Know The Star, Know the Planet. IV. A Stellar Companion to the Host star of the Eccentric Exoplanet HD 8673b

HD 8673 hosts a massive exoplanet in a highly eccentric orbit (e=0.723). Based on two epochs of speckle interferometry a previous publication identified a candidate stellar companion. We observed HD 8673 multiple times with the 10 m Keck II telescope, the 5 m Hale telescope, the 3.63 m AEOS telescope and the 1.5m Palomar telescope in a variety of filters with the aim of confirming and characterizing the stellar companion. We did not detect the candidate companion, which we now conclude was a false detection, but we did detect a fainter companion. We collected astrometry and photometry of the companion on six epochs in a variety of filters. The measured differential photometry enabled us to determine that the companion is an early M dwarf with a mass estimate of 0.33-0.45 M?. The companion has a projected separation of 10 AU, which is one of the smallest projected separations of an exoplanet host binary system. Based on the limited astrometry collected, we are able to constrain the orbit of the stellar companion to a semi-major axis of 35{60 AU, an eccentricity ? 0.5 and an inclination of 75{85?. The stellar companion has likely strongly in uenced the orbit of the exoplanet and quite possibly explains its high eccentricity.Comment: Accepted to the Astronomical Journal, 6 Pages, 5 Figure

KELT-8b: A highly inflated transiting hot Jupiter and a new technique for extracting high-precision radial velocities from noisy spectra

We announce the discovery of a highly inflated transiting hot Jupiter discovered by the KELT-North survey. A global analysis including constraints from isochrones indicates that the V = 10.8 host star (HD 343246) is a mildly evolved, G dwarf with $T_{\rm eff} = 5754_{-55}^{+54}$ K, $\log{g} = 4.078_{-0.054}^{+0.049}$, $[Fe/H] = 0.272\pm0.038$, an inferred mass $M_{*}=1.211_{-0.066}^{+0.078}$ M$_{\odot}$, and radius $R_{*}=1.67_{-0.12}^{+0.14}$ R$_{\odot}$. The planetary companion has mass $M_P = 0.867_{-0.061}^{+0.065}$ $M_{J}$, radius $R_P = 1.86_{-0.16}^{+0.18}$ $R_{J}$, surface gravity $\log{g_{P}} = 2.793_{-0.075}^{+0.072}$, and density $\rho_P = 0.167_{-0.038}^{+0.047}$ g cm$^{-3}$. The planet is on a roughly circular orbit with semimajor axis $a = 0.04571_{-0.00084}^{+0.00096}$ AU and eccentricity $e = 0.035_{-0.025}^{+0.050}$. The best-fit linear ephemeris is $T_0 = 2456883.4803 \pm 0.0007$ BJD$_{\rm TDB}$ and $P = 3.24406 \pm 0.00016$ days. This planet is one of the most inflated of all known transiting exoplanets, making it one of the few members of a class of extremely low density, highly-irradiated gas giants. The low stellar $\log{g}$ and large implied radius are supported by stellar density constraints from follow-up light curves, plus an evolutionary and space motion analysis. We also develop a new technique to extract high precision radial velocities from noisy spectra that reduces the observing time needed to confirm transiting planet candidates. This planet boasts deep transits of a bright star, a large inferred atmospheric scale height, and a high equilibrium temperature of $T_{eq}=1675^{+61}_{-55}$ K, assuming zero albedo and perfect heat redistribution, making it one of the best targets for future atmospheric characterization studies.Comment: Submitted to ApJ, feedback is welcom

Quantitative MRI brain in congenital adrenal hyperplasia: in vivo assessment of the cognitive and structural impact of steroid hormones

Abstract Context Brain white matter hyper-intensities are seen on routine clinical imaging in 46% of adults with congenital adrenal hyperplasia (CAH). The extent and functional relevance of these abnormalities have not been studied using quantitative MRI analysis. Objective To examine white matter microstructure, neural volumes and CNS metabolites in CAH due to 21-hydroxylase deficiency (21OHD) and to determine whether identified abnormalities are associated with cognition, glucocorticoid and androgen exposure. Design, setting and participants A cross-sectional study at a tertiary hospital including 19 females (18-50 years) with 21OHD and 19 age-matched healthy females. Main outcome measure Recruits underwent cognitive assessment and brain imaging including; diffusion weighted imaging of white matter, T1-weighted volumetry and magnetic resonance spectroscopy for neural metabolites. We evaluated white matter microstructure using tract-based spatial statistics. We compared cognitive scores, neural volumes and metabolites between groups and relationships between glucocorticoid exposure, MRI and neurologic outcomes. Results Patients with 21OHD had widespread reductions in white matter structural integrity, reduced volumes of right hippocampus, bilateral thalami, cerebellum and brainstem, and reduced mesial temporal lobe total choline content. Working memory, processing speed, and digit span and matrix reasoning scores were reduced in patients with 21OHD, despite similar education and intelligence to controls. 21OHD individuals exposed to higher glucocorticoid doses had greater abnormalities in white matter microstructure and cognitive performance. Conclusion For the first time we demonstrate that 21OHD and current glucocorticoid replacement regimens have a profound impact on brain morphology and function. If reversible, these CNS markers represent a potential target for treatment

Pre-post effects of a tetanus care protocol implementation in a sub-Saharan African intensive care unit.

BACKGROUND: Tetanus is a vaccine-preventable, neglected disease that is life threatening if acquired and occurs most frequently in regions where vaccination coverage is incomplete. Challenges in vaccination coverage contribute to the occurrence of non-neonatal tetanus in sub-Saharan countries, with high case fatality rates. The current WHO recommendations for the management of tetanus include close patient monitoring, administration of immune globulin, sedation, analgesia, wound hygiene and airway support [1]. In response to these recommendations, our tertiary referral hospital in Tanzania implemented a standardized clinical protocol for care of patients with tetanus in 2006 and a subsequent modification in 2012. In this study we aimed to assess the impact of the protocol on clinical care of tetanus patients and their outcomes. METHODS AND FINDINGS: We examined provision of care and outcomes among all patients admitted with non-neonatal tetanus to the ICU at Bugando Medical Centre between 2001 and 2016 in this retrospective cohort study. We compared three groups: the pre-protocol group (2001-2005), the Early protocol group (2006-2011), and the Late protocol group (2012-2016) and determined associations with mortality by univariable logistic regression. We observed a significant increase in provision of care as per protocol between the Early and Late groups. Patients in the Late group had a significantly higher utilization of mechanical ventilation (69.9% vs 22.0%, p40%). Institution of a standardized tetanus management protocol, in accordance with WHO recommendations, decreased immediate mortality related to primary causes of death after tetanus. However, this was offset by an increase in death due to later ICU complications such as sepsis. Our results illustrate the complexity in achieving mortality reduction even in illnesses thought to require few critical care interventions. Improving basic ICU care and strengthening vaccination programs to prevent tetanus altogether are essential components of efforts to decrease the mortality caused by this lethal, neglected disease

Sampling the Solution Space in Genome-Scale Metabolic Networks Reveals Transcriptional Regulation in Key Enzymes

Genome-scale metabolic models are available for an increasing number of organisms and can be used to define the region of feasible metabolic flux distributions. In this work we use as constraints a small set of experimental metabolic fluxes, which reduces the region of feasible metabolic states. Once the region of feasible flux distributions has been defined, a set of possible flux distributions is obtained by random sampling and the averages and standard deviations for each of the metabolic fluxes in the genome-scale model are calculated. These values allow estimation of the significance of change for each reaction rate between different conditions and comparison of it with the significance of change in gene transcription for the corresponding enzymes. The comparison of flux change and gene expression allows identification of enzymes showing a significant correlation between flux change and expression change (transcriptional regulation) as well as reactions whose flux change is likely to be driven only by changes in the metabolite concentrations (metabolic regulation). The changes due to growth on four different carbon sources and as a consequence of five gene deletions were analyzed for Saccharomyces cerevisiae. The enzymes with transcriptional regulation showed enrichment in certain transcription factors. This has not been previously reported. The information provided by the presented method could guide the discovery of new metabolic engineering strategies or the identification of drug targets for treatment of metabolic diseases

Identification of Functional Differences in Metabolic Networks Using Comparative Genomics and Constraint-Based Models

Genome-scale network reconstructions are useful tools for understanding cellular metabolism, and comparisons of such reconstructions can provide insight into metabolic differences between organisms. Recent efforts toward comparing genome-scale models have focused primarily on aligning metabolic networks at the reaction level and then looking at differences and similarities in reaction and gene content. However, these reaction comparison approaches are time-consuming and do not identify the effect network differences have on the functional states of the network. We have developed a bilevel mixed-integer programming approach, CONGA, to identify functional differences between metabolic networks by comparing network reconstructions aligned at the gene level. We first identify orthologous genes across two reconstructions and then use CONGA to identify conditions under which differences in gene content give rise to differences in metabolic capabilities. By seeking genes whose deletion in one or both models disproportionately changes flux through a selected reaction (e.g., growth or by-product secretion) in one model over another, we are able to identify structural metabolic network differences enabling unique metabolic capabilities. Using CONGA, we explore functional differences between two metabolic reconstructions of Escherichia coli and identify a set of reactions responsible for chemical production differences between the two models. We also use this approach to aid in the development of a genome-scale model of Synechococcus sp. PCC 7002. Finally, we propose potential antimicrobial targets in Mycobacterium tuberculosis and Staphylococcus aureus based on differences in their metabolic capabilities. Through these examples, we demonstrate that a gene-centric approach to comparing metabolic networks allows for a rapid comparison of metabolic models at a functional level. Using CONGA, we can identify differences in reaction and gene content which give rise to different functional predictions. Because CONGA provides a general framework, it can be applied to find functional differences across models and biological systems beyond those presented here

A community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella Typhimurium LT2

<p>Abstract</p> <p>Background</p> <p>Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. <it>Salmonella enterica </it>subspecies I serovar Typhimurium is a human pathogen, causes various diseases and its increasing antibiotic resistance poses a public health problem.</p> <p>Results</p> <p>Here, we describe a community-driven effort, in which more than 20 experts in <it>S</it>. Typhimurium biology and systems biology collaborated to reconcile and expand the <it>S</it>. Typhimurium BiGG knowledge-base. The consensus MR was obtained starting from two independently developed MRs for <it>S</it>. Typhimurium. Key results of this reconstruction jamboree include i) development and implementation of a community-based workflow for MR annotation and reconciliation; ii) incorporation of thermodynamic information; and iii) use of the consensus MR to identify potential multi-target drug therapy approaches.</p> <p>Conclusion</p> <p>Taken together, with the growing number of parallel MRs a structured, community-driven approach will be necessary to maximize quality while increasing adoption of MRs in experimental design and interpretation.</p

A review of the opportunities and challenges for using remote sensing for management of surface-canopy forming kelps

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Cavanaugh, K. C., Bell, T., Costa, M., Eddy, N. E., Gendall, L., Gleason, M. G., Hessing-Lewis, M., Martone, R., McPherson, M., Pontier, O., Reshitnyk, L., Beas-Luna, R., Carr, M., Caselle, J. E., Cavanaugh, K. C., Miller, R. F., Hamilton, S., Heady, W. N., Hirsh, H. K., Hohman R., Lee L. C., Lorda J., Ray J., Reed D. C., Saccomanno V. R., Schroeder, S. B. A review of the opportunities and challenges for using remote sensing for management of surface-canopy forming kelps. Frontiers in Marine Science, 8, (2021): 753531, https://doi.org/10.3389/fmars.2021.753531.Surface-canopy forming kelps provide the foundation for ecosystems that are ecologically, culturally, and economically important. However, these kelp forests are naturally dynamic systems that are also threatened by a range of global and local pressures. As a result, there is a need for tools that enable managers to reliably track changes in their distribution, abundance, and health in a timely manner. Remote sensing data availability has increased dramatically in recent years and this data represents a valuable tool for monitoring surface-canopy forming kelps. However, the choice of remote sensing data and analytic approach must be properly matched to management objectives and tailored to the physical and biological characteristics of the region of interest. This review identifies remote sensing datasets and analyses best suited to address different management needs and environmental settings using case studies from the west coast of North America. We highlight the importance of integrating different datasets and approaches to facilitate comparisons across regions and promote coordination of management strategies.Funding was provided by the Nature Conservancy (Grant No. 02042019-5719), the U.S. National Science Foundation (Grant No. OCE 1831937), and the U.S. Department of Energy ARPA-E (Grant No. DE-AR0000922)

Genome-Scale Modeling of Light-Driven Reductant Partitioning and Carbon Fluxes in Diazotrophic Unicellular Cyanobacterium Cyanothece sp. ATCC 51142

Genome-scale metabolic models have proven useful for answering fundamental questions about metabolic capabilities of a variety of microorganisms, as well as informing their metabolic engineering. However, only a few models are available for oxygenic photosynthetic microorganisms, particularly in cyanobacteria in which photosynthetic and respiratory electron transport chains (ETC) share components. We addressed the complexity of cyanobacterial ETC by developing a genome-scale model for the diazotrophic cyanobacterium, Cyanothece sp. ATCC 51142. The resulting metabolic reconstruction, iCce806, consists of 806 genes associated with 667 metabolic reactions and includes a detailed representation of the ETC and a biomass equation based on experimental measurements. Both computational and experimental approaches were used to investigate light-driven metabolism in Cyanothece sp. ATCC 51142, with a particular focus on reductant production and partitioning within the ETC. The simulation results suggest that growth and metabolic flux distributions are substantially impacted by the relative amounts of light going into the individual photosystems. When growth is limited by the flux through photosystem I, terminal respiratory oxidases are predicted to be an important mechanism for removing excess reductant. Similarly, under photosystem II flux limitation, excess electron carriers must be removed via cyclic electron transport. Furthermore, in silico calculations were in good quantitative agreement with the measured growth rates whereas predictions of reaction usage were qualitatively consistent with protein and mRNA expression data, which we used to further improve the resolution of intracellular flux values

Integrating Flux Balance Analysis into Kinetic Models to Decipher the Dynamic Metabolism of Shewanella oneidensis MR-1

Shewanella oneidensis MR-1 sequentially utilizes lactate and its waste products (pyruvate and acetate) during batch culture. To decipher MR-1 metabolism, we integrated genome-scale flux balance analysis (FBA) into a multiple-substrate Monod model to perform the dynamic flux balance analysis (dFBA). The dFBA employed a static optimization approach (SOA) by dividing the batch time into small intervals (i.e., ∼400 mini-FBAs), then the Monod model provided time-dependent inflow/outflow fluxes to constrain the mini-FBAs to profile the pseudo-steady-state fluxes in each time interval. The mini-FBAs used a dual-objective function (a weighted combination of “maximizing growth rate” and “minimizing overall flux”) to capture trade-offs between optimal growth and minimal enzyme usage. By fitting the experimental data, a bi-level optimization of dFBA revealed that the optimal weight in the dual-objective function was time-dependent: the objective function was constant in the early growth stage, while the functional weight of minimal enzyme usage increased significantly when lactate became scarce. The dFBA profiled biologically meaningful dynamic MR-1 metabolisms: 1. the oxidative TCA cycle fluxes increased initially and then decreased in the late growth stage; 2. fluxes in the pentose phosphate pathway and gluconeogenesis were stable in the exponential growth period; and 3. the glyoxylate shunt was up-regulated when acetate became the main carbon source for MR-1 growth