Causal Chain Analysis in Systematic Reviews of International Development Interventions

Understanding the extent to which an intervention ‘works’ can provide compelling evidence to decision-makers, although without an accompanying explanation of how an intervention works, this evidence can be difficult to apply in other settings, ultimately impeding its usefulness in making judicious and evidence-informed decisions. In this paper, we describe causal chain analysis as involving the development of a logic model, which outlines graphically a hypothesis of how an intervention leads to a change in an outcome. This logic model is then used to anchor subsequent decisions in the systematic review process, including decisions on synthesis. In this paper, we outline the steps taken in building a logic model, which usually consists of a series of boxes depicting intervention components and processes, outputs, and outcomes with arrows depicting connecting relationships. The nature of these connecting relationships and their basis in causality are considered, through a focus on complex causal relationships and the way in which contextual factors about the intervention setting or population may moderate these. We also explore the way in which specific combinations of intervention components may lead to successful interventions. Evidence synthesis techniques are discussed in the context of causal chain analysis, and their usefulness in exploring different parts of the causal chain or different types of relationship. The approaches outlined in this paper aim to assist systematic reviewers in producing findings that are useful to decision-makers and practitioners, and in turn, help to confirm existing theories or develop entirely new ways of understanding how interventions effect change

Restoration of peatlands and greenhouse gas balances

In this chapter the impact of peatland restoration on greenhouse gas fluxes is discussed based on a literature review. Casestudies are presented covering different peatland types, different regions and different starting conditions

Weathering the storm: developments in the acoustic sensing of wind and rain

An Acoustic Rain Gauge (ARG) analyses the underwater sound levels across a wide frequency range, classifies the observed spectrum according to likely source and then determines the local wind speed or rain rate as appropriate. Thispaper covers a trial on the Scotian Shelf off Canada, comparing the geophysical information derived from the acoustic signals with those obtained from other sources

Using logic models in research and evaluation of Health EDRM interventions

This chapter outlines how logic models can be used to conceptualize how interventions are intended to work, and their relationship with the broader context in which they take place – focusing on Health EDRM settings. Logic models are tools used to outline assumptions about the chains of processes, activities or events expected to occur during the implementation of an intervention, and the way in which these lead to changes in outcomes. They provide an initial set of assumptions about how different components of an intervention are expected to change outcomes, and can be used to develop further sub-research questions to investigate the validity of these assumptions. Logic models can also be used to communicate findings from research and evaluation activities, and can serve as useful tools in planning an intervention, including for the identification of relevant outcomes and monitoring of its delivery. However, this chapter will focus primarily on the use of logic models for research and evaluation purposes

UK Research Information Shared Service (UKRISS) Final Report, July 2014

The reporting of research information is a complex and expensive activity for research organisations (ROs). There is little alignment between funders of the reporting requests made to institutions and requests made to individual researchers about their research outputs and outcomes. This inevitably results in duplication and increased costs across the sector, whilst limiting the potential sharing and reuse of the information. The UK Research Information Shared Service (UKRISS) project conducted a feasibility and scoping study for the reporting of research information at a national level based on CERIF (Common European Research Information Format), with the objective of increasing efficiency, productivity and quality across the sector. The aim was to define and prototype solutions which are compelling, easy to use, have a low entry barrier, and support innovative information sharing and benchmarking. CERIF has emerged as the preferred format for expressing research information across Europe. To date, CERIF has been piloted for specific applications, but not as a format for reporting requirements across all UK ROs. The final report presents the work carried out by the UKRISS project, including requirements gathering, modelling and prototyping, as well as recommendation for sustainability. UKRISS was divided into two phases. Phase 1, mapping the reporting landscape, ran from March 2012 to December 2012. Phase 2, exploring delivery of potential solutions, began in February 2013 and ended in December 2013

Energy spectra of elements with 18 or = Z or = 28 between 10 and 300 GeV/amu

The HEAO-3 Heavy Nuclei Experiment is composed of ionization chambers above and below a plastic Cerenkov counter. The energy dependence of the abundances of elements with atomic number, Z, between 18 and 28 at very high energies where they are rare and thus need the large area x time are measured. The measurements of the Danish-French HEAO-3 experiment (Englemann,, et al., 1983) are extended to higher energies, using the relativistic rise of ionization signal as a measure of energy. Source abundances for Ar and Ca were determined

Differentiation of human fetal mesenchymal stem cells into cells with an oligodendrocyte phenotype

This article is available open access through the publisher’s website at the link below. Copyright @ 2009 Landes Bioscience.The potential of mesenchymal stem cells (MSC) to differentiate into neural lineages has raised the possibility of autologous cell transplantation as a therapy for neurodegenerative diseases. We have identified a population of circulating human fetal mesenchymal stem cells (hfMSC) that are highly proliferative and can readily differentiate into mesodermal lineages such as bone, cartilage, fat and muscle. Here, we demonstrate for the first time that primary hfMSC can differentiate into cells with an oligodendrocyte phenotype both in vitro and in vivo. By exposing hfMSC to neuronal conditioned medium or by introducing the pro-oligodendrocyte gene, Olig-2, hfMSC adopted an oligodendrocyte-like morphology, expressed oligodendrocyte markers and appeared to mature appropriately in culture. Importantly we also demonstrate the differentiation of a clonal population of hfMSC into both mesodermal (bone) and ectodermal (oligodendrocyte) lineages. In the developing murine brain transplanted hfMSC integrated into the parenchyma but oligodendrocyte differentiation of these naïve hfMSC was very low. However, the proportion of cells expressing oligodendrocyte markers increased significantly (from 0.2% to 4%) by pre-exposing the cells to differentiation medium in vitro prior to transplantation. Importantly, the process of in vivo differentiation occurred without cell fusion. These findings suggest that hfMSC may provide a potential source of oligodendrocytes for study and potential therapy

Shaping Robust System through Evolution

Biological functions are generated as a result of developmental dynamics that form phenotypes governed by genotypes. The dynamical system for development is shaped through genetic evolution following natural selection based on the fitness of the phenotype. Here we study how this dynamical system is robust to noise during development and to genetic change by mutation. We adopt a simplified transcription regulation network model to govern gene expression, which gives a fitness function. Through simulations of the network that undergoes mutation and selection, we show that a certain level of noise in gene expression is required for the network to acquire both types of robustness. The results reveal how the noise that cells encounter during development shapes any network's robustness, not only to noise but also to mutations. We also establish a relationship between developmental and mutational robustness through phenotypic variances caused by genetic variation and epigenetic noise. A universal relationship between the two variances is derived, akin to the fluctuation-dissipation relationship known in physics