Molecular mechanisms involved in interleukin-4-induced human neutrophils: expression and regulation of suppressor of cytokine signaling
Bibliographic record
Abstract
Interleukin-4 (IL-4) is a CD132-dependent cytokine known to activate the Jak-STAT pathway in different cells and cell lines. Although IL-4 has been demonstrated previously to be an agonist in human neutrophils, its capacity to activate different cell signaling pathways in these cells has never been investigated. Two types of IL-4 receptor (IL-4R) exist: the Type I (CD132/IL-4Ralpha heterodimer) and the Type II (IL-4Ralpha/IL-13Ralpha1 heterodimer). In a previous study, we demonstrated that neutrophils express the Type I receptor. Herein, using flow cytometry, we demonstrated that neutrophils, unlike U-937 cells, do not express IL-13Ralpha1 and IL-13Ralpha2 and confirmed the expression of CD132 and IL-4Ralpha on their surface. We also demonstrated that IL-4 induced phosphorylation of Syk, p38, Erk-1/2, JNK, Jak-1, Jak-2, STAT6, and STAT1 and that treatment of cells with the inhibitors piceatannol, SB203580, PD98059, or AG490 reversed the ability of IL-4 to delay neutrophil apoptosis. Using RT-PCR, we demonstrated for the first time that neutrophils express mRNA for all suppressor of cytokine signaling (SOCS) members, namely SOCS1-7 and cytokine-inducible Src homology 2 protein. It is interesting that IL-4 increased expression of SOCS3 at the mRNA and protein levels. The effect of IL-4 on SOCS3 protein expression was increased markedly when the proteasome inhibitor MG132 was added to the cultures, but this was inhibited by cycloheximide, suggesting that SOCS3 is de novo-synthesized in response to IL-4. We conclude that neutrophils express only the Type I IL-4R on their surface and that IL-4 signals via different cell signaling pathways, including the Jak/STAT/SOCS pathway.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".