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Objective: Tumor immune infiltration leads to poor prognosis of gastric cancer patients and seriously affects the life quality of gastric cancer patients. This study was based on bioinformatics to screen prognostic biomarkers in patients with high degree of immune invasion of gastric cancer. Meanwhile, the action of biomarker CCDC80 was explored in gastric cancer by cell and tumorigenesis experiments, to provide reference for the cure of gastric cancer patients. Methods: Data sets and clinical massage on gastric cancer were collected from TCGA database and GEO database. ConsensusClusterPlus was used to cluster gastric cancer patients based on the 28 immune cells infiltration in ssGSEA. R "Limma" package was applied to analyze differential mRNAs between Cluster 1 and Cluster 2. Differential expression genes were screened by single factor analysis. Stemness markers (SERPINF1, DCN, CCDC80, FBLN5, SPARCL1, CCL14, DPYSL3) were identified for differential expression genes. Prognostic value of CCDC80 was evaluated in gastric cancer. Differences in genomic mutation and tumor microenvironment immune infiltration were assessed between high or low CCDC80. Finally, gastric cancer cells (HGC-27 and MKN-45) were selected to evaluate the action of silencing CCDC80 on malignant characterization, macrophage polarization, and tumor formation. Results: Bioinformatics analysis showed that CCDC80, as a stemness marker, was significantly overexpressed in gastric cancer. CCDC80 was also related to the degree of gastric cancer immune invasion. CCDC80 was up-expressed in cells of gastric cancer. Silencing CCDC80 inhibited malignant characterization and subcutaneous tumor formation of gastric cancer cells. High expression of CCDC80 was positive correspondence with immune invasion. Silencing CCDC80 inhibited M2 polarization and promoted M1 polarization in tumor tissues. In addition, gastric cancer patients were likely to have mutations in CDH1, ACTRT1, GANAB, and CDH10 genes in the High-CCDC80 group. Conclusion: Silencing CCDC80, a prognostic biomarker in patients with immune invasion of gastric cancer, could effectively inhibit the malignant characterization, M2 polarization, and tumor formation of gastric cancer. [ABSTRACT FROM AUTHOR]

Zirconia implants have great application prospects due to their favorable biocompatibility and esthetic properties. However, the percentage of osseointegration of zirconia implants is lower than that of titanium implants. This study, structures bioactive surfaces on zirconia using a femtosecond laser combined with hydroxyapatite (HA) crystals and evaluates the surface morphology, functional groups, crystal phase, mechanical performance, and cell response. The results revealed that calcium phosphate deposition coincided with the establishment of micro‐grooves on the zirconia surface. The crystal composition and flexural strength of zirconia showed no significant changes after the surface treatment. Furthermore, the modified surface promoted cell adhesion and proliferation through adjustments in cell morphology. The findings suggest that the combination of femtosecond laser and HA crystals offers a clean, rapid, and controllable approach to preparing bioactive surfaces for zirconia implants. [ABSTRACT FROM AUTHOR]

Background: Metastasis poses the greatest threat to the lives of individuals with prostate cancer. Therefore, it is imperative to identify the underlying mechanism driving metastasis. Doing so would facilitate the detection of new diagnostic biomarkers and the advancement of treatment options for patients. Methods: Metastasis‐related modules were identified through weighted gene co‐expression network analysis based on microarray GSE6919. Hub genes were confirmed by quantitative real‐time PCR across different prostate cell lines and clinic samples. Pivotal genes were determined through integration of RNA and transcription factor‐target associated interactions. To predict drugs with potential to suppress tumor metastasis, we applied molecular networks using the DrugBank database. Drug repositioning analysis and confirmation of drug screen were conducted using the compound library. Confirmation of selective cytotoxicity of cupric oxide was carried out via invasion, transwell and apoptosis assays. Results: We identified five metastasis‐related modules. Of these modules, two were identified to represent core dysfunction modules in which five hub genes were determined for each module. Five of these 10 genes correlating with prostate cancer progression. Furthermore, our analysis revealed that there are 36 drugs with the potential to be active against tumor metastasis. Finally, we identified four compounds that have not previously been reported to have any association with cancer therapy. Of these, cupric oxide was determined to have the best chemotherapeutic potential in treating prostate cancer metastasis. Conclusions: By combining bioinformatics methods with compound library screening, this study proposes a valuable approach to drug discovery. Cupric oxide showed the potential in the treatment of prostate cancer metastasis and deserves further study. [ABSTRACT FROM AUTHOR]

A triboelectric nanogenerator (TENG) can convert energy in the surrounding environment to electricity. Therefore, in recent years, research related to TENGs has significantly increased owing to its simple and low‐cost manufacturing process, high portability, and high efficiency. The principle of the TENG lies in the coupling effect of contact electrification and electrostatic induction. Its output performance is directly proportional to the square of the surface charge density, which is related to friction materials. To increase the output power of a TENG and continuously provide electricity for other electronic equipment, many scholars have conducted detailed studies on the triboelectric properties of materials. Particularly, there has been research interest in the chemical functionalization of TENGs due to their unique advantages, such as high triboelectric charge density, durability, stability, and self‐cleaning properties. This Progress Report highlights the research progress in chemical modification methods for improving the charge density of TENGs, and classifies their modification methods according to their mechanisms. The effects of chemical reaction, surface chemical treatment, and chemical substance doping on the output performance of TENGs are systematically elaborated. Furthermore, the applications of chemically modified TENG in self‐powered sensors and emerging fields, including wearable electronic devices, human‐machine interfaces, and implantable electronic devices, are introduced. Lastly, the challenges faced in the future developments of chemical modification methods are discussed, thereby guiding researchers to the use of chemical modification methods for the improvement of charge density for further exploration. [ABSTRACT FROM AUTHOR]

The high‐efficiency conversion of water drop mechanical energy into electrical energy has always been an urgent issue in the development and utilization of raindrop energy. In this work, a novel drum‐like triboelectric nanogenerator (D‐TENG) with robust self‐cleaning superhydrophobic features is developed to harvest water drop energy. An elastic superhydrophobic cellulose paper is created by spray‐coating nanofumed silica dispersed in a thermoplastic elastomer solution, followed by treatment with triethoxy‐1H,1H,2H,2H‐tridecafluoro‐n‐octylsilane. When raindrops hit the D‐TENG surface, the superhydrophobic cellulose paper will vibrate and periodic contact and separation with polytetrafluoroethylene will occur to generate electricity. The results demonstrate that when a 6 mm water drop falls from a height of 2.5 m and hits the D‐TENG, the generated voltage output can reach a peak of 21.6 V and charge transfer of 10 nC. The output power of the D‐TENG can reach 16 µW per droplet, which is more than 13.3 times that generated from the previous TENGs based on the electrostatic induction of water droplets. These results indicate that the superhydrophobic cellulose paper‐based D‐TENG is potentially a strong candidate for harvesting energy from raindrops, thereby making it a promising sustainable energy source for next‐generation electronics. [ABSTRACT FROM AUTHOR]

aim of this study was to investigate the anti-cancer effects of Xiaoai Jiedu Recipe (XJR) on HCC development and its underlying mechanisms. Methods: The expression of microRNA-29a (miR-29a) and signal transducer and activator of transcription 3 (STAT3) in HCC tissues and cells was determined by quantitative real-time polymerase chain reaction. The proliferation, migration, and invasion of HCC cells were measured by 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide, wound-healing, and transwell assays, respectively. The regulatory relationship between miR-29a and STAT3 in HCC was predicted by TargetScan and analyzed by luciferase reporter and RNA pull-down assays. The protein expression of matrix metalloproteinase (MMP)-2/9 and STAT3 was detected by Western blotting. A xenograft tumor mouse model was established, and tumor weight and volume were measured. Results: The expression of miR-29a was significantly decreased in HCC tissues and cells compared with that in normal tissues and cells. The up-regulation of miR-29a was related with lymph node metastasis and tumor node metastasis stage. XJR treatment significantly increased the expression of miR-29a, decreased cell viability, migration, and invasion, and reduced the protein expression of MMP-2/9 in HCC cells in a concentration-dependent manner. The anti-tumor effect of XJR on HCC cells was reversed by treatment with miR-29a inhibitor. STAT3 was predicted as a target of miR-29a, and its expression was negatively regulated by miR-29a. Moreover, STAT3 knockdown suppressed the malignant behavior of HCC cells, and its anti-tumor function was reversed by treatment with miR-29a inhibitor. Furthermore, XJR treatment inhibited tumor growth in mice through elevating miR-29a expression and inhibiting STAT3 expression. Conclusion: XJR suppressed the development of HCC via regulating miR-29a and STAT3. [ABSTRACT FROM AUTHOR]

Formalized knowledge representation is the foundation of Big Data computing, mining and visualization. Current knowledge representations regard information as items linked to relevant objects or concepts by tree or graph structures. However, geographic knowledge differs from general knowledge, which is more focused on temporal, spatial, and changing knowledge. Thus, discrete knowledge items are difficult to represent geographic states, evolutions, and mechanisms, e.g., the processes of a storm "{9:30-60 mm-precipitation}-{12:00-80 mm-precipitation}-...". The underlying problem is the constructors of the logic foundation (ALC description language) of current geographic knowledge representations, which cannot provide these descriptions. To address this issue, this study designed a formalized geographic knowledge representation called GeoKG and supplemented the constructors of the ALC description language. Then, an evolution case of administrative divisions of Nanjing was represented with the GeoKG. In order to evaluate the capabilities of our formalized model, two knowledge graphs were constructed by using the GeoKG and the YAGO by using the administrative division case. Then, a set of geographic questions were defined and translated into queries. The query results have shown that GeoKG results are more accurate and complete than the YAGO's with the enhancing state information. Additionally, the user evaluation verified these improvements, which indicates it is a promising powerful model for geographic knowledge representation. [ABSTRACT FROM AUTHOR]