Background Aberrant alternative splicing included alterations in components of the mRNA splicing machinery often occurred in colon cancer. However, the role of SF3A1, one key component of the mRNA ...splicing machinery, on colorectal cancer (CRC) risk was still not elucidated. Method and Findings We performed a hospital-based case-control study containing 801 CRC patients and 817 cancer-free controls to examine the association between SF3A1 polymorphisms and CRC risk in a Chinese population. Four candidate SNPs (rs10376, rs5753073, rs2839998 and rs2074733) were selected based on bioinformatics analysis and previous findings. The results showed no significant associations between these SNPs and CRC risk (P > 0.05). Besides, the stratified analysis based on the smoking and alcohol use status obtained no statistically significant results. Conclusion Our study was the first one to investigate the association between SF3A1 polymorphisms and CRC risk. The results suggested these four SNPs in SF3A1 were not associated with CRC risk in a Chinese population, however, further more studies are needed to confirm our findings.
Upregulated gene 11 (URG11), a new gene upregulated by Heptatitis B Virus X protein (HBx), was previously shown to activate β-catenin and promote hepatocellular growth and tumourigenesis. Although ...the oncogenic role of URG11 in the development of hepatocellular carcinoma has been well documented, its relevance to other human malignancies and the underlying molecular mechanisms remain largely unknown. Here we reported a novel function of URG11 to promote gastric cancer growth and metastasis. URG11 was found to be highly expressed in gastric cancer tissues compared with adjacent nontumourous ones by immunohistochemical staining and western blot. Knockdown of URG11 expression by small interfering RNA (siRNA) effectively attenuated the proliferation, anchorage-independent growth, invasiveness and metastatic potential of gastric cancer cells. URG11 inhibition led to decreased expression of β-catenin and its nuclear accumulation in gastric cancer cells and extensive costaining between URG11 and β-catenin was observed in gastric cancer tissues. Transient transfection assays with the β-catenin promoter showed that it was inhibited by URG11-specific small inhibitory RNA. Moreover, suppression of endogenous URG11 expression results in decreased activation of β-catenin/TCF and its downstream effector genes, cyclinD1 and membrane type 1 matrix metallopeptidase (MT1-MMP), which are known to be involved in cell proliferation and invasion, respectively. Taken together, our data suggest that URG11 contributes to gastric cancer growth and metastasis at least partially through activation of β-catenin signalling pathway. These findings also propose a promising target for gene therapy in gastric cancer. PUBLICATION ABSTRACT
Recently, artificial intelligence has been extensively deployed across various scientific disciplines, optimizing and guiding the progression of experiments through the integration of abundant ...datasets, whilst continuously probing the vast theoretical space encapsulated within the data. Particularly, deep learning models, due to their end-to-end adaptive learning capabilities, are capable of autonomously learning intrinsic data features, thereby transcending the limitations of traditional experience to a certain extent. Here, we unveil previously unreported information characteristics pertaining to different frequencies emerged during our work on predicting the terahertz spectral modulation effects of metasurfaces based on AI-prediction. Moreover, we have substantiated that our proposed methodology of simply adding supplementary multi-frequency inputs to the existing dataset during the target spectral prediction process can significantly enhance the predictive accuracy of the network. This approach effectively optimizes the utilization of existing datasets and paves the way for interdisciplinary research and applications in artificial intelligence, chemistry, composite material design, biomedicine, and other fields.
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