Abstract
Diagnosing intracerebral hemorrhage (ICH) in prehospital settings remains challenging due to unavailability of immediate neuroimaging, clinical overlap with ischemic stroke, and absence of validated circulating biomarkers for time-critical settings. Extracellular vesicles (EVs), subcellular structures capable of transporting biomolecular payloads (e.g., proteins, nucleic acids) across the blood-brain barrier, have emerged as compelling diagnostic candidates for ICH. Nevertheless, their clinical translation has been impeded by inherent biophysical heterogeneity, particularly polydisperse size distributions. To address this limitation, we engineer a steric hindrance-mediated EV analysis and size fractionation (SHEAF) platform, integrating steric hindrance-based size fractionation with membrane protein profiling to stratify EVs into three size subtypes within a 45-min workflow. Systematic evaluation using the SHEAF platform reveals that the 90 − 180 nm EV subtype exhibits superior discriminative capacity in differentiating ICH from ischemic stroke plasma specimens. This technology not only advances rapid prehospital ICH diagnostics but also establishes a method for elucidating size-dependent EV functionalities across neurological pathologies.
Data availability
The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (https://proteomecentral.proteomexchange.org) via the iProX partner repository with the dataset identifier PXD075777. The main data supporting the results in this study are available within the paper and its Supplementary Information. Source data are provided with this paper for Figs. 2 - 5 and Supplementary Figs. 1, 5 − 7, 9 − 14, and 18. Source data are provided with this paper.
References
Greenberg, S. M. et al. Guideline for the management of patients with spontaneous intracerebral hemorrhage: a guideline from the American Heart Association/American. Stroke Assoc. Stroke 53, e282–e361 (2022).
Sandset, E. C. et al. European Stroke Organisation (ESO) guidelines on blood pressure management in acute ischaemic stroke and intracerebral haemorrhage. Eur. Stroke J. 6, X48–L69 (2021).
Qin, C. et al. Signaling pathways involved in ischemic stroke: molecular mechanisms and therapeutic interventions. Signal Transduct. Target Ther. 7, 215 (2022).
Tsivgoulis, G. et al. Thrombolysis for acute ischaemic stroke: current status and future perspectives. Lancet Neurol. 22, 418–429 (2023).
Tuo, Q.-Z., Zhang, S.-T. & Lei, P. Mechanisms of neuronal cell death in ischemic stroke and their therapeutic implications. Med. Res. Rev. 42, 259–305 (2022).
Liu, T. et al. Intracerebral hemorrhage: advances, knowledge gaps, and future directions. MedComm 6, e70436 (2025).
Pensato, U. et al. Spot sign in intracerebral hemorrhage: critical reappraisal and future clinical implications. Stroke 56, 1612–1624 (2025).
Mendelson, S. J. & Prabhakaran, S. Diagnosis and management of transient ischemic attack and acute ischemic stroke. JAMA 325, 1088–1098 (2021).
Warach, S. J. & David, G. Sherman lecture: improving stroke diagnosis and treatment-a journey toward the end of time. Stroke 55, 2567–257 (2024).
Montaner, J. et al. Multilevel omics for the discovery of biomarkers and therapeutic targets for stroke. Nat. Rev. Neurol. 16, 247–264 (2020).
Zylyftari, S. et al. GFAP point-of-care measurement for prehospital diagnosis of intracranial hemorrhage in acute coma. Crit. Care 28, 109 (2024).
Natalia, A., Zhang, L., Sundah, N. R., Zhang, Y. & Shao, H. Analytical device miniaturization for the detection of circulating biomarkers. Nat. Rev. Bioeng. 1, 481–498 (2023).
Wu, X. et al. Exosome-templated nanoplasmonics for multiparametric molecular profiling. Sci. Adv. 6, eaba2556 (2020).
Zhao, H. et al. A hydrogel-based mechanical metamaterial for the interferometric profiling of extracellular vesicles in patient samples. Nat. Biomed. Eng. 7, 135–148 (2022).
Wu, X. et al. Dual-protein orthogonal extracellular vesicle sorting and NEase amplified miRNA profiling by giant magneto resistance (GMR) biochip for the diagnosis of glioma. Chem. Eng. J. 514, 163186 (2025).
Wu, X. et al. One-to-one fusion-mediated single extracellular vesicle analysis for early screening of breast cancer. ACS Sens 10, 8373–8382 (2025).
Yousif, G. et al. Circulating exosomes of neuronal origin as potential early biomarkers for development of stroke. Mol. Diagn. Ther. 25, 163–180 (2021).
Cano, A. et al. Extracellular vesicles, the emerging mirrors of brain physiopathology. Int. J. Biol. Sci. 19, 721–743 (2023).
Yashar, M. et al. Extracellular microRNAs in blood differentiate between ischaemic and haemorrhagic stroke subtypes. J. Extracell. Vesicles 9, 1713540 (2020).
Hirsch, Y. et al. Unpacking the role of extracellular vesicles in ischemic and hemorrhagic stroke: pathophysiology and therapeutic implications. Transl. Stroke Res. 14, 146–159 (2022).
Magoling, B. J. A. et al. Membrane protein modification modulates big and small extracellular vesicle biodistribution and tumorigenic potential in breast cancers in vivo. Adv. Mater. 35, 2208966 (2023).
Zhai, C. et al. Correlation between membrane proteins and sizes of extracellular vesicles and particles: A potential signature for cancer diagnosis. J. Extracell. Vesicles 12, 12391 (2023).
Liu, C. et al. λ-DNA- and aptamer-mediated sorting and analysis of extracellular vesicles. J. Am. Chem. Soc. 141, 3817–3821 (2019).
Zhang, Q. et al. Supermeres are functional extracellular nanoparticles replete with disease biomarkers and therapeutic targets. Nat. Cell Biol. 23, 1240–1254 (2021).
Zhang, H. et al. Identification of distinct nanoparticles and subsets of extracellular vesicles by asymmetric flow field-flow fractionation. Nat. Cell Biol. 20, 332–343 (2018).
Iinuma, R., Chen, X., Masubuchi, T., Ueda, T. & Tadakuma, H. Size-selective capturing of exosomes using DNA tripods. J. Am. Chem. Soc. 146, 10293–10298 (2024).
Qin, T. et al. Size-exclusion chromatography-based extracellular vesicles size subtyping and multiplex membrane protein profiling for differentiating gastrointestinal cancer prognosis. Analyst 148, 5745–5752 (2023).
Kim, D. et al. EV-Ident: Identifying tumor-specific extracellular vesicles by size fractionation and single-vesicle analysis. Anal. Chem. 92, 6010–6018 (2020).
Bu, Y. et al. High-performance gel-free and label-free size fractionation of extracellular vesicles with two-dimensional electrophoresis in a microfluidic artificial sieve. Anal. Chem. 96, 3508–3516 (2024).
Middleton, E. R. & Rhoades, E. Effects of curvature and composition on α-synuclein binding to lipid vesicles. Biophys. J. 99, 2279–2288 (2010).
Iwamoto, K. et al. Curvature-dependent recognition of ethanolamine phospholipids by duramycin and cinnamycin. Biophys. J. 93, 1608–1619 (2007).
Sugiura, Y., Ikeda, K. & Nakano, M. High membrane curvature enhances binding, conformational changes, and fibrillation of amyloid-β on lipid bilayer surfaces. Langmuir 31, 11549–11557 (2015).
Phan, H. T. et al. Bimodal brush-functionalized nanoparticles selective to receptor surface density. Proc. Natl. Acad. Sci. USA 120, e2208377120 (2023).
Noureddine, A. et al. Future of mesoporous silica nanoparticles in nanomedicine: protocol for reproducible synthesis, characterization, lipid coating, and loading of therapeutics (chemotherapeutic, proteins, siRNA and mRNA). ACS Nano 17, 16308–16325 (2023).
Lérida-Viso, A., Estepa-Fernández, A., García-Fernández, A., Martí-Centelles, V. & Martínez-Máñez, R. Biosafety of mesoporous silica nanoparticles; towards clinical translation. Adv. Drug Deliv. Rev. 201, 115049 (2023).
Kim, M. G., Ryu, S. M. & Shin, Y. Recent advances in bioreceptor-based sensing for extracellular vesicle analysis. Biosens. Bioelectron. 280, 117432 (2025).
Wu, Q. et al. Advances in extracellular vesicle nanotechnology for precision theranostics. Adv. Sci. 10, e2204814 (2023).
Meng, X. et al. Redox-manipulating nanocarriers for anticancer drug delivery: a systematic review. J. Nanobiotechnology 22, 587 (2024).
Dixson, A. C., Dawson, T. R., Di Vizio, D. & Weaver, A. M. Context-specific regulation of extracellular vesicle biogenesis and cargo selection. Nat. Rev. Mol. Cell Biol. 24, 454–476 (2023).
Rädler, J., Gupta, D., Zickler, A. & Andaloussi, S. E. Exploiting the biogenesis of extracellular vesicles for bioengineering and therapeutic cargo loading. Mol. Ther. 31, 1231–1250 (2023).
Johnsen, K. B., Gudbergsson, J. M., Andresen, T. L. & Simonsen, J. B. What is the blood concentration of extracellular vesicles? Implications for the use of extracellular vesicles as blood-borne biomarkers of cancer. Biochim. Biophys. Acta Rev. Cancer 1871, 109–116 (2019).
Bang, O. Y. et al. Circulating extracellular vesicles in stroke patients treated with mesenchymal stem cells: a biomarker analysis of a randomized trial. Stroke 53, 2276–2286 (2022).
Monguió-Tortajada, M., Gálvez-Montón, C., Bayes-Genis, A., Roura, S. & Borràs, F. E. Extracellular vesicle isolation methods: rising impact of size-exclusion chromatography. Cell. Mol. Life Sci. 76, 2369–2382 (2019).
Guo, J. et al. Establishment of a simplified dichotomic size-exclusion chromatography for isolating extracellular vesicles toward clinical applications. J. Extracell. Vesicles 10, e12145 (2021).
Benayas, B., Morales, J., Egea, C., Armisén, P. & Yáñez-Mó, M. Optimization of extracellular vesicle isolation and their separation from lipoproteins by size exclusion chromatography. J. Extracell. Biol. 2, e100 (2023).
Arab, T. et al. Proteomic characterisation of leech microglia extracellular vesicles (EVs): comparison between differential ultracentrifugation and Optiprep™ density gradient isolation. J. Extracell. Vesicle 8, 1603048 (2019).
Crescitelli, R., Lässer, C. & Lötvall, J. Isolation and characterization of extracellular vesicle subpopulations from tissues. Nat. Protoc. 16, 1548–1580 (2021).
Auquière, M., Muccioli, G. G. & Rieux, A. Methods and challenges in purifying drug-loaded extracellular vesicles. J. Extracell. Vesicle 14, e70097 (2025).
Welsh, J. A. et al. Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches. J. Extracell. Vesicles 13, e12404 (2024).
Zhang, H. & Lyden, D. Asymmetric-flow field-flow fractionation technology for exomere and small extracellular vesicle separation and characterization. Nat. Protoc. 14, 1027–1053 (2019).
Lee, C. et al. Vascular endothelial growth factor signaling in health and disease: from molecular mechanisms to therapeutic perspectives. Signal Transduct. Target Ther. 10, 170 (2025).
Hewitt, B. J., Ali, M., Hubbard, J., Hill, L. J. & Botfield, H. Systematic review of the differential effects of TGF-β1 in ischemic and hemorrhagic preclinical stroke models. J. Am. Heart Assoc. 14, e037890 (2025).
Cheng, F. et al. Neuronal PD-L1 suppression attenuates ischemic stroke injury via PD-1/RFX1 axis-mediated microglial polarization. Int J. Surg. 22, 7711–7726 (2025).
Nordestgaard, A. T. et al. High-sensitivity C-reactive protein, LDL cholesterol, lipoprotein(a) and 30-year risk of stroke in healthy women: a prospective, longitudinal cohort study. Lancet Neurol. 24, 920–930 (2025).
Thougaard, E. et al. Systemic inhibition of soluble TNF significantly changes glial cell populations leading to improved myelin integrity and better functional outcome after experimental stroke. Biomed. Pharmacother. 189, 118334 (2025).
Witsch, J. et al. Association between soluble intercellular adhesion molecule-1 and intracerebral hemorrhage outcomes in the FAST trial. Stroke 54, 1726–1734 (2023).
Lino, M. M. et al. Engineered extracellular vesicles as brain therapeutics. J. Control. Release 338, 472–485 (2021).
Vandendriessche, C., Kapogiannis, D. & Vandenbroucke, R. E. Biomarker and therapeutic potential of peripheral extracellular vesicles in Alzheimer’s disease. Adv. Drug Deliv. Rev. 190, 14486 (2022).
Nonaka, Y. et al. Affinity improvement of a VEGF aptamer by in silico maturation for a sensitive VEGF-detection system. Anal. Chem. 85, 1132–1137 (2012).
Kang, J., Myung Soog Lee, Copland, J. A., Luxon, B. A. & Gorenstein, D. G. Combinatorial selection of a single stranded DNA thioaptamer targeting TGF-β1 protein. Bioorg. Med. Chem. Lett. 18, 1835–1839 (2008).
Wu, L. et al. Aptamer-based liquid biopsy. ACS Appl. Bio. Mater. 3, 2743–2764 (2020).
Wu, B. et al. Detection of c-reactive protein using nanoparticle-enhanced surface plasmon resonance using an aptamer-antibody sandwich assay. Chem. Commun. 52, 3568–3571 (2016).
Lai, W.-Y., Wang, J.-W., Huang, B.-T., Lin, E. P.-Y. & Yang, P.-C. A novel TNF-α-targeting aptamer for TNF-α-mediated acute lung injury and acute liver failure. Theranostics 9, 1741–1751 (2019).
Dursun, A. D. et al. Surface plasmon resonance aptasensor for soluble ICAM-1 protein in blood samples. Analyst 147, 1663–1668 (2022).
Bai, Y. et al. Myricetin ameliorates ox-LDL-induced HUVECs apoptosis and inflammation via lncRNA GAS5 upregulating the expression of miR-29a-3p. Sci. Rep. 11, 19637 (2021).
Sun, Y. et al. Oxidized low-density lipoprotein changes the inflammatory status and metabolomics profiles in human and mouse macrophages and microglia. Heliyon 10, e28806–e28806 (2024).
Zhao, Y. et al. Salvianolic acid B inhibits atherosclerosis and TNF-α-induced inflammation by regulating NF-κB/NLRP3 signaling pathway. Phytomedicine 119, 155002 (2023).
Acknowledgements
This work was supported by the National Natural Science Foundation of China: Grant No. 22064007 (X.W.), 52375577 (H.Z.), 82560244 (G.W.), and 82260244 (G.W.). X.W. acknowledges support from the Guizhou Provincial Natural Science Foundation (Grant No. ZK[2021]482). G.W. acknowledges support from the Leading Discipline Program of The Affiliated Hospital of Guizhou Medical University (Grant No. gyfyxkrc-2023-05), the Key Lab of Acute Brain Injury and Function Repair in Guizhou Medical University (Grant No. [2024]fy007), and the Key Advantageous Discipline Construction Project of Guizhou Provincial Health Commission in 2023 in Emergency Department.
Author information
Authors and Affiliations
Contributions
X.W., H.Z., G.W., and X.S. conceived the project, designed the experiments and wrote the manuscript. X.W., S.X., and L.Z. conducted the experiments and performed data analysis. Y.Z. performed SEC- and DGUC-based EV size fractionation. Q.G. and Y.E.W. established cellular inflammation models. W. Long conducted the Western blotting experiments and proteomic analyses. Z.S., L.W., W.L., and G.W. collected clinical samples and performed clinical diagnosis. Y.C. and L.T. coded the programs.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Peer review
Peer review information
Nature Communications thanks Jiashu Sun, Dan Stratton and the other anonymous reviewer for their contribution to the peer review of this work. [A peer review file is available].
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Source data
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
About this article
Cite this article
Wu, X., Xiong, S., Zhang, L. et al. Steric hindrance-mediated extracellular vesicle size fractionation for rapid prehospital diagnosis of intracerebral hemorrhage. Nat Commun (2026). https://doi.org/10.1038/s41467-026-71751-y
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41467-026-71751-y