Differential expression of microRNAs in bovine papillomavirus type 1 transformed equine cells

Bovine papillomavirus (BPV) types 1 and 2 play an important role in the pathogenesis of equine sarcoids (ES), the most common cutaneous tumour affecting horses. MicroRNAs (miRNAs), small non-coding RNAs that regulate essential biological and cellular processes, have been found dysregulated in a wide range of tumours. The aim of this study was to identify miRNAs associated with ES. Differential expression of miRNAs was assessed in control equine fibroblasts (EqPalFs) and EqPalFs transformed with the BPV-1 genome (S6-2 cells). Using a commercially available miRNA microarray, 492 mature miRNAs were interrogated. In total, 206 mature miRNAs were differentially expressed in EqPalFs compared with S6-2 cells. Aberrant expression of these miRNAs in S6-2 cells can be attributed to the presence of BPV-1 genomes. Furthermore, we confirm the presence of 124 miRNAs previously computationally predicted in the horse. Our data supports the involvement of miRNAs in the pathogenesis of ES

Individual Factors Affecting Entrepreneurship in Hispanics

A model of entrepreneurship (Baron & Henry, 2011) is used to understand and explain the factors related to the behaviors of Hispanic entrepreneurs. Testable hypotheses to guide future research are presented

Large-scale Nonlinear Variable Selection via Kernel Random Features

We propose a new method for input variable selection in nonlinear regression. The method is embedded into a kernel regression machine that can model general nonlinear functions, not being a priori limited to additive models. This is the first kernel-based variable selection method applicable to large datasets. It sidesteps the typical poor scaling properties of kernel methods by mapping the inputs into a relatively low-dimensional space of random features. The algorithm discovers the variables relevant for the regression task together with learning the prediction model through learning the appropriate nonlinear random feature maps. We demonstrate the outstanding performance of our method on a set of large-scale synthetic and real datasets.Comment: Final version for proceedings of ECML/PKDD 201

Influence of Raters’ Attributes on Biases Toward Immigrants

Although immigrants offer many benefits for organizations and our society, they continue to experience unfair discrimination, prejudice, and hostility in the employment process. One contributing factor towards the negative perceptions toward immigrants are the raters’ attributes (i.e., decision makers in the workplace). These attributes include their demographic background (e.g., age, gender), differences between raters’ and immigrants’ cultural values, raters’ personality, and raters’ previous contact with immigrants. In order to understand raters’ biases toward immigrants, we used the social cognition framework (Miller & Brewer, 1984) to explain the reasons for these biases, and offered hypotheses to guide future research on the issue