A Meta‐Analysis of Carbon Nanotube Pulmonary Toxicity Studies—How Physical Dimensions and Impurities Affect the Toxicity of Carbon Nanotubes

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.

A quantitative framework to group nanoscale and microscale particles by hazard potency to derive occupational exposure limits: Proof of concept evaluation

“…The results show that this framework was useful in identifying important physicochemical properties (Fig. 6), which have also been shown in a number of studies to predict pulmonary inflammation and related pulmonary responses (Monteiller et al, 2007; Donaldson et al, 2008; Rushton et al, 2010; Pauluhn, 2011; Porter et al, 2013; Gernand and Casman, 2014). Several standard modeling methods are utilized in this framework to develop hazard potency groups and then to predict the group for a new ENM based on physicochemical properties only.…”

“…Weight of evidence and decision analysis methods have been proposed in other analysis frameworks (Hristozov et al, 2014; Zuin et al, 2011). Several quantitative structure-activity relationship (QSAR) models have been developed, which describe the important factors influencing the toxicity (Munro et al, 1996; Burello and Worth, 2011; Gernand and Casman, 2014, 2016) and allow for hazard grouping and ranking (Liu et al, 2011, 2013; Oh et al, 2016; Zhang et al, 2012); however, these models have not thus far been used in human health risk assessment. A recent quantitative framework proposes a human health risk prioritization based on a margin of exposure method (i.e., estimating the ratio between animal effect level and human exposure) (Hristozov et al, 2016).…”

Nanoparticles and direct immunosuppression

“…[11][12][13][14][15] Reports in the fields of nanotoxicology and nanomedicine are exploring the fundamental mechanisms for both intended and unintended immunosuppression by nanomaterials. [16][17][18][19] Understanding the direct immunosuppressive effect of nanoparticles and resultant development of new immunosuppressive therapies can impact both pharmaceutical and regenerative medicine technologies. 9,20,21 When developing methods to suppress immune response, it is important to consider both innate and adaptive immune responses.…”

Research Paper in Literature of Increasing Thickness by Inclined Target

“…This change of affirmation is basically proportionate to the development of locale thickness and thusly mass, and can offer no weight advantage. In this way, in protected vehicle diagram the two other rule effects of inclining have been the manner of thinking to apply slanted support [1][2][3][4][5][6][7][8][9][10].…”

“…In any case, these effects are immovably dependent on the correct defensive layer materials used and the qualities of the shot hitting it: inclining may even incite an unrivalled passageway. Formed charge warheads may disregard to invade and even detonate when striking defensive layer at a sideways edge [9][10][11][12][13][14][15][16][17][18][19][20][21].…”