Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 219

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

A Novel Mechanism Is Involved in Cationic Lipid-Mediated Functional siRNA Delivery

Open access
Lu, James J., Langer, Robert, Chen, Jianzhu·2009·Molecular Pharmaceutics

Abstract

A key challenge for therapeutic application of RNA interference is to efficiently deliver synthetic small interfering RNAs (siRNAs) into target cells that will lead to the knockdown of the target transcript (functional siRNA delivery). To facilitate rational development of nonviral carriers, we have investigated by imaging, pharmacological and genetic approaches the mechanisms by which a cationic lipid carrier mediates siRNA delivery into mammalian cells. We show that approximately 95% of siRNA lipoplexes enter the cells through endocytosis and persist in endolysosomes for a prolonged period of time. However, inhibition of clathrin-, caveolin-, or lipid-raft-mediated endocytosis or macropinocytosis fails to inhibit the knockdown of the target transcript. In contrast, depletion of cholesterol from the plasma membrane has little effect on the cellular uptake of siRNA lipoplexes, but it abolishes the target transcript knockdown. Furthermore, functional siRNA delivery occurs within a few hours and is gradually inhibited by lowering temperatures. These results demonstrate that although endocytosis is responsible for the majority of cellular uptake of siRNA lipoplexes, a minor pathway, probably mediated by fusion between siRNA lipoplexes and the plasma membrane, is responsible for the functional siRNA delivery. Our findings suggest possible directions for improving functional siRNA delivery by cationic lipids.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/mp900023v

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 3 references

Cited by

Metadata

Authors
Lu, J. J., Langer, R., & Chen, J.
Venue
Molecular Pharmaceutics
Published
2009-03-30
Volume
6
Issue
3
Pages
763-771
ISSN
  • 1543-8384 (ISSN-L)
  • 1543-8392
OpenAlex
W2097202791
Cited by
219
References
3
FWCI
6.36
Type
journal article
Language
en
Open access
hybrid

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.