ERK3‐MK5 signaling regulates myogenic differentiation and muscle regeneration by promoting FoxO3 degradation
Bibliographic record
Abstract
Abstract The physiological functions and downstream effectors of the atypical mitogen‐activated protein kinase extracellular signal‐regulated kinase 3 (ERK3) remain to be characterized. We recently reported that mice expressing catalytically‐inactive ERK3 ( Mapk6 KD/KD ) exhibit a reduced postnatal growth rate as compared to control mice. Here, we show that genetic inactivation of ERK3 impairs postnatal skeletal muscle growth and adult muscle regeneration after injury. Loss of MAPK‐activated protein kinase 5 (MK5) phenocopies the muscle phenotypes of Mapk6 KD/KD mice. At the cellular level, genetic or pharmacological inactivation of ERK3 or MK5 induces precocious differentiation of C2C12 or primary myoblasts, concomitant with MyoD activation. Reciprocally, ectopic expression of activated MK5 inhibits myogenic differentiation. Mechanistically, we show that MK5 directly phosphorylates FoxO3, promoting its degradation and reducing its association with MyoD. Depletion of FoxO3 rescues in part the premature differentiation of C2C12 myoblasts observed upon inactivation of ERK3 or MK5. Our findings reveal that ERK3 and its substrate MK5 act in a linear signaling pathway to control postnatal myogenic differentiation.
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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) | 0.002 | 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".