52 research outputs found

    The glutathione biosynthetic pathway of Plasmodium is essential for mosquito transmission

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    1Infection of red blood cells (RBC) subjects the malaria parasite to oxidative stress. Therefore, efficient antioxidant and redox systems are required to prevent damage by reactive oxygen species. Plasmodium spp. have thioredoxin and glutathione (GSH) systems that are thought to play a major role as antioxidants during blood stage infection. In this report, we analyzed a critical component of the GSH biosynthesis pathway using reverse genetics. Plasmodium berghei parasites lacking expression of gamma-glutamylcysteine synthetase (γ-GCS), the rate limiting enzyme in de novo synthesis of GSH, were generated through targeted gene disruption thus demonstrating, quite unexpectedly, that γ-GCS is not essential for blood stage development. Despite a significant reduction in GSH levels, blood stage forms of pbggcs− parasites showed only a defect in growth as compared to wild type. In contrast, a dramatic effect on development of the parasites in the mosquito was observed. Infection of mosquitoes with pbggcs− parasites resulted in reduced numbers of stunted oocysts that did not produce sporozoites. These results have important implications for the design of drugs aiming at interfering with the GSH redox-system in blood stages and demonstrate that de novo synthesis of GSH is pivotal for development of Plasmodium in the mosquito

    Combining Asian and European genome-wide association studies of colorectal cancer improves risk prediction across racial and ethnic populations

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    Polygenic risk scores (PRS) have great potential to guide precision colorectal cancer (CRC) prevention by identifying those at higher risk to undertake targeted screening. However, current PRS using European ancestry data have sub-optimal performance in non-European ancestry populations, limiting their utility among these populations. Towards addressing this deficiency, we expand PRS development for CRC by incorporating Asian ancestry data (21,731 cases; 47,444 controls) into European ancestry training datasets (78,473 cases; 107,143 controls). The AUC estimates (95% CI) of PRS are 0.63(0.62-0.64), 0.59(0.57-0.61), 0.62(0.60-0.63), and 0.65(0.63-0.66) in independent datasets including 1681-3651 cases and 8696-115,105 controls of Asian, Black/African American, Latinx/Hispanic, and non-Hispanic White, respectively. They are significantly better than the European-centric PRS in all four major US racial and ethnic groups (p-values < 0.05). Further inclusion of non-European ancestry populations, especially Black/African American and Latinx/Hispanic, is needed to improve the risk prediction and enhance equity in applying PRS in clinical practice

    Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

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    Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naĂŻve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

    The United States COVID-19 Forecast Hub dataset

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    Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

    The James Webb Space Telescope Mission

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    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 4m4m. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the 6.5m6.5m 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

    Loregic: A Method to Characterize the Cooperative Logic of Regulatory Factors

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    The topology of the gene-regulatory network has been extensively analyzed. Now, given the large amount of available functional genomic data, it is possible to go beyond this and systematically study regulatory circuits in terms of logic elements. To this end, we present Loregic, a computational method integrating gene expression and regulatory network data, to characterize the cooperativity of regulatory factors. Loregic uses all 16 possible twoinput- one-output logic gates (e.g. AND or XOR) to describe triplets of two factors regulating a common target. We attempt to find the gate that best matches each triplet’s observed gene expression pattern across many conditions. We make Loregic available as a generalpurpose tool (github.com/gersteinlab/loregic). We validate it with known yeast transcriptionfactor knockout experiments. Next, using human ENCODE ChIP-Seq and TCGA RNA-Seq data, we are able to demonstrate how Loregic characterizes complex circuits involving both proximally and distally regulating transcription factors (TFs) and also miRNAs. Furthermore, we show that MYC, a well-known oncogenic driving TF, can be modeled as acting independently from other TFs (e.g., using OR gates) but antagonistically with repressing miRNAs. Finally, we inter-relate Loregic’s gate logic with other aspects of regulation, such as indirect binding via protein-protein interactions, feed-forward loop motifs and global regulatory hierarchy

    THE NEEDLE in the 100 deg<sup>2</sup> HAYSTACK: UNCOVERING AFTERGLOWS of FERMI GRB<inf>s</inf> with the PALOMAR TRANSIENT FACTORY

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    The Fermi Gamma-ray Space Telescope has greatly expanded the number and energy window of observations of gamma-ray bursts (GRBs). However, the coarse localizations of tens to a hundred square degrees provided by the Fermi GRB Monitor instrument have posed a formidable obstacle to locating the bursts' host galaxies, measuring their redshifts, and tracking their panchromatic afterglows. We have built a target-of-opportunity mode for the intermediate Palomar Transient Factory in order to perform targeted searches for Fermi afterglows. Here, we present the results of one year of this program: 8 afterglow discoveries out of 35 searches. Two of the bursts with detected afterglows (GRBs 130702A and 140606B) were at low redshift (z = 0.145 and 0.384, respectively) and had spectroscopically confirmed broad-line Type Ic supernovae. We present our broadband follow-up including spectroscopy as well as X-ray, UV, optical, millimeter, and radio observations. We study possible selection effects in the context of the total Fermi and Swift GRB samples. We identify one new outlier on the Amati relation. We find that two bursts are consistent with a mildly relativistic shock breaking out from the progenitor star rather than the ultra-relativistic internal shock mechanism that powers standard cosmological bursts. Finally, in the context of the Zwicky Transient Facility, we discuss how we will continue to expand this effort to find optical counterparts of binary neutron star mergers that may soon be detected by Advanced LIGO and Virgo. © 2015. The American Astronomical Society. All rights reserved

    Postharvest survival of navel orangeworm assessed in pistachios

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    Controlling navel orangeworm, a key pistachio pest, is problematic because the moth overwinters in “mummy” nuts. After harvest, there may be more than 30,000 pistachio nuts (mummies) left behind per acre. To provide better information for winter sanitation decisions, we investigated the number of available mummies and their levels of navel orangeworm infestation from winter through early summer in California pistachio orchards. Navel orangeworm mortality was highest from late December through mid-February, and was also higher on the ground than in trees. Mortality on the ground was highest when mummies were tilled or mowed with the groundcover than when nuts were left on the raised berm. Our data indicates that, in contrast to almonds, it is more productive to focus on clearing pistachios from the ground than on removing them from trees. However, winter sanitation procedures also should be augmented in order to destroy more overwintering navel orangeworm
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