Deficiency of Phosphatidylinositol 3-Kinase δ Signaling Leads to Diminished Numbers of Regulatory T Cells and Increased Neutrophil Activity Resulting in Mortality Due to Endotoxic Shock
Bibliographic record
Abstract
Abstract Despite decades of clinical and biomedical research, the pathogenesis of sepsis and its spectrum of diseases (severe sepsis and septic shock), which are leading causes of death in intensive care units, are still poorly understood. In this article, we show that signaling via the p110δ isoform of PI3K is critical for survival in experimental sepsis. Mice with an inactive knock-in mutation in the p110δ gene (p110δD910A) succumbed acutely to nonlethal dose LPS challenge. The susceptibility of p110δD910A mice to LPS was associated with increased neutrophil numbers and activities in the tissues, due in part to delayed apoptosis resulting mostly from inherent reduced regulatory T cell (Treg) numbers. Adoptive transfer of wild-type or p110δD910A Tregs abrogated exaggerated neutrophil activity, increased neutrophil apoptosis, and rescued p110δD910A mice from mortality after LPS challenge. We confirmed the clinical relevance of these findings by showing that human Tregs also regulate neutrophil function and survival. Collectively, our results show that PI3K δ is essential for survival during sepsis. In addition, our data highlight the importance of Tregs in regulating the pathogenesis of sepsis and septic shock via their effects on neutrophil survival and function, and provide evidence of regulation of innate immunity by cells of the adaptive immune system.
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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".