Copper uptake, patterns of bioaccumulation, and effects in glochidia (larvae) of the freshwater mussel (<i>Lampsilis cardium</i>)
Bibliographic record
Abstract
Abstract The early life stages of freshwater mussels are particularly sensitive to copper (Cu) contamination. We measured the acute toxicity, bioaccumulation, and sublethal effects of Cu in glochidia. In addition, we used radiolabeled Cu (64Cu) to examine the time-dependent kinetics of uptake over 24 h. Uptake of 64Cu by live and dead glochidia exposed to 0.11 μmol/L exhibited similar hyperbolic patterns over the first 40 min, indicating an adsorptive phase independent of larval metabolism. Thereafter, uptake was linear with time, with a 10-fold lower bioaccumulation rate in live than in dead animals, representing a close to steady state of Cu regulation. In contrast, dead glochidia exhibited a progressively increasing uptake, possibly attributable to the fact that metal-binding sites become more accessible. Mortality was strongly correlated with bioaccumulation (48 h); live glochidia exposed to Cu concentrations >0.27 μmol/L lost their regulatory ability and accumulated Cu to an even greater extent than dead animals. Exposure to Cu induced significant decreases in whole-body Na+ and Mg2+ concentrations; increases in reactive oxygen species concentration, lipid peroxidation, and protein carbonylation; and a decrease in antioxidant capacity against peroxyl radicals. Overall, these results clarify the patterns of Cu uptake and regulation, emphasize the importance of distinguishing between live and dead larvae, and indicate that toxicity is associated with Cu bioaccumulation, involving both ionoregulatory disturbance and oxidative stress. Environ Toxicol Chem 2018;37:1092–1103. © 2017 SETAC
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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".