Salivary IgA and vimentin differentiate in vitro SARS-CoV-2 infection: a study of 290 convalescent COVID-19 patients

SARS-CoV-2 initially infects cells in the nasopharynx and oral cavity. The immune system at these mucosal sites plays a crucial role in minimizing viral transmission and infection. To develop new strategies for preventing SARS-CoV-2 infection, this study aimed to identify proteins that protect against viral infection in saliva. We collected 551 saliva samples from 290 healthcare workers who had tested positive for COVID-19, before vaccination, between June and December 2020. The samples were categorized based on their ability to block or enhance infection using in vitro assays. Mass spectrometry and ELISA experiments were used to identify and measure the abundance of proteins that specifically bind to SARS-CoV-2 antigens. IgA specific to SARS-CoV-2 antigens was detectable in over 83% of the convalescent saliva samples. We found that concentrations of anti-RBD IgA >500 pg/µg total protein in saliva correlates with reduced viral infectivity in vitro. However, there is a dissociation between the salivary IgA response to SARS-CoV-2, and systemic IgG titres in convalescent COVID19 patients. Then, using an innovative technique known as spike-baited mass spectrometry, we identified novel spike-binding proteins in saliva, most notably vimentin, which correlated with increased viral infectivity in vitro, could serve as a therapeutic target against COVID-19

Impact of a Randomized Campus/Community Trial to Prevent High-Risk Drinking Among College Students

High-risk drinking by college students continues to pose a significant threat to public health. Despite increasing evidence of the contribution of community-level and campus-level environmental factors to high risk drinking, there have been few rigorous tests of interventions that focus on changing these interlinked environments. The Study to Prevent Alcohol Related Consequences (SPARC) assessed the efficacy of a comprehensive intervention using a community organizing approach to implement environmental strategies in and around college campuses. The goal of SPARC was to reduce high-risk drinking and alcohol-related consequences among college students

The James Webb Space Telescope Mission

Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least $4m$. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the $6.5m$ James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figure

Impact of a Randomized Campus/Community Trial to Prevent High-Risk Drinking Among College Students

BACKGROUND: High-risk drinking by college students continues to pose a significant threat to public health. Despite increasing evidence of the contribution of community-level and campus-level environmental factors to high risk drinking, there have been few rigorous tests of interventions that focus on changing these interlinked environments. The Study to Prevent Alcohol Related Consequences (SPARC) assessed the efficacy of a comprehensive intervention using a community organizing approach to implement environmental strategies in and around college campuses. The goal of SPARC was to reduce high-risk drinking and alcohol-related consequences among college students. METHODS: Ten universities in North Carolina were randomized to an Intervention or Comparison condition. Each Intervention school was assigned a campus/community organizer. The organizer worked to form a campus-community coalition, which developed and implemented a strategic plan to use environmental strategies to reduce high-risk drinking and its consequences. The intervention was implemented over a period of 3 years. Primary outcome measures were assessed using a web-based survey of students. Measures of high-risk drinking included number of days alcohol was consumed, number of days of binge drinking, and greatest number of drinks consumed (all in the past 30 days); and number of days one gets drunk in a typical week. Measures of alcohol-related consequences included indices of moderate consequences due to one’s own drinking, severe consequences due to one’s own drinking, interpersonal consequences due to others’ drinking, and community consequences due to others’ drinking (all using a past 30-day timeframe). Measure of alcohol-related injuries included (1) experiencing alcohol-related injuries and (2) alcohol-related injuries caused to others. RESULTS: We found significant decreases in the Intervention group compared to the Comparison group in severe consequences due to students’ own drinking and alcohol-related injuries caused to others. In secondary analyses, higher levels of implementation of the intervention were associated with reductions in interpersonal consequences due to others’ drinking and alcohol-related injuries caused to others. CONCLUSIONS: A community organizing approach promoting implementation of environmental interventions can significantly affect high-risk drinking and its consequences among college students

Fast and Efficient Root Phenotyping via Pose Estimation

Image segmentation is commonly used to estimate the location and shape of plants and their external structures. Segmentation masks are then used to localize landmarks of interest and compute other geometric features that correspond to the plant’s phenotype. Despite its prevalence, segmentation-based approaches are laborious (requiring extensive annotation to train) and error-prone (derived geometric features are sensitive to instance mask integrity). Here, we present a segmentation-free approach that leverages deep learning-based landmark detection and grouping, also known as pose estimation. We use a tool originally developed for animal motion capture called SLEAP (Social LEAP Estimates Animal Poses) to automate the detection of distinct morphological landmarks on plant roots. Using a gel cylinder imaging system across multiple species, we show that our approach can reliably and efficiently recover root system topology at high accuracy, few annotated samples, and faster speed than segmentation-based approaches. In order to make use of this landmark-based representation for root phenotyping, we developed a Python library (sleap-roots) for trait extraction directly comparable to existing segmentation-based analysis software. We show that pose-derived root traits are highly accurate and can be used for common downstream tasks including genotype classification and unsupervised trait mapping. Altogether, this work establishes the validity and advantages of pose estimation-based plant phenotyping. To facilitate adoption of this easy-to-use tool and to encourage further development, we make sleap-roots, all training data, models, and trait extraction code available at: https://github.com/talmolab/sleap-roots and https://osf.io/k7j9g/