A Review of the Current Testing Methods for SARS-COV-2 in the US

On March 11th 2020, the WHO classified the Covid-19 out-break as a pandemic1. As of May 10th 2020, according the WHO Situation Report-111, there are 3,917,366 confirmed cases of Covid-19 with 274,361 deaths globally2. The estimated basic reproduction number for Covid-19 is 2.2, meaning on average a person with the disease will infect 2 other people3. As of the date this paper was written, there are no conclusive methods of treatment, nor a vaccine for Covid-194. It is because of this that, arguably, the most effective policy to preventing deaths, harm, and extending isolation policies, is with mass tracking of current cases, followed by rapid testing of populations exposed to said individuals5. The United States of America has taken a triage approach to testing however, with classifications of people being designated as those who should receive testing while others are not. A list of symptoms6 is first used to identify if a patient could have Covid-19. Other risk factors such as, exposure to a person with a confirmed case, if they work in a high-risk area, or if their local area has a high exposure rate are used to judge if a test is required. The CDC provides official guidelines on classification of risk assessment for testing7

The Impact of Equity Engagement Evaluating the Impact of Shareholder Engagement in Public Equity Investing

Over the last decade, growing numbers of investors have become increasingly concerned with the environmental and social impact of their investments across asset classes. This trend has recently been driven by new waves of "impact investors" proactively seeking measurable social and environmental impact in addition to financial returns, and by "responsible investors" making commitments to engage on environmental, social, and governance (ESG) issues through initiatives such as the United Nations-backed Principles for Responsible Investment (PRI). At the same time, engaged shareholders have had long-standing experience using "the power of the proxy" and their voices as investors to hold companies accountable for the impacts they have on employees, stakeholders, communities, and ecosystems.While investor interest in shareholder engagement has grown, our understanding of the impacts associated with engagement activities remains largely anecdotal.In 2012, an important study on Total Portfolio Activation provided a new conceptual and analytical framework for investors to pursue environmental and social impact across all asset classes commonly found in a diversified investment portfolio. Building upon the insights of Total Portfolio Activation, the Impact of Equity Engagement (IE2) initiative seeks to deepen our understanding of the nature of impact in one specific asset class—public equities— where investors' engagement activities have generated meaningful social and environmental impacts.Given the large social and environmental footprints of publicly traded corporations and the persistently high allocation to public equities in most investor portfolios, public equity investing presents a major opportunity for impact investing. Yet impact investing, as currently practiced, has concentrated primarily on smallscale direct investments in private equity and debt, where many investors perceive that social and environmental impact can be more readily observed than in publicly traded companies where ownership is intermediated, diluted, and diffused through secondary capital markets.Indeed, the nature of impact within public equity investing remains poorly understood and insufficiently documented. Because of this, many investors may be overlooking readily available opportunities for generating impact within their existing investment portfolios.To address these misperceptions and missed opportunities, the IE2 initiative is developing a more rigorous framework for documenting the impact of engagement within the public equity asset class.

Family-based genetic risk prediction of multifactorial disease

Genome-wide association studies have detected dozens of variants underlying complex diseases, although it is uncertain how often these discoveries will translate into clinically useful predictors. Here, to improve genetic risk prediction, we consider including phenotypic and genotypic information from related individuals. We develop and evaluate a family-based liability-threshold prediction model and apply it to a simulation of known Crohn's disease risk variants. We show that genotypes of a relative of known phenotype can be informative for an individual's disease risk, over and above the same locus genotyped in the individual. This approach can lead to better-calibrated estimates of disease risk, although the overall benefit for prediction is typically only very modest

Efficiency and Power as a Function of Sequence Coverage, SNP Array Density, and Imputation

High coverage whole genome sequencing provides near complete information about genetic variation. However, other technologies can be more efficient in some settings by (a) reducing redundant coverage within samples and (b) exploiting patterns of genetic variation across samples. To characterize as many samples as possible, many genetic studies therefore employ lower coverage sequencing or SNP array genotyping coupled to statistical imputation. To compare these approaches individually and in conjunction, we developed a statistical framework to estimate genotypes jointly from sequence reads, array intensities, and imputation. In European samples, we find similar sensitivity (89%) and specificity (99.6%) from imputation with either 1× sequencing or 1 M SNP arrays. Sensitivity is increased, particularly for low-frequency polymorphisms (MAF <5%), when low coverage sequence reads are added to dense genome-wide SNP arrays — the converse, however, is not true. At sites where sequence reads and array intensities produce different sample genotypes, joint analysis reduces genotype errors and identifies novel error modes. Our joint framework informs the use of next-generation sequencing in genome wide association studies and supports development of improved methods for genotype calling

Direct Observation of ultrafast exciton Formation in a monolayer of WSe2

Many of the fundamental optical and electronic properties of atomically thin transition metal dichalcogenides are dominated by strong Coulomb interactions between electrons and holes, forming tightly bound atom-like states called excitons. Here, we directly trace the ultrafast formation of excitons by monitoring the absolute densities of bound and unbound electron hole pairs in single monolayers of WSe2 on a diamond substrate following femtosecond nonresonant optical excitation. To this end, phase locked mid-infrared probe pulses and field-sensitive electro-optic sampling are used to map out the full complex-valued optical conductivity of the nonequilibrium system and to discern the hallmark low-energy responses of bound and unbound pairs. While the spectral shape of the infrared response immediately after above-bandgap injection is dominated by free charge carriers, up to 60% of the electron-hole pairs are bound into excitons already on a subpicosecond time scale, evidencing extremely fast and efficient exciton formation. During the subsequent recombination phase, we still find a large density of free carriers in addition to excitons, indicating a nonequilibrium state of the photoexcited electron-hole system

Patient-derived glioblastoma cultures as a tool for small-molecule drug discovery

There is a compelling need for new therapeutic strategies for glioblastoma multiforme (GBM). Preclinical target and therapeutic discovery for GBMs is primarily conducted using cell lines grown in serum-containing media, such as U-87 MG, which do not reflect the gene expression profiles of tumors found in GBM patients. To address this lack of representative models, we sought to develop a panel of patient-derived GBM models and characterize their genomic features, using RNA sequencing (RNA-seq) and growth characteristics, both when grown as neurospheres in culture, and grown orthotopically as xenografts in mice. When we compared these with commonly used GBM cell lines in the Cancer Cell Line Encyclopedia (CCLE), we found these patient-derived models to have greater diversity in gene expression and to better correspond to GBMs directly sequenced from patient tumor samples. We also evaluated the potential of these models for targeted therapy, by using the genomic characterization to identify small molecules that inhibit the growth of distinct subsets of GBMs, paving the way for precision medicines for GBM

High-throughput identification of genotype-specific cancer vulnerabilities in mixtures of barcoded tumor cell lines.

Hundreds of genetically characterized cell lines are available for the discovery of genotype-specific cancer vulnerabilities. However, screening large numbers of compounds against large numbers of cell lines is currently impractical, and such experiments are often difficult to control. Here we report a method called PRISM that allows pooled screening of mixtures of cancer cell lines by labeling each cell line with 24-nucleotide barcodes. PRISM revealed the expected patterns of cell killing seen in conventional (unpooled) assays. In a screen of 102 cell lines across 8,400 compounds, PRISM led to the identification of BRD-7880 as a potent and highly specific inhibitor of aurora kinases B and C. Cell line pools also efficiently formed tumors as xenografts, and PRISM recapitulated the expected pattern of erlotinib sensitivity in vivo

Unique properties of a subset of human pluripotent stem cells with high capacity for self-renewal.

Archetypal human pluripotent stem cells (hPSC) are widely considered to be equivalent in developmental status to mouse epiblast stem cells, which correspond to pluripotent cells at a late post-implantation stage of embryogenesis. Heterogeneity within hPSC cultures complicates this interspecies comparison. Here we show that a subpopulation of archetypal hPSC enriched for high self-renewal capacity (ESR) has distinct properties relative to the bulk of the population, including a cell cycle with a very low G1 fraction and a metabolomic profile that reflects a combination of oxidative phosphorylation and glycolysis. ESR cells are pluripotent and capable of differentiation into primordial germ cell-like cells. Global DNA methylation levels in the ESR subpopulation are lower than those in mouse epiblast stem cells. Chromatin accessibility analysis revealed a unique set of open chromatin sites in ESR cells. RNA-seq at the subpopulation and single cell levels shows that, unlike mouse epiblast stem cells, the ESR subset of hPSC displays no lineage priming, and that it can be clearly distinguished from gastrulating and extraembryonic cell populations in the primate embryo. ESR hPSC correspond to an earlier stage of post-implantation development than mouse epiblast stem cells

Mapping Copy Number Variation by Population Scale Genome Sequencing

Genomic structural variants (SVs) are abundant in humans, differing from other forms of variation in extent, origin and functional impact. Despite progress in SV characterization, the nucleotide resolution architecture of most SVs remains unknown. We constructed a map of unbalanced SVs (that is, copy number variants) based on whole genome DNA sequencing data from 185 human genomes, integrating evidence from complementary SV discovery approaches with extensive experimental validations. Our map encompassed 22,025 deletions and 6,000 additional SVs, including insertions and tandem duplications. Most SVs (53%) were mapped to nucleotide resolution, which facilitated analysing their origin and functional impact. We examined numerous whole and partial gene deletions with a genotyping approach and observed a depletion of gene disruptions amongst high frequency deletions. Furthermore, we observed differences in the size spectra of SVs originating from distinct formation mechanisms, and constructed a map of SV hotspots formed by common mechanisms. Our analytical framework and SV map serves as a resource for sequencing-based association studies.Organismic and Evolutionary Biolog