Chronic rhinosinusitis is a process involving a number of adverse changes in the mucosa of the paranasal sinuses and nasal polyps. The main histological features of tissue remodeling are changes in epithelial structure, oedema, degradation of ECM (extracellular matrix), angiogenesis, and subepithelial fibrosis. In this study, patients were divided into two groups: group 1—patients with CRSwNP (chronic rhinosinusitis with nasal polyps) taking a nasal steroid and an oral steroid in the preoperative period, and group 2—patients with CRSwNP taking only the nasal steroid in the preoperative period. All samples were subject to histopatologic evaluation. The aim of this study was to investigate the effect of oral corticosteroids and topical steroids on the tissue of paranasal sinuses. We have shown statistically significant decreases in tissue eosinophilia per 5HPF and decreased fibrosis in group 1. No significant differences were presented in the percentage of total tissue oedema, epithelium, neutrophils, basement membrane thickening and vessels. Using systemic administration of 40 mg of prednisone for seven days decreased the counts of eosinophils and decreased fibrosis in the nasal polyps tissue in CRSwNP.

The emergence of clinical resistance to currently available systemic therapies forces us to rethink our approach to clear cell renal cell carcinoma (ccRCC). The ability to influence ccRCC evolution by inhibiting processes that propel it or manipulating its course may be an adequate strategy. There are seven deterministic evolutionary trajectories of ccRCC, which correlate with clinical phenotypes. We suspect that each trajectory has its own unique weaknesses that could be exploited. In this review, we have summarized recent advances in the treatment of ccRCC and demonstrated how to improve systemic therapies from the evolutionary perspective. Since there are only a few evolutionary trajectories in ccRCC, it appears feasible to use them as potential biomarkers for guiding intervention and surveillance. We believe that the presented patient stratification could help predict future steps of malignant progression, thereby informing optimal and personalized clinical decisions.