Sevoflurane reduces lipopolysaccharide-induced apoptosis and pulmonary fibrosis in the RAW264.7 cells and mice models to ameliorate acute lung injury by eliminating oxidative damages
Bibliographic record
Abstract
Sevoflurane is identified as an effective candidate drug for acute lung injury (ALI) treatment, but its curing effects and detailed mechanisms have not been fully disclosed. The present study was designed to resolve this academic issue. The ALI mice models were established, and Hematoxylin-eosin staining assay was performed to examine tissue morphologies. Cell viability was determined by CCK-8 assay, and Annexin V-FITC/PI double staining assay was used to examine cell apoptosis. The expression levels of proteins were determined by performing Western Blot analysis and immunofluorescence staining assay. ROS levels were examined by using DCFH-DA staining assay. In this study, we investigated this issue and the ALI models were respectively established by treating the BALB/c mice and the murine macrophage cell line RAW264.7 with different concentrations of lipopolysaccharide (LPS) in vivo and in vitro, which were subsequently subjected to sevoflurane co-treatment. The results showed that sevoflurane reduced LPS-induced ALI in mice and suppressed LPS-triggered oxidative stress and apoptotic cell death in the RAW264.7 cells. Interestingly, we evidenced that the elimination of reactive oxygen species (ROS) by N-acetyl-L-cysteine (NAC) reversed LPS-induced cell apoptosis in RAW264.7 cells. Then, we verified that sevoflurane suppressed oxidative damages to restrain LPS-induced apoptotic cell death in the RAW264.7 cells through activating the anti-oxidant Keap1/Nrf2 pathway. Mechanistically, sevoflurane down-regulated Keap1 and upregulated Nrf2 in nucleus to activate the downstream anti-oxidant signaling cascades, which further ameliorated LPS-induced cell apoptosis and lung injury by eliminating oxidative damages. Taken together, our study illustrated that the sevoflurane attenuates LPS-induced ALI by inhibiting oxidative stress-mediated apoptotic cell death and inflammation, and the Keap1/Nrf2 pathway played an important role in this process.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".