Physicochemical characteristics and toxicity of surface-modified zinc oxide nanoparticles to freshwater and marine microalgae
Bibliographic record
Abstract
Abstract Because of wide applications of surface-modified zinc oxide nanoparticles (ZnO-NPs) in commercial sunscreens and their easiness of being released into water, concerns have been raised over their potential effects on aquatic organisms. This study compared physicochemical properties of silane-coated and uncoated ZnO-NPs to elucidate their toxic potencies toward three freshwater and three marine microalgae. Surfaces of ZnO-NPs (20 nm) were modified by coating with 3-aminopropyltrimethoxysilane (A-ZnO-NPs) that provides the particles with a more hydrophilic surface, or dodecyltrichlorosilane (D-ZnO-NPs) that turns the particles to hydrophobic. Uncoated ZnO-NPs formed larger aggregates and released more Zn 2+ than did either of the two coated ZnO-NPs. The three nanoparticles formed larger aggregates but released less Zn 2+ at pH 8 than at pH 7. Although sensitivities varied among algal species, A-ZnO-NPs and uncoated ZnO-NPs were more potent at inhibiting growth of algal cells than were D-ZnO-NPs after 96-h exposure to ZnO, uncoated ZnO-NPs, each of the coated ZnO-NPs or ZnSO 4 at 10 concentrations ranging from 0.1 to 100 mg/L. The marine diatom Thalassiosira pseudonana exposed to ZnO-NPs, A-ZnO-NPs or D-ZnO-NPs resulted in differential expressions of genes, suggesting that each of the coatings resulted in ZnO-NPs acting through different mechanisms of toxic action.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.001 | 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 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".