Background. As a type of malignant tumor, head and neck squamous cell carcinoma (HNSCC) seriously threatens human health. This study is aimed at constructing a new, reliable prognostic model. Method. The gene expression profile data of HNSCC patients were downloaded from the Gene Expression Omnibus and The Cancer Genome Atlas databases. The immune-related differentially expressed genes (IRDEGs) related to HNSCC were identified. We then used Cox regression analysis and least absolute shrinkage and selection operator (LASSO) analysis to explore IRDEGs related to the HNSCC prognosis and to construct and validate a risk scoring model and used ESTIMATE to evaluate tumor immune infiltration in HNSCC patients. Finally, we validated IGSF5 expression and function in HNSCC cells. Results. A total of 1,195 IRDEGs were found from the GSE65858 dataset. Thirty-one of the 1,195 IRDEGs were associated with the prognosis of HNSCC. Nine key IRDEGs were further selected using the LASSO method, and a risk scoring model was established for predicting the survival of HNSCC patients. According to the risk scoring model, the prognosis of patients in the high-risk group was worse than that of the low-risk group; the high-risk group had significantly higher immune scores than the low-risk group; and between the high- and low-risk samples, there were significant differences in the proportion of 10 types of cells, including naive cells, plasma cells, and resting CD4+ memory T cells. IGSF5 has low expression in HNSCC, and overexpression of IGSF5 significantly impaired HNSCC cell proliferation. Conclusion. This prognostic risk assessment model can help systematically evaluate the survival prognosis of HNSCC patients and provides a new research direction for the improvement of the survival prognosis of HNSCC patients in clinical practice.

Respiratory syncytial virus (RSV) is a common virus that causes respiratory infection, especially severe respiratory infection in infants and young children, the elderly people over 65 years old, and people with weak immunity. Currently, RSV infection has no effective vaccine and antiviral treatment. The number of deaths due to RSV infection increases every year. Moreover, RSV A infection occurs in a large number and has severe clinical symptoms and complications than RSV B infection. Therefore, the development of a simple, rapid, and inexpensive detection method with high amplification efficiency, high sensitivity, and specificity is very important for the diagnosis of RSV A or RSV B infection, which can help in the early clinical medication and prevent the progress of the disease. Therefore, we developed an integrated trinity test with an RPA-CRISPR/Cas12a-fluorescence (termed IT-RAISE) assay system to detect RSV A or RSV B. The characteristic of the IT-RAISE system is that after target recognition, the reporter single-stranded DNA (ssDNA) is cleaved by Cas12a that is activated by different crRNAs to detect the generated fluorescent signal. This method is simple and helps in adding all reagents rapidly. It is a high-sensitive method that can detect 1.38 × 101 copies/μl of the target sequences, and it can distinguish RSV A or RSV B infection within 37 min. In addition, clinical specimens were detected for IT-RAISE system. It was found that the sensitivity and specificity of RSV A were 73.08 and 90%, respectively, and those of RSV B were 42.86 and 93.33%, respectively. The cost of ONE specimen for IT-RAISE system was approximately $ 2.6 (excluding rapid RNA extraction and reverse transcription costs). IT-RAISE system has good clinical application prospects for detecting RSV A or RSV B infection; it is a simple, rapid, and inexpensive method with high amplification efficiency, high sensitivity, and high specificity. The IT-RAISE system might also detect other viral or bacterial infections.

Background. Lung adenosquamous carcinoma (LASC) is a special type of lung cancer. LASC is a malignant tumor with strong aggressiveness and a poor prognosis. Previous studies have revealed that microRNAs (miRNAs) are widely involved in the development of tumors by targeting mRNA. This study is aimed at identifying the key mRNAs and miRNAs of LASC and constructing miRNA-mRNA networks for deeply comprehending the latent molecular mechanisms. Methods. mRNA dataset (GSE51852) and miRNA dataset (GSE51853) were extracted and downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were picked out by the GEO2R web tool. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were conducted in the DAVID database. The protein-protein interaction (PPI) network was performed and analyzed by using the STRING database and Cytoscape software, respectively. TransmiR v2.0 was applied to predict potential transcription factors of miRNAs. The target genes of DEMs were predicted in the miRWalk database. Results. In comparison to normal tissues, a total of 1458 DEGs (511 upregulated and 947 downregulated) and 13 DEMs (5 upregulated and 8 downregulated) were screened out in LASC tissues. The PPI network of the DEGs displayed five key modules and seventeen hub genes. Six target genes of the DEMs were predicted, and five essential miRNA-mRNA regulatory pairs were established. Ensuingly, CENPF, one of the target genes, was also the hub genes of GSE51852, which was obtained from MCODE and cytoHubba and regulated by hsa-miR-205. Conclusions. We constructed the miRNA-mRNA regulatory pairs, which are helpful to study the potential regulatory mechanisms and find out promising diagnosis biomarkers and therapeutic targets for LASC.

Respiratory syncytial virus (RSV) infection is known as a risk factor for chronic obstructive pulmonary disease (COPD). RSV infection induces the upregulation of Toll-like receptor 3 (TLR3). This study aimed to investigate the association of TLR3 with RSV induced acute exacerbations of chronic obstructive pulmonary disease (AECOPD).Serum/sputum samples from AECOPD patients, stable chronic obstructive pulmonary disease (SCOPD) patients, and healthy controls were collected. Nested PCR was used to detect RSV. The lung function parameters were assessed by blood gas and lung function analysis. The expression levels of inflammatory factors in sputum and serum samples were determined by enzyme-linked immunosorbent assay. BEAS-2B cell lines were infected with RSV, and the expression of TLR3 mRNA was determined by PCR and the levels of inflammatory factors were also investigated. The presence of RSV was detected in 3 SCOPD and 8 AECOPD patients, but not in healthy patients. The expression levels of TNF-α and IRF-3 in both sputum and serum samples of RSV-positive group were significantly higher than in RSV-negative group. TLR3 mRNA levels in RSV-positive group were significantly higher than those in RSVnegative group. Interestingly, the level of TLR3 mRNA expression was negatively correlated with oxygenation index and lung function parameters. Furthermore, BEAS-2B cells infected with RSV led to significant increase of the expression of TLR3 mRNA and inflammatory factors IFN-β, IL-13, IL-32, and TNF-α. Our observations indicate that AECOPD is associated with RSV infection and the upregulation of TLR3.