Evidence map›Paper›PMID 30988697›Full record

ReviewJournal of biological engineering2019

Three-dimensional microengineered models of human cardiac diseases.

Jaimeson Veldhuizen, Raymond Q Migrino, Mehdi Nikkhah

Abstract readReview
In one paragraph

Review in Journal of biological engineering, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

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  17. Article
  18. Article
  19. Engineering and Assessing Cardiac Tissue Complexity.International journal of molecular sciences · 2021
    Review
  20. 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

3 authors.

Jaimeson Veldhuizen1School of Biological and Health Systems Engineering (SBHSE), Arizona State University, 501 E Tyler Mall Building ECG, Suite 334, Tempe, AZ 85287-9709 USA.
Raymond Q MigrinoPhoenix Veterans Affairs Health Care System, Phoenix, AZ 85012 USA.
Mehdi Nikkhah1School of Biological and Health Systems Engineering (SBHSE), Arizona State University, 501 E Tyler Mall Building ECG, Suite 334, Tempe, AZ 85287-9709 USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In vitro three-dimensional (3D) microengineered tissue models have been the recent focus of pathophysiological studies, particularly in the field of cardiovascular research. These models, as classified by 3D biomimetic tissues within micrometer-scale platforms, enable precise environmental control on the molecular- and cellular-levels to elucidate biological mechanisms of disease progression and enhance efficacy of therapeutic research. Microengineered models also incorporate directed stem cell differentiation and genome modification techniques that warrant derivation of patient-specific and genetically-edited human cardiac cells for precise recapitulation of diseased tissues. Additionally, integration of added functionalities and/or structures into these models serves to enhance the capability to further extract disease-specific phenotypic, genotypic, and electrophysiological information. This review highlights the recent progress in the development of in vitro 3D microengineered models for study of cardiac-related diseases (denoted as CDs). We will primarily provide a brief overview on currently available 2D assays and animal models for studying of CDs. We will further expand our discussion towards currently available 3D microengineered cardiac tissue models and their implementation for study of specific disease conditions.

Indexed as

CardiacDisease modelingMicroengineered modelsStem cells

Identifiers

PMID30988697
PMCPMC6448321

What OpenQuestion holds

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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.