Evidence map›Paper›PMID 18074201›Full record

ReviewPharmaceutical research2008

RNAi for treating hepatitis B viral infection.

Yong Chen, Guofeng Cheng, Ram I Mahato

Abstract readReview
In one paragraph

Review in Pharmaceutical research, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.

0numbers the graph read from it
0cells of the map it votes in
49citing 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

49 citing papers in PubMed.

  1. Article
  2. Review
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  6. Review
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  11. Article
  12. Prevention of HBV Recurrence after Liver Transplant: A Review.Journal of clinical and translational hepatology · 2020
    Review
  13. Review
  14. Article
  15. Review
  16. 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.

Yong ChenHuai-An 4th People's Hospital, Jiangsu, China.
Guofeng Cheng
Ram I Mahato

Funding

Growth Factor and Antiapoptotic Gene Delivery to Human IsletsR01DK069968 · NIDDK · UNIVERSITY OF TENNESSEE HEALTH SCI CTR · PI MAHATO, RAM I. · 2005 to 2012
$2.2M
NIDDK NIH HHS R01 DK 064633NIDDK NIH HHS R01 DK 069968NIDDK NIH HHS R01 DK069968
6 · The paper itself

Abstract

Chronic hepatitis B virus (HBV) infection is one of the leading causes of liver cirrhosis and hepatocellular carcinoma (HCC). Current treatment strategies of HBV infection including the use of interferon (IFN)-alpha and nucleotide analogues such as lamivudine and adefovir have met with only partial success. Therefore, it is necessary to develop more effective antiviral therapies that can clear HBV infection with fewer side effects. RNA interference (RNAi), by which a small interfering RNA (siRNA) induces the gene silence at a post-transcriptional level, has the potential of treating HBV infection. The successful use of chemically synthesized siRNA, endogenous expression of small hairpin RNA (shRNA) or microRNA (miRNA) to silence the target gene make this technology towards a potentially rational therapeutics for HBV infection. However, several challenges including poor siRNA stability, inefficient cellular uptake, widespread biodistribution and non-specific effects need to be overcome. In this review, we discuss several strategies for improving the anti-HBV therapeutic efficacy of siRNAs, while avoiding their off-target effects and immunostimulation. There is an in-depth discussion on the (1) mechanisms of RNAi, (2) methods for siRNA/shRNA production, (3) barriers to RNAi-based therapies, and (4) delivery strategies of siRNA for treating HBV infection.

Indexed as

AnimalsAntiviral AgentsDrug Delivery SystemsExcipientsGenetic VectorsHepatitis BHepatitis B virusHumansRNA, Small InterferingAntiviral AgentsExcipientsRNA, Small Interfering

Identifiers

PMID18074201
PMCPMC2217617

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.