Scholarlink

<p>Replicating the intricate hierarchical architecture of natural vascular networks, especially at capillary-scale resolution, remains a pivotal challenge in organ fabrication. Here we present a machine learning-enhanced hybrid bioprinting strategy that combines high-resolution aerosol jet printing of sacrificial materials and high-throughput extrusion printing of tissue matrices. This integrated approach enables sub-10-µm resolution, achieving capillary-like channels and allowing on-demand modulation of vessel diameters in real time. Constrained Bayesian optimization rapidly identifies optimal printing parameters, ensuring reliable, high-fidelity attainment of target channel sizes without exhaustive trial and error. This streamlined workflow supports the fabrication from one-dimensional conduits to three-dimensional multibranch hierarchical networks with tunable geometries. Endothelial cells seeded into these channels form continuous, functional monolayers, substantially reducing permeability while maintaining high cell viability and proliferation. By transcending the resolution limits of conventional sacrificial printing, this bioprinting method establishes a new route for producing biomimetic vasculature. The combination of rapid optimization, real-time tunability and microcapillary-scale precision holds promise for tissue engineering, regenerative medicine and drug discovery.</p><p></p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Hybrid bioprinting of hierarchical vascular networks at capillary-scale resolution

  • 期刊论文

  • 发表日期：

    2026年5月28日

查看全文
  • Yuxuan Liao,
  • Salvador Gallegos-Martínez,
  • Xiao Kuang,
  • Yipu Du,
  • Yu Shrike Zhang,
  • Yanliang Zhang

摘要

Replicating the intricate hierarchical architecture of natural vascular networks, especially at capillary-scale resolution, remains a pivotal challenge in organ fabrication. Here we present a machine learning-enhanced hybrid bioprinting strategy that combines high-resolution aerosol jet printing of sacrificial materials and high-throughput extrusion printing of tissue matrices. This integrated approach enables sub-10-µm resolution, achieving capillary-like channels and allowing on-demand modulation of vessel diameters in real time. Constrained Bayesian optimization rapidly identifies optimal printing parameters, ensuring reliable, high-fidelity attainment of target channel sizes without exhaustive trial and error. This streamlined workflow supports the fabrication from one-dimensional conduits to three-dimensional multibranch hierarchical networks with tunable geometries. Endothelial cells seeded into these channels form continuous, functional monolayers, substantially reducing permeability while maintaining high cell viability and proliferation. By transcending the resolution limits of conventional sacrificial printing, this bioprinting method establishes a new route for producing biomimetic vasculature. The combination of rapid optimization, real-time tunability and microcapillary-scale precision holds promise for tissue engineering, regenerative medicine and drug discovery.