3D Printed Organisms Enabled by Aspiration-Assisted Adaptive Strategies

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2019 – 09 – 01
2023 – 08 – 01

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2023 – 08 – 01

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3D Printed Organisms Enabled by Aspiration-Assisted Adaptive Strategies

Published Date

2024-06-17

Author Contact

Han, Guebum
hanguebum@gmail.com

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Abstract

Devising an approach to deterministically position organisms could impact various fields such as bioimaging, cybernetics, cryopreservation, and organism-integrated devices. This requires continuously assessing the locations of randomly distributed organisms to collect and transfer them to target spaces without harm. Here we developed an aspiration-assisted adaptive printing system that tracks, harvests, and relocates living and moving organisms on target spaces via a pick-and-place mechanism that continuously adapts to updated visual and spatial information about the organisms and target spaces. These adaptive printing strategies successfully positioned a single static organism, multiple organisms in droplets, and a single moving organism on target spaces. Their capabilities were exemplified by printing vitrification-ready organisms in cryoprotectant droplets, sorting live organisms from dead ones, positioning organisms on curved surfaces, organizing organism-powered displays, and integrating organisms with materials and devices in customizable shapes. These printing strategies could ultimately lead to autonomous biomanufacturing methods to evaluate and assemble organisms for a variety of single and multi-organism-based applications.

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This data set includes the supporting data for the article, 3D Printed Organisms Enabled by Aspiration-Assisted Adaptive Strategies. Images may be viewed with Origin Viewer (https://www.originlab.com/viewer), an open software for viewing the OPJU files.

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https://doi.org/10.1002/advs.202404617

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This work was supported by grants from the National Science Foundation (Award No. EEC-1941543 and Award No. IIP-1913772), the National Institutes of Health (Award No. 9R44MH122118-02), and Regenerative Medicine Minnesota (Award No. ML2017, Ch 89, Art 1, sec 4, REGEN MED, FY19). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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Han, Guebum; Khosla, Kanav; Smith, Kieran T; Ng, Daniel Wai Hou; Lee, JiYong; Ouyang, Xia; Bischof, John C; McAlpine, Michael C. (2024). 3D Printed Organisms Enabled by Aspiration-Assisted Adaptive Strategies. Retrieved from the Data Repository for the University of Minnesota (DRUM), https://hdl.handle.net/11299/263942.
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