Leukotriene B4 Induces Release of Antimicrobial Peptides in Lungs of Virally Infected Mice
Bibliographic record
Abstract
Leukotriene B(4) (LTB(4)) is a lipid mediator of inflammation that was recently shown to exert antiviral activities. In this study, we demonstrate that the release of antimicrobial proteins by neutrophils contribute to an early host defense against influenza virus infection in vitro as well as in vivo. Daily i.v. treatments with LTB(4) lead to a significant decrease in lung viral loads at day 5 postinfection in mice infected with influenza A virus compared with the placebo-treated group. This reduction in viral load was not present in mice deficient in the high-affinity LTB(4) receptor. Viral clearance in lungs was associated with up-regulated presence of antimicrobial peptides such as beta-defensin-3, members of the mouse eosinophil-related RNase family, and the mouse cathelicidin-related antimicrobial peptide. Our results also indicate that neutrophils are important in the antiviral effect of LTB(4). Viral loads in neutrophil-depleted mice were not diminished by LTB(4) administration, and a substantial reduction in the presence of murine cathelicidin-related antimicrobial peptide and the murine eosinophil-related RNase family in lung tissue was observed. Moreover, in vitro treatment of human neutrophil cultures with LTB(4) led rapidly to the secretion of the human cathelicidin LL-37 and eosinophil-derived neurotoxin, known as antiviral peptides. Pretreatment of cell cultures with specific LTB(4) receptor antagonists clearly demonstrate the implication of the high-affinity LTB(4) receptor in the LTB(4)-mediated activity. Together, these results demonstrate the importance of neutrophils and the secretion of antimicrobial peptides during the early immune response mediated by LTB(4) against a viral pathogen.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".