A Meta‐Analysis of Carbon Nanotube Pulmonary Toxicity Studies—How Physical Dimensions and Impurities Affect the Toxicity of Carbon Nanotubes
Identifieur interne : 004C79 ( Main/Exploration ); précédent : 004C78; suivant : 004C80A Meta‐Analysis of Carbon Nanotube Pulmonary Toxicity Studies—How Physical Dimensions and Impurities Affect the Toxicity of Carbon Nanotubes
Auteurs : Jeremy M. Gernand [États-Unis] ; Elizabeth A. Casman [États-Unis]Source :
- Risk Analysis [ 0272-4332 ] ; 2014-03.
Descripteurs français
- KwdFr :
- MESH :
- Pascal (Inist)
- Wicri :
- topic : Homme.
English descriptors
- KwdEn :
- Carbon nanotubes, Evidence-based medicine, Human, Impurity, Inhalation, Lung, Lung (drug effects), Metaanalysis, Nanostructured materials, Nanotubes, Carbon (toxicity), Particle Size, Particle size, Probability, Regression Analysis, Regression analysis, Risk Assessment, Support Vector Machine, Toxicity, Toxicity test.
- MESH :
- chemical , toxicity : Nanotubes, Carbon.
- drug effects : Lung.
- Particle Size, Probability, Regression Analysis, Risk Assessment, Support Vector Machine.
Abstract
This article presents a regression‐tree‐based meta‐analysis of rodent pulmonary toxicity studies of uncoated, nonfunctionalized carbon nanotube (CNT) exposure. The resulting analysis provides quantitative estimates of the contribution of CNT attributes (impurities, physical dimensions, and aggregation) to pulmonary toxicity indicators in bronchoalveolar lavage fluid: neutrophil and macrophage count, and lactate dehydrogenase and total protein concentrations. The method employs classification and regression tree (CART) models, techniques that are relatively insensitive to data defects that impair other types of regression analysis: high dimensionality, nonlinearity, correlated variables, and significant quantities of missing values. Three types of analysis are presented: the RT, the random forest (RF), and a random‐forest‐based dose‐response model. The RT shows the best single model supported by all the data and typically contains a small number of variables. The RF shows how much variance reduction is associated with every variable in the data set. The dose‐response model is used to isolate the effects of CNT attributes from the CNT dose, showing the shift in the dose‐response caused by the attribute across the measured range of CNT doses. It was found that the CNT attributes that contribute the most to pulmonary toxicity were metallic impurities (cobalt significantly increased observed toxicity, while other impurities had mixed effects), CNT length (negatively correlated with most toxicity indicators), CNT diameter (significantly positively associated with toxicity), and aggregate size (negatively correlated with cell damage indicators and positively correlated with immune response indicators). Increasing CNT N2‐BET‐specific surface area decreased toxicity indicators.
Url:
DOI: 10.1111/risa.12109
Affiliations:
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Le document en format XML
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The resulting analysis provides quantitative estimates of the contribution of CNT attributes (impurities, physical dimensions, and aggregation) to pulmonary toxicity indicators in bronchoalveolar lavage fluid: neutrophil and macrophage count, and lactate dehydrogenase and total protein concentrations. The method employs classification and regression tree (CART) models, techniques that are relatively insensitive to data defects that impair other types of regression analysis: high dimensionality, nonlinearity, correlated variables, and significant quantities of missing values. Three types of analysis are presented: the RT, the random forest (RF), and a random‐forest‐based dose‐response model. The RT shows the best single model supported by all the data and typically contains a small number of variables. The RF shows how much variance reduction is associated with every variable in the data set. The dose‐response model is used to isolate the effects of CNT attributes from the CNT dose, showing the shift in the dose‐response caused by the attribute across the measured range of CNT doses. It was found that the CNT attributes that contribute the most to pulmonary toxicity were metallic impurities (cobalt significantly increased observed toxicity, while other impurities had mixed effects), CNT length (negatively correlated with most toxicity indicators), CNT diameter (significantly positively associated with toxicity), and aggregate size (negatively correlated with cell damage indicators and positively correlated with immune response indicators). Increasing CNT N2‐BET‐specific surface area decreased toxicity indicators.</div></front></TEI><affiliations><list><country><li>États-Unis</li></country><region><li>Pennsylvanie</li></region><settlement><li>Pittsburgh</li></settlement><orgName><li>Université Carnegie-Mellon</li></orgName></list><tree><country name="États-Unis"><region name="Pennsylvanie"><name sortKey="Gernand, Jeremy M" sort="Gernand, Jeremy M" uniqKey="Gernand J" first="Jeremy M." last="Gernand">Jeremy M. Gernand</name></region><name sortKey="Casman, Elizabeth A" sort="Casman, Elizabeth A" uniqKey="Casman E" first="Elizabeth A." last="Casman">Elizabeth A. Casman</name><name sortKey="Casman, Elizabeth A" sort="Casman, Elizabeth A" uniqKey="Casman E" first="Elizabeth A." last="Casman">Elizabeth A. Casman</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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