PTPN1/2 inhibition promotes muscle stem cell differentiation in Duchenne muscular dystrophy
Bibliographic record
Abstract
Duchenne muscular dystrophy (DMD) is a lethal disease caused by mutations in the DMD gene that encodes dystrophin. Dystrophin deficiency also impacts muscle stem cells (MuSCs), resulting in impaired asymmetric stem cell division and myogenic commitment. Using MuSCs from DMD patients and the DMD mouse model mdx , we found that PTPN1 phosphatase expression is up-regulated and STAT3 phosphorylation is concomitantly down-regulated in DMD MuSCs. To restore STAT3-mediated myogenic signaling, we examined the effect of K884, a novel PTPN1/2 inhibitor, on DMD MuSCs. Treatment with K884 enhanced STAT3 phosphorylation and promoted myogenic differentiation of DMD patient-derived MuSCs. In MuSCs from mdx mice, K884 treatment increased the number of asymmetric cell divisions, correlating with enhanced myogenic differentiation. Interestingly, the pro-myogenic effect of K884 is specific to human and murine DMD MuSCs and is absent from control MuSCs. Moreover, PTPN1/2 loss-of-function experiments indicate that the pro-myogenic impact of K884 is mediated mainly through PTPN1. We propose that PTPN1/2 inhibition may serve as a therapeutic strategy to restore the myogenic function of MuSCs in DMD.
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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".