Intelligent machine health monitoring and fault diagnosis are becoming increasingly important for modern manufacturing industries. Current fault diagnosis approaches mostly depend on expert-designed features for building prediction models. In this paper, we proposed IDSCNN, a novel bearing fault diagnosis algorithm based on ensemble deep convolutional neural networks and an improved Dempster–Shafer theory based evidence fusion. The convolutional neural networks take the root mean square (RMS) maps from the FFT (Fast Fourier Transformation) features of the vibration signals from two sensors as inputs. The improved D-S evidence theory is implemented via distance matrix from evidences and modified Gini Index. Extensive evaluations of the IDSCNN on the Case Western Reserve Dataset showed that our IDSCNN algorithm can achieve better fault diagnosis performance than existing machine learning methods by fusing complementary or conflicting evidences from different models and sensors and adapting to different load conditions.
miRNAs regulate gene expression and are key mediators of tumourigenesis. miR-129 has diverse effects in tumours, but its role in laryngeal squamous cell carcinoma (LSCC) remains unknown. This article focuses on the role of miR-129-5p in LSCC. We show miR-129-5p is upregulated in primary LSCC tumours and correlated with advanced disease. Down-regulating miR-129-5p suppressed cell proliferation and migration, and caused cell cycle arrest in Hep-2 cell lines. Downregulation of miR-129-5p alone is sufficient to induce apoptosis both in vivo and in vitro. Moreover, the growth of LSCC xenograft exposed to miR-129-5p antisense oligonucleotides (ASO) in BALB/c mice was markedly inhibited. In addition, we found that miR-129-5p targeted adenomatous polyposis coli (APC) to release inhibition of Wnt signalling causing cell growth and tumourigenesis. Our results suggest miR-129-5p functions as an oncogene in LSCC by repressing APC and is a potential therapeutic target for LSCC.
The purpose of this study was to examine the expression of MMP-14, 15 and 16 (MT1, MT2 and MT3-MMP) in supraglottic carcinoma and to explore their clinical significance. Expression of MMP-14, 15 and 16 was examined using RT-PCR and immunohistochemistry methods in samples from 85 cases of supraglottic carcinoma. Results showed that both mRNA and protein expression of MMP-14, 15 and 16 were increased in supraglottic carcinoma tissues compared to expression in control adjacent non-neoplastic tissues (P < 0.05). Expression of MMP-14, but not MMP-15 and MMP-16, was significantly increased in the T3 and neck nodal metastasis groups compared with the T1-2 group and the group without nodal metastasis at both mRNA and protein levels (P < 0.05). Expression of MMP-14 mRNA and protein was also higher in tumors of patients with stage III-IV disease compared to patients with clinical stage I-II tumors (P < 0.05). Kaplan-Meier survival curves showed that the groups with high MMP-14 protein expression had a poorer prognosis than patients in the groups with weak or negative expression of MMP-14 protein (P < 0.05). In conclusion, MMP-14 may play an important role in the progression of supraglottic carcinoma and may be a novel prognostic factor for patients with supraglottic carcinoma.
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