First Trimester Urine and Serum Metabolomics for Prediction of Preeclampsia and Gestational Hypertension: A Prospective Screening Study

Hypertensive disorders of pregnancy, including preeclampsia, are major contributors to maternal morbidity. The goal of this study was to evaluate the potential of metabolomics to predict preeclampsia and gestational hypertension from urine and serum samples in early pregnancy, and elucidate the metabolic changes related to the diseases. Metabolic profiles were obtained by nuclear magnetic resonance spectroscopy of serum and urine samples from 599 women at medium to high risk of preeclampsia (nulliparous or previous preeclampsia/gestational hypertension). Preeclampsia developed in 26 (4.3%) and gestational hypertension in 21 (3.5%) women. Multivariate analyses of the metabolic profiles were performed to establish prediction models for the hypertensive disorders individually and combined. Urinary metabolomic profiles predicted preeclampsia and gestational hypertension at 51.3% and 40% sensitivity, respectively, at 10% false positive rate, with hippurate as the most important metabolite for the prediction. Serum metabolomic profiles predicted preeclampsia and gestational hypertension at 15% and 33% sensitivity, respectively, with increased lipid levels and an atherogenic lipid profile as most important for the prediction. Combining maternal characteristics with the urinary hippurate/creatinine level improved the prediction rates of preeclampsia in a logistic regression model. The study indicates a potential future role of clinical importance for metabolomic analysis of urine in prediction of preeclampsia.     

Multianalyte single-cell analysis with multiple cell lines using a fiber-optic array

A single-cell drug screening method is described that produces rich single-cell data and discriminates between single-cell responses from clonal populations stimulated with different agonists. Ligand-induced receptor activation is commonly detected by observing intracellular Ca2+ oscillations using high-throughput screening (HTS) methods. In most cases, HTS results in an average signal from several cells and is not sensitive enough to enable the identification of population outliers or population variance. In order to obtain this information, many individual cells must be analyzed simultaneously. We have developed a novel system using a specialized fiber-optic platform and have combined it with statistical analysis, to simultaneously analyze the dynamics of Ca2+ oscillations in a large number of single cells. Mammalian cells ectopically expressing different human GPCR receptors were stimulated, and Ca2+ changes in numerous single cells were recorded over time using a fluorescent microscope and a CCD camera. We determined the percentage of live cells in a population responding to stimuli, the distribution of responses within a population of clonal cells, and the number of outliers. By employing principal component analysis and K-nearest neighbor modeling, we classified the time-resolved Ca2+ traces of single cells as a function of the stimulus type with high certainty for a population of cells. This method is potentially a powerful tool for identifying new drug targets or for investigating the single-cell behavior of an existing target or known receptor. The development of this single-cell drug screening method is presented, and fluorescent and statistical analyses of single-cell dynamic responses are discussed.     

Comparing the climate effect of emissions of short- and long-lived climate agents

Multi-gas climate agreements require a metric by which emissions of gases with different lifetimes and radiative properties can be placed on a common scale. The Kyoto Protocol to the United Nations Framework Convention on Climate Change uses the global warming potential (GWP) as such a metric. The GWP has attracted particular criticism as being inappropriate in the context of climate policy which seeks to restrict warming below a given target, because it gives equal weight to emissions irrespective of the target and the proximity to the target. The use of an alternative metric, the time-dependent global temperature change potential (GTP), is examined for its suitability and the prospects for it including very short-lived species. It retains the transparency and relative ease of use, which are attractive features of the GWP, but explicitly includes a dependence on the target of climate policy. The weighting of emissions using the GTP is found to be significantly dependent on the scenarios of future emissions and the sensitivity of the climate system. This may indicate that the use of any GTP-based weighting in future policymaking would necessitate regular revisions, as the global-mean temperature moves towards a specified target.     

Globalisation, place and gender

Current processes linking different parts of the world together economically and culturally are referred to asglobalisation. Though this term has gained immense popularity within a short time, critics have argued that it is hard to find empirical evidence that the world is becoming one. A crucial question is thenhow to look for such evidence. In many studies of globalisation, the general view taken is that of global, meaning that one searches for a global overview, or outlook, which is situated at no specific place. The present paper argues for a shift of focus, reasoning that to understand what is global we have to start with the local. The experiences of the global take place in particular local places, and to study such processes of change we need to situate our study in such a way that we can study the relationships between the local and the global. The particular place where our study takes place is rural Malaysia. Changes related to industrialisation are often spoken of in rather deterministic terms, in the sense that the local population are victims of a global shift, whereas we argue for an alternative approach, analysing women workers as agents of change within their local community. Globalisation also mainly refers to external forces imposed on local actors, whereas we find the local to be imperative for the strategies of industrialists, as well as for the present processes of change.     

Confluence of aspects for sequence diagrams

The last decade has seen several aspect language proposals for UML 2 sequence diagrams. Aspects allow the modeler to define crosscutting concerns of sequence diagrams and to have these woven with the sequence diagrams of a so-called base model, in order to create a woven model. In a real-world scenario, there may be multiple aspects applicable to the same base model. This raises the need to analyse the set of aspects to identify possible aspect interactions (dependencies and conflicts) between applications of aspects. We call a set of aspects terminating if they may not be applied infinitely many times for any given base model. Furthermore, we call a set of terminating aspects confluent, if they, for any given base model, always yield the same final result regardless of the order in which they are applied. Since confluence must hold for any base model, this is a much stronger result than many of the current approaches that have addressed detection of aspect interactions limited to a specific base model. Our aspects are specified using standard sequence diagrams with some extensions. In this paper, we present a confluence theory specialized for our highly expressive aspect language. For the most expressive aspects, we prove that confluence is undecidable. For another class of aspects with considerable expressiveness, we prescribe an algorithm to check confluence. This algorithm is based on what we call an extended critical pair analysis. These results are useful both for modelers and researchers working with sequence diagram aspects and for researchers wanting to establish a confluence theory for other aspect-oriented modelling or model transformation approaches.     

A HACCP plan for mycotoxigenic hazards associated with dry-cured meat production processes

This work provided a HACCP plan for mycotoxigenic hazards associated with dry-cured meat production facility. Mycotoxigenic hazards that could emerge at each stage of the production were described. Pathogenic yeasts, toxic secondary metabolites of toxigenic moulds were identified as the potential hazards. Smoking and the dry-ripening stages of production were the critical control points identified. Critical limits for the critical control points were set based on scientific premises and recommendations set by legislative authorities. The status of the critical limits at the identified critical control points need to be monitored, verified and recorded.     

Communication Gaps in Disaster Management: Perceptions by Experts from Governmental and Non‐Governmental Organizations

The complexity of current disasters creates a challenge for crisis communication. This paper aims at identifying gaps in communication in disaster management experienced in practice in order to facilitate learning from those situations. The research was conducted using a qualitative online open‐ended questionnaire. It shows that despite the developments in the discipline, communication as an integral part of decision making in disaster management needs to be further developed. The paper provides a practical‐oriented overview of the communication constraints in complex crisis situations, which has not been provided so far. This research is part of an international project developing performance indicators for a quality measurement system for crisis communication.     

Module superimposition: a composition technique for rule-based model transformation languages

As the application of model transformation becomes increasingly commonplace, the focus is shifting from model transformation languages to the model transformations themselves. The properties of model transformations, such as scalability, maintainability and reusability, have become important. Composition of model transformations allows for the creation of smaller, maintainable and reusable transformation definitions that together perform a larger transformation. This paper focuses on composition for two rule-based model transformation languages: the ATLAS Transformation Language (ATL) and the QVT Relations language. We propose a composition technique called module superimposition that allows for extending and overriding rules in transformation modules. We provide executable semantics as well as a concise and scalable implementation of module superimposition based on ATL.