A fused deposition modeling method was used in this research to investigate the possibility of improving the mechanical properties of poly(lactic acid) by changing the thermal conditions of the printing process. Sample models were prepared while varying a wide range of printing parameters, including bed temperature, melt temperature, and raster angle. Certain samples were also thermally treated by annealing. The prepared materials were subjected to a detailed thermomechanical analysis (differential scanning calorimetry, dynamic mechanical analysis, heat deflection temperature (HDT)), which allowed the formulation of several conclusions. For all prepared samples, the key changes in mechanical properties are related to the content of the poly(lactic acid) crystalline phase, which led to superior properties in annealed samples. The results also indicate the highly beneficial effect of increased bed temperature, where the best results were obtained for the samples printed at 105 °C. Compared to the reference samples printed at a bed temperature of 60 °C, these samples showed the impact strength increased by 80% (from 35 to 63 J/m), HDT increased by 20 °C (from 55 to 75 °C), and also a significant increase in strength and modulus. Scanning electron microscopy observations confirmed the increased level of diffusion between the individual layers of the printed filament.
The most prevalent form of bioprinting—extrusion bioprinting—can generate structures from a diverse range of materials and viscosities. It can create personalized tissues that aid in drug testing and cancer research when used in combination with natural bioinks. This paper reviews natural bioinks and their properties and functions in hard and soft tissue engineering applications. It discusses agarose, alginate, cellulose, chitosan, collagen, decellularized extracellular matrix, dextran, fibrin, gelatin, gellan gum, hyaluronic acid, Matrigel, and silk. Multi-component bioinks are considered as a way to address the shortfalls of individual biomaterials. The mechanical, rheological, and cross-linking properties along with the cytocompatibility, cell viability, and printability of the bioinks are detailed as well. Future avenues for research into natural bioinks are then presented.
The ability of stem cells to differentiate into specialized cells make them a valuable tool for therapeutic applications. 3D bioprinting, a subset of additive manufacturing, uses bioinks composed of cells and biomaterials to create living tissues. The use of bioactive factors like small molecules and proteins can promote stem cell differentiation into the desired cell phenotypes for tissue regeneration. Small molecules can accelerate the process of regeneration in tissue engineering, maintain bioactivity in a biological environment, and minimize the costs associated with this process. Additionally, they can be encapsulated in specialized drug-delivery devices called microspheres for controlled release. Microspheres are small (1-1000 μm) spherical particles usually made from biodegradable and biocompatible polymers that can be loaded with drugs and other bioactive components. They can then be integrated into stem-cell-laden bioinks used to form bioprinted tissues, where they will release the encapsulated drug and promote differentiation of stem cells into the desired mature cell type. Microspheres can be widely used to encapsulate a broad range of therapeutic agents, including hydrophilic and hydrophobic small molecule drugs, DNA, and proteins. The release of encapsulated molecules occurs through degradation and erosion of the polymer matrix. This article provides detailed protocols for fabricating and sterilizing drug-releasing microspheres made from poly-ε-caprolactone, a promising biodegradable polymer often used for controlled drug delivery due to its biocompatibility and biodegradation kinetics. Additional protocols describe characterization of the loading and size of microspheres as well as incorporation of microspheres into a fibrinbased bioink for 3D bioprinting.
Background Alzheimer’s disease (AD), a progressive neurodegenerative disorder, is becoming increasingly prevalent as our population ages. It is characterized by the buildup of amyloid beta plaques and neurofibrillary tangles containing hyperphosphorylated-tau. The current treatments for AD do not prevent the long-term progression of the disease and pre-clinical models often do not accurately represent its complexity. Bioprinting combines cells and biomaterials to create 3D structures that replicate the native tissue environment and can be used as a tool in disease modeling or drug screening. Methods This work differentiated both healthy and diseased patient–derived human induced pluripotent stems cells (hiPSCs) into neural progenitor cells (NPCs) that were bioprinted using the Aspect RX1 microfluidic printer into dome-shaped constructs. The combination of cells, bioink, and puromorphamine (puro)-releasing microspheres were used to mimic the in vivo environment and direct the differentiation of the NPCs into basal forebrain-resembling cholinergic neurons (BFCN). These tissue models were then characterized for cell viability, immunocytochemistry, and electrophysiology to evaluate their functionality and physiology for use as disease-specific neural models. Results Tissue models were successfully bioprinted and the cells were viable for analysis after 30- and 45-day cultures. The neuronal and cholinergic markers β-tubulin III (Tuj1), forkhead box G1 (FOXG1), and choline acetyltransferase (ChAT) were identified as well as the AD markers amyloid beta and tau. Further, immature electrical activity was observed when the cells were excited with potassium chloride and acetylcholine. Conclusions This work shows the successful development of bioprinted tissue models incorporating patient derived hiPSCs. Such models can potentially be used as a tool to screen promising drug candidates for treating AD. Further, this model could be used to increase the understanding of AD progression. The use of patient derived cells also shows the potential of this model for use in personalized medicine applications.
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