ArticleIET nanobiotechnology2025
Ultrafast and Deep Saliva Proteome Reveals the Dynamic of Human Saliva With Aging by Orbitrap Astral Mass Spectrometer.
Article in IET nanobiotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- A Peptide-Centric DIA-NN Reanalysis Uncovers Structurally Coherent Salivary Signatures of Type 2 Diabetes.International journal of molecular sciences · 2026Article
- ITRAQ and PRM-based quantitative saliva proteomics in gastric cancer: biomarker discovery.Frontiers in molecular biosciences · 2025Article
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9 authors.
Funding
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Abstract
Saliva has already proven to be a prospective diagnostic bioresource for both early disease detection and timely intervention due to its easy accessibility, noninvasiveness, and reproducibility. However, the in-depth identification of salivary proteins needs to be further improved. Until now, only 3427 proteins are included in the human salivary proteome (HSP), which is far from the millions of proteins that make up humans. Here, we set out to quantitatively map the HSP in rapid and in-depth Orbitrap Astral mass spectrometer (MS) and coronal nanomagnetic bead-based proteomics workflow. Our study reported 5937 salivary proteins, which was about 73% more than that recorded in HSP. Moreover, we compared the differences between the young and aged salivary proteins. The predominant functions of the upregulated proteins in the young were related to motor proteins and cardiomyopathy, whereas those of the aged were primarily upregulated with oxidation reaction, as well as neurodegenerative disorders. It is the first study to carry out salivary proteomics using a fast and deep Orbitrap Astral MS and remarkably enlarged the number of proteins with HSP, furthermore, salivary proteomics was found to be characterized in the young and aged. With the rapidly advancing MS and proteomics technologies, we believe that salivary protein biomarkers will be more promising for clinical diagnosis and prognosis of human diseases in the future.
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