Evidence map›Paper›PMID 30715361›Full record

ArticleThe Journal of infectious diseases2019

New Vaccine Design and Delivery Technologies.

Masaru Kanekiyo, Daniel Ellis, Neil P King

Abstract read
In one paragraph

Article in The Journal of infectious diseases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 2 pooled it
–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

44 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  7. Improving the immunogenicity ofFrontiers in immunology · 2026
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  12. Generative Artificial Intelligence for Virology.Methods in molecular biology (Clifton, N.J.) · 2025
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  14. 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

3 authors.

Masaru KanekiyoVaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland.
Daniel EllisInstitute for Protein Design, University of Washington, Seattle.
Neil P KingInstitute for Protein Design, University of Washington, Seattle.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Technological advances in immunology, protein design, and genetic delivery have unlocked new possibilities for vaccine concepts and delivery technologies that were previously inaccessible. These next-generation vaccine design efforts are particularly promising in their potential to provide solutions to challenging targets for which conventional approaches have proven ineffective-for example, a universal influenza vaccine. In this perspective, we discuss emerging approaches to vaccine design and engineering based on recent insights into immunology, structural biology, computational biology, and immunoengineering. We anticipate that these cutting-edge, interdisciplinary approaches will lead to breakthrough vaccine concepts for ever-evolving and (re)emerging influenza viruses, with important ramifications for global public health.

Indexed as

AnimalsAntibodies, ViralAntigen PresentationAntigens, ViralBroadly Neutralizing AntibodiesDisease Models, AnimalEpitopesHemagglutinin Glycoproteins, Influenza VirusHumansInfluenza, HumanInfluenza VaccinesMiceOrthomyxoviridaeOrthomyxoviridae InfectionsProtein EngineeringRNA, MessengerAntibodies, ViralAntigens, ViralBroadly Neutralizing AntibodiesEpitopesHemagglutinin Glycoproteins, Influenza VirusInfluenza VaccinesRNA, Messengerantigen designantigen displaybroadly neutralizing antibodymRNA vaccinenanoparticleprotein engineeringstructure-based vaccineuniversal influenza vaccine

Identifiers

PMID30715361
PMCPMC6452296

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.