Evidence map›Paper›PMID 38753706›Full record

ArticlePloS one2024

Semi-automated protocol to quantify and characterize fluorescent three-dimensional vascular images.

Danny F Xie, Christian Crouzet, Krystal LoPresti, Yuke Wang, Christopher Robinson, William Jones, Fjolla Muqolli, Chuo Fang, David H Cribbs, Mark Fisher and 1 more

Abstract read
In one paragraph

Article in PloS one, 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.

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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

11 authors.

Danny F XieBeckman Laser Institute and Medical Clinic, University of California-Irvine, Irvine, CA, United States of America.ORCID 0000-0001-9838-5268
Christian CrouzetBeckman Laser Institute and Medical Clinic, University of California-Irvine, Irvine, CA, United States of America.
Krystal LoPrestiBeckman Laser Institute and Medical Clinic, University of California-Irvine, Irvine, CA, United States of America.
Yuke WangBeckman Laser Institute and Medical Clinic, University of California-Irvine, Irvine, CA, United States of America.
Christopher RobinsonBeckman Laser Institute and Medical Clinic, University of California-Irvine, Irvine, CA, United States of America.
William JonesBeckman Laser Institute and Medical Clinic, University of California-Irvine, Irvine, CA, United States of America.
Fjolla MuqolliBeckman Laser Institute and Medical Clinic, University of California-Irvine, Irvine, CA, United States of America.
Chuo FangDepartment of Neurology, University of California-Irvine, Irvine, CA, United States of America.
David H CribbsInstitute for Memory Impairments and Neurological Disorders, University of California-Irvine, Irvine, CA, United States of America.
Mark FisherBeckman Laser Institute and Medical Clinic, University of California-Irvine, Irvine, CA, United States of America.
Bernard ChoiBeckman Laser Institute and Medical Clinic, University of California-Irvine, Irvine, CA, United States of America.ORCID 0000-0002-4380-8291

Funding

Univ.of Calif., Irvine Cancer Center Support GrantP30CA062203 · NCI · UNIVERSITY OF CALIFORNIA-IRVINE · PI Christine Hui · 1994 to 2026
$57.9M
University of California Health Participation in the National COVID Cohort Collaborative (N3C)UL1TR001414 · NCATS · UNIVERSITY OF CALIFORNIA-IRVINE · PI COOPER, DAN M, VILAIN, ERIC J. · 2015 to 2023
$35.1M
Uncover Strategies Used By Biological SystemsP50GM076516 · NIGMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI NIE, QING · 2007 to 2016
$25.1M
HEMORHOLOGICAL FACTORS IN CEREBRAL ISCHEMIAR01NS020989 · NINDS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CRIBBS, DAVID HASTINGS, FISHER, MARK J · 1985 to 2022
$9.1M
Virtual Photonocs TechnologiesP41EB015890 · NIBIB · UNIVERSITY OF CALIFORNIA-IRVINE · PI DURKIN, ANTHONY · 2012 to 2017
$7.0M
NRSA Training CoreTL1TR001415 · NCATS · UNIVERSITY OF CALIFORNIA-IRVINE · PI CAIOZZO, VINCENT JAMES, HEAD, ELIZABETH · 2015 to 2023
$4.2M
Hypertensive Mechanisms of Cerebral MicrobleedsR21NS111984 · NINDS · UNIVERSITY OF CALIFORNIA-IRVINE · PI CRIBBS, DAVID HASTINGS, FISHER, MARK J · 2019 to 2019
$425k
Multiscale optical characterization of cerebrovascular structure, function and oxygen utilization in a novel mouse model of sporadic Alzheimer's diseaseR21AG066000 · NIA · UNIVERSITY OF CALIFORNIA-IRVINE · PI CHOI, BERNARD · 2020 to 2020
$411k
NCATS NIH HHS TL1 TR001415NCATS NIH HHS UL1 TR001414NCI NIH HHS P30 CA062203NIA NIH HHS R21 AG066000NIBIB NIH HHS P41 EB015890NIGMS NIH HHS P50 GM076516NINDS NIH HHS R01 NS020989NINDS NIH HHS R21 NS111984
6 · The paper itself

Abstract

The microvasculature facilitates gas exchange, provides nutrients to cells, and regulates blood flow in response to stimuli. Vascular abnormalities are an indicator of pathology for various conditions, such as compromised vessel integrity in small vessel disease and angiogenesis in tumors. Traditional immunohistochemistry enables the visualization of tissue cross-sections containing exogenously labeled vasculature. Although this approach can be utilized to quantify vascular changes within small fields of view, it is not a practical way to study the vasculature on the scale of whole organs. Three-dimensional (3D) imaging presents a more appropriate method to visualize the vascular architecture in tissue. Here we describe the complete protocol that we use to characterize the vasculature of different organs in mice encompassing the methods to fluorescently label vessels, optically clear tissue, collect 3D vascular images, and quantify these vascular images with a semi-automated approach. To validate the automated segmentation of vascular images, one user manually segmented one hundred random regions of interest across different vascular images. The automated segmentation results had an average sensitivity of 83±11% and an average specificity of 91±6% when compared to manual segmentation. Applying this procedure of image analysis presents a method to reliably quantify and characterize vascular networks in a timely fashion. This procedure is also applicable to other methods of tissue clearing and vascular labels that generate 3D images of microvasculature.

Indexed as

Imaging, Three-DimensionalAnimalsAutomationMiceMicrovessels

Identifiers

PMID38753706
PMCPMC11098357

What OpenQuestion holds

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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.