Directed Differentiation of Skin-Derived Precursors Into Functional Vascular Smooth Muscle Cells
Bibliographic record
Abstract
OBJECTIVE: The goal of this study was to characterize the factors and conditions required for smooth muscle cell (SMC)-directed differentiation of Sox2(+) multipotent rat and human skin-derived precursors (SKPs) and to define whether they represent a source of fully functional vascular SMCs for applications in vivo. METHODS AND RESULTS: We found that rat SKPs can differentiate almost exclusively into SMCs by reducing serum concentrations to 0.5% to 2% and plating them at low density. Human SKPs derived from foreskin required the addition of transforming growth factor-β1 or -β3 to differentiate into SMCs, but they did so even in the absence of serum. SMC formation was confirmed by quantitative reverse transcription-polymerase chain reaction, immunocytochemistry, and fluorescence-activated cell sorting, with increased expression of smoothelin-B and little to no expression of telokin or smooth muscle γ-actin, together indicating that SKPs differentiated into vascular rather than visceral SMCs. Rat and human SKP-derived SMCs were able to contract in vitro and also wrap around and support new capillary and larger blood vessel formation in angiogenesis assays in vivo. CONCLUSIONS: SKPs are Sox2(+) progenitors that represent an attainable autologous source of stem cells that can be easily differentiated into functional vascular SMCs in defined serum-free conditions without reprogramming. SKPs represent a clinically viable cell source for potential therapeutic applications in neovascularization.
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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 | 0.000 | 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) | 0.001 | 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".