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Nasal olfactory mucosa mesenchymal stem cells (OM-MSCs) have the ability to promote regeneration in the nervous system in vivo. Moreover, with view to the potential for clinical application, OM-MSCs have the advantage of being easily accessible from patients and transplantable in an autologous manner, thus eliminating immune rejection and contentious ethical issues. So far, most studies have been focused on the role of OM-MSCs in central nervous system replacement. However, the secreted proteomics of OM-MSCs have not been reported yet. Here, proteins secreted by OM-MSCs cultured in serum-free conditions were separated on SDS-PAGE and identified by LC-MS/MS. As a result, a total of 274 secreted proteins were identified. These molecules are known to be important in neurotrophy, angiogenesis, cell growth, differentiation, and apoptosis, and inflammation which were highly correlated with the repair of central nervous system. The proteomic profiling of the OM-MSCs secretome might provide new insights into their nature in the neural recovery. However, proteomic analysis for clinical biomarkers of OM-MSCs needs to be further studied.
Pubmed ID: 26949398
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Collection of data of protein sequence and functional information. Resource for protein sequence and annotation data. Consortium for preservation of the UniProt databases: UniProt Knowledgebase (UniProtKB), UniProt Reference Clusters (UniRef), and UniProt Archive (UniParc), UniProt Proteomes. Collaboration between European Bioinformatics Institute (EMBL-EBI), SIB Swiss Institute of Bioinformatics and Protein Information Resource. Swiss-Prot is a curated subset of UniProtKB.
View all literature mentionsComputable knowledge regarding functions of genes and gene products. GO resources include biomedical ontologies that cover molecular domains of all life forms as well as extensive compilations of gene product annotations to these ontologies that provide largely species-neutral, comprehensive statements about what gene products do. Used to standardize representation of gene and gene product attributes across species and databases.
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