Exogenous surfactant prevents hyperoxia-induced lung injury in adult mice
Bibliographic record
Abstract
BACKGROUND: In addition to the risk of developing ventilator-induced lung injury, patients with ARDS are at risk of developing hyperoxic injury due the supra-physiological oxygen supplementation clinically required to reverse hypoxemia. Alterations of endogenous surfactant system participate in the pulmonary dysfunction observed in ARDS. Administration of exogenous surfactant could have protective effects during hyperoxia. METHODS: Male BALB/c mice (8-10 weeks), a strain highly sensitive to hyperoxia, received the exogenous surfactant-containing protein SP-B and SP-C by intranasal instillation 12 h before starting 24 h of exposure to hyperoxia in an inhalation chamber and were compared to mice receiving hyperoxia alone and to controls subjected to normoxia. RESULTS: Compared to the hyperoxia group, the administration of exogenous surfactant was able to reduce lung inflammation through a reduction in the influx of neutrophils and inflammatory biomarkers such as TNF, IL-17, and HMGB1 expression. The antioxidant activity prevented oxidative damage by reducing lipid peroxidation and protein carbonylation and increasing superoxide dismutase activity when compared to the hyperoxia group. CONCLUSION: Our results offer new perspectives on the effects and the mechanism of exogenous surfactant in protecting the airway and lungs, in oxygen-rich lung microenvironment, against oxidative damage and aggravation of acute inflammation induced by hyperoxia.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".