Evidence map›Paper›PMID 18066041›Full record

ReviewNature biotechnology2007

Genetic therapies against HIV.

John J Rossi, Carl H June, Donald B Kohn

Open access · greenAbstract readReview
In one paragraph

Review in Nature biotechnology, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 116 papers.

0numbers the graph read from it
0cells of the map it votes in
116citing papers in PubMed
10.3field-weighted citation impact, top 1% 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

116 citing papers in PubMed, 230 citations in OpenAlex.

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  20. Stem cell-based therapies for HIV/AIDS.Advanced drug delivery reviews · 2016
    Review

56 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 at 3 institutions in 1 country.

John J RossiDivision of Molecular Biology, Graduate School of Biological Sciences, Beckman Research Institute of City of Hope, Duarte, California 91010, USA. jrossi@coh.org
Carl H June
Donald B Kohn
City of Hope · USUniversity of Pennsylvania · USUniversity of Southern California · US

Funding

Lentivirus-based Immunogene Therapy for HIV InfectionU19AI066290 · NIAID · UNIVERSITY OF PENNSYLVANIA · PI JUNE, CARL H. · 2005 to 2009
$7.2M
Role of co-receptor modified cells in HIV infectionR01AI104400 · NIAID · UNIVERSITY OF PENNSYLVANIA · PI JUNE, CARL H. · 2012 to 2012
$1.3M
NIAID NIH HHS R01 AI104400NIAID NIH HHS U19 AI066290
6 · The paper itself

Abstract

Highly active antiretroviral therapy prolongs the life of HIV-infected individuals, but it requires lifelong treatment and results in cumulative toxicities and viral-escape mutants. Gene therapy offers the promise of preventing progressive HIV infection by sustained interference with viral replication in the absence of chronic chemotherapy. Gene-targeting strategies are being developed with RNA-based agents, such as ribozymes, antisense, RNA aptamers and small interfering RNA, and protein-based agents, such as the mutant HIV Rev protein M10, fusion inhibitors and zinc-finger nucleases. Recent advances in T-cell-based strategies include gene-modified HIV-resistant T cells, lentiviral gene delivery, CD8(+) T cells, T bodies and engineered T-cell receptors. HIV-resistant hematopoietic stem cells have the potential to protect all cell types susceptible to HIV infection. The emergence of viral resistance can be addressed by therapies that use combinations of genetic agents and that inhibit both viral and host targets. Many of these strategies are being tested in ongoing and planned clinical trials.

Indexed as

Drug DesignDrug Delivery SystemsGene TargetingGenetic TherapyHIV InfectionsHumansVaccines, DNAVaccines, DNA

Identifiers

PMID18066041
PMCPMC4539027
OpenAlexW2077088013

What OpenQuestion holds

Textmetadata
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.