Label-Free Mass and Size Characterization of Few-kDa Biomolecules by Hierarchical Vision Transformer Augmented Nanofluidic Scattering Microscopy

Label-Free Mass and Size Characterization of Few-kDa Biomolecules by Hierarchical Vision Transformer Augmented Nanofluidic Scattering 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 Label-Free Mass and Size Characterization of Few-kDa Biomolecules by Hierarchical Vision Transformer Augmented Nanofluidic Scattering Microscopy Christoph Langhammer, Henrik Klein Moberg, Bohdan Yeroshenko, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6753006/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Mar, 2026 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Nanofluidic scattering microscopy characterizes single molecules in subwavelength nanofluidic channels label-free, using the interference of visible light scattered by the molecule and nanochannel. It determines a molecule’s hydrodynamic radius by tracking its diffusion trajectory and its molecular weight by analyzing its scattering intensity along that trajectory. However, using standard analysis algorithms, it is limited to characterization of proteins larger than ≈ 60 kDa. Here, we push this limit by one order of magnitude to below ≈ 6 kDa molecular weight and ≈ 1.5 nm hydrodynamic radius — as we exemplify on the peptide hormone insulin — by using ultrasmall nanofluidic channels and by analyzing the data with a hierarchical vision transformer. When we benchmark this approach against the theoretical limit set by the Cramér-Rao Lower Bound, we find that it can be approached with sufficiently long molecular trajectories. This opens interesting prospects for quantitative label-free single-molecule microscopy to characterize biologically relevant families of sub-10-kDa molecules, such as cytokines, chemokines and peptide hormones. Biological sciences/Biophysics/Single-molecule biophysics Biological sciences/Biophysics/Computational biophysics Biological sciences/Biological techniques/Microscopy Nanofluidic scattering microscopy Label-free microscopy Vision Transformer Deep Learning Full Text Additional Declarations Yes there is potential Competing Interest. B.S., D.A., J.F., C.L. are co-founders of Envue Technologies AB that markets nanofluidic scattering microscopy Supplementary Files KleinMobergetalSI10.pdf Suplementary Information for publication Cite Share Download PDF Status: Published Journal Publication published 13 Mar, 2026 Read the published version in Nature Communications → 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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