Next generation planar waveguide detection of microcystins in freshwater and cyanobacterial extracts, utilising a novel lysis method for portable sample preparation and analysis

The study details the development of a fully validated, rapid and portable sensor based method for the on-site analysis of microcystins in freshwater samples. The process employs a novel lysis method for the mechanical lysis of cyanobacterial cells, with glass beads and a handheld frother in only 10min. The assay utilises an innovative planar waveguide device that, via an evanescent wave excites fluorescent probes, for amplification of signal in a competitive immunoassay, using an anti-microcystin monoclonal with cross-reactivity against the most common, and toxic variants. Validation of the assay showed the limit of detection (LOD) to be 0.78ngmL and the CCß to be 1ngmL. Robustness of the assay was demonstrated by intra- and inter-assay testing. Intra-assay analysis had % C.V.s between 8 and 26% and recoveries between 73 and 101%, with inter-assay analysis demonstrating % C.V.s between 5 and 14% and recoveries between 78 and 91%. Comparison with LC-MS/MS showed a high correlation (R=0.9954) between the calculated concentrations of 5 different Microcystis aeruginosa cultures for total microcystin content. Total microcystin content was ascertained by the individual measurement of free and cell-bound microcystins. Free microcystins can be measured to 1ngmL, and with a 10-fold concentration step in the intracellular microcystin protocol (which brings the sample within the range of the calibration curve), intracellular pools may be determined to 0.1ngmL. This allows the determination of microcystins at and below the World Health Organisation (WHO) guideline value of 1µgL. This sensor represents a major advancement in portable analysis capabilities and has the potential for numerous other applications.

COS-STAR: a reporting guideline for studies developing core outcome sets (protocol)

BACKGROUND: Core outcome sets can increase the efficiency and value of research and, as a result, there are an increasing number of studies looking to develop core outcome sets (COS). However, the credibility of a COS depends on both the use of sound methodology in its development and clear and transparent reporting of the processes adopted. To date there is no reporting guideline for reporting COS studies. The aim of this programme of research is to develop a reporting guideline for studies developing COS and to highlight some of the important methodological considerations in the process.

METHODS/DESIGN: The study will include a reporting guideline item generation stage which will then be used in a Delphi study. The Delphi study is anticipated to include two rounds. The first round will ask stakeholders to score the items listed and to add any new items they think are relevant. In the second round of the process, participants will be shown the distribution of scores for all stakeholder groups separately and asked to re-score. A final consensus meeting will be held with an expert panel and stakeholder representatives to review the guideline item list. Following the consensus meeting, a reporting guideline will be drafted and review and testing will be undertaken until the guideline is finalised. The final outcome will be the COS-STAR (Core Outcome Set-STAndards for Reporting) guideline for studies developing COS and a supporting explanatory document.

DISCUSSION: To assess the credibility and usefulness of a COS, readers of a COS development report need complete, clear and transparent information on its methodology and proposed core set of outcomes. The COS-STAR guideline will potentially benefit all stakeholders in COS development: COS developers, COS users, e.g. trialists and systematic reviewers, journal editors, policy-makers and patient groups.

Modelling and Prediction of NOx Emission in a Coal-Fired Power Generation Plant

In this paper NOx emissions modelling for real-time operation and control of a 200 MWe coal-fired power generation plant is studied. Three model types are compared. For the first model the fundamentals governing the NOx formation mechanisms and a system identification technique are used to develop a grey-box model. Then a linear AutoRegressive model with eXogenous inputs (ARX) model and a non-linear ARX model (NARX) are built. Operation plant data is used for modelling and validation. Model cross-validation tests show that the developed grey-box model is able to consistently produce better overall long-term prediction performance than the other two models.