3D printing and characterization of a soft and biostable elastomer with high flexibility and strength for biomedical applications.

Recent advancements in 3D printing have revolutionized biomedical engineering by enabling the manufacture of complex and functional devices in a low-cost, customizable, and small-batch fabrication manner. Soft elastomers are particularly important for biomedical applications because they can provide similar mechanical properties as tissues with improved biocompatibility. However, there are very few biocompatible elastomers with 3D printability, and little is known about the material properties of biocompatible 3D printable elastomers. Here, we report a new framework to 3D print a soft, biocompatible, and biostable polycarbonate-based urethane silicone (PCU-Sil) with minimal defects. We systematically characterize the rheological and thermal properties of the material to guide the 3D printing process and have determined a range of processing conditions. Optimal printing parameters such as printing speed, temperature, and layer height are determined via parametric studies aimed at minimizing porosity while maximizing the geometric accuracy of the 3D-printed samples as evaluated via micro-CT. We also characterize the mechanical properties of the 3D-printed structures under quasistatic and cyclic loading, degradation behavior and biocompatibility. The 3D-printed materials show a Young's modulus of 6.9 ± 0.85 MPa and a failure strain of 457 ± 37.7% while exhibiting good cell viability. Finally, compliant and free-standing structures including a patient-specific heart model and a bifurcating arterial structure are printed to demonstrate the versatility of the 3D-printed material. We anticipate that the 3D printing framework presented in this work will open up new possibilities not only for PCU-Sil, but also for other soft, biocompatible and thermoplastic polymers in various biomedical applications requiring high flexibility and strength combined with biocompatibility, such as vascular implants, heart valves, and catheters.

Variability of Action Potentials Within and Among Cardiac Cell Clusters Derived from Human Embryonic Stem Cells.

Electrophysiological variability in cardiomyocytes derived from pluripotent stem cells continues to be an impediment for their scientific and translational applications. We studied the variability of action potentials (APs) recorded from clusters of human embryonic stem cell-derived cardiomyocytes (hESC-CMs) using high-resolution optical mapping. Over 23,000 APs were analyzed through four parameters: APD30, APD80, triangulation and fractional repolarization. Although measures were taken to reduce variability due to cell culture conditions and rate-dependency of APs, we still observed significant variability in APs among and within the clusters. However, similar APs were found in spatial locations with close proximity, and in some clusters formed distinct regions having different AP characteristics that were reflected as separate peaks in the AP parameter distributions, suggesting multiple electrophysiological phenotypes. Using a recently developed automated method to group cells based on their entire AP shape, we identified distinct regions of different phenotypes within single clusters and common phenotypes across different clusters when separating APs into 2 or 3 subpopulations. The systematic analysis of the heterogeneity and potential phenotypes of large populations of hESC-CMs can be used to evaluate strategies to improve the quality of pluripotent stem cell-derived cardiomyocytes for use in diagnostic and therapeutic applications and in drug screening.

Automated grouping of action potentials of human embryonic stem cell-derived cardiomyocytes.

Methods for obtaining cardiomyocytes from human embryonic stem cells (hESCs) are improving at a significant rate. However, the characterization of these cardiomyocytes (CMs) is evolving at a relatively slower rate. In particular, there is still uncertainty in classifying the phenotype (ventricular-like, atrial-like, nodal-like, etc.) of an hESC-derived cardiomyocyte (hESC-CM). While previous studies identified the phenotype of a CM based on electrophysiological features of its action potential, the criteria for classification were typically subjective and differed across studies. In this paper, we use techniques from signal processing and machine learning to develop an automated approach to discriminate the electrophysiological differences between hESC-CMs. Specifically, we propose a spectral grouping-based algorithm to separate a population of CMs into distinct groups based on the similarity of their action potential shapes. We applied this method to a dataset of optical maps of cardiac cell clusters dissected from human embryoid bodies. While some of the nine cell clusters in the dataset are presented with just one phenotype, the majority of the cell clusters are presented with multiple phenotypes. The proposed algorithm is generally applicable to other action potential datasets and could prove useful in investigating the purification of specific types of CMs from an electrophysiological perspective.

A universal system for highly efficient cardiac differentiation of human induced pluripotent stem cells that eliminates interline variability.

BACKGROUND: The production of cardiomyocytes from human induced pluripotent stem cells (hiPSC) holds great promise for patient-specific cardiotoxicity drug testing, disease modeling, and cardiac regeneration. However, existing protocols for the differentiation of hiPSC to the cardiac lineage are inefficient and highly variable. We describe a highly efficient system for differentiation of human embryonic stem cells (hESC) and hiPSC to the cardiac lineage. This system eliminated the variability in cardiac differentiation capacity of a variety of human pluripotent stem cells (hPSC), including hiPSC generated from CD34(+) cord blood using non-viral, non-integrating methods. METHODOLOGY/PRINCIPAL FINDINGS: We systematically and rigorously optimized >45 experimental variables to develop a universal cardiac differentiation system that produced contracting human embryoid bodies (hEB) with an improved efficiency of 94.7±2.4% in an accelerated nine days from four hESC and seven hiPSC lines tested, including hiPSC derived from neonatal CD34(+) cord blood and adult fibroblasts using non-integrating episomal plasmids. This cost-effective differentiation method employed forced aggregation hEB formation in a chemically defined medium, along with staged exposure to physiological (5%) oxygen, and optimized concentrations of mesodermal morphogens BMP4 and FGF2, polyvinyl alcohol, serum, and insulin. The contracting hEB derived using these methods were composed of high percentages (64-89%) of cardiac troponin I(+) cells that displayed ultrastructural properties of functional cardiomyocytes and uniform electrophysiological profiles responsive to cardioactive drugs. CONCLUSION/SIGNIFICANCE: This efficient and cost-effective universal system for cardiac differentiation of hiPSC allows a potentially unlimited production of functional cardiomyocytes suitable for application to hPSC-based drug development, cardiac disease modeling, and the future generation of clinically-safe nonviral human cardiac cells for regenerative medicine.