Upregulated PD-L1 delays human neutrophil apoptosis and promotes lung injury in an experimental mouse model of sepsis
Bibliographic record
Abstract
PD-L1 is a ligand for PD-1, and its expression has been shown to be upregulated in neutrophils harvested from septic patients. However, the effect of PD-L1 on neutrophil survival and sepsis-induced lung injury remains largely unknown. In this study, PD-L1 expression correlated negatively with rates of apoptosis in human neutrophils harvested from patients with sepsis. Coimmunoprecipitation assays on control neutrophils challenged with interferon-γ and LPS showed that PD-L1 complexes with the p85 subunit of phosphatidyl 3-kinase (PI3K) to activate AKT-dependent survival signaling. Conditional CRE/LoxP deletion of neutrophil PD-L1 in vivo further protected against lung injury and reduced neutrophil lung infiltration in a cecal ligation and puncture (CLP) experimental sepsis animal model. Compared with wild-type animals, PD-L1-deficient animals presented lower levels of plasma tumor necrosis factor-α and interleukin-6 (IL-6) and higher levels of IL-10 after CLP, and reduced 7-day mortality in CLP PD-L1-knockout animals. Taken together, our data suggest that increased PD-L1 expression on human neutrophils delays cellular apoptosis by triggering PI3K-dependent AKT phosphorylation to drive lung injury and increase mortality during clinical and experimental sepsis.
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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) | 0.001 | 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 | 0.002 |
| 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".