Application of a novel phytotoxicity assay for the detection of herbicides in Hervey Bay and the Great Sandy Straits

A novel phytotoxicity assay was incorporated into an environmental assessment of Hervey Bay and the Great Sandy Straits, to investigate the role of run-off associated herbicides in the deteriorated health of intertidal seagrass meadows. Dose response curves of common herbicides were performed and their toxicity equivalents elucidated to assist in analysis. The results of the assay were reproducible and corresponded strongly with results of chemical analyses. The incorporation of the assay into the assessment of surface waters added an important aspect to the study by allowing investigation of the toxicity of cumulative herbicide concentrations and yielding biologically relevant data. The highest herbicide concentration detected during the study was equivalent to 0.23 mu g 1(-1) diuron; a concentration known to inhibit photosynthetic efficiency of the assay biomaterial by approximately 3%. (c) 2004 Elsevier Ltd. All rights reserved.

Comparison of commercially available and novel West Nile virus immunoassays for detection of seroconversion in pig-tailed macaques (Macaca nemestrina)

We report the assessment and validation of an NS1 epitope-blocking enzyme-linked immunosorbent assay (ELISA) for detection of antibodies to West Nile virus (WNV) in macaques. Sera from naturally infected Macaca nemestrina were tested by ELISA and plaque reduction neutralization test (PRNT). Results were correlated with hemagglutination inhibition (HAI) data. Our results demonstrate that the blocking ELISA rapidly and specifically detects WNV infection in M. nemestrina. In addition, the diagnostic value of 7 commercially available immunoassays (PanBio immunoglobulin [Ig] M ELISA, PanBio IgG ELISA, PanBio immunofluorescence assay (IFA), InBios IgG ELISA, InBios IgM ELISA, Focus Diagnostics IgG ELISA, and Focus Diagnostics IgM ELISA) in M. nemestrina was evaluated and compared with that of the epitope-blocking ELISA. The PanBio IgG ELISA was found to effectively diagnose WNV exposure in M. nemestrina. Further, PanBio IFA slides are fast and reliable screening tools for diagnosing flaviviral exposure in M. nemestrina.

Chemical and functional identification and characterization of novel sulfated alpha-conotoxins from the cone snail Conus anemone

An LC/MS analysis with diagnostic screening for the detection of peptides with posttranslational modifications revealed the presence of novel sulfated peptides within the -conotoxin molecular mass range in Conus anemone crude venom. A functional assay of the extract showed activity at several neuronal nicotinic acetylcholine receptors (nAChRs). Three sulfated alpha-conotoxins (AnIA, AnIB, and AnIC) were identified by LC/MS and assay-directed fractionation and sequenced after purification. The most active of these, alpha-AnIB, was further characterized and used to investigate the influence of posttranslational modifications on affinity. Synthetic AnIB exhibited subnanomolar potency at the rat alpha3/beta2 nAChR (IC50 0.3 nM) and was 200-fold less active on the rat alpha7 nAChR (IC50 76 nM). The unsulfated peptide [Tyr(16)]AnIB showed a 2-fold and 10-fold decrease in activities at alpha3beta2 (IC50 0.6 nM) and alpha7(IC50 836 nM) nAChR, respectively. Likewise, removal of the C-terminal amide had a greater influence on potency at the alpha7 (IC50 367 nM) than at the alpha3beta2 nAChR (IC50 0.5 nM). Stepwise removal of two N-terminal glycine residues revealed that these residues affect the binding kinetics of the peptide. Comparison with similar 4/7-alpha-conotoxin sequences suggests that residue 11 (alanine or glycine) and residue 14 (glutamine) constitute important determinants for alpha3beta2 selectivity, whereas the C-terminal amidation and sulfation at tyrosine-16 favor alpha7 affinity.

The selection of a model microalgal species as biomaterial for a novel aquatic phytotoxicity assay

A phytotoxicity assay based on the ToxY-PAM dual-channel yield analyser has been developed and successfully incorporated into field assessments for the detection of phytotoxicants in water. As a means of further exploring the scope of the assay application and of selecting a model biomaterial to complement the instrument design, nine algal species were exposed to four chemical substances deemed of priority for water quality monitoring purposes (chlorpyrifos, copper, diuron and nonylphenol ethoxylate). Inter-species differences in sensitivity to the four toxicants varied by a factor of 1.9-100. Measurements of photosystem-II quantum yield using these nine single-celled microalgae as biomaterial corroborated previous studies which have shown that the ToxY-PAM dual-channel yield analyser is a highly sensitive method for the detection of PS-II impacting herbicides. Besides Phaeodactylum tricornutum, the previously applied biomaterial, three other species consistently performed well (Nitzschia closterium, Chlorella vulgaris and Dunaliella tertiolecta) and will be used in further test optimisation experiments. In addition to sensitivity, response time was evaluated and revealed a high degree of variation between species and toxicants. While most species displayed relatively weak and slow responses to copper, C. vulgaris demonstrated an IC10 of 51 μ g L-1, with maximum response measured within 25 minutes and inhibition being accompanied by a large decrease in fluorescence yield. The potential for this C vulgaris-based bioassay to be used for the detection of copper is discussed. There was no evidence that the standard ToxY-PAM protocol, using these unicellular algae species, could be used for the detection of chlorpyrifos or nonylphenol ethoxylate at environmentally relevant levels. © 2005 Elsevier B.V. All rights reserved.

The combined SPE : ToxY-PAM phytotoxicity assay; application and appraisal of a novel biomonitoring tool for the aquatic environment

Mounting concerns regarding the environmental impact of herbicides has meant a growing requirement for accurate, timely information regarding herbicide residue contamination of, in particular, aquatic systems. Conventional methods of detection remain limited in terms of practicality due to high costs of operation and the specialised information that analysis provides. A new phytotoxicity bioassay was trialled for the detection of herbicide residues in filter-purified (Milli-Q) as well as natural waters. The performance of the system, which combines solid-phase extraction (SPE) with the ToxY-PAM dual-channel yield analyser (Heinz Walz GmbH), was tested alongside the traditional method of liquid chromatography-mass spectrometry (LC-MS). The assay methodology was found to be highly sensitive (LOD 0.1 ng L-1 diuron) with good reproducibility. The study showed that the assay protocol is time effective and can be employed for the aquatic screening of herbicide residues in purified as well as natural waters.

Development of an oligonucleotide-based SNP detection method on lateral flow strips using hexapet tages

Detection of point mutations or single nucleotide polymorphisms (SNPs) is important in relation to disease susceptibility or detection in pathogens of mutations determining drug resistance or host range. There is an emergent need for rapid detection methods amenable to point-of-care applications. The purpose of this study was to reduce to practice a novel method for SNP detection and to demonstrate that this technology can be used downstream of nucleic acid amplification. The authors used a model system to develop an oligonucleotide-based SNP detection system on nitrocellulose lateral flow strips. To optimize the assay they used cloned sequences of the herpes simplex virus-1 (HSV-1) DNA polymerase gene into which they introduced a point mutation. The assay system uses chimeric polymerase chain reaction (PCR) primers that incorporate hexameric repeat tags ("hexapet tags"). The chimeric sequences allow capture of amplified products to predefined positions on a lateral flow strip. These "hexapet" sequences have minimal cross-reactivity and allow specific hybridization-based capture of the PCR products at room temperature onto lateral flow strips that have been striped with complementary hexapet tags. The allele-specific amplification was carried out with both mutant and wild-type primer sets present in the PCR mix ("competitive" format). The resulting PCR products carried a hexapet tag that corresponded with either a wild-type or mutant sequence. The lateral flow strips are dropped into the PCR reaction tube, and mutant sequence and wild-type sequences diffuse along the strip and are captured at the corresponding position on the strip. A red line indicative of a positive reaction is visible after 1 minute. Unlike other systems that require separate reactions and strips for each target sequence, this system allows multiplex PCR reactions and multiplex detection on a single strip or other suitable substrates. Unambiguous visual discrimination of a point mutation under room temperature hybridization conditions was achieved with this model system in 10 minutes after PCR. The authors have developed a capture-based hybridization method for the detection and discrimination of HSV-1 DNA polymerase genes that contain a single nucleotide change. It has been demonstrated that the hexapet oligonucleotides can be adapted for hybridization on the lateral flow strip platform for discrimination of SNPs. This is the first step in demonstrating SNP detection on lateral flow using the hexapet oligonucleotide capture system. It is anticipated that this novel system can be widely used in point-of-care settings.

Multigradient field-active contour model for multilayer boundary detection of ultrasound rectal wall image

Extraction and reconstruction of rectal wall structures from an ultrasound image is helpful for surgeons in rectal clinical diagnosis and 3-D reconstruction of rectal structures from ultrasound images. The primary task is to extract the boundary of the muscular layers on the rectal wall. However, due to the low SNR from ultrasound imaging and the thin muscular layer structure of the rectum, this boundary detection task remains a challenge. An active contour model is an effective high-level model, which has been used successfully to aid the tasks of object representation and recognition in many image-processing applications. We present a novel multigradient field active contour algorithm with an extended ability for multiple-object detection, which overcomes some limitations of ordinary active contour models—"snakes." The core part in the algorithm is the proposal of multigradient vector fields, which are used to replace image forces in kinetic function for alternative constraints on the deformation of active contour, thereby partially solving the initialization limitation of active contour for rectal wall boundary detection. An adaptive expanding force is also added to the model to help the active contour go through the homogenous region in the image. The efficacy of the model is explained and tested on the boundary detection of a ring-shaped image, a synthetic image, and an ultrasound image. The experimental results show that the proposed multigradient field-active contour is feasible for multilayer boundary detection of rectal wall

Off-line signature verification and forgery detection using fuzzy modeling

Automatic signature verification is a well-established and an active area of research with numerous applications such as bank check verification, ATM access, etc. This paper proposes a novel approach to the problem of automatic off-line signature verification and forgery detection. The proposed approach is based on fuzzy modeling that employs the Takagi-Sugeno (TS) model. Signature verification and forgery detection are carried out using angle features extracted from box approach. Each feature corresponds to a fuzzy set. The features are fuzzified by an exponential membership function involved in the TS model, which is modified to include structural parameters. The structural parameters are devised to take account of possible variations due to handwriting styles and to reflect moods. The membership functions constitute weights in the TS model. The optimization of the output of the TS model with respect to the structural parameters yields the solution for the parameters. We have also derived two TS models by considering a rule for each input feature in the first formulation (Multiple rules) and by considering a single rule for all input features in the second formulation. In this work, we have found that TS model with multiple rules is better than TS model with single rule for detecting three types of forgeries; random, skilled and unskilled from a large database of sample signatures in addition to verifying genuine signatures. We have also devised three approaches, viz., an innovative approach and two intuitive approaches using the TS model with multiple rules for improved performance. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

A multiresolution terrain model for efficient visualization query processing

Multiresolution Triangular Mesh (MTM) models are widely used to improve the performance of large terrain visualization by replacing the original model with a simplified one. MTM models, which consist of both original and simplified data, are commonly stored in spatial database systems due to their size. The relatively slow access speed of disks makes data retrieval the bottleneck of such terrain visualization systems. Existing spatial access methods proposed to address this problem rely on main-memory MTM models, which leads to significant overhead during query processing. In this paper, we approach the problem from a new perspective and propose a novel MTM called direct mesh that is designed specifically for secondary storage. It supports available indexing methods natively and requires no modification to MTM structure. Experiment results, which are based on two real-world data sets, show an average performance improvement of 5-10 times over the existing methods.

Hierarchical indexing structure for efficient similarity search in video retrieval

With the rapid increase in both centralized video archives and distributed WWW video resources, content-based video retrieval is gaining its importance. To support such applications efficiently, content-based video indexing must be addressed. Typically, each video is represented by a sequence of frames. Due to the high dimensionality of frame representation and the large number of frames, video indexing introduces an additional degree of complexity. In this paper, we address the problem of content-based video indexing and propose an efficient solution, called the Ordered VA-File (OVA-File) based on the VA-file. OVA-File is a hierarchical structure and has two novel features: 1) partitioning the whole file into slices such that only a small number of slices are accessed and checked during k Nearest Neighbor (kNN) search and 2) efficient handling of insertions of new vectors into the OVA-File, such that the average distance between the new vectors and those approximations near that position is minimized. To facilitate a search, we present an efficient approximate kNN algorithm named Ordered VA-LOW (OVA-LOW) based on the proposed OVA-File. OVA-LOW first chooses possible OVA-Slices by ranking the distances between their corresponding centers and the query vector, and then visits all approximations in the selected OVA-Slices to work out approximate kNN. The number of possible OVA-Slices is controlled by a user-defined parameter delta. By adjusting delta, OVA-LOW provides a trade-off between the query cost and the result quality. Query by video clip consisting of multiple frames is also discussed. Extensive experimental studies using real video data sets were conducted and the results showed that our methods can yield a significant speed-up over an existing VA-file-based method and iDistance with high query result quality. Furthermore, by incorporating temporal correlation of video content, our methods achieved much more efficient performance.

Real-time PCR assays for detection of bocavirus in human specimens

The recently discovered human bocavirus (HBoV) is the first member of the family Parpoviridae, genus Bocavirus, to be potentially associated with human disease. Several studies have identified HBoV in respiratory specimens from children with acute respiratory disease, but the full spectrum of clinical disease and the epidemiology of HBoV infection remain unclear. The availability of rapid and reliable molecular diagnostics would therefore aid future studies of this novel virus. To address this, we developed two sensitive and specific real-time TaqMan PCR assays that target the HBoV NS1 and NP-1 genes. Both assays could reproducibly detect 10 copies of a recombinant DNA plasmid containing a partial region of the HBoV genome, with a dynamic range of 8 log units (10(1) to 10(8) copies). Eight blinded clinical specimen extracts positive for HBoV by an independent PCR assay were positive by both real-time assays. Among 1,178 NP swabs collected from hospitalized pneumonia patients in Sa Kaeo Province, Thailand, 53 (4.5%) were reproducibly positive for HBoV by one or both targets. Our data confirm the possible association of HBoV infection with pneumonia and demonstrate the utility of these real-time PCR assays for HBoV detection.

Toward efficient multifeature query processing

In many advanced applications, data are described by multiple high-dimensional features. Moreover, different queries may weight these features differently; some may not even specify all the features. In this paper, we propose our solution to support efficient query processing in these applications. We devise a novel representation that compactly captures f features into two components: The first component is a 2D vector that reflects a distance range ( minimum and maximum values) of the f features with respect to a reference point ( the center of the space) in a metric space and the second component is a bit signature, with two bits per dimension, obtained by analyzing each feature's descending energy histogram. This representation enables two levels of filtering: The first component prunes away points that do not share similar distance ranges, while the bit signature filters away points based on the dimensions of the relevant features. Moreover, the representation facilitates the use of a single index structure to further speed up processing. We employ the classical B+-tree for this purpose. We also propose a KNN search algorithm that exploits the access orders of critical dimensions of highly selective features and partial distances to prune the search space more effectively. Our extensive experiments on both real-life and synthetic data sets show that the proposed solution offers significant performance advantages over sequential scan and retrieval methods using single and multiple VA-files.