Evidence map›Paper›PMID 35857830›Full record

ArticleScience advances2022

Microrobotic swarms for selective embolization.

Junhui Law, Xian Wang, Mengxi Luo, Liming Xin, Xingzhou Du, Wenkun Dou, Tiancong Wang, Guanqiao Shan, Yibin Wang, Peng Song and 3 more

Abstract read
In one paragraph

Article in Science advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing 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

45 citing papers in PubMed.

  1. Review
  2. Article
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  7. Article
  8. Enzymatic microbubble robots.Nature nanotechnology · 2026
    Article
  9. Article
  10. Recent Advances in Collective Behaviors of Micro/Nanomotor Swarms.Advanced materials (Deerfield Beach, Fla.) · 2026
    Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
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  18. 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

13 authors.

Junhui LawDepartment of Mechanical and Industrial Engineering, University of Toronto, Toronto, Canada.ORCID 0000-0002-6033-7639
Xian WangDepartment of Mechanical and Industrial Engineering, University of Toronto, Toronto, Canada.ORCID 0000-0002-1501-2544
Mengxi LuoDepartment of Mechanical and Industrial Engineering, University of Toronto, Toronto, Canada.
Liming XinSchool of Computer Engineering and Science, Shanghai University, Shanghai, China.ORCID 0000-0002-3447-9932
Xingzhou DuShenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, China.ORCID 0000-0002-8526-7286
Wenkun DouDepartment of Mechanical and Industrial Engineering, University of Toronto, Toronto, Canada.
Tiancong WangDepartment of Mechanical and Industrial Engineering, University of Toronto, Toronto, Canada.
Guanqiao ShanDepartment of Mechanical and Industrial Engineering, University of Toronto, Toronto, Canada.ORCID 0000-0002-2570-769X
Yibin WangShenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, China.ORCID 0000-0003-4361-606X
Peng SongDepartment of Interventional Therapy, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital and Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.ORCID 0000-0001-9803-9656
Xi HuangProgram in Developmental and Stem Cell Biology, The Hospital for Sick Children, Toronto, Canada.ORCID 0000-0002-7177-7525
Jiangfan YuShenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, China.ORCID 0000-0002-7981-6744
Yu SunDepartment of Mechanical and Industrial Engineering, University of Toronto, Toronto, Canada.ORCID 0000-0001-7895-0741

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inspired by the collective intelligence in natural swarms, microrobotic agents have been controlled to form artificial swarms for targeted drug delivery, enhanced imaging, and hyperthermia. Different from these well-investigated tasks, this work aims to develop microrobotic swarms for embolization, which is a clinical technique used to block blood vessels for treating tumors, fistulas, and arteriovenous malformations. Magnetic particle swarms were formed for selective embolization to address the low selectivity of the present embolization technique that is prone to cause complications such as stroke and blindness. We established an analytical model that describes the relationships between fluid viscosity, flow rate, branching angle, magnetic field strength, and swarm integrity, based on which an actuation strategy was developed to maintain the swarm integrity inside a targeted region under fluidic flow conditions. Experiments in microfluidic channels, ex vivo tissues, and in vivo porcine kidneys validated the efficacy of the proposed strategy for selective embolization.

Identifiers

PMID35857830
PMCPMC9299543

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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.