Dose-Dependent Suppression of Cytokine production from T cells by a Novel Phosphoinositide 3-Kinase Delta Inhibitor
Bibliographic record
Abstract
There remains a significant need for development of effective small molecules that can inhibit cytokine-mediated inflammation. Phosphoinositide 3 kinase (PI3K) is a direct upstream activator of AKT, and plays a critical role in multiple cell signaling pathways, cell cycle progression, and cell growth, and PI3K inhibitors have been approved or are in clinical development. We examined novel PI3Kdelta inhibitors, which are highly selective for the p110delta isoform of in CD3/CD28 stimulated T-cell cytokine production. In vitro generated CD4+ T effector cells stimulated in the presence of a PI3Kdelta inhibitor demonstrated a dose-dependent suppression of cytokines produced by Th1, Th2, and Th17 cells. This effect was T-cell intrinsic, and we observed similar effects on human PBMCs. Th17 cells expressing a constitutively activated form of AKT were resistant to PI3Kdelta inhibition, suggesting that the inhibitor is acting through AKT signaling pathways. Additionally, PI3Kdelta inhibition decreased IL-17 production in vivo and decreased neutrophil recruitment to the lung in a murine model of acute pulmonary inflammation. These experiments show that targeting PI3Kdelta activity can modulate T-cell cytokine production and reduce inflammation in vivo, suggesting that PI3Kdelta inhibition could have therapeutic potential in treating inflammatory diseases.
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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 | 0.001 |
| 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".