Acute stroke alters the systemic immune response as can be observed in peripheral blood; however, the molecular mechanism by which microRNA (miRNA) regulates target gene expression in response to acute stroke is unknown. We performed a miRNA microarray on the peripheral blood of 10 patients with acute ischemic stroke and 11 control subjects. Selected miRNAs were quantified using a TaqMan assay. After searching for putative targets from the selected miRNAs using bioinformatic analysis, functional studies including binding capacity and protein expression of the targets of the selected miRNAs were performed. The results reveal a total of 30 miRNAs that were differentially expressed (16 miRNAs were upregulated and 14 miRNAs were downregulated) during the acute phase of stroke. Using prediction analysis, we found that miR-340-5p was predicted to bind to the 3'-untranslated region of the arginase-1 (ARG1) gene; a luciferase reporter assay confirmed the binding of miR-340-5p to ARG1. miR-340-5p was downregulated whereas ARG1 mRNA was upregulated in peripheral blood in patients experiencing acute stroke. Overexpression of miR-340-5p in human neutrophil and mouse macrophage cell lines induced downregulation of the ARG1 protein. Transfection with miR-340-5p increased nitric oxide production after LPS treatment in a mouse macrophage cell line. Our results suggest that several miRNAs are dynamically altered in the peripheral blood during the acute phase of ischemic stroke, including miR-340-5p. Acute stroke induces the downregulation of miR-340-5p, which subsequently upregulates ARG1 protein expression.

Despite people’s concerns over privacy leakage in the Internet of Things (IoT), the needs for personalized IoT services are increasing, creating a conflicting phenomenon viewed as the personalization–privacy (P–P) paradox. This study proposes a research model that utilizes dual-factor theory to investigate the P–P paradox in IoT. It aims to analyze the impact of the dual factor—personalization and privacy concerns related to IoT services—on the intention to use IoT. Further, the model includes four-dimensional motivated innovativeness and previous privacy-invasion experience as key antecedents of the dual factor. Particularly, this study examines the moderating effects of the type of IoT service and user value on the relationship between dual factor and usage intention. Data were collected using a web-based survey. The results showed that personalization had a significant impact on the intention to use IoT, whereas privacy concerns did not. The effects of all antecedents except social innovativeness were significant. The P–P paradox phenomenon appeared differently depending on the type of IoT service and user value. This study contributes to gaining a better understanding of the factors that influence the increase in IoT usage in terms of both protecting and appropriately using personal information for IoT services.

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