Anti-apoptotic Effects of Human Wharton's Jelly-derived Mesenchymal Stem Cells on Skeletal Muscle Cells Mediated via Secretion of XCL1
Bibliographic record
Abstract
The role of Wharton's jelly-derived human mesenchymal stem cells (WJ-MSCs) in inhibiting muscle cell death has been elucidated in this study. Apoptosis induced by serum deprivation in mouse skeletal myoblast cell lines (C2C12) was significantly reduced when the cell lines were cocultured with WJ-MSCs. Antibody arrays indicated high levels of chemokine (C motif) ligand (XCL1) secretion by cocultured WJ-MSCs and XCL1 protein treatment resulted in complete inhibition of apoptosis in serum-starved C2C12 cells. Apoptosis of C2C12 cells and loss of differentiated C2C12 myotubes induced by lovastatin, another muscle cell death inducer, was also inhibited by XCL1 treatment. However, XCL1 treatment did not inhibit apoptosis of cell lines other than C2C12. When XCL1-siRNA pretreated WJ-MSCs were cocultured with serum-starved C2C12 cells, apoptosis was not inhibited, thus confirming that XCL1 is a key factor in preventing C2C12 cell apoptosis. We demonstrated the therapeutic effect of XCL1 on the zebrafish myopathy model, generated by knock down of a causative gene ADSSL1. Furthermore, the treatment of XCL1 resulted in significant recovery of the zebrafish skeletal muscle defects. These results suggest that human WJ-MSCs and XCL1 protein may act as promising and novel therapeutic agents for treatment of myopathies and other skeletal muscle diseases.
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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".