The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Nanoparticles Containing Oxidized Cholesterol Deliver mRNA to the Liver Microenvironment at Clinically Relevant Doses
Open accessAbstract
Using mRNA to produce therapeutic proteins is a promising approach to treat genetic diseases. However, systemically delivering mRNA to cell types besides hepatocytes remains challenging. Fast identification of nanoparticle delivery (FIND) is a DNA barcode‐based system designed to measure how over 100 lipid nanoparticles (LNPs) deliver mRNA that functions in the cytoplasm of target cells in a single mouse. By using FIND to quantify how 75 chemically distinct LNPs delivered mRNA to 28 cell types in vivo, it is found that an LNP formulated with oxidized cholesterol and no targeting ligand delivers Cre mRNA, which edits DNA in hepatic endothelial cells and Kupffer cells at 0.05 mg kg−1. Notably, the LNP targets liver microenvironmental cells fivefold more potently than hepatocytes. The structure of the oxidized cholesterols added to the LNP is systematically varied to show that the position of the oxidative modification may be important; cholesterols modified on the hydrocarbon tail associated with sterol ring D tend to outperform cholesterols modified on sterol ring B. These data suggest that LNPs formulated with modified cholesterols can deliver gene‐editing mRNA to the liver microenvironment at clinically relevant doses.
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“For example, barcoding has been applied to study how the structure of cholesterol derivatives impact cell selectivity of lipid nanoparticles, revealing that selective accumulation in liver endothelial cells, Kupffer cells and hepatocytes125,126 depends on cholesterol structures.”
From Lipid nanoparticles for mRNA delivery (2021) · cites this paper as [126]
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
Apolipoprotein E: Cholesterol Transport Protein with Expanding Role in Cell Biology
Mahley, R. W. (1988) · Science · doi:10.1126/science.3283935 · Cited by 4,028
Gilleron, 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
Cellular cholesterol trafficking and compartmentalization
Ikonen, E. (2008) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2336 · Cited by 1,506
Liver sinusoidal endothelial cells: Physiology and role in liver diseases
Poisson, J., Lemoinne, S., Boulanger, C., Durand, F., Moreau, R., Valla, D., & Rautou, P.-E. (2017) · Journal of Hepatology · doi:10.1016/j.jhep.2016.07.009 · Cited by 1,047
Mechanism of hard-nanomaterial clearance by the liver
Tsoi, K. M., MacParland, S. A., Ma, X., Spetzler, V. N., Echeverri, J. A., Ouyang, B., Fadel, S. M., Sykes, E. A., Goldaracena, N., Kaths, J. M., et al. (2016) · Nature Materials · doi:10.1038/nmat4718 · Cited by 1,035
Tools for translation: non-viral materials for therapeutic mRNA delivery
Hajj, K. A., & Whitehead, K. A. (2017) · Nature Reviews Materials · doi:10.1038/natrevmats.2017.56 · Cited by 799
Miller, J. B., Zhang, S., Kos, P., Xiong, H., Zhou, K., Perelman, S. S., Zhu, H., & Siegwart, D. J. (2017) · Angewandte Chemie International Edition · doi:10.1002/anie.201610209 · Cited by 540
Mui, B. L., Tam, Y. K., Jayaraman, M., Ansell, S. M., Du, X., Tam, Y. Y. C., Lin, P. J. C., Chen, S., Narayanannair, J. K., Rajeev, K. G., et al. (2013) · Molecular Therapy — Nucleic Acids · doi:10.1038/mtna.2013.66 · Cited by 509
Role of Kupffer cells in the pathogenesis of liver disease
Kolios, G. (2006) · World Journal of Gastroenterology · doi:10.3748/wjg.v12.i46.7413 · Cited by 505
Lipopeptide nanoparticles for potent and selective siRNA delivery in rodents and nonhuman primates
Dong, Y., Love, K. T., Dorkin, J. R., Sirirungruang, S., Zhang, Y., Chen, D., Bogorad, R. L., Yin, H., Chen, Y., Vegas, A. J., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1322937111 · Cited by 488
Flagged first, then by citations
Cited by
Sorted by citations
Items 201–205 of 205
Current Advances in Liver-Targeted Drug Delivery: Synthetic, Biological, and Biomimetic Platforms
Sergazy, S. D., Сейдахметова, Р. Б., Zakirov, Y., Zhilkaidarov, A., Amirbek, D., Shulgau, Z., Berikkhanova, K., & GULYAEV, A. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27177959
“Other lipid compositions can shift delivery toward distinct cellular populations within the liver microenvironment [25].”
Petrova, E., Georgiev, I., Stoyanov, N., & Kolev, P. (2026) · Journal of Applied Pharmaceutical Technologies and Systems · doi:10.68159/a787099787
Beyond Precision: A Multidimensional Framework for Selecting Genetic Medicine Platforms
Wieland, J., Jackson, P., Penrod, W., Nadauld, S., & Barrott, J. J. (2026) · Cells · doi:10.3390/cells15181647
“The liver is currently the best-established target for systemic LNP-mediated nucleic-acid delivery [5–9, 74,79].”
Nano Delivery Systems for In Vivo CRISPR/Cas-Based Gene Therapy: From Vectors to Clinical Outcomes
Chen, R., Zhou, H., Wu, Q., & Gong, C. (2026) · ACS Nano · doi:10.1021/acsnano.6c12154
Emerging Lipid Nanoparticle Targeting Strategies for Extrahepatic Delivery of RNA Therapeutics
Li, J., Liu, J., Wang, N., Zhang, K., Zhang, W., Gao, M., Lu, Z., Chen, X. S., & Li, Y. (2026) · Advanced Materials · doi:10.1002/adma.75408 · Cited by 1
Metadata
- Authors
- Paunovska, K., Da Silva Sanchez, A. J., Sago, C. D., Gan, Z., Lokugamage, M. P., Islam, F. Z., Kalathoor, S., Krupczak, B. R., & Dahlman, J. E.
- Affiliations
- Georgia Institute of Technology (US)
- Wallace H. Coulter Department of Biomedical Engineering Georgia Institute of Technology and Emory School of Medicine Atlanta GA 30332 USA
- Corresponding author
- Dahlman, James E.
- ORCID
- Venue
- Advanced Materials
- Publisher
- Wiley
- Published
- 2019-02-12
- Volume
- 31
- Issue
- 14
- Pages
- e1807748-e1807748
- ISSN
- 0935-9648 (ISSN-L)
- 1521-4095
- PMC
- PMC6445717
- OpenAlex
- W2913721132
- Cited by
- 205
- References
- 26
- Citations by year
- 2026: 21 · 2025: 31 · 2024: 40 · 2023: 40 · 2022: 34 · 2021: 15 · 2020: 19 · 2019: 4
- FWCI
- 5.95
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Advanced Materials (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of General Medical Sciences (T32GM008433, T32GM105490)
- National Institute of Biomedical Imaging and Bioengineering (T32EB021962)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Interference and Gene Delivery
- Physical Sciences › Materials Science › Biomaterials › Nanoparticle-Based Drug Delivery
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmaceutical Science › Advanced Drug Delivery Systems
- Keywords
- lipid nanoparticles, oxysterols, mRNA delivery, liver microenvironment, genome editing, hepatic endothelial cells, Kupffer cells, nanoparticle targeting, in vivo delivery
- MeSH terms
- Animals, Cholesterol, Drug Carriers, Liver, Oxidation-Reduction, RNA, Messenger, Mice, Nanoparticles, Cellular Microenvironment
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
