The endothelium in lung fibrosis: a core signaling hub in disease pathogenesis?
Bibliographic record
Abstract
Pulmonary fibrosis (PF) is a progressive chronic lung disease characterized by excessive deposition of extracellular matrix (ECM) and structural destruction, associated with a severe 5-year mortality rate. The onset of the disease is thought to be triggered by chronic damage to the alveolar epithelium. Since the pulmonary endothelium is an important component of the alveolar-capillary niche, it is also affected by the initial injury. In addition to ensuring proper gas exchange, the endothelium has critical functional properties, including regulation of vascular tone, inflammatory responses, coagulation, and maintenance of vascular homeostasis and integrity. Recent single-cell analyses have shown that shifts in endothelial cell (EC) subtypes occur in PF. Furthermore, the increased vascular remodeling associated with PF leads to deteriorated outcomes for patients, underscoring the importance of the vascular bed in PF. To date, the causes and consequences of endothelial and vascular involvement in lung fibrosis are poorly understood. Therefore, it is of great importance to investigate the involvement of EC and the vascular system in the pathogenesis of the disease. In this review, we will outline the current knowledge on the role of the pulmonary vasculature in PF, in terms of abnormal cellular interactions, hyperinflammation, vascular barrier disorders, and an altered basement membrane composition. Finally, we will summarize recent advances in extensive therapeutic research and discuss the significant value of novel therapies targeting the endothelium.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".