ReviewBioactive materials2026
Artificial intelligence virtual extracellular vesicles (AIVEVs).
Review in Bioactive materials, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Biomaterials at the interface of bone-derived factors and inter-organ communication: Current evidence and future perspectives.Bioactive materials · 2026Review
- Extracellular Vesicle-Based Therapies for Osteoarthritis-Advances, Challenges and Hopes.Exploration (Beijing, China) · 2026Article
- Review
- Advances in multivariate analysis of extracellular vesicles using visible light-based analytical methods.Nanoscale · 2026Review
- Decoding Immune Dysregulation in Sepsis Through Extracellular Vesicles: A Path to Precision Medicine.Pharmaceutics · 2026Review
- Plant-Derived Exosomes in Aesthetic Medicine.Biomaterials research · 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent progress in artificial intelligence (AI) has given rise to AI virtual cells (AIVCs), which are digital twins of predictable or dynamic biological cells. This model can simulate, predict and replicate the behavior of real cells in digital software. Extracellular vesicles (EVs) are nanoscale phospholipid bilayer structures released by cells and are important for intercellular communication. To fully leverage digital models in EVs research, we propose the interdisciplinary concept of AI virtual EVs (AIVEVs). This review systematically outlines the construction of AIVEVs through both knowledge-driven (white-box) and data-driven (black-box) modeling paradigms, integrating multi-omics data to simulate EVs biogenesis, cargo sorting, and intercellular communication. Moreover, we highlight how AIVCs drive models to predict the composition of AIVEVs, analyze cell communication behavior, construct diagnostic atlases of pathological virtual cells, and enhance the ability to trace vesicle origins. Furthermore, we also present a closed-loop workflow from
Indexed as
Identifiers
What Socratic 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 Socratic graph.