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Abstract Previous studies have shown that selenium possessed chemotherapeutic effect against multiple malignant cancers, inducing diverse stress responses including apoptosis and autophagy. Selenite was previously shown to induce apoptosis and autophagy in colorectal cancer cells. However, the relationship between selenite-induced apoptosis and autophagy was not fully understood. Our results revealed a pro-survival role of selenite-induced autophagy against apoptosis in colorectal cancer cells. Real-time PCR array of autophagy-related genes showed that GABARAPL-1 was significantly upregulated in colorectal cancer cells, which was confirmed by western blot and immunofluorescence results. Knockdown of GABARAPL-1 significantly inhibited selenite-induced autophagy and enhanced apoptosis. Furthermore, we found that selenite-induced upregulation of GABARAPL-1 was caused by upregulated p-AMPK and FoxO3a level. Their interaction was correlated with involved in regulation of GABARAPL-1. We observed that activation and inhibition of AMPK influenced both autophagy and apoptosis level via FoxO3a/ GABARAPL-1 signaling, implying the pro-survival role of autophagy against apoptosis. Importantly, we corroborated these findings in a colorectal cancer xenograft animal model with immunohistochemistry and western blot results. Collectively, these results show that sodium selenite could induce ROS/AMPK/FoxO3a/GABARAPL-1-mediated autophagy and downregulate apoptosis in both colorectal cancer cells and colon xenograft model. These findings help to explore sodium selenite as a potential anti-cancer drug in clinical practices.

Recently, fully convolutional network (FCN) has been successfully used to locate spliced regions in synthesized images. However, all the existing FCN-based algorithms use real-valued FCN to process each channel separately. As a consequence, they fail to capture the inherent correlation between color channels and the integrity of three channels. So, in this paper, quaternion fully convolutional network (QFCN) is proposed to generalize FCN to quaternion domain by replacing real-valued conventional blocks in FCN with quaternion conventional blocks. In addition, a new color image splicing localization algorithm is proposed by combining QFCNs and superpixel (SP)-enhanced pairwise conditional random field (CRF). QFCNs consider three different versions (QFCN32, QFCN16, and QFCN8) with different up-sampling layers. The SP-enhanced pairwise CRF is used to refine the results of QFCNs. Experimental results on three publicly available datasets demonstrate that the proposed algorithm outperforms the existing algorithms including some conventional algorithms and some deep learning-based algorithms.

Introduction: Hepatic resection is the mainstay of treatment for Hepatocellular carcinoma (HCC). Three- dimensional technique helps to create an image of the liver using pre-operative computed tomography (CT) scans which can be used for planning of surgery and counselling of the patient. Various lab parameters have also been shown to affect the prognosis of HCC. This study was designed to analyse whether three dimensional technique and blood parameters are correlated with the prognosis among HCC patients following hepatic resection and also to find a relation between these variables. Methods: Data were collected retrospectively to recruit HCC patients treated between January 2010 and December 2016. Seventy-three HCC patients without extrahepatic metastasis, who underwent hepatic resection and had pre-operative CT scan done in our centre were enrolled for this study. IQQA® was used to create a three-dimensional imaging, and various related laboratory parameters were also collected. Outcomes of these patients were calculated to establish a relationship between IQQA, laboratory results and the prognosis of the patients. Results: The one, three and five year overall survival (OS) rates were 94.4%, 53.3% and 19.4% respectively, and disease-free survival (DFS) rates were 75%, 31.3% and 12.8% respectively. IQQA percentage of tumor was statistically significant for both OS and DFS. In the multivariate analysis, patients having lymph node metastasis, vascular invasion and high pre-op CA 19-9 had lower DFS rate, while it increased in those with high pre-op albumin. Other significant variables for OS were lymph node metastasis, Child Pugh score, high pre-op alpha fetoprotein (AFP) value and high CA 19-9. Resected segments, lymph node metastasis, liver cirrhosis, blood loss and hospital stay were significant between the two IQQA subgroups (IQQA?30% and IQQA>30%). Additionally in these IQQA subgroups, significant difference was found between DFS and OS. Conclusion: IQQA software is helpful to create a 3D image of the liver, and can be combined with lab parameters to predict prognosis for patients with liver cancer. Therefore, this three-dimensional imaging technique can be used as a routine technique for patients undergoing liver resection.