Opposing Forces in Asthma: Regulation of Signaling Pathways by Kinases and Phosphatases
Bibliographic record
Abstract
Allergic asthma is a chronic inflammatory disease that involves a sustained T-helper-2 (Th2) type immune response and the recruitment of inflammatory cells such as lymphocytes, mast cells, and eosinophils to the lung. The complex cellular interactions involved in this disease are dependent on cellular responses generated following the integration of environmental signals through the cell signaling pathways. Therefore, the elucidation of the biochemical cascades involved in cellular responses contributing to asthma development has been of great interest in this field. Much attention has been given to the activities of kinases, enzymes that catalyze the addition of a phosphate group to a protein, thus allowing them to modify the function of the target enzyme. This resulted in the identification of key kinases and various cellular processes involved in disease development. New investigations have also begun to unravel the importance of phosphatases, which catalyze the removal of a phosphate group from their target protein. Together, these studies reveal a signaling picture in allergic asthma that is far more complex than originally thought. Herein, we review critical mechanisms of asthma development and discuss how kinases and phosphatases are likely to regulate the development of disease through their effect on these various mechanisms.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".