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Diving beetle-like miniaturized plungers with reversible, rapid biofluid capturing for machine learning-based care of skin disease

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dc.contributor.authorSangyul Baik-
dc.contributor.authorJihyun Lee-
dc.contributor.authorEun Je Jeon-
dc.contributor.authorBo-yong Park-
dc.contributor.authorDa Wan Kim-
dc.contributor.authorJin Ho Song-
dc.contributor.authorHeon Joon Lee-
dc.contributor.authorSeung Yeop Han-
dc.contributor.authorSeung-Woo Cho-
dc.contributor.authorChanghyun Pang-
dc.date.accessioned2022-01-10T02:30:19Z-
dc.date.available2022-01-10T02:30:19Z-
dc.date.created2021-07-07-
dc.date.issued2021-06-
dc.identifier.issn2375-2548-
dc.identifier.urihttps://pr.ibs.re.kr/handle/8788114/11057-
dc.description.abstractCopyright © 2021 The Authors, some rights reserved.Recent advances in bioinspired nano/microstructures have received attention as promising approaches with which to implement smart skin-interfacial devices for personalized health care. In situ skin diagnosis requires adaptable skin adherence and rapid capture of clinical biofluids. Here, we report a simple, all-in-one device consisting of microplungers and hydrogels that can rapidly capture biofluids and conformally attach to skin for stable, real-time monitoring of health. Inspired by the male diving beetle, the microplungers achieve repeatable, enhanced, and multidirectional adhesion to human skin in dry/wet environments, revealing the role of the cavities in these architectures. The hydrogels within the microplungers instantaneously absorb liquids from the epidermis for enhanced adhesiveness and reversibly change color for visual indication of skin pH levels. To realize advanced biomedical technologies for the diagnosis and treatment of skin, our suction-mediated device is integrated with a machine learning framework for accurate and automated colorimetric analysis of pH levels.-
dc.language영어-
dc.publisherAmerican Association for the Advancement of Science-
dc.titleDiving beetle-like miniaturized plungers with reversible, rapid biofluid capturing for machine learning-based care of skin disease-
dc.typeArticle-
dc.type.rimsART-
dc.identifier.wosid000664958400013-
dc.identifier.scopusid2-s2.0-85108027051-
dc.identifier.rimsid75949-
dc.contributor.affiliatedAuthorSeung-Woo Cho-
dc.identifier.doi10.1126/sciadv.abf5695-
dc.identifier.bibliographicCitationSCIENCE ADVANCES, v.7, no.25-
dc.relation.isPartOfSCIENCE ADVANCES-
dc.citation.titleSCIENCE ADVANCES-
dc.citation.volume7-
dc.citation.number25-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaScience & Technology - Other Topics-
dc.relation.journalWebOfScienceCategoryMultidisciplinary Sciences-
dc.subject.keywordPlusADHESION-
dc.subject.keywordPlusPH-
dc.subject.keywordPlusSENSORS-
dc.subject.keywordPlusPATCH-
dc.subject.keywordPlusACNE-
Appears in Collections:
Center for Nanomedicine (나노의학 연구단) > 1. Journal Papers (저널논문)
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