Syk: A Novel Target for Treatment of Inflammation in Lung Disease
Bibliographic record
Abstract
Spleen Tyrosine Kinase (Syk) is widely expressed in the immune system and functions in the transmission of inflammatory signals via ITAM-bearing cell surface receptors. The broad expression pattern and importance of Syk in regulating innate immunity and the inflammatory response have led to significant interest from the pharmaceutical industry to developing anti-Syk therapeutics for the treatment of inflammatory disorders such as allergic rhinitis and rheumatoid arthritis. While the function and regulation of Syk has been well-described in leukocytes, where its primary role is an early transducer of signaling following immunoreceptor engagement, Syk has recently been described in non-immune cells, such as the airway epithelium, that also play an important role in mediating the inflammatory response. This manuscript will focus on the expression and function of Syk in the context of inflammatory lung diseases, and review recent data that have demonstrated novel roles for Syk in airway epithelial cells, particularly its role in mediating the human rhinovirus (HRV) induced inflammatory response and viral cell entry. In addition, data describing the efficacy of novel Syk inhibitors in the management of inflammatory diseases in animal models and early clinical trials are also reviewed.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".