Comparison of toxicity of uncoated and coated silver nanoparticles
Bibliographic record
Abstract
This study compares toxic effects of uncoated (20, 40, 60 and 80 nm) and OECD (Organization for Economic Co-operation and Development) standard citrate- and polyvinylpyrrolidone (PVP)-coated (10, 50, and 75 nm) silver nanoparticles (Ag-NPs) in J774A. 1 macrophage and HT29 epithelial cells. The cells were exposed to different concentrations (silver content) of Ag-NPs for 24 h. Analysis showed that uncoated Ag-NPs, at a concentration of 1 μg/ml, decreased cell viability by 20–40% and that 20 and 40 nm particles were 10% more cytotoxic than the 60 and 80 nm particles. In exposures to coated Ag-NPs, cell viability dropped at 25 μg/ml or higher concentrations, and the effects were also size-dependent. PVP-coated particles induced greater cytotoxicity than citrate-coated particles. Changes in sub-cellular architecture were observed in J774A. 1 cells upon exposure to test Ag-NPs. Furthermore, uncoated Ag-NPs (1 μg/mL) decreased the expression of selected cytokines including TNF-α, IL-1β, and IL-12 (p70) in J774A. 1 and IL-8 in HT29 cells. In contrast, both citrate- and PVP-coated Ag-NPs increased the expression of these cytokines at higher concentrations (25 μg/ml), and PVP-coated particles elevated cytokine levels the most. Moreover, while uncoated Ag-NPs resulted in decreased glutathione (GSH) content and increased superoxide dismutase (SOD) activity in test cells in a size-dependent manner at 1 μg/ml, coated Ag-NPs caused non-significant changes in GSH and SOD, even at the highest test concentrations. Lastly, uncoated (20 and 40 nm) at 1 μg/ml and coated Ag-NPs (10 nm PVP) at 50 μg/ml slightly increased the production of reactive oxygen species (ROS). Our data showed that uncoated Ag-NPs are more toxic than coated Ag-NPs. While uncoated Ag-NPs appear to suppress inflammatory responses and enhance oxidative stress in the test cells, coated Ag-NPs induce toxic effects through up-regulation of cytokines. Our findings support the toxicity of Ag-NPs as being size- and coating- dependent while providing additional insight on the health impact of Ag-NPs.
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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".