Evidence map›Paper›PMID 38817814›Full record

ArticlemLife2023

Protective efficacy of a universal influenza mRNA vaccine against the challenge of H1 and H5 influenza A viruses in mice.

Yulei Li, Xi Wang, Xi Zeng, Wenbo Ren, Pu Liao, Baoli Zhu

Abstract read
In one paragraph

Article in mLife, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Review
  2. mRNA Vaccines for Influenza: Hope for a Universal Vaccine?BioDrugs : clinical immunotherapeutics, biopharmaceuticals and gene therapy · 2026
    Review
  3. Article
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  5. Article
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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

6 authors.

Yulei LiSavaid Medical School University of Chinese Academy of Sciences Beijing China.ORCID 0000-0001-6918-2779
Xi WangCAS Key Laboratory of Pathogenic Microbiology and Immunology Chinese Academy of Sciences Beijing China.
Xi ZengBeijing Children's Hospital Capital Medical University Beijing China.
Wenbo RenCollege of Life Sciences Jiangxi Science and Technology Normal University Nanchang China.
Pu LiaoDepartment of Clinical Laboratory Chongqing General Hospital Chongqing China.
Baoli ZhuCAS Key Laboratory of Pathogenic Microbiology and Immunology Chinese Academy of Sciences Beijing China.ORCID 0000-0001-5326-9503

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current influenza vaccines need to be updated annually owing to constant antigenic drift in the globular head of the viral surface hemagglutinin (HA) glycoprotein. The immunogenic subdominant stem domain of HA is highly conserved and can be recognized by antibodies capable of binding multiple HA subtypes. Therefore, the HA stem antigen is a promising target for the design of universal influenza vaccines. On the basis of an established lipid nanoparticle-encapsulated mRNA vaccine platform, we designed and developed a novel universal influenza mRNA vaccine (mHAs) encoding the HA stem antigen of the influenza A (H1N1) virus. We tested the efficacy of the mHAs vaccine using a mouse model. The vaccine induced robust humoral and specific cellular immune responses against the stem region of HA. Importantly, two doses of the mHAs vaccine fully protected mice from lethal challenges of the heterologous H1N1 and heterosubtypic H5N8 influenza viruses. Vaccinated mice had less pathological lung damage and lower viral titers than control mice. These results suggest that an mRNA vaccine using the conserved stem region of HA may provide effective protection against seasonal and other possible influenza variants.

Indexed as

immunogenicityinfluenza virusmRNA vaccineuniversal vaccine

Identifiers

PMID38817814
PMCPMC10989953

What OpenQuestion holds

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Registered trials

None linked

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.