How the mere desire for certainty can lead to a preference for men in authority (particularly among political liberals)

AbstractWomen are harmed by stereotypes about their fit for positions of authority and changing these stereotypes is not a simple task. As stereotypes have strong epistemic properties, individuals with a high need for cognitive closure (NCC; i.e., the desire for epistemic certainty) can be more likely to accept these stereotypes and, consequently, to prefer men in positions of authority. Consistent with the reactive liberal hypothesis, this effect could be actually more visible among individuals with both a high NCC and left‐wing political orientations. We supported these hypotheses in a series of three studies. In Study 1 (N = 217), we found that manipulated NCC predicted preference for men in authority through stereotypes of women as not being fit for authority in a measurement‐of‐mediation design. In Study 2 (N = 151), we supported this effect in a mediation‐as‐process design. In Study 3 (N = 391), we found the indirect NCC effect on preference for men in authority was more visible among political liberals. A major implication of this work is that ways of changing the effect of these stereotypes should take into account the NCC, but particularly among individuals with left‐wing beliefs

Different Thymosin Beta 4 Immunoreactivity in Foetal and Adult Gastrointestinal Tract

Background: Thymosin beta 4 (T beta(4)) is a member of beta-thymosins, a family of peptides that play essential roles in many cellular functions. A recent study from our group suggested a role for T beta(4) in the development of human salivary glands. The aim of this study was to analyze the expression of T beta(4) in the human gut during development, and in the adult. Methodology/Principal Findings: Immunolocalization of T beta(4) was studied in autoptic samples of tongue, oesophagus, stomach, ileum, colon, liver and pancreas obtained from two human foetuses and two adults. T beta(4) appeared unevenly distributed, with marked differences between foetuses and adults. In the stomach, superficial epithelium was positive in foetuses and negative in adults. Ileal enterocytes were strongly positive in the adult and weakly positive in the foetuses. An increase in reactivity for T beta(4) was observed in superficial colon epithelium of adults as compared with the foetuses. Striking differences were found between foetal and adult liver: the former showed a very low reactivity for T beta(4) while in the adult we observed a strong reactivity in the vast majority of the hepatocytes. A peculiar pattern was found in the pancreas, with the strongest reactivity observed in foetal and adult islet cells. Significance: Our data show a strong expression of T beta(4) in the human gut and in endocrine pancreas during development. The observed differential expression of T beta(4) suggests specific roles of the peptide in the gut of foetuses and adults. The observed heterogeneity of T beta(4) expression in the foetal life, ranging from a very rare detection in liver cells up to a diffuse reactivity in endocrine pancreas, should be taken into account when the role of T beta(4) in the development of human embryo is assessed. Future studies are needed to shed light on the link between T beta(4) and organogenesis

Thymosin β 4 in colorectal cancer is localized predominantly at the invasion front in tumor cells undergoing epithelial mesenchymal transition.

Thymosin β 4 (Tβ(4)) is a ubiquitous peptide that plays pivotal roles in the cytoskeletal system and in cell differentiation during embryogenesis. Recently, a role for Tβ(4) has been proposed in experimental and human carcinogenesis. This study was aimed at evaluating the correlation between Tβ(4) immunoractivity and colorectal cancer, with particular attemption to tumor cells undergoing epithelial-mesenchymal transition.86 intestinal biopsies were retrospectively analyzed including 76 colorectal adenocarcinomas with evident features of epithelial-mesenchymal transition, and 10 samples of normal colorectal mucosa. Paraffin sections were immunostained for Tβ(4) and for E-cadherin. Total RNA was isolated from frozen specimens obtained, at surgery, from the normal colon mucosa, the deeper regions and the superficial tumor regions in four cases of colon cancer. Tβ(4) immunoreactivity was detected in the vast majority (59/76) of colon carcinomas, showing a patchy distribution, with well differentiated areas significantly more reactive than the less differentiated tumor zones. We also noted a zonal pattern in the majority of tumors, characterized by a progressive increase in immunostaining for Tβ(4) from the superficial toward the deepest tumor regions. The strongest expression for Tβ(4) was frequently detected in invading tumor cells with features of epithelial-mesenchymal transition. The increase in reactivity for Tβ(4) matched with a progressive decrease in E-cadherin expression in invading cancer cells. At mRNA level, the differences in Tβ(4) expression between the surrounding colon mucosa and the tumors samples were not significant.Our data show that Tβ(4) is expressed in the majority of colon cancers, with preferential immunoreactivity in deep tumor regions. The preferential expression of the peptide and the increase in intensity of the immunostaining at the invasion front suggests a possible link between the peptide and the process of epithelial mesenchymal transition, suggesting a role for Tβ(4) in colorectal cancer invasion and metastasis

A Clinical Prognostic Model Based on Machine Learning from the Fondazione Italiana Linfomi (FIL) MCL0208 Phase III Trial

BACKGROUND Multicenter clinical trials are producing growing amounts of clinical data. Machine Learning (ML) might facilitate the discovery of novel tools for prognostication and disease-stratification. Taking advantage of a systematic collection of multiple variables, we developed a model derived from data collected on 300 patients with mantle cell lymphoma (MCL) from the Fondazione Italiana Linfomi-MCL0208 phase III trial (NCT02354313). METHODS We developed a score with a clustering algorithm applied to clinical variables. The candidate score was correlated to overall survival (OS) and validated in two independent data series from the European MCL Network (NCT00209222, NCT00209209); Results: Three groups of patients were significantly discriminated: Low, Intermediate (Int), and High risk (High). Seven discriminants were identified by a feature reduction approach: albumin, Ki-67, lactate dehydrogenase, lymphocytes, platelets, bone marrow infiltration, and B-symptoms. Accordingly, patients in the Int and High groups had shorter OS rates than those in the Low and Int groups, respectively (Int→Low, HR: 3.1, 95% CI: 1.0-9.6; High→Int, HR: 2.3, 95% CI: 1.5-4.7). Based on the 7 markers, we defined the engineered MCL international prognostic index (eMIPI), which was validated and confirmed in two independent cohorts; Conclusions: We developed and validated a ML-based prognostic model for MCL. Even when currently limited to baseline predictors, our approach has high scalability potential

A Clinical Prognostic Model Based on Machine Learning from the Fondazione Italiana Linfomi (FIL) MCL0208 Phase III Trial

SIMPLE SUMMARY: The interest in using Machine-Learning (ML) techniques in clinical research is growing. We applied ML to build up a novel prognostic model from patients affected with Mantle Cell Lymphoma (MCL) enrolled in a phase III open-labeled, randomized clinical trial from the Fondazione Italiana Linfomi (FIL)—MCL0208. This is the first application of ML in a prospective clinical trial on MCL lymphoma. We applied a novel ML pipeline to a large cohort of patients for which several clinical variables have been collected at baseline, and assessed their prognostic value based on overall survival. We validated it on two independent data series provided by European MCL Network. Due to its flexibility, we believe that ML would be of tremendous help in the development of a novel MCL prognostic score aimed at re-defining risk stratification. ABSTRACT: Background: Multicenter clinical trials are producing growing amounts of clinical data. Machine Learning (ML) might facilitate the discovery of novel tools for prognostication and disease-stratification. Taking advantage of a systematic collection of multiple variables, we developed a model derived from data collected on 300 patients with mantle cell lymphoma (MCL) from the Fondazione Italiana Linfomi-MCL0208 phase III trial (NCT02354313). Methods: We developed a score with a clustering algorithm applied to clinical variables. The candidate score was correlated to overall survival (OS) and validated in two independent data series from the European MCL Network (NCT00209222, NCT00209209); Results: Three groups of patients were significantly discriminated: Low, Intermediate (Int), and High risk (High). Seven discriminants were identified by a feature reduction approach: albumin, Ki-67, lactate dehydrogenase, lymphocytes, platelets, bone marrow infiltration, and B-symptoms. Accordingly, patients in the Int and High groups had shorter OS rates than those in the Low and Int groups, respectively (Int→Low, HR: 3.1, 95% CI: 1.0–9.6; High→Int, HR: 2.3, 95% CI: 1.5–4.7). Based on the 7 markers, we defined the engineered MCL international prognostic index (eMIPI), which was validated and confirmed in two independent cohorts; Conclusions: We developed and validated a ML-based prognostic model for MCL. Even when currently limited to baseline predictors, our approach has high scalability potential

Preliminary data on the microbial profile of dry and wet aged bovine meat obtained from different breeds in Sardinia

This study aimed to evaluate the influence of dry and wet aging on microbial profile and physicochemical characteristics of bovine loins obtained from four animals of two different breeds, namely two Friesian cull cows and two Sardo-Bruna bovines. During dry and wet aging aerobic colony count, Enterobacteriaceae, mesophilic lactic acid bacteria, Pseudomonas, molds and yeasts, Salmonella enterica, Listeria monocytogenes and Yersinia enterocolitica, pH and water activity (aw) were determined in meat samples collected from the internal part of the loins. Moreover, the microbial profile was determined with sponge samples taken from the surface of the meat cuts. Samples obtained from Friesian cows were analyzed starting from the first day of the aging period and after 7, 14, and 21 days. Samples obtained from the Sardo Bruna bovines were also analyzed after 28 and 35 days. Wet aging allowed better control of Pseudomonas spp. during storage that showed statistically lower levels (P>0.05) in wet-aged meats with respect to dry-aged meats during aging and particularly at the end of the period (P>0.01) in both cattle breeds. At the end of the experiment (21 days), aerobic colony count and Pseudomonas in Fresian cows’ dry-aged meats showed mean levels >8 log, while lactic acid bacteria mean counts >7 log were detected in wet-aged meats of both cattle breeds. In meats submitted to dry aging, pH was significantly higher (P<0.01) with respect to wet-aged meats at all analysis times and in both cattle breeds. Aw showed a stable trend during both dry and wet aging without significant differences. These preliminary results highlight the critical importance of the strict application of good hygiene practices during all stages of production of these particular cuts of meat intended for aging

Modulation of Genetic Associations with Serum Urate Levels by Body-Mass-Index in Humans

We tested for interactions between body mass index (BMI) and common genetic variants affecting serum urate levels, genome-wide, in up to 42569 participants. Both stratified genome-wide association (GWAS) analyses, in lean, overweight and obese individuals, and regression-type analyses in a non BMI-stratified overall sample were performed. The former did not uncover any novel locus with a major main effect, but supported modulation of effects for some known and potentially new urate loci. The latter highlighted a SNP at RBFOX3 reaching genome-wide significant level (effect size 0.014, 95% CI 0.008-0.02, P-inter= 2.6 x 10(-8)). Two top loci in interaction term analyses, RBFOX3 and ERO1LB-EDAR-ADD, also displayed suggestive differences in main effect size between the lean and obese strata. All top ranking loci for urate effect differences between BMI categories were novel and most had small magnitude but opposite direction effects between strata. They include the locus RBMS1-TANK (men, Pdifflean-overweight= 4.7 x 10(-8)), a region that has been associated with several obesity related traits, and TSPYL5 (men, Pdifflean-overweight= 9.1 x 10(-8)), regulating adipocytes-produced estradiol. The top-ranking known urate loci was ABCG2, the strongest known gout risk locus, with an effect halved in obese compared to lean men (Pdifflean-obese= 2 x 10(-4)). Finally, pathway analysis suggested a role for N-glycan biosynthesis as a prominent urate-associated pathway in the lean stratum. These results illustrate a potentially powerful way to monitor changes occurring in obesogenic environment.Peer reviewe