Skin-Derived Precursors Differentiate Into Skeletogenic Cell Types and Contribute to Bone Repair
Why this work is in the frame
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Bibliographic record
Abstract
Skin-derived precursors (SKPs) are multipotent dermal precursors that share similarities with neural crest stem cells and that can give rise to peripheral neural and some mesodermal cell types, such as adipocytes. Here, we have asked whether rodent or human SKPs can generate other mesenchymally derived cell types, with a particular focus on osteocytes and chondrocytes. In culture, rodent and human foreskin-derived SKPs differentiated into alkaline-positive, collagen type-1-positive, mineralizing osteocytes, and into collagen type-II-positive chondrocytes that secreted chondrocyte-specific proteoglycans. Clonal analysis demonstrated that SKPs efficiently generated these skeletogenic cell types, and that they were multipotent with regard to the osteogenic and chondrogenic lineages. To ask if SKPs could generate these same lineages in vivo, genetically tagged, undifferentiated rat SKPs were transplanted into a tibial bone fracture model. Over the ensuing 6 weeks, many of the transplanted cells survived within the bone callus, where they were morphologically and phenotypically similar to the endogenous mesenchymal/osteogenic cells. Moreover, some transplanted cells adopted a mature osteocyte phenotype and integrated into the newly formed bone. Some transplanted cells also differentiated into chondrocytes and into smooth muscle cells and/or pericytes that were associated with blood vessels. Thus, both rodent and human SKPs generate skeletogenic cell types in culture, and the injured bone environment is sufficient to instruct SKPs to differentiate down an osteogenic lineage, in a fashion similar to the endogenous mesenchymal precursors.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it