Injury modifies the fate of hair follicle dermal stem cell progeny in a hair cycle‐dependent manner
Bibliographic record
Abstract
Abstract The dermal papilla ( DP ) is one of two principal mesenchymal compartments of the hair follicle ( HF ). We previously reported that a population of HF dermal stem cells (hf DSC s) function to regenerate the dermal sheath ( DS ), but intriguingly also contribute new cells to the adult DP at the onset of anagen hair growth to maintain normal cycling of HF s and support the production of large hair fibres. Here, we asked whether injury altered the behaviour of hf DSC s and their progeny in order to support wound‐induced hair growth ( WIHG ) and if the response was modulated by hair cycle stage. α SMAC re ER T 2 : ROSA YFP mice received tamoxifen to label the DS , including hf DSC s. Full‐thickness excisions were made on the dorsal skin during various stages of the hair cycle. The skin was harvested at the subsequent anagen. Interestingly, there was an increase in the magnitude of recruitment of hf DSC progeny into the DP after injury compared to follicles entering natural second anagen. This bias towards a DP fate only occurred when a wound was induced during certain stages of the HC . In summary, injury modifies the fate of hf DSC s progeny, biasing them towards recruitment into the DP , with the hair cycle stage also influencing this response.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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 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".