Identification of immune-associated prognostic biomarkers in lung adenocarcinoma on the basis of gene co-expression network.

Objective: We aimed to explore immune-related prognosis genes of lung adenocarcinoma (LUAD).Materials and methods: TCGA-LUAD and GSE31210 data sets were accessed from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) respectively. By using "WGCNA" R package, we established a gene co-expression network and clustered genes into various modules. The correlation between immune scores and module eigengenes by using Pearson analysis. Screened hub genes and constructed prognostic model by using LASSO and Cox regression analysis. Evaluated model by survival analysis and receiver operating characteristic (ROC) curves. Hub genes expression in clinical tissues of LUAD patients by qRT-PCR analysis. ssGSEA and TIMER (a website tool for examination of different immune cells in different cancers) analyzed immune correlation of hub genes. Gene set variation analysis (GSVA) uncovered difference of signal pathway between high- and low-risk score group.Results: We found that brown module significantly correlated with the immune scores of immune cells. Therefore, we constructed a 7-gene prognostic model based on brown module genes, and indicated that this model possessed good predictive performance. Patients in training and validation sets were stratified into the high- and low-risk group using this model. Also, hub genes CDCP1, PLSCR1 and CD79A were highly expressed in clinical tissues of LUAD patients, while ID1, CLEC7A, KIAA1324 and CMTM7 were lowly expressed. Both ssGSEA and TIMER revealed a significant negative correlation between risk score and B cell infiltration. Additionally, some signal pathways were suppressed in the high-risk group.Conclusion: We identified 7 immune-associated prognostic markers, which may play vital roles in LUAD and could be used as hopeful targets for immunotherapy of LUAD.

Removal of styrene in air stream by absorption combined with electrochemical oxidation.

Aqueous solution absorptions are widely used as an effective way for the treatment of noxious gases discharged from various industrial processes. However, this technology may encounter problems in removing gaseous pollutants with low Henry constants, such as styrene from contaminated air. In this study, a novel electrochemical absorption reactor was devised to remove these air pollutants. The reactor consists of five pairs of stacked mesh electrodes. Each pair of mesh electrodes consists of a Ti/RuO2 anode and a Ti cathode. The dimension of mesh electrode is 100 mm × 100 mm with 3 mm × 5 mm rhombic holes evenly distributed. The distance between two neighbouring electrodes is 25 mm. The simulated gas was introduced into the reactor from the bottom of the reactor by a gas distributor. The experimental result shows that styrene in the air was effectively removed by the electrochemical absorption reactor, and the removal increased with the increase of current density applied to the reactor. It was found that almost 100% styrene removal was achieved in 1% NaCl solution with 1 pH value and a current density of 0.04 A/cm2 applied to the reactor. The major liquid phase products from styrene oxidation were confirmed to be 1-Phenyl-1, 2-ethanediol and benzaldehyde.