Role of the COX2-PGE<sub>2</sub> axis in <i>S. pneumoniae</i>-induced exacerbation of experimental fibrosis
Bibliographic record
Abstract
Idiopathic pulmonary fibrosis (IPF) is an interstitial lung disease (ILD) associated with high morbidity and mortality. Patients with ILD frequently develop an acute exacerbation of their disease, which may be triggered by viral and/or bacterial infections. Prostaglandin E2 (PGE2) is an eicosanoid released in a cyclooxygenase-2 (COX2)–dependent manner and is considered to contribute to regulation of lung fibrosis. However, its role in infection-induced exacerbation of lung fibrosis is poorly defined. We found significantly increased levels of PGE2 in lung tissue of patients with ILD. Increased levels of PGE2 were also found in lung tissue of mice with AdTGF-β1–induced lung fibrosis and even more so in Streptococcus pneumoniae exacerbated lung fibrosis. Type II alveolar epithelial cells (AT II cells) and alveolar macrophages (AM) contributed to PGE2 release during exacerbating fibrosis. Application of parecoxib to inhibit PGE2 synthesis ameliorated lung fibrosis, whereas intratracheal application of PGE2 worsened lung fibrosis in mice. Both interventions had no effect on S. pneumoniae-exacerbated lung fibrosis. Together, we found that the COX2-PGE2 axis has dual roles in fibrosis that may offset each other: PGE2 helps resolve infection/attenuate inflammation in fibrosis exacerbation but accentuates TGF-β/AT II cell–mediated fibrosis. These data support the efficacy of COX/PGE2 interventions in the setting of non-exacerbating lung fibrosis
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.001 | 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".