Genetic toxicity assessment of engineered nanoparticles using a 3D in vitro skin model (EpiDerm™)
Bibliographic record
Abstract
BACKGROUND: The rapid production and incorporation of engineered nanomaterials into consumer products alongside research suggesting nanomaterials can cause cell death and DNA damage (genotoxicity) makes in vitro assays desirable for nanosafety screening. However, conflicting outcomes are often observed when in vitro and in vivo study results are compared, suggesting more physiologically representative in vitro models are required to minimise reliance on animal testing. METHOD: BASF Levasil® silica nanoparticles (16 and 85 nm) were used to adapt the 3D reconstructed skin micronucleus (RSMN) assay for nanomaterials administered topically or into the growth medium. 3D dose-responses were compared to a 2D micronucleus assay using monocultured human B cells (TK6) after standardising dose between 2D / 3D assays by total nanoparticle mass to cell number. Cryogenic vitrification, scanning electron microscopy and dynamic light scattering techniques were applied to characterise in-medium and air-liquid interface exposures. Advanced transmission electron microscopy imaging modes (high angle annular dark field) and X-ray spectrometry were used to define nanoparticle penetration / cellular uptake in the intact 3D models and 2D monocultured cells. RESULTS: For all 2D exposures, significant (p < 0.002) increases in genotoxicity were observed (≥100 μg/mL) alongside cell viability decreases (p < 0.015) at doses ≥200 μg/mL (16 nm-SiO2) and ≥100 μg/mL (85 nm-SiO2). In contrast, 2D-equivalent exposures to the 3D models (≤300 μg/mL) caused no significant DNA damage or impact on cell viability. Further increasing dose to the 3D models led to probable air-liquid interface suffocation. Nanoparticle penetration / cell uptake analysis revealed no exposure to the live cells of the 3D model occurred due to the protective nature of the skin model's 3D cellular microarchitecture (topical exposures) and confounding barrier effects of the collagen cell attachment layer (in-medium exposures). 2D monocultured cells meanwhile showed extensive internalisation of both silica particles causing (geno)toxicity. CONCLUSIONS: The results establish the importance of tissue microarchitecture in defining nanomaterial exposure, and suggest 3D in vitro models could play a role in bridging the gap between in vitro and in vivo outcomes in nanotoxicology. Robust exposure characterisation and uptake assessment methods (as demonstrated) are essential to interpret nano(geno)toxicity studies successfully.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".