IL-4Rα, a New Member that Associates with Syk Kinase: Implication in IL-4-Induced Human Neutrophil Functions
Bibliographic record
Abstract
Although Syk has been reported to be associated with IL-2R beta [corrected] and IL-15R alpha in some hematopoietic cells, its association has never been investigated in the IL-4/IL-4R system. In this study, we demonstrate for the first time that Syk is constitutively associated with IL-4R(alpha)in human polymorphonuclear neutrophils (PMNs) and that IL-4 stimulation increases the amount of Syk associated with IL-4R(alpha). Moreover, upon IL-4 treatment, a pool of Syk associated with IL-4R(alpha) is phosphorylated. We also report that such association is not unique to PMNs because Syk associates with IL-4R(alpha) in Raji and in PBMC cells. Stimulation of PMNs by IL-4 increased the amount of Syk associated with PLC-gamma2, pAkt, and alpha-tubulin. Pretreatment of cells with the Syk-selective inhibitor piceatannol or Syk inhibitor II, significantly inhibited the ability of IL-4 to enhance phagocytosis and cell adhesion and to delay apoptosis, and these results correlate with the ability of piceatannol to reduce Syk activation and its association with IL-4R(alpha). Down-regulation of Syk by antisense techniques demonstrates the importance of Syk in the antiapoptotic effect of IL-4. We conclude that association of Syk to IL-4R(alpha) is of biological significance and that IL-4R(alpha) is a new candidate to be added to the few cytokine receptor components which associate with Syk.
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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) | 0.001 | 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 | 0.000 |
| 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".