Aspects of the interaction between Xanthorrhoea australis and Phytophthora cinnamomi in south-western Victoria, Australia

Diseases in natural ecosystems are often assumed to be less severe than those observed in domestic cropping systems due to the extensive biodiversity exhibited in wild vegetation communities. In Australia, it is this natural biodiversity that is now under threat from Phytophthora cinnamomi. The soilborne Oomycete causes severe decline of native vegetation communities in south-western Victoria, Australia, disrupting the ecological balance of native forest and heathland communities. While the effect of disease caused by P. cinnamomi on native vegetation communities in Victoria has been extensively investigated, little work has focused on the Anglesea healthlands in south-western Victoria. Nothing is known about the population structure of P. cinnamomi at Anglesea. This project was divided into two main components to investigate fundamental issues affecting the management of P. cinnamomi in the Anglesea heathlands. The first component examined the phenotypic characteristics of P. cinnamomi isolates sampled from the population at Anglesea, and compared these with isolates from other regions in Victoria, and also from Western Australia. The second component of the project investigated the effect of the fungicide phosphonate on the host response following infection by P. cinnamomi. Following soil sampling in the Anglesea heathlands, a collection of P, cinnamomi isolates was established. Morphological and physiological traits of each isolate were examined. All isolates were found to be of the A2 mating type. Variation was demonstrated among isolates in the following characteristics: radial growth rate on various nutrient media, sporangial production, and sporangial dimensions. Oogonial dimensions did not differ significantly between isolates. Morphological and physiological variation was rarely dependant on isolate origin. To examine the genetic diversity among isolates and to determine whether phenotypic variation observed was genetically based, Random Amplified Polymorphic DNA (RAPD) analyses were conducted. No significant variation was observed among isolates based on an analysis of molecular variance (AMQVA). The results are discussed in relation to population biology, and the effect of genetic variation on population structure and population dynamics. X australis, an arborescent monocotyledon indigenous to Australia, is highly susceptible to infection by P. cinnamomi. It forms an important component of the heathland vegetation community, providing habitat for native flora and fauna, A cell suspension culture system was developed to investigate the effect of the fungicide phosphonate on the host-pathogen interaction between X. australis and P. cinnamomi. This allowed the interaction between the host and the pathogen to be examined at a cellular level. Subsequently, histological studies using X. australis seedlings were undertaken to support the cellular study. Observations in the cell culture system correlated well with those in the plant. The anatomical structure of X australis roots was examined to assist in the interpretation of results of histopathological studies. The infection of single cells and roots of X. australis, and the effect of phosphonate on the interaction are described. Phosphonate application prior to inoculation with P. cinnamomi reduced the infection of cells in culture and of cells in planta. In particular, phosphonate was found to stimulate the production of phenolic material in roots of X australis seedlings and in cells in suspension cultures. In phosphonate-treated roots of X australis seedlings, the deposition of electron dense material, possibly lignin or cellulose, was observed following infection with P. cinnamomi. It is proposed that this is a significant consequence of the stimulation of plant defence pathways by the fungicide. Results of the study are discussed in terms of the implications of the findings on management of the Anglesea heathlands in Victoria, taking into account variation in pathogen morphology, pathogenicity and genotype. The mode of action of phosphonate in the plant is discussed in relation to plant physiology and biochemistry.

Automated classification of human daily activities in ambulatory environment

This paper presents a human daily activity classification approach based on the sensory data collected from a single tri-axial accelerometer worn on waist belt. The classification algorithm was realized to distinguish 6 different activities including standing, jumping, sitting-down, walking, running and falling through three major steps: wavelet transformation, Principle Component Analysis (PCA)-based dimensionality reduction and followed by implementing a radial basis function (RBF) kernel Support Vector Machine (SVM) classifier. Two trials were conducted to evaluate different aspects of the classification scheme. In the first trial, the classifier was trained and evaluated by using a dataset of 420 samples collected from seven subjects by using a k-fold cross-validation method. The parameters σ and c of the RBF kernel were optimized through automatic searching in terms of yielding the highest recognition accuracy and robustness. In the second trial, the generation capability of the classifier was also validated by using the dataset collected from six new subjects. The average classification rates of 95% and 93% are obtained in trials 1 and 2, respectively. The results in trial 2 show the system is also good at classifying activity signals of new subjects. It can be concluded that the collective effects of the usage of single accelerometer sensing, the setting of the accelerometer placement and efficient classifier would make this wearable sensing system more realistic and more comfortable to be implemented for long-term human activity monitoring and classification in ambulatory environment, therefore, more acceptable by users.

Temporal PDMs for gait classification

Gait classification is a developing research area, particularly with regards to biometrics. It aims to use the distinctive spatial and temporal characteristics of human motion to classify differing activities. As a biometric, this extends to recognising different people by the heterogeneous aspects of their gait. This research aims to use a modified deformable model, the temporal PDM, to distinguish the movements of a walking and miming person. The movement of 2D points on the moving form is used to provide input into the model and classify the type of gait present.

Improved GART neural network model for pattern classification and rule extraction with application to power systems

Generalized adaptive resonance theory (GART) is a neural network model that is capable of online learning and is effective in tackling pattern classification tasks. In this paper, we propose an improved GART model (IGART), and demonstrate its applicability to power systems. IGART enhances the dynamics of GART in several aspects, which include the use of the Laplacian likelihood function, a new vigilance function, a new match-tracking mechanism, an ordering algorithm for determining the sequence of training data, and a rule extraction capability to elicit if-then rules from the network. To assess the effectiveness of IGART and to compare its performances with those from other methods, three datasets that are related to power systems are employed. The experimental results demonstrate the usefulness of IGART with the rule extraction capability in undertaking classification problems in power systems engineering.

Towards a classification of biomarkers of neuropsychiatric disease: from encompass to compass

There is currently considerable imprecision in the nosology of biomarkers used in the study of neuropsychiatric disease. The neuropsychiatric field lags behind others such as oncology, wherein, rather than using 'biomarker' as a blanket term for a diverse range of clinical phenomena, biomarkers have been actively classified into separate categories, including prognostic and predictive tests. A similar taxonomy is proposed for neuropsychiatric diseases in which the core biology remains relatively unknown. This paper divides potential biomarkers into those of (1) risk, (2) diagnosis/trait, (3) state or acuity, (4) stage, (5) treatment response and (6) prognosis, and provides illustrative exemplars. Of course, biomarkers rely on available technology and, as we learn more about the neurobiological correlates of neuropsychiatric disorders, we will realize that the classification of biomarkers across these six categories can change, and some markers may fit into more than one category.Molecular Psychiatry advance online publication, 28 October 2014; doi:10.1038/mp.2014.139.

Medulloblastoma Down Under 2013 : a report from the third annual meeting of the International Medulloblastoma Working Group.

Medulloblastoma is curable in approximately 70% of patients. Over the past decade, progress in improving survival using conventional therapies has stalled, resulting in reduced quality of life due to treatment-related side effects, which are a major concern in survivors. The vast amount of genomic and molecular data generated over the last 5-10 years encourages optimism that improved risk stratification and new molecular targets will improve outcomes. It is now clear that medulloblastoma is not a single-disease entity, but instead consists of at least four distinct molecular subgroups: WNT/Wingless, Sonic Hedgehog, Group 3, and Group 4. The Medulloblastoma Down Under 2013 meeting, which convened at Bunker Bay, Australia, brought together 50 leading clinicians and scientists. The 2-day agenda included focused sessions on pathology and molecular stratification, genomics and mouse models, high-throughput drug screening, and clinical trial design. The meeting established a global action plan to translate novel biologic insights and drug targeting into treatment regimens to improve outcomes. A consensus was reached in several key areas, with the most important being that a novel classification scheme for medulloblastoma based on the four molecular subgroups, as well as histopathologic features, should be presented for consideration in the upcoming fifth edition of the World Health Organization's classification of tumours of the central nervous system. Three other notable areas of agreement were as follows: (1) to establish a central repository of annotated mouse models that are readily accessible and freely available to the international research community; (2) to institute common eligibility criteria between the Children's Oncology Group and the International Society of Paediatric Oncology Europe and initiate joint or parallel clinical trials; (3) to share preliminary high-throughput screening data across discovery labs to hasten the development of novel therapeutics. Medulloblastoma Down Under 2013 was an effective forum for meaningful discussion, which resulted in enhancing international collaborative clinical and translational research of this rare disease. This template could be applied to other fields to devise global action plans addressing all aspects of a disease, from improved disease classification, treatment stratification, and drug targeting to superior treatment regimens to be assessed in cooperative international clinical trials.