Getting to the root of neuronal signalling in plant-parasitic nematodes using RNA interference

A variety of genes expressed in preparasitic second-stage juveniles (J2) of plant-parasitic nematodes appear to be vulnerable to RNA interference (RNAi) in vitro by coupling double-stranded (ds)RNA soaking with the artificial stimulation of pharyngeal pumping. Also, there is mounting evidence that the in planta generation of nematode-specific double-stranded RNAs (dsRNAs) has real utility in the control of these pests. Although neuronally-expressed genes in Caenorhabditis elegans are commonly refractory to RNAi, we have discovered that neuronally-expressed genes in plant-parasitic nematodes are highly susceptible to RNAi and that silencing can be induced by simple soaking procedures without the need for pharyngeal stimulation. Since most front-line anthelmintics that are used for the control of nematode parasites of animals and humans act to disrupt neuromuscular coordination, we argue that intercellular signalling processes associated with neurons have much appeal as targets for transgenic plant-based control strategies for plant-parasitic nematodes. FMRFamide-like peptides (FLPs) are a large family of neuropeptides which are intimately associated with neuromuscular regulation, and our studies on flp gene function in plant-parasitic nematodes have revealed that their expression is central to coordinated locomotory activities. We propose that the high level of conservation in nervous systems across nematodes coupled with the RNAi-susceptibility of neuronally-expressed genes in plant-parasitic nematodes provides a valuable research tool which could be used to interrogate neuronal signalling processes in nematodes.

flp-32 Ligand/Receptor Silencing Phenocopy Faster Plant Pathogenic Nematodes

Restrictions on nematicide usage underscore the need for novel control strategies for plant pathogenic nematodes such as Globodera pallida (potato cyst nematode) that impose a significant economic burden on plant cultivation activities. The nematode neuropeptide signalling system is an attractive resource for novel control targets as it plays a critical role in sensory and motor functions. The FMRFamide-like peptides (FLPs) form the largest and most diverse family of neuropeptides in invertebrates, and are structurally conserved across nematode species, highlighting the utility of the FLPergic system as a broad-spectrum control target. flp-32 is expressed widely across nematode species. This study investigates the role of flp-32 in G. pallida and shows that: (i) Gp-flp-32 encodes the peptide AMRNALVRFamide; (ii) Gp-flp-32 is expressed in the brain and ventral nerve cord of G. pallida; (iii) migration rate increases in Gp-flp-32-silenced worms; (iv) the ability of G. pallida to infect potato plant root systems is enhanced in Gp-flp-32-silenced worms; (v) a novel putative Gp-flp-32 receptor (Gp-flp-32R) is expressed in G. pallida; and, (vi) Gp-flp-32R silenced worms also display an increase in migration rate. This work demonstrates that Gp30 flp-32 plays an intrinsic role in the modulation of locomotory behaviour in G. pallida, and putatively interacts with at least one novel G-protein coupled receptor (Gp-flp-32R). This is the first functional characterisation of a parasitic nematode FLP-GPCR. © 2013 Atkinson et al.

Availability of stage at diagnosis, cancer treatment delay and compliance with cancer guidelines as cancer registry indicators for cancer care in Europe:Results of EUROCHIP-3 survey

EUROCHIP (European Cancer Health Indicators Project) focuses on understanding inequalities in the cancer burden, care and survival by the indicators "stage at diagnosis," "cancer treatment delay" and "compliance with cancer guidelines" as the most important indicators. Our study aims at providing insight in whether cancer registries collect well-defined variables to determine these indicators in a comparative way. Eighty-six general European population-based cancer registries (PBCR) from 32 countries responded to the questionnaire, which was developed by EUROCHIP in collaboration with ENCR (European Network of Cancer Registries) and EUROCOURSE. Only 15% of all the PBCR in EU had all three indicators available. The indicator "stage at diagnosis" was gathered for at least one cancer site by 81% (using TNM in 39%). Variables for the indicator "cancer treatment delay" were collected by 37%. Availability of type of treatment (30%), surgery date (36%), starting date of radiotherapy (26%) and starting date of chemotherapy (23%) resulted in 15% of the PBCRs to be able to gather the indicator "compliance to guidelines". Lack of data source access and qualified staff were the major reasons for not collecting all the variables. In conclusion, based on self-reporting, a few of the participating PBCRs had data available which could be used for clinical audits, evaluation of cancer care projects, survival and for monitoring national cancer control strategies. Extra efforts should be made to improve this very efficient tool to compare cancer burden and the effects of the national cancer plans over Europe and to learn from each other. © 2012 UICC.

Multi-Objective Reactive Power Support from Wind farms for Network Performance Enhancement

This paper examines the ability of the doubly fed induction generator (DFIG) to deliver multiple reactive power objectives during variable wind conditions. The reactive power requirement is decomposed based on various control objectives (e.g. power factor control, voltage control, loss minimisation, and flicker mitigation) defined around different time frames (i.e. seconds, minutes, and hourly), and the control reference is generated by aggregating the individual reactive power requirement for each control strategy. A novel coordinated controller is implemented for the rotor-side converter and the grid-side converter considering their capability curves and illustrating that it can effectively utilise the aggregated DFIG reactive power capability for system performance enhancement. The performance of the multi-objective strategy is examined for a range of wind and network conditions, and it is shown that for the majority of the scenarios, more than 92% of the main control objective can be achieved while introducing the integrated flicker control scheme with the main reactive power control scheme. Therefore, optimal control coordination across the different control strategies can maximise the availability of ancillary services from DFIG-based wind farms without additional dynamic reactive power devices being installed in power networks.

COD and NH4-N Estimation in the Inflow of Wastewater Treatment Plants using Machine Learning Techniques

The in-line measurement of COD and NH4-N in the WWTP inflow is crucial for the timely monitoring of biological wastewater treatment processes and for the development of advanced control strategies for optimized WWTP operation. As a direct measurement of COD and NH4-N requires expensive and high maintenance in-line probes or analyzers, an approach estimating COD and NH4-N based on standard and spectroscopic in-line inflow measurement systems using Machine Learning Techniques is presented in this paper. The results show that COD estimation using Radom Forest Regression with a normalized MSE of 0.3, which is sufficiently accurate for practical applications, can be achieved using only standard in-line measurements. In the case of NH4-N, a good estimation using Partial Least Squares Regression with a normalized MSE of 0.16 is only possible based on a combination of standard and spectroscopic in-line measurements. Furthermore, the comparison of regression and classification methods shows that both methods perform equally well in most cases.

Low rates of Pseudomonas aeruginosa misidentification in isolates from cystic fibrosis patients

Pseudomonas aeruginosa is an important cause of pulmonary infection in cystic fibrosis (CF). Its correct identification ensures effective patient management and infection control strategies. However, little is known about how often CF sputum isolates are falsely identified as P. aeruginosa. We used P. aeruginosa-specific duplex real-time PCR assays to determine if 2,267 P. aeruginosa sputum isolates from 561 CF patients were correctly identified by 17 Australian clinical microbiology laboratories. Misidentified isolates underwent further phenotypic tests, amplified rRNA gene restriction analysis, and partial 16S rRNA gene sequence analysis. Participating laboratories were surveyed on how they identified P. aeruginosa from CF sputum. Overall, 2,214 (97.7%) isolates from 531 (94.7%) CF patients were correctly identified as P. aeruginosa. Further testing with the API 20NE kit correctly identified only 34 (59%) of the misidentified isolates. Twelve (40%) patients had previously grown the misidentified species in their sputum. Achromobacter xylosoxidans (n = 21), Stenotrophomonas maltophilia (n = 15), and Inquilinus limosus (n = 4) were the species most commonly misidentified as P. aeruginosa. Overall, there were very low rates of P. aeruginosa misidentification among isolates from a broad cross section of Australian CF patients. Additional improvements are possible by undertaking a culture history review, noting colonial morphology, and performing stringent oxidase, DNase, and colistin susceptibility testing for all presumptive P. aeruginosa isolates. Isolates exhibiting atypical phenotypic features should be evaluated further by additional phenotypic or genotypic identification techniques.

A smart load appliance application using a single compressor fridge-freezer to support grid operations

This paper describes a fridge-freezer smart load model, which responds to external signals from the wholesale electricity market to support grid operations while switching the fridge-freezer on and off to maintain optimum operations for the owner. The key parameters of the model are the appliance dimensions, thermal mass, the fridge and freezer thermal time constants and the compressor power consumption. The model demonstrates that control strategies help to minimise load at times when the grid is under stress from high demand, and shift some load to a lower wholesale price or when there is excess renewable power. Three control strategies are proposed, based on peak shaving and valley filling, price signals and wind availability.

Neuropeptides in Helminths: Occurrence and Distribution

Nematode neuropeptide systems comprise an exceptionally complex array of similar to 250 peptidic signaling molecules that operate within a structurally simple nervous system of similar to 300 neurons. A relatively complete picture of the neuropeptide complement is available for Caenorhabditis elegans, with 30 flp, 38 ins and 43 nlp genes having been documented; accumulating evidence indicates similar complexity in parasitic nematodes from clades I, III, IV and V. In contrast, the picture for parasitic platyhelminths is less clear, with the limited peptide sequence data available providing concrete evidence for only FMRFamide-like peptide (FLP) and neuropeptide F (NPF) signaling systems, each of which only comprises one or two peptides. With the completion of the Schmidtea meditteranea and Schistosoma mansoni genome projects and expressed sequence tag datasets for other flatworm parasites becoming available, the time is ripe for a detailed reanalysis of neuropeptide signaling in flatworms. Although the actual neuropeptides provide limited obvious value as targets for chemotherapeutic-based control strategies, they do highlight the signaling systems present in these helminths and provide tools for the discovery of more amenable targets such as neuropeptide receptors or neuropeptide processing enzymes. Also, they offer opportunities to evaluate the potential of their associated signaling pathways as targets through RNA interference (RNAi)-based, target validation strategies. Currently, within both helminth phyla, the flp signaling systems appear to merit further investigation as they are intrinsically linked with motor function, a proven target for successful anti-parasitics; it is clear that some nematode NLPs also play a role in motor function and could have similar appeal. At this time, it is unclear if flatworm NPF and nematode INS peptides operate in pathways that have utility for parasite control. Clearly, RNAi-based validation could be a starting point for scoring potential target pathways within neuropeptide signaling for parasiticide discovery programs. Also, recent successes in the application of in planta-based RNAi control strategies for plant parasitic nematodes reveal a strategy whereby neuropeptide encoding genes could become targets for parasite control. The possibility of developing these approaches for the control of animal and human parasites is intriguing, but will require significant advances in the delivery of RNAi-triggers.

Droop setting design for multi-terminal HVDC grids considering voltage deviation impacts

In multi-terminal high voltage direct current (HVDC) grids, the widely deployed droop control strategies will cause a non-uniform voltage deviation on the power flow, which is determined by the network topology and droop settings. This voltage deviation results in an inconsistent power flow pattern when the dispatch references are changed, which could be detrimental to the operation and seamless integration of HVDC grids. In this paper, a novel droop setting design method is proposed to address this problem for a more precise power dispatch. The effects of voltage deviations on the power sharing accuracy and transmission loss are analysed. This paper shows that there is a trade-off between minimizing the voltage deviation, ensuring a proper power delivery and reducing the total transmission loss in the droop setting design. The efficacy of the proposed method is confirmed by simulation studies.

Hui and Walter's latent-class model extended to estimate diagnostic test properties from surveillance data: a latent model for latent data

Diagnostic test sensitivity and specificity are probabilistic estimates with far reaching implications for disease control, management and genetic studies. In the absence of 'gold standard' tests, traditional Bayesian latent class models may be used to assess diagnostic test accuracies through the comparison of two or more tests performed on the same groups of individuals. The aim of this study was to extend such models to estimate diagnostic test parameters and true cohort-specific prevalence, using disease surveillance data. The traditional Hui-Walter latent class methodology was extended to allow for features seen in such data, including (i) unrecorded data (i.e. data for a second test available only on a subset of the sampled population) and (ii) cohort-specific sensitivities and specificities. The model was applied with and without the modelling of conditional dependence between tests. The utility of the extended model was demonstrated through application to bovine tuberculosis surveillance data from Northern and the Republic of Ireland. Simulation coupled with re-sampling techniques, demonstrated that the extended model has good predictive power to estimate the diagnostic parameters and true herd-level prevalence from surveillance data. Our methodology can aid in the interpretation of disease surveillance data, and the results can potentially refine disease control strategies.

Time series wind power forecasting based on variant Gaussian process and TLBO

Due to the variability and stochastic nature of wind power system, accurate wind power forecasting has an important role in developing reliable and economic power system operation and control strategies. As wind variability is stochastic, Gaussian Process regression has recently been introduced to capture the randomness of wind energy. However, the disadvantages of Gaussian Process regression include its computation complexity and incapability to adapt to time varying time-series systems. A variant Gaussian Process for time series forecasting is introduced in this study to address these issues. This new method is shown to be capable of reducing computational complexity and increasing prediction accuracy. It is further proved that the forecasting result converges as the number of available data approaches innite. Further, a teaching learning based optimization (TLBO) method is used to train the model and to accelerate
the learning rate. The proposed modelling and optimization method is applied to forecast both the wind power generation of Ireland and that from a single wind farm to show the eectiveness of the proposed method.

A prospective view of animal and human Fasciolosis

Fasciolosis, a food-borne trematodiasis, results following infection with the parasites, Fasciola hepatica and Fasciola gigantica. These trematodes greatly affect the global agricultural community, infecting millions of ruminants worldwide and causing annual economic losses in excess of US $3 billion. Fasciolosis, an important zoonosis, is classified by WHO as a neglected tropical disease with an estimated 17 million people infected and a further 180 million people at risk of infection. The significant impact on agriculture and human health together with the increasing demand for animal-derived food products to support global population growth demonstrate that fasciolosis is a major One Health problem. This review details the problematic issues surrounding fasciolosis control, including drug resistance, lack of diagnosis and the threat that hybridization of the Fasciola species poses to future animal and human health. We discuss how these parasites may mediate their long-term survival through regulation and modulation of the host immune system, by altering the host immune homeostasis and/or by influencing the intestinal microbiome particularly in respect to concurrent infections with other pathogens. Large genome, transcriptome and proteomic data sets are now available to support an integrated One Health approach to develop novel diagnostic and control strategies for both animal and human disease.

Prospective strategies underlie the control of interceptive actions.

The purpose of this study was to test whether a constant bearing angle strategy could account for the displacement regulations produced by a moving observer when attempting to intercept a ball following a curvilinear path. The participants were asked to walk through a virtual environment and to change, if (deemed) necessary, their walking speed so as to intercept a moving ball that followed either a rectilinear or a curvilinear path. The results showed that ball path curvature did indeed influence the participants' displacement kinematics in a way that was predicted by adherence to a constant bearing angle strategy mode of control. Velocity modifications were found to be proportional to the magnitude of target curvature with opposing curvatures giving rise to mirror displacement velocity changes. The role of prospective strategies in the control of interceptive action is discussed

The consequences of resistance training for movement control in older adults

Older adults who undertake resistance training are typically seeking to maintain or increase their muscular strength with the goal of preserving or improving their functional capabilities. The extent to which resistance training adaptations lead to improved performance on tasks of everyday living is not particularly well understood. Indeed, studies examining changes in functional task performance experienced by older adults following periods of resistance training have produced equivocal findings. A clear understanding of the principles governing the transfer of resistance training adaptations is therefore critical in seeking to optimize the prescription of training regimes that have as their aim the maintenance and improvement of functional movement capacities in older adults. The degenerative processes that occur in the aging motor system are likely to influence heavily any adaptations to resistance training and the subsequent transfer to functional task performance. The resulting characteristics of motor behavior, such as the substantial decline in the rate of force development and the decreased steadiness of force production, may entail that specialized resistance training strategies are necessary to maximize the benefits for older adults. In this review, we summarize the alterations in the neuromuscular system that are responsible for the declines in strength, power, and force control, and the subsequent deterioration in the everyday movement capabilities of older adults. We examine the literature concerning the neural adaptations that older adults experience in response to resistance training, and consider the readiness with which these adaptations will improve the functional movement capabilities of older adults.