A Ferredoxin Disulfide Reductase Delivers Electrons to the to the Methanosarcina barkeri Class III Ribonucleotide Reductase

Two subtypes of class III anaerobic ribonucleotide reductases (RNRs) studied so far couple the reduction of ribonucleotides to the oxidation of formate, or the oxidation of NADPH via thioredoxin and thioredoxin reductase. Certain methanogenic archaea contain a phylogenetically distinct third subtype of class III RNR, with distinct active-site residues. Here we report the cloning and recombinant expression of the Methanosarcina barkeri class III RNR and show that the electrons required for ribonucleotide reduction can be delivered by a [4Fe-4S] protein ferredoxin disulfide reductase, and a conserved thioredoxin-like protein NrdH present in the RNR operon. The diversity of class III RNRs reflects the diversity of electron carriers used in anaerobic metabolism.Singapore. Agency for Science, Technology and ResearchNational Institutes of Health (U.S.) (Grant GM081393

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

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 naïve 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

Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity.

Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant

The United States COVID-19 Forecast Hub dataset

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

Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity

Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant

Comparison of nutrient density of selected commercial and laboratory prepared vegetable dishes

Green leafy vegetables occupy an important place among the food crops as these provide adequate amounts ofmany vitamins, minerals, antioxidants which are responsible for maintaining good health. Food composition databases areessential tools to assess the dietary status of individual, to assess the dietary intakes of population groups with defineddemographic characteristics. For the development of nutrient database of dishes based on green leafy vegetables and rootsand tubers, three products such as palak paneer, potato sabji and carrot halwawere prepared in the laboratory and theirnutritional value was computed using the food composition tables for serving sizes in standard measuring cups. Disheswere also procured from three different commercial establishments and analyzed for their nutritional composition.Standardized methods were followed for analysis. Results showed that highest fat content was observed in carrot halwaranging from 11-16% contributed by added ghee and khoa, followed by palakpaneer, 7-15%, and potato sabji, 2-7%. Theprotein content was highest in carrot halwa, 3-6% followed by pala paneer, 4.5-5.6%, and 2.1-2.6% in potato sabji. Carrothalwa showed higher iron and calcium content followed by palak paneer and potato sabji. The energy content of carrothalwa, palak paneer and potato sabji ranged from 122-480 kcal, 84-298 kcal and 93-302 kcal respectively with theincreasing cup size from 1/4th to 1 cup. The study concludes that products prepared from these vegetables contributed toconsiderable amounts of nutrients depending on the variety, other ingredients used in the preparation of the product and thequantity of the vegetable used. Considerable variations were seen in products procured from different sources in fat andenergy contents, which obviously depends on the added ingredients. Hence, there is a need to know the nutritional value ofcommercially sold products to calculate an individual’s nutrient intake from such food

Barriers and opportunities in achieving climate and sustainable development goals in India: a multilevel analysis

ABSTRACTClimate action plans are essential for climate mitigation and adaptation as well as to achieve climate and development goals like the Paris Agreement and the Sustainable Development Goals (SDGs). However, the development and implementation of climate action plans at multiple levels involve decision-making processes. In this article, we examine the barriers and opportunities to decision-making in climate action plans for adaptation at three different governance levels in India: national, sub-national and local. Through a literature review and analysis of case studies, we find that lack of usable climate information, institutional weaknesses and capacity of actors are critical barriers to decision-making at all three levels in India. We recommend that providing usable and accessible climate information, creating evidence and knowledge on adaptation, strengthening the science-policy interface and institutional mechanisms, as well as building the capacities of actors can contribute to better decision-making and achieving targeted climate action plans and SDGs

Model analysis and electrical characterization of atmospheric pressure cold plasma jet in pin electrode configuration

In this study, both model analysis and electrical characterization of a dielectric barrier discharge based argon plasma jet have been carried at atmospheric pressure in a pin electrode configuration. The plasma and fluid dynamics modules of COMSOL multi-physics code have been used for the modeling of the plasma jet. The plasma parameters, such as, electron density, electron temperature and electrical potential have been analyzed with respect to the electrical parameters, i.e., supply voltage and supply frequency with and without the flow of gas. In all the experiments, gas flow rate has been kept constant at 1 liter per minute. This electrode configuration is subjected to a range of supply frequencies (10-25 kHz) and supply voltages (3.5-6.5 kV). The power consumed by the device has been estimated at different applied combinations (supply voltage & frequency) for optimum power consumption at maximum jet length. The maximum power consumed by the device in this configuration for maximum jet length of ∼26 mm is just ∼1 W

Bacterial transformation using micro-shock waves

Shock waves are one of the most competent mechanisms of energy dissipation observed in nature. We have developed a novel device to generate controlled micro-shock waves using an explosive-coated polymer tube. In this study, we harnessed these controlled micro-shock waves to develop a unique bacterial transformation method. The conditions were optimized for the maximum transformation efficiency in Escherichia coli. The maximum transformation efficiency was obtained when we used a 30 cm length polymer tube, 100 mu m thick metal foil, 200 mM CaCl(2), 1 ng/mu l plasmid DNA concentration, and 1 x 10(9) cell density. The highest transformation efficiency achieved (1 x 10(-5) transformants/cell) was at least 10 times greater than the previously reported ultrasound-mediated transformation (1 x 10(-6) transformants/cell). This method was also successfully employed for the efficient and reproducible transformation of Pseudomonas aeruginosa and Salmonella typhimurium. This novel method of transformation was shown to be as efficient as electroporation with the added advantage of better recovery of cells, reduced cost (40 times cheaper than a commercial electroporator), and growth phase independent transformation. (C) 2011 Elsevier Inc. All rights reserved