Mutual antagonistic relationship between prostaglandin E<sub>2</sub> and IFN‐γ: Implications for rheumatoid arthritis
Bibliographic record
Abstract
Prostaglandin E(2) (PGE(2)) is a major mediator of inflammation and is present at high concentrations in the synovial fluid of rheumatoid arthritis (RA) patients. PGE(2), acting through the EP4 receptor, has both pro- and anti-inflammatory roles in vivo. To shed light on this dual role of PGE(2), we investigated its effects in whole blood and in primary human fibroblast-like synoviocytes (FLS). Gene expression analysis in human leukocytes, confirmed at the protein level, revealed an EP4-dependent inhibition of the expression of genes involved in the IFN-gamma-activation pathway, including IFN-gamma itself. This effect of the PGE(2)/EP4 axis on IFN-gamma is a reciprocal phenomenon since IFN-gamma blocks PGE(2) release and blocks EP receptor expression. The mutually antagonistic relationship between IFN-gamma and PGE(2) extends to downstream cytokine and chemokine release; PGE(2) counters the effects of IFN-gamma, on the release of IP-10, IL-8, TNF-alpha and IL-1beta. To gain further insight into IFN-gamma-mediated cellular events in RA, we assessed the effects of IFN-gamma on gene expression in FLS. We observed an IFN-gamma-dependent up-regulation of macrophage-attracting chemokines, and down-regulation of metalloprotease expression. These results suggest the existence of a mutually antagonistic relationship between PGE(2) and IFN-gamma, which may represent a fundamental mechanism of immune control in diseases such as RA.
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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".