The characterisation of the behaviour and gill toxicity of CdS/CdTe quantum dots in rainbow trout (Oncorhynchus mykiss)
Bibliographic record
Abstract
The increasing commercial application of nanomaterials is raising concerns about their potential release to aquatic environments. The purpose of this study was to examine the behaviour in freshwater of capped CdS/CdTe quantum dots and the sublethal effects on gills of rainbow trout. Rainbow trout (Oncorhynchus mykiss) were exposed to increasing concentrations of CdS/CdTe or dissolved cadmium (CdSO4) for 48 h at 15°C. The initial Cd and Te concentration in the aquarium water and size fractionation were determined. After the exposure period, the gills were analysed for labile Cd content, changes in lactate and pyruvate, total and redox status of metallothioneins (MT), lipid peroxidation, protein chaperones of the heat shock protein (Hsp) 72 family and ubiquitin conjugates. QDs were mostly between 6.8 and 25 nm suggesting aggregates. Significant increases in total and metal-binding MT, gill lactate and pyruvate levels and Hsp 72 proteins were observed while ubiquitin protein conjugates were significantly decreased by the QDs only with dissolved Cd, LPO and lactate/pyruvate ratio were not affected by the QDs. A discriminant function analysis of the biomarker responses revealed that colloidal and dissolved Cd differed significantly from each other, suggesting different modes of action.
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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) | 0.000 | 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".