Evidence map›Paper›PMID 41912488›Full record

ArticleMicrosystems & nanoengineering2026

Design of an automated cell batch microinjection system based on magnetic tweezers for zebrafish embryos.

Xiangyu Guo, Fanghao Wang, Antian Zhao, Youchao Zhang, Huanyu Jiang, Alois Knoll, Meixiao Shen, Fan Lv, Mingchuan Zhou

Abstract read
In one paragraph

Article in Microsystems & nanoengineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Xiangyu GuoEye Research Center, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Eye Hospital, Wenzhou Medical University, Hangzhou, China.
Fanghao WangRobotic Micro-nano Manipulation Lab, College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China.
Antian ZhaoRobotic Micro-nano Manipulation Lab, College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China.
Youchao ZhangRobotic Micro-nano Manipulation Lab, College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China.
Huanyu JiangRobotic Micro-nano Manipulation Lab, College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China.
Alois KnollSchool of Computation, Information and Technology Technical University of Munich, Munich, Germany.ORCID http://orcid.org/0000-0003-4840-076X
Meixiao ShenEye Research Center, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Eye Hospital, Wenzhou Medical University, Hangzhou, China.
Fan LvEye Research Center, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Eye Hospital, Wenzhou Medical University, Hangzhou, China.
Mingchuan ZhouRobotic Micro-nano Manipulation Lab, College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China. mczhou@zju.edu.cn.ORCID http://orcid.org/0000-0002-6944-1483

Funding

National Natural Science Foundation of China (National Science Foundation of China) 62576312
6 · The paper itself

Abstract

Batch microinjection significantly enhances throughput and reproducibility in gene delivery and developmental studies, thereby accelerating the advancement of intelligent experimentation in the life sciences. In this work, we propose a novel visual-guided automated batch microinjection system based on magnetic tweezers, designed for zebrafish embryos. The system enables rapid and precise cell reorientation and puncture by integrating a microfluidic chip with coupled fluidic and magnetic actuation for cell manipulation. To address the challenge of robust perception in a narrow microscopic field, we introduce a microscopic manipulation perception network (MMPN), which incorporates a dual-backbone architecture and an attention mechanism to enhance feature extraction and recognition accuracy. Experimental validation demonstrates a detection mean average precision (mAP) of 98.8% and a segmentation accuracy of 98.4%. The proposed system achieves an average operation time of 33.8 seconds per cell, with a cell survival rate of 88% and a reorientation error as low as 2.1

Identifiers

PMID41912488
PMCPMC13036081

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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.