Phosphoinositide-3 Kinase γ Activity Contributes to Sepsis and Organ Damage by Altering Neutrophil Recruitment
Bibliographic record
Abstract
RATIONALE: Sepsis is a leading cause of death in the intensive care unit, characterized by a systemic inflammatory response (SIRS) and bacterial infection, which can often induce multiorgan damage and failure. Leukocyte recruitment, required to limit bacterial spread, depends on phosphoinositide-3 kinase γ (PI3Kγ) signaling in vitro; however, the role of this enzyme in polymicrobial sepsis has remained unclear. OBJECTIVES: This study aimed to determine the specific role of the kinase activity of PI3Kγ in the pathogenesis of sepsis and multiorgan damage. METHODS: PI3Kγ wild-type, knockout, and kinase-dead mice were exposed to cecal ligation and perforation-induced sepsis and assessed for survival; pulmonary, hepatic, and cardiovascular damage; coagulation derangements; systemic inflammation; bacterial spread; and neutrophil recruitment. Additionally, wild-type mice were treated either before or after the onset of sepsis with a PI3Kγ inhibitor and assessed for survival, neutrophil recruitment, and bacterial spread. MEASUREMENTS AND MAIN RESULTS: Both genetic and pharmaceutical PI3Kγ kinase inhibition significantly improved survival, reduced multiorgan damage, and limited bacterial decompartmentalization, while modestly affecting SIRS. Protection resulted from both neutrophil-independent mechanisms, involving improved cardiovascular function, and neutrophil-dependent mechanisms, through reduced susceptibility to neutrophil migration failure during severe sepsis by maintaining neutrophil surface expression of the chemokine receptor, CXCR2. Furthermore, PI3Kγ pharmacological inhibition significantly decreased mortality and improved neutrophil migration and bacterial control, even when administered during established septic shock. CONCLUSIONS: This study establishes PI3Kγ as a key molecule in the pathogenesis of septic infection and the transition from SIRS to organ damage and identifies it as a novel possible therapeutic target.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".