P021 <break /> 15-deoxy-Δ12,14-Prostaglandin J2 inhibits TGFβ–induced lung epithelial cell changes associated with pulmonary fibrosis
Bibliographic record
Abstract
Rationale: Glutathione (GSH) concentration in the lung epitheial lining fluid (ELF) of the healthy alveolus is high, but is markedly deficient in the ELF of patients with idiopathic pulmonary fibrosis (IPF). TGF-β1 suppresses the transcription of the gene encoding glutamate-cysteine ligase catalytic subunit (GCLC), the rate-limiting enzyme in GSH synthesis. Patients with IPF also demonstrate increased epithelial to mesenchymal transition (EMT). Hypothesis: We hypothesized that the Nrf2 and PPARγ agonist, prostaglandin J2 (15d-PGJ2) inhibits TGFß-induced alveolar epithelial cell GSH depletion and EMT. Methods: The human alveolar epithelial cells A549 were exposed to 5 ng/ml TGF-β1 for 0 - 72 hours with or without 0 - 10 µM 15d-PGJ2. Nrf2 and PPARγ-dependent promoter transactivation were determined using luciferase assay. GSH content and the expression of the EMT marker vimentin were analyzed upon cellular treatments. Results: Nrf2 and PPARγ-dependent gene transcription were both increased by 15d-PGJ2. 15d-PGJ2 induced a concentration-dependent increase in cellular GSH. TGF-β1 depleted cellular GSH, altered cell morphology and markedly increased the expression of the EMT marker, vimentin. The addition of 5 µM 15d-PGJ2 completely prevented GSH depletion and vimentin increase by TGF-β1. Lung hydroxyproline content in mice exposed to bleomycin was also decreased by daily treatment with 15d-PGJ2 (25µg s.c.) for 14 days. Conclusions: We conclude that 15d-PGJ2, a potent agonist of Nrf2 and PPARγ transcription pathways prevents TGFβ-induced lung epithelial cell changes in GSH content and in vimentin expression. Importantly, 15d-PGJ2 prevents lung fibrosis associated with bleomycin.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".