ArticleACS nano2024
Single Extracellular Vesicle Imaging and Computational Analysis Identifies Inherent Architectural Heterogeneity.
Article in ACS nano, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
28 citing papers in PubMed.
- Beyond spherical vesicles: morphological diversity of extracellular vesicles in health and disease.Annals of medicine · 2026Review
- Skeletal muscle‑derived extracellular vesicles in multi‑organ degenerative disease: Mechanisms and therapeutic delivery perspectives (Review).International journal of molecular medicine · 2026Review
- Review
- Advances in Extracellular Vesicle-Based Surface-Enhanced Raman Spectroscopy for Cancer Diagnosis.Biosensors · 2026Review
- Cryogenic Electron Microscopy of Extracellular Vesicles from Temozolomide-Treated Glioblastoma Cells Reveals Great Morphological Heterogeneity.Nanomaterials (Basel, Switzerland) · 2026Article
- Automated Cryo-EM and Supervised Machine Learning Enable Reproducible Characterization of Extracellular Vesicles and Co-Isolating Particles.Journal of extracellular vesicles · 2026Article
- Engineering Yeast Extracellular Vesicle Biogenesis Through Rewiring Membrane Trafficking Pathways.Microbial biotechnology · 2026Article
- Recent advances in machine learning-enhanced extracellular vesicle omics for oncology.Journal of nanobiotechnology · 2026Review
- Extracellular Vesicles in Ophthalmology: From Natural Nanocarriers to Engineered Therapeutics.Bioengineering (Basel, Switzerland) · 2026Review
- Advancing Extracellular Vesicle Research: A Review of Systems Biology and Multiomics Perspectives.Proteomics · 2026Review
- Machine learning for extracellular vesicles enables diagnostic and therapeutic nanobiotechnology.Journal of nanobiotechnology · 2026Review
- Immune cell-derived exosomes in cancer: double-edged mechanisms of antitumor immunity and tumor progression.Frontiers in immunology · 2026Review
- Extracellular vesicle-mediated immune-metabolic crosstalk: research advances in inflammatory regulation and the pathogenesis of metabolic diseases.Frontiers in immunology · 2026Review
- Unveiling Heterogeneity: Innovations and Challenges in Single-Vesicle Analysis for Clinical Translation.Journal of extracellular vesicles · 2025Article
- Automated morphological classification and quantification of cerebrospinal fluid extracellular vesiclesNanoscale advances · 2025Article
- Engineered exosomes with KrasNature communications · 2025Article
- Quantifying the Shape and Stiffness of Single Extracellular Vesicles in Aqueous Solution via Membrane Diffusivity Measurements.Chemical & biomedical imaging · 2025Article
- Extracellular Vesicles for Clinical Diagnostics: From Bulk Measurements to Single-Vesicle Analysis.ACS nano · 2025Review
- Zika Virus Infection Modulates Extracellular Vesicle Biogenesis and Morphology in Human Umbilical Cord Endothelial Cells: A Proteomic and Microscopic Analysis.Microorganisms · 2025Article
- Toward Clarity in Single Extracellular Vesicle Research: Defining the Field and Correcting Missteps.ACS nano · 2025Review
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Authors and funding
10 authors.
Funding
Abstract
Evaluating the heterogeneity of extracellular vesicles (EVs) is crucial for unraveling their complex actions and biodistribution. Here, we identify consistent architectural heterogeneity of EVs using cryogenic transmission electron microscopy (cryo-TEM), which has an inherent ability to image biological samples without harsh labeling methods while preserving their native conformation. Imaging EVs isolated using different methodologies from distinct sources, such as cancer cells, normal cells, immortalized cells, and body fluids, we identify a structural atlas of their dominantly consistent shapes. We identify EV architectural attributes by utilizing a segmentation neural network model. In total, 7,576 individual EVs were imaged and quantified by our computational pipeline. Across all 7,576 independent EVs, the average eccentricity was 0.5366 ± 0.2, and the average equivalent diameter was 132.43 ± 67 nm. The architectural heterogeneity was consistent across all sources of EVs, independent of purification techniques, and compromised of single spherical, rod-like or tubular, and double shapes. This study will serve as a reference foundation for high-resolution images of EVs and offer insights into their potential biological impact.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.