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Nanoenabled Trainable Systems: From Biointerfaces to Biomimetics

[Image: see text] In the dynamic biological system, cells and tissues adapt to diverse environmental conditions and form memories, an essential aspect of training for survival and evolution. An understanding of the biological training principles will inform the design of biomimetic materials whose p...

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Detalles Bibliográficos
Autores principales: Li, Pengju, Kim, Saehyun, Tian, Bozhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9798864/
https://www.ncbi.nlm.nih.gov/pubmed/36516872
http://dx.doi.org/10.1021/acsnano.2c08042
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author Li, Pengju
Kim, Saehyun
Tian, Bozhi
author_facet Li, Pengju
Kim, Saehyun
Tian, Bozhi
author_sort Li, Pengju
collection PubMed
description [Image: see text] In the dynamic biological system, cells and tissues adapt to diverse environmental conditions and form memories, an essential aspect of training for survival and evolution. An understanding of the biological training principles will inform the design of biomimetic materials whose properties evolve with the environment and offer routes to programmable soft materials, neuromorphic computing, living materials, and biohybrid robotics. In this perspective, we examine the mechanisms by which cells are trained by environmental cues. We outline the artificial platforms that enable biological training and examine the relationship between biological training and biomimetic materials design. We place emphasis on nanoscale material platforms which, given their applicability to chemical, mechanical and electrical stimulation, are critical to bridging natural and synthetic systems.
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spelling pubmed-97988642022-12-30 Nanoenabled Trainable Systems: From Biointerfaces to Biomimetics Li, Pengju Kim, Saehyun Tian, Bozhi ACS Nano [Image: see text] In the dynamic biological system, cells and tissues adapt to diverse environmental conditions and form memories, an essential aspect of training for survival and evolution. An understanding of the biological training principles will inform the design of biomimetic materials whose properties evolve with the environment and offer routes to programmable soft materials, neuromorphic computing, living materials, and biohybrid robotics. In this perspective, we examine the mechanisms by which cells are trained by environmental cues. We outline the artificial platforms that enable biological training and examine the relationship between biological training and biomimetic materials design. We place emphasis on nanoscale material platforms which, given their applicability to chemical, mechanical and electrical stimulation, are critical to bridging natural and synthetic systems. American Chemical Society 2022-12-14 2022-12-27 /pmc/articles/PMC9798864/ /pubmed/36516872 http://dx.doi.org/10.1021/acsnano.2c08042 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Li, Pengju
Kim, Saehyun
Tian, Bozhi
Nanoenabled Trainable Systems: From Biointerfaces to Biomimetics
title Nanoenabled Trainable Systems: From Biointerfaces to Biomimetics
title_full Nanoenabled Trainable Systems: From Biointerfaces to Biomimetics
title_fullStr Nanoenabled Trainable Systems: From Biointerfaces to Biomimetics
title_full_unstemmed Nanoenabled Trainable Systems: From Biointerfaces to Biomimetics
title_short Nanoenabled Trainable Systems: From Biointerfaces to Biomimetics
title_sort nanoenabled trainable systems: from biointerfaces to biomimetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9798864/
https://www.ncbi.nlm.nih.gov/pubmed/36516872
http://dx.doi.org/10.1021/acsnano.2c08042
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AT kimsaehyun nanoenabledtrainablesystemsfrombiointerfacestobiomimetics
AT tianbozhi nanoenabledtrainablesystemsfrombiointerfacestobiomimetics