AIMC Topic: Myocytes, Cardiac

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Artificial intelligence-enabled "inherited noninvasive intracellular recording" for prolonged monitoring of cardiac action potentials.

Science advances
Intracellular action potential (AP) recording that allows long-term monitoring is challenging because permanent membrane penetration is impossible due to cell death or resealing of perforated cell membrane. Herein, an "inherited noninvasive intracell...

Deep-learning analysis of 3D microarchitectural remodeling in hypertrophic cardiomyopathy.

Science (New York, N.Y.)
Hypertrophic cardiomyopathy (HCM), a genetic heart disease defined by unexplained cardiac wall thickening, is a leading cause of sudden death worldwide. However, the three-dimensional organization of cardiac tissue underlying left ventricular hypertr...

Advances in large-scale electrophysiology with high-density microelectrode arrays.

Lab on a chip
A detailed functional characterization of electrogenic cells, such as neurons and cardiomyocytes, by means of high-density microelectrode arrays (HD-MEAs) has emerged as a powerful approach for inferring cellular phenotypes and elucidating fundamenta...

Integrated phenotypic and transcriptomic characterization of desmin-related cardiomyopathy in hiPSC-derived cardiomyocytes and machine learning-based classification of disease features.

European journal of cell biology
Desmin-related diseases are characterized by skeletal muscle weakness, cardiomyopathy, and respiratory dysfunction due to mutations in the desmin gene (DES), which encodes a protein essential for muscle cell integrity. This study investigates the eff...

Epistasis regulates genetic control of cardiac hypertrophy.

Nature cardiovascular research
Although genetic variant effects often interact nonadditively, strategies to uncover epistasis remain in their infancy. Here we develop low-signal signed iterative random forests to elucidate the complex genetic architecture of cardiac hypertrophy, u...

Automated phenotypic analysis and classification of drug-treated cardiomyocytes via synergized time-lapse holographic imaging and deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Predicting cardiovascular risk is critical for the therapy and control of cardiovascular illnesses. This work studies screening the toxicity of three drugs, (E-4031, isoprenaline, and sertindole) with various concentrations ...

Induced Pluripotent Stem Cells in Cardiomyopathy: Advancing Disease Modeling, Therapeutic Development, and Regenerative Therapy.

International journal of molecular sciences
Cardiomyopathies are a heterogeneous group of heart muscle diseases that can lead to heart failure, arrhythmias, and sudden cardiac death. Traditional animal models and in vitro systems have limitations in replicating the complex pathology of human c...

Prediction of cardiac differentiation in human induced pluripotent stem cell-derived cardiomyocyte supernatant using surface-enhanced Raman spectroscopy and machine learning.

Biosensors & bioelectronics
The efficient manufacturing of cardiomyocytes from human-induced pluripotent stem cells (hiPSCs) is essential for advancing regenerative therapies for myocardial injuries. However, ensuring cell quality during production is challenging since traditio...

Logic-based machine learning predicts how escitalopram attenuates cardiomyocyte hypertrophy.

Proceedings of the National Academy of Sciences of the United States of America
Cardiomyocyte hypertrophy is a key clinical predictor of heart failure. High-throughput and AI-driven screens have the potential to identify drugs and downstream pathways that modulate cardiomyocyte hypertrophy. Here, we developed LogiRx, a logic-bas...

Cardiac Heterogeneity Prediction by Cardio-Neural Network Simulation.

Neuroinformatics
The bidirectional interactions between brain and heart through autonomic nervous system is the prime focus of neuro-cardiology community. The computer models designed to analyze brain and heart signals are either complex in terms of molecular and cel...