Lineage tracing of Foxd1‐expressing embryonic progenitors to assess the role of divergent embryonic lineages on adult dermal fibroblast function
Bibliographic record
Abstract
Abstract Recent studies have highlighted the functional diversity of dermal fibroblast populations in health and disease, with part of this diversity linked to fibroblast lineage and embryonic origin. Fibroblasts derived from foxd1‐expressing progenitors contribute to the myofibroblast populations present in lung and kidney fibrosis in mice but have not been investigated in the context of dermal wound repair. Using a Cre/Lox system to genetically track populations derived from foxd1‐expressing progenitors, lineage‐positive fibroblasts were identified as a subset of the dermal fibroblast population. During development, lineage‐positive cells were most abundant within the dorsal embryonic tissues, contributing to the developing dermal fibroblast population, and remaining in this niche into adulthood. In adult mice, assessment of fibrosis‐related gene expression in lineage‐positive and lineage‐negative populations isolated from wounded and unwounded dorsal skin was performed, identifying an enrichment of transcripts associated with matrix synthesis and remodeling in the lineage‐positive populations. Using a novel excisional wound model, ventral skin healed with a greatly reduced frequency of foxd1 lineage‐positive cells. This work supports that the embryonic origin of fibroblasts is an important predictor of fibroblast function, but also highlights that within disparate regions, fibroblasts of different lineages likely undergo convergent differentiation contributing to phenotypic similarities.
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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 | 0.000 |
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".