An Integrated Data-Driven Strategy for Safe-by-Design Nanoparticles: The FP7 MODERN Project

Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 947)


The development and implementation of safe-by-design strategies is key for the safe development of future generations of nanotechnology enabled products. The safety testing of the huge variety of nanomaterials that can be synthetized is unfeasible due to time and cost constraints. Computational modeling facilitates the implementation of alternative testing strategies in a time and cost effective way. The development of predictive nanotoxicology models requires the use of high quality experimental data on the structure, physicochemical properties and bioactivity of nanomaterials. The FP7 Project MODERN has developed and evaluated the main components of a computational framework for the evaluation of the environmental and health impacts of nanoparticles. This chapter describes each of the elements of the framework including aspects related to data generation, management and integration; development of nanodescriptors; establishment of nanostructure-activity relationships; identification of nanoparticle categories; hazard ranking and risk assessment.


Nanotoxicology Nanoinformatics Nanodescriptors QNAR Risk assessment 



Authors acknowledge the financial support received from the European Commission through the FP7 MODERN Project (Contract No. 309314). RR also acknowledges the support received from Generalitat de Catalunya (2014SGR 1352).


  1. 1.
    Arts JHE, Hadi M, Irfan M-A, Keene AM, Kreiling R, Lyon D, Maier M, Michel K, Petry T, Sauer UG, Warheit D, Wiench K, Wohlleben W, Landsiedel R (2015) A decision-making framework for the grouping and testing of nanomaterials (DF4nanoGrouping). Regul Toxicol Pharmacol 71:S1–27. doi: 10.1016/j.yrtph.2015.03.007 CrossRefPubMedGoogle Scholar
  2. 2.
    Aruoja V, Dubourguier H-C, Kasemets K, Kahru A (2009) Toxicity of nanoparticles of CuO, ZnO and TiO2 to microalgae Pseudokirchneriella subcapitata. Sci Total Environ 407:1461–1468. doi: 10.1016/j.scitotenv.2008.10.053 CrossRefPubMedGoogle Scholar
  3. 3.
    Aruoja V, Pokhrel S, Sihtmäe M, Mortimer M, Mädler L, Kahru A (2015) Toxicity of 12 metal-based nanoparticles to algae, bacteria and protozoa. Environ Sci Nano 2:630–644. doi: 10.1039/C5EN00057B CrossRefGoogle Scholar
  4. 4.
    Bai W, Zhang Z, Tian W, He X, Ma Y, Zhao Y, Chai Z (2009) Toxicity of zinc oxide nanoparticles to zebrafish embryo: a physicochemical study of toxicity mechanism. J Nanopart Res 12:1645–1654. doi: 10.1007/s11051-009-9740-9 CrossRefGoogle Scholar
  5. 5.
    Bastian M, Heymann S, Jacomy M (2009) Gephi: an open source software for exploring and manipulating networks. ICWSM 8:361–362Google Scholar
  6. 6.
    Bondarenko O, Juganson K, Ivask A, Kasemets K, Mortimer M, Kahru A (2013) Toxicity of Ag, CuO and ZnO nanoparticles to selected environmentally relevant test organisms and mammalian cells in vitro: a critical review. Arch Toxicol 87:1181–1200. doi: 10.1007/s00204-013-1079-4 CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Brüggemann R, Patil G (2011) Ranking and prioritization for multsi-indicator systems: Introduction to partial order applications. Springer, New YorkCrossRefGoogle Scholar
  8. 8.
    Chattaraj PK, Giri S, Duley S (2011) Update 2 of: electrophilicity index. Chem Rev 111:PR43–PR75. doi: 10.1021/cr100149p CrossRefPubMedGoogle Scholar
  9. 9.
    Choi O, Hu Z (2008) Size dependent and reactive oxygen species related nanosilver toxicity to nitrifying bacteria. Environ Sci Technol 42:4583–4588. doi: 10.1021/es703238h CrossRefPubMedGoogle Scholar
  10. 10.
    Cohen Y, Rallo R, Liu R, Liu HH (2013) In silico analysis of nanomaterials hazard and risk. Acc Chem Res 46:802–812. doi: 10.1021/ar300049e CrossRefPubMedGoogle Scholar
  11. 11.
    Cronin MTD, Schultz TW (1997) Validation of Vibrio fisheri acute toxicity data: mechanism of action-based QSARs for non-polar narcotics and polar narcotic phenols. Sci Total Environ 204:75–88. doi: 10.1016/S0048-9697(97)00179-4 CrossRefPubMedGoogle Scholar
  12. 12.
    Damoiseaux R, George S, Li M, Pokhrel S, Ji Z, France B, Xia T, Suarez E, Rallo R, Mädler L, Cohen Y, Hoek EMV, Nel A (2011) No time to lose – high throughput screening to assess nanomaterial safety. Nanoscale 3:1345–1360. doi: 10.1039/c0nr00618a CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Eom HJ, Roca CP, Roh JY, Chatterjee N, Jeong JS, Shim I, Kim HM, Kim PJ, Choi K, Giralt F, Choi J (2015) A systems toxicology approach on the mechanism of uptake and toxicity of MWCNT in Caenorhabditis elegans. Chem Biol Interact 239:153–163. doi: 10.1016/j.cbi.2015.06.031 CrossRefPubMedGoogle Scholar
  14. 14.
    Esteban G, Tellez C, Bautista L (1992) The indicator value of Tetrahymena thermophila populations in the activated sludge process. Acta Protozool 31:129–132Google Scholar
  15. 15.
    Ewald PP (1921) Die Berechnung optischer und elektrostatischer Gitterpotentiale. Ann Phys 369:253–287. doi: 10.1002/andp.19213690304 CrossRefGoogle Scholar
  16. 16.
    George S, Pokhrel S, Xia T, Gilbert B, Ji Z, Schowalter M, Rosenauer A, Damoiseaux R, Bradley KA, Mädler L, Nel AE (2010) Use of a rapid cytotoxicity screening approach to engineer a safer zinc oxide nanoparticle through iron doping. ACS Nano 4:15–29. doi: 10.1021/nn901503q CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    George S, Pokhrel S, Ji Z, Henderson BL, Xia T, Li L, Zink JI, Nel AE, Mädler L (2011) Role of Fe doping in tuning the band gap of TiO2 for the photo-oxidation-induced cytotoxicity paradigm. J Am Chem Soc 133:11270–11278. doi: 10.1021/ja202836s CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Girvan M, Newman MEJ (2002) Community structure in social and biological networks. Proc Natl Acad Sci U S A 99:7821–7826. doi: 10.1073/pnas.122653799 CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Goeman JJ, Bühlmann P (2007) Analyzing gene expression data in terms of gene sets: methodological issues. Bioinformatics 23:980–987. doi: 10.1093/bioinformatics/btm051 CrossRefPubMedGoogle Scholar
  20. 20.
    Grimme S, Antony J, Ehrlich S, Krieg H (2010) A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu. J Chem Phys 132:154104. doi: 10.1063/1.3382344 CrossRefPubMedGoogle Scholar
  21. 21.
    Gupta A, Condit C, Qian X (2010) BioDB: an ontology-enhanced information system for heterogeneous biological information. Data Knowl Eng 69:1084–1102CrossRefGoogle Scholar
  22. 22.
    Hartmann NB, Engelbrekt C, Zhang J, Ulstrup J, Kusk KO, Baun A (2012) The challenges of testing metal and metal oxide nanoparticles in algal bioassays: titanium dioxide and gold nanoparticles as case studies. Nanotoxicology 7:1082–1094CrossRefPubMedGoogle Scholar
  23. 23.
    Hastings J, Jeliazkova N, Owen G, Tsiliki G, Munteanu CR, Steinbeck C, Willighagen E (2015) eNanoMapper: harnessing ontologies to enable data integration for nanomaterial risk assessment. J Biomed Semantics 6:10. doi: 10.1186/s13326-015-0005-5 CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Heinlaan M, Ivask A, Blinova I, Dubourguier H-C, Kahru A (2008) Toxicity of nanosized and bulk ZnO, CuO and TiO2 to bacteria Vibrio fischeri and crustaceans Daphnia magna and Thamnocephalus platyurus. Chemosphere 71:1308–1316. doi: 10.1016/j.chemosphere.2007.11.047 CrossRefPubMedGoogle Scholar
  25. 25.
    Hoffmann MR, Martin ST, Choi W, Bahnemann DW (1995) Environmental applications of semiconductor photocatalysis. Chem Rev 95:69–96. doi: 10.1021/cr00033a004 CrossRefGoogle Scholar
  26. 26.
    Hristozov DR, Gottardo S, Cinelli M, Isigonis P, Zabeo A, Critto A, Van Tongeren M, Tran L, Marcomini A (2014) Application of a quantitative weight of evidence approach for ranking and prioritising occupational exposure scenarios for titanium dioxide and carbon nanomaterials. Nanotoxicology 8:117–131. doi: 10.3109/17435390.2012.760013 CrossRefPubMedGoogle Scholar
  27. 27.
    Ioannidis JPA, Khoury MJ (2011) Improving validation practices in “omics” research. Science 334:1230–1232. doi: 10.1126/science.1211811 CrossRefPubMedGoogle Scholar
  28. 28.
    ISO 21338:2010 – Water quality – Kinetic determination of the inhibitory effects of sediment, other solids and coloured samples on the light emission of Vibrio fischeri (kinetic luminescent bacteria test) [WWW Document], n.d. URL Accessed 17 Feb 2016
  29. 29.
    Ivask A, Kurvet I, Kasemets K, Blinova I, Aruoja V, Suppi S, Vija H, Käkinen A, Titma T, Heinlaan M, Visnapuu M, Koller D, Kisand V, Kahru A (2014) Size-dependent toxicity of silver nanoparticles to bacteria, yeast, algae, crustaceans and mammalian cells in vitro. PLoS One 9:e102108. doi: 10.1371/journal.pone.0102108 CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Jacquet-Lagreze E, Siskos J (1982) Assessing a set of additive utility functions for multicriteria decision-making, the UTA method. Eur J Oper Res 10:151–164. doi: 10.1016/0377-2217(82)90155-2 CrossRefGoogle Scholar
  31. 31.
    Ji Z, Jin X, George S, Xia T, Meng H, Wang X, Suarez E, Zhang H, Hoek EMV, Godwin H, Nel AE, Zink JI (2010) Dispersion and stability optimization of TiO2 nanoparticles in cell culture media. Environ Sci Technol 44:7309–7314. doi: 10.1021/es100417s CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Kahru A, Dubourguier H-C (2010) From ecotoxicology to nanoecotoxicology. Toxicology 269:105–119. doi: 10.1016/j.tox.2009.08.016 CrossRefPubMedGoogle Scholar
  33. 33.
    Kahru A, Dubourguier H, Blinova I, Ivask A, Kasemets K (2008) Biotests and biosensors for ecotoxicology of metal oxide nanoparticles: a minireview. Sensors 8:5153–5170CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Kammler HK, Mädler L, Pratsinis SE (2001) Flame synthesis of nanoparticles. Chem Eng Technol 24:583–596. doi: 10.1002/1521-4125(200106)24:6<583::AID-CEAT583>3.0.CO;2-H CrossRefGoogle Scholar
  35. 35.
    Kar S, Gajewicz A, Puzyn T, Roy K (2014) Nano-quantitative structure-activity relationship modeling using easily computable and interpretable descriptors for uptake of magnetofluorescent engineered nanoparticles in pancreatic cancer cells. Toxicol In Vitro 28:600–606. doi: 10.1016/j.tiv.2013.12.018 CrossRefPubMedGoogle Scholar
  36. 36.
    Karlsson HL, Gustafsson J, Cronholm P, Moller L (2009) Size-dependent toxicity of metal oxide particles-A comparison between nano- and micrometer size. Toxicol Lett 188:112–118CrossRefPubMedGoogle Scholar
  37. 37.
    Kasemets K, Ivask A, Dubourguier H-C, Kahru A (2009) Toxicity of nanoparticles of ZnO, CuO and TiO2 to yeast Saccharomyces cerevisiae. Toxicol In Vitro 23:1116–1122. doi: 10.1016/j.tiv.2009.05.015 CrossRefPubMedGoogle Scholar
  38. 38.
    Katritzky AR, Lobanov VS, Karelson M (1995) QSPR: the correlation and quantitative prediction of chemical and physical properties from structure. Chem Soc Rev 24:279. doi: 10.1039/cs9952400279 CrossRefGoogle Scholar
  39. 39.
    Kemmler JA, Pokhrel S, Birkenstock J, Schowalter M, Rosenauer A, Bârsan N, Weimar U, Mädler L (2012) Quenched, nanocrystalline In4Sn3O12 high temperature phase for gas sensing applications. Sens Actuators B 161:740–747. doi: 10.1016/j.snb.2011.11.026 CrossRefGoogle Scholar
  40. 40.
    Khatri P, Sirota M, Butte AJ (2012) Ten years of pathway analysis: current approaches and outstanding challenges. PLoS Comput Biol 8:e1002375. doi: 10.1371/journal.pcbi.1002375 CrossRefPubMedPubMedCentralGoogle Scholar
  41. 41.
    Kohonen T (1990) The self-organizing map. Proc IEEE 78:1464–1480CrossRefGoogle Scholar
  42. 42.
    Krug HF, Wick P (2011) Nanotoxicology: an interdisciplinary challenge. Angew Chem Int Ed Engl 50:1260–1278. doi: 10.1002/anie.201001037 CrossRefPubMedGoogle Scholar
  43. 43.
    Lay JO, Liyanage R, Borgmann S, Wilkins CL (2006) Problems with the “omics”. TrAC Trends Anal Chem 25:1046–1056. doi: 10.1016/j.trac.2006.10.007 CrossRefGoogle Scholar
  44. 44.
    Linkov I, Satterstrom F, Steevens J, Ferguson E, Pleus R (2007) Multi-criteria decision analysis and environmental risk assessment for nanomaterials. J Nanopart Res 9:543–554CrossRefGoogle Scholar
  45. 45.
    Liu R, Zhang HY, Ji ZX, Rallo R, Xia T, Chang CH, Nel A, Cohen Y (2013) Development of structure-activity relationship for metal oxide nanoparticles. Nanoscale 5:5644–5653. doi: 10.1039/c3nr01533e CrossRefPubMedGoogle Scholar
  46. 46.
    Long TC, Saleh N, Tilton RD, Lowry GV, Veronesi B (2006) Titanium dioxide (P25) produces reactive oxygen species in immortalized brain microglia (BV2): implications for nanoparticle neurotoxicity †. Environ Sci Technol 40:4346–4352. doi: 10.1021/es060589n CrossRefPubMedGoogle Scholar
  47. 47.
    Mädler L (2004) Liquid-fed aerosol reactors for one-step synthesis of nano-structured particles. KONA Powder Part J 22:107–120. doi: 10.14356/kona.2004014 CrossRefGoogle Scholar
  48. 48.
    Marchese Robinson RL, Cronin MTD, Richarz A-N, Rallo R (2015) An ISA-TAB-Nano based data collection framework to support data-driven modelling of nanotoxicology. Beilstein J Nanotechnol 6:1978–1999. doi: 10.3762/bjnano.6.202 CrossRefPubMedPubMedCentralGoogle Scholar
  49. 49.
    Mortimer M, Kasemets K, Heinlaan M, Kurvet I, Kahru A (2008) High throughput kinetic Vibrio fischeri bioluminescence inhibition assay for study of toxic effects of nanoparticles. Toxicol In Vitro 22:1412–1417. doi: 10.1016/j.tiv.2008.02.011 CrossRefPubMedGoogle Scholar
  50. 50.
    Mortimer M, Kasemets K, Kahru A (2010) Toxicity of ZnO and CuO nanoparticles to ciliated protozoa Tetrahymena thermophila. Toxicology 269:182–189. doi: 10.1016/j.tox.2009.07.007 CrossRefPubMedGoogle Scholar
  51. 51.
    Mortimer M, Kahru A, Slaveykova VI (2014) Uptake, localization and clearance of quantum dots in ciliated protozoa Tetrahymena thermophila. Environ Pollut 190:58–64. doi: 10.1016/j.envpol.2014.03.021 CrossRefPubMedGoogle Scholar
  52. 52.
    Neese F (2012) The ORCA program system. Wiley Interdiscip Rev Comput Mol Sci 2:73–78. doi: 10.1002/wcms.81 CrossRefGoogle Scholar
  53. 53.
    Nel A, Mädler L, Velegol D, Xia T, Hoek E, Somasundaran P, Klaessig F, Castranova V, Thompson M (2009) Understanding biophysicochemical interactions at the nano–bio interface. Nat Mater 8:543–557CrossRefPubMedGoogle Scholar
  54. 54.
    Netzeva TI, Schultz TW (2005) QSARs for the aquatic toxicity of aromatic aldehydes from Tetrahymena data. Chemosphere 61:1632–1643. doi: 10.1016/j.chemosphere.2005.04.040 CrossRefPubMedGoogle Scholar
  55. 55.
    Newman M (2010) Networks: an introduction. Oxford University Press Inc, New YorkGoogle Scholar
  56. 56.
    Newman M, Girvan M (2004) Finding and evaluating community structure in networks. Phys Rev E 69:026113. doi: 10.1103/PhysRevE.69.026113 CrossRefGoogle Scholar
  57. 57.
    OECD (2006) OECD Guidelines for the Testing of Chemicals, Section 2, Test No. 201: Freshwater Alga and Cyanobacteria, Growth Inhibition Test. Organization for Economic Cooperation and Development, ParisCrossRefGoogle Scholar
  58. 58.
    Oomen AG, Bleeker EAJ, Bos PMJ, van Broekhuizen F, Gottardo S, Groenewold M, Hristozov D, Hund-Rinke K, Irfan M-A, Marcomini A, Peijnenburg WJGM, Rasmussen K, Jiménez AS, Scott-Fordsmand JJ, van Tongeren M, Wiench K, Wohlleben W, Landsiedel R (2015) Grouping and read-across approaches for risk assessment of nanomaterials. Int J Environ Res Public Health 12:13415–13434. doi: 10.3390/ijerph121013415 CrossRefPubMedPubMedCentralGoogle Scholar
  59. 59.
    Parr RG, Pearson RG (1983) Absolute hardness: companion parameter to absolute electronegativity. J Am Chem Soc 105:7512–7516. doi: 10.1021/ja00364a005 CrossRefGoogle Scholar
  60. 60.
    Parr RG, Donnelly RA, Levy M, Palke WE (1978) Electronegativity: the density functional viewpoint. J Chem Phys 68:3801. doi: 10.1063/1.436185 CrossRefGoogle Scholar
  61. 61.
    Passagne I, Morille M, Rousset M, Pujalté I, L’azou B (2012) Implication of oxidative stress in size-dependent toxicity of silica nanoparticles in kidney cells. Toxicology 299:112–124. doi: 10.1016/j.tox.2012.05.010 CrossRefPubMedGoogle Scholar
  62. 62.
    Perdew JP, Burke K, Ernzerhof M (1996) Generalized gradient approximation made simple. Phys Rev Lett 77:3865–3868. doi: 10.1103/PhysRevLett.77.3865 CrossRefPubMedGoogle Scholar
  63. 63.
    Plimpton S (1995) Fast parallel algorithms for short-range molecular dynamics. J Comput Phys 117:1–19. doi: 10.1006/jcph.1995.1039 CrossRefGoogle Scholar
  64. 64.
    Puzyn T, Leszczynska D, Leszczynski J (2009) Toward the development of “Nano-QSARs”: advances and challenges. Small 5:2494–2509CrossRefPubMedGoogle Scholar
  65. 65.
    Puzyn T, Rasulev B, Gajewicz A, Hu X, Dasari TP, Michalkova A, Hwang H-M, Toropov A, Leszczynska D, Leszczynski J (2011) Using nano-QSAR to predict the cytotoxicity of metal oxide nanoparticles. Nat Nanotechnol 6:175–178. doi: 10.1038/nnano.2011.10 CrossRefPubMedGoogle Scholar
  66. 66.
    Restrepo G, Weckert M, Brüggemann R, Gerstmann S, Frank H (2008) Ranking of refrigerants. Environ Sci Technol 42:2925–2930. doi: 10.1021/es7026289 CrossRefPubMedGoogle Scholar
  67. 67.
    Rushton EK, Jiang J, Leonard SS, Eberly S, Castranova V, Biswas P, Elder A, Han X, Gelein R, Finkelstein J, Oberdörster G (2010) Concept of assessing nanoparticle hazards considering nanoparticle dosemetric and chemical/biological response metrics. J Toxicol Environ Heal Part A 3:445–461CrossRefGoogle Scholar
  68. 68.
    Savolainen K, Backman U, Brouwer D, Fadeel B, Fernandes T, Kuhlbusch T, Landsiedel R, Lynch I, Pylkkänen L (2013) Nanosafety in Europe 2015–2025: Towards Safe and Sustainable Nanomaterials and Nanotechnology Innovations. Helsinki, Finish Institute of Occupational HealthGoogle Scholar
  69. 69.
    Singh J (2001) Semiconductor devices. Basic principles. Wiley, New YorkGoogle Scholar
  70. 70.
    Sinha RP, Häder D-P (2002) UV-induced DNA damage and repair: a review. Photochem Photobiol Sci 1:225–236. doi: 10.1039/b201230h CrossRefPubMedGoogle Scholar
  71. 71.
    Suzuki R, Shimodaira H (2006) Pvclust: an R package for assessing the uncertainty in hierarchical clustering. Bioinformatics 22:1540–1542CrossRefPubMedGoogle Scholar
  72. 72.
    Tani, T. 2003. Flame Spray Pyrolysis of Zinc Oxide/silica Particles. PhD Thesis, Swiss Federal Institute of Technology, Zurich. Dissertation ETHNo. 15266, 1-116Google Scholar
  73. 73.
    Tani T, Mädler L, Pratsinis SE (2002) Homogeneous ZnO nanoparticles by flame spray pyrolysis. J Nanopart Res 4:337–343. doi: 10.1023/A:1021153419671 CrossRefGoogle Scholar
  74. 74.
    Teoh WY, Amal R, Mädler L (2010) Flame spray pyrolysis: an enabling technology for nanoparticles design and fabrication. Nanoscale 2:1324–1347. doi: 10.1039/c0nr00017e CrossRefPubMedGoogle Scholar
  75. 75.
    Thomas DG, Pappu RV, Baker NA (2011) NanoParticle Ontology for cancer nanotechnology research. J Biomed Inform 44:59–74. doi: 10.1016/j.jbi.2010.03.001 CrossRefPubMedGoogle Scholar
  76. 76.
    Thomas DG, Gaheen S, Harper SL, Fritts M, Klaessig F, Hahn-Dantona E, Paik D, Pan S, Stafford GA, Freund ET, Klemm JD, Baker NA (2013) ISA-TAB-Nano: a specification for sharing nanomaterial research data in spreadsheet-based format. BMC Biotechnol 13:2. doi: 10.1186/1472-6750-13-2 CrossRefPubMedPubMedCentralGoogle Scholar
  77. 77.
    Toropov AA, Toropova AP, Puzyn T, Benfenati E, Gini G, Leszczynska D, Leszczynski J (2013) QSAR as a random event: modeling of nanoparticles uptake in PaCa2 cancer cells. Chemosphere 92:31–37. doi: 10.1016/j.chemosphere.2013.03.012 CrossRefPubMedGoogle Scholar
  78. 78.
    Toropova AP, Toropov AA, Rallo R, Leszczynska D, Leszczynski J (2015) Optimal descriptor as a translator of eclectic data into prediction of cytotoxicity for metal oxide nanoparticles under different conditions. Ecotoxicol Environ Saf 112:39–45. doi: 10.1016/j.ecoenv.2014.10.003 CrossRefPubMedGoogle Scholar
  79. 79.
    von Moos N, Slaveykova VI (2014) Oxidative stress induced by inorganic nanoparticles in bacteria and aquatic microalgae – state of the art and knowledge gaps. Nanotoxicology 8:605–630. doi: 10.3109/17435390.2013.809810 CrossRefGoogle Scholar
  80. 80.
    Weigend F, Ahlrichs R (2005) Balanced basis sets of split valence, triple zeta valence and quadruple zeta valence quality for H to Rn: design and assessment of accuracy. Phys Chem Chem Phys 7:3297–3305. doi: 10.1039/b508541a CrossRefPubMedGoogle Scholar
  81. 81.
    Wesselkamper SC, Chen LC, Gordon T (2001) Development of pulmonary tolerance in mice exposed to zinc oxide fumes. Toxicol Sci 60:144–151. doi: 10.1093/toxsci/60.1.144 CrossRefPubMedGoogle Scholar
  82. 82.
    Wolf D, Keblinski P, Phillpot SR, Eggebrecht J (1999) Exact method for the simulation of Coulombic systems by spherically truncated, pairwise r[sup −1] summation. J Chem Phys 110:8254. doi: 10.1063/1.478738 CrossRefGoogle Scholar
  83. 83.
    Xia T, Kovochich M, Liong M, Mädler L, Gilbert B, Shi H, Yeh J, Zink J, Nel A (2008) Comparison of the mechanism of toxicity of zinc oxide and cerium oxide nanoparticles based on dissolution and oxidative stress properties. ACS Nano 2:2121–2134CrossRefPubMedPubMedCentralGoogle Scholar
  84. 84.
    Xia T, Zhao Y, Sager T, George S, Pokhrel S, Li N, Schoenfeld D, Meng H, Lin S, Wang X, Wang M, Ji Z, Zink JI, Mädler L, Castranova V, Lin S, Nel AE (2011) Decreased dissolution of ZnO by iron doping yields nanoparticles with reduced toxicity in the rodent lung and zebrafish embryos. ACS Nano 5:1223–1235. doi: 10.1021/nn1028482 CrossRefPubMedPubMedCentralGoogle Scholar
  85. 85.
    Zhang H, Ji Z, Xia T, Meng H, Low-Kam C, Liu R, Pokhrel S, Lin S, Wang X, Liao Y-P, Wang M, Li L, Rallo R, Damoiseaux R, Telesca D, Mädler L, Cohen Y, Zink JI, Nel AE (2012) Use of metal oxide nanoparticle band gap to develop a predictive paradigm for oxidative stress and acute pulmonary inflammation. ACS Nano 6:4349–4368. doi: 10.1021/nn3010087 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.UFZ Department of Ecological ChemistryHelmholtz Centre for Environmental ResearchLeipzigGermany
  2. 2.Faculty for Chemistry and MineralogyUniversity of LeipzigLeipzigGermany
  3. 3.Institute for Organic ChemistryTechnical University Bergakademie FreibergFreibergGermany
  4. 4.Institute of ChemistryUniversity of TartuTartuEstonia
  5. 5.Institut de Chimie de Nice (UMR CNRS 7272)Université Nice Sophia AntipolisNiceFrance
  6. 6.Institute of TechnologyUniversity of TartuTartuEstonia
  7. 7.Foundation Institute of Materials Science (IWT), Department of Production EngineeringUniversity of BremenBremenGermany
  8. 8.Laboratory of Environmental ToxicologyNational Institute of Chemical Physics and BiophysicsTallinnEstonia
  9. 9.Department of BioscienceAarhus UniversitSilkeborgDenmark
  10. 10.Departament d’Enginyeria QuímicaUniversitat Rovira i VirgiliTarragonaSpain
  11. 11.Departament d’Enginyeria Informatica i MatematiquesUniversitat Rovira i VirgiliTarragonaSpain

Personalised recommendations