The Influence of Surface Coatings of Silver Nanoparticles on the Bioavailability and Toxicity to <i>Elliptio complanata</i> Mussels
Bibliographic record
Abstract
Nanomaterials could be modified with various coatings which could modulate their behavior in the environment, bioavailability and toxicity. The purpose of this study was to determine if the selected coatings of silver nanoparticles (nAg) could influence the fate, bioavailability, and toxicity toward suspension feeding freshwater mussels, Elliptio complanata. Mussels were exposed for 96 h to 50 μg/L of nAg with the following surface coatings: citrate, silicate (Si), polyvinylpyrrolidone (PVP), and branched polyethylenimine (bPEI). After the exposure period, mussels were analyzed for total Ag, resistance to air emersion, oxidative stress, genotoxicity, and autophagosome protein uptake (protein ubiquitinylation) in gills and digestive glands. The data revealed that citrate- and PVP-coated nAg were 2 times more abundant in the digestive gland compared to bPEI- and Si-coated nAg with estimated bioaccumulation factors between 5 and 10. The data revealed that tissue Ag levels were closely associated with air survival time, weight loss during air exposure, DNA strand breaks, LPO, and protein-ubiquitin levels in the digestive gland. The data supports the hypothesis that the coatings could influence bioavailability and toxicity in freshwater mussels.
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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".