The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Influence of Cationic Lipid Composition on Gene Silencing Properties of Lipid Nanoparticle Formulations of siRNA in Antigen-Presenting Cells
Open accessAbstract
Lipid nanoparticles (LNPs) are currently the most effective in vivo delivery systems for silencing target genes in hepatocytes employing small interfering RNA. Antigen-presenting cells (APCs) are also potential targets for LNP siRNA. We examined the uptake, intracellular trafficking, and gene silencing potency in primary bone marrow macrophages (bmMΦ) and dendritic cells of siRNA formulated in LNPs containing four different ionizable cationic lipids namely DLinDAP, DLinDMA, DLinK-DMA, and DLinKC2-DMA. LNPs containing DLinKC2-DMA were the most potent formulations as determined by their ability to inhibit the production of GAPDH target protein. Also, LNPs containing DLinKC2-DMA were the most potent intracellular delivery agents as indicated by confocal studies of endosomal versus cytoplamic siRNA location using fluorescently labeled siRNA. DLinK-DMA and DLinKC2-DMA formulations exhibited improved gene silencing potencies relative to DLinDMA but were less toxic. In vivo results showed that LNP siRNA systems containing DLinKC2-DMA are effective agents for silencing GAPDH in APCs in the spleen and peritoneal cavity following systemic administration. Gene silencing in APCs was RNAi mediated and the use of larger LNPs resulted in substantially reduced hepatocyte silencing, while similar efficacy was maintained in APCs. These results are discussed with regard to the potential of LNP siRNA formulations to treat immunologically mediated diseases.
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.
Integrity signals
Registry
Cites
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.
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
Knocking down barriers: advances in siRNA delivery
Whitehead, K. A., Langer, R., & Anderson, D. G. (2009) · Nature Reviews Drug Discovery · doi:10.1038/nrd2742 · Cited by 3,115
Rational design of cationic lipids for siRNA delivery
Semple, S. C., Akinc, A., Chen, J., Sandhu, A. P., Mui, B. L., Cho, C. K., Sah, D. W. Y., Stebbing, D., Crosley, E. J., Yaworski, E., et al. (2010) · Nature Biotechnology · doi:10.1038/nbt.1602 · Cited by 1,822
Self-citationRNAi-mediated gene silencing in non-human primates
Zimmermann, T. S., Lee, A. C. H., Akinc, A., Bramlage, B., Bumcrot, D., Fedoruk, M. N., Harborth, J., Heyes, J. A., Jeffs, L. B., John, M., et al. (2006) · Nature · doi:10.1038/nature04688 · Cited by 1,357
Targeted delivery of RNAi therapeutics with endogenous and exogenous ligand-based mechanisms
Akinc, A., Querbes, W., De, S., Qin, J., Frank-Kamenetsky, M., Jayaprakash, K. N., Jayaraman, M., Rajeev, K. G., Cantley, W. L., Dorkin, J. R., et al. (2010) · Molecular Therapy · doi:10.1038/mt.2010.85 · Cited by 1,261
Semple, S. C., Klimuk, S. K., Harasym, T. O., Dos Santos, N., Ansell, S. M., Wong, K. F., Maurer, N., Stark, H., Cullis, P. R., Hope, M. J., et al. (2001) · Biochimica et Biophysica Acta (BBA) - Biomembranes · doi:10.1016/s0005-2736(00)00343-6 · Cited by 454
Self-citation
Cited by
Liposomal drug delivery systems: From concept to clinical applications
Allen, T. M., & Cullis, P. R. (2013) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2012.09.037 · Cited by 4,839
Self-citationGilleron, J., Querbes, W., Zeigerer, A., Borodovsky, A., Marsico, G., Schubert, U., Manygoats, K., Seifert, S., Andree, C., Stöter, M., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2612 · Cited by 1,681
Self-citationZuris, J. A., Thompson, D. B., Shu, Y., Guilinger, J. P., Bessen, J. L., Hu, J. H., Maeder, M. L., Joung, J. K., Chen, Z.-Y., & Liu, D. R. (2015) · Nature Biotechnology · doi:10.1038/nbt.3081 · Cited by 1,460
Lipid Nanoparticle Systems for Enabling Gene Therapies
Cullis, P. R., & Hope, M. J. (2017) · Molecular Therapy · doi:10.1016/j.ymthe.2017.03.013 · Cited by 1,208
Self-citationEfficiency of siRNA delivery by lipid nanoparticles is limited by endocytic recycling
Sahay, G., Querbes, W., Alabi, C., Eltoukhy, A., Sarkar, S., Zurenko, C., Karagiannis, E., Love, K., Chen, D., Zoncu, R., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2614 · Cited by 948
Metadata
- Authors
- Basha, G., Novobrantseva, T. I., Rosin, N., Tam, Y. Y. C., Hafez, I. M., Wong, M. K., Sugo, T., Ruda, V. M., Qin, J., Klebanov, B., Ciufolini, M., Akinc, A., Tam, Y. K., Hope, M. J., & Cullis, P. R.
- Venue
- Molecular Therapy
- Publisher
- Elsevier BV
- Published
- 2011-12
- Volume
- 19
- Issue
- 12
- Pages
- 2186-2200
- ISSN
- 1525-0016 (ISSN-L)
- OpenAlex
- W2141208964
- Cited by
- 181
- References
- 5
- FWCI
- 4.23
- 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.