Poster P6 - Precise Cell Stratification in 3D Construct Using Advanced Chaotic Coaxial Bioprinting

Introduction: Currently, continuously chaotic bioprinting, as emerging extrusion-based bioprinting, effectively employs internal static mixers to attain accurate control of cell distribution within hydrogel filaments. However, achieving such precise cell distribution within stable three-dimensional (3D)-printed constructs remains a challenge in existing bioprinting strategies. To address this challenge, this study aims to explore a direct ink-writing 3D bioprinting strategy and elucidate its fundamental cellular material mechanism to establish an advanced bioprinting technique that can highly control cell distribution. By integrating a custom-designed 3D printing platform and a chaotic coaxial system, stable 3D printing constructs with precise cell-stratified distribution were achieved, which is crucial for enhancing the efficiency and success rate of tissue engineering repair.

Materials and

Methods: : To realize precise stratified cell distribution within 3D constructs, a custom-designed 3D bioprinting system was created, consisting of a static mixing device with a coaxial nozzle, a 3D printer, and two syringe pumps that supply bioinks. The specific steps were as follows: a mixture solution comprising 2% sodium alginate and 5% gelatin methacrylate (GelMA) was chosen as the bioink. The two strands of bioinks were connected to a static mixer, with one component containing 0.5% graphene nanoplatelets to distinguish different regions. Subsequently, the lower end of the static mixer (containing 1, 2, 3, and 13 element(s)) was connected to the inner needle of the coaxial nozzle, while the outer needle was connected to the crosslinking agent (10% calcium chloride solution/10% calcium chloride solution containing 2% GelMA). Both the bioink and the crosslinking agent were controlled by syringe pumps, with bioink flow rates set at 8 mL/h and crosslinking agent flow rates at 1, 4, and 8 mL/h, respectively. Printing speeds were set at 4, 6, and 8 mm/s, with a printing height maintained at 5 mm. After printing, all 3D printed structures were exposed to ultraviolet light (UV) to achieve complete stabilization. Finally, all printed 3D structures were sliced, and their cross-sectional and overall structures were evaluated through image analysis. Utilizing the optimized experimental parameters, bioinks containing L929 fibroblast cells labeled with two different CellTracker(green and red) were printed into 3D constructs, with a cell density of 2.5×106 cells/mL, and cell distribution was observed using a confocal microscope.

Results, Conclusions, and Discussions: As illustrated in Figure 1(A), the custom-design 3D bioprinting system was developed. To achieve stable 3D-printed constructs characterized by precisely stratified micropatterns, several key printing parameters were optimized, including printing speed of 6 mm/s, crosslinking agent composition consisting of a 10% calcium chloride and 2% GelMA, the crosslinking agent flow rate of 4 mL/h, and filling density of 10%. Figure 1(B) shows the impact of varying numbers (1, 2, 3, 13) of static mixing units on the micro-layered distribution within hydrogel filaments, accompanied by a statistical analysis of the area of each stripe on the cross-sectional profile of the printed structures. Additionally, the adoption of a two-step crosslinking methodology facilitated the manufacturing process of 3D structures, coupled with stability assessments conducted on the resultant constructs (Figure 1(C)). Subsequent validation of the system's efficacy in precisely controlling cellular stratification within the three-dimensional structures was achieved through the printing of 3D constructs incorporating L929 fibroblast cells labeled with two different CellTracker markers (Figure 1(D)).
In this study, a series of 3D bioprinted constructs with micro-layered architectures were successfully fabricated by tuning critical parameters including flow rate, composition of the crosslinking agent, and printing speed. This optimization process was facilitated by the combined operation of the chaotic coaxial system and a 3D printer. Cell-based experiments validated the system's capability to achieve stratified cell deposition, resulting in stable 3D constructs. These results offer novel insights and approaches for continuously chaotic bioprinting, with promising implications for tissue engineering advancements.

Acknowledgements (Optional): The authors would like to thank NIH grant # R01HL171317 and NSF EBMS program grant #2110842 for financial support.