Evidence map›Paper›PMID 33033849›Full record

ArticleAngiogenesis2021

Vessel tech: a high-accuracy pipeline for comprehensive mouse retinal vasculature characterization.

Xuelin Wang, Guofu Zhu, Shumin Wang, Jordan Rhen, Jinjiang Pang, Zhengwu Zhang

Open access · greenAbstract readLetter
In one paragraph

Article in Angiogenesis, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.1field-weighted citation impact, top 49% of its field
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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
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 at 4 institutions in 2 countries.

Xuelin Wang *Department of Biostatistics and Computational Biology, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA.
Guofu Zhu *Department of Cardiology, Pan-Vascular Research Institute, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai 200072, China.
Shumin WangAab Cardiovascular Research Institute, Department of Medicine, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA.
Jordan RhenAab Cardiovascular Research Institute, Department of Medicine, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA.
Jinjiang PangAab Cardiovascular Research Institute, Department of Medicine, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA. Jinjiang_pang@urmc.rochester.edu.ORCID http://orcid.org/0000-0001-6946-3941
Zhengwu ZhangDepartment of Biostatistics and Computational Biology, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA. zhengwu_zhang@urmc.rochester.edu.
University of Rochester · USRochester Institute of Technology · USTongji University · CNUniversity of Rochester Medical Center · US

Funding

The novel mechanisms of HIV associated vascular cognitive impairmentR01HL122777 · NHLBI · UNIVERSITY OF ROCHESTER · PI PANG, JINJIANG · 2014 to 2023
$4.1M
NHLBI NIH HHS R01 HL122777NIH HHS R01 HL122777-05NIH HHS R01 HL122777-06A1
6 · The paper itself

Abstract

Mouse retinal vasculature is a well-recognized and commonly used animal model for angiogenesis and microvascular remodeling. Morphological features of retinal vasculature reflect the vessel's biological functions, and are critical in understanding the physiological and pathological process of vascular development and disease. Here we developed a comprehensive software, Vessel Tech, using retinal vasculature images of postnatal mice. This pipeline can automatically process retinal vascular images, reconstruct vessel network with high accuracy and assess global and local vascular characteristics based on the recent machine-learning techniques. The development of Vessel Tech provides a powerful tool for vascular biologists.

Indexed as

SoftwareAnimalsEndothelial CellsImage Processing, Computer-AssistedMiceNeural Networks, ComputerRetinal VesselsAutomatic quantificationDeep learningMorphologic analysisMouse retinal vasculatureVascular development

Identifiers

PMID33033849
PMCPMC7920901
OpenAlexW3091817348

What OpenQuestion holds

Textmetadata
LicenceTDM
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 OpenQuestion graph.