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Related Concept Videos

Mesenchymal Stem Cells01:19

Mesenchymal Stem Cells

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Mesenchymal stem cells (MSCs) are adult stem cells that can differentiate into most connective tissue cell types, except for hematopoietic cells, depending upon the source of MSCs. For example, bone-marrow-derived MSCs (BM-MSCs) can differentiate into osteocytes, hepatocytes, and pancreatic and neuronal cells. MSCs can be isolated from various sources such as bone marrow, placenta, adipose tissue, teeth, and Wharton’s jelly, a gelatinous substance in the umbilical cord. The ease of their...
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Author Spotlight: Enhancing PSC-to-Functional Cell Differentiation Using ML Models Based on Live-Cell Bright-Field Imaging
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An Appearance Data-Driven Model Visualizes Cell State and Predicts Mesenchymal Stem Cell Regenerative Capacity.

Di Wu1,2,3, Lu Zhao1, Bingdong Sui1,4

  • 1Hospital of Stomatology, Guanghua School of Stomatology, South China Center of Craniofacial Stem Cell Research, Guangdong Provincial Key Laboratory of Stomatology, Sun Yat-sen University, Guangzhou, 510055, China.

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|June 8, 2022
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Summary

A new model predicts mesenchymal stem cell (MSC) regenerative capacity using cell appearance features like nucleus shape and size, alongside ERK1/2 signaling. This approach enhances MSC potency evaluation for clinical use.

Keywords:
cell appearancemathematical modelsmesenchymal stem cellspredictive modelsregenerative capacities

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Area of Science:

  • Biomedical Engineering
  • Cell Biology
  • Regenerative Medicine

Background:

  • Mesenchymal stem cells (MSCs) show therapeutic potential but lack standardized potency assessment.
  • Clinical application of MSCs is hindered by the absence of reliable evaluation methods.

Purpose of the Study:

  • To develop a function-oriented mathematical model for predicting MSC regenerative capacity (RC).
  • To identify key indices, including cell morphology and signaling pathways, that correlate with MSC potency.

Main Methods:

  • Developed a mathematical model using exhaustive testing to identify optimal predictive indices.
  • Validated the model's predictive power through screening experiments on new and treated MSCs.
  • Utilized RNA-sequencing to investigate the link between cell appearance and MSC stemness.

Main Results:

  • Identified four optimal indices: nucleus roundness, nucleus/cytoplasm ratio, side-scatter height, and ERK1/2.
  • Three of the identified indices are related to cell appearance.
  • Model accurately predicted MSC regenerative capacity in validation experiments.
  • Cell appearance indices were found to reflect MSC stemness and intracellular signaling.

Conclusions:

  • A data-driven model using cell appearance features can effectively predict MSC regenerative capacity and stemness.
  • This approach offers a reliable method for evaluating MSC potency, potentially advancing their clinical applications.