ArticleJournal of extracellular vesicles2026
EV-Checklist: AI-Powered Rapid Documentation for Enhancing Transparency and Accessibility of Extracellular Vesicle Research Data.
Article in Journal of extracellular vesicles, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- EV-Checklist: AI-Powered Rapid Documentation for Enhancing Transparency and Accessibility of Extracellular Vesicle Research Data.Journal of extracellular vesicles · 2026Article
- Selective EV Protein Sorting and Pathway Perturbation in AML Upon Synergistic FLT3 and Hedgehog Pathway Inhibition.Journal of extracellular vesicles · 2025Article
- Therapeutic Potential of Extracellular Vesicles (Exosomes) Derived From Platelet-Rich Plasma: A Literature Review.Journal of cosmetic dermatology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Transition of extracellular vesicle (EV) research from basic discovery to clinical application raised hopes regarding diagnostic, therapeutic and prognostic progress. Rigorous reporting of experimental details is required to align the EV field with pharmaceutical quality standards. MISEV2023 recommendations encourage concise reporting but widespread adoption remains limited. Current reporting tools are time-consuming, and adherence declines despite rapidly growing number of EV studies. We therefore created EV-Checklist, a complementary digital tool that streamlines reporting and increases transparency. By uploading manuscript text, an AI-assisted algorithm automatically completes a checklist covering EV nomenclature, source, isolation, characterization and function. To ensure accuracy, users validate AI-generated entries before submission-ideally, gaps in reporting can be closed (e.g., missing particle/protein ratio). The resulting concise report can accompany manuscripts helping editors, reviewers and readers by presenting key methodological and results details at a glance. EV-Checklist complements existing comprehensive registries as 'fast-and-easy' tool enhancing clarity and accessibility of EV research data and may promote higher adherence to documentation standards. Adoption may be encouraged by journal endorsement to streamline the review process for compliant submissions, signalling adherence to MISEV2023 standards. EV-Checklist and an accompanying AI-assisted search tool (PMC EV Search), spanning over 45,700 open-access EV manuscripts, are publicly available at https://ev-zone.org/.
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.