Investigating the regulatory roles of Platelet-derived Growth Factor in the dermal stem cell niche
Bibliographic record
Abstract
Skin-derived Precursors (SKPs) are multipotent, self-renewing adult dermal stem cells able to differentiate into functional neural and mesenchymal progeny. SKPs reside within a specialized niche including both the hair follicle dermal papilla and dermal sheath and function to induce hair follicle morphogenesis and cyclic regeneration. However, the factors regulating their behavior are not understood. My work demonstrates that Platelet-derived Growth Factor (PDGF) is a key regulator of SKP function within their hair follicle niche. Using adult SKPs I show that growth in the presence of PDGF-B promotes increased SKP proliferation and self-renewal in vitro, as well as increased hair follicle formation in an ex vivo hair growth assay. Finally, my work identifies the hair follicle epithelium (outer root sheath) and potentially dermal adipocytes as a source of PDGF in the skin. Understanding this regulation will improve our ability to expand SKP numbers and quality for therapeutic application following skin injury.
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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) | 0.003 | 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".