3D-printed brain-like environment promotes neuron growth

A tool for studying brain disorders.

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Researchers at Delft University of Technology in The Netherlands have created a 3D-printed brain-like environment for neurons to grow, similar to how they do in the brain. They use tiny nanopillars to mimic the brain’s soft tissue and extracellular matrix fibers, helping to understand neuron networks and neurological disorders like Alzheimer’s, Parkinson’s, and autism.

Traditional petri dishes are flat and rigid, unlike the brain’s soft, fibrous environment. Researchers designed nanopillar arrays to replicate this using precise 3D laser printing called two-photon polymerization.

These pillars, thousands of times thinner than a human hair, trick neurons into “thinking” they are in a soft, brain-like environment. This influences how neurons grow and connect.

Researchers tested their model by growing three types of neuronal cells on the nanopillars. Unlike traditional flat dishes where neurons grew randomly, the 3D-printed nanopillars made neurons grow in organized patterns and form networks at specific angles.

nanopillars
Credit: TU Delft

The study revealed new insights into neuronal growth cones, which guide growing neurons to new connections. On the nanopillars, growth cones sent out long projections in all directions, mimicking real brain environments.

George Flamourakis, the study’s first author, noted that the nanopillars also encouraged neurons to mature. Compared to flat surfaces, neural progenitor cells grown on the nanopillars showed higher levels of a marker of mature neurons.

Associate professor Angelo Accardo explained that while soft materials like gels can grow neurons, they often lack precise geometric features and consistency.

The nanopillar arrays model combines a soft-like environment with nanometric features and high reproducibility. This better replicates how neurons grow and connect, offering new insights into healthy brain networks and neurological disorders.

Journal Reference:

  1. George Flamourakis, Qiangrui Dong, Dimitri Kromm, Selina Teurlings, et al. Deciphering the Influence of Effective Shear Modulus on Neuronal Network Directionality and Growth Cones’ Morphology via Laser-Assisted 33D-printedNanostructured Arrays. Advanced Functional Materials. DOI: 10.1002/adfm.202409451
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