Evidence map›Paper›PMID 33191675›Full record

ReviewAllergy, asthma & immunology research2021

Bioengineering of Virus-like Particles for the Prevention or Treatment of Allergic Diseases.

Phornsiri Pechsrichuang, Supannika Namwongnao, Alain Jacquet

Abstract readReview
In one paragraph

Review in Allergy, asthma & immunology research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. Review
  3. Next-Generation Allergen-Specific Immunotherapy for Food Allergy.Clinical reviews in allergy & immunology · 2025
    Review
  4. Review
  5. Review
  6. Review
  7. Review
  8. Article
  9. Review
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.

Phornsiri PechsrichuangCenter of Excellence in Vaccine Research and Development, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
Supannika NamwongnaoCenter of Excellence in Vaccine Research and Development, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
Alain JacquetCenter of Excellence in Vaccine Research and Development, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand. alain.j@chula.ac.th.ORCID https://orcid.org/0000-0002-0980-9741

Funding

Chulalongkorn Academic AdvancementCSP VA RA61/123
6 · The paper itself

Abstract

Recent findings on the mechanism of allergen-specific immunotherapy (AIT) have revisited the role of immunoglobulin G (IgG) as the development of specific blocking IgG antibodies appeared critical for the successful suppression of T-helper 2 (Th2)-biased allergic responses. Consequently, any form of molecular AIT-promoting potent allergen-specific neutralizing antibodies would be preferred to conventional administration of allergen extracts. The potent immunogenicity of virus-like particles (VLPs) could be harnessed for that purpose. The particle size (20-200 nm) optimizes uptake by antigen-presenting cells as well as lymphatic trafficking. Moreover, the display of antigens in repetitive arrays promotes potent B cell activation for the development of sustained antibody responses. The presentation of self-antigens on the particle surface was even capable to break B cell tolerance. In this review, we describe the immunomodulatory properties of the 3 VLP-based strategies designed so far for the treatment of allergic disease: VLP packaged with CpG motifs as well as chimeric particles displaying pro-Th2/Th2 cytokines or allergens (full-length or B cell epitopes).

Indexed as

allergenautoantibodiesblocking antibodiesCpG motifNanoparticles

Identifiers

PMID33191675
PMCPMC7680827

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.