Oxidative stress in fish exposed to pollutants and environmental toxicology
Bibliographic record
Abstract
Fish serve as valuable sentinel organisms for monitoring aquatic ecosystem health through biochemical responses to environmental contaminants. This research investigated oxidative stress biomarkers in rainbow trout exposed to environmentally relevant cadmium concentrations over 42-day exposure periods. Juvenile trout were maintained in water containing 0, 5, 25, or 100 μg/L cadmium chloride, with tissue sampling conducted at 7, 14, 28, and 42 days. Hepatic cadmium accumulation showed dose-dependent increases, reaching 12.4 ± 2.1 μg/g dry weight at highest exposure. Superoxide dismutase activity initially increased at all cadmium concentrations, suggesting compensatory antioxidant response, before declining to below control levels by day 42 in the 100 μg/L group. Catalase and glutathione peroxidase activities followed similar biphasic patterns. Malondialdehyde concentrations increased progressively with exposure duration and cadmium dose, indicating cumulative oxidative damage. Metallothionein expression correlated strongly with tissue cadmium burden, confirming activation of metal-binding protective mechanisms. Gill tissues demonstrated earlier and more pronounced oxidative stress responses compared to liver. These findings establish oxidative stress biomarkers as sensitive indicators of sublethal cadmium toxicity, supporting their application in environmental monitoring programs.
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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 | 0.000 | 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) | 0.001 | 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".