Evidence map›Paper›PMID 21156190›Full record

ReviewAdvanced drug delivery reviews

RNA interference for improving the outcome of islet transplantation.

Feng Li, Ram I Mahato

Abstract readReview
In one paragraph

Review in Advanced drug delivery reviews. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
1.2field-weighted citation impact, top 22% 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

19 citing papers in PubMed, 33 citations in OpenAlex.

  1. Article
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  3. Nanomedicine in the Treatment of Diabetes.International journal of molecular sciences · 2024
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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

2 authors at 1 institution in 1 country.

Feng LiDepartment of Pharmaceutical Sciences, University of Tennessee Health Science Center, Memphis, TN 38103, USA.
Ram I Mahato
University of Tennessee Health Science Center · US

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 DK069968NIDDK NIH HHS R01 DK69968
6 · The paper itself

Abstract

Islet transplantation has the potential to cure type 1 diabetes. Despite recent therapeutic success, it is still not common because a large number of transplanted islets get damaged by multiple challenges including instant blood mediated inflammatory reaction, hypoxia/reperfusion injury, inflammatory cytokines, and immune rejection. RNA interference (RNAi) is a novel strategy to selectively degrade target mRNA. The use of RNAi technologies to downregulate the expression of harmful genes has the potential to improve the outcome of islet transplantation. The aim of this review is to gain a thorough understanding of biological obstacles to islet transplantation and discuss how to overcome these barriers using different RNAi technologies. This eventually will help improve islet survival and function post transplantation. Chemically synthesized small interferring RNA (siRNA), vector based short hairpin RNA (shRNA), and their critical design elements (such as sequences, promoters, and backbone) are discussed. The application of combinatorial RNAi in islet transplantation is also discussed. Last but not the least, several delivery strategies for enhanced gene silencing are discussed, including chemical modification of siRNA, complex formation, bioconjugation, and viral vectors.

Indexed as

RNA InterferenceAnimalsDrug Delivery SystemsGenetic TherapyHumansIslets of Langerhans TransplantationRNA, Small InterferingTreatment OutcomeRNA, Small Interfering

Identifiers

PMID21156190
PMCPMC3065652
OpenAlexW2052726090

What OpenQuestion holds

Textmetadata
LicenceTDM
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.