Predicting toxic potencies of metal oxide nanoparticles by means of nano-QSARs

Mu, Yunsong; Wu, Fengchang; Zhao, Qing; Ji, Rong; Qie, Yu; Zhou, Yue; Yan, Hui‐Juan; Pang, Chengfang; Hristozov, Danail; Giesy, John P.; Xing, Baoshan

doi:10.1080/17435390.2016.1202352

Cited by 77 publications

(54 citation statements)

References 46 publications

(34 reference statements)

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“…The physico-chemical properties of the utilized nanofillers such as shape and composition can elicit adverse effects in biological systems including cytotoxicity, inflammation, and genotoxicity (Mu et al , 2016; Nel et al , 2013). The inclusion of nanofillers in polymers and their subsequent release during thermal decomposition prompts the inevitable question – can nanofiller intrinsic properties play a role on the release potential and subsequently influence toxicological profile when compared to the polymer only control?…”

Section: 0 Discussionmentioning

confidence: 99%

Toxicological implications of released particulate matter during thermal decomposition of nano-enabled thermoplastics

Watson-Wright¹,

Singh²,

Demokritou³

2017

NanoImpact

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Nano-enabled thermoplastics are part of the growing market of nano-enabled products (NEPs) that have vast utility in several industries and consumer goods. The use and disposal of NEPs at their end of life has raised concerns about the potential release of constituent engineered nanomaterials (ENMs) during thermal decomposition and their impact on environmental health and safety. To investigate this issue, industrially relevant nano-enabled thermoplastics including polyurethane, polycarbonate, and polypropylene containing carbon nanotubes (0.1 and 3% w/v, respectively), polyethylene containing nanoscale iron oxide (5% w/v), and ethylene vinyl acetate containing nanoscale titania (2 and 5% w/v) along with their pure thermoplastic matrices were thermally decomposed using the recently developed lab based Integrated Exposure Generation System (INEXS). The life cycle released particulate matter (called LCPM) was monitored using real time instrumentation, size fractionated, sampled, extracted and prepared for toxicological analysis using primary small airway epithelial cells to assess potential toxicological effects. Various cellular assays were used to assess reactive oxygen species and total glutathione as measurements of oxidative stress along with mitochondrial function, cellular viability, and DNA damage. By comparing toxicological profiles of LCPM released from polymer only (control) with nano-enabled LCPM, potential nanofiller effects due to the use of ENMs were determined. We observed associations between NEP properties such as the percent nanofiller loading, host matrix, and nanofiller chemical composition and the physico-chemical properties of released LCPM, which were linked to biological outcomes. More specifically, an increase in percent nanofiller loading promoted a toxicological response independent of increasing LCPM dose. Importantly, differences in host matrix and nanofiller composition were shown to enhance biological activity and toxicity of LCPM. This work highlights the importance of assessing the toxicological properties of LCPM and raises environmental health and safety concerns of nano-enabled products at their end of life during thermal decomposition/incineration.

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Section: 0 Discussionmentioning

confidence: 99%

Toxicological implications of released particulate matter during thermal decomposition of nano-enabled thermoplastics

Watson-Wright¹,

Singh²,

Demokritou³

2017

NanoImpact

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“…Most recently published Nano-(Q)SAR models (Fourches, Pu, and Tropsha 2011;Puzyn et al 2011b;Gajewicz et al 2015;Toropova et al 2015;Mu et al 2016;Pan et al 2016;Basant and Gupta 2017;Fjodorova et al 2017;Gajewicz 2017) have been developed based on a very small data set compared with the data sets underlying classic (chemical) (Q)SAR models. The problem of limited availability of experimental data that are suitable for nano-(Q)SAR modeling has been widely discussed in the literature (Puzyn et al 2011b;Oksel et al 2016;Banares et al 2017).…”

Section: Discussionmentioning

confidence: 99%

Decision tree models to classify nanomaterials according to theDF4nanoGroupingscheme

et al. 2017

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To keep pace with its rapid development an efficient approach for the risk assessment of nanomaterials is needed. Grouping concepts as developed for chemicals are now being explored for its applicability to nanomaterials. One of the recently proposed grouping systems is DF4nanoGrouping scheme. In this study, we have developed three structure-activity relationship classification tree models to be used for supporting this system by identifying structural features of nanomaterials mainly responsible for the surface activity. We used data from 19 nanomaterials that were synthesized and characterized extensively in previous studies. Subsets of these materials have been used in other studies (short-term inhalation, protein carbonylation, and intrinsic oxidative potential), resulting in a unique data set for modeling. Out of a large set of 285 possible descriptors, we have demonstrated that only three descriptors (size, specific surface area, and the quantum-mechanical calculated property 'lowest unoccupied molecular orbital') need to be used to predict the endpoints investigated. The maximum number of descriptors that were finally selected by the classification trees (CT) was very low-one for intrinsic oxidative potential, two for protein carbonylation, and three for NOAEC. This suggests that the models were wellconstructed and not over-fitted. The outcome of various statistical measures and the applicability domains of our models further indicate their robustness. Therefore, we conclude that CT can be a useful tool within the DF4nanoGrouping scheme that has been proposed before. ARTICLE HISTORY

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“…When interacting with cells, PM nanoparticles can induce lipid peroxidation, cause intracellular oxidative stress, in -1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 crease cytosolic calcium ion concentration, activate EGF receptors, and disrupt normal electron transport leading to oxidative stress [27]. Metal oxide nanoparticles (MeONPs) have been known to cause cytotoxicity; the most harmful MeONPs are Tl 2 O/Tl 2 , Ag 2 O, and Au 2 O/Au 2 O 3 [28]. When airborne metals at indoor shooting ranges [9] form oxides, the most toxic to human health could be PbO/PbO 2 , MgO, NiO, ZnO, and CuO [28].…”

Section: Introductionmentioning

confidence: 99%

“…Metal oxide nanoparticles (MeONPs) have been known to cause cytotoxicity; the most harmful MeONPs are Tl 2 O/Tl 2 , Ag 2 O, and Au 2 O/Au 2 O 3 [28]. When airborne metals at indoor shooting ranges [9] form oxides, the most toxic to human health could be PbO/PbO 2 , MgO, NiO, ZnO, and CuO [28]. NiO is known to induce apoptosis by repressing SIRT1 [29].…”

Section: Introductionmentioning

confidence: 99%

Metallic Fumes at Indoor Military Shooting Ranges: Lead, Copper, Nickel, and Zinc in Different Fractions of Airborne Particulate Matter

Orru

Pindus

Harro

et al. 2018

Propellants Explo Pyrotec

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Small firearm shooting emits residues of energetic materials as well as heavy metals of different particle sizes into the air, posing a risk to human health. The current study assessed concentrations of Pb, Cu, Ni and Zn in 14 different size fractions of particulate matter at indoor military shooting ranges. Air samples were collected using ELPI + over two hour period and filters analysed with ICP-MS and ICP-OES.Among the studied metals, Pb concentrations were highest; however, OSHA limit values were only exceeded in one case, when also the highest numbers of gun shots were made. The majority of Pb particles were in fractions > 120 nm. Although concentrations of Cu, Ni, and Zn were significantly lower than Pb, they were more often present as nanoparticles (< 120 nm). This increases their harmfulness, as nanoparticles can easily penetrate the cardiovascular and nervous systems. To decrease the potential health risks of heavy metals at shooting ranges, more efficient ventilation, optimization of the number of gunshots, and the use of lead-free ammunition should be implemented.

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Predicting toxic potencies of metal oxide nanoparticles by means of nano-QSARs

Abstract: These findings may provide an alternative method for prioritizing current and future MeONPs for potential in vivo testing, virtual prescreening and for designing environmentally benign nanomaterials.

Cited by 77 publications

References 46 publications

Toxicological implications of released particulate matter during thermal decomposition of nano-enabled thermoplastics

Toxicological implications of released particulate matter during thermal decomposition of nano-enabled thermoplastics

Decision tree models to classify nanomaterials according to theDF4nanoGroupingscheme

Metallic Fumes at Indoor Military Shooting Ranges: Lead, Copper, Nickel, and Zinc in Different Fractions of Airborne Particulate Matter

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