Platelets inhibit apoptotic lung epithelial cell death and protect mice against infection-induced lung injury
Bibliographic record
Abstract
Abstract Thrombocytopenia is associated with worse outcomes in patients with acute respiratory distress syndrome, which is most commonly caused by infection and marked by alveolar–capillary barrier disruption. However, the mechanisms by which platelets protect the lung alveolar–capillary barrier during infectious injury remain unclear. We found that natively thrombocytopenic Mpl−/− mice deficient in the thrombopoietin receptor sustain severe lung injury marked by alveolar barrier disruption and hemorrhagic pneumonia with early mortality following acute intrapulmonary Pseudomonas aeruginosa (PA) infection; barrier disruption was attenuated by platelet reconstitution. Although PA infection was associated with a brisk neutrophil influx, depletion of airspace neutrophils failed to substantially mitigate PA-triggered alveolar barrier disruption in Mpl−/− mice. Rather, PA cell-free supernatant was sufficient to induce lung epithelial cell apoptosis in vitro and in vivo and alveolar barrier disruption in both platelet-depleted mice and Mpl−/− mice in vivo. Cell-free supernatant from PA with genetic deletion of the type 2 secretion system, but not the type 3 secretion system, mitigated lung epithelial cell death in vitro and lung injury in Mpl−/− mice. Moreover, platelet releasates reduced poly (ADP ribose) polymerase cleavage and lung injury in Mpl−/− mice, and boiling of platelet releasates, but not apyrase treatment, abrogated PA supernatant–induced lung epithelial cell cytotoxicity in vitro. These findings indicate that while neutrophil airspace influx does not potentiate infectious lung injury in the thrombocytopenic host, platelets and their factors protect against severe pulmonary complications from pathogen-secreted virulence factors that promote host cell death even in the absence of overt infection.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".