Population Genetic Analysis Infers Migration Pathways of Phytophthora ramorum in US Nurseries

Recently introduced, exotic plant pathogens may exhibit low genetic diversity and be limited to clonal reproduction. However, rapidly mutating molecular markers such as microsatellites can reveal genetic variation within these populations and be used to model putative migration patterns. Phytophthora ramorum is the exotic pathogen, discovered in the late 1990s, that is responsible for sudden oak death in California forests and ramorum blight of common ornamentals. The nursery trade has moved this pathogen from source populations on the West Coast to locations across the United States, thus risking introduction to other native forests. We examined the genetic diversity of P. ramorum in United States nurseries by microsatellite genotyping 279 isolates collected from 19 states between 2004 and 2007. Of the three known P. ramorum clonal lineages, the most common and genetically diverse lineage in the sample was NA1. Two eastward migration pathways were revealed in the clustering of NA1 isolates into two groups, one containing isolates from Connecticut, Oregon, and Washington and the other isolates from California and the remaining states. This finding is consistent with trace forward analyses conducted by the US Department of Agriculture's Animal and Plant Health Inspection Service. At the same time, genetic diversities in several states equaled those observed in California, Oregon, and Washington and two-thirds of multilocus genotypes exhibited limited geographic distributions, indicating that mutation was common during or subsequent to migration. Together, these data suggest that migration, rapid mutation, and genetic drift all play a role in structuring the genetic diversity of P. ramorum in US nurseries. This work demonstrates that fast-evolving genetic markers can be used to examine the evolutionary processes acting on recently introduced pathogens and to infer their putative migration patterns, thus showing promise for the application of forensics to plant pathogens

Heterochromatin and the molecular mechanisms of 'parent-of-origin' effects in animals.

Twenty five years ago it was proposed that conserved components of constitutive heterochromatin assemble heterochromatinlike complexes in euchromatin and this could provide a general mechanism for regulating heritable (cell-to-cell) changes in gene expressibility. As a special case, differences in the assembly of heterochromatin-like complexes on homologous chromosomes might also regulate the parent-of-origin-dependent gene expression observed in placental mammals. Here, the progress made in the intervening period with emphasis on the role of heterochromatin and heterochromatin-like complexes in parent-of-origin effects in animals is reviewed

The 2010 Hans Cloos lecture : the contribution of urban geology to the development, regeneration and conservation of cities

Urban geology began to develop in the 1950s, particularly in California in relation to land-use planning, and led to Robert Legget publishing his seminal book “Cities and geology” in 1973. Urban geology has now become an important part of engineering geology. Research and practice has seen the evolution from single theme spatial datasets to multi-theme and multi-dimensional outputs for a wide range of users. In parallel to the development of these new outputs to aid urban development, regeneration and conservation, has been the growing recognition that city authorities need access to extensive databases of geo-information that are maintained in the long-term and renewed regularly. A further key advance has been the recognition that, in the urban environment, knowledge and understanding of the geology need to be integrated with those of other environmental topics (for example, biodiversity) and, increasingly, with the research of social scientists, economists and others. Despite these advances, it is suggested that the value of urban geology is not fully recognised by those charged with the management and improvement of the world’s cities. This may be because engineering geologists have failed to adequately demonstrate the benefits of urban geological applications in terms of cost and environmental improvement, have not communicated these benefits well enough and have not clearly shown the long-term contribution of geo-information to urban sustainability. Within this context future actions to improve the situation are proposed

Detection of Multiple Innervation Zones from Multi-Channel Surface EMG Recordings with Low Signal-to-Noise Ratio Using Graph-Cut Segmentation

Knowledge of the location of muscle Innervation Zones (IZs) is important in many applications, e.g. for minimizing the quantity of injected botulinum toxin for the treatment of spasticity or for deciding on the type of episiotomy during child delivery. Surface EMG (sEMG) can be noninvasively recorded to assess physiological and morphological characteristics of contracting muscles. However, it is not often possible to record signals of high quality. Moreover, muscles could have multiple IZs, which should all be identified. We designed a fully-automatic algorithm based on the enhanced image Graph-Cut segmentation and morphological image processing methods to identify up to five IZs in 60-ms intervals of very-low to moderate quality sEMG signal detected with multi-channel electrodes (20 bipolar channels with Inter Electrode Distance (IED) of 5 mm). An anisotropic multilayered cylinder model was used to simulate 750 sEMG signals with signal-to-noise ratio ranging from -5 to 15 dB (using Gaussian noise) and in each 60-ms signal frame, 1 to 5 IZs were included. The micro- and macro- averaged performance indices were then reported for the proposed IZ detection algorithm. In the micro-averaging procedure, the number of True Positives, False Positives and False Negatives in each frame were summed up to generate cumulative measures. In the macro-averaging, on the other hand, precision and recall were calculated for each frame and their averages are used to determine F1-score. Overall, the micro (macro)-averaged sensitivity, precision and F1-score of the algorithm for IZ channel identification were 82.7% (87.5%), 92.9% (94.0%) and 87.5% (90.6%), respectively. For the correctly identified IZ locations, the average bias error was of 0.02±0.10 IED ratio. Also, the average absolute conduction velocity estimation error was 0.41±0.40 m/s for such frames. The sensitivity analysis including increasing IED and reducing interpolation coefficient for time samples was performed. Meanwhile, the effect of adding power-line interference and using other image interpolation methods on the deterioration of the performance of the proposed algorithm was investigated. The average running time of the proposed algorithm on each 60-ms sEMG frame was 25.5±8.9 (s) on an Intel dual-core 1.83 GHz CPU with 2 GB of RAM. The proposed algorithm correctly and precisely identified multiple IZs in each signal epoch in a wide range of signal quality and is thus a promising new offline tool for electrophysiological studies.peerReviewe