Evidence map›Paper›PMID 38334642›Full record

ReviewCells2024

Advances in the Generation of Constructed Cardiac Tissue Derived from Induced Pluripotent Stem Cells for Disease Modeling and Therapeutic Discovery.

Truman J Roland, Kunhua Song

Open access · goldAbstract readReview
In one paragraph

Review in Cells, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.1field-weighted citation impact, top 14% 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

10 citing papers in PubMed, 9 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Truman J RolandHeart Institute, University of South Florida, Tampa, FL 33602, USA.ORCID 0009-0001-0927-9816
Kunhua SongHeart Institute, University of South Florida, Tampa, FL 33602, USA.ORCID 0000-0003-3805-4509
University of South Florida · US

Funding

Mechanisms for cell signaling in the control of cardiomyogenesisR01HL133230 · NHLBI · UNIVERSITY OF SOUTH FLORIDA · PI Kunhua Song · 2016 to 2026
$4.2M
Regulation of gene transcription and alternative splicing by a long non-coding RNAR01HL159086 · NHLBI · UNIVERSITY OF SOUTH FLORIDA · PI SONG, KUNHUA, VONDRISKA, THOMAS M. · 2022 to 2025
$2.1M
NHLBI NIH HHS R01 HL133230NHLBI NIH HHS R01 HL159086NIH HHS HL133230, HL159086
6 · The paper itself

Abstract

The human heart lacks significant regenerative capacity; thus, the solution to heart failure (HF) remains organ donation, requiring surgery and immunosuppression. The demand for constructed cardiac tissues (CCTs) to model and treat disease continues to grow. Recent advances in induced pluripotent stem cell (iPSC) manipulation, CRISPR gene editing, and 3D tissue culture have enabled a boom in iPSC-derived CCTs (iPSC-CCTs) with diverse cell types and architecture. Compared with 2D-cultured cells, iPSC-CCTs better recapitulate heart biology, demonstrating the potential to advance organ modeling, drug discovery, and regenerative medicine, though iPSC-CCTs could benefit from better methods to faithfully mimic heart physiology and electrophysiology. Here, we summarize advances in iPSC-CCTs and future developments in the vascularization, immunization, and maturation of iPSC-CCTs for study and therapy.

Indexed as

Induced Pluripotent Stem CellsDrug DiscoveryHeartHumansRegenerative Medicinecardiac organoid (CO)cardiovascular disease (CVD)disease modelingdrug discoveryengineered heart tissue (EHT)heart-on-a-chip (HoC)high-throughput screeninginduced pluripotent stem cell (iPSC)organ modelingregenerative medicineself-assemblytissue engineering

Identifiers

PMID38334642
PMCPMC10854966
OpenAlexW4391323665

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.