Interleukin‐3, but not granulocyte–macrophage colony‐stimulating factor and interleukin‐5, inhibits apoptosis of human basophils through phosphatidylinositol 3‐kinase: requirement of NF‐κB‐dependent and ‐independent pathways
Bibliographic record
Abstract
Basophils are key effector cells of allergic reactions. Although proinflammatory cytokines, such as interleukin (IL)-3, granulocyte-macrophage colony-stimulating factor (GM-CSF) and IL-5, inhibit eosinophil apoptosis in vitro, little is known about basophil apoptosis, and the signalling mechanisms required for basophil survival remain undefined. To address this issue, we used a novel negative-selection system to isolate human basophils to a purity of > 95%, and evaluated apoptosis by morphology using light and transmission electron microscopy, and by annexin-V binding and propidium iodide incorporation using flow cytometry. In this study, we demonstrated that the spontaneous rate of apoptotic basophils was higher than that of eosinophils as, at 24 hr, 57.6 +/- 4.7% of basophils underwent apoptosis compared with 39.5 +/- 3.8% of eosinophils. In addition, basophil cell death was significantly inhibited when cultured with IL-3 for 48 hr (84.6 +/- 4.9% vehicle-treated cells versus 40.9 +/- 3.9% IL-3-treated cells). IL-3 also up-regulated basophil CD69 surface expression. The effects of IL-3 on apoptosis and CD69 surface expression of human basophils were completely blocked by LY294002 (LY), a potent inhibitor of phosphatidylinositol 3-kinase (PI3-K), but only partially inhibited by lactacystin, a proteasome inhibitor that prevents degradation of IkappaB and NF-kappaB translocation. These observations reveal the novel finding that IL-3 prevents basophil apoptosis through the activation of PI3-K, which is only partially NF-kappaB dependent. As basophils are active participants in allergic reactions and IL-3 is one of the abundant proinflammatory cytokines in secretions from allergic tissue, we suggest that IL-3-mediated inhibition of basophil apoptosis may exacerbate the inflammation associated with allergic disorders.
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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) | 0.001 | 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".