Investigation on the Toxicity of Nanoparticle Mixture in Rainbow Trout Juveniles
Bibliographic record
Abstract
The environmental impacts of nanoparticle mixtures in the aquatic environment is not well understood. The purpose of this study examined the sub-lethal toxicity of low concentrations (ug/L range) of selected nanoparticles alone and in mixtures in juvenile trout. Fish were exposed to to individual and two environmentally relevant mixtures of silver (nAg), copper oxide (nCuO) and cerium oxide (nCeO) nanoparticles for 96 h at 15 °C. After the exposure period, fish were depurated overnight and tissue levels in Ag, Ce, Cu and Zn were determined along with a suite of effects biomarkers such as oxidative stress/inflammation, denatured protein tagging (ubiquitin), DNA strand breaks (genotoxicity) and acetylcholinesterase (AChE) activity. The data showed that these nanoparticles behaved as suspended matter but were nevertheless bioavailable for fish with bioconcentration factors of 6, 8 and 2 for nAg, nCeO and nCuO respectively. Only nCuO alone increased malonaldehyde (lipid peroxidation) contents but all nanoparticles increased DNA damage, protein-ubiquitin labeling, and decreased AChE activity. Globally, the toxicity of nCeO and nCuO was generally stronger than nAg, and antagonist effects were found in the mixtures. The interactions involved in these antagonisms are not well understood but do not involve the liberation of free ions and labile zinc in tissues. In conclusion, the bioavailability and toxicity of these nanoparticles are influenced by mixtures of nanoparticles, which is likely to occur in contaminated environments.
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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 | 0.001 | 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 | 0.001 |
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".