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Related Concept Videos

Pulse rhythm01:30

Pulse rhythm

Pulse rhythm refers to the pattern of pulsations within specific intervals, offering valuable insights into the regularity or irregularity of the heart's beats as observed through the pattern of pulsation within specific intervals. A regular pulse exhibits a consistent heart rate with uniform waveforms and pulsation force, variations of which can be classified as normal, weak, or bounding.
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Arrhythmia or dysrhythmia refers to an abnormal heart rhythm caused by a defect in the heart's conduction system. It can cause the heart to beat irregularly, too quickly, or too slowly, leading to symptoms like chest pain, shortness of breath, and fainting. Factors such as stress, caffeine, alcohol, nicotine, cocaine, certain drugs, congenital defects, diseases, and electrolyte abnormalities can trigger arrhythmias.
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Holter Monitor: 24-Hour Monitoring

Holter monitoring is a continuous electrocardiography (ECG) recording that tracks the heart's electrical activity over an extended period, generally 24 to 48 hours. This noninvasive diagnostic tool detects irregular heart rhythms that may not be captured during a standard ECG performed in a clinical setting.DeviceThe Holter monitor is a portable, small device connected to several electrodes on the patient's chest. These electrodes detect the heart's electrical signals and transmit them to the...
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Dysrhythmias V: Evaluating Dysrhythmias

Dysrhythmias, also known as arrhythmias, are disturbances in the heart's rhythm that range from benign to life-threatening. A thorough evaluation is crucial for appropriate management and involves a comprehensive medical history, physical examination, and various diagnostic tests.Medical HistorySymptoms: Collect detailed information on palpitations, dizziness, syncope, chest pain, and fatigue. Note their onset, frequency, and triggers.Previous Cardiac Issues: Document any history of heart...
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Related Experiment Video

Updated: May 20, 2026

Subtype-specific Optical Action Potential Recordings in Human Induced Pluripotent Stem Cell-derived Ventricular Cardiomyocytes
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Subtype-specific Optical Action Potential Recordings in Human Induced Pluripotent Stem Cell-derived Ventricular Cardiomyocytes

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Creating cell-specific computational models of stem cell-derived cardiomyocytes using optical experiments.

Janice Yang1, Neil J Daily2, Taylor K Pullinger1

  • 1Department of Pharmacological Sciences & Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.

Plos Computational Biology
|September 11, 2024
PubMed
Summary
This summary is machine-generated.

Researchers developed a computational pipeline to calibrate human induced pluripotent stem cell-derived cardiomyocyte (iPSC-CM) electrophysiology. This method improves understanding of iPSC-CM variability and ion channel properties for better cardiac disease modeling.

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Area of Science:

  • Cardiology
  • Computational Biology
  • Stem Cell Research

Background:

  • Human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) are valuable for cardiac research but exhibit immature electrophysiology and lab-specific variability.
  • Existing mathematical models often fail to capture the full range of iPSC-CM phenotypic heterogeneity.
  • Genetic backgrounds of iPSC donors further contribute to variability in cell responses.

Purpose of the Study:

  • To develop a computational pipeline for calibrating cell preparation-specific electrophysiological parameters in iPSC-CMs.
  • To address limitations in current iPSC-CM models regarding phenotypic variability and maturation differences.
  • To optimize experimental protocols for generating sufficient data for accurate parameter calibration.

Main Methods:

  • Utilized a genetic algorithm (GA) to tune ion channel parameters within a mathematical model of iPSC-CM physiology.
  • Generated in silico datasets by simulating various experimental protocols on a population of models with known conductance variations.
  • Calibrated model parameters using voltage and calcium transient data under varied conditions, including electrical pacing, ion channel blockade, and buffer ion concentration changes.

Main Results:

  • Calibrating to voltage and calcium transient data under varied experimental conditions significantly improved model parameter estimates.
  • Model predictions for unseen channel block responses were enhanced after calibration.
  • Normalized fluorescence recordings, a higher-throughput method, sufficiently informed conductance parameters, similar to patch clamp recordings.

Conclusions:

  • The developed computational pipeline can determine cell line-specific ion channel properties in iPSC-CMs.
  • This approach aids in understanding the mechanisms underlying variability in iPSC-CM perturbation responses.
  • The pipeline offers a method to improve the accuracy and applicability of iPSC-CM models in cardiac research.