TNF-mediated alveolar macrophage necroptosis drives disease pathogenesis during respiratory syncytial virus infection
Bibliographic record
Abstract
Respiratory syncytial virus (RSV) is the major cause of acute bronchiolitis in infants under 2 years old. Necroptosis has been implicated in the outcomes of respiratory virus infections. We report that RSV infection triggers necroptosis in primary mouse macrophages and human monocytes in a RIPK1-, RIPK3- and MLKL-dependent manner. Moreover, necroptosis pathways are harmful to RSV clearance from alveolar macrophages. Additionally,Ripk3−/−mice were protected from RSV-induced weight loss and presented with reduced viral loads in the lungs. Alveolar macrophage depletion also protected mice from weight loss and decreased lung RSV virus load. Importantly, alveolar macrophage depletion abolished the upregulation ofRipk3andMlklgene expression induced by RSV infection in the lung tissue. Autocrine tumor necrosis factor (TNF)-mediated RSV-triggered macrophage necroptosis and necroptosis pathways were also involved in TNF secretion even when macrophages were committed to cell death, which can worsen lung injury during RSV infection. In line,Tnfr1−/−mice had a marked decrease inRipk3andMlklgene expression and a sharp reduction in the numbers of necrotic alveolar macrophages in the lungs. Finally, we provide evidence that elevated nasal levels of TNF are associated with disease severity in infants with RSV bronchiolitis. We propose that targeting TNF and/or the necroptotic machinery may be valuable therapeutic approaches to reduce the respiratory morbidity caused by RSV infection in young children.
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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".