Process-optimized gelatin methacryloyl-konjac glucomannan dual-network hydrogels for stable and reproducible extrusion-based 3D bioprinting

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Mendoza-Cerezo, Laura
Rodríguez-Rego, Jesús M.
Macías-García, Antonio
Marcos Romero, Alfonso Carlos

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Mendoza-Cerezo L, Rodríguez-Rego JM, Macías-García A, Díaz-Prado SM, Marcos-Romero AC. Process-optimized gelatin methacryloyl-konjac glucomannan dual-network hydrogels for stable and reproducible extrusion-based 3D bioprinting. Int J Biol Macromol. 2026 Apr;353:151279.

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[Abstract] Dual-network hydrogels are promising candidates for extrusion-based bioprinting because they combine reversible physical interactions with covalent stabilization, enabling controlled flow during printing and structural integrity after deposition. Here, we present a hybrid gelatin methacryloyl (GelMA)-konjac glucomannan (KGM) hydrogel in which KGM forms a physically crosslinked network mediated by hydrogen-bond interactions under physiological pH (7.5) and temperature (37 °C), while the GelMA phase provides covalent stabilization upon photocrosslinking. Rheological analysis demonstrated increased low-shear viscosity, pronounced shear-thinning behavior, and rapid structural recovery after deformation. These properties significantly reduced the extrusion force required to achieve continuous and stable filaments and improved the fidelity of multilayer constructs. Mechanical characterization revealed tunable stiffness and enhanced self-supporting capacity, supporting shape retention and mechanical stability, as confirmed by compressive modulus measurements and post-printing structural stability. Cytocompatibility assays confirmed preserved metabolic activity and membrane integrity in contact with cultured cells. Overall, the GelMA-KGM dual-network hydrogel represents a process-optimized bioink platform for stable and reproducible extrusion-based 3D bioprinting, without the need for ionic crosslinking, particulate fillers, or additional chemical additives.

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© 2026 The Authors. Published by Elsevier B.V.
Attribution 4.0 International
© 2026 The Authors. Published by Elsevier B.V.

Except where otherwise noted, this item's license is described as © 2026 The Authors. Published by Elsevier B.V.