CCAAT/enhancer-binding protein beta promotes muscle stem cell quiescence through regulation of quiescence-associated genes
Bibliographic record
Abstract
Regeneration of skeletal muscle depends on resident muscle stem cells called satellite cells that in healthy, uninjured muscle remain quiescent (noncycling). After activation and expansion of satellite cells postinjury, satellite cell numbers return to uninjured levels and return to mitotic quiescence. Here, we show that the transcription factor CCAAT/enhancer-binding protein beta (C/EBPβ) is required to maintain quiescence of satellite cells in uninjured muscle. We show that C/EBPβ is expressed in quiescent satellite cells in vivo and upregulated in noncycling myoblasts in vitro. Loss of C/EBPβ in satellite cells promotes their premature exit from quiescence resulting in spontaneous activation and differentiation of the stem cell pool. Forced expression of C/EBPβ in myoblasts inhibits proliferation by upregulation of 28 quiescence-associated genes. Furthermore, we find that caveolin-1 is a direct transcriptional target of C/EBPβ and is required for cell cycle exit in muscle satellite cells expressing C/EBPβ. The induction of mitotic quiescence is considered necessary for the long-term maintenance of adult stem cell populations with dysregulation driving increased differentiation of progenitors and depletion of the stem cell pool. Our findings place C/EBPβ as an important transcriptional regulator of muscle satellite cell quiescence.
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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".