Social class and international migration: Female migrants’ narratives of social mobility and social status

It is well established that international migration involves not only geographical but also social mobility, as migrants achieve an improved socioeconomic position through increased economic opportunities, or experience downwards mobility as a result of not being able to transfer their economic, social or educational resources to the receiving country context. While the social mobility that accompanies migration is often considered in the migration literature, the implications for migrants’ social class positioning has been less of a focus. This paper addresses this gap by looking at how female migrants in the UK evaluate social class trajectories as part of their biographical narratives. The paper brings wider sociological debates about class into a discussion about female migrants’ socioeconomic trajectories and social status. By considering material as well as symbolic aspects of class divisions along with the transnational context in which migrants are embedded, the paper highlights the complexity of how migrants are positioned in class terms. It also looks at how class is subjectively interpreted, and outlines different ways in which migrants evaluate their class trajectories, for instance by conceiving of migration from a long-term perspective and in the context of the family unit, by emphasising different quality-oflife aspects, and by challenging dominant meanings associated with class hierarchies. The paper emphasises the intersection of class and gender in female migrants’ experiences, and argues that subjective accounts of class provide an excellent opportunity to explore the complexity of how class is experienced in the context of international migration

Towards multifunctional landscapes coupling low carbon feed and bioenergy production with restorative agriculture: Economic deployment potential of grass-based biorefineries

Grass-based biomass from grasslands can be used as feedstock in green biorefineries (GBs) that produce a range of biobased products. In addition, adjustments made as part of crop rotation to increase areas under temporary grasslands can yield benefits such as carbon sequestration, increased soil productivity, reduced eutrophication and reduced need for pesticides. In this paper, a flexible modeling framework is developed to analyze the deployment options for GBs that use grass–clover to produce protein feed and feedstock for bioenergy. The focus is placed on optimal deployment, considering system configuration and operation, as well as land use changes designed to increase grass–clover cultivation on cropland. A case study involving 17 counties in Sweden showed that the deployment of GB systems could support biomethane and protein feed production corresponding to 5–60 and 13–154%, respectively, of biomethane and soybean feed imports to Sweden in 2020

Effect of atorvastatin on glycaemia progression in patients with diabetes:an analysis from the Collaborative Atorvastatin in Diabetes Trial (CARDS)

AIMS/HYPOTHESIS: In an individual-level analysis we examined the effect of atorvastatin on glycaemia progression in type 2 diabetes and whether glycaemia effects reduce the prevention of cardiovascular disease (CVD) with atorvastatin. METHODS: The study population comprised 2,739 people taking part in the Collaborative Atorvastatin Diabetes Study (CARDS) who were randomised to receive atorvastatin 10 mg or placebo and who had post-randomisation HbA(1c) data. This secondary analysis used Cox regression to estimate the effect of atorvastatin on glycaemia progression, defined as an increase in HbA(1c) of ≥0.5% (5.5 mmol/mol) or intensification of diabetes therapy. Mixed models were used to estimate the effect of atorvastatin on HbA(1c) as a continuous endpoint. RESULTS: Glycaemia progression occurred in 73.6% of participants allocated placebo and 78.1% of those allocated atorvastatin (HR 1.18 [95% CI 1.08, 1.29], p < 0.001) by the end of follow-up. The HR was 1.22 (95% CI 1.19, 1.35) in men and 1.11 (95% CI 0.95, 1.29) in women (p = 0.098 for the sex interaction). A similar effect was seen in on-treatment analyses: HR 1.20 (95% CI 1.07, 1.35), p = 0.001. The net mean treatment effect on HbA(1c) was 0.14% (95% CI 0.08, 0.21) (1.5 mmol/mol). The effect did not increase through time. Diabetes treatment intensification alone did not differ with statin allocation. Neither baseline nor 1-year-attained HbA(1c) predicted subsequent CVD, and the atorvastatin effect on CVD did not vary by HbA(1c) change (interaction p value 0.229). CONCLUSIONS/INTERPRETATION: The effect of atorvastatin 10 mg on glycaemia progression among those with diabetes is statistically significant but very small, is not significantly different between sexes, does not increase with duration of statin and does not have an impact on the magnitude of CVD risk reduction with atorvastatin. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00125-015-3802-6) contains peer-reviewed but unedited supplementary material, which is available to authorised users

Food safety and environmental risks based on meat and dairy consumption surveys

This paper gives an overview of the possibilities of using meat and dairy consumption studies in food safety and environmental risk scenarios. For both types of risk-based scenarios, common denominators are consumption patterns such as frequency and quantity of consumed food, demographic profile of consumers and food safety hazard or environmental impact of a specific type of food. This type of data enables development of simulation models where the Monte Carlo method is considered as a useful mathematical tool. Synergy of three dimensions - field research used in consumption studies, advanced chemometric tools necessary for quantifying chemical food safety hazards or environmental impacts and simulation models - has the potential to adapt datasets from various sources into useful food safety and/or environmental information

Genes Suggest Ancestral Colour Polymorphisms Are Shared across Morphologically Cryptic Species in Arctic Bumblebees

email Suzanne orcd idCopyright: © 2015 Williams et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Itch and skin rash from chocolate during fluoxetine and sertraline treatment: Case report

BACKGROUND: The skin contains a system for producing serotonin as well as serotonin receptors. Serotonin can also cause pruritus when injected into the skin. SSRI-drugs increase serotonin concentrations and are known to have pruritus and other dermal side effects. CASE PRESENTATION: A 46-year-old man consulted his doctor due to symptoms of depression. He did not suffer from any allergy but drinking red wine caused vasomotor rhinitis. Antidepressive treatment with fluoxetine 20 mg daily was initiated which was successful. After three weeks of treatment an itching rash appeared. An adverse drug reaction (ADR) induced by fluoxetine was suspected and fluoxetine treatment was discontinued. The symptoms disappeared with clemastine and betametasone treatment. Since the depressive symptoms returned sertraline medication was initiated. After approximately two weeks of sertraline treatment he noted an intense itching sensation in his scalp after eating a piece of chocolate cake. The itch spread to the arms, abdomen and legs and the patient treated himself with clemastine and the itch disappeared. He now realised that he had eaten a chocolate cake before this episode and remembered that before the first episode he had had a chocolate mousse dessert. He had never had any reaction from eating chocolate before and therefore reported this observation to his doctor. CONCLUSIONS: This case report suggests that there may be individuals that are very sensitive to increases in serotonin concentrations. Dermal side reactions to SSRI-drugs in these patients may be due to high activity in the serotonergic system at the dermal and epidermo-dermal junctional area rather than a hypersensitivity to the drug molecule itself

Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: rationale and design of the epidemiological studies within the IMI DIRECT Consortium

Aims/hypothesis The DIRECT (Diabetes Research on Patient Stratification) Study is part of a European Union Framework 7 Innovative Medicines Initiative project, a joint undertaking between four industry and 21 academic partners throughout Europe. The Consortium aims to discover and validate biomarkers that: (1) predict the rate of glycaemic deterioration before and after type 2 diabetes onset; (2) predict the response to diabetes therapies; and (3) help stratify type 2 diabetes into clearly definable disease subclasses that can be treated more effectively than without stratification. This paper describes two new prospective cohort studies conducted as part of DIRECT. Methods Prediabetic participants (target sample size 2,200-2,700) and patients with newly diagnosed type 2 diabetes (target sample size similar to 1,000) are undergoing detailed metabolic phenotyping at baseline and 18 months and 36 months later. Abdominal, pancreatic and liver fat is assessed using MRI. Insulin secretion and action are assessed using frequently sampled OGTTs in non-diabetic participants, and frequently sampled mixed-meal tolerance tests in patients with type 2 diabetes. Biosamples include venous blood, faeces, urine and nail clippings, which, among other biochemical analyses, will be characterised at genetic, transcriptomic, metabolomic, proteomic and metagenomic levels. Lifestyle is assessed using high-resolution triaxial accelerometry, 24 h diet record, and food habit questionnaires. Conclusinos/interpretation DIRECT will yield an unprecedented array of biomaterials and data. This resource, available through managed access to scientists within and outside the Consortium, will facilitate the development of new treatments and therapeutic strategies for the prevention and management of type 2 diabetes

Predicting and elucidating the etiology of fatty liver disease : A machine learning modeling and validation study in the IMI DIRECT cohorts

Background Non-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in individuals with and without type 2 diabetes (T2D). Early diagnosis of NAFLD is important, as this can help prevent irreversible damage to the liver and, ultimately, hepatocellular carcinomas. We sought to expand etiological understanding and develop a diagnostic tool for NAFLD using machine learning. Methods and findings We utilized the baseline data from IMI DIRECT, a multicenter prospective cohort study of 3,029 European-ancestry adults recently diagnosed with T2D (n= 795) or at high risk of developing the disease (n= 2,234). Multi-omics (genetic, transcriptomic, proteomic, and metabolomic) and clinical (liver enzymes and other serological biomarkers, anthropometry, measures of beta-cell function, insulin sensitivity, and lifestyle) data comprised the key input variables. The models were trained on MRI-image-derived liver fat content (= 5%) available for 1,514 participants. We applied LASSO (least absolute shrinkage and selection operator) to select features from the different layers of omics data and random forest analysis to develop the models. The prediction models included clinical and omics variables separately or in combination. A model including all omics and clinical variables yielded a cross-validated receiver operating characteristic area under the curve (ROCAUC) of 0.84 (95% CI 0.82, 0.86;p = 5%) rather than a continuous one. Conclusions In this study, we developed several models with different combinations of clinical and omics data and identified biological features that appear to be associated with liver fat accumulation. In general, the clinical variables showed better prediction ability than the complex omics variables. However, the combination of omics and clinical variables yielded the highest accuracy. We have incorporated the developed clinical models into a web interface (see:) and made it available to the community.Peer reviewe