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Record W1973022314 · doi:10.1242/dev.003905

Pbx homeodomain proteins direct Myod activity to promote fast-muscle differentiation

2007· article· en· W1973022314 on OpenAlexaff
Lisa Maves, Andrew J. Waskiewicz, Biswajit Paul, Yi Cao, Ashlee E. Tyler, Cecilia B. Moens, Stephen J. Tapscott

Bibliographic record

VenueDevelopment · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsUniversity of Alberta
FundersNational Center for Research ResourcesNational Institute of Arthritis and Musculoskeletal and Skin Diseases
KeywordsMyoDMyogenesisMyogeninBiologyMYF5PITX2MyoD ProteinHomeoboxCell biologyTranscription factorMyocyteGeneticsGene

Abstract

fetched live from OpenAlex

The basic helix-loop-helix (bHLH) transcription factor Myod directly regulates gene expression throughout the program of skeletal muscle differentiation. It is not known how a Myod-driven myogenic program is modulated to achieve muscle fiber-type-specific gene expression. Pbx homeodomain proteins mark promoters of a subset of Myod target genes, including myogenin (Myog); thus, Pbx proteins might modulate the program of myogenesis driven by Myod. By inhibiting Pbx function in zebrafish embryos, we show that Pbx proteins are required in order for Myod to induce the expression of a subset of muscle genes in the somites. In the absence of Pbx function, expression of myog and of fast-muscle genes is inhibited, whereas slow-muscle gene expression appears normal. By knocking down Pbx or Myod function in combination with another bHLH myogenic factor, Myf5, we show that Pbx is required for Myod to regulate fast-muscle, but not slow-muscle, development. Furthermore, we show that Sonic hedgehog requires Myod in order to induce both fast- and slow-muscle markers but requires Pbx only to induce fast-muscle markers. Our results reveal that Pbx proteins modulate Myod activity to drive fast-muscle gene expression, thus showing that homeodomain proteins can direct bHLH proteins to establish a specific cell-type identity.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.008
GPT teacher head0.236
Teacher spread0.228 · 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 source (direct Gemma or distilled Codex), 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

Citations140
Published2007
Admission routes1
Has abstractyes

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