Potential contribution of precursor cells to vascular remodeling in the AdTGF-β1 model of lung fibrosis and pulmonary hypertension
Bibliographic record
Abstract
Pulmonary hypertension (PH) is associated with increased mortality in patients with idiopathic pulmonary fibrosis (IPF). The interaction between the fibrotic process and the pulmonary vasculature is incompletely understood. There is evidence in human and experimental pulmonary fibrosis that precursor cells may play a role in fibrogenesis, and that precursor cells may also be important for vascular remodeling in chronic models of pulmonary hypertension (PH). But the contribution of precursor cells to vascular remodeling and PH in pulmonary fibrosis has not been investigated yet. This study aimed to investigate the potential contribution of precursor cells to vascular remodeling in the AdTGF-β1 model of lung fibrosis and PH. Female Sprague Dawley rats received AdTGF-β1 or AdDL70 and were sacrificed at different time points (7, 14 and 28 days). Immunofluorescence stainings were performed on 3 μm sections of the left lung after formalin fixation. We detected cells expressing markers of endothelial progenitor cells (CD133/vWF, c-kit/vWF, CD133/VEGFR-2) in pulmonary arteries of AdTGF-β1 animals, mainly after 14 days. We also found cells expressing markers of fibrocytes (CXCR4/α-SMA, CXCR4/prolyl-4-hydroxylase, S100A4/CD34), around pulmonary arteries of AdTGF-β1 animals. In contrast, we did not find such cells in or around pulmonary arteries in AdDL70 treated animals. In conclusion, our data support the concept that precursor cells may contribute to postapoptotic vascular repair and pulmonary artery muscularization in experimental lung fibrosis. The detailed mechanisms of precursor cell attraction and activation are currently under investigation.
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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 | 0.001 | 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 | 0.001 |
| 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".