Faculty Opinions recommendation of In vivo fate mapping identifies mesenchymal progenitor cells.
Bibliographic record
Abstract
Adult mesenchymal progenitor cells have enormous potential for use in regenerative medicine. However, the true identity of the progenitors in vivo and their progeny has not been precisely defined. We hypothesize that cells expressing a smooth muscle α-actin promoter (αSMA)-directed Cre transgene represent mesenchymal progenitors of adult bone tissue. By combining complementary colors in combination with transgenes activating at mature stages of the lineage, we characterized the phenotype and confirmed the ability of isolated αSMA(+) cells to progress from a progenitor to fully mature state. In vivo lineage tracing experiments using a new bone formation model confirmed the osteogenic phenotype of αSMA(+) cells. In vitro analysis of the in vivo-labeled SMA9(+) cells supported their differentiation potential into mesenchymal lineages. Using a fracture-healing model, αSMA9(+) cells served as a pool of fibrocartilage and skeletal progenitors. Confirmation of the transition of αSMA9(+) progenitor cells to mature osteoblasts during fracture healing was assessed by activation of bone-specific Col2.3emd transgene. Our findings provide a novel in vivo identification of defined population of mesenchymal progenitor cells with active role in bone remodeling and regeneration.Copyright © 2011 AlphaMed Press. PMID: 22083974 Funding information This work was supported by: NIAMS NIH HHS, United States Grant ID: R01 AR055607 NIAMS NIH HHS, United States Grant ID: AR059315-01 NIAMS NIH HHS, United States Grant ID: AR055607-01 NIAMS NIH HHS, United States Grant ID: AR043457 NHLBI NIH HHS, United States Grant ID: 1RC1HL100569-01
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.649 | 0.465 |
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".