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Loading Ovalbumin into Mesenchymal Stem Cell-Derived Exosomes as a Nanoscale Carrier with Immunomodulatory Potential for Allergen-Specific Immunotherapy.
Dehnavi, Sajad; Khodadadi, Ali; Asadirad, Ali; Ghadiri, Ata.
Afiliação
  • Dehnavi S; Department of Immunology, Faculty of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
  • Khodadadi A; Air Pollution and Respiratory Diseases Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
  • Asadirad A; Immunology Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
  • Ghadiri A; Department of Immunology, Faculty of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Rep Biochem Mol Biol ; 11(4): 626-634, 2023 Jan.
Article em En | MEDLINE | ID: mdl-37131891
Background: Exosomes are nanoscale vesicles widely used as drug delivery systems. Mesenchymal stem cell (MSC)-derived exosomes have shown immunomodulatory potential. This study optimized loading OVA into the mice adipose tissue-derived MSC-isolated exosomes to prepare the OVA-MSC-exosome complex for allergen-specific immunotherapy. Methods: MSCs were harvested from mice adipose tissue and characterized by flow cytometry and evaluating differentiation potential. The exosomes were isolated and characterized via Dynamic Light Scattering, Scanning Electron Microscopy, and flow cytometry. Different concentrations of ovalbumin were incubated with MSC-exosome in various durations to optimize a more suitable protocol. BCA and HPLC analysis were used to quantify, and DLS was applied to qualify the prepared formulation of the OVA-exosome complex. Results: The harvested MSCs and isolated exosomes were characterized. Analysis of the OVA-exosome complex revealed that OVA in primary 500 µg/ml concentration and incubation for 6 h results in higher efficacy. Conclusions: Loading OVA into MSC-derived exosomes was successfully optimized and could be administrated for allergen-specific immunotherapy in the animal model.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article