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Proteomics of Crystal–Cell Interactions: A Model for Kidney Stone Research

Authors: Visith Thongboonkerd;

Proteomics of Crystal–Cell Interactions: A Model for Kidney Stone Research

Abstract

Nephrolithiasis/urolithiasis (i.e., kidney stone disease) remains a global public health problem with increasing incidence/prevalence. The most common chemical composition of kidney stones is calcium oxalate that initiates stone formation by crystallization, crystal growth, crystal aggregation, crystal–cell adhesion, and crystal invasion through extracellular matrix in renal interstitium. Among these processes, crystal–cell interactions (defined as “the phenomena in which the cell is altered by any means of effects from the crystal that adheres onto cellular surface or is internalized into the cell, accompanying with changes of the crystal, e.g., growth, adhesive capability, degradation, etc., induced by the cell”) are very important for crystal retention in the kidney. During the past 12 years, proteomics has been extensively applied to kidney stone research aiming for better understanding of the pathogenic mechanisms of kidney stone formation. This article provides an overview of the current knowledge in this field and summarizes the data obtained from all the studies that applied proteomics to the investigations of crystal–cell interactions that subsequently led to functional studies to address the significant impact or functional roles of the expression proteomics data in the pathogenesis of kidney stone disease.

Keywords

Proteomics, CaOx, QH573-671, Calcium Oxalate, urolithiasis, Review, COD, Kidney, secretome, Kidney Calculi, Cell Adhesion, exosome, Humans, COM, Cytology, Crystallization, mass spectrometry, nephrolithiasis

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    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).
    79
    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.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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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!
79
Top 1%
Top 10%
Top 1%
Green
gold