Leukotriene B <sub>4</sub> -Mediated Release of Antimicrobial Peptides against Cytomegalovirus Is BLT1 Dependent
Bibliographic record
Abstract
Leukotriene B4 (LTB(4)) is a potent lipid mediator of inflammation that possesses antiviral activities. Here we provide evidence that LTB(4)-mediated defense against in vitro cytomegalovirus (CMV) infection of human leukocytes involves activation of the high-affinity LTB(4) receptor (BLT1) and neutrophil degranulation. Treatment of CMV-infected peripheral blood leukocytes with LTB(4) (10 nM) leads to a significant reduction in viral titers. This activity involves neutrophil activation through the BLT1 receptor, because no reduction in viral titers was observed after neutrophil depletion from cellular preparation or when leukocytes were pretreated with the BLT1 antagonist U75,302. Direct stimulation of neutrophils with LTB(4) (in the presence or absence of CMV) leads to the release of myeloperoxidase, alpha-defensins, eosinophil-derived neurotoxin, and the human cathelicidin LL-37 in a BLT1-dependent manner. LTB(4) does not act exclusively on the secretion of preformed antimicrobial peptides, but also acts on the synthesis of selected peptides as reflected by the increase in transcriptional levels of eosinophil-derived neurotoxin (EDN) and LL-37 in LTB(4)-treated neutrophils. Treatment of cell cultures with neutralizing antibodies directed against alpha-defensins, EDN, and LL-37 significantly reduces the antiviral effect of LTB(4), suggesting that LTB(4) may act through the release of antimicrobial peptides. Ex vivo experiments using LTB(4)-treated neutrophils from peritoneal washing of wild-type and BLT1 knockout mice further supported the role played by antimicrobial peptides in LTB(4)-mediated antiviral activity toward CMV. These results provide evidence of a mechanism by which LTB(4) induces host defense against viral infection.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".