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Biosensors 2016, 6(2), 25; doi:10.3390/bios6020025

Optimal Magnetic Field for Crossing Super-Para-Magnetic Nanoparticles through the Brain Blood Barrier: A Computational Approach

1
Department of Mechanical Engineering, Sharif University of Technology, Tehran, PO Box: 11365-11155, Iran
2
Department of Electrical Engineering, York University, Toronto, ON M3J1P3, Canada
*
Authors to whom correspondence should be addressed.
Academic Editor: Jeff D. Newman
Received: 29 April 2016 / Revised: 6 June 2016 / Accepted: 7 June 2016 / Published: 14 June 2016
(This article belongs to the Special Issue Micro- and Nano-Bio-Interfaces)
View Full-Text   |   Download PDF [6904 KB, uploaded 14 June 2016]   |  

Abstract

This paper scrutinizes the magnetic field effect to deliver the superparamagnetic nanoparticles (SPMNs) through the Blood Brain Barrier (BBB). Herein we study the interaction between the nanoparticle (NP) and BBB membrane using Molecular Dynamic (MD) techniques. The MD model is used to enhance our understanding of the dynamic behavior of SPMNs crossing the endothelial cells in the presence of a gradient magnetic field. Actuation of NPs under weak magnetic field offers the great advantage of a non-invasive drug delivery without the risk of causing injury to the brain. Furthermore, a weak magnetic portable stimulator can be developed using low complexity prototyping techniques. Based on MD simulation results in this paper, SPMNs can cross the cell membrane while experiencing very weak mechanical forces in the range of pN. This study also derives guidelines for the design of the SPMNs dedicated to crossing the BBB using external magnetic fields. View Full-Text
Keywords: Molecular Dynamics simulation; force steering; Blood Brain Barrier; superparamagnetic nanoparticles Molecular Dynamics simulation; force steering; Blood Brain Barrier; superparamagnetic nanoparticles
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Pedram, M.Z.; Shamloo, A.; Alasty, A.; Ghafar-Zadeh, E. Optimal Magnetic Field for Crossing Super-Para-Magnetic Nanoparticles through the Brain Blood Barrier: A Computational Approach. Biosensors 2016, 6, 25.

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