ReviewJournal of proteome research2025
Plasma-Derived Extracellular Vesicle Proteomics.
Review in Journal of proteome research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Targeting SIRT3 in Diabetic Cardiomyopathy: Mechanism-Based Therapeutic Strategies.Cardiovascular drugs and therapy · 2026Review
- Article
- Proteomic and Small RNA Characterization of Extracellular Vesicle-enriched Particles Released from Cultured Host-isolated Symbiodiniaceae.Marine biotechnology (New York, N.Y.) · 2026Article
- Developing blood extracellular vesicle protein biomarkers for hepatocellular carcinoma: mechanisms, methods, and translation.Journal of nanobiotechnology · 2026Review
- Plasma extracellular vesicle proteomic analysis identifies WARS as a potential biomarker of infectious mononucleosis.BMC infectious diseases · 2026Article
- Review
- Recent advances in machine learning-enhanced extracellular vesicle omics for oncology.Journal of nanobiotechnology · 2026Review
- Advancing Extracellular Vesicle Research: A Review of Systems Biology and Multiomics Perspectives.Proteomics · 2026Review
- Improvement of small extracellular vesicle isolation from mouse model blood.Extracellular vesicles and circulating nucleic acids · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Extracellular vesicles (EVs) are nanometer-scale lipid bilayer-enclosed particles released by cells under physiological and pathological conditions. Their molecular cargos, including proteins, can reflect the chemical composition and physiological state of the parent cells, carrying signatures of health and disease. As such, EVs are valuable tools for biomarker discovery and mechanistic studies. Among them, plasma-derived EVs (pEVs) are particularly promising, as sampling plasma allows capture of EVs from virtually all of the tissues and organs. The minimally invasive nature of plasma collection further enhances the diagnostic and therapeutic potential of the pEVs. Proteomic profiling of pEVs enables the identification of disease-specific EV-biomarkers. However, the complexity of plasma, with high levels of abundant proteins and large EV heterogeneity, presents challenges for pEV proteomics. Mass spectrometry (MS) has emerged as the preferred state-of-the-art analytical tool for pEV studies due to its nonbiased ability to characterize thousands of proteins in an experiment and its ability to identify low-abundance EV proteins. Here, a comprehensive overview of the advancements in MS-based pEV proteomics in the recent 5 years is presented with a focus on three key areas: sample preparation methodologies, MS-based approaches for protein identification and quantification, and description of pEV studies for basic and disease research. Technical advancements enable greater proteomic details from pEVs, enhancing biomarker discovery, elucidating disease mechanisms, and advancing an understanding of EVs' biological roles.
Indexed as
Identifiers
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.