Evidence map›Paper›PMID 25421889›Full record

ReviewViruses2014

HIV eradication: combinatorial approaches to activate latent viruses.

Elisa De Crignis, Tokameh Mahmoudi

Open access · goldAbstract readReview
In one paragraph

Review in Viruses, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.7field-weighted citation impact, top 17% 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

7 citing papers in PubMed, 15 citations in OpenAlex.

  1. Trial
  2. Review
  3. Article
  4. Article
  5. Effects of HIV on metabolic and biological pathways of CD4Experimental and therapeutic medicine · 2018
    Article
  6. Article
  7. 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

2 authors at 1 institution in 1 country.

Elisa De CrignisDepartment of Biochemistry, Erasmus University Medical Center, Rotterdam 3015 CN, The Netherlands. e.decrignis@erasmusmc.nl.
Tokameh MahmoudiDepartment of Biochemistry, Erasmus University Medical Center, Rotterdam 3015 CN, The Netherlands. t.mahmoudi@erasmusmc.nl.
Erasmus MC · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The concept of eradication of the Human Immune Deficiency Virus (HIV) from infected patients has gained much attention in the last few years. While combination Anti-Retroviral Therapy (c-ART) has been extremely effective in suppressing viral replication, it is not curative. This is due to the presence of a reservoir of latent HIV infected cells, which persist in the presence of c-ART. Recently, pharmaceutical approaches have focused on the development of molecules able to induce HIV-1 replication from latently infected cells in order to render them susceptible to viral cytopathic effects and host immune responses. Alternative pathways and transcription complexes function to regulate the activity of the HIV promoter and might serve as molecular targets for compounds to activate latent HIV. A combined therapy coupling various depressors and activators will likely be the most effective in promoting HIV replication while avoiding pleiotropic effects at the cellular level. Moreover, in light of differences among HIV subtypes and variability in integration sites, the combination of multiple agents targeting multiple pathways will increase likelihood of therapeutic effectiveness and prevent mutational escape. This review provides an overview of the mechanisms that can be targeted to induce HIV activation focusing on potential combinatorial approaches.

Indexed as

Virus ReplicationDrug DiscoveryDrug Therapy, CombinationHIV-1HIV InfectionsHumansVirus Latency

Identifiers

PMID25421889
PMCPMC4246239
OpenAlexW2033670698

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.