Drew Nathan M, Kuempel Eileen D, Pei Ying, Yang Feng
National Institute for Occupational Safety and Health (NIOSH), Nanotechnology Research Center (NTRC), Cincinnati, OH 45226, USA.
National Institute for Occupational Safety and Health (NIOSH), Nanotechnology Research Center (NTRC), Cincinnati, OH 45226, USA.
Regul Toxicol Pharmacol. 2017 Oct;89:253-267. doi: 10.1016/j.yrtph.2017.08.003. Epub 2017 Aug 5.
The large and rapidly growing number of engineered nanomaterials (ENMs) presents a challenge to assessing the potential occupational health risks. An initial database of 25 rodent studies including 1929 animals across various experimental designs and material types was constructed to identify materials that are similar with respect to their potency in eliciting neutrophilic pulmonary inflammation, a response relevant to workers. Doses were normalized across rodent species, strain, and sex as the estimated deposited particle mass dose per gram of lung. Doses associated with specific measures of pulmonary inflammation were estimated by modeling the continuous dose-response relationships using benchmark dose modeling. Hierarchical clustering was used to identify similar materials. The 18 nanoscale and microscale particles were classified into four potency groups, which varied by factors of approximately two to 100. Benchmark particles microscale TiO and crystalline silica were in the lowest and highest potency groups, respectively. Random forest methods were used to identify the important physicochemical predictors of pulmonary toxicity, and group assignments were correctly predicted for five of six new ENMs. Proof-of-concept was demonstrated for this framework. More comprehensive data are needed for further development and validation for use in deriving categorical occupational exposure limits.
大量且数量迅速增长的工程纳米材料(ENM)给评估潜在的职业健康风险带来了挑战。构建了一个包含25项啮齿动物研究的初始数据库,涉及1929只动物,涵盖各种实验设计和材料类型,以识别在引发嗜中性粒细胞性肺部炎症方面效力相似的材料,这种反应与工人相关。剂量在啮齿动物物种、品系和性别之间进行了标准化,以每克肺的估计沉积颗粒质量剂量表示。通过使用基准剂量模型对连续剂量反应关系进行建模,估计了与肺部炎症特定指标相关的剂量。采用层次聚类来识别相似材料。18种纳米级和微米级颗粒被分为四个效力组,其差异约为2至100倍。基准颗粒微米级TiO和结晶二氧化硅分别处于最低和最高效力组。使用随机森林方法来识别肺部毒性的重要物理化学预测因子,并且对六种新的ENM中的五种正确预测了组分配。该框架的概念验证得到了证明。需要更全面的数据以进一步开发和验证,用于推导分类职业接触限值。