Ebselen Decreases Oxygen Free Radical Production and Iron Concentrations in the Hearts of Chronically Iron-Overloaded Mice
Bibliographic record
Abstract
Chronic iron overload is a major cause of cardiac failure throughout the world, but its pathogenesis remains to be clarified. It is conjectured that the toxicity of iron is due to its ability to catalyze the formation of oxygen free radicals (OFR), which can damage cellular membranes, proteins, and DNA. The authors report on the cardioprotective effects of the glutathione peroxidase (GPx) mimic ebselen on iron concentrations in the heart and GPx activity, and on the production of the cytotoxic aldehydes hexanal, 4-hydroxyl-2-nonenal (HNE), and malondialdehyde (MDA). Fifteen B6D2F1 mice were randomized to 1 of 3 treatment groups for a total of 20 treatments: 1) control (0.1 mL normal saline i.p. per mouse, per day); 2) iron-only (10 mg iron dextran i.p. per mouse, per day); 3) iron plus ebselen (25 mg/kg p.o. per mouse, per day). In comparison to iron-only treated mice, the authors' findings show that supplementation with ebselen can decrease both cytotoxic aldehyde and iron concentrations in heart tissue. Additionally, mice supplemented with ebselen had an increase in GPx activity level in comparison to iron-only treated mice. To the authors' knowledge, this is the first study to examine the cardioprotective effects of ebselen against OFR damage in a model of chronic iron overload. These findings suggest that ebselen may have significance in the management of disorders of iron overload.
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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 | 0.001 | 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".