<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Gao H</submitter><funding>Pioneer and Leading Goose R&amp;D Program of Zhejiang</funding><funding>National Key R&amp;D Program of China</funding><funding>Noncommunicable Chronic Diseases-National Science and Technology Major Project</funding><funding>National Natural Science Foundation of China</funding><pagination>275-296</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12808129</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>18(1)</volume><pubmed_abstract>Circulating blood proteomics enables minimally invasive biomarker discovery. Nanoparticle-based circulating plasma proteomics studies have reported varying number of proteins (ca 2000-7000), but it remains unclear whether a higher protein number is more informative. Here, we first develop OmniProt-a silica-nanoparticle workflow optimized through a systematic evaluation of nanoparticle types and protein corona formation parameters. Next, we present an Astral spectral library for 10,109 protein groups. Using the Astral with 60 sample-per-day throughput, OmniProt identifies ca 3000 to 6000 protein groups from human plasma. Platelet/erythrocyte/coagulation-related contamination artificially inflates protein identifications and compromises quantification accuracy in nanoparticle-enriched sample</pubmed_abstract><journal>EMBO molecular medicine</journal><pubmed_title>Systematic evaluation of blood contamination in nanoparticle-based plasma proteomics.</pubmed_title><pmcid>PMC12808129</pmcid><funding_grant_id>2023C03056,2024SSYS0035</funding_grant_id><funding_grant_id>2024ZD0533300</funding_grant_id><funding_grant_id>82303849</funding_grant_id><funding_grant_id>2022YFF0608403</funding_grant_id><pubmed_authors>Zhou L</pubmed_authors><pubmed_authors>Zheng Y</pubmed_authors><pubmed_authors>Liu J</pubmed_authors><pubmed_authors>Zhu Z</pubmed_authors><pubmed_authors>Zhang J</pubmed_authors><pubmed_authors>Zhu Y</pubmed_authors><pubmed_authors>Ruan S</pubmed_authors><pubmed_authors>Miao H</pubmed_authors><pubmed_authors>Guo T</pubmed_authors><pubmed_authors>Gao H</pubmed_authors><pubmed_authors>Xue Z</pubmed_authors><pubmed_authors>Xu H</pubmed_authors><pubmed_authors>Sun Y</pubmed_authors><pubmed_authors>Zhan Y</pubmed_authors><pubmed_authors>Liu Y</pubmed_authors><pubmed_authors>Ge W</pubmed_authors><pubmed_authors>Nie Z</pubmed_authors><pubmed_authors>Xun D</pubmed_authors><pubmed_authors>Qian L</pubmed_authors><pubmed_authors>Wang Y</pubmed_authors><pubmed_authors>Cheng H</pubmed_authors></additional><is_claimable>false</is_claimable><name>Systematic evaluation of blood contamination in nanoparticle-based plasma proteomics.</name><description>Circulating blood proteomics enables minimally invasive biomarker discovery. Nanoparticle-based circulating plasma proteomics studies have reported varying number of proteins (ca 2000-7000), but it remains unclear whether a higher protein number is more informative. Here, we first develop OmniProt-a silica-nanoparticle workflow optimized through a systematic evaluation of nanoparticle types and protein corona formation parameters. Next, we present an Astral spectral library for 10,109 protein groups. Using the Astral with 60 sample-per-day throughput, OmniProt identifies ca 3000 to 6000 protein groups from human plasma. Platelet/erythrocyte/coagulation-related contamination artificially inflates protein identifications and compromises quantification accuracy in nanoparticle-enriched sample</description><dates><release>2026-01-01T00:00:00Z</release><publication>2026 Jan</publication><modification>2026-06-06T15:39:55.298Z</modification><creation>2026-06-02T03:09:09.482Z</creation></dates><accession>S-EPMC12808129</accession><cross_references><pubmed>41350775</pubmed><doi>10.1038/s44321-025-00346-9</doi></cross_references></HashMap>