Non-pharmacological interventions in secondary schizophrenia

Schizophrenia may not be a single disease, but the result of a diverse set of related conditions. Modern neuroscience is beginning to reveal some of the genetic and environmental underpinnings of schizophrenia; however, an approach less well travelled is to examine the medical disorders that produce symptoms resembling schizophrenia. This book is the first major attempt to bring together the diseases that produce what has been termed 'secondary schizophrenia'. International experts from diverse backgrounds ask the questions: does this medical disorder, or drug, or condition cause psychosis? If yes, does it resemble schizophrenia? What mechanisms form the basis of this relationship? What implications does this understanding have for aetiology and treatment? The answers are a feast for clinicians and researchers of psychosis and schizophrenia. They mark the next step in trying to meet the most important challenge to modern neuroscience – understanding and conquering this most mysterious of human diseases.

New palladium catalysed reactions of bromoporphyrins: synthesis and crystal structures of nickel(II) complexes of primary 5-aminoporphyrin, 5,5’-bis(porphyrinyl) secondary amine, and 5-hydroxyporphyrin

Primary aminoporphyrin, secondary bis(porphyrinyl)amine and hydroxyporphyrin complexes have been isolated and characterised both spectroscopically and crystallographically from the reaction of 5-bromo-10,15,20-triphenylporphyrinato-nickel(II) with hydrazine under palladium catalysis.

Hierarchical Bayesian models for estimating the extent of plant pest invasions

Plant biosecurity requires statistical tools to interpret field surveillance data in order to manage pest incursions that threaten crop production and trade. Ultimately, management decisions need to be based on the probability that an area is infested or free of a pest. Current informal approaches to delimiting pest extent rely upon expert ecological interpretation of presence / absence data over space and time. Hierarchical Bayesian models provide a cohesive statistical framework that can formally integrate the available information on both pest ecology and data. The overarching method involves constructing an observation model for the surveillance data, conditional on the hidden extent of the pest and uncertain detection sensitivity. The extent of the pest is then modelled as a dynamic invasion process that includes uncertainty in ecological parameters. Modelling approaches to assimilate this information are explored through case studies on spiralling whitefly, Aleurodicus dispersus and red banded mango caterpillar, Deanolis sublimbalis. Markov chain Monte Carlo simulation is used to estimate the probable extent of pests, given the observation and process model conditioned by surveillance data. Statistical methods, based on time-to-event models, are developed to apply hierarchical Bayesian models to early detection programs and to demonstrate area freedom from pests. The value of early detection surveillance programs is demonstrated through an application to interpret surveillance data for exotic plant pests with uncertain spread rates. The model suggests that typical early detection programs provide a moderate reduction in the probability of an area being infested but a dramatic reduction in the expected area of incursions at a given time. Estimates of spiralling whitefly extent are examined at local, district and state-wide scales. The local model estimates the rate of natural spread and the influence of host architecture, host suitability and inspector efficiency. These parameter estimates can support the development of robust surveillance programs. Hierarchical Bayesian models for the human-mediated spread of spiralling whitefly are developed for the colonisation of discrete cells connected by a modified gravity model. By estimating dispersal parameters, the model can be used to predict the extent of the pest over time. An extended model predicts the climate restricted distribution of the pest in Queensland. These novel human-mediated movement models are well suited to demonstrating area freedom at coarse spatio-temporal scales. At finer scales, and in the presence of ecological complexity, exploratory models are developed to investigate the capacity for surveillance information to estimate the extent of red banded mango caterpillar. It is apparent that excessive uncertainty about observation and ecological parameters can impose limits on inference at the scales required for effective management of response programs. The thesis contributes novel statistical approaches to estimating the extent of pests and develops applications to assist decision-making across a range of plant biosecurity surveillance activities. Hierarchical Bayesian modelling is demonstrated as both a useful analytical tool for estimating pest extent and a natural investigative paradigm for developing and focussing biosecurity programs.

Factors affecting somatic embryogenesis and transformation in modern plant breeding

Somatic embryogenesis and transformation systems are indispensable modern plant breeding components since they provide an alternative platform to develop control strategies against the plethora of pests and diseases affecting many agronomic crops. This review discusses some of the factors affecting somatic embryogenesis and transformation, highlights the advantages and limitations of these systems and explores these systems as breeding tools for the development of crops with improved agronomic traits. The regeneration of non-chimeric transgenic crops through somatic embryogenesis with introduced disease and pest-resistant genes for instance, would be of significant benefit to growers worldwide.

Where does it say I have to do that? How can secondary schools enact assessment policy for students with disabilities

This paper describes effective ways secondary school leaders can enact curriculum policy, particularly assessment practices, to support learning for students with disabilities in mainstream schools. Assessment for learning (AfL) as a pedagogic practice, has gained recent importance through inclusion in curriculum policy in Queensland, Australia. AfL is the frequent assessment of student progress that identifies learning needs and informs future teaching and learning. Assessment of student progress of the standards based curriculum has provided challenges for schools attempting to meet the needs of “all” learners. This paper highlights findings of a small case study to model successful leadership practices used in an inclusive secondary school to improve achievement of students with disabilities through assessment. Successful leadership practices that can be generalized to improve achievement of all learners include making sense of policy for staff; developing staff common and shared beliefs and actions; organizing professional learning opportunities and arranging collaborative curriculum planning and co-teaching.

Depth of focus and visual acuity with primary and secondary spherical aberration

It is known that the depth of focus (DOF) of the human eye can be affected by the higher order aberrations. We estimated the optimal combinations of primary and secondary Zernike spherical aberration to expand the DOF and evaluated their efficiency in real eyes using an adaptive optics system. The ratio between increased DOF and loss of visual acuity was used as the performance indicator. The results indicate that primary or secondary spherical aberration alone shows similar effectiveness in extending the DOF. However, combinations of primary and secondary spherical aberration with different signs provide better efficiency for expanding the DOF. This finding suggests that the optimal combinations of primary and secondary spherical aberration may be useful in the design of optical presbyopic corrections. © 2011 Elsevier Ltd. All rights reserved.

Hierarchical Bayesian modelling of early detection surveillance for plant pest invasions

Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.