Detection and distribution of Craspedacusta sowerbii: Observations of medusae are not enough

The freshwater cnidarian Craspedacusta sowerbii, native to the Yangtze valley, has invaded lakes and ponds throughout the world. Most distribution records have to date been based on observations of the medusa (jellyfish) stage, including numerous recent publications. We aimed to determine whether polyps are widespread in lakes, and geographical areas, outside of where medusae have been observed, and whether constructed waters are more easily invaded than natural waters. Our results show that C. sowerbii is more common and widespread than is apparent from observations of medusae. We argue that observed occurrences of medusae provide little useful information regarding the distribution of this species, and that published records of new jellyfish occurrences provide unreliable estimates of the timing of introduction, establishment or spread of C. sowerbii in new regions. We found no evidence that constructed waters were more readily invaded than natural waters. Overall, accurate determination of Craspedacusta occurrence and distribution requires systematic surveys of the polyp stages

Recovering low molecular weight extractives from degraded straw by oyster mushroom at the farm scale for high value use

The cultivation of mushrooms on wheat straw can be considered a solid state fermentation, yet following harvest the residual, partially degraded straw is discarded. During cultivation, the degradation of lignocellulose in the straw takes place by the fungus under the action of enzymes releasing degradation products with small molecular weight, some of which are potentially valuable. These compounds may be extracted from straw after mushroom cultivation in two stages: an aqueous extraction followed by a solvent extraction. The present work is focused on the first stage of the process. The aqueous extraction releases water soluble compounds, such as sugars and phenolics with lower molecular weight, which are easily obtained. The partially degraded straw may then be treated with organic solvents to release water insoluble lignin breakdown products, such as fatty acids, phenolics and other aromatics. It is important to conduct scale-up experiments at a scale that would reflect the amount of waste straw generated by a mushroom farm. A study was performed using a vessel of 300 L capacity with mixing impeller, by observing the influence of the temperature (20oC, 25oC, 40oC, 60oC and 80oC) and water-to-dry straw ratio (from 40:1 to 90:1) on the total extracted matter and especially on sugar and phenolic compounds yields. A microbial study of the aqueous extract was also performed at 20oC and 25oC to explain the high concentration of organic carbon in the extract under certain circumstances. The optimum extraction conditions were determined by taking into account the yield and the energy consumption of the process. The conclusion was that the extraction temperature can be conducted between 20oC and 25oC with good results for obtaining liquor which can be used in a biogas installation. The extraction should be conducted at 80oC to obtain greater yields of sugars and phenolics

Centaur Standard Shroud (CSS) static limit load structural tests

The structural capabilities of the jettisonable metal shroud were tested and the interaction of the shroud with the Centaur stage was evaluated. A flight-configured shroud and the assemblies of the associated Centaur stage were tested for applied axial and shear loads to flight limit values. The tests included various thermal, pressure, and load conditions to verify localized strength capabilities, to evaluate subsystem performance, and to determine the aging effect on insulation system properties. The tests series verified the strength capabilities of the shroud and of all associated flight assembles. Shroud deflections were shown to remain within allowable limits so long as load sharing members were connected between the shroud and the Centaur stage

Sunjammer

No abstract available

Statistical modelling of transcript profiles of differentially regulated genes

Background: The vast quantities of gene expression profiling data produced in microarray studies, and the more precise quantitative PCR, are often not statistically analysed to their full potential. Previous studies have summarised gene expression profiles using simple descriptive statistics, basic analysis of variance (ANOVA) and the clustering of genes based on simple models fitted to their expression profiles over time. We report the novel application of statistical non-linear regression modelling techniques to describe the shapes of expression profiles for the fungus Agaricus bisporus, quantified by PCR, and for E. coli and Rattus norvegicus, using microarray technology. The use of parametric non-linear regression models provides a more precise description of expression profiles, reducing the "noise" of the raw data to produce a clear "signal" given by the fitted curve, and describing each profile with a small number of biologically interpretable parameters. This approach then allows the direct comparison and clustering of the shapes of response patterns between genes and potentially enables a greater exploration and interpretation of the biological processes driving gene expression. Results: Quantitative reverse transcriptase PCR-derived time-course data of genes were modelled. "Splitline" or "broken-stick" regression identified the initial time of gene up-regulation, enabling the classification of genes into those with primary and secondary responses. Five-day profiles were modelled using the biologically-oriented, critical exponential curve, y(t) = A + (B + Ct)Rt + ε. This non-linear regression approach allowed the expression patterns for different genes to be compared in terms of curve shape, time of maximal transcript level and the decline and asymptotic response levels. Three distinct regulatory patterns were identified for the five genes studied. Applying the regression modelling approach to microarray-derived time course data allowed 11% of the Escherichia coli features to be fitted by an exponential function, and 25% of the Rattus norvegicus features could be described by the critical exponential model, all with statistical significance of p < 0.05. Conclusion: The statistical non-linear regression approaches presented in this study provide detailed biologically oriented descriptions of individual gene expression profiles, using biologically variable data to generate a set of defining parameters. These approaches have application to the modelling and greater interpretation of profiles obtained across a wide range of platforms, such as microarrays. Through careful choice of appropriate model forms, such statistical regression approaches allow an improved comparison of gene expression profiles, and may provide an approach for the greater understanding of common regulatory mechanisms between genes

Protein Structure Prediction: The Next Generation

Over the last 10-15 years a general understanding of the chemical reaction of protein folding has emerged from statistical mechanics. The lessons learned from protein folding kinetics based on energy landscape ideas have benefited protein structure prediction, in particular the development of coarse grained models. We survey results from blind structure prediction. We explore how second generation prediction energy functions can be developed by introducing information from an ensemble of previously simulated structures. This procedure relies on the assumption of a funnelled energy landscape keeping with the principle of minimal frustration. First generation simulated structures provide an improved input for associative memory energy functions in comparison to the experimental protein structures chosen on the basis of sequence alignment