A more fine-grained measure towards animal welfare: a study with regards to gender differences in Spanish students

The environmental issue is nowadays taking more importance in the environmental awareness all around the world, and in this field, animal consideration is more and more spread. A highlighted part in globalisation is the animal welfare awareness. This article presents a study comparing attitudes towards animals among secondary and university students in reference to gender. It was carried out on 1394 Spanish participants from 11 to 26 years. The instrument used in the study is the reviewed version of the Animal Welfare Attitude Scale which was renamed as “Animal Welfare Attitude-Revised Scale” (AWA-R Scale), with a Cronbach a reliability value of 0.85. It is subdivided into four components namely C1: animal abuse for pleasure or due to ignorance; C2: leisure with animals; C3: farm animals; and C4: animal abandonment. These components have been deeply detailed by a confirmatory factor analysis (CFA), which highly contributes to define the position of participants for the different dimensions of animal welfare. It is concluded that significant differences exist between males’ and females’ attitudes in all components of the AWA-R Scale. It is also suggested that two social characteristics—people’s attitudes towards animals and towards environmental protection—are, at the very least, coexistent and may indeed be interdependent. These differences between gender in matters of socialisation could thus be reflected in environmental attitudes, and also in others related to them, i.e. animal welfare attitudes

Identification of retinoic acid-regulated nuclear matrix-associated protein as a novel regulator of gastric cancer

Background: Retinoic acid-regulated nuclear matrix-associated protein (RAMP) is a WD40 repeat-containing protein that is involved in various biological functions, but little is known about its role in human cancer. This study aims to delineate the oncogenic role of RAMP in gastric carcinogenesis

Helicobacter pylori Perturbs Iron Trafficking in the Epithelium to Grow on the Cell Surface

Helicobacter pylori (Hp) injects the CagA effector protein into host epithelial cells and induces growth factor-like signaling, perturbs cell-cell junctions, and alters host cell polarity. This enables Hp to grow as microcolonies adhered to the host cell surface even in conditions that do not support growth of free-swimming bacteria. We hypothesized that CagA alters host cell physiology to allow Hp to obtain specific nutrients from or across the epithelial barrier. Using a polarized epithelium model system, we find that isogenic ΔcagA mutants are defective in cell surface microcolony formation, but exogenous addition of iron to the apical medium partially rescues this defect, suggesting that one of CagA's effects on host cells is to facilitate iron acquisition from the host. Hp adhered to the apical epithelial surface increase basolateral uptake of transferrin and induce its transcytosis in a CagA-dependent manner. Both CagA and VacA contribute to the perturbation of transferrin recycling, since VacA is involved in apical mislocalization of the transferrin receptor to sites of bacterial attachment. To determine if the transferrin recycling pathway is involved in Hp colonization of the cell surface, we silenced transferrin receptor expression during infection. This resulted in a reduced ability of Hp to colonize the polarized epithelium. To test whether CagA is important in promoting iron acquisition in vivo, we compared colonization of Hp in iron-replete vs. iron-deficient Mongolian gerbils. While wild type Hp and ΔcagA mutants colonized iron-replete gerbils at similar levels, ΔcagA mutants are markedly impaired in colonizing iron-deficient gerbils. Our study indicates that CagA and VacA act in concert to usurp the polarized process of host cell iron uptake, allowing Hp to use the cell surface as a replicative niche

The rise of multiple imputation: a review of the reporting and implementation of the method in medical research

BACKGROUND: Missing data are common in medical research, which can lead to a loss in statistical power and potentially biased results if not handled appropriately. Multiple imputation (MI) is a statistical method, widely adopted in practice, for dealing with missing data. Many academic journals now emphasise the importance of reporting information regarding missing data and proposed guidelines for documenting the application of MI have been published. This review evaluated the reporting of missing data, the application of MI including the details provided regarding the imputation model, and the frequency of sensitivity analyses within the MI framework in medical research articles. METHODS: A systematic review of articles published in the Lancet and New England Journal of Medicine between January 2008 and December 2013 in which MI was implemented was carried out. RESULTS: We identified 103 papers that used MI, with the number of papers increasing from 11 in 2008 to 26 in 2013. Nearly half of the papers specified the proportion of complete cases or the proportion with missing data by each variable. In the majority of the articles (86%) the imputed variables were specified. Of the 38 papers (37%) that stated the method of imputation, 20 used chained equations, 8 used multivariate normal imputation, and 10 used alternative methods. Very few articles (9%) detailed how they handled non-normally distributed variables during imputation. Thirty-nine papers (38%) stated the variables included in the imputation model. Less than half of the papers (46%) reported the number of imputations, and only two papers compared the distribution of imputed and observed data. Sixty-six papers presented the results from MI as a secondary analysis. Only three articles carried out a sensitivity analysis following MI to assess departures from the missing at random assumption, with details of the sensitivity analyses only provided by one article. CONCLUSIONS: This review outlined deficiencies in the documenting of missing data and the details provided about imputation. Furthermore, only a few articles performed sensitivity analyses following MI even though this is strongly recommended in guidelines. Authors are encouraged to follow the available guidelines and provide information on missing data and the imputation process. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12874-015-0022-1) contains supplementary material, which is available to authorized users