8-Gene signature related to CD8+ T cell infiltration by integrating single-cell and bulk RNA-sequencing in head and neck squamous cell carcinoma.

Background: CD8+ T cells, a critical component of the tumor immune microenvironment, have become a key target of cancer immunotherapy. Considering the deficiency of robust biomarkers for head and neck squamous cell carcinoma (HNSCC), this study aimed at establishing a molecular signature associated with CD8+T cells infiltration. Methods: Single-cell RNA sequencing data retrieved from the Gene Expression Omnibus (GEO) database was analyzed to obtain the different cell types. Next, the cell proportions were investigated through deconvolution of RNA sequencing in the Cancer Genome Atlas (TCGA) database, and then the immune-related genes (IRGs) were identified by weighted gene co-expression network analysis (WGCNA). LASSO-Cox analysis was employed to establish a gene signature, followed by validation using a GEO dataset. Finally, the molecular and immunological properties, and drug responses between two subgroups were explored by applying "CIBERSORT", "ESTIMATE", and single sample gene set enrichment analysis (ssGSEA) methods. Results: A total of 215 differentially expressed IRGs were identified, of which 45 were associated with the overall survival of HNSCC. A risk model was then established based on eight genes, including DEFB1, AICDA, TYK2, CCR7, SCARB1, ULBP2, STC2, and LGR5. The low-risk group presented higher infiltration of memory activated CD4+ T cells, CD8+ T cells, and plasma cells, as well as a higher immune score, suggesting that they could benefit more from immunotherapy. On the other hand, the high-risk group showed higher abundance of activated mast cells and M2 macrophages, as well as a lower immune score. Conclusion: It was evident that the 8-gene signature could accurately predict HNSCC prognosis and thus it may serve as an index for clinical treatment.

Comprehensive analysis of immune cell infiltration and significant genes in head and neck squamous cell carcinoma.

OBJECTIVE: Immunotherapy directed at the tumor microenvironment is effective in the treatment of head and neck squamous cell carcinoma (HNSCC). In contrast, there has been a paucity of research on the relationship between the HNSCC microenvironment and prognostic outcome. Meanwhile, tumor immune cell infiltration (ICI) has emerged as a critical step in immunotherapy. METHODS: Two algorithms, CIBERSORT and ESTIMATE, were performed to evaluate the ICI view of 885 HNSCC patients using three databases: the Cancer Genome Atlas (TCGA), Arrayexpress, and Gene Expression Omnibus (GEO). RESULTS: Different ICI subtypes were identified. Following that, 57 different expression genes (DEGs) were discovered. The ICI scores of all patients were calculated using the Principal Component Analysis (PCA) algorithm. Additionally, an immune-related prognostic signature was developed and validated using 17 of 57 DEGs. Patients with a low-ICI or low-risk score had a higher infiltration immune-activated related cells and higher expression of most immune checkpoint-related molecules, indicating a better prognosis. Furthermore, using the pRRophetic algorithm, the sensitivities of many chemotherapeutic drugs were significantly different between two ICI subtypes or two risk groups. Moreover, a nomogram incorporating the ICI score, risk score, and clinical characteristics was developed and was capable of accurately predicting outcomes. CONCLUSION: The ICI score and 17-gene signature could improve HNSCC survival prediction, promote individual treatment strategies, and provide promising novel immunotherapy biomarkers.

Slow-release lubrication of artificial joints using self-healing polyvinyl alcohol/polyethylene glycol/ graphene oxide hydrogel.

New fabrication methods and lubrication materials must be developed to improve the lubrication performance of artificial joints and increase the lubrication duration. Herein, a novel polyvinyl alcohol/polyethylene glycol/graphene oxide (PVA/PEG/GO) hydrogel was prepared by a physical cross-linking method, and then the hydrogel and its sustained-release solution were used as lubricant for friction evaluation. The results demonstrated that the slow-release gel solution has good lubrication performance, and coefficient of friction (COF) is only 0.04, which is much lower than the COF of distilled water (about 0.08) under the same conditions. The structure characterization results revealed that no new materials are formed in the gel. The results of thermogravimetric analyses and differential scanning calorimetry demonstrated that the addition of GO may improve the network crosslinking structure of the PVA/PEG hydrogel and improve its mechanical strength. In addition, PVA/PEG/GO hydrogel has superior self-healing function. The self-healing hydrogel did not break again after being pulled under 200 G of weights. The PVA/PEG/GO hydrogel with excellent slow-release lubricating performance and self-healing properties provides a novel candidate for design of long-term lubricating artificial joints, and is expected to promote the progress of artificial joint lubrication applications.

Research on Multi-Dimensional Optimal Location Selection of Maintenance Station Based on Big Data of Vehicle Trajectory.

In order to rationally lay out the location of automobile maintenance service stations, a method of location selection of maintenance service stations based on vehicle trajectory big data is proposed. Taking the vehicle trajectory data as the demand points, the demand points are divided according to the region by using the idea of zoning, and the location of the second-level maintenance station is selected for each region. The second-level maintenance stations selected in the whole country are set as the demand points of the first-level maintenance stations. Considering the objectives of the two dimensions of cost and service level, the location model of the first-level maintenance stations under two-dimensional programming is established, and the improved particle swarm optimization algorithm and immune algorithm, respectively, are used to solve the problem. In this way, the first-level maintenance stations in each region are obtained. The example verification shows that the location selection results for the maintenance stations using the vehicle trajectory big data are reasonable and closer to the actual needs.

[Influence of Industrial Wastewater Quality on Advanced Treatment of Microbubble Ozonation].

The treatment performance of microbubble ozonation used for advanced treatment of actual pharmaceutical wastewater and tannery wastewater was investigated and compared to show the influence of complicated wastewater quality. The results showed that most organic pollutants in pharmaceutical wastewater and tannery wastewater could be degraded by microbubble ozonation effectively. and COD was removed simultaneously. In addition, the biodegradability was improved and the bio-toxicity was eliminated significantly. The ratios of COD amount removed and ozone amount consumed were 0.77 and 1.02, respectively, in such advanced treatment of pharmaceutical wastewater and tannery wastewater, indicating different ozone oxidation efficiencies between pharmaceutical wastewater and tannery wastewater. The main types of organic pollutants in pharmaceutical wastewater and tannery wastewater were determined by GC-MS and 3D-EEM, which showed the influence on treatment performance of microbubble ozonation. More refractory complex aromatic organic pollutants were found in pharmaceutical wastewater, which seemed more difficult to undergo degradation by microbubble ozone oxidation. As a result, the microbubble ozone oxidation of pharmaceutical wastewater was less efficient than that of tannery wastewater. The inorganic anions in both kinds of wastewater were unfavorable for ozone mass transfer, ozone decomposition, and·OH generation, which reduced the reaction efficiency of microbubble ozonation as well as biodegradability improvement. The lower concentrations of inorganic anions were better for microbubble ozonation.