ArticleNPJ vaccines2026
Durability of DNA-LNP and mRNA-LNP vaccine-induced immunity against SARS-CoV-2 XBB.1.5.
Article in NPJ vaccines, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
mRNA-lipid nanoparticle (LNP) vaccines induce robust adaptive immune responses and have proven highly effective against SARS-CoV-2. However, their long-term effectiveness is limited by waning humoral responses, which decline substantially within the first six months post-boost vaccination. DNA-LNPs are being investigated as an alternative vaccine platform, offering prolonged antigen expression and robust immunity. Here, we compare DNA- and mRNA-LNP vaccines encoding CD40L-adjuvanted SARS-CoV-2 XBB.1.5 Spike (S
Identifiers
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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.