Evidence map›Paper›PMID 24130558›Full record

ReviewFrontiers in immunology2013

Immunostimulation by synthetic lipopeptide-based vaccine candidates: structure-activity relationships.

Mehfuz Zaman, Istvan Toth

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in immunology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
2.9field-weighted citation impact, top 9% 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

37 citing papers in PubMed, 87 citations in OpenAlex.

  1. Article
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  9. Review
  10. Stereoisomeric PamRSC medicinal chemistry · 2022
    Article
  11. Article
  12. Current Prospects in Peptide-Based Subunit Nanovaccines.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
  13. Article
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  15. 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

2 authors at 1 institution in 1 country.

Mehfuz ZamanSchool of Chemistry and Molecular Biosciences, The University of Queensland , St Lucia, QLD , Australia.
Istvan Toth
University of Queensland · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Peptide-based vaccines offer several advantages over conventional whole organism or protein approaches by offering improved purity and specificity in inducing immune response. However, peptides alone are generally non-immunogenic. Concerns remain about the toxicity of adjuvants which are critical for immunogenicity of synthetic peptides. The use of lipopeptides in peptide vaccines is currently under intensive investigation because potent immune responses can be generated without the use of adjuvant (thus are self-adjuvanting). Several lipopeptides derived from microbial origin, and their synthetic versions or simpler fatty acid moieties impart this self-adjuvanting activity by signaling via Toll-like receptor 2 (TLR2). Engagement of this innate immune receptor on antigen-presenting cell leads to the initiation and development of potent immune responses. Therefore optimization of lipopeptides to enhance TLR2-mediated activation is a promising strategy for vaccine development. Considerable structure-activity relationships that determine TLR2 binding and consequent stimulation of innate immune responses have been investigated for a range of lipopeptides. In this mini review we address the development of lipopeptide vaccines, mechanism of TLR2 recognition, and immune activation. An overview is provided of the best studied lipopeptide vaccine systems.

Indexed as

lipopeptidepeptideself-adjuvantingtoll-like receptorvaccine

Identifiers

PMID24130558
PMCPMC3793171
OpenAlexW1980775088

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.