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Record W2026700322 · doi:10.1074/jbc.m112.400184

Hedgehog Signaling Regulates MyoD Expression and Activity

2012· article· en· W2026700322 on OpenAlexafffund
Anastassia Voronova, Erin M. Coyne, Ashraf Al Madhoun, Joel Fair, Neven Bosiljcic, Catherine St‐Louis, Grace Li, Sherry Thurig, Valerie A. Wallace, Nadine Wiper‐Bergeron, Ilona S. Skerjanc

Bibliographic record

VenueJournal of Biological Chemistry · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHedgehog Signaling Pathway Studies
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsMyoDMyogenesisPITX2MyogeninMyoD ProteinCell biologyBiologyMyogenic regulatory factorsMyocyteTranscription factorGeneticsHomeoboxGene

Abstract

fetched live from OpenAlex

The inhibition of MyoD expression is important for obtaining muscle progenitors that can replenish the satellite cell niche during muscle repair. Progenitors could be derived from either embryonic stem cells or satellite cells. Hedgehog (Hh) signaling is important for MyoD expression during embryogenesis and adult muscle regeneration. To date, the mechanistic understanding of MyoD regulation by Hh signaling is unclear. Here, we demonstrate that the Hh effector, Gli2, regulates MyoD expression and associates with MyoD gene elements. Gain- and loss-of-function experiments in pluripotent P19 cells show that Gli2 activity is sufficient and required for efficient MyoD expression during skeletal myogenesis. Inhibition of Hh signaling reduces MyoD expression during satellite cell activation in vitro. In addition to regulating MyoD expression, Hh signaling regulates MyoD transcriptional activity, and MyoD activates Hh signaling in myogenic conversion assays. Finally, Gli2, MyoD, and MEF2C form a protein complex, which enhances MyoD activity on skeletal muscle-related promoters. We therefore link Hh signaling to the function and expression of MyoD protein during myogenesis in stem cells.

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 score0.007
Threshold uncertainty score0.447

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 head0.031
GPT teacher head0.269
Teacher spread0.238 · 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

Citations60
Published2012
Admission routes2
Has abstractyes

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