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Objective: Curcumin is a plant polyphenol extracted from the Chinese herb turmeric. It was found that curcumin has good anti-cancer properties in a variety of cancers, but the exact mechanism is not clear. Based on the network pharmacology and molecular docking to deeply investigate the molecular mechanism of curcumin for the treatment of colon cancer, it provides a new research direction for the treatment of colon cancer.Methods: Curcumin-related targets were collected using PharmMapper, SwissTargetPrediction, Targetnet and SuperPred. Colon cancer related targets were obtained using OMIM, DisGeNET, GeneCards and GEO databases. Drug-disease intersection targets were obtained via Venny 2.1.0. GO and KEGG enrichment analysis of drug-disease common targets were performed using DAVID. Construct PPI network graphs of intersecting targets using STRING database as well as Cytoscape 3.9.0 and filter core targets. Molecular docking via AutoDockTools 1.5.7. The core targets were further analyzed by GEPIA, HPA, cBioPortal and TIMER databases.Results: A total of 73 potential targets of curcumin for the treatment of colon cancer were obtained. GO function enrichment analysis yielded 256 entries, including BP(Biological Progress):166, CC(celluar component):36 and MF(Molecular Function):54. The KEGG pathway enrichment analysis yielded 34 signaling pathways, mainly involved in Metabolic pathways, Nucleotide metabolism, Nitrogen metabolism, Drug metabolism - other enzymes, Pathways in cancer,PI3K-Akt signaling pathway, etc. CDK2, HSP90AA1, AURKB, CCNA2, TYMS, CHEK1, AURKA, DNMT1, TOP2A, and TK1 were identified as core targets by Cytoscape 3.9.0. Molecular docking results showed that the binding energies of curcumin to the core targets were all less than 0 kJ-mol-1, suggesting that curcumin binds spontaneously to the core targets. These results were further validated in terms of mRNA expression levels, protein expression levels and immune infiltration.Conclusion: Based on network pharmacology and molecular docking initially revealed that curcumin exerts its therapeutic effects on colon cancer with multi-target, multi-pathway. Curcumin may exert anticancer effects by binding to core targets. Curcumin may interfere with colon cancer cell proliferation and apoptosis by regulating signal transduction pathways such as PI3K-Akt signaling pathway,IL-17 signaling pathway, Cell cycle. This will deepen and enrich our understanding of the potential mechanism of curcumin against colon cancer and provide a theoretical basis for subsequent studies.

As the foundation of driverless vehicle and intelligent robots, Simultaneous Localization and Mapping(SLAM) has attracted much attention these days. However, nongeometric modules of traditional SLAM algorithms are limited by data association tasks and have become a bottleneck preventing the development of SLAM. To deal with such problems, many researchers seek to Deep Learning for help. But most of these studies are limited to virtual datasets or specific environments, and even sacrifice efficiency for accuracy. Thus, they are not practical enough.We propose DF-SLAM system that uses deep local feature descriptors obtained by the neural network as a substitute for traditional hand-made features. Experimental results demonstrate its improvements in efficiency and stability. DF-SLAM outperforms popular traditional SLAM systems in various scenes, including challenging scenes with intense illumination changes. Its versatility and mobility fit well into the need for exploring new environments. Since we adopt a shallow network to extract local descriptors and remain others the same as original SLAM systems, our DF-SLAM can still run in real-time on GPU.

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