Protective effects of lycopene on oxidative stress, proliferation and autophagy in iron supplementation rats
Bibliographic record
Abstract
Lycopene is common in diet and known for its antioxidant activities. However, the impact of lycopene on iron metabolism is poorly investigated. In this study, we hypothesize that lycopene can prevent iron-mediated oxidative stress, proliferation and autophagy in liver and use a rat model of nutritional iron supplementation to confirm its intervention in these defence mechanisms. We found that iron supplementation induced cell proliferation predominantly in non parenchymal cells compared with hepatocytes, but not apoptosis. In addition, iron was accumulated within the hepatic lysosomes where it triggered autophagy as evidenced by the formation of autophagic vesicles detected by LC3-B staining. Iron supplementation also induced morphologic alterations of the mitochondrial membranes probably due to increased lipid peroxidation as indicated by elevated iron and malondialdehyde concentrations in serum and tissues. Lycopene reduced iron-catalyzed lipid peroxidation by decreasing the malondialdehyde level in the liver and colon and enhancing the total superoxide dismutase activities in serum and tissues. The result suggest that lycopene prevents iron-induced oxidative stress, proliferation and autophagy at both biochemical and histological levels due to its potent free radical scavenging and antioxidant properties.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".