Expression of CCAAT/Enhancer Binding Protein Beta in Muscle Satellite Cells Inhibits Myogenesis in Cancer Cachexia
Bibliographic record
Abstract
Cancer cachexia is a paraneoplastic syndrome that causes profound weight loss and muscle mass atrophy and is estimated to be the cause of up to 30% of cancer deaths. Though the exact cause is unknown, patients with cancer cachexia have increased muscle protein catabolism. In healthy muscle, injury activates skeletal muscle stem cells, called satellite cells, to differentiate and promote regeneration. Here, we provide evidence that this mechanism is inhibited in cancer cachexia due to persistent expression of CCAAT/Enhancer Binding Protein beta (C/EBPβ) in muscle myoblasts. C/EBPβ is a bzip transcription factor that is expressed in muscle satellite cells and is normally downregulated upon differentiation. However, in myoblasts exposed to a cachectic milieu, C/EBPβ expression remains elevated, despite activation to differentiate, resulting in the inhibition of myogenin expression and myogenesis. In vivo, cancer cachexia results in increased number of Pax7+ cells that also express C/EBPβ and the inhibition of normal repair mechanisms. Loss of C/EBPβ expression in primary myoblasts rescues differentiation under cachectic conditions without restoring myotube size, indicating that C/EBPβ is an important inhibitor of myogenesis in cancer cachexia.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".