Evidence map›Paper›PMID 40706593›Full record

ArticleCell reports methods2025

Volumetric imaging and computation to explore contractile function in zebrafish hearts.

Alireza Saberigarakani, Riya P Patel, Milad Almasian, Xinyuan Zhang, Jonathan Brewer, Sohail S Hassan, Jichen Chai, Juhyun Lee, Baowei Fei, Jie Yuan and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell reports methods, 2025. 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. Article
  2. Zebrafish in Cardiovascular Disease Research: from Model to Application.International journal of biological sciences · 2026
    Review
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Alireza SaberigarakaniDepartment of Bioengineering, The University of Texas at Dallas, Richardson, TX 75080, USA.
Riya P PatelDepartment of Biology, The University of Texas at Dallas, Richardson, TX 75080, USA.
Milad AlmasianDepartment of Bioengineering, The University of Texas at Dallas, Richardson, TX 75080, USA.
Xinyuan ZhangDepartment of Bioengineering, The University of Texas at Dallas, Richardson, TX 75080, USA.
Jonathan BrewerDepartment of Bioengineering, The University of Texas at Dallas, Richardson, TX 75080, USA.
Sohail S HassanDepartment of Bioengineering, The University of Texas at Dallas, Richardson, TX 75080, USA.
Jichen ChaiDepartment of Bioengineering, The University of Texas at Dallas, Richardson, TX 75080, USA.
Juhyun LeeDepartment of Bioengineering, The University of Texas at Arlington, Arlington, TX 76019, USA.
Baowei FeiDepartment of Bioengineering, The University of Texas at Dallas, Richardson, TX 75080, USA; Center for Imaging and Surgical Innovation, The University of Texas at Dallas, Richardson, TX 75080, USA.
Jie YuanDepartment of Bioengineering, The University of Texas at Dallas, Richardson, TX 75080, USA.
Kelli CarrollDepartment of Biology, Wofford College, Spartanburg, SC 29303, USA.
Yichen DingDepartment of Bioengineering, The University of Texas at Dallas, Richardson, TX 75080, USA; Center for Imaging and Surgical Innovation, The University of Texas at Dallas, Richardson, TX 75080, USA; Hamon Center for Regenerative Science and Medicine, UT Southwestern Medical Center, Dallas, TX 75390, USA. Electronic address: yichen.ding@utdallas.edu.

Funding

High spatiotemporal optical imaging to study dynamics of 3D cell motion and behavior in living organismsR35GM150947 · NIGMS · UNIVERSITY OF TEXAS ARLINGTON · PI Juhyun Lee · 2023 to 2026
$1.5M
Volumetric imaging and computation to characterize cardiac electromechanical couplingR01HL162635 · NHLBI · UNIVERSITY OF TEXAS DALLAS · PI Yichen Ding · 2023 to 2026
$1.5M
Integrating imaging and computation to characterize neural crest cells in the myocardial development and regenerationR00HL148493 · NHLBI · UNIVERSITY OF TEXAS DALLAS · PI DING, YICHEN · 2020 to 2022
$730k
NHLBI NIH HHS R00 HL148493NHLBI NIH HHS R01 HL162635NIGMS NIH HHS R35 GM150947
6 · The paper itself

Abstract

Novel insights into cardiac contractile dysfunction at the cellular level could deepen understanding of arrhythmia and heart injury, which are leading causes of morbidity and mortality worldwide. We present a comprehensive experimental and computational framework combining light-field microscopy and single-cell tracking to investigate real-time volumetric data in live zebrafish hearts, which share structural and electrical similarities to the human heart. Our system acquires 200 vol/s with lateral resolution of up to 5.02 ± 0.54 μm and axial resolution of 9.02 ± 1.11 μm across the whole depth using an expectation-maximization-smoothed deconvolution algorithm. We apply a deep-learning approach to quantify cell displacement and velocity in blood flow and myocardial motion and to perform real-time volumetric tracking from end-systole to end-diastole within a virtual reality environment. This capability delivers high-speed and high-resolution imaging of cardiac contractility at single-cell resolution over multiple cycles, supporting in-depth investigation of intercellular interactions in health and disease.

Indexed as

HeartMyocardial ContractionZebrafishAlgorithmsAnimalscardiac contractilitycell trackingCP: Computational biologyCP: Imaginglight-field microscopyvirtual realityzebrafish

Identifiers

PMID40706593
PMCPMC12461643

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.