Quantitative nanostructure-activity relationship models for the risk assessment of nanomaterials

Quantitative Structure-Activity Relationships in Drug Design, Predictive Toxicology, and Risk Assessment

Volumn , Issue , 2015, Pages 535-559

  Vrontaki, Eleni ^a,b   Mavromoustakos, Thomas ^b   Melagraki, Georgia ^a   Afantitis, Antreas ^a  

^a NOVAMECHANICS LTD   (Cyprus)

^b UNIVERSITY OF ATHENS   (Greece)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGY; CARBON; NANOSTRUCTURED MATERIALS; NANOSTRUCTURES; NANOTECHNOLOGY; YARN;

COMPUTATIONAL MODEL; COMPUTATIONAL SCIENTISTS; DEVELOPMENT AND APPLICATIONS; LIVING ORGANISMS; NANOTECHNOLOGY APPLICATIONS; RELATIONSHIP MODEL; TIME-CONSUMING PROCEDURE; TOXICOLOGICAL EVALUATION;

RISK ASSESSMENT;

EID: 84945364031     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.4018/978-1-4666-8136-1.ch014     Document Type: Chapter

References (81)

1. Baun, A., Hartmann, N. B., Grieger, K., & Kusk, K. O. (2008). Ecotoxicity of engineered nanoparticles to aquatic invertebrates: A brief review and recommendations for future toxicity testing. Ecotoxicology (London, England), 17(5), 387-395. doi:10.1007/s10646-008-0208-y PMID:18425578
2. 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. Archives of Toxicology, 87(7), 1181-1200. doi:10.1007/s00204-013-1079-4 PMID:23728526
3. Brunner, T. J., Wick, P., Manser, P., Spohn, P., Grass, R. N., & Limbach, L. K. et al. (2006). In vitro cytotoxicity of oxide nanoparticles: Comparison to asbestos, silica, and the effect of particle solubility. Environmental Science & Technology, 40(14), 4374-4381. doi:10.1021/es052069i PMID:16903273
4. Burello, E., & Worth, A. P. (2011). QSAR modeling of nanomaterials. Wiley Interdisciplinary Reviews: Nanomedicine and Nanobiotechnology, 3(3), 298-306. PMID:21384562
5. Cattaneo, A. G., Gornati, R., Sabbioni, E., Chiriva-Internati, M., Cobos, E., Jenkins, M. R., & Bernardini, G. (2010). Nanotechnology and human health: Risks and benefits. Journal of Applied Toxicology, 30(8), 730-744. doi:10.1002/jat.1609 PMID:21117037
6. Chau, Y. T., & Yap, C. W. (2012). Quantitative nanostructure-activity relationship modelling of nanoparticles. RSC Advances, 2(22), 8489-8496. doi:10.1039/c2ra21489j
7. Chen, Y., Chen, J., Dong, J., & Jin, Y. (2004). Comparing study of the effect of nanosized silicon dioxide and microsized silicon dioxide on fibrogenesis in rats. Toxicology and Industrial Health, 20(1), 21-27. doi:10.1191/0748233704th190oa PMID:15807405
8. Clark, K. A., White, R. H., & Silbergeld, E. K. (2011). Predictive models for nanotoxicology: Current challenges and future opportunities. Regulatory Toxicology and Pharmacology, 59(3), 361-363. doi:10.1016/j.yrtph.2011.02.002 PMID:21310205
9. Delay, M., & Frimmel, F. H. (2012). Nanoparticles in aquatic systems. Analytical and Bioanalytical Chemistry, 402(2), 583-592. doi:10.1007/s00216-011-5443-z PMID:22038580
10. Dreher, K. L. (2004). Health and environmental impact of nanotechnology: Toxicological assessment of manufactured nanoparticles. Toxicological Sciences, 77(1), 3-5. doi:10.1093/toxsci/kfh041 PMID:14756123
11. Enalos InSilicoNano Platform. (n.d.). Retrieved from www.insilicotox.com
12. Epa, V. C., Burden, F. R., Tassa, C., Weissleder, R., Shaw, S., & Winkler, D. A. (2012). Modeling biological activities of nanoparticles. Nano Letters, 12(11), 5808-5812. doi:10.1021/nl303144k PMID:23039907
13. Fourches, D., Pu, D., & Tropsha, A. (2011). Exploring quantitative nanostructure-activity relationships (QNAR) modeling as a tool for predicting biological effects of manufactured nanoparticles. Combinatorial Chemistry & High Throughput Screening, 14(3), 217-225. doi:10.2174/138620711794728743 PMID:21275889
14. Fourches, D., Pu, D. Q. Y., Tassa, C., Weissleder, R., Shaw, S. Y., Mumper, R. J., & Tropsha, A. (2010). Quantitative nanostructure activity relationship modeling. ACS Nano, 4(10), 5703-5712. doi:10.1021/nn1013484 PMID:20857979
15. Gajewicz, A., Rasulev, B., Dinadayalane, T. C., Urbaszek, P., Puzyn, T., Leszczynska, D., & Leszczynsk, J. (2012). Advancing risk assessment of engineered nanomaterials: Application of computational approaches. Advanced Drug Delivery Reviews, 64(15), 1663-1693. doi:10.1016/j.addr.2012.05.014 PMID:22664229
16. Gaudin, C., Cunha, D., Ivanoff, E., Horcajada, P., Chevé, G., & Yasri, A. et al. (2012). A quantitative structure activity relationship approach to probe the influence of the functionalization on the drug encapsulation of porous metal-organic frameworks. Microporous and Mesoporous Materials, 157, 124-130. doi:10.1016/j.micromeso.2011.06.011
17. George, S., Xia, T., Rallo, R., Zhao, Y., Ji, Z., & Lin, S. et al. (2011). Use of a high-throughput screening approach coupled with in vivo zebrafish embryo screening to develop hazard ranking for engineered nanomaterials. ACS Nano, 5(3), 1805-1817. doi:10.1021/nn102734s PMID:21323332
18. Ghorbanzadeh, M., Fatemi, M. H., & Karimpour, M. (2012). Modeling the cellular uptake of magnetofluorescent nanoparticles in pancreatic cancer cells: A quantitative structure activity relationship study. Industrial & Engineering Chemistry Research, 51(32), 10712-10718. doi:10.1021/ie3006947
19. Golbraikh, A., & Tropsha, A. (2002). Beware of q2! Journal of Molecular Graphics & Modelling, 20(4), 269-276. doi:10.1016/S1093-3263(01)00123-1 PMID:11858635
20. Gordon, T., Chen, L. C., Fine, J. M., Schlesinger, R. B., Su, W. Y., Kimmel, T. A., & Amdur, M. O. (1992). Pulmonary effects of inhaled zinc oxide in human subjects, guinea pigs, rats, and rabbits. American Industrial Hygiene Association Journal, 53(8), 503-509. doi:10.1080/15298669291360030 PMID:1509990
21. Haase, A., Tentschert, J., & Luch, A. (2012). Nanomaterials: A challenge for toxicological risk assessment? In A. Luch (Ed.), Molecular, clinical and environmental toxicology: Environmental toxicology (pp. 219-250). Heidelberg: Springer. doi:10.1007/978-3-7643-8340-4_8
22. Handy, R. D., & Shaw, B. J. (2007). Toxic effects of nanoparticles and nanomaterials: Implications for public health, risk assessment and the public perception of nanotechnology. Health Risk & Society, 9(2), 125-144. doi:10.1080/13698570701306807
23. Hansen, S. F., Larsen, B. H., Olsen, S. I., & Baun, A. (2007). Categorization framework to aid hazard identification of nanomaterials. Nanotoxicology, 1(3), 243-250. doi:10.1080/17435390701727509
24. Ji, Z., Wang, X., Zhang, H., Lin, S., Meng, H., & Sun, B. et al. (2012). Designed synthesis of CeO2 nanorods and nanowires for studying toxicological effects of high aspect ratio nanomaterials. ACS Nano, 6(6), 5366-5380. doi:10.1021/nn3012114 PMID:22564147
25. Kahru, A., & Ivask, A. (2013). Mapping the dawn of nanoecotoxicological research. Accounts of Chemical Research, 46(3), 823-833. doi:10.1021/ar3000212 PMID:23148404
26. Kang, S. J., Kim, B. M., Lee, Y. J., & Chung, H. W. (2008). Titanium dioxide nanoparticles trigger P53-mediated damage response in peripheral blood lymphocytes. Environmental and Molecular Mutagenesis, 49(5), 399-405. doi:10.1002/em.20399 PMID:18418868
27. Kar, S., Gajewicz, A., Puzyn, T., Roy, K., & Leszczynski, J. (2014). Periodic table-based descriptors to encode cytotoxicity profile of metal oxide nanoparticles: A mechanistic QSTR approach. Ecotoxicology and Environmental Safety, 107, 162-169. doi:10.1016/j.ecoenv.2014.05.026 PMID:24949897
28. Karlsson, H. L., Cronholm, P., Gustafsson, J., & Möller, L. (2008). Copper oxide nanoparticles are highly toxic: A comparison between metal oxide nanoparticles and carbon nanotubes. Chemical Research in Toxicology, 21(9), 1726-1732. doi:10.1021/tx800064j PMID:18710264
29. Klaine, S. J., Alvarez, P. J. J., Batley, G. E., Fernandes, T. F., Handy, R. D., & Lyon, D. Y. et al. (2008). Nanomaterials in the environment: Behavior, fate, bioavailability, and effects. Environmental Toxicology and Chemistry, 27(9), 1825-1851. doi:10.1897/08-090.1 PMID:19086204
30. Limbach, L. K., Li, Y., Grass, R. N., Brunner, T. J., Hintermann, M. A., & Muller, M. et al. (2005). Oxide nanoparticle uptake in human lung fibroblasts: Effects of particle size, agglomeration, and diffusion at low concentrations. Environmental Science & Technology, 39(23), 9370-9376. doi:10.1021/es051043o PMID:16382966
31. Lin, S., Zhao, Y., Ji, Z., Ear, J., Chang, C. H., & Zhang, H. et al. (2013). Zebrafish high-throughput screening to study the impact of dissolvable metal oxide nanoparticles on the hatching enzyme, ZHE1. Small, 9(9-10), 1776-1785. doi:10.1002/smll.201202128 PMID:23180726
32. Liu, R., Rallo, R., George, S., Ji, Z., Nair, S., Nel, A. E., & Cohen, Y. (2011). Classification Nano-SAR development for cytotoxicity of metal oxide nanoparticles. Small, 7(8), 1118-1126. doi:10.1002/smll.201002366 PMID:21456088
33. Liu, R., Zhang, H. Y., Ji, Z. X., Rallo, R., Xia, T., & Chang, C. H. et al. (2013). Development of structure-activity relationship for metal oxide nanoparticles. Nanoscale, 5(12), 5644-5653. doi:10.1039/c3nr01533e PMID:23689214
34. Luan, F., Kleandrova, V. V., González-Díaz, H., Ruso, J. M., Melo, A., Speck-Planche, A., & Cordeiro, M. N. D. S. (2014). Computer-aided nanotoxicology: Assessing cytotoxicity of nanoparticles under diverse experimental conditions by using a novel QSTR-perturbation approach. Nanoscale. Doi: doi:10.1039/c4nr01285b
35. Lyon, D. Y., Fortner, J. D., Sayes, C. M., Colvin, V. L., & Hughe, J. B. (2005). Bacterial cell association and antimicrobial activity of a C60 water suspension. Environmental Toxicology and Chemistry, 24(11), 2757-2762. doi:10.1897/04-649R.1 PMID:16398110
36. Makarucha, A. J., Todorova, N., & Yarovsky, I. (2011). Nanomaterials in biological environment: A review of computer modelling studies. European Biophysics Journal, 40(2), 103-115. doi:10.1007/s00249-010-0651-6 PMID:21153635
37. Martin, D., Maran, U., Sild, S., & Karelson, M. (2007). QSPR modeling of solubility of polyaromatic hydrocarbons and fullerene in 1-octanol and n-heptane. The Journal of Physical Chemistry B, 111(33), 9853-9857. doi:10.1021/jp071679x PMID:17661505
38. Messina, G. A., Olsina, R. A., & Stege, P. W. (2013). Integration of nanomaterials in capillary and microchip electrophoresis as a flexible tool. In C. D. García, K. Y. Chumbimuni-Torres, & E. Carrilho (Eds.), Capillary electrophoresis and microchip capillary electrophoresis, principles, applications, and limitations (pp. 327-353). Hoboken, NJ: Wiley. doi:10.1002/9781118530009.ch19
39. NanoMILE. (n.d.). Retrieved from http://www.nanomile.eu-vri.eu/
40. NanoPuzzles. (n.d.). Retrieved from http://www.nanopuzzles.eu/
41. NanoReg. (n.d.). Retrieved from http://www.nanoreg.eu/
42. NanoTox. (n.d.). Retrieved from http://www.nanotox.com/
43. National Nanotechnology Initiative. (n.d.). Collaborative central point of federal agencies in the USA. Retrieved from www.nano.gov/about-nni
44. Nel, A., Xia, T., Madler, L., & Li, N. (2006). Toxic potential of materials at the nanolevel. Science, 311(5761), 622-627. doi:10.1126/science.1114397 PMID:16456071
45. Oberdörster, G., Maynard, A., Donaldson, K., Castranova, V., Fitzpatrick, J., & Ausman, K. et al. (2005). Principles for characterizing the potential human health effects from exposure to nanomaterials: Elements of a screening strategy. Particle and Fibre Toxicology, 6(2), 8. doi:10.1186/1743-8977-2-8 PMID:16209704
46. OECD. (2007) Guidance document on the grouping of chemicals. Organisation of Economic Cooperation and Development. Retrieved from http://www.oecd.org
47. Puzyn, T., Leszczynska, D., & Leszczynski, J. (2009). Toward the development of "Nano-QSARs": Advances and challenges. Small, 5(22), 2494-2509. doi:10.1002/smll.200900179 PMID:19787675
48. Puzyn, T., Rasulev, B., Gajewicz, A., Hu, X. K., Dasari, T. P., & Michalkova, A. et al. (2011). Using nano-QSAR to predict the cytotoxicity of metal oxide nanoparticles. Nature Nanotechnology, 6(3), 175-178. doi:10.1038/nnano.2011.10 PMID:21317892
49. Rehn, B., Seiler, F., Rehn, S., Bruch, J., & Maier, M. (2003). Investigations on the inflammatory and genotoxic lung effects of two types of titanium dioxide: Untreated and surface treated. Toxicology and Applied Pharmacology, 189(2), 84-95. doi:10.1016/S0041-008X(03)00092-9 PMID:12781626
50. Sayes, C., & Ivanov, I. (2010). Comparative study of predictive computational models for nanoparticle-induced cytotoxicity. Risk Analysis, 30(11), 1723-1734. doi:10.1111/j.1539-6924.2010.01438.x PMID:20561263
51. Sayes, C. M., Fortner, J. D., Guo, W., Lyon, D., Boyd, A. M., & Ausman, K. D. et al. (2004). The differential cytotoxicity of water-soluble fullerenes. Nano Letters, 4(10), 1881-1887. doi:10.1021/nl0489586
52. Schaafsma, G., Kroese, E. D., Tielemans, E. L. J. P., Van de Sandt, J. J. M., & Van Leeuwen, C. J. (2009). REACH, non-testing approaches and the urgent need for a change in mind set. Regulatory Toxicology and Pharmacology, 53(1), 70-80. doi:10.1016/j.yrtph.2008.11.003 PMID:19061930
53. Shaw, S. Y., Westly, E. C., Pittet, M. J., Subramanian, A., Schreiber, S. L., & Weissleder, R. (2008). Perturbational profiling of nanomaterial biologic activity. Proceedings of the National Academy of Sciences of the United States of America, 105(21), 7387-7392. doi:10.1073/pnas.0802878105 PMID:18492802
54. Shinohara, N., Matsumoto, K., Endoh, S., Maru, J., & Nakanishi, J. (2009). In vitro and in vivo genotoxicity tests on fullerene C60 nanoparticles. Toxicology Letters, 191(2-3), 289-296. doi:10.1016/j.toxlet.2009.09.012 PMID:19772904
55. SRC/SEMATECH Engineering Research Program. (n.d.). Retrieved from http://www.erc.arizona.edu/
56. Sushko, I., Novotarskyi, S., Körner, R., Pandey, A. K., Rupp, M., & Teetz, W. et al. (2011). Online chemical modeling environment (OCHEM): Web platform for data storage, model development and publishing of chemical information. Journal of Computer-Aided Molecular Design, 6(6), 533-554. doi:10.1007/s10822-011-9440-2 PMID:21660515
57. Tassa, C., Duffner, J. L., Lewis, T. A., Weissleder, R., Schreiber, S. L., Koehler, A. N., & Shaw, S. Y. (2010). Binding affinity and kinetic analysis of targeted small molecule-modified nanoparticles. Bioconjugate Chemistry, 21(1), 14-19. doi:10.1021/bc900438a PMID:20028085
58. Toropov, A. A., Leszczynska, D., & Leszczynski, J. (2007). Predicting water solubility and octanol water partition coefficient for carbon nanotubes based on the chiral vector. Computational Biology and Chemistry, 31(2), 127-128. doi:10.1016/j.compbiolchem.2007.02.002 PMID:17363328
59. Toropov, A. A., & Leszczynski, J. (2007). A new approach to the characterization of nanomaterials: Predicting young's modulus by correlation weighting of nanomaterials codes. Chemical Physics Letters, 433(1-3), 125-129. doi:10.1016/j.cplett.2006.11.010
60. Toropov, A. A., & Toropova, A. P. (2014). Optimal descriptor as a translator of eclectic data into endpoint prediction: Mutagenicity of fullerene as a mathematical function of conditions. Chemosphere, 104, 262-264. doi:10.1016/j.chemosphere.2013.10.079 PMID:24246220
61. Toropov, A. A., Toropova, A. P., Benfenati, E., Gini, G., Puzyn, T., Leszczynska, D., & Leszczynski, J. (2012). Novel application of the CORAL software to model cytotoxicity of metal oxide nanoparticles to bacteria Escherichia coli. Chemosphere, 89(9), 1098-1102. doi:10.1016/j.chemosphere.2012.05.077 PMID:22704203
62. Toropov, A. A., Toropova, A. P., 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(1), 31-37. doi:10.1016/j.chemosphere.2013.03.012 PMID:23566368
63. Toropova, A. P., & Toropov, A. A. (2013). Optimal descriptor as a translator of eclectic information into the prediction of membrane damage by means of various TiO2 nanoparticles. Chemosphere, 93(10), 2650-2655. doi:10.1016/j.chemosphere.2013.09.089 PMID:24161577
64. Wang, J., Byrne, J. D., Napier, M. E., & DeSimone, J. M. (2011). More effective nanomedicines through particle design. Small, 7(14), 1919-1931. doi:10.1002/smll.201100442 PMID:21695781
65. Weissleder, R., Kelly, K., Sun, E. Y., Shtatland, T., & Josephson, L. (2005). Cell-specific targeting of nanoparticles by multivalent attachment of small molecules. Nature Biotechnology, 23(11), 1418-1423. doi:10.1038/nbt1159 PMID:16244656
66. White, R. M., Sessa, A., Burke, C., Bowman, T., Leblanc, J., & Ceol, C. et al. (2008). Transparent adult zebrafish as a tool for in vivo transplantation analysis. Cell Stem Cell, 2(2), 183-189. doi:10.1016/j.stem.2007.11.002 PMID:18371439
67. Zhang, H., Ji, Z., Xia, T., Meng, H., Low-Kam, C., & Liu, R. et al. (2012). Use of metal oxide nanoparticle band gap to develop a predictive paradigm for oxidative stress and acute pulmonary inflammation. ACS Nano, 6(5), 4349-4368. doi:10.1021/nn3010087 PMID:22502734
68. Zhou, H., Mu, Q., Gao, N., Liu, A., Xing, Y., & Gao, S. et al. (2008). A nano-combinatorial library strategy for the discovery of nanotubes with reduced protein-binding, cytotoxicity, and immune response. Nano Letters, 8(3), 859-865. doi:10.1021/nl0730155 PMID:18288815
69. Berhanu, W. M., Pillai, G. G., Oliferenko, A. A., & Katritzky, A. R. (2012). Quantitative Structure Activity/Property Relationships: The Ubiquitous Links between Cause and Effect. ChemPlusChem, 77(7), 507-517. doi:10.1002/cplu.201200038
70. Elzey, S., Larsen, R. G., Howe, C., & Grassian, V. H. (2009). Nanoscience and nanotechnology: Environmental and health impacts. In K. J. Klabunde & R. M. Richards (Eds.), Nanoscale Materials in Chemistry (2nd ed., pp. 681-727). Hoboken, NJ: Wiley. doi:10.1002/9780470523674.ch21
71. Fourches, D., & Tropsha, A. (2014). Quantitative Nanostructure-Activity Relationships: from unstructured data to predictive models for designing nanomaterials with controlled properties. In: N. A. Monteiro-Riviere, & C. Lang Tran (Eds.), Nanotoxicology: Progress toward Nanomedicine, Edition: 2nd. CRC Press (03/2014; ISBN: 9781482203875). doi:10.1201/b16562-11
72. Gajewicz, A., Puzyn, T., Rasulev, B., Leszczynska, D., & Leszczynski, J. (2011). Metal Oxide Nanoparticles: Size-Dependence of Quantum-Mechanical Properties. Nanoscience & Nanotechnology-Asia, 1, 53-58. http://www.nature.com/nnano/focus/nanotoxicology
73. Le, T., Epa, V. C., Burden, F. R., & Winkler, D. A. (2012). Quantitative Structure-Property Relationship Modeling of Diverse Materials Properties. Chemical Reviews, 112(5), 2889-2919. doi:10.1021/cr200066h PMID:22251444
74. Liu, R., Rallo, R., Weissleder, R., Tassa, C., Shaw, S., & Cohen, Y. (2013). Nano-SAR development for bioactivity of nanoparticles with considerations of decision boundaries. Small, 9(9-10), 1842-1852. doi:10.1002/smll.201201903 PMID:23423856
75. Marvin, H. J. P., Bouwmeester, H., Bakker, M., Kroese, E. D., van de Meent, D., & Bourgeois, F. (1839). Verhelst, L. (2013). Exploring the development of a decision support system (DSS) to prioritize engineered nanoparticles for risk assessment. Journal of Nanoparticle Research, 15(8).
76. Pickrell, J. A., Erickson, L. E., Dhakal, K., & Klabunde, K. J. (2009). Toxicity of inhaled nanomaterials. In K. J. Klabunde & R. M. Richards (Eds.), Nanoscale Materials in Chemistry (2nd ed., pp. 730-769). Hoboken, NJ: Wiley. doi:10.1002/9780470523674.ch22
77. Rallo, R., France, B., Liu, R., Nair, S., George, S., & Damoiseaux, R. et al. (2011). Self-Organizing Map Analysis of Toxicity-Related Cell Signaling Pathways for Metal and Metal Oxide Nanoparticles. Environmental Science & Technology, 45(4), 1695-1702. doi:10.1021/es103606x PMID:21250674
78. Sayes, C. M., Smith, P. A., & Ivanov, I. V. (2013). A framework for grouping nanoparticles based on their measurable characteristics. International Journal of Nanomedicine, 8(Suppl. 1), 45-56. doi:10.2147/IJN.S40521 PMID:24098078
79. Stefaniak, A. B., Hackley, V. A., Roebben, G., Ehara, K., Hankin, S., & Postek, M. T. et al. (2013). Nanoscale reference materials for environmental, health and safety measurements: Needs, gaps and opportunities. Nanotoxicology, 7(8), 1325-1337. doi:10.3109/17435390.2012.739664 PMID:23061887
80. Thomas, D. G., Gaheen, S., Harper, S. L., Fritts, M., Klaessig, F., & Hahn-Dantona, E. et al. (2013). ISA-TAB-Nano: A Specification for Sharing Nanomaterial Research Data in Spreadsheet-based Format. BMC Biotechnology, 13(1), 2. doi:10.1186/1472-6750-13-2 PMID:23311978
81. Zhu, Z.-J., Posati, T., Moyano, D. F., Tang, R., Yan, B., Vachet, R. W., & Rotello, V. M. (2012). The Interplay of Monolayer Structure and Serum Protein Interactions on the Cellular Uptake of Gold Nanoparticles. Small, 8(17), 2659-2663. doi:10.1002/smll.201200794 PMID:22730215