Evidence map›Paper›PMID 41773075›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

An Artificial Antibody-Based Toolbox Accelerates Validation of Hidden Microproteins Encoded by the Dark Genome.

Hui He, Anqi Zhang, Zhanchen Guo, Qi Li, Song Gao, Wenyan Guan, Ying Li, Jingran Chen, Sijia Sun, Jian He and 1 more

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Hui HeState Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry, Nanjing University, Nanjing, China.
Anqi ZhangState Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry, Nanjing University, Nanjing, China.
Zhanchen GuoState Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry, Nanjing University, Nanjing, China.
Qi LiDepartment of Pathology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China.
Song GaoState Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry, Nanjing University, Nanjing, China.
Wenyan GuanDepartment of Pathology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China.
Ying LiState Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry, Nanjing University, Nanjing, China.
Jingran ChenState Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry, Nanjing University, Nanjing, China.
Sijia SunState Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry, Nanjing University, Nanjing, China.
Jian HeDepartment of Nuclear Medicine, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China.
Zhen LiuState Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry, Nanjing University, Nanjing, China.ORCID https://orcid.org/0000-0002-8440-2554

Funding

Key Scientific Instrumentation Grant 21627810Key Scientific Instrumentation Grant 22327804National Natural Science Foundation of China 22004064
6 · The paper itself

Abstract

Microproteins encoded by small open reading frames are a pivotal blind spot redefining the conventional protein-coding assumptions. However, the annotation of the "dark proteome" remains time- and labor-consuming due to the limited efficiency, sensitivity, and comprehensiveness of existing validation methods. To address these issues, we developed a comprehensive toolbox called CLAIMID to achieve accelerated and ultrasensitive validation at multiple biological scales. As the core of CLAIMID, molecularly imprinted polymers (MIPs), which are synthesized artificial antibodies toward putative microproteins, provide ultrasensitive and precise annotation in combination with surface-enhanced Raman scattering (SERS) detection. The excellent specificity, comparable to antibodies, of MIPs enables high anti-interference against biological matrix. The adaptability of MIPs engineering confers the rigorous validations by CLAIMID at multiple scales (single living cells, cell populations, and tissues) and diverse detection formats (SERS-based immunoassay and imaging, and mass spectrometric identification). Through CLAIMID, we rapidly confirmed the protein-level translation of four predicted microproteins-previously supported only by computational or ribosome profiling data-across various cell lines, and further identified three as potential tumor biomarkers, thereby demonstrating its university to putative microproteins. Together, we present an annotation toolbox with unparalleled efficiency, sensitivity, and scalability, moving forward for the advent of intriguing microprotein biology era.

Indexed as

AntibodiesMolecular ImprintingAnimalsHumansMicropeptidesOpen Reading FramesPolymersProteomicsSpectrum Analysis, RamanAntibodiesMicropeptidesPolymersmicroproteinsmolecularly imprinted polymersnon‐coding RNAssmall open reading framessurface‐enhanced Raman scattering

Identifiers

PMID41773075
PMCPMC13185872

What Socratic holds

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LicenceCC BY
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Registered trials

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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.