Prostaglandin E<sub>2</sub> inhibits profibrotic function of human pulmonary fibroblasts by disrupting Ca<sup>2+</sup> signaling
Bibliographic record
Abstract
We have shown that calcium (Ca2+) oscillations in human pulmonary fibroblasts (HPFs) contribute to profibrotic effects of transforming growth factor-β (TGF-β) and that disruption of these oscillations blunts features of pulmonary fibrosis. Prostaglandin E2 (PGE2) exerts antifibrotic effects in the lung, but the mechanisms for this action are not well defined. We thus sought to explore interactions between PGE2 and the profibrotic agent TGF-β in pulmonary fibroblasts (PFs) isolated from patients with or without idiopathic pulmonary fibrosis (IPF). PGE2 inhibited TGF-β-promoted [Ca2+] oscillations and prevented the activation of Akt and Ca2+/calmodulin-dependent protein kinase-II (CaMK-II) but did not prevent activation of Smad-2 or ERK. PGE2 also eliminated TGF-β-stimulated expression of collagen A1, fibronectin, and α-smooth muscle actin and reduced stress fiber formation in the HPFs. RNA sequencing revealed that HPFs preferentially express EP2 receptors relative to other prostanoid receptor subtypes: EP2 expression is ~10-fold higher than that of EP4 receptors; EP1 and EP3 receptors are barely detectable; and EP2-receptor expression is ~3.5-fold lower in PFs from IPF patients than in normal HPFs. The inhibitory effects of PGE2 on synthetic function and stress fiber formation were blocked by selective EP2 or EP4 antagonists and mimicked by selective EP2 or EP4 agonists, the phosphodiesterase inhibitor isobutylmethylxanthine and forskolin, all of which elevate cellular cAMP concentrations. We conclude that PGE2, likely predominantly via EP2 receptors, interferes with Ca2+ signaling, CaMK-II activation, and Akt activation in IPF-HPFs and HPFs treated with TGF-β. Moreover, a decreased expression of EP2 receptors in pulmonary fibroblasts from IPF patients may contribute to the pathophysiology of this disease.
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) | 0.000 | 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".