Novel differences in gene expression and functional capabilities of myofibroblast populations in idiopathic pulmonary fibrosis
Bibliographic record
Abstract
Idiopathic pulmonary fibrosis (IPF), a chronic progressive interstitial pneumonia, is characterized by excessive fibroproliferation. Key effector cells in IPF are myofibroblasts that are recruited from three potential sources: resident fibroblasts, fibrocytes, and epithelial cells. We hypothesized that IPF myofibroblasts from different sources display unique gene expression differences and distinct functional characteristics. Primary human pulmonary fibroblasts (normal and IPF), fibrocytes, and epithelial cells were activated using the profibrotic factors TGF-β and TNF-α. The resulting myofibroblasts were characterized using cell proliferation, soluble collagen, and contractility assays, ELISA, and human fibrosis PCR arrays. Genes of significance in human whole lung were validated by immunohistochemistry on human lung sections. Fibroblast-derived myofibroblasts exhibited the greatest increase in expression of profibrotic genes and genes involved in extracellular matrix remodeling and signal transduction. Functional studies demonstrated that myofibroblasts derived from fibrocytes expressed mostly soluble collagen and chemokine (C-C) motif ligand (CCL) 18 but were the least proliferative of the myofibroblast progeny. Activated IPF fibroblasts displayed the highest levels of contractility and CCL2 production. This study identified novel differences in gene expression and functional characteristics of different myofibroblast populations. Further investigation into the myofibroblast phenotype may lead to potential therapeutic targets in future IPF research.
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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".