Browsing by Author "McAlpine Research Group"

Now showing 1 - 9 of 9
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    Supporting data for "3D Bioprinted In Vitro Metastatic Models via Reconstruction of Tumor Microenvironments"
    (2020-05-29) Meng, Fanben; Meyer, Carolyn M; Joung, Daeha; Vallera, Daniel A; McAlpine, Michael C; Panoskaltsis-Mortari, Angela; mcalpine@umn.edu; McAlpine, Michael C; McAlpine Research Group
    The data set includes the experimental data and the corresponding code files for " 3D Bioprinted In Vitro Metastatic Models via Reconstruction of Tumor Microenvironments", Fanben Meng, Carolyn M Meyer, Daeha Joung, Daniel A Vallera, Michael C McAlpine, Angela Panoskaltsis‐Mortari, Adv. Mater. 2019, 31 (10), 1806899. The development of 3D in vitro models capable of recapitulating native tumor microenvironments could improve the translatability of potential anticancer drugs and treatments. Here, 3D bioprinting techniques are used to build tumor constructs via precise placement of living cells, functional biomaterials, and programmable release capsules. This enables the spatiotemporal control of signaling molecular gradients, thereby dynamically modulating cellular behaviors at a local level. Vascularized tumor models are created to mimic key steps of cancer dissemination (invasion, intravasation, and angiogenesis), based on guided migration of tumor cells and endothelial cells in the context of stromal cells and growth factors. The utility of the metastatic models for drug screening is demonstrated by evaluating the anticancer efficacy of immunotoxins. These 3D vascularized tumor tissues provide a proof-of-concept platform to i) fundamentally explore the molecular mechanisms of tumor progression and metastasis, and ii) preclinically identify therapeutic agents and screen anticancer drugs.
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    Supporting data for "3D Printed Deformable Sensors"
    (2020-04-28) Zhu, Zhijie; Park, Hyun Soo; McAlpine, Michael C; mcalpine@umn.edu; McAlpine, Michael C; McAlpine Research Group
    The data set includes the experimental data and the corresponding code files supporting the results reported in Zhijie Zhu; Hyun Soo Park; Michael C. McAlpine. 3D Printed Deformable Sensors. Sci. Adv., 2020, DOI: 10.1126/sciadv.aba5575. The ability to directly print compliant biomedical devices on live human organs could benefit patient monitoring and wound treatment, which requires the 3D printer to adapt to the various deformations of the biological surface. We developed an in situ 3D printing system that estimates the motion and deformation of the target surface to adapt the toolpath in real time. With this printing system, a hydrogel-based sensor was printed on a porcine lung under respiration-induced deformation. The sensor was compliant to the tissue surface and provided continuous spatial mapping of deformation via electrical impedance tomography. This adaptive 3D printing approach may enhance robot-assisted medical treatments with additive manufacturing capabilities, enabling autonomous and direct printing of wearable electronics and biological materials on and inside the human body.
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    Supporting data for "3D printed electrically-driven soft actuators"
    (2020-06-09) Haghiashtiani, Ghazaleh; Habtour, Ed; Park, Sung-Hyun; Gardea, Frank; McAlpine, Michael C; mcalpine@umn.edu; McAlpine, Michael C; McAlpine Research Group
    Soft robotics is an emerging field enabled by advances in the development of soft materials with properties commensurate to their biological counterparts, for the purpose of reproducing locomotion and other distinctive capabilities of active biological organisms. The development of soft actuators is fundamental to the advancement of soft robots and bio-inspired machines. Among the different material systems incorporated in the fabrication of soft devices, ionic hydrogel–elastomer hybrids have recently attracted vast attention due to their favorable characteristics, including their analogy with human skin. Here, we demonstrate that this hybrid material system can be 3D printed as a soft dielectric elastomer actuator (DEA) with a unimorph configuration that is capable of generating high bending motion in response to an applied electrical stimulus. We characterized the device actuation performance via applied (i) ramp-up electrical input, (ii) cyclic electrical loading, and (iii) payload masses. A maximum vertical tip displacement of 9.78 ± 2.52 mm at 5.44 kV was achieved from the tested 3D printed DEAs. Furthermore, the nonlinear actuation behavior of the unimorph DEA was successfully modeled using an analytical energetic formulation and a finite element method (FEM).
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    Supporting data for "3D Printed Functional and Biological Materials on Moving Freeform Surfaces"
    (2020-05-13) Zhu, Zhijie; Guo, Shuang-Zhuang; Hirdler, Tessa; Eide, Cindy; Fan, Xiaoxiao; Tolar, Jakub; McAlpine, Michael C; mcalpine@umn.edu; McAlpine, Michael C; McAlpine Research Group; Tolar Laboratory
    The data set includes the experimental data supporting the results reported in Zhu, Zhijie, Shuang‐Zhuang Guo, Tessa Hirdler, Cindy Eide, Xiaoxiao Fan, Jakub Tolar, and Michael C. McAlpine. "3D printed functional and biological materials on moving freeform surfaces." Advanced Materials, 30(23), 1707495. Conventional 3D printing technologies typically rely on open‐loop, calibrate‐then‐print operation procedures. An alternative approach is adaptive 3D printing, which is a closed‐loop method that combines real‐time feedback control and direct ink writing of functional materials in order to fabricate devices on moving freeform surfaces. Here, it is demonstrated that the changes of states in the 3D printing workspace in terms of the geometries and motions of target surfaces can be perceived by an integrated robotic system aided by computer vision. A hybrid fabrication procedure combining 3D printing of electrical connects with automatic pick‐and‐placing of surface‐mounted electronic components yields functional electronic devices on a free‐moving human hand. Using this same approach, cell‐laden hydrogels are also printed on live mice, creating a model for future studies of wound‐healing diseases. This adaptive 3D printing method may lead to new forms of smart manufacturing technologies for directly printed wearable devices on the body and for advanced medical treatments.
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    Supporting data for "3D Printed Organ Models with Physical Properties of Tissue and Integrated Sensors"
    (2020-05-22) Qiu, Kaiyan; Zhao, Zichen; Haghiashtiani, Ghazaleh; Guo, Shuang-Zhuang; He, Mingyu; Su, Ruitao; Zhu, Zhijie; Bhuiyan, Didarul B; Murugan, Paari; Meng, Fanben; Park, Sung Hyun; Chu, Chih-Chang; Ogle, Brenda M; Saltzman, Daniel A; Konety, Badrinath R; Sweet, Robert M; McAlpine, Michael C; mcalpine@umn.edu; McAlpine, Michael C; McAlpine Research Group
    The data set includes the experimental data and the corresponding MRI stereolithography (STL) file supporting the results reported in Kaiyan Qiu; Zichen Zhao; Ghazaleh Haghiashtiani; Shuang-Zhuang Guo; Mingyu He; Ruitao Su; Zhijie Zhu; Didarul B. Bhuiyan; Paari Murugan; Fanben Meng; Sung Hyun Park; Chih-Chang Chu; Brenda M. Ogle; Daniel A. Saltzman; Badrinath R. Konety; Robert M. Sweet; Michael C. McAlpine. 3D Printed Organ Models with Physical Properties of Tissue and Integrated Sensors. Adv. Mater. Technol. 2018, 3, 1700235. The design and development of novel methodologies and customized materials to fabricate patient-specific 3D printed organ models with integrated sensing capabilities could yield advances in smart surgical aids for preoperative planning and rehearsal. Here, we demonstrate 3D printed prostate models with physical properties of tissue and integrated soft electronic sensors using custom-formulated polymeric inks. The models show high quantitative fidelity in static and dynamic mechanical properties, optical characteristics, and anatomical geometries to patient tissues and organs. The models offer tissue-like tactile sensation and behavior and thus can be used for the prediction of organ physical behavior under deformation. The prediction results show good agreement with values obtained from simulations. The models also allow the application of surgical and diagnostic tools to their surface and inner channels. Finally, via the conformal integration of 3D printed soft electronic sensors, pressure applied to the models with surgical tools can be quantitatively measured.
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    Supporting data for "3D printed patient-specific aortic root models with internal sensors for minimally invasive applications"
    (2020-06-09) Haghiashtiani, Ghazaleh; Qiu, Kaiyan; Sanchez, Jorge D Zhingre; Fuenning, Zachary J; Nair, Priya; Ahlberg, Sarah E; Iaizzo, Paul A; McAlpine, Michael C; mcalpine@umn.edu; McAlpine, Michael C; McAlpine Research Group
    Minimally invasive surgeries have numerous advantages, yet complications may arise from limited knowledge about the anatomical site targeted for the delivery of therapy. Transcatheter aortic valve replacement (TAVR) is a minimally invasive procedure for treating aortic stenosis. Here, we demonstrate multi-material 3D printing of patient-specific soft aortic root models with internally-integrated electronic sensor arrays that can augment testing for TAVR preprocedural planning. We evaluated the efficacies of the models by comparing their geometric fidelities with postoperative data from patients, as well as their in vitro hemodynamic performances in cases with and without leaflet calcifications. Furthermore, we uniquely demonstrated that internal sensor arrays can facilitate the optimization of bioprosthetic valve selections and in vitro placements via mapping of the pressures applied on the critical regions of the aortic anatomies. Such models may pave new avenues for mitigating the risks of postoperative complications, as well as facilitating the development of next-generation medical devices.
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    Supporting data for "3D Printed Polymer Photodetectors"
    (2020-05-29) Park, Sung Hyun; Su, Ruitao; Guo, Shuang-Zhuang; Qiu, Kaiyan; Joung, Daeha; Fanben, Meng; McAlpine, Michael C; Jeong, Jaewoo; mcalpine@umn.edu; McAlpine, Michael C; McAlpine Research Group
    Extrusion-based 3D printing, an emerging technology, has been previously used in the comprehensive fabrication of light-emitting diodes using various functional inks, without cleanrooms or conventional microfabrication techniques. Here, polymer-based photodetectors exhibiting high performance are fully 3D printed and thoroughly characterized. A semiconducting polymer ink is printed and optimized for the active layer of the photodetector, achieving an external quantum efficiency of 25.3%, which is comparable to that of microfabricated counterparts and yet created solely via a one-pot custom built 3D-printing tool housed under ambient conditions. The devices are integrated into image sensing arrays with high sensitivity and wide field of view, by 3D printing interconnected photodetectors directly on flexible substrates and hemispherical surfaces. This approach is further extended to create integrated multifunctional devices consisting of optically coupled photodetectors and light-emitting diodes, demonstrating for the first time the multifunctional integration of multiple semiconducting device types which are fully 3D printed on a single platform. The 3D-printed optoelectronic devices are made without conventional microfabrication facilities, allowing for flexibility in the design and manufacturing of next-generation wearable and 3D-structured optoelectronics, and validating the potential of 3D printing to achieve high-performance integrated active electronic materials and devices.
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    Supporting data for "3D Printed Silicon Nanocrystal Light Emitting Diodes"
    (2020-05-20) Su, Ruitao; Park, Sung Hyun; Li, Zhaohan; McAlpine, Michael C; mcalpine@umn.edu; McAlpine, Michael C; McAlpine Research Group
    The application of 3-D printing to the fabrication of light emitting diode (LED) requires the ability to integrate materials with distinct properties into one functional device by tuning the printability of materials and precisely confining the cured patterns within the predesigned 3-D structure. To meet this goal, material properties, e.g., viscosity, surface tension and degree of crosslinking are optimized to improve the compatibility with the 3-D printing technique. Particularly, silicon nano crystal (SiNC), the nontoxic active material for the printed LED, is investigated in terms of controllable dispensing of the solution-based material as well as surface roughness and uniformity of the printed layer. With the successful red-IR light emission from the printed SiNC-LED, 3-D printing displays the potential to fabricate optoelectronic devices that are flexible, biocompatible and conforming to the surface shape of the target object in a freeform manner.
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    Supporting data for 3D Printed Stem-Cell Derived Neural Progenitors Generate Spinal Cord Scaffolds
    (2020-05-15) Joung, Daeha; Truong, Vincent; Neitzke, Colin C; Guo, Shuang-Zhuang; Walsh, Patrick J; Monat, Joseph R; Meng, Fanben; Park, Sung Hyun; Dutton, James R; Parr, Ann M; McAlpine, Michael C; mcalpine@umn.edu; McAlpine, Michael C; McAlpine Research Group
    A bioengineered spinal cord is fabricated via extrusion-based multilateral 3D bioprinting, in which clusters of induced pluripotent stem cell (iPSC)-derived spinal neuronal progenitor cells (sNPCs) and oligodendrocyte progenitor cells (OPCs) are placed in precise positions within 3D printed biocompatible scaffolds during assembly. The location of a cluster of cells, of a single type or multiple types, is controlled using a point-dispensing printing method with a 200 μm center-to-center spacing within 150 μm wide channels. The bioprinted sNPCs differentiate and extend axons throughout microscale scaffold channels, and the activity of these neuronal networks is confirmed by physiological spontaneous calcium flux studies. Successful bioprinting of OPCs in combination with sNPCs demonstrates a multicellular neural tissue engineering approach, where the ability to direct the patterning and combination of transplanted neuronal and glial cells can be beneficial in rebuilding functional axonal connections across areas of central nervous system (CNS) tissue damage. This platform can be used to prepare novel biomimetic, hydrogel-based scaffolds modeling complex CNS tissue architecture in vitro and harnessed to develop new clinical approaches to treat neurological diseases, including spinal cord injury.