The Influence of Thermal Stress on Cadmium Uptake in Arctic Charr (Salvelinus alpinus) and Its Effects on Indicators of Fish Health and Condition, with Implications for Climate Change
Bibliographic record
Abstract
Given the implications of heat stress on contaminant uptake and the importance of salmonid fish to Northern Indigenous peoples, investigating temperature-driven patterns in trace metal bioavailability is essential for assessing climate change risks. Here, juvenile Arctic charr were exposed for 8 weeks to cadmium (Cd) at a nominal concentration of 3 µg·L−1 (measured Cd: 1.81 ± 0.47 µg·L−1) or controls (measured Cd: 0.03 ± 0.03 µg·L−1) at a low (6 °C) or high (16 °C) temperature. Cd concentrations were measured in dorsal muscle, liver, and kidney tissues, and antioxidant (superoxide dismutase (SOD), catalase (CAT)) and anaerobic (lactate dehydrogenase (LDH)) capacities were assessed in liver tissue. Elevated temperatures significantly increased Cd uptake in analyzed tissues. Log10SOD activity decreased in the 6 °C-Cd treatment, while log10CAT activity declined in high-temperature treatments and log10LDH activity was reduced in Cd-exposed groups. The results highlight the influence of temperature, but also of combined thermal and trace metal stressors on Arctic charr’s antioxidant and anaerobic capacities. Biometric data indicate that temperature exerted a stronger negative influence on growth than Cd, with synergistic effects of temperature and Cd on the hepatosomatic index. Overall, this research highlights the thermal stress impacts on Cd uptake and Arctic charr physiology.
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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".