Background: Rapid advances in transcriptomic profiles have resulted in recognizing IRLs (immune-related long noncoding RNAs), as modulators of the expression of genes related to immune cells that mediate immune inhibition as well as immune stimulatory, indicating LncRNAs play fundamental roles in immune modulation. Hence, we establish an IRL classifier to precisely predict prognosis and immunotherapeutic efficiency in laryngeal squamous cell carcinoma (LSCC). Methods: LSCC RNA-seq (RNA sequencing) datasets, somatic mutation data, and corresponding clinicopathologic information were acquired from TCGA (the Cancer Genome Atlas) and Gene Expression Omnibus (GEO) databases. Spearman correlation analysis identified LncRNAs associated with immune-related genes (IRG). Based on Lasso penalized regression and random forest (RF), we constructed an IRL classifier associated with prognosis. GEO database was utilized to validate the IRL classifier. The predictive precision and clinical application of the IRL classifier were assessed and compared to clinicopathologic features. The immune cell infiltration of LSCC was calculated via CIBERSORTx tools and ssGSEA (single-sample gene set enrichment analysis). Then, we systematically correlated the IRL classifier with immunological characteristics from multiple perspectives, such as immune-related cells infiltrating, tumor microenvironment (TME) scoring, microsatellite instability (MSI), tumor mutation burden (TMB), and chemokines. Finally, the TIDE (tumor immune dysfunction and exclusion) algorithm was used to predict response to immunotherapy. Results: Based on machine learning approach, three prognosis-related IRLs (BARX1-DT, KLHL7-DT, and LINC02154) were selected to build an IRL classifier. The IRL classifier could availably classify patients into the low-risk and high-risk groups based on the different endpoints, including recurrence-free survival (RFS) and overall survival (OS). In terms of predictive ability and clinical utility, the IRL classifier was superior to other clinical characteristics. Encouragingly, similar results were observed in the GEO databases. Immune infiltration analysis displayed immune cells that are significantly richer in low-risk group, CD8 T cells and activated NK cells via CIBERSORTx algorithm as well as activated CD8 T cell via ssGSEA. Additionally, compared with the high-risk group, immune score, CD8 T effector was higher in the low-risk group, yet stromal score, score of p53 signaling pathway and TGFher in the Tx algorithm, was lower in the low-risk group. Corresponding results were confirmed in GEO dataset. Finally, TIDE analysis uncovered that the IRL classifier may be effectually predict the clinical response of immunotherapy in LSCC. Conclusion: Based on BARX1-DT, KLHL7-DT, and LINC02154, the IRL classifier was established, which can be used to predict the prognosis, immune infiltration status, and immunotherapy response in LSCC patients and might facilitate personalized counseling for immunotherapy.

The aim of this study was to explore the regulatory role of epoxide hydrolase 3 (EPHX3) in head and neck squamous cell carcinoma (HNSCC) and to analyze its bioinformatic function, as well as, to screen and predict the miRNAs that can regulate EPHX3 expression in HNSCC. We examined the expression profile and prognostic potential of EPHX3 in TCGA and GTEX databases and performed functional enrichment analysis of EPHX3 using string database. Subsequently, we analyzed the regulatory role of miRNAs on EPHX3, including expression analysis, correlation analysis, and survival analysis. In addition, we also used TIMER to investigate the relationship among EPHX3 expression level, immune checkpoints, and immune infiltration in HNSCC. The results of data analysis after TGCA showed that EPHX3 is a key regulator of tumorigenesis in 13 cancers and can be used as a marker of poor prognosis in HNSCC patients. Bioinformatics analysis revealed that miR-4713-3p is a key miRNA of EPHX3 in HNSCC. Together, our findings indicate that EPHX3 exerts its anticancer effects by suppressing tumor immune checkpoint expression and immune cell infiltration. Overall, our data uncovered miRNA-mediated EPHX3 downregulation as a contributor to poor HNSCC prognosis and reduced tumor immune infiltration.

A coumarin-based dual responsive fluorescent probe with a simple structure was developed for the detection of Cys and HSO ₃ ⁻ .

Chronic rhinosinusitis (CRS) is a complex condition brought on for many reasons, and its prevalence is rising gradually around the world. Xanthii Fructus (XF) has been used in the treatment of CRS for decades and is effective. The chemical and pharmacological profiles of XF, on the other hand, are still unknown and need to be clarified. The potential mechanisms of XF in CRS treatment were investigated using a network pharmacology approach in this study. OB and DL were in charge of screening the bioactive components in XF and drug-likeness. TCMSP and PubChem databases were used to identify prospective XF proteins, whereas GeneCards and the DisGeNET database were used to identify potential CRS genes. An interactive network of XF and CRS is built using the STRING database based on common goals identified by the online tool Venny. Cytoscape was used to visualize the topological characteristics of nodes, while the biological function pathways were identified by GO Knowledge Base, KEGG. There were 26 bioactive components and 115 potential targets in XF that bind to CRS or are considered therapeutically relevant. Five significant signaling pathways have been found for CRS by the pathway analysis including the HIF-1 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway, NOD-like receptor signaling pathway, and PI3K-Akt signaling pathway. We simultaneously confirmed that the PI3K-Akt pathway promotes the development of CRS. Finally, this study took a holistic approach to the pharmacological actions and molecular mechanisms of XF in the treatment of CRS. TNF, INS, CCL2, CXCL8, IL-10, VEGFA, and IL-6 have all been identified as potential targets for anti-inflammatory and immune-boosting effects. This network pharmacology prediction could be useful in manifesting the molecular mechanisms of the Chinese herbal compound XF for CRS.

Background: Sensorineural hearing loss (SNHL) is a multifactorial disorder with potential links to various physiological systems, including the cardiovascular system via blood lipid levels such as triglycerides (TG). This study investigates the causal relationship between TG levels and SNHL using Mendelian randomization (MR), which offers a method to reduce confounding and reverse causality by using genetic variants as instrumental variables. Methods: Utilizing publicly available genome-wide association study (GWAS) data, we performed a two-sample MR analysis. The initial analysis unveiled a causal relationship between TG (GWAS ID: ebi-a-GCST90018975) and SNHL (GWAS ID: finn b-H8_HL_SEN-NAS). Subsequent analysis validated this through MR with a larger sample size for TG (GWAS ID: ieu-b-111) and SNHL. To conduct the MR analysis, we utilized several methods including inverse-variance weighted (IVW), MR Egger, weighted median, and weighted mode. We also employed Cochrane’s Q test to identify any heterogeneity in the MR results. To detect horizontal pleiotropy, we conducted the MR-Egger intercept test and MR pleiotropy residual sum and outliers (MR-PRESSO) test. We performed a leave-one-out analysis to assess the sensitivity of this association. Finally, a meta-analysis of the MR results was undertaken. Results: Our study found a significant positive correlation between TG and SNHL, with OR values of 1.14 (95% CI: 1.07–1.23, p < 0.001) in the IVW analysis and 1.09 (95% CI: 1.03–1.16, p < 0.006) in the replicate analysis. We also found no evidence of horizontal pleiotropy or heterogeneity between the genetic variants (p > 0.05), and a leave-one-out test confirmed the stability and robustness of this association. The meta-analysis combining the initial and replicate analyses showed a significant causal effect with OR values of 1.11 (95% CI: 1.06–1.16, p = 0.01). Conclusion: These findings indicate TG as a risk factor for SNHL, suggesting potential pathways for prevention and intervention in populations at risk. This conclusion underscores the importance of managing TG levels as a strategy to mitigate the risk of developing SNHL.

Peroxynitrite (ONOO⁻), a highly reactive nitrogen species, which plays a crucial role in numerous physiological and pathological processes of cell functionalization. The anomalous concentration of ONOO⁻ may result in a range of diseases, such as arthritis, neurological disorders, and even cancer. Therefore, it is urgent to develop a simple and effective tool to monitor the fluctuation of ONOO⁻ levels in biological systems. Herein, an ultrafast fluorescent probe (HND-ONOO) is proposed to detect ONOO⁻, which displays brilliant fluorescence in less than 30s with a large Stokes shift. Furthermore, the probe exhibited the lower detection limit (48nM) and satisfactory results in differentiating ONOO⁻ from other related species. The probe that possesses good biocompatibility and low toxicity was employed to monitor the level of exogenous and endogenous ONOO⁻ in living cells. Thus, the probe HND-ONOO could be served as a potential imaging tool to visualize intracellular ONOO⁻ and understand the relationship between ONOO⁻ and inflammation.