Adaptation to oxidative stress induced-lung injury: friend or foe of influenza infection?
Bibliographic record
Abstract
Introduction: Influenza A virus (IAV) infection may trigger exuberant inflammation which may lead to severity of lung diseases or ultimately the death of the patient. We previously described airway adaptation to repeated oxidative stress-induced lung injury with diminished neutrophilic inflammation and preservation of airway function. We questioned whether protection would apply to other stimuli causing inflammation. Objective: To assess if adaptation to lung injury following chlorine exposure provides protection against IAV. Methods: A model of adaptation to oxidative stress induced-lung injury was established by exposing mice to repeated chlorine gas exposures. 24h after the last chlorine exposure, mice were infected with IAV. Outcome measures were assessed 3 or 6 days post infection and were completed by an evaluation of survival. Lung function mechanics were measured using FlexiVent and inflammation was assessed from bronchoalveolar lavage. Type I interferon and viral load were assessed in lung tissue. Results: Mice adapted to repeated chlorine exposures did not have airway hyperresponsiveness at day 6 post infection compared to naïve infected mice. Both type I interferon and viral load were similar between naïve and adapted mice. However, early inflammation at day 3 was controlled only in adapted mice, presumably accounting in the absence of airway hyperresponsiveness at day 6. However, the survival rate of adapted mice was significantly lower than naïve mice. Conclusions: Adaptation to oxidative injury prevents IAV infection-induced airway hyperresponsiveness and inflammation despite an increased mortality. Understanding beneficial and adverse effects of this model may open new avenues.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".