<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>43(12)</volume><submitter>Luo J</submitter><pubmed_abstract>Efficient and accurate nanocarrier development for targeted drug delivery is hindered by a lack of methods to analyze its cell-level biodistribution across whole organisms. Here we present Single Cell Precision Nanocarrier Identification (SCP-Nano), an integrated experimental and deep learning pipeline to comprehensively quantify the targeting of nanocarriers throughout the whole mouse body at single-cell resolution. SCP-Nano reveals the tissue distribution patterns of lipid nanoparticles (LNPs) after different injection routes at doses as low as 0.0005 mg kg&lt;sup>-1&lt;/sup>-far below the detection limits of conventional whole body imaging techniques. We demonstrate that intramuscularly injected LNPs carrying SARS-CoV-2 spike mRNA reach heart tissue, leading to proteome changes, suggesting im</pubmed_abstract><journal>Nature biotechnology</journal><pagination>2009-2022</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12700832</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Nanocarrier imaging at single-cell resolution across entire mouse bodies with deep learning.</pubmed_title><pmcid>PMC12700832</pmcid><pubmed_authors>Todorov MI</pubmed_authors><pubmed_authors>Kadletz K</pubmed_authors><pubmed_authors>Bruns OT</pubmed_authors><pubmed_authors>Hoeher L</pubmed_authors><pubmed_authors>Al-Maskari R</pubmed_authors><pubmed_authors>Calandra GM</pubmed_authors><pubmed_authors>Su J</pubmed_authors><pubmed_authors>Galensowske N</pubmed_authors><pubmed_authors>Jeridi D</pubmed_authors><pubmed_authors>Negwer M</pubmed_authors><pubmed_authors>Singh I</pubmed_authors><pubmed_authors>Zhao S</pubmed_authors><pubmed_authors>Minde DP</pubmed_authors><pubmed_authors>Dietz H</pubmed_authors><pubmed_authors>Groschup B</pubmed_authors><pubmed_authors>Kimna C</pubmed_authors><pubmed_authors>Simats A</pubmed_authors><pubmed_authors>Ohn TL</pubmed_authors><pubmed_authors>Chen Y</pubmed_authors><pubmed_authors>Bhatia HS</pubmed_authors><pubmed_authors>Singh V</pubmed_authors><pubmed_authors>Khalin I</pubmed_authors><pubmed_authors>Paetzold J</pubmed_authors><pubmed_authors>Protzer U</pubmed_authors><pubmed_authors>Horvath I</pubmed_authors><pubmed_authors>Erturk A</pubmed_authors><pubmed_authors>Ussar S</pubmed_authors><pubmed_authors>Plesnila N</pubmed_authors><pubmed_authors>Ali M</pubmed_authors><pubmed_authors>Rong Z</pubmed_authors><pubmed_authors>Molbay M</pubmed_authors><pubmed_authors>Elsner M</pubmed_authors><pubmed_authors>Arus BA</pubmed_authors><pubmed_authors>Luo J</pubmed_authors><pubmed_authors>Pan C</pubmed_authors><pubmed_authors>Kick B</pubmed_authors><pubmed_authors>Hellal F</pubmed_authors><pubmed_authors>Roth S</pubmed_authors><pubmed_authors>Liesz A</pubmed_authors><pubmed_authors>Zeidler R</pubmed_authors></additional><is_claimable>false</is_claimable><name>Nanocarrier imaging at single-cell resolution across entire mouse bodies with deep learning.</name><description>Efficient and accurate nanocarrier development for targeted drug delivery is hindered by a lack of methods to analyze its cell-level biodistribution across whole organisms. Here we present Single Cell Precision Nanocarrier Identification (SCP-Nano), an integrated experimental and deep learning pipeline to comprehensively quantify the targeting of nanocarriers throughout the whole mouse body at single-cell resolution. SCP-Nano reveals the tissue distribution patterns of lipid nanoparticles (LNPs) after different injection routes at doses as low as 0.0005 mg kg&lt;sup>-1&lt;/sup>-far below the detection limits of conventional whole body imaging techniques. We demonstrate that intramuscularly injected LNPs carrying SARS-CoV-2 spike mRNA reach heart tissue, leading to proteome changes, suggesting im</description><dates><release>2025-01-01T00:00:00Z</release><publication>2025 Dec</publication><modification>2026-06-06T02:07:02.755Z</modification><creation>2026-05-24T03:12:21.266Z</creation></dates><accession>S-EPMC12700832</accession><cross_references><pubmed>39809933</pubmed><doi>10.1038/s41587-024-02528-1</doi></cross_references></HashMap>