Chemresistive Detection of NO2 of ppb Level in Humid Air at 350 K Using Azo-Spaced Polycroconamide.

Organic molecules are of great interest for gas sensing applications. However, achieving high-performance gas sensors with high sensitivity, fast response, low consumption, and workability in humid conditions is still challenging. Herein, we report the rational design and synthesis of an ion-in-conjugation polymer, PADC (poly-4,4'-azodianiline-croconamide), obtained by the condensation of croconic acid with 4-4'diaminoazobenzene for gas sensing under humid conditions. The as-fabricated PADC-based gas sensor exhibits ultrahigh sensitivity (802.7 ppm-1 at 1 ppm), subppb detection limit, and high selectivity under humid air with an 80% humidity effect at a temperature down to 350 K. PADC shows good planarity, excellent thermostability, and a narrow band gap of 1.2 eV because of azobenzene fragments spacing previously repulsed biphenyl rings. Compared to previous humidity immunity works, PADC-based sensors realized humidity immunity at a relatively lower temperature, resulting in lower energy consumption.

The establishment of a hub differential gene model to predict prognosis in stage II and III right- and left-sided colon cancer patients.

BACKGROUND: It is now recognized that the symptoms of colon cancer differ according to whether the tumor is located on the left or right side of the patient. The results of the present study point to the differences in the tissue and embryonic origins of left- and right-sided colon cancer that cause the variations in molecular typing. The research purpose of this study is to establish a core differential gene scoring model and proved its effect. METHODS: We downloaded transcriptome data and clinical information from The Cancer Genome Atlas (TCGA). A total of 243 patients in stages II and III were grouped according to the colon cancer site. Then we screened for differential transcriptome products. The corresponding differential gene were performing a corresponding protein interaction analysis. We used 12 algorithms in Cytoscape to calculate the hub genes and a total of 37 hub genes were obtained finally. We extracted the first principal component value (PC1) of the hub genes to evaluate the effectiveness of screening. Cox regression analysis was performed for the differential genes. Finally, we performed a prognostic analysis on right-sided colon cancer patients using the BST2 gene, PC1 and relevant clinical information. RESULTS: After screening for differentially expressed genes, 37 hub genes were obtained with appropriate algorithms. PC1 showed differences in hub genes between left- and right-sided colon cancer patients. BST2 and 31 other genes were identified as significant by Cox regression analysis and were significantly mutated in patients with right-sided colon cancer. Finally, we selected the BST2 gene and relevant clinical information as the prognostic factors to build a scoring model. The prediction effect of the model was satisfied. CONCLUSIONS: We constructed a prognostic model based on BST2, PC1, and other relevant clinical information and proved its good effect.