Governing in the face of a global crisis: When do voters punish and reward incumbent governments?

The recent COVID-19 pandemic offers a rare opportunity to understand how citizens attribute responsibility for governments' responses to unanticipated negative-and in this case, systemic-exogenous shocks. Classical accounts of responsibility are complicated when crises are pervasive, involve multiple valence dimensions, and where individuals can make relative assessments of performance. We fielded a conjoint experiment in 16 countries with 22,147 respondents.

On the importance of data curation for knowledge mining in antiviral research.

The recent severe acute respiratory syndrome coronavirus 2 pandemic has clearly exemplified the need for broad-spectrum antiviral (BSA) medications. However, previous outbreaks show that about one year after an outbreak, interest in antiviral research diminishes and the work toward an effective medication is left unfinished. Martin et al.

One size does not fit all: revising traditional paradigms for assessing accuracy of QSAR models used for virtual screening.

Traditional best practices for quantitative structure activity relationship (QSAR) modeling recommend dataset balancing and balanced accuracy (BA) as the key desired objective of model development. This study explores the value of the conventional norms in the context of using QSAR models for virtual screening of modern large and ultra-large chemical libraries. For this increasingly common task, we now recommend the use of models with the highest positive predictive value (PPV) built on imbalanced training sets as preferred virtual screening tools.

Applications of Machine Learning Approaches for the Discovery of SARS-CoV-2 PLpro Inhibitors.

The global impact of SARS-CoV-2 highlights the need for treatments beyond vaccination, given the limited availability of effective medications. While Pfizer introduced , an FDA-approved antiviral targeting the SARS-CoV-2 main protease (Mpro), this study focuses on designing new antivirals against another protease, papain-like protease (PLpro), which is crucial for viral replication and immune suppression. NCATS/NIH performed a high-throughput screen of ∼15,000 molecules from an internal molecular library, identifying initial hits with a 0.

A High-Throughput Screening Pipeline to Identify Methyltransferase and Exonuclease Inhibitors of SARS-CoV-2 NSP14.

SARS-CoV-2 infections led to a worldwide pandemic in 2020. As of 2024, therapeutics against SARS-CoV-2 have continued to be desirable. NSP14 is a dual-function methyltransferase (MTase) and exonuclease (ExoN) with key roles in SARS-CoV-2 genome propagation and host immune system evasion.