Evidence map›Paper›PMID 22551453›Full record

ArticleVirology journal2012

HIV taken by STORM: super-resolution fluorescence microscopy of a viral infection.

Cândida F Pereira, Jérémie Rossy, Dylan M Owen, Johnson Mak, Katharina Gaus

Open access · goldAbstract read
In one paragraph

Article in Virology journal, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
4.5field-weighted citation impact, top 5% 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

28 citing papers in PubMed, 49 citations in OpenAlex.

  1. Review
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  3. Article
  4. Virus morphology: Insights from super-resolution fluorescence microscopy.Biochimica et biophysica acta. Molecular basis of disease · 2022
    Review
  5. Review
  6. Review
  7. Review
  8. Article
  9. Single-particle virology.Biophysical reviews · 2020
    Review
  10. Review
  11. Article
  12. Review
  13. Review
  14. Review
  15. Article
  16. Article
  17. Superresolution imaging of viral protein trafficking.Medical microbiology and immunology · 2015
    Review
  18. Article
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  20. Article
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

5 authors at 3 institutions in 1 country.

Cândida F PereiraCentre for Virology, Burnet Institute, Melbourne, Australia.
Jérémie Rossy
Dylan M Owen
Johnson Mak
Katharina Gaus
UNSW Sydney · AUBurnet Institute · AUDeakin University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe visualization of viral proteins has been hindered by the resolution limit of conventional fluorescent microscopes, as the dimension of any single fluorescent signal is often greater than most virion particles. Super-resolution microscopy has the potential to unveil the distribution of proteins at the resolution approaching electron microscopy without relying on morphological features of existing characteristics of the biological specimen that are needed in EM.

resultsUsing direct stochastic optical reconstruction microscopy (dSTORM) to achieve a lateral resolution of 15-20 nm, we quantified the 2-D molecular distribution of the major structural proteins of the infectious human immunodeficiency virus type 1 (HIV-1) before and after infection of lymphoid cells. We determined that the HIV-1 matrix and capsid proteins undergo restructuring soon after HIV-1 infection.

conclusionsThis study provides the proof-of-concept for the use of dSTORM to visualize the changes in the molecular distribution of viral proteins during an infection.

Indexed as

HIV-1HIV InfectionsHumansLymphocytesMicroscopy, FluorescenceViral ProteinsViral Proteins

Identifiers

PMID22551453
PMCPMC3409066
OpenAlexW2119497297

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.