Evidence map›Paper›PMID 33924499›Full record

ArticleMicromachines2021

Optimization of Field-Free Point Position, Gradient Field and Ferromagnetic Polymer Ratio for Enhanced Navigation of Magnetically Controlled Polymer-Based Microrobots in Blood Vessel.

Saqib Sharif, Kim Tien Nguyen, Doyeon Bang, Jong-Oh Park, Eunpyo Choi

Abstract read
In one paragraph

Article in Micromachines, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
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  4. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Saqib SharifSchool of Mechanical Engineering, Chonnam National University, Gwangju 61186, Korea.
Kim Tien NguyenSchool of Mechanical Engineering, Chonnam National University, Gwangju 61186, Korea.ORCID 0000-0003-1260-3610
Doyeon BangKorea Institute of Medical Microrobotics, Gwangju 61011, Korea.
Jong-Oh ParkSchool of Mechanical Engineering, Chonnam National University, Gwangju 61186, Korea.
Eunpyo ChoiSchool of Mechanical Engineering, Chonnam National University, Gwangju 61186, Korea.

Funding

Korea Health Industry Development Institute HI19C0642
6 · The paper itself

Abstract

Microscale and nanoscale robots, frequently referred to as future cargo systems for targeted drug delivery, can effectively convert magnetic energy into locomotion. However, navigating and imaging them within a complex colloidal vascular system at a clinical scale is exigent. Hence, a more precise and enhanced hybrid control navigation and imaging system is necessary. Magnetic particle imaging (MPI) has been successfully applied to visualize the ensemble of superparamagnetic nanoparticles (MNPs) with high temporal sensitivity. MPI uses the concept of field-free point (FFP) mechanism in the principal magnetic field. The gradient magnetic field (|∇B|) of MPI scanners can generate sufficient magnetic force in MNPs; hence, it has been recently used to navigate nanosized particles and micron-sized swimmers. In this article, we present a simulation analysis of the optimized navigation of an ensemble of microsized polymer MNP-based drug carriers in blood vessels. Initially, an ideal two-dimensional FFP case is employed for the basic optimization of the FFP position to achieve efficient navigation. Thereafter, a nine-coil electromagnetic actuation simulation system is developed to generate and manipulate the FFP position and |∇B|. Under certain vessel and fluid conditions, the particle trajectories of different ferromagnetic polymer ratios and |∇B| were compared to optimize the FFP position.

Indexed as

3D localizationfield-free pointmagnetic nanoparticlemicrorobots

Identifiers

PMID33924499
PMCPMC8070347

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.