Anti-Inflammatory Effects of the Iron Chelator, DIBI, in Experimental Acute Lung Injury
Bibliographic record
Abstract
Iron plays a critical role in the immune response to inflammation and infection due to its role in the catalysis of reactive oxygen species (ROS) through the Haber-Weiss and Fenton reactions. However, ROS overproduction can be harmful and damage healthy cells. Therefore, iron chelation represents an innovative pharmacological approach to limit excess ROS formation and the related pro-inflammatory mediator cascades. The present study was designed to investigate the impact of the iron chelator, DIBI, in an experimental model of LPS-induced acute lung injury (ALI). DIBI was administered intraperitoneally in the early and later stages of lung inflammation as determined by histopathological evaluation. We found that lung tissues showed significant injury, as well as increased NF-κB p65 activation and significantly elevated levels of various inflammatory mediators (LIX, CXCL2, CCL5, CXCL10, IL-1𝛽, IL-6) 4 h post ALI induction by LPS. Mice treated with DIBI (80 mg/kg) in the early stages (0 to 2 h) after LPS administration demonstrated a significant reduction of the histopathological damage score, reduced levels of NF-κB p65 activation, and reduced levels of inflammatory mediators. Intravital microscopy of the pulmonary microcirculation also showed a reduced number of adhering leukocytes and improved capillary perfusion with DIBI administration. Our findings support the conclusion that the iron chelator, DIBI, has beneficial anti-inflammatory effects in experimental ALI.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".