CD56+ Muscle Derived Cells but Not Retinal NG2+ Perivascular Cells of Nonhuman Primates are Myogenic after Intramuscular Transplantation in Immunodeficient Mice
Bibliographic record
Abstract
Some reports attributed to pericytes and other perivascular cells (PCs), regardless of their origin, optimal properties for cell therapy in myology.The retina is an ideal tissue to obtain pericytes and one study reported that PCs from the mouse retina were myogenic in vitro.Given the importance of nonhuman primates (NHPs) for translational research, we compared the in vivo myogenicity of NHP retinal PCs and satellite cell derived myoblasts (SCDMs) by transplantation in immunodeficient mice.We used a protocol to culture retinal pericytes of large mammals with macaque retinas.By flow cytometry, 76%-78% of the cultured cells were NG2+.CD56+ SCDMs from another macaque were proliferated in vitro.Both Tibialis anterior muscles of 4 SCID mice were injected with 1x106 cells in saline (SCDMs in the right muscles and PCs in the left), using cardiotoxin to induce muscle regeneration.They were sampled 1 month later and analyzed by histology.In SCDM-grafted muscles, NHP nuclei were abundant, in large regions with numerous NHP-derived myofibers, and some of them were Pax7+.PC-grafted muscles showed no muscle regeneration, have few NHP nuclei in small regions devoid of myofibers, and no NHP-myofibers or Pax7+ NHP nuclei were observed.Therefore, NHP SCDMs, but not retinal NG2+ PCs, regenerated muscle in vivo in immunodeficient mice.
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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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".