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The infrared and visible image fusion task aims to generate a single image that preserves complementary features and reduces redundant information from different modalities. Although convolutional neural networks (CNNs) can effectively extract local features and obtain better fusion performance, the size of the receptive field limits its feature extraction ability. Thus, the Transformer architecture has gradually become mainstream to extract global features. However, current Transformer-based fusion methods ignore the enhancement of details, which is important to image fusion tasks and other downstream vision tasks. To this end, a new super feature attention mechanism and the wavelet-guided pooling operation are applied to the fusion network to form a novel fusion network, termed SFPFusion. Specifically, super feature attention is able to establish long-range dependencies of images and to fully extract global features. The extracted global features are processed by wavelet-guided pooling to fully extract multi-scale base information and to enhance the detail features. With the powerful representation ability, only simple fusion strategies are utilized to achieve better fusion performance. The superiority of our method compared with other state-of-the-art methods is demonstrated in qualitative and quantitative experiments on multiple image fusion benchmarks.
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Immune checkpoint inhibitors (ICIs) therapy has been successfully utilized in the treatment of multiple tumors, but only a fraction of patients with gastric cancer (GC) could greatly benefit from it. A recent study has shown that the tumor microenvironment (TME) can greatly affect the effect of immunotherapy in GC. In this study, we established a novel immune risk signature (IRS) for prognosis and predicting response to ICIs in GC based on the TCGA-STAD dataset. Characterization of the TME was explored and further validated to reveal the underlying survival mechanisms and the potential therapeutic targets of GC. The GC patients were stratified into high- and low-risk groups based on the IRS. Patients in the high-risk group, associated with poorer outcomes, were characterized by significantly higher immune function. Further analysis showed higher T cell immune dysfunction and probability of potential immune escape. In vivo, we detected the expressions of SERPINE1 by the quantitative real-time polymerase chain reaction (qPCR)in tumor tissues and adjacent normal tissues. In vitro, knockdown of SERPINE1 significantly attenuated malignant biological behaviors of tumor cells in GC. Our signature can effectively predict the prognosis and response to immunotherapy in patients with GC.
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BACKGROUND: The expression level of a long non-coding RNA (lncRNA), plasmacytoma variant translocation 1 (PVT1), was studied in serum of Han and Uygur gastric cancer (GC) patients and normal persons in Xinjiang, China, and the prognostic value of PVT1 was analyzed. METHODS: We collected serum samples from 87 GC patients (51 Han and 36 Uygur), and 95 normal persons (55 Han and 40 Uygur). Total RNA was extracted from the serum and used for real-time polymerase chain reaction (PCR) to detect the level of PVT1.The relationships between PVT1 and clinicopathological features were analyzed using the Spearman's relative analysis, rank sum test, and χ2 test. At the same time, selection electrochemiluminescence was used to detect the concentration of serum tumor markers, including alpha fetoprotein (AFP), carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), and carbohydrate antigen 72-4 (CA72-4). The correlation between PVT1 and the tumor markers was analyzed by Spearman's relative analysis. RESULTS: The serum expression level of PVT1 was higher than that of the normal group in both Han and Uygur GC patients (P<0.05). PVT1 expression in Uygur GC serum was higher than that of Han patients (P<0.05). The high level of serum PVT1 correlated with lymph node metastasis in both Han and Uygur GC patients (P<0.05). Compared with Han GC patients, the Uygur people were more likely to develop distant metastasis (P<0.05). Uygur patients were more often diagnosed at stage III or IV (P<0.05). In addition, serum PVT1 showed a significant correlation with CA19-9 in Han GC patients (P<0.05). CONCLUSIONS: Increased serum PVT1 level may indicate an increased tendency for lymphatic metastasis, especially in Uygur GC patients. When combined with CA19-9, the PVT1 expression level may be a better diagnostic marker in Han GC patients.
RESUMO
To analyze the level and diagnostic value of plasmacytoma variant translocation 1 (PVT1) in gastric cancer (GC) of Han and Uygur in Xinjiang, China, we collected 42 GC and 47 normal gastric tissues and performed tissue microarray. In situ hybridization was used to detect PVT1, while immunohistochemistry was used to analyze c-myc. The relationship between PVT1, c-myc and clinical pathological features was investigated. We then analyzed the expression of PVT1 in six GC cell lines. RNA interference was used to silence PVT1 in BGC823 and AGS cells. c-myc was detected by western blotting after silencing PVT1, while proliferation, invasion and migration ability were also analyzed. We found that PVT1 and c-myc were highly expressed in both Han and Uygur GC tissues. In Han GC, PVT1 was correlated with lymph node metastasis and primary tumor site. In Uygur GC, both PVT1 and c-myc were correlated with lymph node metastasis and clinical staging. PVT1 was positively correlated with c-myc. BGC823 and AGS cells exhibited high levels of PVT1. When PVT1 expression was silenced, the expression of c-myc decreased, while migration and invasion ability were also decreased in cells. PVT1 could therefore be a potential biomarker to predict the metastatic tendency of GC in both Han and Uygur patients.