From apparent pseudoprogression to durable complete remission of expansile destructive sinonasal mucosal melanoma under pembrolizumab after primary endoscopic resection: A case report.

Head and neck mucosal melanoma is a rare but highly aggressive malignant tumor that usually has a poor prognosis. We describe a 53-year-old male patient, having no any medical history, with left maxillary sinus mucosal melanoma causing bilateral lung metastasis. Rapid tumor regrowth was observed on the 49th day after radical tumor resection. Subsequent pembrolizumab immunotherapy initially elicited pseudoprogression, for which add-on radiation therapy was carried out during maintenance pembrolizumab. A gradual decrease in tumor volume and complete remission were observed by a series of magnetic resonance imaging scans and lung windows of a computer tomography scan of chest. At the 29-month follow-up, the patient was rendered disease-free. In conclusion, head and neck mucosal melanoma may regrow rapidly after surgical resection and pseudoprogression could be frightening during immunotherapy. Subsequent single-agent pembrolizumab plus localized radiation therapy aiming to release more tumor antigens may offer the possibility of long-term remission.

Complexity of cardiac signals for predicting changes in alpha-waves after stress in patients undergoing cardiac catheterization.

The hierarchical interaction between electrical signals of the brain and heart is not fully understood. We hypothesized that the complexity of cardiac electrical activity can be used to predict changes in encephalic electricity after stress. Most methods for analyzing the interaction between the heart rate variability (HRV) and electroencephalography (EEG) require a computation-intensive mathematical model. To overcome these limitations and increase the predictive accuracy of human relaxing states, we developed a method to test our hypothesis. In addition to routine linear analysis, multiscale entropy and detrended fluctuation analysis of the HRV were used to quantify nonstationary and nonlinear dynamic changes in the heart rate time series. Short-time Fourier transform was applied to quantify the power of EEG. The clinical, HRV, and EEG parameters of postcatheterization EEG alpha waves were analyzed using change-score analysis and generalized additive models. In conclusion, the complexity of cardiac electrical signals can be used to predict EEG changes after stress.