Effects of pyrrophenone, an inhibitor of group IVA phospholipase A<sub>2</sub>, on eicosanoid and PAF biosynthesis in human neutrophils
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The biosynthesis of leukotrienes (LT) and platelet-activating factor (PAF) involves the release of their respective precursors, arachidonic acid (AA) and lyso-PAF by the group IVA PLA2 (cPLA2alpha). This paper aims at characterizing the inhibitory properties of the cPLA2alpha inhibitor pyrrophenone on eicosanoids and PAF in human neutrophils (PMN). EXPERIMENTAL APPROACH: Freshly isolated human PMN were activated with physiological and pharmacological agents (fMLP, PAF, exogenous AA, A23187 and thapsigargin) in presence and absence of the cPLA2alpha inhibitor pyrrophenone and biosynthesis of LT, PAF, and PGE2 was measured. KEY RESULTS: Pyrrophenone potently inhibited LT, PGE2 and PAF biosynthesis in PMN with IC50s in the range of 1-20 nM. These inhibitory effects of pyrrophenone were specific (the consequence of substrate deprivation), as shown by the reversal of inhibition by exogenous AA and lyso-PAF. Comparative assessment of pyrrophenone, methyl-arachidonoyl-fluoro-phosphonate (MAFP) and arachidonoyl-trifluoromethylketone (AACOCF3) demonstrated that pyrrophenone was more specific and 100-fold more potent than MAFP and AACOCF3 for the inhibition of LT biosynthesis in A23187-activated PMN. The inhibitory effect of pyrrophenone on LT biosynthesis was reversible as LT biosynthesis was recovered when pyrrophenone-treated PMN were washed with autologous plasma. No alteration of phospholipase D (PLD) activity in fMLP-activated PMN was observed with up to 10 microM pyrrophenone, suggesting that the cPLA2alpha inhibitor does not directly inhibit PLD. CONCLUSIONS AND IMPLICATIONS: Pyrrophenone is a more potent and specific cPLA2alpha inhibitor than MAFP and AACOCF3 and represents an excellent pharmacological tool to investigate the biosynthesis and the biological roles of eicosanoids and PAF.
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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) | 0.001 | 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".