Search

Language is one of the strongest and most valuable tools that is within our reach and that allows us to communicate in society. However, through both written and spoken language, a certain gender inequality can usually be perceived. Nonetheless, there are some considerable differences depending on the languages. While Spanish and Italian are rooted in a patriarchal society, English seems to be more neutral when it comes to gender. Some nouns used to designate professions clearly represent the best examples of sexist language and dictionaries are a fair reflection of this. In order to deepen the topic from a gender translation perspective, this work will analyze some of the jobs that appear throughout the novel I guardiani della Storia, written by the Italian author Elisabetta Cametti, and its translation into Spanish (by Claudia Conde) and into English (by Scott P. Sheridan). Therefore, this analysis will present a study of the differences among the three languages regarding linguistic sexism as well as examine how gender issues can influence the reception of the translated texts., Anglistica AION: An Interdisciplinary Journal, V. 22 N. 2 (2018): Translating LSP in Literature through a Gender Perspective

Childhood overweight and obesity is a serious public health issue with an increase being observed in preschool-aged children. Treating childhood obesity is difficult and few countries use standardized treatments. Therefore, there is a need to find effective approaches that are feasible for both health care providers and families. Thus, the overall aim of this study is to assess the acceptance and effectiveness of a parent support program (the More and Less, ML) for the management of overweight and obesity followed by a mobile health (mHealth) program (the MINISTOP application) in a socially diverse population of families. Methods/design A two-arm, parallel design randomized controlled trial in 300 2-to 6-year-old children with overweight and obesity from Romania, Spain and Sweden (n = 100 from each). Following baseline assessments children are randomized into the intervention or control group in a 1:1 ratio. The intervention, the ML program, consists of 10-weekly group sessions which focus on evidence-based parenting practices, followed by the previously validated MINISTOP application for 6-months to support healthy eating and physical activity behaviors. The primary outcome is change in body mass index (BMI) z-score after 9-months and secondary outcomes include: waist circumference, eating behavior (Child Eating Behavior Questionnaire), parenting behavior (Comprehensive Feeding Practices Questionnaire), physical activity (ActiGraph wGT3x-BT), dietary patterns (based on metabolic markers from urine and 24 h dietary recalls), epigenetic and gut hormones (fasting blood samples), and the overall acceptance of the overweight and obesity management in young children (semi-structured interviews). Outcomes are measured at baseline and after: 10-weeks (only BMI z-score, waist circumference), 9-months (all outcomes), 15- and 21-months (all outcomes except physical activity, dietary patterns, epigenetics and gut hormones) post-baseline. Discussion This study will evaluate a parent support program for weight management in young children in three European countries. To boost the effect of the ML program the families will be supported by an app for 6-months. If the program is found to be effective, it has the potential to be implemented into routine care to reduce overweight and obesity in young children and the app could prove to be a viable option for sustained effects of the care provided This study is funded through the STOP project, http://www.stopchildobesity. eu/. The STOP project received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No. 774548. The content of this document reflects only the authors’ views and the European Commission is not liable for any use that may be made of the information it contains. JAT, CB, EA and JAM are also funded by CIBEROBN (CB12/03/30038), Instituto de Salud Carlos III and the European Regional Development Fund. CB is also funded by a Fernando Tarongí Bauzà Grant. MS was also funded by CIBERESP, Instituto de Salud Carlos III.

A major purpose of exploratory metabolic profiling is for the identification of molecular species that are statistically associated with specific biological or medical outcomes; unfortunately, the structure elucidation process of unknowns is often a major bottleneck in this process. We present here new holistic strategies that combine different statistical spectroscopic and analytical techniques to improve and simplify the process of metabolite identification. We exemplify these strategies using study data collected as part of a dietary intervention to improve health and which elicits a relatively subtle suite of changes from complex molecular profiles. We identify three new dietary biomarkers related to the consumption of peas (N-methyl nicotinic acid), apples (rhamnitol), and onions (N-acetyl-S-(1Z)-propenyl-cysteine-sulfoxide) that can be used to enhance dietary assessment and assess adherence to diet. As part of the strategy, we introduce a new probabilistic statistical spectroscopy tool, RED-STORM (Resolution EnhanceD SubseT Optimization by Reference Matching), that uses 2D J-resolved 1H NMR spectra for enhanced information recovery using the Bayesian paradigm to extract a subset of spectra with similar spectral signatures to a reference. RED-STORM provided new information for subsequent experiments (e.g., 2D-NMR spectroscopy, solid-phase extraction, liquid chromatography prefaced mass spectrometry) used to ultimately identify an unknown compound. In summary, we illustrate the benefit of acquiring J-resolved experiments alongside conventional 1D 1H NMR as part of routine metabolic profiling in large data sets and show that application of complementary statistical and analytical techniques for the identification of unknown metabolites can be used to save valuable time and resources.

Background: Short-chain fatty acids (SCFAs), metabolites produced through the microbial fermentation of nondigestible dietary components, have key roles in energy homeostasis. Animal research suggests that colon-derived SCFAs modulate feeding behavior via central mechanisms. In humans, increased colonic production of the SCFA propionate acutely reduces energy intake. However, evidence of an effect of colonic propionate on the human brain or reward-based eating behavior is currently unavailable. Objectives: We investigated the effect of increased colonic propionate production on brain anticipatory reward responses during food picture evaluation. We hypothesized that elevated colonic propionate would reduce both reward responses and ad libitum energy intake via stimulation of anorexigenic gut hormone secretion. Design: In a randomized crossover design, 20 healthy nonobese men completed a functional magnetic resonance imaging (fMRI) food picture evaluation task after consumption of control inulin or inulin-propionate ester, a unique dietary compound that selectively augments colonic propionate production. The blood oxygen level–dependent (BOLD) signal was measured in a priori brain regions involved in reward processing, including the caudate, nucleus accumbens, amygdala, anterior insula, and orbitofrontal cortex (n = 18 had analyzable fMRI data). Results: Increasing colonic propionate production reduced BOLD signal during food picture evaluation in the caudate and nucleus accumbens. In the caudate, the reduction in BOLD signal was driven specifically by a lowering of the response to high-energy food. These central effects were partnered with a decrease in subjective appeal of high-energy food pictures and reduced energy intake during an ad libitum meal. These observations were not related to changes in blood peptide YY (PYY), glucagon-like peptide 1 (GLP-1), glucose, or insulin concentrations. Conclusion: Our results suggest that colonic propionate production may play an important role in attenuating reward-based eating behavior via striatal pathways, independent of changes in plasma PYY and GLP-1. This trial was registered at clinicaltrials.gov as NCT00750438.

Background: The appetite-regulating effects of non-digestible carbohydrates (NDC) have in part previously been attributed to their effects on intestinal transit rates as well as microbial production of short chain fatty acids (SCFA). Increased colonic production of the SCFA propionate has been shown to reduce energy intake and stimulate gut hormone secretion acutely in humans.\ud \ud Objective: We investigated the effect of the propiogenic NDC, L-rhamnose, on gastrointestinal transit times using a combined 13CO2/H2 breath test. We hypothesised that L-rhamnose would increase plasma propionate leading to a reduction in appetite, independent of changes in gastrointestinal transit times.\ud \ud Design: We used a dual 13C octanoic acid/lactose 13C-ureide breath test combined with breath H2 to measure intestinal transit times following the consumption of 25g/d L-rhamnose, compared with inulin and cellulose, in 10 healthy humans in a randomised cross-over pilot study. Gastric emptying (GE) and oro-caecal transit times (OCTT) were derived from the breath 13C data and compared with breath H2. Plasma SCFA and peptide YY (PYY) were also measured alongside subjective measures of appetite.\ud \ud Results: L-rhamnose significantly slowed GE rates (by 19.5min) but there was no difference in OCTT between treatments. However, breath H2 indicated fermentation of L-rhamnose before it reached the caecum. OCTT was highly correlated with breath H2 for inulin but not for L-rhamnose or cellulose. L-rhamnose consumption significantly increased plasma propionate and PYY but did not significantly reduce subjective appetite measures.\ud \ud Conclusions: The NDCs tested had a minimal effect on intestinal transit time. Our data suggest that L-rhamnose is partially fermented in the small intestine and that breath H2 reflects the site of gastrointestinal fermentation and is only a reliable marker of OCTT for certain NDCs (e.g. inulin). Future studies should focus on investigating the appetite-suppressing potential of L-rhamnose and verifying the findings in a larger cohort.

Metabolism is altered by genetics, diet, disease status, environment, and many other factors. Modeling either one of these is often done without considering the effects of the other covariates. Attributing differences in metabolic profile to one of these factors needs to be done while controlling for the metabolic influence of the rest. We describe here a data analysis framework and novel confounder-adjustment algorithm for multivariate analysis of metabolic profiling data. Using simulated data, we show that similar numbers of true associations and significantly less false positives are found compared to other commonly used methods. Covariate-adjusted projections to latent structures (CA-PLS) are exemplified here using a large-scale metabolic phenotyping study of two Chinese populations at different risks for cardiovascular disease. Using CA-PLS, we find that some previously reported differences are actually associated with external factors and discover a number of previously unreported biomarkers linked to different metabolic pathways. CA-PLS can be applied to any multivariate data where confounding may be an issue and the confounder-adjustment procedure is translatable to other multivariate regression techniques.