Development and validation of the first high performance-lateral flow immunoassay (HP-LFIA) for the rapid screening of domoic acid from shellfish extracts

A lateral flow immunoassay (LFIA) has been developed and fully validated to detect the primary amnesic shellfish poisoning (ASP) toxin, domoic acid (DA). The performance characteristics of two versions of the test were investigated using spiked and naturally contaminated shellfish (mussels, scallops, oysters, clams, and cockles). The tests provide a qualitative result, to indicate the absence or presence of DA in extracts of shellfish tissues, at concentrations that are relevant to regulatory limits. The new rapid assay (LFIA version 2) was designed to overcome the performance limitations identified in the first version of the assay. The improved test uses an electronic reader to remove the subjective nature of the generated results, and the positive cut-off for screening of DA in shellfish was increased from 10 ppm (version 1) to 17.5 ppm (version 2). A simple extraction and test procedure was employed, which required minimal equipment and materials; results were available 15 min after sample preparation. Stability of the aqueous extracts at room temperature (22 C) at four time points (up to 245 min after extraction) and across a range of DA concentrations was 100.3±1.3% and 98.8±2.4% for pre- and post-buffered extracts, respectively. The assay can be used both within laboratory settings and in remote locations. The accuracy of the new assay, to indicate negative results at or below 10 ppm DA, and positive results at or above 17.5 ppm, was 99.5% (n=216 tests). Validation data were obtained from a 2-day, randomised, blind study consisting of multiple LFIA lots (n=3), readers (n=3) and operators (n=3), carrying out multiple extractions of mussel tissue (n=3) at each concentration (0, 10, 17.5, and 20 ppm). No matrix effects were observed on the performance of the assay with different species (mussels, scallops, oysters, clams, and cockles). There was no impact on accuracy or interference from other phycotoxins, glutamic acid or glutamine with various strip incubations (8, 10, and 12 min). The accuracy of the assay, using naturally contaminated samples to indicate negative results at or below 12.5 ppm and positive results at or above 17.5 ppm, was 100%. Variability between three LFIA lots across a range of DA concentrations, expressed as coefficient of variation (% CV), was 1.1±0.4% (n=2 days) based on quantitative readings from the electronic reader. During an 8 week stability study, accuracy of the method with test strips stored at various temperatures (6, 22, 37 and 50 C) was 100%. Validation for both versions included comparisons with results obtained using reference LC-UV methods. © 2013 Elsevier B.V.

Episodic Reasoning for Vision-Based Human Action Recognition

Smart Spaces, Ambient Intelligence, and Ambient Assisted Living are environmental paradigms that strongly depend on their capability to recognize human actions. While most solutions rest on sensor value interpretations and video analysis applications, few have realized the importance of incorporating common-sense capabilities to support the recognition process. Unfortunately, human action recognition cannot be successfully accomplished by only analyzing body postures. On the contrary, this task should be supported by profound knowledge of human agency nature and its tight connection to the reasons and motivations that explain it. The combination of this knowledge and the knowledge about how the world works is essential for recognizing and understanding human actions without committing common-senseless mistakes. This work demonstrates the impact that episodic reasoning has in improving the accuracy of a computer vision system for human action recognition. This work also presents formalization, implementation, and evaluation details of the knowledge model that supports the episodic reasoning.

Evaluation of a worksite cervical screening initiative to increase Pap smear uptake in Malaysia:a cluster randomized controlled trial

Despite the significant burden of cervical cancer, Malaysia like many middle-income countries relies on opportunistic cervical screening as opposed to a more organized population-based program. The aim of this study was to ascertain the effectiveness of a worksite screening initiative upon Papanicolaou smear test (Pap test) uptake among educated working women in Malaysia.

Understanding the Optimal Adsorption Energies for Catalyst Screening in Heterogeneous Catalysis

The fundamental understanding of the activity in heterogeneous catalysis has long been the major subject in chemistry. This paper shows the development of a two-step model to understand this activity. Using the theory of chemical potential kinetics with Bronsted-Evans-Polanyi relations, the general adsorption energy window is determined from volcano curves, using which the best catalysts can be searched. Significant insights into the reasons for catalytic activity are obtained.

Probing charge screening dynamics and electrochemical processes at the solid–liquid interface with electrochemical force microscopy

The presence of mobile ions complicates the implementation of voltage-modulated scanning probe microscopy techniques such as Kelvin probe force microscopy (KPFM). Overcoming this technical hurdle, however, provides a unique opportunity to probe ion dynamics and electrochemical processes in liquid environments and the possibility to unravel the underlying mechanisms behind important processes at the solid–liquid interface, including adsorption, electron transfer and electrocatalysis. Here we describe the development and implementation of electrochemical force microscopy (EcFM) to probe local bias- and time-resolved ion dynamics and electrochemical processes at the solid–liquid interface. Using EcFM, we demonstrate contact potential difference measurements, consistent with the principles of open-loop KPFM operation. We also demonstrate that EcFM can be used to investigate charge screening mechanisms and electrochemical reactions in the probe–sample junction. We further establish EcFM as a force-based imaging mode, allowing visualization of the spatial variability of sample-dependent local electrochemical properties.

Production of a broad specificity antibody for the development and validation of an optical SPR screening method for free and intracellular microcystins and nodularin in cyanobacteria cultures

A highly sensitive broad specificity monoclonal antibody was produced and characterised for microcystin detection through the development of a rapid surface plasmon resonance (SPR) optical biosensor based immunoassay. The antibody displayed the following cross-reactivity: MC-LR 100%; MC-RR 108%; MC-YR 68%; MC-LA 69%; MC-LW 71%; MC-LF 68%; and Nodularin 94%. Microcystin-LR was covalently attached to a CM5 chip and with the monoclonal antibody was employed in a competitive 4min injection assay to detect total microcystins in water samples below the WHO recommended limit (1µg/L). A 'total microcystin' level was determined by measuring free and intracellular concentrations in cyanobacterial culture samples as this toxin is an endotoxin. Glass bead beating was used to lyse the cells as a rapid extraction procedure. This method was validated according to European Commission Decision 96/23/EC criteria. The method was proven to measure intracellular microcystin levels, the main source of the toxin, which often goes undetected by other analytical procedures and is advantageous in that it can be used for the monitoring of blooms to provide an early warning of toxicity. It was shown to be repeatable and reproducible, with recoveries from spiked samples ranging from 74 to 123%, and had % CVs below 10% for intra-assay analysis and 15% for inter-assay analysis. The detection capability of the assay was calculated as 0.5ng/mL for extracellular toxins and 0.05ng/mL for intracellular microcystins. A comparison of the SPR method with LC-MS/MS was achieved by testing six Microcystis aeruginosa cultures and this study yielded a correlation R(2) value of 0.9989.

Automatic Analysis of Digital Retinal Images for Glaucoma Detection

In this paper we propose a novel automated glaucoma detection framework for mass-screening that operates on inexpensive retinal cameras. The proposed methodology is based on the assumption that discriminative features for glaucoma diagnosis can be extracted from the optical nerve head structures,
such as the cup-to-disc ratio or the neuro-retinal rim variation. After automatically segmenting the cup and optical disc, these features are feed into a machine learning classifier. Experiments were performed using two different datasets and from the obtained results the proposed technique provides
better performance than approaches based on appearance. A main advantage of our approach is that it only requires a few training samples to provide high accuracy over several different glaucoma stages.

An optimized stereo vision implementation for embedded systems: application to RGB and Infra-Red images

The aim of this paper is to demonstrate the applicability and the effectiveness of a computationally demanding stereo matching algorithm in different lowcost and low-complexity embedded devices, by focusing on the analysis of timing and image quality performances. Various optimizations have been implemented to allow its deployment on specific hardware architectures while decreasing memory and processing time requirements: (1) reduction of color channel information and resolution for input images, (2) low-level software optimizations such as parallel computation, replacement of function calls or loop unrolling, (3) reduction of redundant data structures and internal data representation. The feasibility of a stereovision system on a low cost platform is evaluated by using standard datasets and images taken from Infra-Red (IR) cameras. Analysis of the resulting disparity map accuracy with respect to a full-size dataset is performed as well as the testing of suboptimal solutions

The CACTOS Vision of Context-Aware Cloud Topology Optimization and Simulation

Recent advances in hardware development coupled with the rapid adoption and broad applicability of cloud computing have introduced widespread heterogeneity in data centers, significantly complicating the management of cloud applications and data center resources. This paper presents the CACTOS approach to cloud infrastructure automation and optimization, which addresses heterogeneity through a combination of in-depth analysis of application behavior with insights from commercial cloud providers. The aim of the approach is threefold: to model applications and data center resources, to simulate applications and resources for planning and operation, and to optimize application deployment and resource use in an autonomic manner. The approach is based on case studies from the areas of business analytics, enterprise applications, and scientific computing.