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STORM imaging of mitochondrial dynamics using a vicinal-dithiol-proteins-targeted probe

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dc.contributor.authorChen, Bingling-
dc.contributor.authorGong, Wanjun-
dc.contributor.authorYang, Zhigang-
dc.contributor.authorPan, Wenhui-
dc.contributor.authorVerwilst, Peter-
dc.contributor.authorShin, Jinwoo-
dc.contributor.authorYan, Wei-
dc.contributor.authorLiu, Liwei-
dc.contributor.authorQu, Junle-
dc.contributor.authorKim, Jong Seung-
dc.date.accessioned2021-08-30T22:16:01Z-
dc.date.available2021-08-30T22:16:01Z-
dc.date.created2021-06-18-
dc.date.issued2020-06-
dc.identifier.issn0142-9612-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/55473-
dc.description.abstractStochastic optical reconstruction microscopy (STORM) is a promising method for the visualization of ultra-fine mitochondrial structures. However, this approach is limited to monitoring dynamic intracellular events owing to its low temporal resolution. We developed a new strategy to capture mitochondrial dynamics using a compressed sensing STORM algorithm following raw data pre-treatments by a noise-corrected principal component analysis and K-factor image factorization. Using STORM microscopy with a vicinal-dithiol-proteins targeting probe, visualizing mitochondrial dynamics was attainable with spatial and temporal resolutions of 45 nm and 0.8 s, notably, dynamic mitochondrial tubulation retraction of similar to 746 nm in 1.2 s was monitored. The labeled conjugate was observed as clusters (radii, similar to 90 nm) distributed on the outer mitochondrial membranes, not yet reported as far as we know. This strategy is promising for the quantitative analysis of intracellular behaviors below the optical diffraction limit.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherELSEVIER SCI LTD-
dc.subjectSUPERRESOLUTION-
dc.subjectALGORITHM-
dc.subjectFUSION-
dc.titleSTORM imaging of mitochondrial dynamics using a vicinal-dithiol-proteins-targeted probe-
dc.typeArticle-
dc.contributor.affiliatedAuthorKim, Jong Seung-
dc.identifier.doi10.1016/j.biomaterials.2020.119938-
dc.identifier.scopusid2-s2.0-85081136722-
dc.identifier.wosid000523565800008-
dc.identifier.bibliographicCitationBIOMATERIALS, v.243-
dc.relation.isPartOfBIOMATERIALS-
dc.citation.titleBIOMATERIALS-
dc.citation.volume243-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaMaterials Science-
dc.relation.journalWebOfScienceCategoryEngineering, Biomedical-
dc.relation.journalWebOfScienceCategoryMaterials Science, Biomaterials-
dc.subject.keywordPlusSUPERRESOLUTION-
dc.subject.keywordPlusALGORITHM-
dc.subject.keywordPlusFUSION-
dc.subject.keywordAuthorSTORM-
dc.subject.keywordAuthorMitochondrial imaging-
dc.subject.keywordAuthorVDP Targeting-
dc.subject.keywordAuthorCyanine-
dc.subject.keywordAuthorLive cell imaging-
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