ArticleNucleic acids research2026
SVAtlas: a comprehensive single extracellular vesicle omics resource.
Article in Nucleic acids research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed.
- Exosomal circular RNAs in the tumor immune microenvironment: From regulatory mechanisms to therapeutic opportunities and translational hurdles (Review).International journal of molecular medicine · 2026Review
- Beyond Exosomes: Biological Properties, Isolation Challenges, and Functional Redefinition of Non-Vesicular Extracellular Nanoparticles (NVEPs).Biomolecules · 2026Review
- Artificial intelligence virtual extracellular vesicles (AIVEVs).Bioactive materials · 2026Review
- The 'sugar' side of extracellular vesicle-glycome: a panorama from basic characteristics, deciphering technologies, functions, to applications.Journal of nanobiotechnology · 2026Review
- Extracellular Vesicles in the Gut-Vascular-Brain Axis: A Missing Mechanistic Link Between IBD and Stroke Risk.Biomolecules · 2026Review
- Recent advances in machine learning-enhanced extracellular vesicle omics for oncology.Journal of nanobiotechnology · 2026Review
- Article
- Cell Surface Shaving-Based Proteomic Profiling of the Surfaceome in Pathogenic Microorganisms.International journal of molecular sciences · 2026Review
- Advanced Technologies in Extracellular Vesicle Biosensing: Platforms, Standardization, and Clinical Translation.Molecules (Basel, Switzerland) · 2026Review
- Harnessing plant-derived extracellular vesicles in advanced biomaterials: from structural scaffolds to responsive systems for next-generation wound therapeutics.Burns & trauma · 2026Review
- An updated review on the role of extracellular vesicles in immune system modulation in breast cancer with special emphasis on immune checkpoint regulators.Frontiers in immunology · 2026Review
- Extracellular Vesicle-Associated Non-Coding RNAs in Preeclampsia: Mechanistic Insights, Biomarker Discovery, and Emerging Nanomedicine Concepts.International journal of nanomedicine · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
Extracellular vesicles (EVs) are nanoscale particles released by cells, carrying proteins, nucleic acids, lipids, and metabolites. These vesicles mediate intercellular communication and modulate disease progression across various conditions. Owing to their molecular heterogeneity and the stable bilayer protecting their cargo, EVs serve as valuable tools for early disease detection and personalized therapies. However, traditional bulk EV studies aggregate data, which can mask the distinct molecular profiles of individual EVs critical for targeted diagnostics and treatments, diminishing diagnostic precision. Recent advances in single-EV analysis, leveraging high-resolution sequencing and imaging technologies, have revealed unique molecular signatures. However, a comprehensive database integrating multi-omics data from single EVs remains lacking. To address this, we developed SVAtlas, the first database dedicated to integrating single-EV datasets (2015-2025). SVAtlas incorporates 8120 protein entries, 106 RNA entries (miRNA, mRNA, circRNA, and lncRNA), 2 DNA entries, and 8 lipid/metabolite entries across 276 EV projects, spanning 31 diseases, 32 tissues/organs, and 10 biofluids from five species. SVAtlas offers single-EV datasets with experimental parameters, heterogeneity analyses, disease-specific marker exploration, built-in analysis/clustering/visualization pipelines, and an LLM-based question-answering tool, empowering researchers to explore single-EV omics in detail. Free and accessible at https://www.svatlas.org/, SVAtlas accelerates the clinical translation of single-EV analysis and biomarker discovery.
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What OpenQuestion holds
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.