Embedded 3D Printing in Self-Healing Annealable Composites for Precise Patterning of Functionally Mature Human Neural...

Area of Science:

• Biomaterials Science
• Neuroscience
• Tissue Engineering

Background:

• Developing in vitro models of human neural tissue with controlled microenvironments is crucial for studying brain development and diseases.
• Current embedded printing methods are limited by the availability of suitable support materials.
• There is a need for novel biomaterials that mimic bulk hydrogels while providing granular gel-like support for high-fidelity printing.

Purpose of the Study:

• To present a modular platform for bioengineering neuronal networks using direct embedded 3D printing.
• To introduce Self-Healing Annealable Particle-Extracellular matrix (SHAPE) composites as a versatile printing support material.
• To enable the generation of mature, subtype-specific neurons with extended projections within engineered neural constructs.

Main Methods:

• Developed SHAPE composites comprising soft microgels in an extracellular matrix solution.
• Utilized direct embedded 3D printing of human stem cells within SHAPE composites.
• Incorporated multi-ink deposition and real-time oxygen monitoring capabilities.
• Created vascular-like channels within the engineered neural constructs.

Main Results:

• Achieved precise and programmable patterning of human stem cells.
• Generated mature subtype-specific neurons that extended projections into the support matrix.
• Demonstrated the ability to create complex, multi-component neural constructs.
• Successfully integrated vascular-like channels and monitored oxygen levels.

Conclusions:

• The SHAPE composite platform offers a versatile and modular approach for biomanufacturing neural constructs.
• This technology facilitates the creation of advanced in vitro models for neuroscience research.
• The platform has potential applications beyond neural tissue modeling, including other mechanically sensitive constructs.