Toll‐like receptor ligands induce polymorphonuclear leukocyte migration: key roles for leukotriene B <sub>4</sub> and platelet‐activating factor
Bibliographic record
Abstract
Activation of toll-like receptors (TLRs) and polymorphonuclear leukocyte (PMN) accumulation at infection sites are critical events of host defense. The involvement of leukotriene (LT) B(4) and platelet-activating factor (PAF) in TLR ligand-induced activation of inflammatory cell functions is essentially unknown. Using an in vitro model of human PMN migration through human endothelial cell monolayers, we demonstrate that prototypic ligands of TLR1/2, 2/6, 3, 4, 5, and 7/8 promote PMN migration, an effect markedly inhibited by 3 LTB(4) receptor antagonists (70-80% inhibition at 100 nM compared to vehicle-treated cells), 3 PAF receptor antagonists (20-50% inhibition at 10 nM), 3 LT biosynthesis inhibitors (75-85% inhibition at 100 nM), and 1 cytosolic phospholipase A(2)alpha (cPLA(2)alpha) inhibitor (90% inhibition at 1 microM). Accordingly, selected TLR ligands caused Ser-505-phosphorylation of cPLA(2)alpha and measurable LTB(4) and PAF biosynthesis in the transmigration assay. As negative controls, interleukin-8- and formyl-methionyl-leucyl-phenylalanine-elicited migration in vitro was not inhibited either by an LTB(4) receptor antagonist or by the cPLA(2)alpha inhibitor. Finally, LTB(4) and PAF receptor antagonists inhibited (up to approximately 65% at optimal doses) TLR ligand-induced PMN infiltration in the mouse air-pouch model. These studies unravel the critical involvement of de novo LTB(4) and PAF biosynthesis in PMN migration elicited by TLR ligands.
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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 | 0.001 | 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) | 0.000 | 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".