Back

Integrating Microchannels and Flows into 3D Printable Granular Hydrogel Matrices

Ferrarese, E.; Swanekamp, E.; Bui, T.-v.; Highley, C. B.

2025-06-08 bioengineering
10.1101/2025.06.08.658465 bioRxiv
Show abstract

Microfluidic systems incorporating or contained within hydrogels are important in creating microphysiological systems (MPSs). Often naturally derived hydrogels are used, as their inherent bioactivity supports dynamic cellular behaviors. Hydrogel biomaterials that are partly or fully synthetic are desirable in engineering systems with specific, designed properties, though they typically lack bioactive features of natural materials without additional molecular design. In particular, permissive biomaterials enable physiologically relevant dynamic cellular behaviors. Granular hydrogels offer inherent permissiveness, owning to porosity between particles and dynamic behaviors in the absence of interparticle crosslinking. However, applying these in MPS to model tissues requires stable channels to perfuse fluid in these dynamic systems. Here, we establish channels within granular hydrogels to enable perfusion through spatially controlled interparticle crosslinking. Selective crosslinking allowed for the formation of stable channels while allowing the microparticles of a granular hydrogel between two channels to remained uncrosslinked. This allowed spatiotemporal control of signals within an environment established from microparticles without interparticle crosslinking. Fluorescently tagged molecules allowed for the visualization of controlled soluble gradients between two channels within the device. Additionally, embedded 3D printing processes can be used to specify material composition within the system, demonstrating integrated technology for engineering well-defined hydrogel systems. Integrated microfluidic-based control over soluble signals in a system that is compatible with 3D printing processes will establish a basis for building MPSs for broad applications, and the ability to maintain granular systems in culture without interparticle crosslinking will enable design of synthetic hydrogels that access unique dynamic properties within these systems.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
Advanced Materials Technologies
27 papers in training set
Top 0.1%
13.9%
2
Lab on a Chip
88 papers in training set
Top 0.1%
11.9%
3
Biofabrication
32 papers in training set
Top 0.1%
11.9%
4
Advanced Healthcare Materials
71 papers in training set
Top 0.3%
6.6%
5
ACS Biomaterials Science & Engineering
37 papers in training set
Top 0.1%
6.6%
50% of probability mass above
6
Advanced Materials
53 papers in training set
Top 0.6%
4.2%
7
Advanced Functional Materials
41 papers in training set
Top 0.8%
3.5%
8
ACS Applied Materials & Interfaces
39 papers in training set
Top 0.2%
3.5%
9
Advanced Science
249 papers in training set
Top 7%
2.6%
10
Cellular and Molecular Bioengineering
21 papers in training set
Top 0.1%
1.8%
11
Biomaterials Science
21 papers in training set
Top 0.3%
1.7%
12
Biomacromolecules
25 papers in training set
Top 0.2%
1.6%
13
Materials Today Bio
18 papers in training set
Top 0.3%
1.6%
14
Bioengineering & Translational Medicine
21 papers in training set
Top 0.4%
1.6%
15
Analytical Chemistry
205 papers in training set
Top 2%
1.4%
16
Nature Communications
4913 papers in training set
Top 54%
1.4%
17
PLOS ONE
4510 papers in training set
Top 59%
1.3%
18
Scientific Reports
3102 papers in training set
Top 65%
1.3%
19
Small
70 papers in training set
Top 0.7%
1.3%
20
ACS Applied Bio Materials
21 papers in training set
Top 0.6%
1.2%
21
ACS Synthetic Biology
256 papers in training set
Top 2%
1.2%
22
Bioactive Materials
18 papers in training set
Top 0.6%
1.2%
23
ACS Nano
99 papers in training set
Top 3%
0.9%
24
Acta Biomaterialia
85 papers in training set
Top 0.8%
0.8%
25
Frontiers in Bioengineering and Biotechnology
88 papers in training set
Top 3%
0.7%
26
Journal of Biomedical Materials Research Part A
18 papers in training set
Top 0.4%
0.7%
27
ACS Sensors
45 papers in training set
Top 1%
0.7%
28
ACS Omega
90 papers in training set
Top 5%
0.6%
29
Advanced Materials Interfaces
10 papers in training set
Top 0.5%
0.6%
30
Langmuir
31 papers in training set
Top 0.7%
0.6%