Evidence map›Paper›PMID 36874479›Full record

ArticleBiomedical optics express2023

Three-dimensional cerebral vasculature topological parameter extraction of transgenic zebrafish embryos with a filling-enhancement deep learning network.

Chong Chen, YuJun Tang, Yao Tan, LinBo Wang, Hui Li

Abstract read
In one paragraph

Article in Biomedical optics express, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

5 authors.

Chong ChenSchool of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, 230041, China.ORCID https://orcid.org/0000-0002-6814-0013
YuJun TangSchool of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, 230041, China.
Yao TanSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China.
LinBo WangSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China.
Hui LiSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative analysis of zebrafish cerebral vasculature is essential for the study of vascular development and disease. We developed a method to accurately extract the cerebral vasculature topological parameters of transgenic zebrafish embryos. The intermittent and hollow vascular structures of transgenic zebrafish embryos, obtained from 3D light-sheet imaging, were transformed into continuous solid structures with a filling-enhancement deep learning network. The enhancement enables the extraction of 8 vascular topological parameters accurately. Quantitation of the zebrafish cerebral vasculature vessels with the topological parameters show a developmental pattern transition from 2.5 to 5.5 dpf.

Identifiers

PMID36874479
PMCPMC9979664

What Socratic holds

Textmetadata
Read underepoch 390

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 Socratic graph.