Evidence map›Paper›PMID 35665220›Full record

ArticleFrontiers in physiology2022

High-Resolution 3D Heart Models of Cardiomyocyte Subpopulations in Cleared Murine Heart.

Huiying Ren, Zhaoli Pu, Tianyi Sun, Tangting Chen, Leiying Liu, Zhu Liu, Christopher O'Shea, Davor Pavlovic, Xiaoqiu Tan, Ming Lei

Open access · goldAbstract read
In one paragraph

Article in Frontiers in physiology, 2022. 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
0.8field-weighted citation impact, top 20% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Review
  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

10 authors at 4 institutions in 2 countries.

Huiying RenLaboratory of Medical Electrophysiology, Ministry of Education, Collaborative Innovation Center for Prevention and Treatment of Cardiovascular Disease/Institute of Cardiovascular Research, Luzhou Medical College, Luzhou, China.
Zhaoli PuLaboratory of Medical Electrophysiology, Ministry of Education, Collaborative Innovation Center for Prevention and Treatment of Cardiovascular Disease/Institute of Cardiovascular Research, Luzhou Medical College, Luzhou, China.
Tianyi SunDepartment of Pharmacology, University of Oxford, Oxford, United Kingdom.
Tangting ChenLaboratory of Medical Electrophysiology, Ministry of Education, Collaborative Innovation Center for Prevention and Treatment of Cardiovascular Disease/Institute of Cardiovascular Research, Luzhou Medical College, Luzhou, China.
Leiying LiuLaboratory of Medical Electrophysiology, Ministry of Education, Collaborative Innovation Center for Prevention and Treatment of Cardiovascular Disease/Institute of Cardiovascular Research, Luzhou Medical College, Luzhou, China.
Zhu LiuLaboratory of Medical Electrophysiology, Ministry of Education, Collaborative Innovation Center for Prevention and Treatment of Cardiovascular Disease/Institute of Cardiovascular Research, Luzhou Medical College, Luzhou, China.
Christopher O'SheaInstitute of Cardiovascular Sciences, College of Medicine and Dental Sciences, University of Birmingham, Birmingham, United Kingdom.
Davor PavlovicInstitute of Cardiovascular Sciences, College of Medicine and Dental Sciences, University of Birmingham, Birmingham, United Kingdom.
Xiaoqiu TanLaboratory of Medical Electrophysiology, Ministry of Education, Collaborative Innovation Center for Prevention and Treatment of Cardiovascular Disease/Institute of Cardiovascular Research, Luzhou Medical College, Luzhou, China.
Ming LeiLaboratory of Medical Electrophysiology, Ministry of Education, Collaborative Innovation Center for Prevention and Treatment of Cardiovascular Disease/Institute of Cardiovascular Research, Luzhou Medical College, Luzhou, China.
Southwest Medical University · CNUniversity of Birmingham · GBAffiliated Hospital of Southwest Medical University · CNUniversity of Oxford · GB

Funding

British Heart Foundation FS/PHD/20/29053British Heart Foundation PG/21/10512Medical Research Council G1002082
6 · The paper itself

Abstract

Biological tissues are naturally three-dimensional (3D) opaque structures, which poses a major challenge for the deep imaging of spatial distribution and localization of specific cell types in organs in biomedical research. Here we present a 3D heart imaging reconstruction approach by combining an improved heart tissue-clearing technique with high-resolution light-sheet fluorescence microscopy (LSFM). We have conducted a three-dimensional and multi-scale volumetric imaging of the ultra-thin planes of murine hearts for up to 2,000 images per heart in x-, y-, and z three directions. High-resolution 3D volume heart models were constructed in real-time by the Zeiss Zen program. By using such an approach, we investigated detailed three-dimensional spatial distributions of two specific cardiomyocyte populations including HCN4 expressing pacemaker cells and Pnmt

Indexed as

3D volume heart modelsHCN4 expression (HCN4+) pacemaker cellsheart tissue-clearinglight-sheet fluorescence microscopyoptogeneticsPnmt+ cell-derived cardiomyocytes (PdCMs)

Identifiers

PMID35665220
PMCPMC9158482
OpenAlexW4280562982

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.