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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Computer Methods and...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Computer Methods and Programs in Biomedicine
Article . 2021 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
DBLP
Article . 2022
Data sources: DBLP
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On the magnetic aggregation of Fe3O4 nanoparticles

Authors: Evangelos G. Karvelas; N. K. Lampropoulos; Lefteris Benos; Theodoros E. Karakasidis; Ioannis E. Sarris;

On the magnetic aggregation of Fe3O4 nanoparticles

Abstract

Background and objective In-vivo MRI-guided drug delivery concept is a personalized technique towards cancer treatment. A major bottleneck of this method, is the weak magnetic response of nanoparticles. A crucial improvement is the usage of paramagnetic nanoparticles aggregates since they can easier manipulated in human arteries than isolated particles. However its significance, not a comprehensive study to estimate the mean length and time to aggregate exists. Methods The present detailed numerical study includes all major discrete and continues forces and moments of the nanoscale in a global model. The effort is given in summarizing the effects of particle diameter and concentration, and magnetic field magnitude to comprehensive relations. Therefore, several cases with nanoparticles having various diameters and concentrations are simulated as magnetic field increases. Results It is found that aggregations with maximum length equal to 2000nm can be formed. In addition, the increase of the concentration leads to a decrease in the amount of the isolated particles. Consequently, 33% of the particles are isolated for the concentration of 2.25mg/ml while 13% for the concentration of 10mg/ml. Moreover, the increase of the permanent magnetic field and diameter of particles gives rise to an asymptotic behavior in the number of isolated particles. Furthermore, the mean length of aggregates scales linear with diameter and magnetic field, however, concentration increase results in a weaker effect. The larger aggregation that is formed is composed by 21 particles. Smaller time is needed for the completion of the aggregation process with larger particles. Additionally, the increase of the magnitude of the magnetic field leads to a decrease in the aggregation time process. Therefore, 8.5ms are needed for the completion of the aggregation process for particles of 100nm at B0=0.1T while 7ms at B0=0.9T. Surprisedly, the mean time to aggregate is of the same order as in microparticles, although, with an opposite trend. Conclusions In this study, the evolution of the mean length of aggregations as well as the completion time of the aggregation process in the nano and micro range is evaluated. The present results could be useful to improve the magnetic nanoparticles assisted drug delivery method in order to minimize the side effects from the convectional cancer treatments like radiation and chemotherapy.

Keywords

Magnetics, Drug Delivery Systems, Magnetic Fields, Humans, Nanoparticles, Particle Size

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
69
Top 1%
Top 10%
Top 1%
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