Identification of a putative pathway for the muscle homing of stem cells in a muscular dystrophy model
Bibliographic record
Abstract
Attempts to repair muscle damage in Duchenne muscular dystrophy (DMD) by transplanting skeletal myoblasts directly into muscles are faced with the problem of the limited migration of these cells in the muscles. The delivery of myogenic stem cells to the sites of muscle lesions via the systemic circulation is a potential alternative approach to treat this disease. Muscle-derived stem cells (MDSCs) were obtained by a MACS(R) multisort method. Clones of MDSCs, which were Sca-1+/CD34-/L-selectin+, were found to adhere firmly to the endothelium of mdx dystrophic muscles after i.v. or i.m. injections. The subpopulation of Sca-1+/CD34- MDSCs expressing L-selectin was called homing MDSCs (HMDSCs). Treatment of HMDSCs with antibodies against L-selectin prevented adhesion to the muscle endothelium. Importantly, we found that vascular endothelium from striate muscle of young mdx mice expresses mucosal addressin cell adhesion molecule-1 (MAdCAM-1), a ligand for L-selectin. Our results showed for the first time that the expression of the adhesion molecule L-selectin is important for muscle homing of MDSCs. This discovery will aid in the improvement of a potential therapy for muscular dystrophy based on the systemic delivery of MDSCs.
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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 | 0.001 | 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) | 0.003 | 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".