Evidence map›Paper›PMID 41236534›Full record

ArticleThe Journal of general virology2025

Improved efficacy of an influenza DNA vaccine through high-density microarray patch delivery.

Chloe G Entriken, Kimberley L Bruce, Bridget M Coyne, Saxon H Kruyer, Jane E Sinclair, Jovin J Y Choo, David A Muller, Christopher L D McMillan

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The Journal of general virology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Chloe G EntrikenSchool of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, QLD, 4072, Australia.
Kimberley L BruceSchool of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, QLD, 4072, Australia.
Bridget M CoyneSchool of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, QLD, 4072, Australia.
Saxon H KruyerSchool of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, QLD, 4072, Australia.
Jane E SinclairSchool of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, QLD, 4072, Australia.
Jovin J Y ChooSchool of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, QLD, 4072, Australia.
David A MullerSchool of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, QLD, 4072, Australia.
Christopher L D McMillanSchool of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, QLD, 4072, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pandemic preparedness requires vaccine platforms that are fast to produce, thermostable and suitable for broad deployment. DNA vaccines are well suited to this task but have historically suffered from poor immunogenicity when delivered by conventional intramuscular (IM) injection. Here, we evaluated high-density microarray patch (HD-MAP) delivery of a DNA vaccine encoding the influenza A/California/01/2009 (H1N1pdm09) haemagglutinin (HA) antigen.

Indexed as

Hemagglutinin Glycoproteins, Influenza VirusInfluenza A Virus, H1N1 SubtypeInfluenza VaccinesMicroarray AnalysisOrthomyxoviridae InfectionsVaccines, DNAAnimalsAntibodies, ViralFemaleHumansImmunoglobulin GInjections, IntramuscularMiceMice, Inbred BALB CVaccinationAntibodies, ViralHemagglutinin Glycoproteins, Influenza VirusImmunoglobulin GInfluenza VaccinesVaccines, DNAinfluenzamicroarray patchpandemicvaccine

Identifiers

PMID41236534
PMCPMC12617852

What OpenQuestion holds

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Registered trials

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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.