Regulation of Discrete Functional Responses by Syk and Src Family Tyrosine Kinases in Human Neutrophils
Bibliographic record
Abstract
Neutrophils play a critical role in innate immunity and also influence adaptive immune responses. This occurs in good part through their production of inflammatory and immunomodulatory cytokines, in conjunction with their prolonged survival at inflamed foci. While a picture of the signaling machinery underlying these neutrophil responses is now emerging, much remains to be uncovered. In this study, we report that neutrophils constitutively express various Src family isoforms (STKs), as well as Syk, and that inhibition of these protein tyrosine kinases selectively hinders inflammatory cytokine generation by acting posttranscriptionally. Accordingly, STK or Syk inhibition decreases the phosphorylation of signaling intermediates (e.g., eIF-4E, S6K, and MNK1) involved in translational control. By contrast, delayed apoptosis appears to be independent of either STKs or Syk. Our data therefore significantly extend our understanding of which neutrophil responses are governed by STKs and Syk and pinpoint some signaling intermediates that are likely involved. In view of the foremost role of neutrophils in several chronic inflammatory conditions, our findings identify potential molecular targets that could be exploited for future therapeutic intervention.
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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) | 0.001 | 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".