20-Hydroxy- and 20-carboxy-leukotriene (LT) B4 downregulate LTB4-mediated responses of human neutrophils and eosinophils
Bibliographic record
Abstract
Abstract Leukotriene B4 (LTB4) plays a prominent role in innate immunity as it induces phagocyte recruitment, the release of antimicrobial effectors, and as it potentiates the ingestion and killing of pathogens. In humans, LTB4 has a short half-life and is rapidly metabolized by leukocytes, notably into 20-OH- and 20-COOH-LTB4 by neutrophils. Although these LTB4 metabolites bind to the BLT1 receptor with high affinity, they activate neutrophils to a much lower extent than LTB4. We thus postulated that LTB4 metabolites could dampen BLT1-mediated responses, therefore limiting the impact of LTB4 on human neutrophil functions. We found that 20-OH-LTB4 and 20-COOH-LTB4 inhibited all of the LTB4-mediated neutrophil responses we tested (migration, degranulation, leukotriene biosynthesis). The potencies of the different compounds at inhibiting LTB4-mediated responses were 20-OH-LTB4 = CP 105,696 (BLT1 antagonist) > > 20-COOH-LTB4 ≥ resolvin E1 (RVE1). In contrast, the fMLP- and IL-8-mediated responses we tested were not affected by the LTB4 metabolites or RVE1. 20-OH-LTB4 and 20-COOH-LTB4 also inhibited the LTB4-mediated migration of human eosinophils but not that induced by 5-KETE. Moreover, using 20-COOH-LTB4, LTB4, and LTB4-alkyne, we show that LTB4 is a chemotactic, rather than a chemokinetic factor for both human neutrophils and eosinophils. In conclusion, our data indicate that LTB4 metabolites and RVE1 act as natural inhibitors of LTB4-mediated responses. Thus, preventing LTB4 ω-oxidation might result in increased innate immunity and granulocyte functions.
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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) | 0.001 | 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".