Soaring cases of coronavirus disease (COVID-19) are pummeling the global health system. Overwhelmed health facilities have endeavored to mitigate the pandemic, but mortality of COVID-19 continues to increase. Here, we present a mortality risk prediction model for COVID-19 (MRPMC) that uses patients’ clinical data on admission to stratify patients by mortality risk, which enables prediction of physiological deterioration and death up to 20 days in advance. This ensemble model is built using four machine learning methods including Logistic Regression, Support Vector Machine, Gradient Boosted Decision Tree, and Neural Network. We validate MRPMC in an internal validation cohort and two external validation cohorts, where it achieves an AUC of 0.9621 (95% CI: 0.9464–0.9778), 0.9760 (0.9613–0.9906), and 0.9246 (0.8763–0.9729), respectively. This model enables expeditious and accurate mortality risk stratification of patients with COVID-19, and potentially facilitates more responsive health systems that are conducive to high risk COVID-19 patients.

Obesity increases the risk for a number of diseases including cardiovascular diseases and type 2 diabetes. Excess saturated fatty acids (SFAs) in obesity play a significant role in cardiovascular diseases by activating innate immunity responses. However, the mechanisms by which SFAs activate the innate immune system are not fully known. Here we report that palmitic acid (PA), the most abundant circulating SFA, induces myocardial inflammatory injury through the Toll-like receptor 4 (TLR4) accessory protein MD2 in mouse and cell culture experimental models. Md2 knockout mice are protected against PA- and high-fat diet-induced myocardial injury. Studies of cell surface binding, cell-free protein–protein interactions and molecular docking simulations indicate that PA directly binds to MD2, supporting a mechanism by which PA activates TLR4 and downstream inflammatory responses. We conclude that PA is a crucial contributor to obesity-associated myocardial injury, which is likely regulated via its direct binding to MD2.

Autophagy dysfunction is a common feature in neurodegenerative disorders characterized by accumulation of toxic protein aggregates. Increasing evidence has demonstrated that activation of TFEB (transcription factor EB), a master regulator of autophagy and lysosomal biogenesis, can ameliorate neurotoxicity and rescue neurodegeneration in animal models. Currently known TFEB activators are mainly inhibitors of MTOR (mechanistic target of rapamycin [serine/threonine kinase]), which, as a master regulator of cell growth and metabolism, is involved in a wide range of biological functions. Thus, the identification of TFEB modulators acting without inhibiting the MTOR pathway would be preferred and probably less deleterious to cells. In this study, a synthesized curcumin derivative termed C1 is identified as a novel MTOR-independent activator of TFEB. Compound C1 specifically binds to TFEB at the N terminus and promotes TFEB nuclear translocation without inhibiting MTOR activity. By activating TFEB, C1 enhances autophagy and lysosome biogenesis in vitro and in vivo. Collectively, compound C1 is an orally effective activator of TFEB and is a potential therapeutic agent for the treatment of neurodegenerative diseases.