A modular tissue-clearing framework integrated with light-field microscopy enables rapid volumetric phenotyping of cardiac tissue

A modular tissue-clearing framework integrated with light-field microscopy enables rapid volumetric phenotyping of cardiac tissue | 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 A modular tissue-clearing framework integrated with light-field microscopy enables rapid volumetric phenotyping of cardiac tissue Shi Lin, Denise Schichines, Hua-Man Hsu, Yen-Ling Hung, Kaushik Chowdhury, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8566379/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 Tissue clearing has transformed volumetric imaging by improving optical access to thick tissues, yet most existing protocols remain rigid and fail to accommodate the biochemical diversity of different samples. Here, we introduce a question-oriented modular framework that enables flexible assembly of clearing and imaging pipelines tailored to specific biological objectives. By systematically optimizing each module to preserve endogenous fluorescence, antigenicity, and tissue integrity while achieving high transparency and protein retention, we demonstrate its use across diverse cardiac applications—development, infarction and regeneration, as well as immune and vascular mapping—showing that different questions require distinct module assemblies and parameters. Coupled with light-field microscopy (LFM), the workflow efficiently captures submillimeter sections with 30–100-fold smaller datasets and rapid computational reconstruction, enabling high-throughput quantitative volumetric analysis. Together, this modular framework and imaging integration provide a rational and practical foundation for adaptable and interoperable 3D analyses of regenerative, pathological, and comparative systems across vertebrate models. Biological sciences/Biological techniques/Imaging/Optical imaging Biological sciences/Developmental biology/Differentiation Full Text Additional Declarations There is NO Competing Interest. Supplementary Files Supplementarysummarytable.xlsx Supplementary Table 1 Supplementaryvideos.zip Supplementary_videos 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-8566379","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":573484132,"identity":"2b4e6502-5a42-4e77-9f3d-02db75335639","order_by":0,"name":"Shi 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