Evidence map›Paper›PMID 28216554›Full record

ReviewVaccines2017

Harnessing Nanoparticles for Immunomodulation and Vaccines.

Ariane C Gomes, Mona Mohsen, Martin F Bachmann

Abstract readReview
In one paragraph

Review in Vaccines, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
80citing papers in PubMed, 1 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

80 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Vaccines for the common cold.The Cochrane database of systematic reviews · 2022
    Pooled it
  2. Trial
  3. Article
  4. Review
  5. Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. Hantavirus GnACS infectious diseases · 2025
    Article
  11. Article
  12. Article
  13. Article
  14. Nanoimmunotherapy: the smart trooper for cancer therapy.Exploration of targeted anti-tumor therapy · 2025
    Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

20 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

3 authors.

Ariane C GomesThe Jenner Institute, Oxford University, Old Road Campus Research Building, Roosevelt Drive, Oxford OX3 7DQ, UK. ariane.cruzgomes@ndm.ox.ac.uk.
Mona MohsenThe Jenner Institute, Oxford University, Old Road Campus Research Building, Roosevelt Drive, Oxford OX3 7DQ, UK. mona.mohsen@kellogg.ox.ac.uk.
Martin F BachmannThe Jenner Institute, Oxford University, Old Road Campus Research Building, Roosevelt Drive, Oxford OX3 7DQ, UK. martin.bachmann@ndm.ox.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The first successful use of nanoparticles (NPs) for vaccination was reported almost 40 years ago with a virus-like particle-based vaccine against Hepatitis B. Since then, the term NP has been expanded to accommodate a large number of novel nano-sized particles engineered from a range of materials. The great interest in NPs is likely not only a result of the two successful vaccines against hepatitis B and Human Papilloma Virus (HPV) that use this technology, but also due to the versatility of those small-sized particles, as indicated by the wide range of applications reported so far, ranging from medicinal and cosmetics to purely technical applications. In this review, we will focus on the use of NPs, especially virus-like particles (VLPs), in the field of vaccines and will discuss their employment as vaccines, antigen display platforms, adjuvants and drug delivery systems.

Indexed as

immunogennanoparticlesvaccinesvirus-like particles

Identifiers

PMID28216554
PMCPMC5371742

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.