Convergent Genesis of an Adult Neural Crest-Like Dermal Stem Cell from Distinct Developmental Origins
Bibliographic record
Abstract
Skin-derived precursors (SKPs) are multipotent dermal stem cells that reside within a hair follicle niche and that share properties with embryonic neural crest precursors. Here, we have asked whether SKPs and their endogenous dermal precursors originate from the neural crest or whether, like the dermis itself, they originate from multiple developmental origins. To do this, we used two different mouse Cre lines that allow us to perform lineage tracing: Wnt1-cre, which targets cells deriving from the neural crest, and Myf5-cre, which targets cells of a somite origin. By crossing these Cre lines to reporter mice, we show that the endogenous follicle-associated dermal precursors in the face derive from the neural crest, and those in the dorsal trunk derive from the somites, as do the SKPs they generate. Despite these different developmental origins, SKPs from these two locations are functionally similar, even with regard to their ability to differentiate into Schwann cells, a cell type only thought to be generated from the neural crest. Analysis of global gene expression using microarrays confirmed that facial and dorsal SKPs exhibit a very high degree of similarity, and that they are also very similar to SKPs derived from ventral dermis, which has a lateral plate origin. However, these developmentally distinct SKPs also retain differential expression of a small number of genes that reflect their developmental origins. Thus, an adult neural crest-like dermal precursor can be generated from a non-neural crest origin, a finding with broad implications for the many neuroendocrine cells in the body.
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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".