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      hUC-MSC-EV-miR-24 enhances the protective effect of dexmedetomidine preconditioning against myocardial ischemia–reperfusion injury through the KEAP1/Nrf2/HO-1 signaling

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          Abstract

          The cardioprotective effect of microRNAs (miRNAs) on myocardial ischemic-reperfusion (I/R) injury has been documented. Here, we aim to decipher the mechanism of miR-24 delivered by human umbilical cord mesenchymal stem cell-derived extracellular vesicles (hUC-MSC-EVs) in myocardial I/R injury after dexmedetomidine (DEX) preconditioning. We collected and identified hUC-MSCs and extracted EVs, which were co-cultured with DEX-preconditioned hypoxia/reoxygenation (H/R) cardiomyocyte models or injected into I/R mouse models. The cardiomyocytes and myocardial injury were evaluated by molecular biology experiments. miR-24 was highly expressed in hUC-MSC-EVs. hUC-MSC-EVs could transfer miR-24 into cardiomyocytes where miR-24 augmented cell viability and inhibited cell apoptosis after DEX preconditioning. In the co-culture system of RAW264.7 macrophages with hUC-MSC-EVs, miR-24 promoted M2-type polarization of macrophages and reduced M1-type macrophage polarization. Mechanistically, miR-24 targeted KEAP1 and inhibited its expression, resulting in disruption of the Nrf2/HO-1 signaling. In vivo data confirmed that miR-24 delivered by hUC-MSC-EVs enhanced the suppressing effect of DEX preconditioning on inflammation and apoptosis in rats following myocardial I/R injury. Overall, miR-24 delivered by hUC-MSC-EVs can promote M2 polarization of macrophages and enhance the protective effect of DEX preconditioning on myocardial I/R injury by down-regulating the KEAP1/Nrf2/HO-1 signaling axis.

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          Author and article information

          Journal
          Drug Delivery and Translational Research
          Drug Deliv. and Transl. Res.
          Springer Science and Business Media LLC
          2190-393X
          2190-3948
          August 04 2023
          Article
          10.1007/s13346-023-01388-7
          37540334
          11f4d753-4571-445f-994d-67f2603e9a45
          © 2023

          https://www.springernature.com/gp/researchers/text-and-data-mining

          https://www.springernature.com/gp/researchers/text-and-data-mining

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