Discerning the Sources of Silver Nanoparticle in a Terrestrial Food Chain by Stable Isotope Tracer Technique
Bibliographic record
Abstract
The increasing use of silver-containing nanoparticles (NPs) in commercial products has led to NP accumulation in the environment and potentially in food webs. Identifying the uptake pathways of different chemical species of NPs, such as Ag2S-NP and metallic AgNPs, into plants is important to understanding their entry into food chains. In this study, soybean Glycine max L. was hydroponically exposed to Ag2S-NPs via their roots (10–50 mg L–1) and stable-isotope-enriched 109AgNPs via their leaves [7.9 μg (g fresh weight)−1]. Less than 29% of Ag in treated leaves (in direct contact with 109AgNP) was accumulated from root uptake of Ag2S-NPs, whereas almost all of the Ag in soybean roots and untreated leaves sourced from Ag2S-NPs. Therefore, Ag2S-NPs are phytoavailable and translocate upward. During trophic transfer the Ag isotope signature was preserved, indicating that accumulated Ag in snails most likely originated from Ag2S-NPs. On average, 78% of the Ag in the untreated leaves was assimilated by snails, reinforcing the considerable trophic availability of Ag2S-NPs via root uptake. By highlighting the importance of root uptake of Ag2S-NPs in plant uptake and trophic transfer to herbivores, our study advances current understanding of the biogeochemical fate of Ag-containing NPs in the terrestrial environment.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".