Several lines of evidence suggest that circular RNAs (circRNAs) play important roles in oncogenesis and tumor progression. However, our knowledge of the role of circRNAs in gastric cancer (GC) remains limited. We investigated the possibility that circular RNA 0047905 (circRNA0047905) might act as a tumor promoter in the pathogenesis of gastric cancer by profiling miRNA expression in GC tissues and paired noncancerous mucosa tissues using miRNA microarrays. Next, a ceRNA network was constructed according to common miRNAs binding circRNAs and mRNAs. Mechanistically, we demonstrated that circRNA0047905 directly binds miR4516 and miR1227-5p, relieving suppression for targets SERPINB5 and MMP11. We observed that down-regulated circRNA0047905 expression in gastric cancer cells inhibited Akt/CREB signaling pathway activation. RNA scope in situ hybridization revealed expression of circRNA0047905 in GC. Our data suggest that circRNA0047905 is a promising target for GC diagnosis and therapy.
For the sake of addressing the issue of extracting multiple features embedded in a noise-heavy vibration signal for bearing compound fault diagnosis, a novel model based on improved adaptive chirp mode decomposition (IACMD) and sparse representation, namely IACMDSR, is developed in this paper. Firstly, the IACMD is employed to simultaneously separate the distinct fault types and extract multiple resonance frequencies induced by them. Next, an adaptive bilateral wavelet hyper-dictionary that digs deeper into the periodicity and waveform characteristics exhibited by the real fault impulse response is constructed to identify and reconstruct each type of fault-induced feature with the help of the orthogonal matching pursuit (OMP) algorithm. Finally, the fault characteristic frequency can be detected via an envelope demodulation analysis of the reconstructed signal. A simulation and two sets of experimental results confirm that the developed IACMDSR model is a powerful and versatile tool and consistently outperforms the leading MCKDSR and MCKDMWF models. Furthermore, the developed model has satisfactory capability in practical applications because the IACMD has no requirement for the input number of the signal components and the adaptive bilateral wavelet is powerfully matched to the real fault-induced impulse response.
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