The role of the IFI6 gene has been described in several cancers, but its involvement in esophageal cancer (ESCA) remains unclear. This study aimed to identify novel prognostic indicators for ESCA-targeted therapy by investigating IFI6’s expression, epigenetic mechanisms, and signaling activities. We utilized public data from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) to analyze IFI6’s expression, clinical characteristics, gene function, pathways, and correlation with different immune cells in ESCA. The TIMER2.0 database was employed to assess the pan-cancer expression of IFI6, while UALCAN was used to examine its expression across tumor stages and histology subtypes. Additionally, the KEGG database helped identify related pathways. Our findings revealed 95 genes positively correlated and 15 genes negatively correlated with IFI6 in ESCA. IFI6 was over-expressed in ESCA and other cancers, impacting patient survival and showing higher expression in tumor tissues than normal tissues. IFI6 was also correlated with CD4+ T cells and B cell receptors (BCRs), both essential in immune response. GO Biological Process (GO BP) enrichment analysis indicated that IFI6 was primarily associated with the Type I interferon signaling pathway and the defense response to viruses. Intriguingly, KEGG pathway analysis demonstrated that IFI6 and its positively correlated genes in ESCA were mostly linked to the Cytosolic DNA-sensing pathway, which plays a crucial role in innate immunity and viral defense, and the RIG-I-like receptor (RLR) signaling pathway, which detects viral infections and activates immune responses. Pathways related to various viral infections were also identified. It is important to note that our study relied on online databases. Given that ESCA consists of two distinct subgroups (ESCC and EAC), most databases combine them into a single category. Future research should focus on evaluating IFI6 expression and its impact on each subgroup to gain more specific insights. In conclusion, inhibiting IFI6 using targeted therapy could be an effective strategy for treating ESCA considering its potential as a biomarker and correlation with immune cell factors.

Few efforts have been made regarding the optimization of porcine small intestinal submucosa (SIS) to improve its biocompatibility. This study aims to evaluate the effect of SIS degassing on the promotion of cell attachment and wound healing. The degassed SIS was evaluated in vitro and in vivo, compared with the nondegassed SIS control. In the cell sheet reattachment model, the reattached cell sheet coverage was significantly higher in the degassed SIS group than in the nondegassed group. Cell sheet viability was also significantly higher in the SIS group than in the control group. In vivo studies showed that the tracheal defect repaired by the degassed SIS patch showed enhanced healing and reductions in fibrosis and luminal stenosis compared to the nondegassed SIS control group, with the thickness of the transplanted grafts in the degassed SIS group significantly lower than those in the control group (346.82 ± 28.02 µm vs. 771.29 ± 20.41 µm, p < 0.05). Degassing the SIS mesh significantly promoted cell sheet attachment and wound healing by reducing luminal fibrosis and stenosis compared to the nondegassed control SIS. The results suggest that the degassing processing might be a simple and effective way to improve the biocompatibility of SIS.

Post-irradiation xerostomia remains a significant quality of life concern for patients with head and neck cancers. Conventional therapies offer limited effectiveness. This study aims to investigate the therapeutic potential of office-based salivary ductal steroid irrigation in patients with post-irradiation xerostomia. This single-center observational study recruited 147 head and neck cancer patients suffering from post-irradiation xerostomia between November 2020 and October 2022. All included subjects received at least one round of successful salivary ductal cannulation and irrigation. The primary measure of efficacy was improvement in subjective xerostomia and objective salivary amylase levels. A logistic regression was employed to evaluate factors affecting treatment responsiveness. The response rate among nasopharyngeal cancer (NPC) patients was 74.8%, and that among non-NPC cancer was 65.6%, without significant intergroup differences. The statistical analysis revealed no significant influence of age, gender, or disease stage on treatment responsiveness. Post-treatment salivary amylase levels were significantly higher in responsive non-NPC patients. In conclusion, salivary ductal steroid irrigation emerged as a promising therapeutic modality for the management of post-irradiation xerostomia in head and neck cancer patients. While no explicit factors were predictive of responsiveness, the high rate of symptom improvement suggests that this therapy may be a viable alternative for patients that are refractory to standard treatments.

During the SARS-CoV-2 pandemic, the use of in-laboratory positive airway pressure (PAP) titration studies was not routinely suggested. PAP pressure prediction calculations are emerging as alternative methods for the treatment of these patients. The underestimation of PAP titration pressure usually leads to unsatisfactory results for PAP therapy. This study aimed to evaluate the factors associated with the underestimation of PAP titration pressure when using PAP pressure prediction equations. Estimated PAP pressure formulas based on body mass index (BMI) and apnea-hypopnea index (AHI) were chosen to validate the accuracy of equations in the successful prediction of titration pressure. Among 341 adult patients diagnosed with obstructive sleep apnea (OSA) by overnight polysomnography (PSG) and who received overnight PAP titration in order to select a successful pressure, the mean age of the total subjects was 55.4 years old and 78.9% of patients were male. The average BMI and AHI scores were 27.1 ± 4.8 and 37 ± 21.7, respectively. After multivariate stepwise regression analysis, the odds ratio of participants with a pretitration AHI was 1.017 (95% CI: 1.005–1.030). Only the severity of OSA was significantly different between the underestimated group and the adequately assessed group. In conclusion, a high AHI, but not BMI, is associated with an underestimated CPAP titration pressure in adult patients with OSA.

Head and neck squamous cancer (HNSC) is a prevalent malignancy with a complex genetic profile. Tumor Mutational Burden (TMB) is an emerging biomarker associated with prognostic and therapeutic implications. In this study, we aimed to develop machine-learning models for predicting TMB and patient survival using RNA sequencing data and clinical features. Methods: We collected RNA sequencing data and clinical information of HNSC patients from Gene Expression Omnibus (GEO) (GSE142083) and The Cancer Genome Atlas (TCGA) databases. Machine learning models, including Random Forest, Support Vector Machine (SVM), k-Nearest Neighbors (kNN), and Logistic Regression, were built to predict TMB levels based on patient gene expression profiles. The top 100 important features (genes) were selected from these models to create a survival prediction model. Results: Among the tested models, Random Forest showed the highest accuracy (0.8011), followed by SVM (0.796), kNN (0.777), and logistic regression (0.704). Using the top 100 important genes, we developed a model to predict HNSC patient survival (under 3 years, 3--5 years, and over 5 years). Random forest achieved an accuracy of 0.70, while SVM and kNN reached 0.65. We identified five genes (KRT14, KRT6B, COL1A1, FN1, KRT6C) most closely related to TMB and patient survival. Through KEGG pathway analysis and neural network approaches, we discovered that these genes play a significant role in three pathways: PI3K-Akt signaling pathway, Human papillomavirus infection, and Bacterial invasion of epithelial cells. In Conclusion, our study highlights the potential of machine learning in integrating bioinformatics for predicting TMB and patient survival in HNSC. The identified genes (KRT14, KRT6B, COL1A1, FN1, KRT6C) and related pathways may serve as potential biomarkers and therapeutic targets in HNSC treatment and prognosis.