microRNAs have been reported to play important roles in the pathogenesis of rheumatoid arthritis (RA). This study examined the effects of miR-522 on the biological behaviors of RA synovial fibroblasts. The expression levels of miR-522 and relevant genes were measured by quantitative real-time PCR. The protein levels of cytokines were determined by ELISA assay. The protein levels of matrix metalloproteinases (MMPs) and suppressor of cytokine signaling 3 (SOCS3) were determined by western blot assay. Luciferase reporter assay was used to confirm the potential target of miR-522. Our results showed that miR-522 was upregulated in synovial fibroblasts from RA patients, and miR-522 expression level was significantly associated with the RA-associated clinical parameters. miR-522 overexpression increased the mRNA and protein expression levels of tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β) and MMPs (MMP-1, MMP-3, and MMP-13) in RA synovial fibroblasts. Lipopolysaccharide induced the upregulation of TNF-α, IL-1β, and MMPs in RA synovial fibroblasts, which was reversed by miR-522 knockdown. Bioinformatics analysis identified SOCS3 as a potential target of miR-522, and this target of miR-522 was confirmed by luciferase reporter assay, and miR-522 overexpression suppressed the mRNA and protein expression levels of SOCS3. The enforced expression of SOCS3 attenuated the enhanced effects of miR-522 on mRNA expression levels of TNF-α, IL-1β, and MMPs. Collectively, our results suggested that miR-522 regulated the expression of proinflammatory cytokines and MMPs partly via targeting SOCS3 in RA synovial fibroblasts, which may contribute to pathogenesis of RA.
SummaryThis paper is devoted to investigating the stability of interconnected nonlinear fractional‐order systems via a single‐state variable control. First of all, based on stability theory, the Grönwall‐Bellman lemma and the Mittag‐Leffler function, the relevant stability results are derived. The obtained results are general and can further extend the application range. Meanwhile, an improved single‐state variable control method is introduced. The control scheme only needs to control some state variable of the system or some subsystem(s) to realize and any additional restrictions are not added. Finally, the effectiveness of the obtained results is demonstrated by several typical examples. Besides, by comparison, simulation results show that the proposed control method can indeed decrease the design and control cost and improve flexibility of control.
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