Alveolar Macrophages from Septic Mice Promote Polymorphonuclear Leukocyte Transendothelial Migration via an Endothelial Cell Src Kinase/NADPH Oxidase Pathway
Bibliographic record
Abstract
Alveolar macrophages (AMphi) have been implicated in the polymorphonuclear leukocyte (PMN) recruitment to the lungs during sepsis. Using an in vivo murine model of sepsis (feces in the peritoneum), we show that peritonitis leads to increased activation of AMphi and PMN migration into pulmonary alveoli. To assess cellular mechanisms, an in vitro construct of the pulmonary vascular-interstitial interface (murine AMphi, pulmonary endothelial cells, and PMN) and a chimera approach were used. Using immunologic (Abs) and genetic blockade (CXCR2-deficient AMphi), we show that CXC chemokines in septic plasma are responsible for the activation of AMphi. The activated AMphi can promote PMN transendothelial migration, even against a concentration gradient of septic plasma, by generating platelet-activating factor and H(2)O(2). Platelet-activating factor/H(2)O(2) induce an oxidant stress in the adjacent endothelial cells, an event that appears to be a prerequisite for PMN transendothelial migration, since PMN migration is abrogated across Cu/Zn-superoxide dismutase overexpressing endothelial cells. Using gp91-deficient endothelial cells, we show that NADPH oxidase plays an important role in the AMphi-induced PMN transendothelial migration. Pharmacologic/small interfering RNA blockade of Src kinase inhibits AMphi-induced endothelial NADPH oxidase activation and PMN migration. Collectively, our findings indicate that the PMN transendothelial migration induced by septic AMphi is dependent on the generation of superoxide in endothelial cells via the Src kinase/NADPH oxidase signaling pathway.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".