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Related Experiment Video

Updated: May 8, 2026

Reprogramming Primary Amniotic Fluid and Membrane Cells to Pluripotency in Xeno-free Conditions
09:34

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Published on: November 27, 2017

Deep Learning-Guided Holotomography Reveals Early Structural Remodelling During Pluripotency Exit.

Hoewon Park1,2, Geon Kim3,4, Jeongwon Shin1

  • 1Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea.

Biorxiv : the Preprint Server for Biology
|May 7, 2026
PubMed
Summary
This summary is machine-generated.

DeepHOPE, a novel deep-learning platform, non-invasively assesses human pluripotent stem cell (hPSC) quality using 3D imaging. It identifies early pluripotency loss indicators linked to cytoskeletal changes, improving regenerative medicine applications.

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Last Updated: May 8, 2026

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08:01

A Two-Step Strategy that Combines Epigenetic Modification and Biomechanical Cues to Generate Mammalian Pluripotent Cells

Published on: August 29, 2020

Area of Science:

  • Biotechnology
  • Stem Cell Biology
  • Regenerative Medicine

Background:

  • Assessing human pluripotent stem cell (hPSC) quality is crucial for safe and reproducible regenerative medicine.
  • Current methods for hPSC quality assessment are often invasive, labor-intensive, and operator-dependent.

Purpose of the Study:

  • To develop a non-invasive, automated, and statistics-driven platform for real-time hPSC quality assessment.
  • To integrate 3D refractive index imaging with deep learning for pluripotency evaluation.

Main Methods:

  • Developed DeepHOPE (Deep-learning-guided Holotomography for Pluripotency Evaluation).
  • Utilized 3D refractive index imaging and deep learning algorithms.
  • Validated performance across various differentiation contexts (germ-layer, retinoic acid, reprogramming).

Main Results:

  • DeepHOPE demonstrated robust performance in diverse hPSC culture conditions.
  • The platform enabled streamlined cell production and improved differentiation efficiency via informed colony selection.
  • Mechanistically, DeepHOPE detected subtle topological changes preceding pluripotency loss, linked to F-actin remodeling and cytoskeletal dynamics.

Conclusions:

  • DeepHOPE offers a non-invasive, efficient method for real-time hPSC quality control.
  • Cytoskeletal dynamics, particularly actomyosin tension, are identified as upstream regulators of early pluripotency exit.
  • This technology can enhance reproducibility and safety in regenerative medicine applications.