Notes

Thorough Evaluation of Components Influencing Tremor Backslide soon after MRgFUS Thalamotomy: Any Case-Control Review.
New therapeutics are urgently needed to inhibit SARS-CoV-2, the virus responsible for the on-going Covid-19 pandemic. Nsp15, a uridine-specific endoribonuclease found in all coronaviruses, processes viral RNA to evade detection by RNA-activated host defense systems, making it a promising drug target. Previous work with SARS-CoV-1 established that Nsp15 is active as a hexamer, yet how Nsp15 recognizes and processes viral RNA remains unknown. Here this website report a series of cryo-EM reconstructions of SARS-CoV-2 Nsp15. The UTP-bound cryo-EM reconstruction at 3.36 Å resolution provides molecular details into how critical residues within the Nsp15 active site recognize uridine and facilitate catalysis of the phosphodiester bond, whereas the apo-states reveal active site conformational heterogeneity. We further demonstrate the specificity and mechanism of nuclease activity by analyzing Nsp15 products using mass spectrometry. Collectively, these findings advance understanding of how Nsp15 processes viral RNA and provide a structural framework for the development of new therapeutics.Interferon-induced transmembrane proteins (IFITMs) restrict infections by many viruses, but a subset of IFITMs enhance infections by specific coronaviruses through currently unknown mechanisms. Here we show that SARS-CoV-2 Spike-pseudotyped virus and genuine SARS-CoV-2 infections are generally restricted by expression of human IFITM1, IFITM2, and IFITM3, using both gain- and loss-of-function approaches. Mechanistically, restriction of SARS-CoV-2 occurred independently of IFITM3 S -palmitoylation sites, indicating a restrictive capacity that is distinct from reported inhibition of other viruses. In contrast, the IFITM3 amphipathic helix and its amphipathic properties were required for virus restriction. Mutation of residues within the human IFITM3 endocytosis-promoting YxxΦ motif converted human IFITM3 into an enhancer of SARS-CoV-2 infection, and cell-to-cell fusion assays confirmed the ability of endocytic mutants to enhance Spike-mediated fusion with the plasma membrane. Overexpression of TMPRSS2, which reportedly increases plasma membrane fusion versus endosome fusion of SARS-CoV-2, attenuated IFITM3 restriction and converted amphipathic helix mutants into strong enhancers of infection. In sum, these data uncover new pro- and anti-viral mechanisms of IFITM3, with clear distinctions drawn between enhancement of viral infection at the plasma membrane and amphipathicity-based mechanisms used for endosomal virus restriction. Indeed, the net effect of IFITM3 on SARS-CoV-2 infections may be a result of these opposing activities, suggesting that shifts in the balance of these activities could be coopted by viruses to escape this important first line innate defense mechanism.The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has emphasized the urgency to develop effective therapeutics. Drug repurposing screening is regarded as one of the most practical and rapid approaches for the discovery of such therapeutics. The 3C like protease (3CL pro ), or main protease (M pro ) of SARS-CoV-2 is a valid drug target as it is a specific viral enzyme and plays an essential role in viral replication. We performed a quantitative high throughput screening (qHTS) of 10,755 compounds consisting of approved and investigational drugs, and bioactive compounds using a SARS-CoV-2 3CL pro assay. Twenty-three small molecule inhibitors of SARS-CoV-2 3CL pro have been identified with IC50s ranging from 0.26 to 28.85 μM. Walrycin B (IC 50 = 0.26 µM), Hydroxocobalamin (IC 50 = 3.29 µM), Suramin sodium (IC 50 = 6.5 µM), Z-DEVD-FMK (IC 50 = 6.81 µM), LLL-12 (IC 50 = 9.84 µM), and Z-FA-FMK (IC 50 = 11.39 µM) are the most potent 3CL pro inhibitors. The activities of anti-SARS-CoV-2 viral infection was confirmed in 7 of 23 compounds using a SARS-CoV-2 cytopathic effect assay. #link# The results demonstrated a set of SARS-CoV-2 3CL pro inhibitors that may have potential for further clinical evaluation as part of drug combination therapies to treating COVID-19 patients, and as starting points for chemistry optimization for new drug development.Blind people have limited access to information about their surroundings, which is important for ensuring one's safety, managing social interactions, and identifying approaching pedestrians. With advances in computer vision, wearable cameras can provide equitable access to such information. However, the always-on nature of these assistive technologies poses privacy concerns for parties that may get recorded. We explore this tension from both perspectives, those of sighted passersby and blind users, taking into account camera visibility, in-person versus remote experience, and extracted visual information. We conduct two studies an online survey with MTurkers (N=206) and an in-person experience study between pairs of blind (N=10) and sighted (N=40) participants, where blind participants wear a working prototype for pedestrian detection and pass by sighted participants. Our results suggest that both of the perspectives of users and bystanders and the several factors mentioned above need to be carefully considered to mitigate potential social tensions.Spatial transformations are enablers in a variety of medical image analysis applications that entail aligning images to a common coordinate systems. Population analysis of such transformations is expected to capture the underlying image and shape variations, and hence these transformations are required to produce anatomically feasible correspondences. This is usually enforced through some smoothness-based generic metric or regularization of the deformation field. Alternatively, population-based regularization has been shown to produce anatomically accurate correspondences in cases where anatomically unaware (i.e., data independent) regularization fail. Recently, deep networks have been used to generate spatial transformations in an unsupervised manner, and, once trained, these networks are computationally faster and as accurate as conventional, optimization-based registration methods. However, the deformation fields produced by these networks require smoothness penalties, just as the conventional registration methods, and ignores population-level statistics of the transformations.
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