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Data-Driven Maturity Level Evaluation for Cardiomyocytes Derived from Human Pluripotent Stem Cells (Invited Paper).

Yan Hong1, Xueqing Huang1, Fang Li2

  • 1Department of Computer Science, New York Institute of Technology, Old Westbury, NY 11568, USA.

Electronics
|January 31, 2025
PubMed
Summary

Researchers developed a data-driven method to measure the maturity of human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs). This approach uses gene expression to accurately assess maturation, improving cardiac cell therapies and disease modeling.

Keywords:
cardiac gene selectioncardiovascular diseasesculture time predictiongene expressionhPSC-CM maturity

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Area of Science:

  • Biomedical Engineering
  • Stem Cell Biology
  • Cardiovascular Research

Background:

  • Cardiovascular diseases are a major global health concern.
  • Human pluripotent stem cells (hPSCs) differentiate into cardiomyocytes (hPSC-CMs) for disease modeling and therapies.
  • Immature hPSC-CMs limit their clinical and experimental utility, with a lack of standardized maturity metrics.

Purpose of the Study:

  • To develop a data-driven pipeline for quantifying hPSC-CM maturity.
  • To establish standardized metrics for assessing hPSC-CM maturation.
  • To identify key cardiac genes correlating with maturation stages.

Main Methods:

  • Utilized gene expression data across various cardiac development stages.
  • Employed machine learning algorithms to identify predictive genes.
  • Validated culture time as a proxy for maturity.

Main Results:

  • Developed a pipeline that quantifies hPSC-CM maturity using gene expression.
  • Achieved an average discrepancy of 4.461 days between predicted and observed culture time.
  • Identified CASQ2 (Calsequestrin 2) as the most critical gene associated with culture duration.

Conclusions:

  • Established a novel, data-driven framework for assessing hPSC-CM maturity.
  • This quantitative approach surpasses traditional qualitative methods.
  • Provides a foundation for real-time maturity monitoring devices and improved maturation strategies.