published observations suggest a combinatorial model of MnSF/Rs function, which assumes that during the PCD phase, MNs are expressing combinations of MnSFRs, whereas the limb muscles innervated by these MNs express cognate combinations of MnSFs. We tested this model by expression profiling of MnSFs and their receptors in the avian lumbosacral spinal cord and limb muscles during the peak PCD period. Our findings highlight the complexity of MnSF/Rs function in the control of LMC motor neuron survival.

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 score0.055
Threshold uncertainty score0.321

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 head0.015
GPT teacher head0.240
Teacher spread0.225 · 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

Citations5
Published2010
Admission routes2
Has abstractyes

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