The understanding of the interaction between disease dynamics and human behavior is an important and essential point to control infectious. Disease outbreak can be influenced by social distancing and vaccination. In this study, we introduce two compartmental models to derive the epidemic curve and analyze the individual’s behavior in spreading and controlling the COVID-19 epidemic. The first model includes Susceptible, Exposed, Infectious, Hospitalized, Recovered and Death compartments and in the second model, we added a new compartment namely, semi-susceptible individuals that are assumed to be more immune than the susceptible. A comparison of the two models shows that the second model provides a better fit to the daily infected cases from Egypt, Belgium, Japan, Nigeria, Italy, and Germany released by WHO. Finally, we added a vaccinated term to the model to predict how vaccination could control the epidemic. The model was applied on the record data from WHO.

Non-functioning pituitary adenomas (NFPAs) are typical pituitary macroadenomas in adults that are associated with increased mortality and morbidity. Although pituitary adenomas are commonly considered slow-growing benign brain tumors, numerous of them possess an invasive nature. Such tumors destroy sella turcica and invade the adjacent tissues such as the cavernous sinus and sphenoid sinus. The most critical obstacle for complete surgical removal in these cases is the high risk of damaging adjacent vital structures. Therefore, the development of novel therapeutic strategies for either early diagnosis through biomarkers or medical therapies to reduce the recurrence rate of NFPAs is imperative. Identification of gene interactions has paved the way for decoding complex molecular mechanisms, including disease-related pathways, and identifying the most momentous genes involved in a specific disease. Currently, our knowledge of the invasion of the pituitary adenoma at the molecular level is not sufficient. The current study aimed to identify critical biomarkers and biological pathways associated with invasiveness in the NFPAs using a three-way interaction model for the first time. In the current study, the Liquid association method was applied to capture the statistically significant triplets that are involved in NFPAs invasiveness. Subsequently, Random Forest analysis was applied to select the most important switch genes. Finally, gene set enrichment (GSE) and gene regulatory network (GRN) analyses were applied to trace the biological relevance of the statistically significant triplets. The results of this study suggest that “mRNA processing” and “spindle organization” biological processes are important in NFAPs invasiveness. Specifically, our results suggest Nkx3-1 and Fech as two switch genes in NFAPs invasiveness that may be a potential biomarkers or target genes, in this pathology.

Adenoid cystic carcinoma (ACC) is a slow-growing malignancy that most often occurs in the salivary glands. Although reasonable local control is usually achieved by tumor surgery and subsequent radiation therapy, recurrence at the same or distant site is the cause of treatment failure. Currently, no FDA-approved therapeutic target or diagnostic biomarker has been identified for this cancer. To find the therapeutic and diagnostic targets for ACC, we extracted the gene expression information from two GEO datasets. Different expression genes (DEGs) between ACC and normal samples were extracted and used to explore the biochemical pathways involved in ACC and create a protein-protein interaction (PPI) network.After analyzing the PPI network, 20 hub genes were introduced that have potential as diagnostic and therapeutic target. Among them, PLCG1 and EZH2 were introduced as new biomarkers in ACC that might have a high value in the diagnosis and treatment of ACC. Furthermore, by studying the roles of the hub genes in the enriched biochemical pathways, we found that most likely, IGF-1R/IR and PPARG pathways play a critical role in tumorigenesis and drug resistance in the ACC and have a high potential for selection as a therapeutic target in future studies.