Muscle cell survival mediated by the transcriptional coactivators p300 and PCAF displays different requirements for acetyltransferase activity
Bibliographic record
Abstract
Normal skeletal muscle development requires the proper orchestration of genetic programs by myogenic regulatory factors (MRFs). The actions of the MRF protein MyoD are enhanced by the transcriptional coactivators p300 and the p300/CBP-associated factor (PCAF). We previously described C2 skeletal myoblasts lacking expression of insulin-like growth factor-II (IGF-II) that underwent progressive apoptotic death when incubated in differentiation-promoting medium. Viability of these cells was sustained by addition of IGF analogs or unrelated peptide growth factors. We now show that p300 or PCAF maintains myoblast viability as effectively as added growth factors through mechanisms requiring the acetyltransferase activity of PCAF but not of p300. The actions of p300 to promote cell survival were not secondary to increased expression of known MyoD targets, as evidenced by results of gene microarray experiments, but rather appeared to be mediated by induction of other genes, including fibroblast growth factor-1 (FGF-1). Conditioned culture medium from cells expressing p300 increased myoblast viability, and this was blocked by pharmacological inhibition of FGF receptors. Our results define a role for p300 in promoting cell survival, which is independent of its acetyltransferase activity and acts at least in part through FGF-1.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".