MicroRNAs (miRNAs) possess oncogenic and tumour‑suppressive roles in the carcinogenesis and progression of pancreatic ductal adenocarcinoma (PDAC) by regulating the expression of numerous cancer‑related genes. Thus, the investigation on the expression and roles of miRNAs in PDAC may facilitate the identification of novel and effective targets for the clinical diagnosis and treatment of patients with PDAC. miRNA‑539 (miR‑539) has been studied in multiple types of human cancer. However, its expression and potential biological function in PDAC remain unclear. In the current study, the expression level, clinical significance, roles and underlying molecular mechanism of miR‑539 in PDAC. The present results demonstrated that miR‑539 expression was downregulated in PDAC tissues and cell lines. A low miR‑539 level was associated with TNM stage and lymph node metastasis of patients with PDAC. miR‑539 overexpression induced a significant reduction in the proliferation, colony formation and invasion of PDAC cells. Insulin‑like growth factor 1 receptor (IGF‑1R) was confirmed as a direct target gene of miR‑539 in PDAC. Further analysis indicated that IGF‑1R was overexpressed in PDAC tissues. Notably, the mRNA expression of IGF‑1R was negatively correlated with miR‑539 levels in PDAC tissues. In addition, the recovered IGF‑1R expression also partially counteracted the suppressive roles of miR‑539 overexpression in PDAC cells. Overall, miR‑539 may inhibit the aggressive behaviour of PDAC by directly targeting IGF‑1R and may serve as a novel therapeutic target for patients with this disease.
In this paper, we investigate a class of the scalar discrete-time adaptive control system based on an extremely simple one-step-guess (OSG) estimator, whose closed loop is rather complex and nontrivial despite that it has ever been ignored for a long time partially due to its quite simple form and idea. The OSG adaptive controller is based on the most intuitive idea to estimate the unknown parameter with only the information available from one step, and its form is much simpler than and different from that of other widely used adaptive controllers based on least-squars algorithm or gradient-type algorithms. We show that the closed-loop system of the OSG adaptive controller is indeed governed by a timevarying nonlinear difference equation, which was not thoroughly investigated in previous studies of difference equations. The primordial OSG adaptive controller without dead zone and the extended OSG adaptive controller with time-varying dead zone are analyzed in this contribution, and their closedloop properties are rigorously established, which show that the simple OSG adaptive controller is stable under mild conditions. Extensive numerical simultions also illustrate the effectiveness of the proposed method.
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