Evidence map›Paper›PMID 40608767›Full record

ArticlePLoS biology2025

Highly accurate image registration for 3D multiplexed cyclic imaging using dense labeling in expandable tissue gels.

Hyunwoo Kim, Joon-Goon Kim, Jueun Sim, Hoyeon Nam, In Cho, Hyejin Shin, Junyoung Kwon, Dae-Hyeon Song, Seoungbin Bae, Young-Gyu Yoon and 2 more

Abstract read
In one paragraph

Article in PLoS biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

12 authors.

Hyunwoo KimDepartment of Materials Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
Joon-Goon KimGraduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
Jueun SimDepartment of Materials Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
Hoyeon NamDepartment of Materials Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
In ChoDepartment of Materials Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
Hyejin ShinDepartment of Materials Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
Junyoung KwonDepartment of Materials Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
Dae-Hyeon SongDepartment of Materials Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
Seoungbin BaeSchool of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
Young-Gyu YoonSchool of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
Taeyun KuGraduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
Jae-Byum ChangDepartment of Materials Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.ORCID 0000-0002-3554-5647

Funding

Bio & Medical Technology Development Program of the NRFKorea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI)Korean government (MSIT)Ministry of Health & Welfare, Republic of KoreaNational Research Foundation of Korea (NRF)
6 · The paper itself

Abstract

Multiplexed cyclic imaging in expandable tissue gels has been extensively studied to visualize numerous biomolecules at a nanoscale resolution in situ. Previous studies have employed sparse labels, such as DAPI or lectin staining, as registration markers. However, these sparse labels do not adequately capture the full extent of deformation across the entire region of interest. To overcome this challenge, we propose the use of dense labels, specifically fluorophore N-hydroxysuccinimide (NHS)-ester staining, as registration markers to achieve highly accurate image registration. We first tested several NHS-functionalized fluorophores as fiducial markers and identified the proper candidates for three-dimensional (3D) multiplexed cyclic imaging. We analyzed the registration accuracy between DAPI and NHS-ester staining and illustrated that dense label-based registration provides a more accurate registration performance. In the multiplexed imaging of expanded specimens, we observed that repetitive expansion/shrinking processes and chemical treatments for signal elimination can induce 3D nonlinear distortion. This sample distortion can be mitigated by re-embedding the tissue gel or replacing the chemical de-staining process with photobleaching-based signal removal or computational signal unmixing. With such an optimized experimental setup, we demonstrated 3D multiplexed cyclic imaging with nanoscale precision image registration. Finally, we prove that dense biological structures, such as actin, can be used as registration markers to achieve high registration accuracy. We anticipate that the proposed dense labeling strategy will overcome the technical limitations of multiplexed cyclic imaging in expandable tissue gels, offering high-precision registration. We expect it to be widely adopted by the biological and medical communities.

Indexed as

Imaging, Three-DimensionalAnimalsFluorescent DyesGelsHumansMiceStaining and LabelingSuccinimidesFluorescent DyesGelsN-hydroxysuccinimideSuccinimides

Identifiers

PMID40608767
PMCPMC12225881

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.