Modulation of Leukotriene B4 Receptor-1 Expression by Dexamethasone: Potential Mechanism for Enhanced Neutrophil Survival
Bibliographic record
Abstract
Glucocorticoids can down-regulate many inflammatory and immune responses and constitute a powerful therapeutic tool in a number of diseases. However, they have a somewhat paradoxical effect on neutrophils, in that they prolong their survival. Because leukotriene B(4) (LTB(4)) can also extend neutrophil survival, we proposed that glucocorticoids could prevent neutrophil apoptosis by up-regulating their expression of the high-affinity LTB(4) receptor (BLT1). Here we show that, indeed, dexamethasone (DEX) up-regulates the steady-state levels of BLT1 mRNA in human neutrophils. The effect was time and concentration dependent, being maximal at 4 h and at 10-100 nM DEX. The effect was also dependent on transcriptional activity, whereas BLT1 mRNA stability was not affected. DEX-induced up-regulation of BLT1 expression was prevented by pretreatment with the LTB(4) antagonist LY255283. Moreover, LTB(4) itself up-regulated the expression of BLT1 mRNA. BLT1 protein expression on neutrophils exposed to DEX for 24 h was also up-regulated 2- to 3-fold, and DEX-treated as well as LTB(4)-treated cells showed enhanced responsiveness to LTB(4) in terms of intracellular Ca(2+) mobilization and chemotaxis. Whereas DEX and LTB(4) alone decreased neutrophil apoptosis by approximately 50%, neutrophils treated with both LTB(4) and DEX showed >90% survival at 24 h. Moreover, BLT1 antagonists prevented the increased neutrophil survival induced by DEX as well as by LTB(4). Taken together, our results suggest that DEX-induced up-regulation of BLT1 expression in neutrophils may be one mechanism through which glucocorticoids can prolong neutrophil survival, namely by enhancing cell responses to the antiapoptotic effect of LTB(4).
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".