Evidence map›Paper›PMID 38706842›Full record

ArticleiScience2024

A robust vessel-labeling pipeline with high tissue clearing compatibility for 3D mapping of vascular networks.

Yating Deng, Jingtan Zhu, Xiaomei Liu, Junyao Dai, Tingting Yu, Dan Zhu

Abstract read
In one paragraph

Article in iScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. 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

6 authors.

Yating DengBritton Chance Center for Biomedical Photonics- MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China.
Jingtan ZhuBritton Chance Center for Biomedical Photonics- MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China.
Xiaomei LiuBritton Chance Center for Biomedical Photonics- MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China.
Junyao DaiBritton Chance Center for Biomedical Photonics- MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China.
Tingting YuBritton Chance Center for Biomedical Photonics- MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China.
Dan ZhuBritton Chance Center for Biomedical Photonics- MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The combination of vessel-labeling, tissue-clearing, and light-sheet imaging techniques provides a potent tool for accurately mapping vascular networks, enabling the assessment of vascular remodeling in vascular-related disorders. However, most vascular labeling methods face challenges such as inadequate labeling efficiency or poor compatibility with current tissue clearing technology, which significantly undermines the image quality. To address this limitation, we introduce a vessel-labeling pipeline, termed Ultralabel, which relies on a specially designed dye hydrogel containing lysine-fixable dextran and gelatins for double enhancement. Ultralabel demonstrates not only excellent vessel-labeling capability but also strong compatibility with all tissue clearing methods tested, which outperforms other vessel-labeling methods. Consequently, Ultralabel enables fine mapping of vascular networks in diverse organs, as well as multi-color labeling alongside other labeling techniques. Ultralabel should provide a robust and user-friendly method for obtaining 3D vascular networks in different biomedical applications.

Indexed as

biological sciencesbiological sciences toolsoptical imaging

Identifiers

PMID38706842
PMCPMC11068851

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.