ArticleJournal of nanobiotechnology2026
Microfluidics engineered autologous nanovaccine for activating and visualizing antitumor activity.
Article in Journal of nanobiotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
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Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Tumor-derived extracellular vesicles (TEVs) are promising autologous cancer vaccines due to their intrinsic tumor-associated antigens. However, their translation is hindered by immune evasion and the lack of non-invasive tools to monitor vaccination efficacy in vivo. Here, we report a self-reporting nanovaccine engineered by coating TEVs under microfluidics with pH-sensitive manganese dioxide (mTEV). This surface biomineralization on TEVs chemically block inhibitory ligands such as CD47, promoting dendritic cell (DC) uptake and degrades under lysosomal conditions to expose tumor antigens and release Mn
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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.