Prostaglandin E<sub>2</sub> inhibits neutrophil extracellular trap formation through production of cyclic AMP
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Upon stimulation, neutrophils release their nuclear contents called neutrophil extracellular traps (NETs), which contain unfolded chromatin and lysosomal enzymes. NETs have been demonstrated to play a critical role in host defence, although the role of PGE2 , a bioactive substance generated in inflammatory tissues, in the formation of NETs remains unclear. EXPERIMENTAL APPROACH: The effects of PGE2 , agonists and antagonists of its receptors, and modulators of the cAMP-PKA pathway on the formation of NETs were examined in vitro in isolated neutrophils and in vivo in a newly established mouse model. KEY RESULTS: PGE2 inhibited PMA-induced NET formation in vitro through EP2 and EP4 Gαs-coupled receptors. Incubation with a cell-permeable cAMP analogue, dibutyryl cAMP, or various inhibitors of a cAMP-degrading enzyme, PDE, also suppressed NET formation. In the assay established here, where an agarose gel was s.c. implanted in mice and NET formation was detected on the surface of the gel, the extent of the NET formed was inhibited in agarose gels containing rolipram, a PDE4 inhibitor, and butaprost, an EP2 receptor agonist. CONCLUSIONS AND IMPLICATIONS: PGE2 inhibits NET formation through the production of cAMP. These findings will contribute to the development of novel treatments for NETosis-related diseases.
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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 | 0.000 |
| 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".