| Title |
Capture Efficiency of Biocompatible Magnetic Nanoparticles in Arterial Flow: A Computer Simulation for Magnetic Drug Targeting
|
|---|---|
| Published in |
Discover Nano, October 2015
|
| DOI | 10.1186/s11671-015-1127-5 |
| Pubmed ID | |
| Authors |
Thodsaphon Lunnoo, Theerapong Puangmali |
| Abstract |
The primary limitation of magnetic drug targeting (MDT) relates to the strength of an external magnetic field which decreases with increasing distance. Small nanoparticles (NPs) displaying superparamagnetic behaviour are also required in order to reduce embolization in the blood vessel. The small NPs, however, make it difficult to vector NPs and keep them in the desired location. The aims of this work were to investigate parameters influencing the capture efficiency of the drug carriers in mimicked arterial flow. In this work, we computationally modelled and evaluated capture efficiency in MDT with COMSOL Multiphysics 4.4. The studied parameters were (i) magnetic nanoparticle size, (ii) three classes of magnetic cores (Fe3O4, Fe2O3, and Fe), and (iii) the thickness of biocompatible coating materials (Au, SiO2, and PEG). It was found that the capture efficiency of small particles decreased with decreasing size and was less than 5 % for magnetic particles in the superparamagnetic regime. The thickness of non-magnetic coating materials did not significantly influence the capture efficiency of MDT. It was difficult to capture small drug carriers (D<200 nm) in the arterial flow. We suggest that the MDT with high-capture efficiency can be obtained in small vessels and low-blood velocities such as micro-capillary vessels. |
Mendeley readers
The data shown below were compiled from readership statistics for 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| South Africa | 1 | 1% |
| Unknown | 93 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 20 | 21% |
| Student > Ph. D. Student | 11 | 12% |
| Researcher | 6 | 6% |
| Student > Doctoral Student | 6 | 6% |
| Student > Bachelor | 6 | 6% |
| Other | 15 | 16% |
| Unknown | 30 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 25 | 27% |
| Physics and Astronomy | 8 | 9% |
| Chemical Engineering | 5 | 5% |
| Materials Science | 5 | 5% |
| Chemistry | 4 | 4% |
| Other | 15 | 16% |
| Unknown | 32 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 November 2015.
All research outputs
#6,748,456
of 25,373,627 outputs
Outputs from Discover Nano
#175
of 1,146 outputs
Outputs of similar age
#77,506
of 295,443 outputs
Outputs of similar age from Discover Nano
#2
of 18 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 1,146 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done well, scoring higher than 84% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 295,443 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.