ReviewTrends in cardiovascular medicine2014
Modeling heart disease in a dish: from somatic cells to disease-relevant cardiomyocytes.
Review in Trends in cardiovascular medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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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.
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.
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Who cites it
12 citing papers in PubMed, 23 citations in OpenAlex.
- Towards Improved HumanBiomedicines · 2023Review
- Translational potential of hiPSCs in predictive modeling of heart development and disease.Birth defects research · 2022Review
- Engineered Heart Slice Model of Arrhythmogenic Cardiomyopathy Using Plakophilin-2 Mutant Myocytes.Tissue engineering. Part A · 2019Article
- Autonomous and Non-autonomous Defects Underlie Hypertrophic Cardiomyopathy in BRAF-Mutant hiPSC-Derived Cardiomyocytes.Stem cell reports · 2016Article
- Biology of the cardiac myocyte in heart disease.Molecular biology of the cell · 2016Review
- Myocyte-fibroblast communication in cardiac fibrosis and arrhythmias: Mechanisms and model systems.Journal of molecular and cellular cardiology · 2016Review
- Patient-Specific Induced Pluripotent Stem Cell Models: Generation and Characterization of Cardiac Cells.Methods in molecular biology (Clifton, N.J.) · 2016Article
- Lessons from Toxicology: Developing a 21st-Century Paradigm for Medical Research.Environmental health perspectives · 2015Article
- CytoSpectre: a tool for spectral analysis of oriented structures on cellular and subcellular levels.BMC bioinformatics · 2015Article
- Toward Personalized Medicine: Using Cardiomyocytes Differentiated From Urine-Derived Pluripotent Stem Cells to Recapitulate Electrophysiological Characteristics of Type 2 Long QT Syndrome.Journal of the American Heart Association · 2015Article
- Induced pluripotent stem cells for cardiovascular disease: from product-focused disease modeling to process-focused disease discovery.Regenerative medicine · 2015Review
- Organ-on-a-chip platforms for studying drug delivery systems.Journal of controlled release : official journal of the Controlled Release Society · 2014Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
A scientific milestone that has tremendously impacted the cardiac research field has been the discovery and establishment of human-induced pluripotent stem cells (hiPSC). Key to this discovery has been uncovering a viable path in generating human patient and disease-specific cardiac cells to dynamically model and study human cardiac diseases in an in vitro setting. Recent studies have demonstrated that hiPSC-derived cardiomyocytes can be used to model and recapitulate various known disease features in hearts of patient donors harboring genetic-based cardiac diseases. Experimental drugs have also been tested in this setting and shown to alleviate disease phenotypes in hiPSC-derived cardiomyocytes, further paving the way for therapeutic interventions for cardiac disease. Here, we review state-of-the-art methods to generate high-quality hiPSC and differentiate them towards cardiomyocytes as well as the full range of genetic-based cardiac diseases, which have been modeled using hiPSC. We also provide future perspectives on exploiting the potential of hiPSC to compliment existing studies and gain new insights into the mechanisms underlying cardiac disease.
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Registered trials
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.