Impact of a Pandemic on Attitudes towards Immigrants

Immigration control is an issue that figures prominently in public policy discussions and election campaigns throughout the world. Immigrants can be perceived as posing both realistic and symbolic threats to the host society. During the current global pandemic, these threats are amplified. This research investigated how attitudes towards immigrants were likely to be more negative when the impact of the pandemic was made salient. Based on intergroup threat theory (Rios et al., 2018) and uncertainty identity theory (Hogg, 2021a), two empirical studies investigated the effect of realistic and symbolic threats from the COVID-19 pandemic on people’s attitudes towards immigrants. Study 1 (N =303) tested if priming pandemic induced symbolic threats increased social identity uncertainty and found that pandemic-related symbolic but not realistic threats increased social identity uncertainty. Study 2 (N =363) again primed the two types of threat induced by the pandemic, measured their effects on attitudes towards immigrants, and examined if the effects could be explained by social identity uncertainty and collective angst. Results showed that people who perceived more COVID-19 related symbolic threat than COVID-19 related realistic threat experienced more COVID-19 related national identity uncertainty and collective angst, which predicted less positive attitudes towards immigrants. People who perceived more COVID-19 related realistic threat than COVID-19 related symbolic threat experienced less COVID-19 specific national identity uncertainty and collective angst, which predicted their more positive attitudes towards immigrants

Hormonal Regulation of Cholesterol Homeostasis

Cholesterol homeostasis is tightly regulated by a group of endocrine hormones under physiological conditions. Hormonal dysregulation is often associated with disturbed cholesterol homeostasis, resulting in many clinical disorders including atherosclerosis, fatty liver and metabolic syndrome. Circulating hormones regulate cholesterol metabolism by altering levels of relative genes either through their interactions with nuclear receptors or by interfering with bile acid signaling pathways. A better understanding of hormonal regulation of cholesterol metabolism would improve our likelihood of identifying effective and selective targets for the intervention of disturbed cholesterol. In this review, we discuss selected hormones critical for the cholesterol balance, including thyroid hormone, sex hormones, growth hormone, glucagon and irisin. We focus our discussion on the most recent advance in clinical epidemiology, animal mechanistic studies and the clinical application

Methods for Comparing a DNA Sequence with a Protein Sequence

We describe two methods for constructing an optimal global alignment of, and an optimal local alignment between, a DNA sequence and a protein sequence. The alignment model of the methods addresses the problems of frameshifts and introns in the DNA sequence. The methods require computer memory proportional to the sequence lengths, so they can rigorously process very huge sequences. The simplified versions of the methods were implemented as computer programs named NAP and LAP. The experimental results demonstrate that the programs are sensitive and powerful tools for finding genes by DNA-protein sequence homology

Information retrieval of mass encrypted data over multimedia networking with N-level vector model-based relevancy ranking

With an explosive growth in the deployment of networked applications over the Internet, searching the encrypted information that the user needs becomes increasingly important. However, the information search precision is quite low when using Vector space model for mass information retrieval, because long documents having poor similarity values are poorly represented in the vector space model and the order in which the terms appear in the document is lost in the vector space representation with intuitive weighting. To address the problems, this study proposed an N-level vector model (NVM)-based relevancy ranking scheme with an introduction of a new formula of the term weighting, taking into account the location of the feature term in the document to describe the content of the document properly, investigated into ways of ranking the encrypted documents using the proposed scheme, and conducted realistic simulation of information retrieval of mass encrypted data over multimedia networking. Results indicated that the timing of the index building, the most costing part of the relevancy ranking scheme, increased with the increase in both the document size and the multimedia content of the document being searched, which is in agreement with the expected. Performance evaluation demonstrated that our specially designed NVM-based encrypted information retrieval system is effective in ranking the encrypted documents transmitted over multimedia networks with large recall ratio and great retrieval precision

Gene functional similarity search tool (GFSST)

BACKGROUND: With the completion of the genome sequences of human, mouse, and other species and the advent of high throughput functional genomic research technologies such as biomicroarray chips, more and more genes and their products have been discovered and their functions have begun to be understood. Increasing amounts of data about genes, gene products and their functions have been stored in databases. To facilitate selection of candidate genes for gene-disease research, genetic association studies, biomarker and drug target selection, and animal models of human diseases, it is essential to have search engines that can retrieve genes by their functions from proteome databases. In recent years, the development of Gene Ontology (GO) has established structured, controlled vocabularies describing gene functions, which makes it possible to develop novel tools to search genes by functional similarity. RESULTS: By using a statistical model to measure the functional similarity of genes based on the Gene Ontology directed acyclic graph, we developed a novel Gene Functional Similarity Search Tool (GFSST) to identify genes with related functions from annotated proteome databases. This search engine lets users design their search targets by gene functions. CONCLUSION: An implementation of GFSST which works on the UniProt (Universal Protein Resource) for the human and mouse proteomes is available at GFSST Web Server. GFSST provides functions not only for similar gene retrieval but also for gene search by one or more GO terms. This represents a powerful new approach for selecting similar genes and gene products from proteome databases according to their functions