Published and unpublished reports show that SARS-CoV-2 RNA in publicly owned treatment work (POTW) wastewater influent and solids is associated with new COVID-19 cases or incidence in associated sewersheds, but methods for comparing data collected from diverse POTWs to infer information about the relative incidence of laboratory-confirmed COVID-19 cases, and scaling to allow such comparisons, have not been previously established. Here, we show that SARS-CoV-2 N1 and N2 concentrations in solids normalized by concentrations of PMMoV RNA in solids can be used to compare incidence of laboratory confirmed new COVID-19 cases across POTWs. Using data collected at seven POTWs along the United States West Coast, Midwest, and East Coast serving ∼3% of the U.S. population (9 million people), we show that a 1 log change in N gene/PMMoV is associated with a 0.24 (range 0.19 to 0.29) log 10 change in incidence of laboratory confirmed COVID-19. Scaling of N1 and N2 by PMMoV is consistent, conceptually, with a mass balance model relating SARS-CoV-2 RNA to the number of infected individuals shedding virus in their stool. This information should support the application of wastewater-based epidemiology to inform the response to the COVID-19 pandemic and potentially future viral pandemics.

For quantitative phase imaging (QPI) based on transport-of-intensity equation (TIE), partially coherent illumination provides speckle-free imaging, compatibility with brightfield microscopy, and transverse resolution beyond coherent diffraction limit. Unfortunately, in a conventional microscope with circular illumination aperture, partial coherence tends to diminish the phase contrast, exacerbating the inherent noise-to-resolution tradeoff in TIE imaging, resulting in strong low-frequency artifacts and compromised imaging resolution. Here, we demonstrate how these issues can be effectively addressed by replacing the conventional circular illumination aperture with an annular one. The matched annular illumination not only strongly boosts the phase contrast for low spatial frequencies, but significantly improves the practical imaging resolution to near the incoherent diffraction limit. By incorporating high-numerical aperture (NA) illumination as well as high-NA objective, it is shown, for the first time, that TIE phase imaging can achieve a transverse resolution up to 208 nm, corresponding to an effective NA of 2.66. Time-lapse imaging of in vitro Hela cells revealing cellular morphology and subcellular dynamics during cells mitosis and apoptosis is exemplified. Given its capability for high-resolution QPI as well as the compatibility with widely available brightfield microscopy hardware, the proposed approach is expected to be adopted by the wider biology and medicine community.

India has experienced significant Land-Use and Land-Cover Change (LULCC) over the past few decades. In this context, careful observation and mapping of LULCC using satellite data of high to medium spatial resolution is crucial for understanding the long-term usage patterns of natural resources and facilitating sustainable management to plan, monitor and evaluate development. The present study utilizes the satellite images to generate national level LULC maps at decadal intervals for 1985, 1995 and 2005 using onscreen visual interpretation techniques with minimum mapping unit of 2.5 hectares. These maps follow the classification scheme of the International Geosphere Biosphere Programme (IGBP) to ensure compatibility with other global/regional LULC datasets for Remote Sens. 2015, 7 2403 comparison and integration. Our LULC maps with more than 90% overall accuracy highlight the changes prominent at regional level, i.e., loss of forest cover in central and northeast India, increase of cropland area in Western India, growth of peri-urban area, and relative increase in plantations. We also found spatial correlation between the cropping area and precipitation, which in turn confirms the monsoon dependent agriculture system in the country. On comparison with the existing global LULC products (GlobCover and MODIS), it can be concluded that our dataset has captured the maximum cumulative patch diversity frequency indicating the detailed representation that can be attributed to the on-screen visual interpretation technique. Comparisons with global LULC products (GlobCover and MODIS) show that our dataset captures maximum landscape diversity, which is partly attributable to the on-screen visual interpretation techniques. We advocate the utility of this database for national and regional studies on land dynamics and climate change research. The database would be updated to 2015 as a continuing effort of this study.

No abstract

Background Coastal marine environments are one of the most productive ecosystems on Earth. However, anthropogenic impacts exert significant pressure on coastal marine biodiversity, contributing to functional shifts in microbial communities and human health risk factors. However, relatively little is known about the impact of eutrophication—human-derived nutrient pollution—on the marine microbial biosphere. Results Here, we tested the hypothesis that benthic microbial diversity and function varies along a pollution gradient, with a focus on human pathogens and antibiotic resistance genes. Comprehensive metagenomic analysis including taxonomic investigation, functional detection, and ARG annotation revealed that zinc, lead, total volatile solids, and ammonia nitrogen were correlated with microbial diversity and function. We propose several microbes, including Planctomycetes and sulfate-reducing microbes as candidates to reflect pollution concentration. Annotation of antibiotic resistance genes showed that the highest abundance of efflux pumps was found at the most polluted site, corroborating the relationship between pollution and human health risk factors. This result suggests that sediments at polluted sites harbor microbes with a higher capacity to reduce intracellular levels of antibiotics, heavy metals, or other environmental contaminants. Conclusions Our findings suggest a correlation between pollution and the marine sediment microbiome and provide insight into the role of high-turnover microbial communities as well as potential pathogenic organisms as real-time indicators of water quality, with implications for human health and demonstrate the inner functional shifts contributed by the microcommunities. Electronic supplementary material The online version of this article (10.1186/s40168-019-0714-6) contains supplementary material, which is available to authorized users.