A spike in coronavirus disease 2019 (COVID-19) has occurred in Southern California since October 2020. Analysis of the severe acute respiratory syndrome coronavirus (SARS-CoV-2) in Southern California prior to October indicated most isolates originated from clade 20C that likely emerged from New York via Europe early in the pandemic. 1 Since then, novel variants of SARS-CoV-2 including those seen in the UK (20I/ 501Y.V1/B.1.1.7), South Africa (20H/501Y.V2/B.1.351), and Brazil (P.1/20J/501Y.V3/B.1.1.248) have emerged with the concern of increased infectivity and virulence. 2,3 Thus, we analyzed variants of SARS-CoV-2 in Southern California to establish whether one of these known strains or a novel variant had emerged. Methods | Regulatory review with waiver of consent was completed by Cedars-Sinai Medical Center (CSMC). From all samples from symptomatic inpatients and ambulatory care (urgent care, primary care, and employee health) that tested positive for SARS-CoV-2 collected from November 22, 2020, to December 28, 2020, at CSMC with cycle threshold values less than 30, a random sample from selected runs and dates within the collection period was sequenced and analyzed (Supplement). In addition, phylogenetic analysis was conducted with CSMC samples and globally representative genomes on January 11, 2021, by utilizing Nextstrain, a collection of open-source tools for visualizing the genetics behind the spread of viral outbreaks. 4 The representative global samples were randomly chosen using a computer algorithm from more than 400 000 available genomes on GISAID (Global Initiative on Sharing All Influenza Data), an open-access global collection of viral genomic data, 5 collected between December 21, 2019, and January 11, 2021 (Supplement). The proportional prevalence of each clade over time in samples from California as a whole and Southern California specifically and presence of any novel lineages discovered worldwide was calculated using publicly available sequences from GISAID (including samples from CSMC), collected between

The [O iii] λ5007 planetary nebula luminosity function (PNLF) is an established distance indicator that has been used for more than 30 yr to measure the distances of galaxies out to ∼15 Mpc. With the advent of the Multi-Unit Spectroscopic Explorer on the Very Large Telescope (MUSE) as an efficient wide-field integral-field spectrograph, the PNLF method is due for a renaissance, as the spatial and spectral information contained in the instrument’s data cubes provides many advantages over classical narrowband imaging. Here we use archival MUSE data to explore the potential of a novel differential emission-line filter (DELF) technique to produce spectrophotometry that is more accurate and more sensitive than other methods. We show that DELF analyses are superior to classical techniques in high surface brightness regions of galaxies, and we validate the method both through simulations and via the analysis of data from two early-type galaxies (NGC 1380 and NGC 474) and one late-type spiral (NGC 628). We demonstrate that with adaptive optics support or under excellent seeing conditions, the technique is capable of producing precision (≲0.05 mag) [O iii] photometry out to distances of 40 Mpc while providing discrimination between planetary nebulae and other emission-line objects such as H ii regions, supernova remnants, and background galaxies. These capabilities enable us to use MUSE to measure precise PNLF distances beyond the reach of Cepheids and the tip of the red giant branch method and become an additional tool for constraining the local value of the Hubble constant.

We measure the Balmer decrements of 23 of the brightest planetary nebulae (PNe) in the inner bulge (r 3 ) of M31 and de-redden the bright end of the region's [O III] λ5007 planetary nebula luminosity function. We show that the most luminous PNe produce 1,200 L of power in their [O III] λ5007 line, implying central star luminosities of at least ∼ 11,000 L . Even with the most recent acceleratedevolution post-AGB models, such luminosities require central star masses in excess of 0.66 M , and main sequence progenitors of at least ∼ 2.5 M . Since M31's bulge has very few intermediate-age stars, we conclude that conventional single-star evolution cannot be responsible for these extremely luminous objects. We also present the circumstellar extinctions for the region's bright PNe and demonstrate that the distribution is similar to that found for PNe in the Large Magellanic Cloud, with a median value of A 5007 = 0.71. Finally, we compare our results to extinction measurements made for PNe in the E6 elliptical NGC 4697 and the interacting lenticular NGC 5128. We show that such extinctions are not unusual, and that the existence of very high-mass PN central stars is a general feature of old stellar populations. Our results suggest that single-star population synthesis models significantly underestimate the maximum luminosities and total integrated light of AGB stars.

Since October 2020, novel strains of SARS-CoV-2 including B.1.1.7, have been identified to be of global significance from an infection and surveillance perspective. While this strain (B.1.1.7) may play an important role in increased COVID rates in the UK, there are still no reported strains to account for the spike of cases in Los Angeles (LA) and California as a whole, which currently has some of the highest absolute and per-capita COVID transmission rates in the country. From the early days of the pandemic when LA only had a single viral genome uploaded onto GISAID we have been at the forefront of generating and analyzing the SARS-CoV-2 sequencing data from the LA region. We report a novel strain emerging in Southern California. Most current cases in the catchment population in LA fall into two distinct subclades: 1) 20G (24% of total) is the predominant subclade currently in the United States 2) a relatively novel strain in clade 20C, CAL.20C strain (∼36% of total) is defined by five concurrent mutations. After an analysis of all of the publicly available data and a comparison to our recent sequences, we see a dramatic growth in the relative percentage of the CAL.20C strain beginning in November of 2020. The predominance of this strain coincides with the increased positivity rate seen in this region. Unlike 20G, this novel strain CAL.20C is defined by multiple mutations in the S protein, a characteristic it shares with both the UK and South African strains, both of which are of significant clinical and scientific interest

Background The development of next generation sequencing (NGS) methods led to a rapid rise in the generation of large genomic datasets, but the development of user-friendly tools to analyze and visualize these datasets has not developed at the same pace. This presents a two-fold challenge to biologists; the expertise to select an appropriate data analysis pipeline, and the need for bioinformatics or programming skills to apply this pipeline. The development of graphical user interface (GUI) applications hosted on web-based servers such as Shiny can make complex workflows accessible across operating systems and internet browsers to those without programming knowledge. Results We have developed GENAVi (Gene Expression Normalization Analysis and Visualization) to provide a user-friendly interface for normalization and differential expression analysis (DEA) of human or mouse feature count level RNA-Seq data. GENAVi is a GUI based tool that combines Bioconductor packages in a format for scientists without bioinformatics expertise. We provide a panel of 20 cell lines commonly used for the study of breast and ovarian cancer within GENAVi as a foundation for users to bring their own data to the application. Users can visualize expression across samples, cluster samples based on gene expression or correlation, calculate and plot the results of principal components analysis, perform DEA and gene set enrichment and produce plots for each of these analyses. To allow scalability for large datasets we have provided local install via three methods. We improve on available tools by offering a range of normalization methods and a simple to use interface that provides clear and complete session reporting and for reproducible analysis. Conclusion The development of tools using a GUI makes them practical and accessible to scientists without bioinformatics expertise, or access to a data analyst with relevant skills. While several GUI based tools are currently available for RNA-Seq analysis we improve on these existing tools. This user-friendly application provides a convenient platform for the normalization, analysis and visualization of gene expression data for scientists without bioinformatics expertise.