Evidence map›Paper›PMID 38680536›Full record

ArticleCyborg and bionic systems (Washington, D.C.)2024

Magnetic Soft Microrobot Design for Cell Grasping and Transportation.

Fanghao Wang, Youchao Zhang, Daoyuan Jin, Zhongliang Jiang, Yaqian Liu, Alois Knoll, Huanyu Jiang, Yibin Ying, Mingchuan Zhou

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cyborg and bionic systems (Washington, D.C.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Review
  3. Embodied Cross-Domain Intelligence in Biomedical Microrobots: A Review.Cyborg and bionic systems (Washington, D.C.) · 2026
    Review
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  5. Review
  6. Review
  7. Review
  8. Review
  9. Review
  10. Article
  11. Review
  12. Article
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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

9 authors.

Fanghao WangCollege of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China.
Youchao ZhangCollege of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China.
Daoyuan JinCollege of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China.
Zhongliang JiangTUM School of Computation, Information, and Technology, Garching 85748, Germany.
Yaqian LiuCollege of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China.
Alois KnollTUM School of Computation, Information, and Technology, Garching 85748, Germany.
Huanyu JiangCollege of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China.
Yibin YingCollege of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China.
Mingchuan ZhouCollege of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Manipulating cells at a small scale is widely acknowledged as a complex and challenging task, especially when it comes to cell grasping and transportation. Various precise methods have been developed to remotely control the movement of microrobots. However, the manipulation of micro-objects necessitates the use of end-effectors. This paper presents a study on the control of movement and grasping operations of a magnetic microrobot, utilizing only 3 pairs of electromagnetic coils. A specially designed microgripper is employed on the microrobot for efficient cell grasping and transportation. To ensure precise grasping, a bending deformation model of the microgripper is formulated and subsequently validated. To achieve precise and reliable transportation of cells to specific positions, an approach that combines an extended Kalman filter with a model predictive control method is adopted to accomplish the trajectory tracking task. Through experiments, we observe that by applying the proposed control strategy, the mean absolute error of path tracking is found to be less than 0.155 mm. Remarkably, this value accounts for only 1.55% of the microrobot's size, demonstrating the efficacy and accuracy of our control strategy. Furthermore, an experiment involving the grasping and transportation of a zebrafish embryonic cell (diameter: 800 μm) is successfully conducted. The results of this experiment not only validate the precision and effectiveness of the proposed microrobot and its associated models but also highlight its tremendous potential for cell manipulation in vitro and in vivo.

Identifiers

PMID38680536
PMCPMC11052606

What OpenQuestion holds

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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.