Abstract It is well‐known that tissue engineering scaffolds that feature highly interconnected and size‐adjustable micropores are oftentimes desired to promote cellular viability, motility, and functions. Unfortunately, the ability of precise control over the microporous structures within bioinks in a cytocompatible manner for applications in 3D bioprinting is generally lacking, until a method of micropore‐forming bioink based on gelatin methacryloyl (GelMA) was reported recently. This bioink took advantage of the unique aqueous two‐phase emulsion (ATPE) system, where poly(ethylene oxide) (PEO) droplets are utilized as the porogen. Considering the limitations associated with this very initial demonstration, this article has furthered the understanding of the micropore‐forming GelMA bioinks by conducting a systematic investigation into the additional GelMA types (porcine and fish, different methacryloyl‐modification degrees) and porogen types (PEO, poly(vinyl alcohol), and dextran), as well as the effects of the porogen concentrations and molecular weights on the properties of the GelMA‐based ATPE bioink system. This article exemplifies not only the significantly wider range of micropore sizes achievable and better emulsion stability, but also the improved suitability for both extrusion and digital light processing bioprinting with favorable cellular responses.
more »
« less
Continuous synthesis of elastomeric macroporous microbeads
Macroporous microbeads are synthesized by microfluidic production of silica-loaded polymeric microdroplets followed by porogen removal via selective etching. Microdroplets are produced in a flow-focusing microreactor to ensure monodispersity with uniform porogen loading. Effects of porogen size and polymer network density on the porosity and effective modulus of the microbeads are studied.
more »
« less
- Award ID(s):
- 1803428
- NSF-PAR ID:
- 10098951
- Date Published:
- Journal Name:
- Reaction Chemistry & Engineering
- Volume:
- 4
- Issue:
- 2
- ISSN:
- 2058-9883
- Page Range / eLocation ID:
- 254 to 260
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Despite national and international regulations, plastic microbeads are still widely used in personal care and consumer products (PCCPs) as exfoliants and rheological modifiers, causing significant microplastic pollution following use. As a sustainable alternative, microbeads were produced by extrusion of biomass solutions and precipitation into anti-solvent. Despite using novel blends of biodegradable, non-derivatized biomass including cellulose and Kraft lignin, resulting microbeads are within the shape, size, and stiffness range of commercial plastic microbeads, even without crosslinking. Solution processability and resulting bead shape and Young’s modulus can be tuned via biomass source, concentration, and degree of polymerization; biomass concentration, extrusion geometry, and precipitation and extraction conditions control the bead size. Lignin incorporation reduces the solution viscosity, which improves processability but also produces flatter beads with higher moduli than cellulose-only microbeads. While some lignin leaches from the beads when stored in water, adding surfactants like sodium dodecyl sulfate suppresses this effect, resulting in good mechanical stability over 2 months with no noticeable structural degradation. The stability of these mixed-source biomass microbeads—despite the absence of chemical crosslinking or derivatization—makes this route a promising, robust approach for obtaining environmentally-benign microbeads of tunable size and stiffness for use in PCCPs.more » « less
-
more » « less
Abstract Susceptibility of mammalian cells against harsh processing conditions limit their use in cell transplantation and tissue engineering applications. Besides modulation of the cell microenvironment, encapsulation of mammalian cells within hydrogel microbeads attract attention for cytoprotection through physical isolation of the encapsulated cells. The hydrogel formulations used for cell microencapsulation are largely dominated by ionically crosslinked alginate (Alg), which suffer from low structural stability under physiological culture conditions and poor cell–matrix interactions. Here the fabrication of Alg templated silk and silk/gelatin composite hydrogel microspheres with permanent or on‐demand cleavable enzymatic crosslinks using simple and cost‐effective centrifugation‐based droplet processing are demonstrated. The composite microbeads display structural stability under ion exchange conditions with improved mechanical properties compared to ionically crosslinked Alg microspheres. Human mesenchymal stem and neural progenitor cells are successfully encapsulated in the composite beads and protected against environmental factors, including exposure to polycations, extracellular acidosis, apoptotic cytokines, ultraviolet (UV) irradiation, anoikis, immune recognition, and particularly mechanical stress. The microbeads preserve viability, growth, and differentiation of encapsulated stem and progenitor cells after extrusion in viscous polyethylene oxide solution through a 27‐gauge fine needle, suggesting potential applications in injection‐based delivery and three‐dimensional bioprinting of mammalian cells with higher success rates.
-
more » « less
Abstract An intelligent sensing framework using Machine Learning (ML) and Deep Learning (DL) architectures to precisely quantify dielectrophoretic force invoked on microparticles in a textile electrode-based DEP sensing device is reported. The prediction accuracy and generalization ability of the framework was validated using experimental results. Images of pearl chain alignment at varying input voltages were used to build deep regression models using modified ML and CNN architectures that can correlate pearl chain alignment patterns of Saccharomyces cerevisiae(yeast) cells and polystyrene microbeads to DEP force. Various ML models such as K-Nearest Neighbor, Support Vector Machine, Random Forest, Neural Networks, and Linear Regression along with DL models such as Convolutional Neural Network (CNN) architectures of AlexNet, ResNet-50, MobileNetV2, and GoogLeNet have been analyzed in order to build an effective regression framework to estimate the force induced on yeast cells and microbeads. The efficiencies of the models were evaluated using Mean Absolute Error, Mean Absolute Relative, Mean Squared Error, R-squared, and Root Mean Square Error (RMSE) as evaluation metrics. ResNet-50 with RMSPROP gave the best performance, with a validation RMSE of 0.0918 on yeast cells while AlexNet with ADAM optimizer gave the best performance, with a validation RMSE of 0.1745 on microbeads. This provides a baseline for further studies in the application of deep learning in DEP aided Lab-on-Chip devices.
-
Cancer immunotherapy has shifted the paradigm for cancer treatment in the past decade, but new immunotherapies enabling the effective treatment of solid tumors are still greatly demanded. Here we report a pore-forming hydrogel-based immunotherapy that enables simultaneous recruitment of dendritic cells and in situ activation of T cells, for reshaping the immunosuppressive tumor microenvironment and amplifying cytotoxic T lymphocyte response. The injectable pore-forming hydrogel composed of porogen-dispersed alginate network can form a macroporous structure upon injection into mice, and enables controlled release of granulocyte-macrophage colony-stimulating factor (GM-CSF), a chemoattractant for recruiting dendritic cells, and epacadostat, an inhibitor of indoleamine 2, 3-dioxygenase for activating T cells. We show that gels loaded with GM-CSF and epacadostat, after peritumoral injection, can recruit massive dendritic cells in situ and activate effector T cells in the tumor tissues, resulting in enhanced frequency and activation status of dendritic cells, reduced numbers of regulatory T (Treg) cells, and increased CD8 + /Treg ratios in the tumor microenvironment. This hydrogel-based immunotherapy holds great promise for treating poorly-immunogenic solid tumors.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1039/C8RE00189H
