Public Debt Frontier: A Python Toolkit for Analyzing Public Debt Sustainability

This study proposes a synthetic visual indicator with which to perform debt sustainability analysis using dynamic general equilibrium models. In a single diagram, we summarized the general equilibrium relationships among economic activity, government budget, and the maximum amount of sustainable public debt. Then, we measured sustainability using the distance of actual debt from the model-consistent maximum debt. This indicator can be implemented with any DSGE model;as a backing theory, we used a neoclassical model augmented with endogenous tax revenues, disaggregated public spending, different production technologies for public and private goods, non-atomistic wage setters in public labor (unions), and a fully specified maturity curve for public bonds. We provided an example of its usage using the case of Greece during the last public debt crisis. To perform the numerical analysis, we developed original software, whose advantage is allowing an audience without expertise in DSGE models to perform general equilibrium debt sustainability analyses without requiring an understanding of the technicalities of DSGE models.

The Autophagy, Inflammation and Metabolism Center international eSymposium - an early-career investigators' seminar series during the COVID-19 pandemic.

The Autophagy, Inflammation and Metabolism (AIM) Center organized a globally accessible, virtual eSymposium during the COVID-19 pandemic in 2020. The conference included presentations from scientific leaders, as well as a career discussion panel, and provided a much-needed platform for early-career investigators (ECIs) to showcase their research in autophagy. This Perspective summarizes the science presented by the ECIs during the event and discusses the lessons learned from a virtual meeting of this kind during the pandemic. The meeting was a learning experience for all involved, and the ECI participants herein offer their thoughts on the pros and cons of virtual meetings as a modality, either as standalone or hybrid events, with a view towards the post-pandemic world.

Cerebral Venous Sinus Thrombosis in the COVID-19 Pandemic.

BACKGROUND: Recent studies have noted concern for increased thromboembolic events in the setting of Coronavirus Disease 2019 (COVID-19). Cerebral venous sinus thrombosis (CVST) is a form of thromboembolism that has been observed as a neuro-ophthalmologic complication of COVID-19. METHODS: Review of the scientific literature. RESULTS: In this article, we report an overview of CVST epidemiology, clinical presentation, diagnostics, disease pathophysiology, and management in the setting of COVID-19. CONCLUSION: CVST is an uncommon thromboembolic event with variable phenotypes and multiple etiologies. Neurologic complications can be severe, including significant visual deficits and death. Current observations suggest that the risk of CVST may be profoundly impacted by this novel COVID-19 pandemic, thus prompting increased attention to disease presentation, pathogenesis, and management.