A long noncoding RNAs (lncRNA) called LINC00657 is dysregulated and contributes to tumor progression in a number of human cancer types. However, there is limited information on the expression profile and functions of LINC00657 in pancreatic ductal adenocarcinoma (PDAC). The expression profile of LINC00657 in PDAC was estimated by reverse-transcription quantitative polymerase chain reaction (RT-qPCR). The effects of LINC00657 upregulation on PDAC cell proliferation, apoptosis, migration, and invasion in vitro and tumor growth in vivo were explored using CCK-8, flow cytometry, Transwell migration and invasion assays, and a xenograft tumor formation experiment, respectively. The results revealed that LINC00657 was evidently upregulated in the PDAC tumors and cell lines. High LINC00657 expression significantly correlated with the pathological T stage, lymph node metastasis, and shorter overall survival. Functional analysis demonstrated that LINC00657 knockdown inhibited the proliferation, migration, and invasion while promoted the apoptosis of PDAC cells. In addition, LINC00657 knockdown markedly suppressed tumor growth of these cells in vivo. In terms of the mechanism, LINC00657 could directly interact with microRNA-433 (miR-433) and effectively worked as an miR-433 sponge, thus decreasing the competitive binding of miR-433 to PAK4 mRNA and ultimately increasing PAK4 expression. The actions of LINC00657 knockdown on malignant phenotype of PDAC cells were strongly attenuated by miR-433 inhibition and PAK4 restoration. These results indicate that LINC00657 promotes PDAC progression by increasing the output of the miR-433-PAK4 regulatory loop, thus highlighting the importance of the LINC00657-miR-433-PAK4 network in PDAC pathogenesis.

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In this paper, we present a model for temperature dependent hysteretic nonlinearities with nonlocal memories. This model can be applied to describe hysteretic material behavior. Common applications are ferromagnetic or magnetostrictive materials. Our model consists mainly of a Preisach operator with a continuous Preisach weight function. We choose a weight function which shows a strong correlation between the function's parameters and certain properties of the hysteresis curve. As a new approach, the weight function is written as a function of temperature. The model parameters are customized to a set of symmetric hysteresis curves. We verify our model for magnetic materials with differently shaped hysteresis curves, different temperatures and magnetic field amplitudes.

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