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Record W2143662485 · doi:10.1083/jcb.200502101

MyoD induces myogenic differentiation through cooperation of its NH2- and COOH-terminal regions

2005· article· en· W2143662485 on OpenAlexaff
Jeff Ishibashi, Robert L. Perry, Atsushi Asakura, Michael A. Rudnicki

Bibliographic record

VenueThe Journal of Cell Biology · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsMcMaster UniversityUniversity of Ottawa
Fundersnot available
KeywordsMyoDMYF5MyogeninPITX2BiologyMyogenesisMyoD ProteinMyocyteCellular differentiationCell biologyMolecular biologyTranscription factorGeneticsGeneHomeobox

Abstract

fetched live from OpenAlex

MyoD and Myf5 are basic helix-loop-helix transcription factors that play key but redundant roles in specifying myogenic progenitors during embryogenesis. However, there are functional differences between the two transcription factors that impact myoblast proliferation and differentiation. Target gene activation could be one such difference. We have used microarray and polymerase chain reaction approaches to measure the induction of muscle gene expression by MyoD and Myf5 in an in vitro model. In proliferating cells, MyoD and Myf5 function very similarly to activate the expression of likely growth phase target genes such as L-myc, m-cadherin, Mcpt8, Runx1, Spp1, Six1, IGFBP5, and Chrnbeta1. MyoD, however, is strikingly more effective than Myf5 at inducing differentiation-phase target genes. This distinction between MyoD and Myf5 results from a novel and unanticipated cooperation between the MyoD NH2- and COOH-terminal regions. Together, these results support the notion that Myf5 functions toward myoblast proliferation, whereas MyoD prepares myoblasts for efficient differentiation.

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 score0.006
Threshold uncertainty score0.204

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 head0.014
GPT teacher head0.258
Teacher spread0.245 · 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

Citations157
Published2005
Admission routes1
Has abstractyes

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