Evidence map›Paper›PMID 29467737›Full record

ReviewFrontiers in microbiology2018

Universal Vaccines and Vaccine Platforms to Protect against Influenza Viruses in Humans and Agriculture.

Daniela S Rajão, Daniel R Pérez

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in microbiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers.

0numbers the graph read from it
0cells of the map it votes in
93citing papers in PubMed
14.1field-weighted citation impact, top 1% of its field
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

93 citing papers in PubMed, 160 citations in OpenAlex.

  1. Review
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  15. Cyanobacterial and microalgae polymers: antiviral activity and applications.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2024
    Review
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33 more citing papers are in PubMed but not listed here.

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

2 authors at 1 institution in 1 country.

Daniela S RajãoDepartment of Population Health, University of Georgia, Athens, GA, United States.
Daniel R PérezDepartment of Population Health, University of Georgia, Athens, GA, United States.
University of Georgia · US

Funding

NIAID NIH HHS HHSN272201400008C
6 · The paper itself

Abstract

Influenza virus infections pose a significant threat to public health due to annual seasonal epidemics and occasional pandemics. Influenza is also associated with significant economic losses in animal production. The most effective way to prevent influenza infections is through vaccination. Current vaccine programs rely heavily on the vaccine's ability to stimulate neutralizing antibody responses to the hemagglutinin (HA) protein. One of the biggest challenges to an effective vaccination program lies on the fact that influenza viruses are ever-changing, leading to antigenic drift that results in escape from earlier immune responses. Efforts toward overcoming these challenges aim at improving the strength and/or breadth of the immune response. Novel vaccine technologies, the so-called universal vaccines, focus on stimulating better cross-protection against many or all influenza strains. However, vaccine platforms or manufacturing technologies being tested to improve vaccine efficacy are heterogeneous between different species and/or either tailored for epidemic or pandemic influenza. Here, we discuss current vaccines to protect humans and animals against influenza, highlighting challenges faced to effective and uniform novel vaccination strategies and approaches.

Indexed as

immune responseinfluenza vaccineslive attenuated vaccinespoultryswineuniversal vaccinesvaccine platformvectored vaccine

Identifiers

PMID29467737
PMCPMC5808216
OpenAlexW2790341375

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.