The toxicity of silver to soil organisms exposed to silver nanoparticles and silver nitrate in biosolids-amended field soil
Bibliographic record
Abstract
Abstract The use of engineered silver nanoparticles (AgNPs) is widespread, with expected release to the terrestrial environment through the application of biosolids onto agricultural lands. The toxicity of AgNPs and silver nitrate (AgNO3; as ionic Ag+) to plant (Elymus lanceolatus and Trifolium pratense) and soil invertebrate (Eisenia andrei and Folsomia candida) species was assessed using Ag-amended biosolids applied to a natural sandy loam soil. Bioavailable Ag+ in soil samples was estimated using an ion-exchange technique applied to KNO3 soil extracts, whereas exposure to dispersible AgNPs was verified by single-particle inductively coupled plasma–mass spectrometry and transmission electron microscopy-energy dispersive X-ray spectroscopy analysis. Greater toxicity to plant growth and earthworm reproduction was observed in AgNP exposures relative to those of AgNO3, whereas no difference in toxicity was observed for F. candida reproduction. Transformation products in the AgNP-biosolids exposures resulted in larger pools of extractable Ag+ than those from AgNO3-biosolids exposures, at similar total Ag soil concentrations. The results of the present study reveal intrinsic differences in the behavior and bioavailability of the 2 different forms of Ag within the biosolids-soils pathway. The present study demonstrates how analytical methods that target biologically relevant fractions can be used to advance the understanding of AgNP behavior and toxicity in terrestrial environments. Environ Toxicol Chem 2017;36:2756–2765. © 2017 Crown in the Right of Canada. Published Wiley Periodicals Inc., on behalf of SETAC.
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 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".