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Part of book or chapter of book . 2021
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https://doi.org/10.5772/intech...
Part of book or chapter of book . 2023 . Peer-reviewed
License: CC BY
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https://www.intechopen.com/cit...
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The Salivary Secretome

Authors: Luís, Perpétuo,; Rita, Ferreira,; Sofia, Guedes,; Francisco, Amado,; Rui, Vitorino,;

The Salivary Secretome

Abstract

Recently, proteomics has emerged as an important tool for understanding biological systems, protein–protein interactions, and networks that ultimately lead to a deeper understanding of the underlying mechanisms of certain diseases. More recently, the study of secretomes, a type of proteomics, has also been highlighted as a potential next step in the field of diagnosis/prognosis. The secretome is the set of proteins expressed by an organism and secreted into the extracellular space, comprising 13–20% of all proteins. Since almost all, if not all, organs produce secretomes, this means that it is possible to study secretomes and trace these proteins back to their origin, supporting the idea that this could indeed be very important in diagnosing certain diseases. This is often combined with techniques such as mass spectrometry to measure the secretome of, for example, a particular tissue, and bioinformatics tools and databases to give us an idea of what to expect (prediction). In this paper, we will give a general overview of this world, but with a focus on the new bioinformatics tools and databases, their advantages and disadvantages, as well as a deeper look at isolation systems for proteomes, specifically salivary secretomes. Indeed, the salivary secretome represents a valuable new tool capable of providing insights into immunopathology and potentially aiding in diagnostics. Furthermore, we will explore applications of these methods and give an idea of what the future holds for such promising techniques: Salivary secretome in conjunction with bioinformatics tools/databases in the diagnosis of diseases (such as diabetes, Sjogren’s syndrome, and cardiovascular disease).

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
hybrid
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