Bibliographic record
Abstract
Skeletal muscle contains multiple progenitor populations of distinct embryonic origins and developmental potential. Myogenic progenitors, usually residing in a "satellite cell position" between the myofiber plasma membrane and the laminin-rich basement membrane that ensheaths it, are self-renewing cells that are solely committed to the myogenic lineage. We have recently described a second class of vessel associated progenitors that can generate myofibroblasts and white adipocytes, which responds to damage by efficiently entering proliferation and provides trophic support to myogenic cells during tissue regeneration. One of the most trusted assays to determine the developmental and regenerative potential of a given cell population relies on their isolation and transplantation. To this end we have optimized protocols for their purification by flow cytometry from enzymatically dissociated muscle, which we will outline in this article. The populations obtained using this method will contain either myogenic or fibro/adipogenic colony forming cells: no other cell types are capable of expanding in vitro or surviving in vivo delivery. However, when these populations are used immediately after the sort for molecular analysis (e.g qRT-PCR) one must keep in mind that the freshly sorted subsets may contain other contaminant cells that lack the ability of forming colonies or engrafting recipients.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.006 |
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".