C. elegans RNA-dependent RNA polymerases rrf-1 and ego-1 silence Drosophila transgenes by differing mechanisms

Drosophila possesses the core gene silencing machinery but, like all insects, lacks the canonical RNA-dependent RNA polymerases (RdRps) that in C. elegans either trigger or enhance two major small RNA-dependent gene silencing pathways. Introduction of two different nematode RdRps into Drosophila showed them to be functional, resulting in differing silencing activities. While RRF-1 enhanced transitive dsRNA-dependent silencing, EGO-1 triggered dsRNA-independent silencing, specifically of transgenes. The strain w; da-Gal4; UAST-ego-1, constitutively expressing ego-1, is capable of silencing transgene including dsRNA hairpin upon a single cross, which created a powerful tool for research in Drosophila. In C. elegans, EGO-1 is involved in transcriptional gene silencing (TGS) of chromosome regions that are unpaired during meiosis. There was no opportunity for meiotic interactions involving EGO-1 in Drosophila that would explain the observed transgene silencing. Transgene DNA is, however, unpaired during the pairing of chromosomes in embryonic mitosis that is an unusual characteristic of Diptera, suggesting that in Drosophila, EGO-1 triggers transcriptional silencing of unpaired DNA during embryonic mitosis. © 2012 Springer Basel.

Expression of Caenorhabditis elegans RNA-directed RNA polymerase in transgenic Drosophila melanogaster does not affect morphological development

Drosophila melanogaster, along with all insects and the vertebrates, lacks an RdRp gene. We created transgenic strains of Drosophila melanogaster in which the rrf-1 or ego-1 RdRp genes from C. elegans were placed under the control of the yeast GAL4 upstream activation sequence. Activation of the gene was performed by crossing these lines to flies carrying the GAL4 transgene under the control of various Drosophila enhancers. RT-PCR confirmed the successful expression of each RdRp gene. The resulting phenotypes indicated that introduction of the RdRp genes had no effect on D. melanogaster morphological development. © 2010 Springer Science+Business Media B.V.

Interview with Dr. Young-Ki Paik, President of the Human Proteome Organization (HUPO): Pharmacoproteomics and the approaching wave of “Proteomics Diagnostics”

Dr. Young-Ki Paik directs the Yonsei Proteome Research Center in Seoul, Korea and was elected as the President of the Human Proteome Organization (HUPO) in 2009. In the December 2009 issue of the Current Pharmacogenomics and Personalized Medicine (CPPM), Dr. Paik explains the new field of pharmacoproteomics and the approaching wave of “proteomics diagnostics” in relation to personalized medicine, HUPO’s role in advancing proteomics technology applications, the HUPO Proteomics Standards Initiative, and the future impact of proteomics on medicine, science, and society. Additionally, he comments that (1) there is a need for launching a Gene-Centric Human Proteome Project (GCHPP) through which all representative proteins encoded by the genes can be identified and quantified in a specific cell and tissue and, (2) that the innovation frameworks within the diagnostics industry hitherto borrowed from the genetics age may require reevaluation in the case of proteomics, in order to facilitate the uptake of pharmacoproteomics innovations. He stresses the importance of biological/clinical plausibility driving the evolution of biotechnologies such as proteomics,instead of an isolated singular focus on the technology per se. Dr. Paik earned his Ph.D. in biochemistry from the University of Missouri-Columbia and carried out postdoctoral work at the Gladstone Foundation Laboratories of Cardiovascular Disease, University of California at San Francisco. In 2005, his research team at Yonsei University first identified and characterized the chemical structure of C. elegans dauer pheromone (daumone) which controls the aging process of this nematode. He is interviewed by a multidisciplinary team specializing in knowledge translation, technology regulation, health systems governance, and innovation analysis.

Multifractal characterisation and analysis of complex networks

Complex networks have been studied extensively due to their relevance to many real-world systems such as the world-wide web, the internet, biological and social systems. During the past two decades, studies of such networks in different fields have produced many significant results concerning their structures, topological properties, and dynamics. Three well-known properties of complex networks are scale-free degree distribution, small-world effect and self-similarity. The search for additional meaningful properties and the relationships among these properties is an active area of current research. This thesis investigates a newer aspect of complex networks, namely their multifractality, which is an extension of the concept of selfsimilarity. The first part of the thesis aims to confirm that the study of properties of complex networks can be expanded to a wider field including more complex weighted networks. Those real networks that have been shown to possess the self-similarity property in the existing literature are all unweighted networks. We use the proteinprotein interaction (PPI) networks as a key example to show that their weighted networks inherit the self-similarity from the original unweighted networks. Firstly, we confirm that the random sequential box-covering algorithm is an effective tool to compute the fractal dimension of complex networks. This is demonstrated on the Homo sapiens and E. coli PPI networks as well as their skeletons. Our results verify that the fractal dimension of the skeleton is smaller than that of the original network due to the shortest distance between nodes is larger in the skeleton, hence for a fixed box-size more boxes will be needed to cover the skeleton. Then we adopt the iterative scoring method to generate weighted PPI networks of five species, namely Homo sapiens, E. coli, yeast, C. elegans and Arabidopsis Thaliana. By using the random sequential box-covering algorithm, we calculate the fractal dimensions for both the original unweighted PPI networks and the generated weighted networks. The results show that self-similarity is still present in generated weighted PPI networks. This implication will be useful for our treatment of the networks in the third part of the thesis. The second part of the thesis aims to explore the multifractal behavior of different complex networks. Fractals such as the Cantor set, the Koch curve and the Sierspinski gasket are homogeneous since these fractals consist of a geometrical figure which repeats on an ever-reduced scale. Fractal analysis is a useful method for their study. However, real-world fractals are not homogeneous; there is rarely an identical motif repeated on all scales. Their singularity may vary on different subsets; implying that these objects are multifractal. Multifractal analysis is a useful way to systematically characterize the spatial heterogeneity of both theoretical and experimental fractal patterns. However, the tools for multifractal analysis of objects in Euclidean space are not suitable for complex networks. In this thesis, we propose a new box covering algorithm for multifractal analysis of complex networks. This algorithm is demonstrated in the computation of the generalized fractal dimensions of some theoretical networks, namely scale-free networks, small-world networks, random networks, and a kind of real networks, namely PPI networks of different species. Our main finding is the existence of multifractality in scale-free networks and PPI networks, while the multifractal behaviour is not confirmed for small-world networks and random networks. As another application, we generate gene interactions networks for patients and healthy people using the correlation coefficients between microarrays of different genes. Our results confirm the existence of multifractality in gene interactions networks. This multifractal analysis then provides a potentially useful tool for gene clustering and identification. The third part of the thesis aims to investigate the topological properties of networks constructed from time series. Characterizing complicated dynamics from time series is a fundamental problem of continuing interest in a wide variety of fields. Recent works indicate that complex network theory can be a powerful tool to analyse time series. Many existing methods for transforming time series into complex networks share a common feature: they define the connectivity of a complex network by the mutual proximity of different parts (e.g., individual states, state vectors, or cycles) of a single trajectory. In this thesis, we propose a new method to construct networks of time series: we define nodes by vectors of a certain length in the time series, and weight of edges between any two nodes by the Euclidean distance between the corresponding two vectors. We apply this method to build networks for fractional Brownian motions, whose long-range dependence is characterised by their Hurst exponent. We verify the validity of this method by showing that time series with stronger correlation, hence larger Hurst exponent, tend to have smaller fractal dimension, hence smoother sample paths. We then construct networks via the technique of horizontal visibility graph (HVG), which has been widely used recently. We confirm a known linear relationship between the Hurst exponent of fractional Brownian motion and the fractal dimension of the corresponding HVG network. In the first application, we apply our newly developed box-covering algorithm to calculate the generalized fractal dimensions of the HVG networks of fractional Brownian motions as well as those for binomial cascades and five bacterial genomes. The results confirm the monoscaling of fractional Brownian motion and the multifractality of the rest. As an additional application, we discuss the resilience of networks constructed from time series via two different approaches: visibility graph and horizontal visibility graph. Our finding is that the degree distribution of VG networks of fractional Brownian motions is scale-free (i.e., having a power law) meaning that one needs to destroy a large percentage of nodes before the network collapses into isolated parts; while for HVG networks of fractional Brownian motions, the degree distribution has exponential tails, implying that HVG networks would not survive the same kind of attack.

Identifying programs to reduce road trauma to A.C.T. motorcyclists

A broad range of motorcycle safety programs and systems exist in Australia and New Zealand. These vary from statewide licensing and training systems run by government licensing and transport agencies to safety programs run in small communities and by individual rider groups. While the effectiveness of licensing and training has been reviewed and recommendations for improvement have been developed (e.g. Haworth & Mulvihill, 2005), little is known about many smaller or innovative programs, and their potential to improve motorcycle safety in the ACT.

Impacts of periodic tillage on soil C stocks : a synthesis

Long-term loss of soil C stocks under conventional tillage and accrual of soil C following adoption of no-tillage have been well documented. No-tillage use is spreading, but it is common to occasionally till within a no-till regime or to regularly alternate between till and no-till practices within a rotation of different crops. Short-term studies indicate that substantial amounts of C can be lost from the soil immediately following a tillage event, but there are few field studies that have investigated the impact of infrequent tillage on soil C stocks. How much of the C sequestered under no-tillage is likely to be lost if the soil is tilled? What are the longer-term impacts of continued infrequent no-tillage? If producers are to be compensated for sequestering C in soil following adoption of conservation tillage practices, the impacts of infrequent tillage need to be quantified. A few studies have examined the short-term impacts of tillage on soil C and several have investigated the impacts of adoption of continuous no-tillage. We present: (1) results from a modeling study carried out to address these questions more broadly than the published literature allows, (2) a review of the literature examining the short-term impacts of tillage on soil C, (3) a review of published studies on the physical impacts of tillage and (4) a synthesis of these components to assess how infrequent tillage impacts soil C stocks and how changes in tillage frequency could impact soil C stocks and C sequestration. Results indicate that soil C declines significantly following even one tillage event (1-11 % of soil C lost). Longer-term losses increase as frequency of tillage increases. Model analyses indicate that cultivating and ripping are less disruptive than moldboard plowing, and soil C for those treatments average just 6% less than continuous NT compared to 27% less for CT. Most (80%) of the soil C gains of NT can be realized with NT coupled with biannual cultivating or ripping. (C) 2007 Elsevier B.V. All rights reserved.

Stabilization mechanisms of soil organic matter: Implications for C-saturation of soils

The relationship between soil structure and the ability of soil to stabilize soil organic matter (SOM) is a key element in soil C dynamics that has either been overlooked or treated in a cursory fashion when developing SOM models. The purpose of this paper is to review current knowledge of SOM dynamics within the framework of a newly proposed soil C saturation concept. Initially, we distinguish SOM that is protected against decomposition by various mechanisms from that which is not protected from decomposition. Methods of quantification and characteristics of three SOM pools defined as protected are discussed. Soil organic matter can be: (1) physically stabilized, or protected from decomposition, through microaggregation, or (2) intimate association with silt and clay particles, and (3) can be biochemically stabilized through the formation of recalcitrant SOM compounds. In addition to behavior of each SOM pool, we discuss implications of changes in land management on processes by which SOM compounds undergo protection and release. The characteristics and responses to changes in land use or land management are described for the light fraction (LF) and particulate organic matter (POM). We defined the LF and POM not occluded within microaggregates (53-250 mum sized aggregates as unprotected. Our conclusions are illustrated in a new conceptual SOM model that differs from most SOM models in that the model state variables are measurable SOM pools. We suggest that physicochemical characteristics inherent to soils define the maximum protective capacity of these pools, which limits increases in SOM (i.e. C sequestration) with increased organic residue inputs.

Validation of the Chinese version of the Problem Areas in Diabetes (PAID-C) scale

OBJECTIVE To examine the psychometric properties of a Chinese version of the Problem Areas In Diabetes (PAID-C) scale. RESEARCH DESIGN AND METHODS The reliability and validity of the PAID-C were evaluated in a convenience sample of 205 outpatients with type 2 diabetes. Confirmatory factor analysis, Bland-Altman analysis, and Spearman's correlations facilitated the psychometric evaluation. RESULTS Confirmatory factor analysis confirmed a one-factor structure of the PAID-C (χ2/df ratio = 1.894, goodness-of-fit index = 0.901, comparative fit index = 0.905, root mean square error of approximation = 0.066). The PAID-C was associated with A1C (rs = 0.15; P < 0.05) and diabetes self-care behaviors in general diet (rs = −0.17; P < 0.05) and exercise (rs = −0.17; P < 0.05). The 4-week test-retest reliability demonstrated satisfactory stability (rs = 0.83; P < 0.01). CONCLUSIONS The PAID-C is a reliable and valid measure to determine diabetes-related emotional distress in Chinese people with type 2 diabetes.