Particokinetics: computational analysis of the superparamagnetic iron oxide nanoparticles deposition process
Walter HZ Cárdenas, Javier B Mamani, Tatiana T Sibov, Cristofer A Caous, Edson Amaro Jr, Lionel F GamarraInstituto do Cérebro, Hospital Israelita Albert Einstein, São Paulo, BrazilBackground: Nanoparticles in suspension are often utilized for intracellula...
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| Autores principales: | , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
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Dove Medical Press
2012
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| Acceso en línea: | https://doaj.org/article/58b2ed958f0f4077b5a62911cda70a66 |
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| Sumario: | Walter HZ Cárdenas, Javier B Mamani, Tatiana T Sibov, Cristofer A Caous, Edson Amaro Jr, Lionel F GamarraInstituto do Cérebro, Hospital Israelita Albert Einstein, São Paulo, BrazilBackground: Nanoparticles in suspension are often utilized for intracellular labeling and evaluation of toxicity in experiments conducted in vitro. The purpose of this study was to undertake a computational modeling analysis of the deposition kinetics of a magnetite nanoparticle agglomerate in cell culture medium.Methods: Finite difference methods and the Crank-Nicolson algorithm were used to solve the equation of mass transport in order to analyze concentration profiles and dose deposition. Theoretical data were confirmed by experimental magnetic resonance imaging.Results: Different behavior in the dose fraction deposited was found for magnetic nanoparticles up to 50 nm in diameter when compared with magnetic nanoparticles of a larger diameter. Small changes in the dispersion factor cause variations of up to 22% in the dose deposited. The experimental data confirmed the theoretical results.Conclusion: These findings are important in planning for nanomaterial absorption, because they provide valuable information for efficient intracellular labeling and control toxicity. This model enables determination of the in vitro transport behavior of specific magnetic nanoparticles, which is also relevant to other models that use cellular components and particle absorption processes.Keywords: magnetite, nanoparticles, diffusion, sedimentation, agglomerates, computational modeling, cellular labeling, magnetic resonance imaging |
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