Evidence map›Paper›PMID 29439476›Full record

ReviewVaccines2018

Virus-Like-Vaccines against HIV.

Anne-Marie C Andersson, Melanie Schwerdtfeger, Peter J Holst

Abstract readReview
In one paragraph

Review in Vaccines, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Article
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  7. Article
  8. Article
  9. Review
  10. Article
  11. Review
  12. 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.

Anne-Marie C Andersson
Melanie SchwerdtfegerDepartment of Immunology and Microbiology (ISIM), Faculty of Health Sciences, University of Copenhagen, The Panum Institute Building 7-13-16, Blegdamsvej 3B, DK2200 Copenhagen, Denmark. melanies@sund.ku.dk.
Peter J HolstDepartment of Immunology and Microbiology (ISIM), Faculty of Health Sciences, University of Copenhagen, The Panum Institute Building 7-13-16, Blegdamsvej 3B, DK2200 Copenhagen, Denmark. pholst@sund.ku.dk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protection against chronic infections has necessitated the development of ever-more potent vaccination tools. HIV seems to be the most challenging foe, with a remarkable, poorly immunogenic and fragile surface glycoprotein and the ability to overpower the cell immune system. Virus-like-particle (VLP) vaccines have emerged as potent inducers of antibody and helper T cell responses, while replication-deficient viral vectors have yielded potent cytotoxic T cell responses. Here, we review the emerging concept of merging these two technologies into virus-like-vaccines (VLVs) for the targeting of HIV. Such vaccines are immunologically perceived as viruses, as they infect cells and produce VLPs in situ, but they only resemble viruses, as the replication defective vectors and VLPs cannot propagate an infection. The inherent safety of such a platform, despite robust particle production, is a distinct advantage over live-attenuated vaccines that must balance safety and immunogenicity. Previous studies have delivered VLVs encoded in modified Vaccinia Ankara vectors and we have developed the concept into a single-reading adenovirus-based technology capable of eliciting robust CD8⁺ and CD4⁺ T cells responses and trimer binding antibody responses. Such vaccines offer the potential to display the naturally produced immunogen directly and induce an integrated humoral and cellular immune response.

Indexed as

antibodiesHIVT cellsvirus-like-particlesvirus-like-vaccinesvirus vectors

Identifiers

PMID29439476
PMCPMC5874651

What OpenQuestion holds

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LicenceCC BY
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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.