1,25-Dihydroxyvitamin D <sub>3</sub> Increases the Transplantation Success of Human Muscle Precursor Cells in SCID Mice
Bibliographic record
Abstract
Human muscle precursor cell (hMPC) transplantation is a potential therapy for severe muscle trauma or myopathies. Some previous studies demonstrated that 1,25-dihydroxyvitamin-D3 (1,25-D3) acted directly on myoblasts, regulating their proliferation and fusion. 1,25-D3 is also involved in apoptosis modulation of other cell types and may thus contribute to protect the transplanted hMPCs. We have therefore investigated whether 1,25-D3 could improve the hMPC graft success. The 1,25-D3 effects on hMPC proliferation, fusion, and survival were initially monitored in vitro. hMPCs were also grafted in the tibialis anterior of SCID mice treated or not with 1,25-D3 to determine its in vivo effect. Graft success, proliferation, and viability of transplanted hMPCs were evaluated. 1,25-D3 enhanced proliferation and fusion of hMPCs in vitro and in vivo. However, 1,25-D3 did not protect hMPCs from various proapoptotic factors (in vitro) or during the early posttransplantation period. 1,25-D3 enhanced hMPC graft success because the number of muscle fibers expressing human dystrophin was significantly increased in the TA sections of 1,25-D3-treated mice (166.75 +/- 20.64) compared to the control mice (97.5 +/- 16.58). This result could be partly attributed to the improvement of the proliferation and differentiation of hMPCs in the presence of 1,25-D3. Thus, 1,25-D3 administration could improve the clinical potential of hMPC transplantation currently developed for muscle trauma or myopathies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".