Lattice light sheet activation structured illumination volumetric super-resolution live microscopy

Lattice light sheet activation structured illumination volumetric super-resolution live microscopy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Lattice light sheet activation structured illumination volumetric super-resolution live microscopy Dong Li, Xue Dong, Quan Meng, Xiaoyu Yang, Haoyu Chen, Chang Qiao, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5864510/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Volumetric super-resolution (SR) live imaging at high-speed for long-time remains challenging, especially for fluorescent thick specimens. In this work, we develop Lattice light sheet Activation Structured Illumination Microscopy (LA-SIM), which integrates the unique advantages of superior optical sectioning and low photo-toxicity offered by light sheet configuration with full-version SR-SIM in both linear and nonlinear schemes together, by means of reversibly photo-switchable fluorescent protein (rsFP). Moreover, LA-SIM allows implementing rationalized deep-learning (rDL) denoising in a self-supervised manner, enabling the production of high-quality three-dimensional (3D) SR images at limited SNR levels, while achieving bona fide optical resolution improvement beyond 2-fold relative to diffraction-limit in both lateral and axial dimensions. We utilize the high-quality rDL LA-SIM data to train a large-scale transformer model --- SRFormer that can overcome the inferior properties of rsFPs and enable multi-color long-term volumetric SR imaging. We demonstrate that SRFormer LA-SIM can shed new light on subcellular dynamics from single-cell to multi-cellular specimens. Biological sciences/Biological techniques/Imaging/Optical imaging Biological sciences/Biological techniques/Microscopy/Light-sheet microscopy Biological sciences/Biological techniques/Microscopy/Super-resolution microscopy Full Text Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryVideo1.mp4 Supplementary Video 1 SupplementaryVideo2.mp4 Supplementary Video 2 SupplementaryVideo3.mp4 Supplementary Video 3 SupplementaryVideo4.mp4 Supplementary Video 4 SupplementaryVideo5.mp4 Supplementary Video 5 SupplementaryVideo6.mp4 Supplementary Video 6 SupplementaryVideo7.mp4 Supplementary Video 7 SupplementaryVideo8.mp4 Supplementary Video 8 SupplementaryVideo9.mp4 Supplementary Video 9 SupplementaryVideo10.mp4 Supplementary Video 10 SupplementaryVideo11.mp4 Supplementary Video 11 SupplementaryVideo12.mp4 Supplementary Video 12 SupplementaryVideo13.mp4 Supplementary Video 13 SupplementaryVideo14.mp4 Supplementary Video 14 SupplementaryVideo15.mp4 Supplementary Video 15 SupplementaryFigure1.pdf Supplementary Figure 1 SupplementaryFigure2.pdf Supplementary Figure 2 SupplementaryFigure3.pdf Supplementary Figure 3 SupplementaryFigure4.pdf Supplementary Figure 4 SupplementaryFigure5.pdf Supplementary Figure 5 SupplementaryFigure6.pdf Supplementary Figure 6 SupplementaryFigure7.pdf Supplementary Figure 7 SupplementaryMaterial.pdf Supplementary Material Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5864510","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":407878428,"identity":"3e52df49-cebf-40b8-a9c6-17333b34b9fd","order_by":0,"name":"Dong 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microscopy","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research 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In this work, we develop Lattice light sheet Activation Structured Illumination Microscopy (LA-SIM), which integrates the unique advantages of superior optical sectioning and low photo-toxicity offered by light sheet configuration with full-version SR-SIM in both linear and nonlinear schemes together, by means of reversibly photo-switchable fluorescent protein (rsFP). Moreover, LA-SIM allows implementing rationalized deep-learning (rDL) denoising in a self-supervised manner, enabling the production of high-quality three-dimensional (3D) SR images at limited SNR levels, while achieving bona fide optical resolution improvement beyond 2-fold relative to diffraction-limit in both lateral and axial dimensions. We utilize the high-quality rDL LA-SIM data to train a large-scale transformer model --- SRFormer that can overcome the inferior properties of rsFPs and enable multi-color long-term volumetric SR imaging. We demonstrate that SRFormer LA-SIM can shed new light on subcellular dynamics from single-cell to multi-cellular specimens.","manuscriptTitle":"Lattice light sheet activation structured illumination volumetric super-resolution live microscopy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-29 06:15:32","doi":"10.21203/rs.3.rs-5864510/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4f90eeed-925e-48f6-a203-c05f038a15eb","owner":[],"postedDate":"January 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":43486780,"name":"Biological sciences/Biological techniques/Imaging/Optical imaging"},{"id":43486781,"name":"Biological sciences/Biological techniques/Microscopy/Light-sheet microscopy"},{"id":43486782,"name":"Biological sciences/Biological techniques/Microscopy/Super-resolution microscopy"}],"tags":[],"updatedAt":"2025-11-11T16:40:03+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-29 06:15:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5864510","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5864510","identity":"rs-5864510","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}