In silico simulations of diffusion tensors and tortuosity in cells grown on 3D-printed scaffolds for tissue engineering
In silico simulations of diffusion tensors and tortuosity in cells grown on 3D-printed scaffolds for tissue engineering
Tissue engineering is set to revolutionise regenerative medicine, drug discovery, and cancer biology. For this to succeed, improved 3D imaging methods that penetrate non-invasively into the developing tissue is fundamental to guide the design of new and improved 3D supports. In particular, it is very important to characterise the time- and space-heterogeneous pore network that continuously changes as the tissue grows, since delivery of nutrients and removal of waste is key to avoid the development of necrotic tissues. In this paper, we combine high-resolution microfocus Computed Tomography (μCT) imaging and in silico simulations to calculate the diffusion tensor of molecules diffusing in the actual pore structure of a tissue grown on 3D-printed plastic scaffolds. We use such tensors to derive information about the changing pore network and derive tortuosity, a key parameter to understand how pore interconnection changes with cell proliferation. Such information can be used to improve the design of 3D-printed supports as well as to validate and improve cell culture protocols.
32398-32410
Cartlidge, Topaz A.A.
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Wu, Yan
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Robertson, Thomas B.R.
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Katsamenis, Orestis L.
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Pileio, Giuseppe
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Cartlidge, Topaz A.A.
f7afbdd8-5906-46d3-bd5f-454b706e8247
Wu, Yan
17512290-4dbb-44a9-a7a7-b562227d0c06
Robertson, Thomas B.R.
957b392c-1212-4721-bd6d-d1e00ed50a09
Katsamenis, Orestis L.
8553e7c3-d860-4b7a-a883-abf6c0c4b438
Pileio, Giuseppe
13f78e66-0707-4438-b9c9-6dbd3eb7d4e8
Cartlidge, Topaz A.A., Wu, Yan, Robertson, Thomas B.R., Katsamenis, Orestis L. and Pileio, Giuseppe
(2024)
In silico simulations of diffusion tensors and tortuosity in cells grown on 3D-printed scaffolds for tissue engineering.
RSC Advances, 14 (44), .
(doi:10.1039/d4ra05362a).
Abstract
Tissue engineering is set to revolutionise regenerative medicine, drug discovery, and cancer biology. For this to succeed, improved 3D imaging methods that penetrate non-invasively into the developing tissue is fundamental to guide the design of new and improved 3D supports. In particular, it is very important to characterise the time- and space-heterogeneous pore network that continuously changes as the tissue grows, since delivery of nutrients and removal of waste is key to avoid the development of necrotic tissues. In this paper, we combine high-resolution microfocus Computed Tomography (μCT) imaging and in silico simulations to calculate the diffusion tensor of molecules diffusing in the actual pore structure of a tissue grown on 3D-printed plastic scaffolds. We use such tensors to derive information about the changing pore network and derive tortuosity, a key parameter to understand how pore interconnection changes with cell proliferation. Such information can be used to improve the design of 3D-printed supports as well as to validate and improve cell culture protocols.
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d4ra05362a
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Accepted/In Press date: 27 September 2024
e-pub ahead of print date: 14 October 2024
Identifiers
Local EPrints ID: 495650
URI: http://eprints.soton.ac.uk/id/eprint/495650
ISSN: 2046-2069
PURE UUID: 1fe53971-a27f-4e8d-ac66-b30696c12578
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Date deposited: 20 Nov 2024 17:34
Last modified: 21 Nov 2024 02:59
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Author:
Topaz A.A. Cartlidge
Author:
Yan Wu
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