Cigarette smoke augments CSF3 expression in neutrophils to compromise alveolar–capillary barrier function during influenza infection
Bibliographic record
Abstract
Background Cigarette smokers are at increased risk of acquiring influenza, developing severe disease and requiring hospitalisation/intensive care unit admission following infection. However, immune mechanisms underlying this predisposition are incompletely understood, and therapeutic strategies for influenza are limited. Methods We used a mouse model of concurrent cigarette smoke exposure and H1N1 influenza infection, colony-stimulating factor (CSF)3 supplementation/receptor (CSF3R) blockade and single-cell RNA sequencing (scRNAseq) to investigate this relationship. Results Cigarette smoke exposure exacerbated features of viral pneumonia such as oedema, hypoxaemia and pulmonary neutrophilia. Smoke-exposed infected mice demonstrated an increase in viral (v)RNA, but not replication-competent viral particles, relative to infection-only controls. Interstitial rather than airspace neutrophilia positively predicted morbidity in smoke-exposed infected mice. Screening of pulmonary cytokines using a novel dysregulation score identified an exacerbated expression of CSF3 and interleukin-6 in the context of smoke exposure and influenza. Recombinant (r)CSF3 supplementation during influenza aggravated morbidity, hypothermia and oedema, while anti-CSF3R treatment of smoke-exposed infected mice improved alveolar–capillary barrier function. scRNAseq delineated a shift in the distribution of Csf3 + cells towards neutrophils in the context of cigarette smoke and influenza. However, although smoke-exposed lungs were enriched for infected, highly activated neutrophils, gene signatures of these cells largely reflected an exacerbated form of typical influenza with select unique regulatory features. Conclusion This work provides novel insight into the mechanisms by which cigarette smoke exacerbates influenza infection, unveiling potential therapeutic targets ( e.g. excess vRNA accumulation, oedematous CSF3R signalling) for use in this context, and potential limitations for clinical rCSF3 therapy during viral infectious disease.
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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".