T40 - Post-Print Reinforcement of GelMA/HAMA Scaffolds via PEGDA Infiltration

Friday, October 10, 2025

10:00 AM - 11:00 AM PDT

Location: Exhibit Hall F, G & H

Presenting Author(s)

SM

Sabina Martinez Carreon

Undergraduate Student
Southwestern University, United States

Co-Author(s)

BG

Bryan Guzman-Sanchez

Undergraduate Student
Southwestern University
San Antonio, Texas, United States
RR

Rishi Rajesh

Undergraduate Student
Southwestern University, United States
DM

Dany Munoz Pinto

Associate Professor of Engineering Science
Trinity University, United States

Last Author(s)

Cody Crosby, PhD

Assistant Professor of Physics
Southwestern University
Georgetown, Texas, United States

Primary Investigator(s)

Cody Crosby, PhD

Assistant Professor of Physics
Southwestern University
Georgetown, Texas, United States

Moderator(s)

Cody Crosby, PhD

Assistant Professor of Physics
Southwestern University
Georgetown, Texas, United States

Introduction: : The blood-brain barrier (BBB) is a highly selective endothelial barrier that regulates the exchange of molecules between the circulatory system and the central nervous system. While this regulation is essential for protecting neural tissue from toxins and pathogens, it also poses a significant challenge when delivering therapeutic agents. Many therapeutic molecules cannot cross the BBB, and in vivo studies are limited by technical and ethical constraints. Similarly, imaging the BBB in vivo is an invasive and technically challenging process because the thick cranial bone must be removed and the exposed site then maintained under physiological conditions.
To overcome these limitations, the development of in vitro BBB models is critical. An effective model must mimic the biophysical properties of brain tissue—namely, its limited elasticity and extracellular matrix (ECM) composition. It has been demonstrated that native brain parenchyma has a compressive modulus of less than 10 kPa and is rich in hyaluronic acid and structural proteins.
To create an in vitro biomimetic model of the BBB, we developed a bioprinted scaffold composed of gelatin methacryloyl (GelMA, "G") and hyaluronic acid methacrylate (HAMA, "H"), printed into a gelatin coacervate suspension bath to support the creation of complex geometries. While GelMA and HAMA together offer biocompatibility and ECM mimicry, they lack sufficient mechanical strength when used alone. We investigated the use of low-molecular-weight polyethylene glycol diacrylate (PEGDA, "P") as a secondary crosslinking agent to reinforce GelMA-HAMA networks post-printing, without compromising softness or cytocompatibility.

Materials and

Methods: : Dual-network hydrogel formulations were prepared via the stepwise addition of 0.02% w/v lithium phenyl-2,4,6-trimethylbenzoylphosphinate (LAP), 4% w/v GelMA, and 2% w/v HAMA in 5 mL of Ultrapure water in a scintillation vial. The mixture of these two polymers was incubated for 20 minutes at 37 °C to ensure proper dissolution of each component.. The hydrogels were cast directly in molds or printed into a gelatin coacervate suspension bath using the FRESH (Freeform Reversible Embedding of Suspended Hydrogels) bioprinting method and an unpublished open-source bioprinter. Cast and printed samples were UV-crosslinked (365 nm) for 6 minutes at ~4 mW/cm2 to form the primary network.
To investigate mechanical reinforcement, 3.4 kDa PEGDA was passively diffused into select cast or bioprinted groups at 7% (w/v) concentration. The hydrogels with infiltrated PEGDA then underwent a second UV crosslinking step to form an interpenetrating network.
Four sample conditions were evaluated in compression: G + H Cast, G + H + P Cast, G + H Print, and G + H + P Print. Each group contained five replicates. Mechanical properties were assessed using unconfined compression testing with a CellScale Univert and a Dynamic Mechanical Analyzer (DMA). Metrics recorded included storage modulus (kPa), stiffness (N/mm), and compressive modulus (kPa).

Results, Conclusions, and Discussions:: Mechanical testing demonstrated that PEGDA incorporation significantly improved the performance of both cast and printed GelMA-HAMA hydrogels. Among the four groups tested, G + H + P Print exhibited the highest average storage modulus (11.45 ± 1.79 kPa) and stiffness (13.46 ± 2.80 N/mm), followed closely by G + H + P Cast (7.36 ± 1.95 kPa, 12.68 ± 2.97 N/mm). In contrast, G + H Cast and G + H Print exhibited lower storage modulus values (5.19 ± 0.50 kPa and 2.42 ± 1.45 kPa, respectively) and stiffness values (9.74 ± 0.56 N/mm and 4.94 ± 0.71 N/mm, respectively), indicating reduced mechanical integrity in the absence of PEGDA. Compressive modulus results followed a similar trend. G + H + P Cast had the highest average compressive modulus (50.73 ± 4.90 kPa), while G + H + P Print showed slightly lower but more variable values (28.17 ± 24.88 kPa). Both G + H Cast and G + H Print remained below 10 kPa (7.40 ± 0.42 kPa and 5.75 ± 1.25 kPa, respectively), suggesting insufficient mechanical reinforcement in the absence of PEGDA.

The updated mechanical data confirm that PEGDA significantly enhances the performance of GelMA-HAMA hydrogels. Both PEGDA-containing groups outperformed their non-PEGDA counterparts, particularly in terms of compressive strength and elastic response. Notably, G + H + P Print achieved the highest storage modulus, indicating that post-print PEGDA infiltration reinforces soft hydrogel networks without compromising elasticity. The larger variability observed in G + H + P Print may result from irregular sample geometry. Meanwhile, G + H Print exhibited the weakest properties, highlighting the limitations of printing soft gels without secondary crosslinking.

PEGDA infiltration significantly improves the mechanical integrity of GelMA-HAMA hydrogels, especially when applied post-printing. Among all groups, G + H + P Print offers the most favorable balance of printability, stiffness, and softness, making it the most suitable candidate for modeling the blood-brain barrier. These results support the use of PEGDA for tunable, structurally stable bioinks in soft tissue engineering applications.

Acknowledgements and/or References (Optional): : The authors would like to thank Joseph Dorsey and Amanda Mejia of Southwestern University for their prior work in adapting our current open-source bioprinter. The authors also acknowledge the developers of the Allstruder, Riley Patten and Dr. Thomas J. Hinton.