Self-organising neural networks for adaptive control

Self-organizing neural networks have been implemented in a wide range of application areas such as speech processing, image processing, optimization and robotics. Recent variations to the basic model proposed by the authors enable it to order state space using a subset of the input vector and to apply a local adaptation procedure that does not rely on a predefined test duration limit. Both these variations have been incorporated into a new feature map architecture that forms an integral part of an Hybrid Learning System (HLS) based on a genetic-based classifier system. Problems are represented within HLS as objects characterized by environmental features. Objects controlled by the system have preset targets set against a subset of their features. The system's objective is to achieve these targets by evolving a behavioural repertoire that efficiently explores and exploits the problem environment. Feature maps encode two types of knowledge within HLS — long-term memory traces of useful regularities within the environment and the classifier performance data calibrated against an object's feature states and targets. Self-organization of these networks constitutes non-genetic-based (experience-driven) learning within HLS. This paper presents a description of the HLS architecture and an analysis of the modified feature map implementing associative memory. Initial results are presented that demonstrate the behaviour of the system on a simple control task.

Adaptive alarm processor for fault diagnosis on power transmission networks

The authors describe a learning classifier system (LCS) which employs genetic algorithms (GA) for adaptive online diagnosis of power transmission network faults. The system monitors switchgear indications produced by a transmission network, reporting fault diagnoses on any patterns indicative of faulted components. The system evaluates the accuracy of diagnoses via a fault simulator developed by National Grid Co. and adapts to reflect the current network topology by use of genetic algorithms.

Analysis of protein networks in resting and collagen receptor (GPVI)-stimulated platelet sub-proteomes.

Proteomics approaches have made important contributions to the characterisation of platelet regulatory mechanisms. A common problem encountered with this method, however, is the masking of low-abundance (e.g. signalling) proteins in complex mixtures by highly abundant proteins. In this study, subcellular fractionation of washed human platelets either inactivated or stimulated with the glycoprotein (GP) VI collagen receptor agonist, collagen-related peptide, reduced the complexity of the platelet proteome. The majority of proteins identified by tandem mass spectrometry are involved in signalling. The effect of GPVI stimulation on levels of specific proteins in subcellular compartments was compared and analysed using in silico quantification, and protein associations were predicted using STRING (the search tool for recurring instances of neighbouring genes/proteins). Interestingly, we observed that some proteins that were previously unidentified in platelets including teneurin-1 and Van Gogh-like protein 1, translocated to the membrane upon GPVI stimulation. Newly identified proteins may be involved in GPVI signalling nodes of importance for haemostasis and thrombosis.

The integration of proteomics and systems approaches to map regulatory mechanisms underpinning platelet function.

Platelets in the circulation are triggered by vascular damage to activate, aggregate and form a thrombus that prevents excessive blood loss. Platelet activation is stringently regulated by intracellular signalling cascades, which when activated inappropriately lead to myocardial infarction and stroke. Strategies to address platelet dysfunction have included proteomics approaches which have lead to the discovery of a number of novel regulatory proteins of potential therapeutic value. Global analysis of platelet proteomes may enhance the outcome of these studies by arranging this information in a contextual manner that recapitulates established signalling complexes and predicts novel regulatory processes. Platelet signalling networks have already begun to be exploited with interrogation of protein datasets using in silico methodologies that locate functionally feasible protein clusters for subsequent biochemical validation. Characterization of these biological systems through analysis of spatial and temporal organization of component proteins is developing alongside advances in the proteomics field. This focused review highlights advances in platelet proteomics data mining approaches that complement the emerging systems biology field. We have also highlighted nucleated cell types as key examples that can inform platelet research. Therapeutic translation of these modern approaches to understanding platelet regulatory mechanisms will enable the development of novel anti-thrombotic strategies.

Genetic responses to phosphorus deficiency

Background: Phosphorus (P) is an essential macronutrient for plants. Plants take up P as phosphate (Pi) from the soil solution. Since little Pi is available in most soils, P fertilizers are applied to crops. However, the use of P fertilizers is unsustainable and may cause pollution. Consequently, there is a need to develop more P-use-efficient (PUE) crops and precise methods to monitor crop P-status. Scope: Manipulating the expression of genes to improve the PUE of crops could reduce their P fertilizer requirement. This has stimulated research towards the identification of genes and signalling cascades involved in plant responses to P deficiency. Genes that respond to P deficiency can be grouped into 'early' genes that respond rapidly and often non-specifically to P deficiency, or 'late' genes that impact on the morphology, physiology or metabolism of plants upon Prolonged P deficiency. Summary: The use of micro-array technology has allowed researchers to catalogue the genetic responses of plants to P deficiency. Genes whose expression is altered by P deficiency include various transcription factors, which are thought to coordinate plant responses to P deficiency, and other genes involved in P acquisition and tissue P economy. Several common cis-regulatory elements have been identified in the promoters of these genes, suggesting that their expression might be coordinated. It is suggested that knowledge of the genes whose expression changes in response to P deficiency might allow the development of crops with improved PUE, and could be used in diagnostic techniques to monitor P deficiency in crops either directly using 'smart' indicator plants or indirectly through transcript profiling. The development of crops with improved PUE and the adoption of diagnostic technology could reduce production costs, minimize the use of a non-renewable resource, reduce pollution and enhance biodiversity.

Alterations in predicted regulatory and coding regions of the sterol 14α-demethylase gene (CYP51) confer decreased azole sensitivity in the oilseed rape pathogen Pyrenopeziza brassicae

The incidence and severity of light leaf spot epidemics caused by the ascomycete fungus Pyrenopeziza brassicae on UK oilseed rape crops is increasing. The disease is currently controlled by a combination of host resistance, cultural practices and fungicide applications. We report decreases in sensitivities of modern UK P. brassicae isolates to the azole (imidazole and triazole) class of fungicides. By cloning and sequencing the P. brassicae CYP51 (PbCYP51) gene, encoding the azole target sterol 14α-demethylase, we identified two non-synonymous mutations encoding substitutions G460S and S508T associated with reduced azole sensitivity. We confirmed the impact of the encoded PbCYP51 changes on azole sensitivity and protein activity by heterologous expression in a Saccharomyces cerevisiae mutant YUG37::erg11 carrying a controllable promoter of native CYP51 expression. In addition, we identified insertions in the predicted regulatory regions of PbCYP51 in isolates with reduced azole sensitivity. The presence of these insertions was associated with enhanced transcription of PbCYP51 in response to sub-inhibitory concentrations of the azole fungicide tebuconazole. Genetic analysis of in vitro crosses of sensitive and resistant isolates confirmed the impact of PbCYP51 alterations in coding and regulatory sequences on a reduced sensitivity phenotype, as well as identifying a second major gene at another locus contributing to resistance in some isolates. The least sensitive field isolates carry combinations of upstream insertions and non-synonymous mutations, suggesting PbCYP51 evolution is on-going and the progressive decline in azole sensitivity of UK P. brassicae populations will continue. The implications for the future control of light leaf spot are discussed.

Genetic variant rs17225178 in the ARNT2 gene is associated with Asperger Syndrome

Background Autism Spectrum Conditions (ASC) are neurodevelopmental conditions characterized by difficulties in communication and social interaction, alongside unusually repetitive behaviours and narrow interests. Asperger Syndrome (AS) is one subgroup of ASC and differs from classic autism in that in AS there is no language or general cognitive delay. Genetic, epigenetic and environmental factors are implicated in ASC and genes involved in neural connectivity and neurodevelopment are good candidates for studying the susceptibility to ASC. The aryl-hydrocarbon receptor nuclear translocator 2 (ARNT2) gene encodes a transcription factor involved in neurodevelopmental processes, neuronal connectivity and cellular responses to hypoxia. A mutation in this gene has been identified in individuals with ASC and single nucleotide polymorphisms (SNPs) have been nominally associated with AS and autistic traits in previous studies. Methods In this study, we tested 34 SNPs in ARNT2 for association with AS in 118 cases and 412 controls of Caucasian origin. P values were adjusted for multiple comparisons, and linkage disequilibrium (LD) among the SNPs analysed was calculated in our sample. Finally, SNP annotation allowed functional and structural analyses of the genetic variants in ARNT2. We tested the replicability of our result using the genome-wide association studies (GWAS) database of the Psychiatric Genomics Consortium (PGC). Results We report statistically significant association of rs17225178 with AS. This SNP modifies transcription factor binding sites and regions that regulate the chromatin state in neural cell lines. It is also included in a LD block in our sample, alongside other genetic variants that alter chromatin regulatory regions in neural cells. Conclusions These findings demonstrate that rs17225178 in the ARNT2 gene is associated with AS and support previous studies that pointed out an involvement of this gene in the predisposition to ASC.

Global scale transcriptome analysis of Arabidopsis embryogenesis in vitro

Background Somatic embryogenesis (SE) in plants is a process by which embryos are generated directly from somatic cells, rather than from the fused products of male and female gametes. Despite the detailed expression analysis of several somatic-to-embryonic marker genes, a comprehensive understanding of SE at a molecular level is still lacking. The present study was designed to generate high resolution transcriptome datasets for early SE providing the way for future research to understand the underlying molecular mechanisms that regulate this process. We sequenced Arabidopsis thaliana somatic embryos collected from three distinct developmental time-points (5, 10 and 15 d after in vitro culture) using the Illumina HiSeq 2000 platform. Results This study yielded a total of 426,001,826 sequence reads mapped to 26,520 genes in the A. thaliana reference genome. Analysis of embryonic cultures after 5 and 10 d showed differential expression of 1,195 genes; these included 778 genes that were more highly expressed after 5 d as compared to 10 d. Moreover, 1,718 genes were differentially expressed in embryonic cultures between 10 and 15 d. Our data also showed at least eight different expression patterns during early SE; the majority of genes are transcriptionally more active in embryos after 5 d. Comparison of transcriptomes derived from somatic embryos and leaf tissues revealed that at least 4,951 genes are transcriptionally more active in embryos than in the leaf; increased expression of genes involved in DNA cytosine methylation and histone deacetylation were noted in embryogenic tissues. In silico expression analysis based on microarray data found that approximately 5% of these genes are transcriptionally more active in somatic embryos than in actively dividing callus and non-dividing leaf tissues. Moreover, this identified 49 genes expressed at a higher level in somatic embryos than in other tissues. This included several genes with unknown function, as well as others related to oxidative and osmotic stress, and auxin signalling. Conclusions The transcriptome information provided here will form the foundation for future research on genetic and epigenetic control of plant embryogenesis at a molecular level. In follow-up studies, these data could be used to construct a regulatory network for SE; the genes more highly expressed in somatic embryos than in vegetative tissues can be considered as potential candidates to validate these networks.

Platelet signaling: a complex interplay between inhibitory and activatory networks

The role of platelets in hemostasis and thrombosis is dependent on a complex balance of activatory and inhibitory signaling pathways. Inhibitory signals released from the healthy vasculature suppress platelet activation in the absence of platelet receptor agonists. Activatory signals present at a site of injury initiate platelet activation and thrombus formation; subsequently, endogenous negative signaling regulators dampen activatory signals to control thrombus growth. Understanding the complex interplay between activatory and inhibitory signaling networks is an emerging challenge in the study of platelet biology and necessitates a systematic approach to utilize experimental data effectively. In this review, we will explore the key points of platelet regulation and signaling that maintain platelets in a resting state, mediate activation to elicit thrombus formation or provide negative feedback. Platelet signaling will be described in terms of key signaling molecules that are common to the pathways activated by platelet agonists and can be described as regulatory nodes for both positive and negative regulators. This article is protected by copyright. All rights reserved.

Balanced polymorphism in bottlenecked populations: The case of the CCR5 5 ` cis-regulatory region in Amazonian Amerindians

The 5` cis-regulatory region of the CCR5 gene exhibits a strong signature of balancing selection in several human populations. Here we analyze the polymorphism of this region in Amerindians from Amazonia, who have a complex demographic history, including recent bottlenecks that are known to reduce genetic variability. Amerindians show high nucleotide diversity (pi = 0.27%) and significantly positive Tajima`s D, and carry haplotypes associated with weak and strong gene expression. To evaluate whether these signatures of balancing selection could be explained by demography, we perform neutrality tests based on empiric and simulated data. The observed Tajima`s D was higher than that of other world populations: higher than that found for 18 noncoding regions of South Amerindians, and higher than 99.6% of simulated genealogies, which assume nonequilibrium conditions. Moreover, comparing Amerindians and Asians, the Fst for CCR5 cis-regulatory region was unusually low, in relation to neutral markers. These findings indicate that, despite their complex demographic history, South Amerindians carry a detectable signature of selection on the CCR5 cis-regulatory region. (C) 2010 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.

Genetic and Functional Evidence Implicating DLL1 as the Gene That Influences Susceptibility to Visceral Leishmaniasis at Chromosome 6q27

Background. Visceral leishmaniasis (VL) is caused by Leishmania donovani and Leishmania infantum chagasi. Genome-wide linkage studies from Sudan and Brazil identified a putative susceptibility locus on chromosome 6q27. Methods. Twenty-two single-nucleotide polymorphisms (SNPs) at genes PHF10, C6orf70, DLL1, FAM120B, PSMB1, and TBP were genotyped in 193 VL cases from 85 Sudanese families, and 8 SNPs at genes PHF10, C6orf70, DLL1, PSMB1, and TBP were genotyped in 194 VL cases from 80 Brazilian families. Family-based association, haplotype, and linkage disequilibrium analyses were performed. Multispecies comparative sequence analysis was used to identify conserved noncoding sequences carrying putative regulatory elements. Quantitative reverse-transcription polymerase chain reaction measured expression of candidate genes in splenic aspirates from Indian patients with VL compared with that in the control spleen sample. Results. Positive associations were observed at PHF10, C6orf70, DLL1, PSMB1, and TBP in Sudan, but only at DLL1 in Brazil (combined P = 3 x 10(-4) at DLL1 across Sudan and Brazil). No functional coding region variants were observed in resequencing of 22 Sudanese VL cases. DLL1 expression was significantly (P = 2 x 10(-7)) reduced (mean fold change, 3.5 [SEM, 0.7]) in splenic aspirates from patients with VL, whereas other 6q27 genes showed higher levels (1.27 x 10(-6) < P < .01) than did the control spleen sample. A cluster of conserved noncoding sequences with putative regulatory variants was identified in the distal promoter of DLL1. Conclusions. DLL1, which encodes Delta-like 1, the ligand for Notch3, is strongly implicated as the chromosome 6q27 VL susceptibility gene.

Artificial Neural Networks and the Study of the Psychoactivity of Cannabinoid Compounds

Cannabinoid compounds have widely been employed because of its medicinal and psychotropic properties. These compounds are isolated from Cannabis sativa (or marijuana) and are used in several medical treatments, such as glaucoma, nausea associated to chemotherapy, pain and many other situations. More recently, its use as appetite stimulant has been indicated in patients with cachexia or AIDS. In this work, the influence of several molecular descriptors on the psychoactivity of 50 cannabinoid compounds is analyzed aiming one obtain a model able to predict the psychoactivity of new cannabinoids. For this purpose, initially, the selection of descriptors was carried out using the Fisher`s weight, the correlation matrix among the calculated variables and principal component analysis. From these analyses, the following descriptors have been considered more relevant: E(LUMO) (energy of the lowest unoccupied molecular orbital), Log P (logarithm of the partition coefficient), VC4 (volume of the substituent at the C4 position) and LP1 (Lovasz-Pelikan index, a molecular branching index). To follow, two neural network models were used to construct a more adequate model for classifying new cannabinoid compounds. The first model employed was multi-layer perceptrons, with algorithm back-propagation, and the second model used was the Kohonen network. The results obtained from both networks were compared and showed that both techniques presented a high percentage of correctness to discriminate psychoactive and psychoinactive compounds. However, the Kohonen network was superior to multi-layer perceptrons.

Multi-Objective Pipe Smoothing Genetic Algorithm For Water Distribution Network Design

This paper describes the formulation of a Multi-objective Pipe Smoothing Genetic Algorithm (MOPSGA) and its application to the least cost water distribution network design problem. Evolutionary Algorithms have been widely utilised for the optimisation of both theoretical and real-world non-linear optimisation problems, including water system design and maintenance problems. In this work we present a pipe smoothing based approach to the creation and mutation of chromosomes which utilises engineering expertise with the view to increasing the performance of the algorithm whilst promoting engineering feasibility within the population of solutions. MOPSGA is based upon the standard Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and incorporates a modified population initialiser and mutation operator which directly targets elements of a network with the aim to increase network smoothness (in terms of progression from one diameter to the next) using network element awareness and an elementary heuristic. The pipe smoothing heuristic used in this algorithm is based upon a fundamental principle employed by water system engineers when designing water distribution pipe networks where the diameter of any pipe is never greater than the sum of the diameters of the pipes directly upstream resulting in the transition from large to small diameters from source to the extremities of the network. MOPSGA is assessed on a number of water distribution network benchmarks from the literature including some real-world based, large scale systems. The performance of MOPSGA is directly compared to that of NSGA-II with regard to solution quality, engineering feasibility (network smoothness) and computational efficiency. MOPSGA is shown to promote both engineering and hydraulic feasibility whilst attaining good infrastructure costs compared to NSGA-II.

Effects of polymorphic microsatellites in the regulatory region of IGF1 and GHR on growth and carcass traits in beef cattle

Growth hormone (GH), insulin-like growth factors 1 and 2 (IGF1 and IGF2) and their associated binding proteins and transmembrane receptors (GHR, IGF1R and IGF2R) play an important role in the physiology of mammalian growth. The objectives of the present study were to estimate the allele and genotype frequencies of microsatellite markers located in the 5'-regulatory region of the IGF1 and GHR genes in beef cattle belonging to different genetic groups and to determine effects of these markers on growth and carcass traits in these animals under an intensive production system. For this purpose, genotyping was performed on 384 bulls including 79 Nellore, 30 Canchim (5/8 Charolais + 3/8 Zebu) and 275 crossbred animals originating from crosses of Simmental (1/2 Simmental, n = 30) and Angus (1/2 Angus, n = 245) sires with Nellore females. The effects of substituting L allele for S allele of GHR microsatellite across Nellore, Canchim and 1/2 Angus were significant for weight gain and body weight (P < 0.05). The IGF1 microsatellite allele substitutions of 229 for 225 within Nellore group and of 225 for 229 within 1/2 Angus were not significant for any of the traits.