PDGFRα and αSMA mark two distinct mesenchymal cell populations involved in parenchymal and vascular remodeling in pulmonary fibrosis
Bibliographic record
Abstract
Pulmonary fibrosis is characterized by pronounced collagen deposition and myofibroblast expansion, whose origin and plasticity remain elusive. We utilized a fate-mapping approach to investigate α-smooth muscle actin (αSMA)+ and platelet-derived growth factor receptor α (PDGFRα)+ cells in two lung fibrosis models, complemented by cell type-specific next-generation sequencing and investigations on human lungs. Our data revealed that αSMA+ and PDGFRα+ cells mark two distinct mesenchymal lineages with minimal transdifferentiation potential during lung fibrotic remodeling. Parenchymal and perivascular fibrotic regions were populated predominantly with PDGFRα+ cells expressing collagen, while αSMA+ cells in the parenchyma and vessel wall showed variable expression of collagen and the contractile protein desmin. The distinct gene expression profile found in normal conditions was retained during pathologic remodeling. Cumulatively, our findings identify αSMA+ and PDGFRα+ cells as two separate lineages with distinct gene expression profiles in adult lungs. This cellular heterogeneity suggests that anti-fibrotic therapy should target diverse cell populations.
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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".