MiR-380 inhibits the proliferation and invasion of cholangiocarcinoma cells by silencing LIS1.

BACKGROUND: The objective of this study was to determine the role and regulatory mechanism of miR-380 in cholangiocarcinoma. METHODS: The TargetScan database and a dual-luciferase reporter assay system were used to determine if LIS1 was a target gene of miR-380. The Cell Counting Kit 8 assay, flow cytometry, and Transwell assay were used to detect the effects of miR-380 and LIS1 on the proliferation, S-phase ratio, and invasiveness of HCCC-9810/HuCCT1/QBC939 cells. Western blotting was used to determine the effect of miR-380 on MMP-2/p-AKT. Immunohistochemistry detected the regulatory effect of miR-380 on the expression of MMP-2/p-AKT/LIS1. RESULTS: Expression of miR-380 in cholangiocarcinoma was decreased but expression of LIS1 was increased. LIS1 was confirmed to be a target gene of miR-380. Transfection with miR-380 mimics inhibited the proliferation, S-phase arrest, and invasion of HCCC-9810/HuCCT1/QBC939 cells, and LIS1 reversed these inhibitory effects. miR-380 inhibitor promoted proliferation, S-phase ratio, and invasiveness of HCCC-9810/HuCCT1/QBC939 cells. si-LIS1 salvaged the promotive effect of miR-380 inhibitor. Overexpression of miR-380 inhibited expression of MMP-2/p-AKT/LIS1, but miR-380 inhibitor promoted their expression. CONCLUSION: An imbalance of miR-380 expression is closely related to cholangiocarcinoma, and overexpression of miR-380 inhibits the expression of MMP-2/p-AKT by directly targeting LIS1.

Remote Sensing Image Dehazing through an Unsupervised Generative Adversarial Network.

The degradation of visual quality in remote sensing images caused by haze presents significant challenges in interpreting and extracting essential information. To effectively mitigate the impact of haze on image quality, we propose an unsupervised generative adversarial network specifically designed for remote sensing image dehazing. This network includes two generators with identical structures and two discriminators with identical structures. One generator is focused on image dehazing, while the other generates images with added haze. The two discriminators are responsible for distinguishing whether an image is real or generated. The generator, employing an encoder-decoder architecture, is designed based on the proposed multi-scale feature-extraction modules and attention modules. The proposed multi-scale feature-extraction module, comprising three distinct branches, aims to extract features with varying receptive fields. Each branch comprises dilated convolutions and attention modules. The proposed attention module includes both channel and spatial attention components. It guides the feature-extraction network to emphasize haze and texture within the remote sensing image. For enhanced generator performance, a multi-scale discriminator is also designed with three branches. Furthermore, an improved loss function is introduced by incorporating color-constancy loss into the conventional loss framework. In comparison to state-of-the-art methods, the proposed approach achieves the highest peak signal-to-noise ratio and structural similarity index metrics. These results convincingly demonstrate the superior performance of the proposed method in effectively removing haze from remote sensing images.

Ten-gene signature reveals the significance of clinical prognosis and immuno-correlation of osteosarcoma and study on novel skeleton inhibitors regarding MMP9.

OBJECTIVES: This study aimed to identify novel targets in the carcinogenesis, therapy and prognosis of osteosarcoma from genomic level, together with screening ideal lead compounds with potential inhibition regarding MMP-9. METHODS: Gene expression profiles from GSE12865, GSE14359, GSE33382, GSE36001 and GSE99671 were obtained respectively from GEO database. Differentially expressed genes were identified, and functional enrichment analysis, such as GO, KEGG, GSEA, PPI were performed to make a comprehensive understanding of the hub genes. Next, a series of high-precision computational techniques were conducted to screen potential lead compounds targeting MMP9, including virtual screening, ADME, toxicity prediction, and accurate docking analysis. RESULTS: 10 genes, MMP9, CD74, SPP1, CXCL12, TYROBP, FCER1G, HCLS1, ARHGDIB, LAPTM5 and IGF1R were identified as hub genes in the initiation of osteosarcoma. Machine learning, multivariate Cox analysis, ssGSEA and survival analysis demonstrated that these genes had values in prognosis, immune-correlation and targeted treatment. Tow novel compounds, ZINC000072131515 and ZINC000004228235, were screened as potential inhibitor regarding MMP9, and they could bind to MMP9 with favorable interaction energy and high binding affinity. Meanwhile, they were precited to be efficient and safe drugs with low-ames mutagenicity, none weight evidence of carcinogenicity, as well as non-toxic with liver. CONCLUSIONS: This study revealed the significance of 10-gene signature in the development of osteosarcoma. Besides, drug candidates identified in this study provided a solid basis on MMP9 inhibitors' development.

Novel Natural Inhibitors Targeting Enhancer of Zeste Homolog 2: A Comprehensive Structural Biology Research.

The enhancer of zeste homolog 2 (EZH2) is a methylated modification enzyme of Histone H3-Lys 27. The high expression of EZH2 in cells is closely related to the progression, invasion, and metastasis of neoplasm. Therefore, this target is gradually becoming one of the research hot spots of tumor pathogenesis, and the inhibitors of the EZH2 enzyme are expected to become new antitumor drugs. This study used a series of virtual screening technologies to calculate the affinity between the compounds obtained from the ZINC15 database and the target protein EZH2, the stability of the ligand-receptor complex. This experiment also predicted the toxicity and absorption, distribution, metabolism, and excretion (ADME) properties of the candidate drugs in order to obtain compounds with excellent pharmacological properties. Finally, the ligand-receptor complex under in vivo situation was estimated by molecular dynamics simulation to observe whether the complex could exist steadily in the body. The experimental results showed that the two natural compounds ZINC000004217536 and ZINC000003938642 could bind tightly to EZH2, and the ligand-receptor complex could exist stably in vivo. Moreover, these two compounds were calculated to be nontoxic. They also had a high degree of intestinal absorption and high bioavailability. In vitro experiments confirmed that drug ZINC000003938642 could inhibit the proliferation and migration of osteosarcoma, which could serve as potential lead compounds. Therefore, the discovery of these two natural products had broad prospects in the development of EZH2 inhibitors, providing new clues for the treatment or adjuvant treatment of tumors.