Influenza-Induced Priming and Leak of Human Lung Microvascular Endothelium upon Exposure to <i>Staphylococcus aureus</i>
Bibliographic record
Abstract
A major cause of death after influenza virus infection is lung injury due to a bacterial superinfection, yet the mechanism is unknown. Death has been attributed to virus-induced immunosuppression and bacterial overgrowth, but this hypothesis is based on data from the preantibiotic era and animal models that omit antimicrobial therapy. Because of diagnostic uncertainty, most patients with influenza receive antibiotics, making bacterial overgrowth unlikely. Respiratory failure after superinfection presents as acute respiratory distress syndrome, a disorder characterized by lung microvascular leak and edema. The objective of this study was to determine whether the influenza virus sensitizes the lung endothelium to leak upon exposure to circulating bacterial-derived molecular patterns from Staphylococcus aureus. In vitro as well as in vivo models of influenza followed by S. aureus superinfection were used. Molecular mechanisms were explored using molecular biology, knockout mice, and human autopsy specimens. Influenza virus infection sensitized human lung endothelium to leak when challenged with S. aureus, even at low doses of influenza and even when the pathogens were given days apart. Influenza virus increased endothelial expression of TNFR1 both in vitro and in intact lungs, a finding corroborated by human autopsy specimens of patients with influenza. Leak was recapitulated with protein A, a TNFR1 ligand, and sequential infection caused protein A-dependent loss of IκB, cleavage of caspases 8 and 3, and lung endothelial apoptosis. Mice infected sequentially with influenza virus and S. aureus developed significantly increased lung edema that was protein A and TNFR1 dependent. Influenza virus primes the lung endothelium to leak, predisposing patients to acute respiratory distress syndrome upon exposure to S. aureus.
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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 | 0.000 |
| 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".