A framework for grouping nanoparticles based on their measurable characteristics

Christie M Sayes,1–3 P Alex Smith,2 Ivan V Ivanov3 1Center for Aerosol and Nanomaterials Engineering, RTI International, Research Triangle Park, NC, USA; 2Department of Biomedical Engineering, 3Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Stat...

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Autores principales:	Sayes CM, Smith PA, Ivanov IV
Formato:	article
Lenguaje:	EN
Publicado:	Dove Medical Press 2013
Materias:	Medicine (General) R5-920
Acceso en línea:	https://doaj.org/article/1fa095abbbe14c7f9d28b520d7de7522
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spelling	oai:doaj.org-article:1fa095abbbe14c7f9d28b520d7de75222021-12-02T01:25:31ZA framework for grouping nanoparticles based on their measurable characteristics1176-91141178-2013https://doaj.org/article/1fa095abbbe14c7f9d28b520d7de75222013-09-01T00:00:00Zhttp://www.dovepress.com/a-framework-for-grouping-nanoparticles-based-on-their-measurable-chara-a14394https://doaj.org/toc/1176-9114https://doaj.org/toc/1178-2013Christie M Sayes,1–3 P Alex Smith,2 Ivan V Ivanov3 1Center for Aerosol and Nanomaterials Engineering, RTI International, Research Triangle Park, NC, USA; 2Department of Biomedical Engineering, 3Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX, USA Background: There is a need to take a broader look at nanotoxicological studies. Eventually, the field will demand that some generalizations be made. To begin to address this issue, we posed a question: are metal colloids on the nanometer-size scale a homogeneous group? In general, most people can agree that the physicochemical properties of nanomaterials can be linked and related to their induced toxicological responses. Methods: The focus of this study was to determine how a set of selected physicochemical properties of five specific metal-based colloidal materials on the nanometer-size scale – silver, copper, nickel, iron, and zinc – could be used as nanodescriptors that facilitate the grouping of these metal-based colloids. Results: The example of the framework pipeline processing provided in this paper shows the utility of specific statistical and pattern recognition techniques in grouping nanoparticles based on experimental data about their physicochemical properties. Interestingly, the results of the analyses suggest that a seemingly homogeneous group of nanoparticles could be separated into sub-groups depending on interdependencies observed in their nanodescriptors. Conclusion: These particles represent an important category of nanomaterials that are currently mass produced. Each has been reputed to induce toxicological and/or cytotoxicological effects. Here, we propose an experimental methodology coupled with mathematical and statistical modeling that can serve as a prototype for a rigorous framework that aids in the ability to group nanomaterials together and to facilitate the subsequent analysis of trends in data based on quantitative modeling of nanoparticle-specific structure–activity relationships. The computational part of the proposed framework is rather general and can be applied to other groups of nanomaterials as well. Keywords: structure–activity relationships, principal component analysis, linear discriminant analysis, nanoparticle, modeling frameworkSayes CMSmith PAIvanov IVDove Medical PressarticleMedicine (General)R5-920ENInternational Journal of Nanomedicine, Vol 2013, Iss Supplement 1 Nanoinformatics, Pp 45-56 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine (General) R5-920
spellingShingle	Medicine (General) R5-920 Sayes CM Smith PA Ivanov IV A framework for grouping nanoparticles based on their measurable characteristics
description	Christie M Sayes,1–3 P Alex Smith,2 Ivan V Ivanov3 1Center for Aerosol and Nanomaterials Engineering, RTI International, Research Triangle Park, NC, USA; 2Department of Biomedical Engineering, 3Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX, USA Background: There is a need to take a broader look at nanotoxicological studies. Eventually, the field will demand that some generalizations be made. To begin to address this issue, we posed a question: are metal colloids on the nanometer-size scale a homogeneous group? In general, most people can agree that the physicochemical properties of nanomaterials can be linked and related to their induced toxicological responses. Methods: The focus of this study was to determine how a set of selected physicochemical properties of five specific metal-based colloidal materials on the nanometer-size scale – silver, copper, nickel, iron, and zinc – could be used as nanodescriptors that facilitate the grouping of these metal-based colloids. Results: The example of the framework pipeline processing provided in this paper shows the utility of specific statistical and pattern recognition techniques in grouping nanoparticles based on experimental data about their physicochemical properties. Interestingly, the results of the analyses suggest that a seemingly homogeneous group of nanoparticles could be separated into sub-groups depending on interdependencies observed in their nanodescriptors. Conclusion: These particles represent an important category of nanomaterials that are currently mass produced. Each has been reputed to induce toxicological and/or cytotoxicological effects. Here, we propose an experimental methodology coupled with mathematical and statistical modeling that can serve as a prototype for a rigorous framework that aids in the ability to group nanomaterials together and to facilitate the subsequent analysis of trends in data based on quantitative modeling of nanoparticle-specific structure–activity relationships. The computational part of the proposed framework is rather general and can be applied to other groups of nanomaterials as well. Keywords: structure–activity relationships, principal component analysis, linear discriminant analysis, nanoparticle, modeling framework
format	article
author	Sayes CM Smith PA Ivanov IV
author_facet	Sayes CM Smith PA Ivanov IV
author_sort	Sayes CM
title	A framework for grouping nanoparticles based on their measurable characteristics
title_short	A framework for grouping nanoparticles based on their measurable characteristics
title_full	A framework for grouping nanoparticles based on their measurable characteristics
title_fullStr	A framework for grouping nanoparticles based on their measurable characteristics
title_full_unstemmed	A framework for grouping nanoparticles based on their measurable characteristics
title_sort	framework for grouping nanoparticles based on their measurable characteristics
publisher	Dove Medical Press
publishDate	2013
url	https://doaj.org/article/1fa095abbbe14c7f9d28b520d7de7522
work_keys_str_mv	AT sayescm aframeworkforgroupingnanoparticlesbasedontheirmeasurablecharacteristics AT smithpa aframeworkforgroupingnanoparticlesbasedontheirmeasurablecharacteristics AT ivanoviv aframeworkforgroupingnanoparticlesbasedontheirmeasurablecharacteristics AT sayescm frameworkforgroupingnanoparticlesbasedontheirmeasurablecharacteristics AT smithpa frameworkforgroupingnanoparticlesbasedontheirmeasurablecharacteristics AT ivanoviv frameworkforgroupingnanoparticlesbasedontheirmeasurablecharacteristics
_version_	1718403060218200064

A framework for grouping nanoparticles based on their measurable characteristics

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