Interleukin-12 Inhibits Eosinophil Degranulation and Migration but Does Not Promote Eosinophil Apoptosis
Bibliographic record
Abstract
BACKGROUND: Animal and human studies demonstrated that interleukin (IL)-12, a Th1 cytokine, reduces blood and bronchial eosinophilia, and airway hyperreactivity. According to current concepts, these effects are mediated through the release of cytokines promoting eosinophil recruitment and activation. However, the presence of IL-12 receptors on eosinophils suggests that IL-12 also acts directly on eosinophils. We postulated that IL-12 directly modulates eosinophil functions and has the capacity to regulate eosinophil degranulation, migration and survival, in vitro. METHOD: Effects of IL- 12 on purified human blood eosinophils were evaluated for peroxidase (EPO) release, eotaxin-induced migration through a model of basement membrane (Matrigel), and survival. RESULTS: IL-12 inhibited 50% of PAF and secretory IgA-induced EPO release (n = 8, p < 0.001). IL-12 also reduced eotaxin-induced migration through Matrigel by 54 +/-6% (n = 6, p < 0.01). These effects were not explained by an IL-12-induced impaired viability or apoptosis. CONCLUSION: Our results demonstrate that IL-12 directly modulates eosinophil functions without promoting apoptosis and explain, at least in part, the effects of IL-12 on eosinophils observed in in vivo studies.
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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 | 0.000 | 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".