A predictive bayesian dose-response assessment for evaluating the toxicity of carbon nanotubes relative to crocidolite using a proposed emergent model

Jeffrey J. Iudicello, James Douglas Englehardt

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Carbon Nanotubes (CNTs) are a product of the nanotechnology revolution and show great promise in industrial applications. However, their relative toxicity is still not well understood and has drawn comparison to asbestos fibers due to their size and shape. In this study, a predictive Bayesian dose-response assessment was conducted with extremely limited initial dose-response data to compare the toxicity of long-fiber CNTs with that of crocidolite, an asbestos fiber associated with human mesothelioma. In the assessment, a new, theoretically derived emergent dose-response model was used and compared with the single-hit and multistage models. The multistage and emergent DRFs were selected for toxicity assessment based on two criteria: visual fit to several datasets, and a goodness-of-fit test using an available data-rich study with crocidolite. The predictive assessment supports previous concerns that long-fiber CNTs have toxicity comparable to crocidolite in intratracheal and intraperitoneal applications. Collection of further dose-response data on these materials is strongly recommended.

Original languageEnglish
Pages (from-to)1168-1186
Number of pages19
JournalHuman and Ecological Risk Assessment
Volume15
Issue number6
DOIs
StatePublished - Nov 1 2009

Fingerprint

Crocidolite Asbestos
Carbon Nanotubes
Toxicity
Carbon nanotubes
toxicity
Asbestos
Fibers
asbestos
Nanotechnology
Mesothelioma
nanotechnology
Industrial applications
carbon nanotube
dose
fibre

Keywords

  • Bayesian
  • Carbon nanotubes
  • Crocidolite
  • Markov chain monte carlo
  • Toxicity

ASJC Scopus subject areas

  • Ecological Modeling
  • Health, Toxicology and Mutagenesis
  • Pollution

Cite this

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N2 - Carbon Nanotubes (CNTs) are a product of the nanotechnology revolution and show great promise in industrial applications. However, their relative toxicity is still not well understood and has drawn comparison to asbestos fibers due to their size and shape. In this study, a predictive Bayesian dose-response assessment was conducted with extremely limited initial dose-response data to compare the toxicity of long-fiber CNTs with that of crocidolite, an asbestos fiber associated with human mesothelioma. In the assessment, a new, theoretically derived emergent dose-response model was used and compared with the single-hit and multistage models. The multistage and emergent DRFs were selected for toxicity assessment based on two criteria: visual fit to several datasets, and a goodness-of-fit test using an available data-rich study with crocidolite. The predictive assessment supports previous concerns that long-fiber CNTs have toxicity comparable to crocidolite in intratracheal and intraperitoneal applications. Collection of further dose-response data on these materials is strongly recommended.

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