ReviewCell reports. Medicine2026
Human iPSC models of myocardial infarction: From injury to repair and therapeutic discovery.
Review in Cell reports. Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
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0 citing papers in PubMed.
No citing paper in PubMed yet.
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Myocardial infarction (MI) remains a leading cause of death worldwide, and therapies that limit injury, promote repair, and restore cardiac function remain limited. Human induced pluripotent stem cells (hiPSCs) provide a renewable source of patient-specific cardiac cells and have enabled the development of increasingly complex in vitro models that incorporate cardiomyocytes together with supporting stromal and vascular cell types. These models are now being used to study multiple stages of MI pathophysiology and are increasingly being applied in therapeutic discovery and regenerative strategies. In this review, we summarize hiPSC-based cardiac models spanning 2D cultures to advanced 3D tissues, organoids, and heart-on-chip systems, evaluating how well they capture key features of human MI. We further discuss hiPSC applications in therapeutic discovery, drug screening, precision medicine, and regenerative repair. Finally, we highlight priorities for the field, including improved physiological complexity, stronger translational robustness, bioengineering strategies, and integration with multi-omics.
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