Apocynin Attenuates Lipopolysaccharide-Induced Lung Injury in an Isolated and Perfused Rat Lung Model
Bibliographic record
Abstract
Apocynin (Apo) suppresses the generation of reactive oxygen species that are implicated in lipopolysaccharide (LPS)-induced lung injury (LPSLI). We thus hypothesized that Apo may attenuate LPSLI. In addition, we explored the cellular and molecular mechanisms of Apo treatment in LPSLI. Lipopolysaccharide-induced lung injury was induced by intratracheal instillation of 10 mg/kg LPS in isolated and perfused rat lung model. Apocynin was administered in the perfusate at 15 min before LPS was administered. Hemodynamics, lung injury indices, inflammatory responses, and activation of apoptotic pathways were assessed. There was an increase in lung vascular permeability associated with lung weight gain after LPS exposure. The levels of interleukin 1β (IL-1β), tumor necrosis factor α (TNF-α), macrophage inflammatory protein 2, H2O2, and albumin increased in the bronchoalveolar lavage fluid. Adhesion molecule of neutrophil (CD31) was upregulated. The expression of TNF-α, IL-1β, glutathione, myeloperoxidase, JNK, P38, caspase 3, p-AKT, and plasminogen activator inhibitor 1 in lung tissue was greater in the LPS groups when compared with the control group. Upregulation and activation of nuclear factor κB occurred along with increased histopathologic lung injury score in LPSLI. The Apo attenuated these inflammatory responses including the levels of CD31, H2O2, TNF-α, IL-1β, myeloperoxidase, P38, and nuclear factor κB along with downregulation of apoptosis as reflected by caspase 3 and p-AKT. In addition, Apo attenuated the increase in lung weight, bronchoalveolar lavage fluid albumin content, and the histopathologic lung injury score. In conclusion, LPSLI is associated with increased inflammatory responses, apoptosis, and coagulation. The administration of Apo attenuates LPSLI through downregulation of the inflammatory responses and apoptosis.
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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 | 0.000 |
| 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 | 0.001 |
| 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".