Syk tyrosine kinase participates in β<sub>1</sub>-integrin signaling and inflammatory responses in airway epithelial cells
Bibliographic record
Abstract
The protein tyrosine kinase Syk is critically involved in immunoreceptor signaling in hematopoietic cells. Recent studies demonstrate Syk expression in nonhematopoietic cells, including fibroblasts, endothelial cells, hepatocytes, and breast epithelium. However, the role of Syk in these cells is uncertain. We hypothesized that Syk is expressed in respiratory epithelial cells (EC) and that it functions as a signaling molecule involved in inflammatory responses in the epithelium. With the use of immunohistochemistry, Western blot, PCR, and laser scanning confocal microscopy, Syk was detected in human, rat, and mouse bronchial epithelium in situ and in cultured human bronchial EC in primary cells and the cell lines HS-24 and BEAS-2B. Syk-dependent signaling pathways in EC were initiated by engagement of beta1-integrin receptors. Stimulation of beta1-integrin receptors by fibronectin or antibody cross-linking caused redistribution of Syk from a cytoplasmic to plasma membrane localization. In stimulated cells, Syk and beta1-integrin colocalized. In addition, following beta1-integrin receptor engagement, tyrosine phosphorylation of Syk was observed. Expression of the intercellular adhesion molecule-1 (ICAM-1) and production of IL-6, both important molecules in lung inflammation, was downregulated in EC treated with Syk small interfering RNA or Syk inhibitor piceatannol. We propose that Syk is involved in signaling pathways induced by integrin engagement in airway EC. Syk-mediated signaling regulates IL-6 and ICAM-1 expression and may be important in the pathophysiology of lung inflammation.
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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".