Specific subsets of kinases mediate Siglec-8 engagement-induced ROS production and apoptosis in human eosinophils.
Bibliographic record
Abstract
Abstract Siglecs are type I transmembrane proteins expressed primarily on leukocytes. Among them is Siglec-8, a CD33 subfamily member that is selectively expressed on the cell surface of human eosinophils. Siglec-8 has an intracellular immunoreceptor tyrosine-based inhibitory motif (ITIM) and an immunoreceptor tyrosine-based switch motif (ITSM), putatively responsible for signal transduction. In cytokine-activated eosinophils, Siglec-8 binding causes apoptosis with increased mitochondrial damage and ROS production, but exact signaling mechanisms are unknown. Using a mAb (2C4) against Siglec-8 in combination with small molecule inhibitors, we first examined Siglec-8-mediated apoptosis and ROS production by flow cytometry after 24 hr IL-5 priming (30 ng/mL) of human eosinophils. We observed that 2C4-mediated eosinophil apoptosis was inhibited by PP1 and SU6656 (Src kinase inhibitors), ibrutinib (Btk inhibitor), LY294002 (PI3K inhibitor), GF109203x (PKC inhibitor), and sodium orthovanadate (a protein phosphatase inhibitor) at IC50’s of 1.7 μM, 1.8 μM, 0.9 nM, 1.2 μM, 2.4 μM, and 22 μM respectively. Complete inhibition of ROS production occurred at expected IC90’s. Western blot analysis following Siglec-8 cross-linking with 2C4 showed increased phosphorylation of Src530, Csk, PI3Kδ, and Blk that was detectable within 15 min, and c-Abl phosphorylation that was detectable within 60 min. Additionally, co-immunoprecipitation data shows that Siglec-8 associates with SHP-2, a protein tyrosine phosphatase. While the sequence of signaling events is yet to be determined, Siglec-8 mediated apoptosis in eosinophils involves the unexpected recruitment of molecules normally associated with cell survival.
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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 | 0.000 |
| 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".