Machine Learning-Based Prediction of COVID-19 Prognosis Using Clinical and Hematologic Data.

The coronavirus disease 2019 (COVID-19) pandemic is challenging healthcare systems worldwide. The prediction of disease prognosis has a critical role in confronting the burden of COVID-19. We aimed to investigate the feasibility of predicting COVID-19 patient outcomes and disease severity based on clinical and hematological parameters using machine learning techniques.

Rapamycin treatment correlates changes in primary cilia expression with cell cycle regulation in epithelial cells.

Primary cilia are sensory organelles that regulate cell cycle and signaling pathways. In addition to its association with cancer, dysfunction of primary cilia is responsible for the pathogenesis of polycystic kidney disease (PKD) and other ciliopathies. Because the association between cilia formation or length and cell cycle or division is poorly understood, we here evaluated their correlation in this study.