Wnt Signaling Regulates the Function of MyoD and Myogenin
Bibliographic record
Abstract
The myogenic regulatory factors (MRFs), MyoD and myogenin, can induce myogenesis in a variety of cell lines but not efficiently in monolayer cultures of P19 embryonal carcinoma stem cells. Aggregation of cells expressing MRFs, termed P19[MRF] cells, results in an approximately 30-fold enhancement of myogenesis. Here we examine molecular events occurring during P19 cell aggregation to identify potential mechanisms regulating MRF activity. Although myogenin protein was continually present in the nuclei of >90% of P19[myogenin] cells, only a fraction of these cells differentiated. Consequently, it appears that post-translational regulation controls myogenin activity in a cell lineage-specific manner. A correlation was obtained between the expression of factors involved in somite patterning, including Wnt3a, Wnt5b, BMP-2/4, and Pax3, and the induction of myogenesis. Co-culturing P19[Wnt3a] cells with P19[MRF] cells in monolayer resulted in a 5- to 8-fold increase in myogenesis. Neither BMP-4 nor Pax3 was efficient in enhancing MRF activity in unaggregated P19 cultures. Furthermore, BMP-4 abrogated the enhanced myogenesis induced by Wnt signaling. Consequently, signaling events resulting from Wnt3a expression but not BMP-4 signaling or Pax3 expression, regulate MRF function. Therefore, the P19 cell culture system can be used to study the link between somite patterning events and myogenesis.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".