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Pulmonary Sarcoidosis: Experimental Models and Perspectives of Molecular Diagnostics Using Quantum Dots

Authors :
Natalia Linkova
Anastasiia Diatlova
Yulia Zinchenko
Anastasiia Kornilova
Petr Snetkov
Svetlana Morozkina
Dmitrii Medvedev
Alexandr Krasichkov
Victoria Polyakova
Piotr Yablonskiy
Source :
International Journal of Molecular Sciences, Vol 24, Iss 14, p 11267 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Sarcoidosis is a complex inflammatory multisystem disease of unknown etiology that is characterised by epithelioid cell granulomatous lesions affecting various organs, mainly the lungs. In general, sarcoidosis is asymptomatic, but some cases result in severe complications and organ failure. So far, no accurate and validated modelling for clinical and pathohistological manifestations of sarcoidosis is suggested. Moreover, knowledge about disease-specific diagnostic markers for sarcoidosis is scarce. For instance, pulmonary granulomatosis is associated with the upregulated production of proinflammatory molecules: TNF-α, IL-6, CXCL1, CCL2, CCL18, CD163, serum angiotensin-converting enzyme (sACE), lysozyme, neopterin, and serum amyloid A (SAA). Quantum dots (QDs) are widely applied for molecular diagnostics of various diseases. QDs are semiconductor nanoparticles of a few nanometres in size, made from ZnS, CdS, ZnSe, etc., with unique physical and chemical properties that are useful for the labelling and detection in biological experiments. QDs can conjugate with various antibodies or oligonucleotides, allowing for high-sensitivity detection of various targets in organs and cells. Our review describes existing experimental models for sarcoidosis (in vitro, in vivo, and in silico), their advantages and restrictions, as well as the physical properties of quantum dots and their potential applications in the molecular diagnostics of sarcoidosis. The most promising experimental models include mice with TSC2 deletion and an in silico multiscale computational model of sarcoidosis (SarcoidSim), developed using transcriptomics and flow cytometry of human sarcoid biopsies. Both models are most efficient to test different candidate drugs for sarcoidosis.

Details

Language :
English
ISSN :
14220067 and 16616596
Volume :
24
Issue :
14
Database :
Directory of Open Access Journals
Journal :
International Journal of Molecular Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.fa96c956184d339cafd3242fba0612
Document Type :
article
Full Text :
https://doi.org/10.3390/ijms241411267