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2.5D Model for Ex Vivo Mechanical Characterization of Sprouting Angiogenesis in Living Tissue
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2D data-driven stalk cell prediction model based on tip-stalk cell interaction in angiogenesis.

Mengmeng Wang, Lee-Ling Sharon Ong, Justin Dauwels

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    This study models endothelial cell (EC) migration during blood vessel growth (angiogenesis). The model accurately predicts stalk cell movement based on tip cell trajectories, aiding angiogenesis research, particularly in cancer.

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    Area of Science:

    • Cell Biology
    • Biophysics
    • Computational Biology

    Background:

    • Angiogenesis involves endothelial cells (ECs) differentiating into tip and stalk cells.
    • Tip cells lead, forming conduits, while stalk cells follow to create new vessels.
    • Cell-cell interactions and physical forces govern EC migration dynamics.

    Purpose of the Study:

    • To develop a predictive model for stalk cell migration trajectories.
    • To utilize known tip cell trajectories as input for stalk cell prediction.
    • To understand the biophysical factors influencing stalk cell movement.

    Main Methods:

    • A mathematical model incorporating cell-cell interactions and drag forces was developed.
    • Chemotactic and cell-ECM interactions were excluded due to minimal influence on stalk cells.
    • Model parameters were estimated using Maximum Likelihood Estimation (MLE) from time-lapse imaging data.

    Main Results:

    • The model successfully predicted stalk cell migration trajectories.
    • Numerical simulations demonstrated high accuracy in trajectory prediction.
    • The model highlights the importance of cell-cell interactions and drag force.

    Conclusions:

    • The proposed model accurately predicts stalk cell behavior during angiogenesis.
    • This computational approach can advance the study of blood vessel formation.
    • Findings may contribute to understanding angiogenesis in cancer development.