Remote, subsurface detection of the algal toxin domoic acid onboard the Environmental Sample Processor: Assay development and field trials

The ability to detect harmful algal bloom (HAB) species and their toxins in real- or near real-time is a critical need for researchers studying HAB/toxin dynamics, as well as for coastal resource managers charged with monitoring bloom populations in order to mitigate their wide ranging impacts. The Environmental Sample Processor (ESP), a robotic electromechanical/fluidic system, was developed for the autonomous, subsurface application of molecular diagnostic tests and has successfully detected several HAB species using DNA probe arrays during field deployments. Since toxin production and thus the potential for public health and ecosystem effects varies considerably in natural phytoplankton populations, the concurrent detection of HAB species and their toxins onboard the ESP is essential. We describe herein the development of methods for extracting the algal toxin domoic acid (DA) from Pseudonitzschia cells (extraction efficiency >90%) and testing of samples using a competitive ELISA onboard the ESP. The assay detection limit is in the low ng/mL range (in extract), which corresponds to low ng/L levels of DA in seawater for a 0.5 L sample volume acquired by the ESP. We also report the first in situ detection of both a HAB organism (i.e., Pseudo-nitzschia) and its toxin, domoic acid, via the sequential (within 2-3 h) conduct of species- and toxin-specific assays during ESP deployments in Monterey Bay, CA, USA. Efforts are now underway to further refine the assay and conduct additional calibration exercises with the aim of obtaining more reliable, accurate estimates of bloom toxicity and thus their potential impacts. Published by Elsevier B.V.

Part-whole relations between food webs and the validity of local food-web descriptions

This work analyzes the relationship between large food webs describing potential feeding relations between species and smaller sub-webs thereof describing relations actually realized in local communities of various sizes. Special attention is given to the relationships between patterns of phylogenetic correlations encountered in large webs and sub-webs. Based on the current theory of food-web topology as implemented in the matching model, it is shown that food webs are scale invariant in the following sense: given a large web described by the model, a smaller, randomly sampled sub-web thereof is described by the model as well. A stochastic analysis of model steady states reveals that such a change in scale goes along with a re-normalization of model parameters. Explicit formulae for the renormalized parameters are derived. Thus, the topology of food webs at all scales follows the same patterns, and these can be revealed by data and models referring to the local scale alone. As a by-product of the theory, a fast algorithm is derived which yields sample food webs from the exact steady state of the matching model for a high-dimensional trophic niche space in finite time. (C) 2008 Elsevier B.V. All rights reserved.

A similarity measure for graphs with low computational complexity

We present and analyze an algorithm to measure the structural similarity of generalized trees, a new graph class which includes rooted trees. For this, we represent structural properties of graphs as strings and define the similarity of two Graphs as optimal alignments of the corresponding property stings. We prove that the obtained graph similarity measures are so called Backward similarity measures. From this we find that the time complexity of our algorithm is polynomial and, hence, significantly better than the time complexity of classical graph similarity methods based on isomorphic relations. (c) 2006 Elsevier Inc. All rights reserved.

Information theoretic measures of UHG graphs with low computational complexity

We introduce a novel graph class we call universal hierarchical graphs (UHG) whose topology can be found numerously in problems representing, e.g., temporal, spacial or general process structures of systems. For this graph class we show, that we can naturally assign two probability distributions, for nodes and for edges, which lead us directly to the definition of the entropy and joint entropy and, hence, mutual information establishing an information theory for this graph class. Furthermore, we provide some results under which conditions these constraint probability distributions maximize the corresponding entropy. Also, we demonstrate that these entropic measures can be computed efficiently which is a prerequisite for every large scale practical application and show some numerical examples. (c) 2007 Elsevier Inc. All rights reserved.

No Association of Dysbindin With Symptom Factors of Schizophrenia in an Irish Case-Control Sample

Robust associations between the dysbindin gene (DTNBP1) and schizophrenia have been demonstrated in many but not all samples, and evidence that this gene particularly predisposes to negative symptoms in this illness has been presented. The current study sought to replicate the previously reported negative symptom associations in an Irish case-control sample. Association between dysbindin and schizophrenia has been established in this cohort, and a factor analysis of the assessed symptoms yielded three factors, Positive, Negative, and Schneiderian. The sequential addition method was applied using UNPHASED to assess the relationship between these symptom factors and the high-risk haplotype. No associations were detected for any of the symptom factors indicating that the dysbindin risk haplotype does not predispose to a particular group of symptoms in this sample. Several possibilities, such as differing risk haplotypes, may explain this finding. (C) 2009 Wiley-Liss, Inc.

Replication of association between schizophrenia and ZNF804A in the Irish Case-Control Study of Schizophrenia sample

A recent genome-wide association study reported association between schizophrenia and the ZNF804A gene on chromosome 2q32.1. We attempted to replicate these findings in our Irish Case-Control Study of Schizophrenia (ICCSS) sample (N=1021 cases, 626 controls). Following consultation with the original investigators, we genotyped three of the most promising single-nucleotide polymorphisms (SNPs) from the Cardiff study. We replicate association with rs1344706 (trend test one-tailed P=0.0113 with the previously associated A allele) in ZNF804A. We detect no evidence of association with rs6490121 in NOS1 (one-tailed P=0.21), and only a trend with rs9922369 in RGRIP1L (one-tailed P=0.0515). On the basis of these results, we completed genotyping of 11 additional linkage disequilibrium-tagging SNPs in ZNF804A. Of 12 SNPs genotyped, 11 pass quality control criteria and 4 are nominally associated, with our most significant evidence of association at rs7597593 (P=0.0013) followed by rs1344706. We observe no evidence of differential association in ZNF804A on the basis of family history or sex of case. The associated SNP rs1344706 lies in approximately 30 bp of conserved mammalian sequence, and the associated A allele is predicted to maintain binding sites for the brain-expressed transcription factors MYT1l and POU3F1/OCT-6. In controls, expression is significantly increased from the A allele of rs1344706 compared with the C allele. Expression is increased in schizophrenic cases compared with controls, but this difference does not achieve statistical significance. This study replicates the original reported association of ZNF804A with schizophrenia and suggests that there is a consistent link between the A allele of rs1344706, increased expression of ZNF804A and risk for schizophrenia.

The dystrobrevin binding protein 1 (DTNBP1) gene is associated with schizophrenia in the Irish Case Control Study of Schizophrenia (ICCSS) sample

Background: DTNBP1 is associated with schizophrenia in many studies, but the associated alleles and haplotypes vary between samples.

Genetic Variation in the Serotonin 2A Receptor and Suicidal Ideation in a Sample of 270 Irish High-Density Schizophrenia Families

Genetic variation in the serotonin 2A receptor (HTR2A) has been associated with both schizophrenia and suicidal behavior. Our sample comprised 270 Irish high-density schizophrenia families (n = 1,408 subjects, including 755 with psychotic illness). Diagnoses were generated using a modified SCID. All patients who had at least one episode of psychosis were rated on the Operation Criteria Checklist for Psychotic Illness (OPCRIT). Lifetime history of suicidal ideation was determined from medical records and psychiatric interviews and was scored in the OPCRIT. Twelve SNPs were selected for study. Ten of these were tagSNPs derived from HapMap data, along with His452Tyr and T102C. We tested for association with psychotic illness as a whole, as well as stratified by the presence of suicidal ideation, using FBAT and PDTPHASE. Single-marker as well as haplotype-based tests using a

The trace amine associated receptor (TAAR6) gene is not associated with schizophrenia in the Irish Case-Control Study of Schizophrenia (ICCSS) sample

To replicate previous association between TAAR6 and schizophrenia, including our own finding in the Irish Study of High Density Schizophrenia Families (ISHDSF) sample, we genotyped 12 single nucleotide polymorphisms (SNPs) in the Irish Case-Control Study of Schizophrenia (ICCSS) sample. Only rs9389020 provided nominal evidence for association (p

Impact of Sample Heterogeneity on Methylation Analysis

The recent emergence of high-throughput arrays for methylation analysis has made the influence of tumor content on the interpretation of methylation levels increasingly pertinent. However, to what degree does tumor content have an influence, and what degree of tumor content makes a specimen acceptable for accurate analysis remains unclear. Taking a systematic approach, we analyzed 98 unselected formalin-fixed and paraffin-embedded gastric tumors and matched normal tissue samples using the Illumina GoldenGate methylation assay. Unsupervised hierarchical clustering showed 2 separate clusters with a significant difference in average tumor content levels. The probes identified to be significantly differentially methylated between the tumors and normals also differed according to the tumor content of the samples included, with the sensitivity of identifying the

‘The ‘Complexity of Imprisonment: The Northern Ireland Experience'

This article will examine the thesis that Northern Ireland experiences a relatively low level of crime. It will explore the possible reasons why crime in the North has not witnessed a dramatic increase. In light of this, the article will highlight the difficulties surrounding the current prison system and illustrate that once again Northern Ireland is experiencing a very different criminal justice system in comparison to Great Britain. Although the prisons are now being used predominately to deal with “ordinary’ crime”, they are still part of the political process.

Assessing software upgrades, plan properties and patient geometry using intensity modulated radiation therapy (IMRT) complexity metrics

Purpose: The aim of this study is to compare the sensitivity of different metrics to detect differences in complexity of intensity modulated radiation therapy (IMRT) plans following upgrades, changes to planning parameters, and patient geometry. Correlations between complexity metrics are also assessed.

Real-valued fixed-complexity sphere decoder for high dimensional QAM-MIMO systems

The development of high performance, low computational complexity detection algorithms is a key challenge for real-time Multiple-Input Multiple-Output (MIMO) communication system design. The Fixed-Complexity Sphere Decoder (FSD) algorithm is one of the most promising approaches, enabling quasi-ML decoding accuracy and high performance implementation due to its deterministic, highly parallel structure. However, it suffers from exponential growth in computational complexity as the number of MIMO transmit antennas increases, critically limiting its scalability to larger MIMO system topologies. In this paper, we present a solution to this problem by applying a novel cutting protocol to the decoding tree of a real-valued FSD algorithm. The new Real-valued Fixed-Complexity Sphere Decoder (RFSD) algorithm derived achieves similar quasi-ML decoding performance as FSD, but with an average 70% reduction in computational complexity, as we demonstrate from both theoretical and implementation perspectives for Quadrature Amplitude Modulation (QAM)-MIMO systems.