Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands

Accurate in silico models for the quantitative prediction of the activity of G protein-coupled receptor (GPCR) ligands would greatly facilitate the process of drug discovery and development. Several methodologies have been developed based on the properties of the ligands, the direct study of the receptor-ligand interactions, or a combination of both approaches. Ligand-based three-dimensional quantitative structure-activity relationships (3D-QSAR) techniques, not requiring knowledge of the receptor structure, have been historically the first to be applied to the prediction of the activity of GPCR ligands. They are generally endowed with robustness and good ranking ability; however they are highly dependent on training sets. Structure-based techniques generally do not provide the level of accuracy necessary to yield meaningful rankings when applied to GPCR homology models. However, they are essentially independent from training sets and have a sufficient level of accuracy to allow an effective discrimination between binders and nonbinders, thus qualifying as viable lead discovery tools. The combination of ligand and structure-based methodologies in the form of receptor-based 3D-QSAR and ligand and structure-based consensus models results in robust and accurate quantitative predictions. The contribution of the structure-based component to these combined approaches is expected to become more substantial and effective in the future, as more sophisticated scoring functions are developed and more detailed structural information on GPCRs is gathered.

A Multicenter Blinded Study to Evaluate KRAS Mutation Testing Methodologies in the Clinical Setting

Evidence that activating mutations of the KRAS oncogene abolish the response to anti-epidermal growth factor receptor therapy has revolutionized the treatment of advanced colorectal cancer. This has resulted in the urgent demand for KRAS mutation testing in the clinical setting to aid choice of therapy. The Am of this study was to evaluate six different KRAS mutation detection methodologies on two series of primary colorectal cancer samples. Two series of 80 frozen and 74 formalin-fixed paraffin-embedded tissue samples were sourced and DNA was extracted at a central site before distribution to seven different testing sites. KRAS mutations in codons 12 and 13 were assessed by using single strand conformation polymorphism analysis, pyrosequencing, high resolution melting analysis, dideoxy sequencing, or the commercially available TIB Molbiol (Berlin, Germany) or DxS Diagnostic innovations (Manchester, UK) kits. in frozen tissue samples, concordance in KRAS status (defined as consensus in at least five assays) was observed in 66/80 (83%) cases. In par-affin tissue, concordance was 46/74 (63%) if all assays were considered or 71/74 (96%) using the five best performing assays. These results demonstrate that a variety of detection methodologies are suitable and provide comparable results for KRAS mutation analysis of clinical samples. (J Mol Diagn 2009, 11:543-552; DOI: 10.2353/jmoldx.2009.090057)

Exploring Innovative Methodologies in time and place to analyze child protection documents as elements of practice

This paper aims to demonstrate how a derived approach to case file analysis, influenced by the work of Michel Foucault and Dorothy E.Smith, can offer innovative means by which to study the relations between discourse and practices in child welfare. The article explores text-based forms of organization in histories of child protection in Finland and in Northern Ireland. It is focused on case file records in different organizational child protection contexts in two jurisdictions. Building on a previous article (Author 1 & 2: 2011), we attempt to demonstrate the potential of how the relations between practices and discourses –a majorly important theme for understanding child welfare social work – can be effectively analysed using a combination of two approaches This article is based on three different empirical studies from our two jurisdictions Northern Ireland (UK) and Finland; one study used Foucault; the other Smith and the third study sought to combine the methods. This article seeks to report on ongoing work in developing, for child welfare studies, ‘a history that speaks back’ as we have described it.

Computational simulation methodologies for mechanobiological modelling: a cell-centred approach to neointima development in stents

The design of medical devices could be very much improved if robust tools were available for computational simulation of tissue response to the presence of the implant. Such tools require algorithms to simulate the response of tissues to mechanical and chemical stimuli. Available methodologies include those based on the principle of mechanical homeostasis, those which use continuum models to simulate biological constituents, and the cell-centred approach, which models cells as autonomous agents. In the latter approach, cell behaviour is governed by rules based on the state of the local environment around the cell; and informed by experiment. Tissue growth and differentiation requires simulating many of these cells together. In this paper, the methodology and applications of cell-centred techniques-with particular application to mechanobiology-are reviewed, and a cell-centred model of tissue formation in the lumen of an artery in response to the deployment of a stent is presented. The method is capable of capturing some of the most important aspects of restenosis, including nonlinear lesion growth with time. The approach taken in this paper provides a framework for simulating restenosis; the next step will be to couple it with more patient-specific geometries and quantitative parameter data.

Utilising Creative Methodologies to Elicit the Views of Young Learners with Additional Needs in Literacy

The research described in this article aimed to explore and examine the dominant ‘assessment’ and ‘participation’ stories of upper-primary pupils with long-standing and marked literacy learning needs, their views on how their level of participation in the assessment and remediation of their additional needs might be increased and also how they perceive themselves as literacy learners. This qualitative small-scale study adopted a case study approach and utilised creative methodologies in the context of focus groups to investigate sensitively theviews and experiences of Key Stage 2 pupils with additional needs in literacy. The findings discussed here are based on the outcomes from the four Northern Irish schools that participated in the original cross-border (Northern Ireland/Republic of Ireland) study. Findings are discussed in the context of strategies for promotingholistic and empowering pathways for learners with additional needs in literacy.

Use of NMR metabolomic plasma profiling methodologies to identify illicit growth-promoting administrations

Detection of growth-promoter use in animal production systems still proves to be an analytical challenge despite years of activity in the field. This study reports on the capability of NMR metabolomic profiling techniques to discriminate between plasma samples obtained from cattle treated with different groups of growth-promoting hormones (dexamethasone, prednisolone, oestradiol) based on recorded metabolite profiles. Two methods of NMR analysis were investigated—a Carr–Purcell–Meiboom–Gill (CPMG)-pulse sequence technique and a conventional 1H NMR method using pre-extracted plasma. Using the CPMG method, 17 distinct metabolites could be identified from the spectra. 1H NMR analysis of extracted plasma facilitated identification of 23 metabolites—six more than the alternative method and all within the aromatic region. Multivariate statistical analysis of acquired data from both forms of NMR analysis separated the plasma metabolite profiles into distinct sample cluster sets representative of the different animal study groups. Samples from both sets of corticosteroid-treated animals—dexamethasone and prednisolone—were found to be clustered relatively closely and had similar alterations to identified metabolite panels. Distinctive metabolite profiles, different from those observed within plasma from corticosteroid-treated animal plasma, were observed in oestradiol-treated animals and samples from these animals formed a cluster spatially isolated from control animal plasma samples. These findings suggest the potential use of NMR methodologies of plasma metabolite analysis as a high-throughput screening technique to aid detection of growth promoter use.