Proceedings of the National Academy of Sciences of the United States of America
-
Policymaking during a pandemic can be extremely challenging. As COVID-19 is a new disease and its global impacts are unprecedented, decisions are taken in a highly uncertain, complex, and rapidly changing environment. In such a context, in which human lives and the economy are at stake, we argue that using ideas and constructs from modern decision theory, even informally, will make policymaking a more responsible and transparent process.
-
The science around the use of masks by the public to impede COVID-19 transmission is advancing rapidly. In this narrative review, we develop an analytical framework to examine mask usage, synthesizing the relevant literature to inform multiple areas: population impact, transmission characteristics, source control, wearer protection, sociological considerations, and implementation considerations. A primary route of transmission of COVID-19 is via respiratory particles, and it is known to be transmissible from presymptomatic, paucisymptomatic, and asymptomatic individuals. ⋯ Given the current shortages of medical masks, we recommend the adoption of public cloth mask wearing, as an effective form of source control, in conjunction with existing hygiene, distancing, and contact tracing strategies. Because many respiratory particles become smaller due to evaporation, we recommend increasing focus on a previously overlooked aspect of mask usage: mask wearing by infectious people ("source control") with benefits at the population level, rather than only mask wearing by susceptible people, such as health care workers, with focus on individual outcomes. We recommend that public officials and governments strongly encourage the use of widespread face masks in public, including the use of appropriate regulation.
-
The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has emerged as a major threat to global health. Although varied SARS-CoV-2-related coronaviruses have been isolated from bats and SARS-CoV-2 may infect bat, the structural basis for SARS-CoV-2 to utilize the human receptor counterpart bat angiotensin-converting enzyme 2 (bACE2) for virus infection remains less understood. Here, we report that the SARS-CoV-2 spike protein receptor binding domain (RBD) could bind to bACE2 from Rhinolophus macrotis (bACE2-Rm) with substantially lower affinity compared with that to the human ACE2 (hACE2), and its infectivity to host cells expressing bACE2-Rm was confirmed with pseudotyped SARS-CoV-2 virus and SARS-CoV-2 wild virus. ⋯ Bats have extensive species diversity and the residues for RBD binding in bACE2 receptor varied substantially among different bat species. Notably, the Y41H mutant, which exists in many bats, attenuates the binding capacity of bACE2-Rm, indicating the central roles of Y41 in the interaction network. These findings would benefit our understanding of the potential infection of SARS-CoV-2 in varied species of bats.
-
Detecting fluorescence in the second near-infrared window (NIR-II) up to ∼1,700 nm has emerged as a novel in vivo imaging modality with high spatial and temporal resolution through millimeter tissue depths. Imaging in the NIR-IIb window (1,500-1,700 nm) is the most effective one-photon approach to suppressing light scattering and maximizing imaging penetration depth, but relies on nanoparticle probes such as PbS/CdS containing toxic elements. On the other hand, imaging the NIR-I (700-1,000 nm) or NIR-IIa window (1,000-1,300 nm) can be done using biocompatible small-molecule fluorescent probes including US Food and Drug Administration-approved dyes such as indocyanine green (ICG), but has a caveat of suboptimal imaging quality due to light scattering. ⋯ Using preclinical fluorophores such as IRDye-800, translation of ∼900-nm NIR molecular imaging of PD-L1 or EGFR greatly enhanced tumor-to-normal tissue ratio up to ∼20 from ∼5 and improved tumor margin localization. Further, deep learning greatly improved in vivo noninvasive NIR-II light-sheet microscopy (LSM) in resolution and signal/background. NIR imaging equipped with deep learning could facilitate basic biomedical research and empower clinical diagnostics and imaging-guided surgery in the clinic.