Evidence for CRHR1 in multiple sclerosis using supervised machine learning and meta-analysis in 12 566 individuals

The primary genetic risk factor in multiple sclerosis (MS) is the HLA-DRB1*1501 allele; however, much of the remaining genetic contribution to MS has yet to be elucidated. Several lines of evidence support a role for neuroendocrine system involvement in autoimmunity which may, in part, be genetically determined. Here, we comprehensively investigated variation within eight candidate hypothalamic-pituitary-adrenal (HPA) axis genes and susceptibility to MS. A total of 326 SNPs were investigated in a discovery dataset of 1343 MS cases and 1379 healthy controls of European ancestry using a multi-analytical strategy. Random Forests, a supervised machine-learning algorithm, identified eight intronic SNPs within the corticotrophin-releasing hormone receptor 1 or CRHR1 locus on 17q21.31 as important predictors of MS. On the basis of univariate analyses, six CRHR1 variants were associated with decreased risk for disease following a conservative correction for multiple tests. Independent replication was observed for CRHR1 in a large meta-analysis comprising 2624 MS cases and 7220 healthy controls of European ancestry. Results from a combined meta-analysis of all 3967 MS cases and 8599 controls provide strong evidence for the involvement of CRHR1 in MS. The strongest association was observed for rs242936 (OR = 0.82, 95% CI = 0.74-0.90, P = 9.7 × 10-5). Replicated CRHR1 variants appear to exist on a single associated haplotype. Further investigation of mechanisms involved in HPA axis regulation and response to stress in MS pathogenesis is warranted. © The Author 2010. Published by Oxford University Press. All rights reserved.

How long is a tweet? Mapping dynamic conversation networks on Twitter using Gawk and Gephi

Twitter is now well established as the world’s second most important social media platform, after Facebook. Its 140-character updates are designed for brief messaging, and its network structures are kept relatively flat and simple: messages from users are either public and visible to all (even to unregistered visitors using the Twitter website), or private and visible only to approved ‘followers’ of the sender; there are no more complex definitions of degrees of connection (family, friends, friends of friends) as they are available in other social networks. Over time, Twitter users have developed simple, but effective mechanisms for working around these limitations: ‘#hashtags’, which enable the manual or automatic collation of all tweets containing the same #hashtag, as well allowing users to subscribe to content feeds that contain only those tweets which feature specific #hashtags; and ‘@replies’, which allow senders to direct public messages even to users whom they do not already follow. This paper documents a methodology for extracting public Twitter activity data around specific #hashtags, and for processing these data in order to analyse and visualize the @reply networks existing between participating users – both overall, as a static network, and over time, to highlight the dynamic structure of @reply conversations. Such visualizations enable us to highlight the shifting roles played by individual participants, as well as the response of the overall #hashtag community to new stimuli – such as the entry of new participants or the availability of new information. Over longer timeframes, it is also possible to identify different phases in the overall discussion, or the formation of distinct clusters of preferentially interacting participants.

AtBAG7, an Arabidopsis Bcl-2-associated athanogene, resides in the endoplasmic reticulum and is involved in the unfolded protein response

The Bcl-2-associated athanogene (BAG) family is an evolutionarily conserved, multifunctional group of cochaperones that perform diverse cellular functions ranging from proliferation to growth arrest and cell death in yeast, in mammals, and, as recently observed, in plants. The Arabidopsis genome contains seven homologs of the BAG family, including four with domain organization similar to animal BAGs. In the present study we show that an Arabidopsis BAG, AtBAG7, is a uniquely localized endoplasmic reticulum (ER) BAG that is necessary for the proper maintenance of the unfolded protein response (UPR). AtBAG7was shown to interact directly in vivo with themolecular chaperone, AtBiP2, by bimolecular fluorescence complementation assays, and the interaction was confirmed by yeast two-hybrid assay. Treatment with an inducer of UPR, tunicamycin, resulted in accelerated cell death of AtBAG7-null mutants. Furthermore, AtBAG7 knockouts were sensitive to known ER stress stimuli, heat and cold. In these knockouts heat sensitivity was reverted successfully to the wild-type phenotype with the addition of the chemical chaperone, tauroursodexycholic acid (TUDCA). Real-time PCR of ER stress proteins indicated that the expression of the heat-shock protein, AtBiP3, is selectively up-regulated in AtBAG7-null mutants upon heat and cold stress. Our results reveal an unexpected diversity of the plant's BAG gene family and suggest that AtBAG7 is an essential component of the UPR during heat and cold tolerance, thus confirming the cytoprotective role of plant BAGs.

Low temperature CO sensitive nanostructured WO3 thin films doped with Fe

Nanostructured tungsten oxide thin film based gas sensors have been developed by thermal evaporation method to detect CO at low operating temperatures. The influence of Fe-doping and annealing heat treatment on microstructural and gas sensing properties of these films have been investigated. Fe was incorporated in WO3 film by co-evaporation and annealing was performed at 400oC for 2 hours in air. AFM analysis revealed a grain size of about 10-15 nm in all the films. GIXRD analysis showed that as-deposited films are amorphous and annealing at 400oC improved the crystallinity. Raman and XRD analysis indicated that Fe is incorporated in the WO3 matrix as a substitutional impurity, resulting in shorter O-W-O bonds and lattice cell parameters. Doping with Fe contributed significantly towards CO sensing performance of WO3 thin films. A good response to various concentrations (10-1000 ppm) of CO has been achieved with 400oC annealed Fe-doped WO3 film at a low operating temperature of 150oC.

Models of collective cell motion for cell populations with different aspect ratio : diffusion, proliferation and travelling waves

Continuum, partial differential equation models are often used to describe the collective motion of cell populations, with various types of motility represented by the choice of diffusion coefficient, and cell proliferation captured by the source terms. Previously, the choice of diffusion coefficient has been largely arbitrary, with the decision to choose a particular linear or nonlinear form generally based on calibration arguments rather than making any physical connection with the underlying individual-level properties of the cell motility mechanism. In this work we provide a new link between individual-level models, which account for important cell properties such as varying cell shape and volume exclusion, and population-level partial differential equation models. We work in an exclusion process framework, considering aligned, elongated cells that may occupy more than one lattice site, in order to represent populations of agents with different sizes. Three different idealizations of the individual-level mechanism are proposed, and these are connected to three different partial differential equations, each with a different diffusion coefficient; one linear, one nonlinear and degenerate and one nonlinear and nondegenerate. We test the ability of these three models to predict the population level response of a cell spreading problem for both proliferative and nonproliferative cases. We also explore the potential of our models to predict long time travelling wave invasion rates and extend our results to two dimensional spreading and invasion. Our results show that each model can accurately predict density data for nonproliferative systems, but that only one does so for proliferative systems. Hence great care must be taken to predict density data for with varying cell shape.

Sequential Monte Carlo for Bayesian sequentially designed experiments for discrete data

In this paper we present a sequential Monte Carlo algorithm for Bayesian sequential experimental design applied to generalised non-linear models for discrete data. The approach is computationally convenient in that the information of newly observed data can be incorporated through a simple re-weighting step. We also consider a flexible parametric model for the stimulus-response relationship together with a newly developed hybrid design utility that can produce more robust estimates of the target stimulus in the presence of substantial model and parameter uncertainty. The algorithm is applied to hypothetical clinical trial or bioassay scenarios. In the discussion, potential generalisations of the algorithm are suggested to possibly extend its applicability to a wide variety of scenarios

Response of partially grouted wider reinforced masonry walls to inplane cyclic shear

Partially grouted wider reinforced masonry wall, built predominantly using face shell bedded hollow concrete blocks, is an economical structural system and is popularly used in the cyclonic areas; its out-of-plane response to lateral loading is well understood, unfortunately its inplane shear behaviour is less well understood as to the effect of partial gouting in intervening the load paths within the wall. For rational analysis of the wall clarification is sought as to whether the wall acts as a composite of unreinforced panels and reinforced cores or as a continuum of masonry embedded with reinforced at wider spacing. This paper reports the results of four full scale walls tested under inplane cyclic shear loading to provide some insight into the effect of the grout cores in altering the load paths within the wall. The global lateral load - lateral deflection hysteric curves as well as local responses of some critical zones of the shear walls are presented.

Evaluation cortical bone elasticity in response to pulse power excitation using ultrasonic technique

This paper presents the ultrasonic velocity measurement method which investigates the possible effects of high voltage high frequency pulsed power on cortical bone material elasticity. Before applying a pulsed power signal on a live bone, it is essential to determine the safe parameters of pulsed power applied on bone non-destructively. Therefore, the possible changes in cortical bone material elasticity due to a specified pulsed power excitation have been investigated. A controllable positive buck-boost converter with adjustable output voltage and frequency has been used to generate high voltage pulses (500V magnitude at 10 KHz frequency). To determine bone elasticity, an ultrasonic velocity measurement has been conducted on two groups of control (unexposed to pulse power but in the same environmental condition) and cortical bone samples exposed to pulsed power. Young’s modulus of cortical bone samples have been determined and compared before and after applying the pulsed power signal. After applying the high voltage pulses, no significant variation in elastic property of cortical bone specimens was found compared to the control. The result shows that pulsed power with nominated parameters can be applied on cortical bone tissue without any considerable negative effect on elasticity of bone material.

Structural damage detection using frequency response functions and neural networks

This paper illustrates the damage identification and condition assessment of a three story bookshelf structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). A major obstacle of using measured frequency response function data is a large size input variables to ANNs. This problem is overcome by applying a data reduction technique called principal component analysis (PCA). In the proposed procedure, ANNs with their powerful pattern recognition and classification ability were used to extract damage information such as damage locations and severities from measured FRFs. Therefore, simple neural network models are developed, trained by Back Propagation (BP), to associate the FRFs with the damage or undamaged locations and severity of the damage of the structure. Finally, the effectiveness of the proposed method is illustrated and validated by using the real data provided by the Los Alamos National Laboratory, USA. The illustrated results show that the PCA based artificial Neural Network method is suitable and effective for damage identification and condition assessment of building structures. In addition, it is clearly demonstrated that the accuracy of proposed damage detection method can also be improved by increasing number of baseline datasets and number of principal components of the baseline dataset.

Structural damage identification with noise polluted Frequency Response Functions (FRFs)

Damage detection in structures has become increasingly important in recent years. While a number of damage detection and localization methods have been proposed, very few attempts have been made to explore the structure damage with noise polluted data which is unavoidable effect in real world. The measurement data are contaminated by noise because of test environment as well as electronic devices and this noise tend to give error results with structural damage identification methods. Therefore it is important to investigate a method which can perform better with noise polluted data. This paper introduces a new damage index using principal component analysis (PCA) for damage detection of building structures being able to accept noise polluted frequency response functions (FRFs) as input. The FRF data are obtained from the function datagen of MATLAB program which is available on the web site of the IASC-ASCE (International Association for Structural Control– American Society of Civil Engineers) Structural Health Monitoring (SHM) Task Group. The proposed method involves a five-stage process: calculation of FRFs, calculation of damage index values using proposed algorithm, development of the artificial neural networks and introducing damage indices as input parameters and damage detection of the structure. This paper briefly describes the methodology and the results obtained in detecting damage in all six cases of the benchmark study with different noise levels. The proposed method is applied to a benchmark problem sponsored by the IASC-ASCE Task Group on Structural Health Monitoring, which was developed in order to facilitate the comparison of various damage identification methods. The illustrated results show that the PCA-based algorithm is effective for structural health monitoring with noise polluted FRFs which is of common occurrence when dealing with industrial structures.

Integrating electrical vehicles to demand side response scheme in Queensland Australia

Depleting fossil fuel resources and increased accumulation of greenhouse gas emissions are increasingly making electrical vehicles (EV) attractive option for the transportation sector. However uncontrolled random charging and discharging of EVs may aggravate the problems of an already stressed system during the peak demand and cause voltage problems during low demand. This paper develops a demand side response scheme for properly integrating EVs in the Electrical Network. The scheme enacted upon information on electricity market conditions regularly released by the Australian Energy Market Operator (AEMO) on the internet. The scheme adopts Internet relays and solid state switches to cycle charging and discharging of EVs. Due to the pending time-of-use and real-price programs, financial benefits will represent driving incentives to consumers to implement the scheme. A wide-scale dissemination of the scheme is expected to mitigate excessive peaks on the electrical network with all associated technical, economic and social benefits.

Optical and microscopic study of a polymer-nanotube mixture for organic photovoltaic applications

Organic solar cells based on bulk heterojunction between a conductive polymer and a carbon nanostructure offer potential advantages compared to conventional inorganic cells. Low cost, light weight, flexibility and high peak power per unit weight are all features that can be considered a reality for organic photovoltaics. Although polymer/carbon nanotubes solar cells have been proposed, only low power conversion efficiencies have been reached without addressing the mechanisms responsible for this poor performance. The purpose of this work is therefore to investigate the basic interaction between carbon nanotubes and poly(3-hexylthiophene) in order to demonstrate how this interaction affects the performance of photovoltaic devices. The outcomes of this study are the contributions made to the knowledge of the phenomena explaining the behaviour of electronic devices based on carbon nanotubes and poly(3-hexylthiophene). In this PhD, polymer thin films with the inclusion of uniformly distributed carbon nanotubes were deposited from solution and characterised. The bulk properties of the composites were studied with microscopy and spectroscopy techniques to provide evidence of higher degrees of polymer order when interacting with carbon nanotubes. Although bulk investigation techniques provided useful information about the interaction between the polymer and the nanotubes, clear evidence of the phenomena affecting the heterojunction formed between the two species was investigated at nanoscale. Identifying chirality-driven polymer assisted assembly on the carbon nanotube surface was one of the major achievements of this study. Moreover, the analysis of the electrical behaviour of the heterojunction between the polymer and the nanotube highlighted the charge transfer responsible for the low performance of photovoltaic devices. Polymer and carbon nanotube composite-based devices were fabricated and characterised in order to study their electronic properties. The carbon nanotube introduction in the polymer matrix evidenced a strong electrical conductivity enhancement but also a lower photoconductivity response. Moreover, the extension of pristine polymer device characterisation models to composites based devices evidenced the conduction mechanisms related to nanotubes. Finally, the introduction of carbon nanotubes in the polymer matrix was demonstrated to improve the pristine polymer solar cell performance and the spectral response even though the power conversion efficiency is still too low.

The role of law in responding to climate change : emerging regulatory, liability and market approaches

Climate change presents as the archetypal environmental problem with short-term economic self-interest operating to the detriment of the long-term sustainability of our society. The scientific reports of the Intergovernmental Panel on Climate Change strongly assert that the stabilisation of emissions in the atmosphere, to avoid the adverse impacts of climate change, requires significant and rapid reductions in ‘business as usual’ global greenhouse gas emissions. The sheer magnitude of emissions reductions required, within this urgent timeframe, will necessitate an unprecedented level of international, multi-national and intra-national cooperation and will challenge conventional approaches to the creation and implementation of international and domestic legal regimes. To meet this challenge, existing international, national and local legal systems must harmoniously implement a strong international climate change regime through a portfolio of traditional and innovative legal mechanisms that swiftly transform current behavioural practices in emitting greenhouse gases. These include the imposition of strict duties to reduce emissions through the establishment of strong command and control regulation (the regulatory approach); mechanisms for the creation and distribution of liabilities for greenhouse gas emissions and climaterelated harm (the liability approach) and the use of innovative regulatory tools in the form of the carbon trading scheme (the market approach). The legal relations between these various regulatory, liability and market approaches must be managed to achieve a consistent, compatible and optimally effective legal regime to respond to the threat of climate change. The purpose of this thesis is to analyse and evaluate the emerging legal rules and frameworks, both international and Australian, required for the effective regulation of greenhouse gas emissions to address climate change in the context of the urgent and deep emissions reductions required to minimise the adverse impacts of climate change. In doing so, this thesis will examine critically the existing and potential role of law in effectively responding to climate change and will provide recommendations on the necessary reforms to achieve a more effective legal response to this global phenomenon in the future.

Phenological changes in six Australian subalpine plants in response to experimental warming and year-to-year variation

The likely phenological responses of plants to climate warming can be measured through experimental manipulation of field sites, but results are rarely validated against year-to-year changes in climate. Here, we describe the response of 1-5 years of experimental warming on phenology (budding, flowering and seed maturation) of six common subalpine plant species in the Australian Alps using the International Tundra Experiment (ITEX) protocol.2. Phenological changes in some species (particularly the forb Craspedia jamesii) were detected in experimental plots within a year of warming, whereas changes in most other species (the forb Erigeron bellidioides, the shrub Asterolasia trymalioides and the graminoids Carex breviculmis and Poa hiemata) did not develop until after 2-4 years; thus, there appears to be a cumulative effect of warming for some species across multiple years.3. There was evidence of changes in the length of the period between flowering and seed maturity in one species (P. hiemata) that led to a similar timing of seed maturation, suggesting compensation.4. Year-to-year variation in phenology was greater than variation between warmed and control plots and could be related to differences in thawing degree days (particularly, for E. bellidioides) due to earlier timing of budding and other events under warmer conditions. However, in Carex breviculmis, there was no association between phenology and temperature changes across years.5. These findings indicate that, although phenological changes occurred earlier in response to warming in all six species, some species showed buffered rather than immediate responses.6. Synthesis. Warming in ITEX open-top chambers in the Australian Alps produced earlier budding, flowering and seed set in several alpine species. Species also altered the timing of these events, particularly budding, in response to year-to-year temperature variation. Some species responded immediately, whereas in others the cumulative effects of warming across several years were required before a response was detected.