Anti-inflammatory potential of PI3Kδ and JAK inhibitors in asthma patients
Bibliographic record
Abstract
BACKGROUND: Phosphatidylinositol 3-kinase delta (PI3Kδ) and Janus-activated kinases (JAK) are both novel anti-inflammatory targets in asthma that affect lymphocyte activation. We have investigated the anti-inflammatory effects of PI3Kδ and JAK inhibition on cytokine release from asthma bronchoalveolar lavage (BAL) cells and T-cell activation, and measured lung PI3Kδ and JAK signalling pathway expression. METHOD: Cells isolated from asthma patients and healthy subjects were treated with PI3Kδ or JAK inhibitors, and/or dexamethasone, before T-cell receptor stimulation. Levels of IFNγ, IL-13 and IL-17 were measured by ELISA and flow cytometry was used to assess T-cell activation. PI3Kδ, PI3Kγ, phosphorylated protein kinase B (pAKT) and Signal Transducer and Activator of Transcription (STAT) protein expression were assessed by immunohistochemistry in bronchial biopsy tissue from asthma patients and healthy subjects. PI3Kδ expression in BAL CD3 cells was measured by flow cytometry. RESULTS: JAK and PI3Kδ inhibitors reduced cytokine levels from both asthma and healthy BAL cells. Combining dexamethasone with either a JAK or PI3Kδ inhibitor showed an additive anti-inflammatory effect. JAK and PI3Kδ inhibitors were shown to have direct effects on T-cell activation. Immunohistochemistry showed increased numbers of PI3Kδ expressing cells in asthma bronchial tissue compared to controls. Asthma CD3 cells in BAL expressed higher levels of PI3Kδ protein compared to healthy cells. CONCLUSIONS: Targeting PI3Kδ or JAK may prove effective in reducing T-cell activation and the resulting cytokine production in asthma.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".