Spleen tyrosine kinase (Syk) as a novel target for allergic asthma and rhinitis
Bibliographic record
Abstract
Allergic asthma and rhinitis are prevalent diseases in the modern world, both marked by inflammation of the airways. The spleen tyrosine kinase (Syk) plays a critical role in the regulation of such immune and inflammatory responses. Although Syk is best known as a key component of immunoreceptor signalling complexes in leukocytes, recent studies demonstrated Syk expression in cells outside the haematopoietic lineage. Moreover, in recent years, it has been established that Syk is involved in various signalling cascades including those originating from integrin and cytokine receptors. Thus, Syk likely has a much wider biological role than previously recognised. Specific inhibition of Syk using aerosolised antisense oligonucleotides in liposome complexes significantly decreased lung inflammatory responses in experimental asthma and acute lung injury models. In addition, pharmacological inhibitors of Syk have been recently developed with potential for use as therapeutics. However, in the development and the rational delivery of drugs targeting Syk, it is important to consider the multiple cell types that express this kinase and the potential effects of its inhibition on various physiological functions. This review focuses on the recent data and the emerging ideas about Syk as a therapeutic target.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".