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Deciphering Fluid Transport Within Leaf-Inspired Capillary Networks Based on a 3D Computational Model.

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Area of Science:

  • Biomimetic engineering
  • Fluid dynamics
  • Vascular biology

Background:

  • Leaf venation serves as a model for efficient fluid transport in capillary networks.
  • Understanding fluid transport in leaf-inspired capillary networks (LICNs) is crucial for biological applications.
  • Existing methods lack quantitative analysis of internal flow characteristics in LICNs.

Purpose of the Study:

  • To develop a computational model for simulating fluid flow in LICNs.
  • To investigate the defect-resistant fluid transport capabilities of LICNs.
  • To optimize parameters for in vitro endothelialized capillary network formation.

Main Methods:

  • A centerline-induced partition-assembly strategy was used to create a 3D computational model.
  • 3D flow simulations were performed to analyze fluid transport characteristics.
  • The model was used to determine optimal perfusion parameters for endothelialized networks.

Main Results:

  • LICNs exhibit excellent defect-resistant fluid transport.
  • Structural defects in primary channels can increase overall perfusion efficiency.
  • Flow patterns in defective LICNs can be predicted by superposition.
  • Endothelialized networks recapitulated vascular colonization and showed shear stress-dependent cancer cell adhesion.

Conclusions:

  • The developed 3D model provides a quantitative tool for analyzing fluid and biological transport in LICNs.
  • LICNs demonstrate potential for engineering vascularized tissues and understanding cancer cell behavior.
  • This approach facilitates the exploration of LICNs for diverse biomedical applications.