Evidence map›Paper›PMID 41350775›Full record

ArticleEMBO molecular medicine2026

Systematic evaluation of blood contamination in nanoparticle-based plasma proteomics.

Huanhuan Gao, Yuecheng Zhan, Yuanqi Liu, Zhiyi Zhu, Yuxiu Zheng, Liqin Qian, Zhangzhi Xue, Honghan Cheng, Zongxiang Nie, Weigang Ge and 11 more

Abstract read
In one paragraph

Article in EMBO molecular medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors.

Huanhuan Gao *Westlake Center for Intelligent Proteomics, State Key Laboratory of Medical Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China.
Yuecheng Zhan *Westlake Omics (Hangzhou) Biotechnology Co., Ltd., Hangzhou, China.
Yuanqi Liu *The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Zhiyi ZhuWestlake Omics (Hangzhou) Biotechnology Co., Ltd., Hangzhou, China.
Yuxiu ZhengWestlake Omics (Hangzhou) Biotechnology Co., Ltd., Hangzhou, China.
Liqin QianWestlake Center for Intelligent Proteomics, State Key Laboratory of Medical Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China.
Zhangzhi XueWestlake Center for Intelligent Proteomics, State Key Laboratory of Medical Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China.
Honghan ChengWestlake Center for Intelligent Proteomics, State Key Laboratory of Medical Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China.
Zongxiang NieWestlake Center for Intelligent Proteomics, State Key Laboratory of Medical Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China.
Weigang GeWestlake Omics (Hangzhou) Biotechnology Co., Ltd., Hangzhou, China.ORCID 0000-0002-1803-4327
Senlin RuanDepartment of Clinical Laboratory, Affiliated Hangzhou First People's Hospital, Hangzhou, Zhejiang Province, China.
Jiaxu LiuState Key Laboratory of Fine Chemicals, Frontier Science Center for Smart Materials, School of Chemical Engineering, Dalian University of Technology, Dalian, China.
Jikai ZhangState Key Laboratory of Fine Chemicals, Frontier Science Center for Smart Materials, School of Chemical Engineering, Dalian University of Technology, Dalian, China.
Yingying SunWestlake Center for Intelligent Proteomics, State Key Laboratory of Medical Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China.
Lei ZhouWestlake Center for Intelligent Proteomics, State Key Laboratory of Medical Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China.
Dongyue XunCollege of Chemistry, Nankai University, Tianjin, China.
Yingrui WangWestlake Center for Intelligent Proteomics, State Key Laboratory of Medical Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China.ORCID 0000-0001-5532-3454
Heyun XuThe First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China. xuheyun@zju.edu.cn.
Huiwen MiaoThe First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China. randy_m@zju.edu.cn.ORCID 0000-0001-6329-9511
Yi ZhuWestlake Center for Intelligent Proteomics, State Key Laboratory of Medical Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China. zhuyi@westlake.edu.cn.ORCID 0000-0003-0429-0802
Tiannan GuoWestlake Center for Intelligent Proteomics, State Key Laboratory of Medical Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China. guotiannan@westlake.edu.cn.ORCID 0000-0003-3869-7651

Funding

National Key R&D Program of China 2022YFF0608403National Natural Science Foundation of China 82303849Noncommunicable Chronic Diseases-National Science and Technology Major Project 2024ZD0533300Pioneer and Leading Goose R&D Program of Zhejiang 2023C03056,2024SSYS0035
6 · The paper itself

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 samples. Through controlled contamination experiments, we identified biomarkers for platelet/erythrocyte/coagulation-related contamination in nanoparticle-based plasma proteomics. We developed open-access software Baize for contamination assessment. We validated the pipeline in 193 patients with CT-indistinct benign nodules or early-stage lung cancers, flagging five contaminated samples. This study reveals that contamination alters protein identification/quantification in nanoparticle-based plasma proteomics and presents Baize software to evaluate it.

Indexed as

Blood ProteinsNanoparticlesPlasmaProteomeProteomicsBiomarkersHumansProtein CoronaSilicon DioxideBiomarkersBlood ProteinsProtein CoronaProteomeSilicon DioxideBlood ProteomicsMass SpectrometryNanoparticlePlatelet/Erythrocyte ContaminationProtein Corona

Identifiers

PMID41350775
PMCPMC12808129

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.