Platelet microparticles load a repertory of miRNAs programmed to drive osteogenic phenotype

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.creatorFerreira, Marcel Rodrigues [UNESP]-
Autor(es): dc.creatorZambuzzi, Willian Fernando [UNESP]-
Data de aceite: dc.date.accessioned2022-02-22T00:48:42Z-
Data de disponibilização: dc.date.available2022-02-22T00:48:42Z-
Data de envio: dc.date.issued2021-06-25-
Data de envio: dc.date.issued2021-06-25-
Data de envio: dc.date.issued2019-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1002/jbm.a.37140-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/206943-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/206943-
Descrição: dc.descriptionAutologous platelet-rich plasma accelerates bone healing by releasing biomolecules during their degranulation process, which are transported by vesicle-like structures called platelet microparticles (PMPs). However, the underlying mechanisms regulating the osteogenic differentiation by PMP-released miRs remain poorly understood and this prompted us to better address this issue. Thus, miRNAseq expression profiles (E-GEOD-76789) were downloaded from ArrayExpress database. GEO2R was performed to evaluate the differential expression, and mirnatap R package was used to find targets for differentially expressed miRNAs. An extend protein–protein (ePPI) network for osteogenic marker proteins was generated using String, and DAVID tools were used to perform gene ontology and KEGG pathway analysis from ePPI and miRNAs targets. Our data show that ePPI network was composed by 232 nodes and 2,175 edges, with a clustering coefficient of 0.546. MCODE was able to identify seven clusters contained in the ePPI network, and the two that presented a score above 10 were used in further analysis. Conversely, 15,944 different targets were found as down-expressed while 5,715 different targets were up-expressed. Among the downregulated 75 miRNAs, 70 have predicted targets present in the ePPI network, while the 21 upregulated miRNAs have 19 predicted targets in the ePPI network. Our study provides a registry of miRNAs that play a central role in regulating osteogenic phenotype, which might have potential therapeutic applications in bone regeneration and bone tissue engineering.-
Descrição: dc.descriptionDepartment of Chemistry and Biochemistry São Paulo State University (UNESP) Institute of Biosciences campus Botucatu-
Descrição: dc.descriptionDepartment of Chemistry and Biochemistry São Paulo State University (UNESP) Institute of Biosciences campus Botucatu-
Idioma: dc.languageen-
Relação: dc.relationJournal of Biomedical Materials Research - Part A-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectbioengineering-
Palavras-chave: dc.subjectbone-
Palavras-chave: dc.subjectmiRNA-
Palavras-chave: dc.subjectplatelet microparticles-
Palavras-chave: dc.subjectplatelets-rich plasma-
Palavras-chave: dc.subjectregeneration-
Título: dc.titlePlatelet microparticles load a repertory of miRNAs programmed to drive osteogenic phenotype-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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