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Evaluation of Hepatic Progenitor and Hepatocyte-Like Cell Differentiation Using Machine Learning Analysis-Assisted

Sanghwa Lee1, Eunyoung Tak2, Jiwan Choi2

  • 1Biomedical Engineering Research Center, Asan Medical Center, Seoul 05505, Republic of Korea.

Biomaterials Research
|May 8, 2025
PubMed
Summary

A new technology uses AI and SERS to monitor stem cell differentiation into liver cells. This non-invasive method accurately tracks human mesenchymal stem cells (hMSCs) becoming hepatic progenitor cells (HPCs) and hepatocyte-like cells (HLCs).

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Area of Science:

  • Biotechnology
  • Regenerative Medicine
  • Nanotechnology

Background:

  • Human mesenchymal stem cells (hMSCs) differentiation into hepatocyte-like cells (HLCs) and hepatic progenitor cells (HPCs) offers ethical alternatives for liver injury therapies.
  • Optimizing cell differentiation is crucial for enhancing cell-based therapy efficacy.

Purpose of the Study:

  • To develop and validate a high-sensitivity, label-free, real-time monitoring technology for hMSC differentiation into HPCs and HLCs.
  • To integrate artificial intelligence (AI) with advanced sensing for evaluating and optimizing the differentiation process.

Main Methods:

  • Utilized an Au-ZnO nanorod array-based surface-enhanced Raman scattering (SERS) sensing chip for non-destructive spectral analysis of cell secretions.
  • Employed principal component-linear discriminant analysis (PC-LDA), an AI algorithm, for spectral data analysis and cell classification.
  • Monitored spectral changes during hMSC to HPC and HPC to HLC differentiation over several days.

Main Results:

  • Achieved high monitoring accuracies: 96.3% for hMSCs, 98.8% for HPCs, and 98.8% for HLCs using PC-LDA.
  • Demonstrated clear spectral grouping of hMSCs, HPCs, and HLCs, confirming differentiation stages.
  • Validated the effectiveness of SERS combined with machine learning for real-time, non-destructive differentiation monitoring.

Conclusions:

  • The SERS-based system with AI analysis provides a robust platform for real-time, non-destructive monitoring and validation of stem cell differentiation.
  • This technology shows significant potential for clinical applications, including the use of patient-derived samples for liver disease therapies.