ArticlebioRxiv : the preprint server for biology2023
Nanoprojectile Secondary Ion Mass Spectrometry Enables Multiplexed Analysis of Individual Hepatic Extracellular Vesicles.
Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
The trial behind it
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Who cites it
0 citing papers in PubMed, 1 citations in OpenAlex.
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Authors and funding
11 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Extracellular vesicles (EVs) are nanoscale lipid bilayer particles secreted by cells. EVs may carry markers of the tissue of origin and its disease state which makes them incredibly promising for disease diagnosis and surveillance. While the armamentarium of EV analysis technologies is rapidly expanding, there remains a strong need for multiparametric analysis with single EV resolution. Nanoprojectile (NP) secondary ion mass spectrometry (NP-SIMS) relies on bombarding a substrate of interest with individual gold NPs resolved in time and space. Each projectile creates an impact crater of 10-20 nm in diameter while molecules emitted from each impact are mass analyzed and recorded as individual mass spectra. We demonstrate the utility of NP-SIMS for analysis of single EVs derived from normal liver cells (hepatocytes) and liver cancer cells. EVs were captured on antibody (Ab)-functionalized gold substrate then labeled with Abs carrying lanthanide (Ln) MS tags (Ab@Ln). These tags targeted four markers selected for identifying all EVs, and specific to hepatocytes or liver cancer. NP-SIMS was used to detect Ab@Ln-tags co-localized on the same EV and to construct scatter plots of surface marker expression for thousands of EVs with the capability of categorizing individual EVs. Additionally, NP-SIMS revealed information about the chemical nano-environment where targeted moieties co-localized. Our approach allowed analysis of population heterogeneity with single EV resolution and distinguishing between hepatocyte and liver cancer EVs based on surface marker expression. NP-SIMS holds considerable promise for multiplexed analysis of single EVs and may become a valuable tool for identifying and validating EV biomarkers of cancer and other diseases.
Identifiers
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Registered trials
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