Inhibition of platelet-activating factor biosynthesis by adenosine and histamine in human neutrophils: involvement of cPLA2α and reversal by lyso-PAF
Bibliographic record
Abstract
Leukotrienes (LT) and platelet-activating factor (PAF) are important lipid mediators of inflammation. We and others reported previously that autacoids such as adenosine, histamine, prostaglandin E2, and beta-adrenergic agents inhibit LT biosynthesis in activated human polymorphonuclear leukocytes (PMN). In this study, we demonstrate that CGS-21680 (a selective agonist of the adenosine A2A receptor) and histamine also potently inhibit PAF biosynthesis in agonist [formyl Met-Leu-Phe (fMLP)]- and thapsigargin-activated human PMN. The observed inhibitions of PAF biosynthesis were reversed effectively by exogenous 1-O-alkyl-lyso-sn-glyceryl-3-phosphocholine (lyso-PAF), suggesting that these effects of CGS-21680 and histamine implicate the blockade of cytosolic phospholipase A2alpha (cPLA2alpha) activity and lyso-PAF release and that the acetyl-coenzyme A/lyso-PAF acetyl transferase is not inhibited by the autacoids. Accordingly, the cPLA2alpha inhibitor pyrrophenone completely blocked PAF formation, and lyso-PAF similarly prevented this effect of pyrrophenone. The inhibitory effects of CGS-21680 and histamine on PAF biosynthesis were prevented by the protein kinase A inhibitor H-89, supporting roles for the Gs -coupled receptors A2A and H2, respectively, and cyclic adenosine monophosphate in the inhibitory mechanism. The fMLP-induced phosphorylations of p38 and extracellular signal-regulated kinase 1/2 were not altered significantly by the CGS-21680, indicating that inhibition of these kinases is not involved in the inhibitory effect of the adenosine A2A receptor ligand on LT and PAF biosynthesis. These data further emphasize the multiple and potent inhibitory effects of adenosine and histamine on leukocyte functions, in particular, on the biosynthesis of two classes of important lipid mediators and their putative regulatory roles in immune processes in health and diseases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".