Search bioRxiv⌕ Search

bioRxiv · 10.1101/2025.06.22.659147

Integration of customizable 3D printed mixing printheads for controlled and tuneable material and stiffness gradient fabrication with high cell viability in extrusion-based bioprinting

Abstract

The fabrication of native tissue-like structures with gradual transitions in material properties, cell types and growth factors remains a major challenge in biofabrication. Particularly the complex hierarchical organization, present in living tissues, has to be mimicked as close as possible for the created models to fulfil the desired function. However, the fabrication of gradual structures incorporating several materials ensuring high cell survival and subsequent unaffected tissue maturation is highly challenging. To get a step closer to the goal of generating tissue models containing controlled gradient structures, here we show a novel approach combining extrusion- based 3D bioprinting with static mixing, using self-designed Digital Light Processing (DLP) printed mixing units to fabricate defined gradual structures. Two passive mixing geometries, sinusoidal and obstacle-based, are designed and fabricated and benchmarked against commercially available static mixers. The mixing performance is assessed pixelwise using dyed alginate solutions that are extruded through the mixers using an adapted 3D printer equipped with cavity pumps. The obstacle structure exhibits the highest mixing rate compared to the sinusoidal design and commercially available static mixers. Beyond mixing efficiency, the biological compatibility of the systems is assessed by evaluating the viability of U87 and NIH3T3 cells after extrusion. Two distinct polymer solutions of differing viscosities, composed of allyl-modified gelatin (gelAGE), polyethylene glycol dithiol (PEG-2-SH), and Matrigel, are extruded through the static mixer, revealing significantly higher cell viability in the self-designed printheads compared to commercial mixers. Subsequently, graded structures mimicking the mechanical profile of native brain tissue are fabricated and mechanically characterized using nanoindentation, confirming the successful generation of continuous stiffness gradients. In summary, this study demonstrates that combining extrusion-based 3D printing with customizable mixing units enables the controlled fabrication of tissue-like gradient structures with enhanced mixing rates and cell viability. The design flexibility and rapid fabrication of DLP-printed printheads enable the adaptation to specific tissue requirements, providing a robust platform for future developments in biofabrication and tissue engineering. This work serves as foundation for the creation of increasingly complex and functional tissue models.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Hofmann, F., Faber, J., Moser, F., Cianciosi, A., Murenu, N., Schenk, J., Heinze, K., Schaefer, N., Budday, S., Jungst, T.. 2025-06-26. Integration of customizable 3D printed mixing printheads for controlled and tuneable material and stiffness gradient fabrication with high cell viability in extrusion-based bioprinting. https://doi.org/10.1101/2025.06.22.659147

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Ferrybots: Programmable Hydrogel Microbots for Rapid Magnetic Navigation and Modular Function

Untethered microrobots could enable localized delivery, sensing, and intervention in confined biological and engineered environments. Magnetic actuation is especially attractive for such systems because it provides remote, fuel-free control, but practical magnetic microrobots remain difficult to manufacture and functionalize. High magnetic loading can interfere with polymerization and structural integrity, while integrating application-specific payloads directly into the robot body often requires the entire material formulation to be redesigned. Here, we introduce Ferrybots, programmable hydrogel microrobots that physically separate magnetic navigation from functional cargo. An automated droplet-on-demand microfluidic flow-lithography process confines high-concentration ferrofluid cores within photopolymerized poly (ethylene glycol) diacrylate (PEGDA) structures, enabling magnetic loading to be programmed through core number and spacing without uniformly dispersing magnetic particles throughout the hydrogel. The process achieved a minimum fabrication cycle time of 15 s. Ferrybots exhibited magnetic-dose-dependent translation and rotation, branched-channel steering, out-of-plane obstacle traversal, and rapid translation, with two-core robots following an external magnet at speeds up to the 9000 mm/min limit of the actuation system. Differences in magnetic loading also enabled sequential selective navigation of distinct Ferrybot populations. Using PEGDA 575 as a common interface material, independently formulated hydrogel cargo modules could subsequently be fused to preformed Ferrybots while preserving navigation. Separately, cargo modules enabled composition-dependent molecular release and oxygen-responsive sensing through 1-mm-thick skin-mimicking optical phantoms representing a broad range of skin types. By decoupling locomotion from function, Ferrybots provide a common magnetic vehicle that can be combined with interchangeable delivery, sensing, or responsive-material modules, offering a general strategy for rapidly adapting microrobots to different applications.

bioengineering↗

Circular-Arc Modal Migration for Ultrasound Imaging--Part I: Finite-Arc Spectral Theory and Stolt-Pullback Factorization

Circular-arc ultrasound imaging requires a spectral construction that accommodates radius-dependent propagation and the spatially varying phase of offset-source transmission. This first of two articles develops Circular-Arc Modal Migration (CAMM), a direct Stolt-type imaging framework in angular modal coordinates. Starting from a first-Born acoustic model, angular decomposition and local radial Stolt mappings convert channel spectra into fields for coherent image synthesis. The offset transmit phase is represented by a phase-screen factorization through reusable spectral factors and spatially weighted fields. A scalar-pullback approximation simplifies this correction to reading one reference image at a geometrically fitted radial coordinate. Both realizations share the same modal construction. Error controls address local radial synthesis, transmit-path expansion, scalar approximation, and phase-screen truncation, with direct integration verifying the separated numerical evaluation. Same-RF point-target comparisons show that scalar pullback closely preserves the principal peak positions and widths of phase-screen imaging in the compact semicircular configuration, while phase screens better control surrounding responses in the shallow convex examples. The retained modal spectrum, frequency band, image radius, and source displacement guide this accuracy--computation choice. CAMM thereby extends direct spectral image formation to circular arcs and supplies the theoretical and numerical basis for the image-quality and performance studies in Part~II.

bioengineering↗

Identification and isolation of migratory subpopulations of cancer cells using microfluidics with fluid walls

Microfluidic assays have great potential for investigating cancer cell migration, a key process underlying metastasis which remains a major clinical challenge. However, adoption by biologists is limited due to complex fabrication and operation methods combined with difficulty in retrieving cells of interest. We jet-print dumbbell-shaped microfluidic environments with fluid walls in standard Petri dishes in seconds using standard growth media and immiscible oil. Prostate cancer cells and chemoattractant (bovine serum) are introduced into each end using local transient differences in Laplace pressure to enable spatial confinement. Automated live-cell imaging monitors chemotaxis towards serum using standard microscopes, as the confining fluid walls are optically transparent. Distinct subpopulations of migratory cells exhibit different morphologies and motilities, assessed using a custom machine-learning segmentation model. Then, we leverage the reconfigurability of fluid walls to isolate and retrieve rapidly-migrating single cells. This demonstrates that fluid-walled microfluidics is a versatile and accessible approach for investigating cancer cell migration at single-cell resolution, offering new opportunities to examine cellular heterogeneity in metastasis.

bioengineering↗