The development of radioactive sample surrogates for training and exercises

The development of radioactive sample surrogates for training and exercises Source term information is required for to reconstruct a device used in a dispersed radiological dispersal device. Simulating a radioactive environment to train and exercise sampling and sample characterization methods with suitable sample materials is a continued challenge. The Idaho National Laboratory has developed and permitted a Radioactive Response Training Range (RRTR), an 800 acre test range that is approved for open air dispersal of activated KBr, for training first responders in the entry and exit from radioactively contaminated areas, and testing protocols for environmental sampling and field characterization. Members from the Department of Defense, Law Enforcement, and the Department of Energy participated in the first contamination exercise that was conducted at the RRTR in the July 2011. The range was contaminated using a short lived radioactive Br-82 isotope (activated KBr). Soil samples contaminated with KBr (dispersed as a solution) and glass particles containing activated potassium bromide that emulated dispersed radioactive materials (such as ceramic-based sealed source materials) were collected to assess environmental sampling and characterization techniques. This presentation summarizes the performance of a radioactive materials surrogate for use as a training aide for nuclear forensics

Correlation between Fischer-Tropsch catalytic activity and composition of catalysts

This paper presents the synthesis and characterization of monometallic and bimetallic cobalt and iron nanoparticles supported on alumina. The catalysts were prepared by a wet impregnation method. Samples were characterized using temperature-programmed reduction (TPR), temperature-programmed oxidation (TPO), CO-chemisorption, transmission electron microscopy (TEM), field emission scanning electron microscopy (FESEM-EDX) and N2-adsorption analysis. Fischer-Tropsch synthesis (FTS) was carried out in a fixed-bed microreactor at 543 K and 1 atm, with H2/CO = 2 v/v and space velocity, SV = 12L/g.h. The physicochemical properties and the FTS activity of the bimetallic catalysts were analyzed and compared with those of monometallic cobalt and iron catalysts at similar operating conditions

Diversification of Genes Encoding Granule-Bound Starch Synthase in Monocots and Dicots Is Marked by Multiple Genome-Wide Duplication Events

Starch is one of the major components of cereals, tubers, and fruits. Genes encoding granule-bound starch synthase (GBSS), which is responsible for amylose synthesis, have been extensively studied in cereals but little is known about them in fruits. Due to their low copy gene number, GBSS genes have been used to study plant phylogenetic and evolutionary relationships. In this study, GBSS genes have been isolated and characterized in three fruit trees, including apple, peach, and orange. Moreover, a comprehensive evolutionary study of GBSS genes has also been conducted between both monocots and eudicots. Results have revealed that genomic structures of GBSS genes in plants are conserved, suggesting they all have evolved from a common ancestor. In addition, the GBSS gene in an ancestral angiosperm must have undergone genome duplication ∼251 million years ago (MYA) to generate two families, GBSSI and GBSSII. Both GBSSI and GBSSII are found in monocots; however, GBSSI is absent in eudicots. The ancestral GBSSII must have undergone further divergence when monocots and eudicots split ∼165 MYA. This is consistent with expression profiles of GBSS genes, wherein these profiles are more similar to those of GBSSII in eudicots than to those of GBSSI genes in monocots. In dicots, GBSSII must have undergone further divergence when rosids and asterids split from each other ∼126 MYA. Taken together, these findings suggest that it is GBSSII rather than GBSSI of monocots that have orthologous relationships with GBSS genes of eudicots. Moreover, diversification of GBSS genes is mainly associated with genome-wide duplication events throughout the evolutionary course of history of monocots and eudicots

Anaerobic digestion and gasification of seaweed

The potential of algal biomass as a source of liquid and gaseous biofuels is a highly topical theme, with over 70 years of sometimes intensive research and considerable financial investment. A wide range of unit operations can be combined to produce algal biofuel, but as yet there is no successful commercial system producing such biofuel. This suggests that there are major technical and engineering difficulties to be resolved before economically viable algal biofuel production can be achieved. Both gasification and anaerobic digestion have been suggested as promising methods for exploiting bioenergy from biomass, and two major projects have been funded in the UK on the gasification and anaerobic digestion of seaweed, MacroBioCrude and SeaGas. This chapter discusses the use of gasification and anaerobic digestion of seaweed for the production of biofuel

Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.Peer reviewe