MétaCan
Menu
Back to cohort
Record W2510713634 · doi:10.1186/s12989-016-0161-5

Genetic toxicity assessment of engineered nanoparticles using a 3D in vitro skin model (EpiDerm™)

2015· article· en· W2510713634 on OpenAlexaff
John W. Wills, Nicole Hondow, Adam D. Thomas, Katherine E. Chapman, David Fish, Thierry G.G. Maffeïs, M. W. Penny, Richard A. Brown, Gareth Jenkins, Andy Brown, Paul A. White, Shareen H. Doak

Bibliographic record

VenueParticle and Fibre Toxicology · 2015
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticles: synthesis and applications
Canadian institutionsUniversity of Ottawa
FundersEngineering and Physical Sciences Research CouncilNational Centre for the Replacement, Refinement and Reduction of Animals in Research
KeywordsGenotoxicityNanotoxicologyViability assayMicronucleus testNanomaterialsPenetration (warfare)In vivoIn vitroBiophysicsMicronucleusMaterials scienceNanoparticleDNA damageIn vitro toxicologyNanotechnologyComet assayToxicityChemistryDNABiologyBiochemistryBiotechnology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.050
GPT teacher head0.307
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations71
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueParticle and Fibre ToxicologySame topicNanoparticles: synthesis and applicationsFrench-language works237,207