Label free electrochemiluminescence protocol for sensitive DNA detection with a tris(2,2'-bipyridyl)ruthenium(II) modified electrode based on nucleic acid oxidation

Label free electrochemiluminescence (ECL) DNA detection based on catalytic guanine and adenine bases oxidation using tris(2,2'-bipyridyl)ruthenium(II) [Ru(bpy)(3)(2+)] modified glassy carbon (GC) electrode was demonstrated in this work. The modified GC electrode was prepared by casting carbon nanotubes (CNT)/Nafion/Ru(bpy)(3)(2+) composite film on the electrode surface. ECL signals of doublestranded DNA and their thermally denatured counterparts can be distinctly discriminated using cyclic voltammetry (CV) with a low concentration (3.04 x 10(-8) mol/L for Salmon Testes-DNA). Most importantly, sensitive single-base mismatch detection of p53 gene sequence segment was realized with 3.93 x 10(-10) mol/L employing CV stimulation (ECL signal of C/A mismatched DNA oligonucleotides was 1.5-fold higher than that of fully base-paired DNA oligonucleotides). Label free, high sensitivity and simplicity for single-base mismatch discrimination were the main advantages of the present ECL technique for DNA detection over the traditional DNA sensors.

Mean Field Theory for Sigmoid Belief Networks

We develop a mean field theory for sigmoid belief networks based on ideas from statistical mechanics. Our mean field theory provides a tractable approximation to the true probability distribution in these networks; it also yields a lower bound on the likelihood of evidence. We demonstrate the utility of this framework on a benchmark problem in statistical pattern recognition -- the classification of handwritten digits.

Vector Associative Maps: Unsupervised Real-time Error-based Learning and Control of Movement Trajectories

This article describes neural network models for adaptive control of arm movement trajectories during visually guided reaching and, more generally, a framework for unsupervised real-time error-based learning. The models clarify how a child, or untrained robot, can learn to reach for objects that it sees. Piaget has provided basic insights with his concept of a circular reaction: As an infant makes internally generated movements of its hand, the eyes automatically follow this motion. A transformation is learned between the visual representation of hand position and the motor representation of hand position. Learning of this transformation eventually enables the child to accurately reach for visually detected targets. Grossberg and Kuperstein have shown how the eye movement system can use visual error signals to correct movement parameters via cerebellar learning. Here it is shown how endogenously generated arm movements lead to adaptive tuning of arm control parameters. These movements also activate the target position representations that are used to learn the visuo-motor transformation that controls visually guided reaching. The AVITE model presented here is an adaptive neural circuit based on the Vector Integration to Endpoint (VITE) model for arm and speech trajectory generation of Bullock and Grossberg. In the VITE model, a Target Position Command (TPC) represents the location of the desired target. The Present Position Command (PPC) encodes the present hand-arm configuration. The Difference Vector (DV) population continuously.computes the difference between the PPC and the TPC. A speed-controlling GO signal multiplies DV output. The PPC integrates the (DV)·(GO) product and generates an outflow command to the arm. Integration at the PPC continues at a rate dependent on GO signal size until the DV reaches zero, at which time the PPC equals the TPC. The AVITE model explains how self-consistent TPC and PPC coordinates are autonomously generated and learned. Learning of AVITE parameters is regulated by activation of a self-regulating Endogenous Random Generator (ERG) of training vectors. Each vector is integrated at the PPC, giving rise to a movement command. The generation of each vector induces a complementary postural phase during which ERG output stops and learning occurs. Then a new vector is generated and the cycle is repeated. This cyclic, biphasic behavior is controlled by a specialized gated dipole circuit. ERG output autonomously stops in such a way that, across trials, a broad sample of workspace target positions is generated. When the ERG shuts off, a modulator gate opens, copying the PPC into the TPC. Learning of a transformation from TPC to PPC occurs using the DV as an error signal that is zeroed due to learning. This learning scheme is called a Vector Associative Map, or VAM. The VAM model is a general-purpose device for autonomous real-time error-based learning and performance of associative maps. The DV stage serves the dual function of reading out new TPCs during performance and reading in new adaptive weights during learning, without a disruption of real-time operation. YAMs thus provide an on-line unsupervised alternative to the off-line properties of supervised error-correction learning algorithms. YAMs and VAM cascades for learning motor-to-motor and spatial-to-motor maps are described. YAM models and Adaptive Resonance Theory (ART) models exhibit complementary matching, learning, and performance properties that together provide a foundation for designing a total sensory-cognitive and cognitive-motor autonomous system.

Ecosystem services, targets, and indicators for the conservation and sustainable use of biodiversity

After the collective failure to achieve the Convention on Biological Diversity's (CBD's) 2010 target to substantially reduce biodiversity losses, the CBD adopted a plan composed of five strategic goals and 20 “SMART” (Specific, Measurable, Ambitious, Realistic, and Time-bound) targets, to be achieved by 2020. Here, an interdisciplinary group of scientists from DIVERSITAS – an international program that focuses on biodiversity science – evaluates these targets and considers the implications of an ecosystem-services-based approach for their implementation. We describe the functional differences between the targets corresponding to distinct strategic goals and identify the interdependency between targets. We then discuss the implications for supporting research and target indicators, and make several specific suggestions for target implementation.

Validation of the detection of Pseudo-nitzschia spp. using specific RNA probes tested in a microarray format: Calibration of signal based on variability of RNA content with environmental conditions.

Harmful algal blooms (HAB) occur worldwide and cause health problems and economic damage to fisheries and tourism. Monitoring for toxic algae is therefore essential but is based primarily on light microscopy, which is time consuming and can be limited by insufficient morphological characters such that more time is needed to examine critical features with electron microscopy. Monitoring with molecular tools is done in only a few places world-wide. EU FP7 MIDTAL (Microarray Detection of Toxic Algae) used SSU and LSU rRNA genes as targets on microarrays to identify toxic species. In order to comply with current monitoring requirements to report cell numbers as the relevant threshold measurement to trigger closure of fisheries, it was necessary to calibrate our microarray to convert the hybridisation signal obtained to cell numbers. Calibration curves for two species of Pseudo-nitzschia for use with the MIDTAL microarray are presented to obtain cell numbers following hybridisation. It complements work presented by Barra et al. (2012b. Environ. Sci. Pollut. Res. doi: 10.1007/s11356-012-1330-1v) for two other Pseudo-nitzschia spp., Dittami and Edvardsen (2012a. J. Phycol. 48, 1050) for Pseudochatonella, Blanco et al. (2013. Harmful Algae 24, 80) for Heterosigma, McCoy et al. (2013. FEMS. doi: 10.1111/1574-6941.12277) for Prymnesium spp., Karlodinium veneficum, and cf. Chatonella spp. and Taylor et al. (2014. Harmful Algae, in press) for Alexandrium.

SOCS3 Targets Siglec 7 for Proteasomal Degradation and Blocks Siglec 7-mediated Responses

CD33-related Siglecs (sialic acid-binding immunoglobulin-like lectins) 5–11 are inhibitory receptors that contain a membrane proximal ITIM (immunoreceptor tyrosine-based inhibitory motif) (I/V/L/)XYXX(L/V), which can recruit SHP-1/2. However, little is known about the regulation of these receptors. SOCS3 (suppressor of cytokine signaling 3) is up-regulated during inflammation and competes with SHP-1/2 for binding to ITIM-like motifs on various cytokine receptors resulting in inhibition of signaling. We show that SOCS3 binds the phosphorylated ITIM of Siglec 7 and targets it for proteasomal-mediated degradation, suggesting that Siglec 7 is a novel SOCS target. Following ligation, the ECS E3 ligase is recruited by SOCS3 to target Siglec 7 for proteasomal degradation, and SOCS3 expression is decreased concomitantly. In addition, we found that SOCS3 expression blocks Siglec 7-mediated inhibition of cytokine-induced proliferation. This is the first time that a SOCS target has been reported to degrade simultaneously with the SOCS protein and that inhibitory receptors have been shown to be degraded in this way. This may be a mechanism by which the inflammatory response is potentiated during infection.

Knowledge-based risk assessment under uncertainty in engineering projects

In this paper we describe how an evidential-reasoner can be used as a component of risk assessment of engineering projects using a direct way of reasoning. Guan & Bell (1991) introduced this method by using the mass functions to express rule strengths. Mass functions are also used to express data strengths. The data and rule strengths are combined to get a mass distribution for each rule; i.e., the first half of our reasoning process. Then we combine the prior mass and the evidence from the different rules; i.e., the second half of the reasoning process. Finally, belief intervals are calculated to help in identifying the risks. We apply our evidential-reasoner on an engineering project and the results demonstrate the feasibility and applicability of this system in this environment.

Generalisation between opposing visuomotor rotations when each is associated with visual targets and movements of different amplitude

Previous studies have attempted to identify sources of contextual information which can facilitate dual adaptation to two variants of a novel environment, which are normally prone to interference. The type of contextual information previously used can be grouped into two broad categories: that which is arbitrary to the motor system, such as a colour cue, and that which is based on an internal property of the motor system, such as a change in movement effector. The experiments reported here examined whether associating visuomotor rotations to visual targets and movements of different amplitude would serve as an appropriate source of contextual information to enable dual adaptation. The results indicated that visual target and movement amplitude is not a suitable source of contextual information to enable dual adaptation in our task. Interference was observed in groups who were exposed to opposing visuomotor rotations, or a visuomotor rotation and no rotation, both when the onset of the visuomotor rotations was sudden, or occurred gradually over the course of training. Furthermore, the pattern of interference indicated that the inability to dual adapt was a result of the generalisation of learning between the two visuomotor mappings associated with each of the visual target and movement amplitudes. (C) 2008 Elsevier B.V. All rights reserved.

Microtubules as antiparasitic drug targets

Background: Parasitic diseases including malaria, leishmaniasis and schistosomiasis take a terrible toll of human life, health and productivity, especially in tropical and subtropical regions, and are also highly significant in animal health worldwide. Antiparasitic drugs are the mainstays of control of most of these diseases, but in many cases current therapies are inadequate and in some the situation is deteriorating because of drug resistance. Microtubules, as essential components of almost all eukaryotic cells, are proven drug targets in many helminth diseases and show promise as targets for the development of new antiprotozoal drugs. Objective: This article reviews the chemistry of the microtubule inhibitors in current use and under investigation as antiparasitic agents, their activities against the major parasites and their mechanisms of action. New directions in both inhibitor chemistry and biological evaluation are discussed. Conclusions: The most promising immediate avenues for discovery and design appear to lie in development of novel benzimidazoles for helminth parasites and compounds based on antimitotic herbicides for protozoal parasites. New understanding from functional genomics, structural biology and microtubular imaging will help accelerate the development of completely novel antiparasitic drugs targeting microtubules.

Interactions between the budding yeast IQGAP homologue Iqg1p and its targets revealed by a split-EGFP bimolecular fluorescence complementation assay.

A split-EGFP based bimolecular fluorescence complementation (BiFC) assay has been used to detect interactions between the Saccharomyces cerevisiae cytoskeletal scaffolding protein Iqg1p and three targets: myosin essential light chain (Mlc1p), calmodulin (Cmd1p) and the small GTPase Cdc42p. The format of the BiFC assay used ensures that the proteins are expressed at wild type levels thereby avoiding artefacts due to overexpression. This is the first direct in vivo detection of these interactions; in each case, the complex is localised to discrete regions of the yeast cytoplasm. The labelling with EGFP fragments results in changes in growth kinetics, cell size and budding frequency. This is partly due to the reassembled EGFP locking the complexes into essentially permanent interactions. The consequences of this for Iqg1p interactions and BiFC assays in general are discussed. (c) 2008 International Federation for Cell Biology. Published by Elsevier Ltd. All rights reserved.

The Relevance Framework for Category-Based Induction: Evidence From Garden-Path Arguments

Relevance theory (Sperber & Wilson. 1995) suggests that people expend cognitive effort when processing information in proportion to the cognitive effects to be gained from doing so. This theory has been used to explain how people apply their knowledge appropriately when evaluating category-based inductive arguments (Medin, Coley, Storms, & Hayes, 2003). In such arguments, people are told that a property is true of premise categories and are asked to evaluate the likelihood that it is also true of conclusion categories. According to the relevance framework, reasoners generate hypotheses about the relevant relation between the categories in the argument. We reasoned that premises inconsistent with early hypotheses about the relevant relation would have greater effects than consistent premises. We designed three premise garden-path arguments where the same 3rd premise was either consistent or inconsistent with likely hypotheses about the relevant relation. In Experiments 1 and 2, we showed that effort expended processing consistent premises (measured via reading times) was significantly less than effort expended on inconsistent premises. In Experiment 2 and 3, we demonstrated a direct relation between cognitive effect and cognitive effort. For garden-path arguments, belief change given inconsistent 3rd premises was significantly correlated with Premise 3 (Experiment 3) and conclusion (Experiments 2 and 3) reading times. For consistent arguments, the correlation between belief change and reading times did not approach significance. These results support the relevance framework for induction but are difficult to accommodate under other approaches.

Managing Software Requirements Changes Based On Negotiation-Style Revision

For any proposed software project, when the software requirements specification has been established, requirements changes may result in not only a modification of the requirements specification but also a series of modifications of all existing artifacts during the development. Then it is necessary to provide effective and flexible requirements changes management. In this paper, we present an approach to managing requirements changes based on Booth’s negotiation-style framework for belief revision. Informally, we consider the current requirements specification as a belief set about the system-to-be. The request of requirements change is viewed as new information about the same system-to-be. Then the process of executing the requirements change is a process of revising beliefs about the system-to-be. We design a family of belief negotiation models appropriate for different processes of requirements revision, including the setting of the request of requirements change being fully accepted, the setting of the current requirements specification being fully preserved, and that of the current specification and the request of requirements change reaching a compromise. In particular, the prioritization of requirements plays an important role in reaching an agreement in each belief negotiation model designed in this paper.

Activated oncogenic pathways and therapeutic targets in extranodal nasal-type NK/T cell lymphoma revealed by gene expression profiling

We performed comprehensive genome-wide gene expression profiling (GEP) of extranodal nasal-type natural killer/T-cell lymphoma (NKTL) using formalin-fixed, paraffin-embedded tissue (n = 9) and NK cell lines (n = 5) in comparison with normal NK cells, with the objective of understanding the oncogenic pathways involved in the pathogenesis of NKTL and to identify potential therapeutic targets. Pathway and network analysis of genes differentially expressed between NKTL and normal NK cells revealed significant enrichment for cell cycle-related genes and pathways, such as PLK1, CDK1, and Aurora-A. Furthermore, our results demonstrated a pro-proliferative and anti-apoptotic phenotype in NKTL characterized by activation of Myc and nuclear factor kappa B (NF-kappa B), and deregulation of p53. In corroboration with GEP findings, a significant percentage of NKTLs (n = 33) overexpressed c-Myc (45.4%), p53 (87.9%), and NF-kappa B p50 (67.7%) on immunohistochemistry using a tissue microarray containing 33 NKTL samples. Notably, overexpression of survivin was observed in 97% of cases. Based on our findings, we propose a model of NKTL pathogenesis where deregulation of p53 together with activation of Myc and NF-kappa B, possibly driven by EBV LMP-1, results in the cumulative up-regulation of survivin. Down-regulation of survivin with Terameprocol (EM-1421, a survivin inhibitor) results in reduced cell viability and increased apoptosis in tumour cells, suggesting that targeting survivin may be a potential novel therapeutic strategy in NKTL. Copyright (C) 2011 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

TRARESA: a tissue microarray-based hospital system for biomarker validation and discovery

Formalin fixed and paraffin embedded tissue (FFPE) collections in pathology departments are the largest resource for retrospective biomedical research studies. Based on the literature analysis of FFPE related research, as well as our own technical validation, we present the Translational Research Arrays (TRARESA), a tissue microarray centred, hospital based, translational research conceptual framework for both validation and/or discovery of novel biomarkers. TRARESA incorporates the analysis of protein, DNA and RNA in the same samples, correlating with clinical and pathological parameters from each case, and allowing (a) the confirmation of new biomarkers, disease hypotheses and drug targets, and (b) the postulation of novel hypotheses on disease mechanisms and drug targets based on known biomarkers. While presenting TRARESA, we illustrate the use of such a comprehensive approach. The conceptualisation of the role of FFPE-based studies in translational research allows the utilisation of this commodity, and adds to the hypothesis-generating armamentarium of existing high-throughput technologies.

Fully hardware based WFQ architecture for high-speed QoS packet scheduling

A full hardware implementation of a Weighted Fair Queuing (WFQ) packet scheduler is proposed. The circuit architecture presented has been implemented using Altera Stratix II FPGA technology, utilizing RLDII and QDRII memory components. The circuit can provide fine granularity Quality of Service (QoS) support at a line throughput rate of 12.8Gb/s in its current implementation. The authors suggest that, due to the flexible and scalable modular circuit design approach used, the current circuit architecture can be targeted for a full ASIC implementation to deliver 50 Gb/s throughput. The circuit itself comprises three main components; a WFQ algorithm computation circuit, a tag/time-stamp sort and retrieval circuit, and a high throughput shared buffer. The circuit targets the support of emerging wireline and wireless network nodes that focus on Service Level Agreements (SLA's) and Quality of Experience.