A 4D view on mRNA

Imaging single molecules in live cells in 4+ D (space, time and colors) is crucial for studying various biological processes, especially for observing the behavior of RNA molecules within the nuclear landscape [1]. RNA molecules are known to serve a multitude of tasks such as being templates for protein translation or to act as enzymes for regulating countless reactions in the nucleus [1]. Studying RNA kinetics in living cells can provide new information on RNA function or even human diseases, for instance caused by viruses such as the human immunodeficiency virus (HIV) [2]. A challenge to imaging nuclear RNA function is that the nucleus as a whole undergoes major reformation during the cell cycle [1] but the time required to step through the sample limits the capability to image large numbers of rapidly moving particles in a 3D space

Associations between Aquaglyceroporin Gene Polymorphisms and Risk of Stroke among Patients with Hypertension

Background: Dysregulations ofAQP7andAQP9were found to be related to lipid metabolism abnormality, which had been provento be one of the mechanisms of stroke. However, limited epidemiological studies explore the associations betweenAQP7andAQP9and the risk of stroke among patients with hypertension in China. Aims: We aimed to investigate the associations between genetic variants in AQP7andAQP9and the risk of stroke among patients with hypertension, as well as to explore gene-gene andgene-environment interactions. Methods: Baseline blood samples were drawn from 211 cases with stroke and 633 matched controls. Genomic DNA was extracted by a commercially available kit. Genotyping of 5 single nucleotide polymorphisms (SNPs) in AQP7 (rs2989924, rs3758269, and rs2542743) and AQP9 (rs57139208, rs16939881) was performed by the polymerase chain reaction assay with TaqMan probes. Results: Participants with the rs2989924 GG genotype were found to be with a 1.74-fold increased risk of stroke compared to those with the AA+AG genotype, and this association remained significant after adjustment for potential confounders (odds ratio (OR): 1.74, 95% confidence interval (CI): 1.23-2.46). The SNP rs3758269 CC+TT genotype was found to be with a 33% decreased risk of stroke after multivariate adjustment (OR: 0.67, 95% CI: 0.45-0.99) compared to the rs3758269 CC genotype. The significantly increased risk of stroke was prominent among males, patients aged 60 or above, and participants who were overweight and with a harbored genetic variant in SNP rs2989924. After adjusting potential confounders, the SNP rs3758269 CT+TT genotype was found to be significantly associated with a decreased risk of stroke compared to the CC genotype among participants younger than 60 years old or overweight. No statistically significant associations were observed between genotypes of rs2542743, rs57139208, or rs16939881 with the risk of stroke. Neither interactions nor linkage disequilibrium had been observed in this study. Conclusions: This study suggests that SNPs rs2989924 and rs3758269 are associated with the risk of stroke among patients with hypertension, while there were no statistically significant associations between rs2542743, rs57139208, and rs16939881 and the risk of stroke being observed

Airline Network Choice and Configuration

As an increasing number of countries liberalize their skies, some airlines, notably carriers in the Middle East, have been able to extend their hub-and-spoke networks beyond domestic borders. This allows them to serve international destinations without going through traditional gateway hubs, so that they can compete with airline alliances relying on the traditional dual-gateway, or the so-called “dog-bone” networks. This paper proposes a stochastic model to investigate the competition between airlines running traditional dog-bone and hub-and-spoke networks in a liberalizing inter-continental market. The proposed model considers the interactions among three types of stakeholders, namely a regulator that aims to maximize the expected social welfare by designating the locations of new gateways; airlines that maximize profits by optimizing the service offerings and airfares; passengers that minimize their own travel disutility. Such a model is applied to analyze the Europe - China aviation market, so that the comparative advantages of different networks can be examined and quantified. The modeling results provide evidence-based recommendations on airline competition and airport development, and infrastructure investment needs in markets being liberlized

Rank Intraclass Correlation for Clustered Data

Clustered data are common in biomedical research. Observations in the same cluster are often more similar to each other than to observations from other clusters. The intraclass correlation coefficient (ICC), first introduced by R. A. Fisher, is frequently used to measure this degree of similarity. However, the ICC is sensitive to extreme values and skewed distributions, and depends on the scale of the data. It is also not applicable to ordered categorical data. We define the rank ICC as a natural extension of Fisher's ICC to the rank scale, and describe its corresponding population parameter. The rank ICC is simply interpreted as the rank correlation between a random pair of observations from the same cluster. We also extend the definition when the underlying distribution has more than two hierarchies. We describe estimation and inference procedures, show the asymptotic properties of our estimator, conduct simulations to evaluate its performance, and illustrate our method in three real data examples with skewed data, count data, and three-level ordered categorical data

catena-Poly[[bis­[2-(2-pyrid­yl)-1-H-imidazole-κ2 N 2,N 3]cadmium]-μ-benzene-1,3-dicarboxyl­ato-κ2 O 1:O 3]

In the title coordinaltion polymer, [Cd(C8H4O4)(C8H7N3)2]n, the CdII atom, lying on a twofold rotation axis, is six-coordinated by two carboxyl­ate O atoms from two benzene-1,3-dicarboxyl­ate (m-BDC) ligands and four N atoms from two chelating 2-(2-pyrid­yl)imidazole mol­ecules, forming a slightly distorted octa­hedral geometry. The m-BDC ligand is located over a twofold rotation axis. The CdII atoms are bridged by the m-BDC ligands, leading to a wave-shaped chain structure along [010]. N—H⋯O hydrogen bonds connect the chains

The prediction of interferon treatment effects based on time series microarray gene expression profiles

<p>Abstract</p> <p>Background</p> <p>The status of a disease can be reflected by specific transcriptional profiles resulting from the induction or repression activity of a number of genes. Here, we proposed a time-dependent diagnostic model to predict the treatment effects of interferon and ribavirin to HCV infected patients by using time series microarray gene expression profiles of a published study.</p> <p>Methods</p> <p>In the published study, 33 African-American (AA) and 36 Caucasian American (CA) patients with chronic HCV genotype 1 infection received pegylated interferon and ribavirin therapy for 28 days. HG-U133A GeneChip containing 22283 probes was used to analyze the global gene expression in peripheral blood mononuclear cells (PBMC) of all the patients on day 0 (pretreatment), 1, 2, 7, 14, and 28. According to the decrease of HCV RNA levels on day 28, two categories of responses were defined: good and poor. A voting method based on Student's t test, Wilcoxon test, empirical Bayes test and significance analysis of microarray was used to identify differentially expressed genes. A time-dependent diagnostic model based on C4.5 decision tree was constructed to predict the treatment outcome. This model not only utilized the gene expression profiles before the treatment, but also during the treatment. Leave-one-out cross validation was used to evaluate the performance of the model.</p> <p>Results</p> <p>The model could correctly predict all Caucasian American patients' treatment effects at very early time point. The prediction accuracy of African-American patients achieved 85.7%. In addition, thirty potential biomarkers which may play important roles in response to interferon and ribavirin were identified.</p> <p>Conclusion</p> <p>Our method provides a way of using time series gene expression profiling to predict the treatment effect of pegylated interferon and ribavirin therapy on HCV infected patients. Similar experimental and bioinformatical strategies may be used to improve treatment decisions for other chronic diseases.</p

Proteomic analysis of swine serum following highly virulent classical swine fever virus infection

<p>Abstract</p> <p>Background</p> <p>Classical swine fever virus (CSFV) belongs to the genus <it>Pestivirus </it>within the family <it>Flaviviridae</it>. Virulent strains of classical swine fever virus (CSFV) cause severe disease in pigs characterized by immunosuppression, thrombocytopenia and disseminated intravascular coagulation, which causes significant economic losses to the pig industry worldwide.</p> <p>Methods</p> <p>To reveal proteomic changes in swine serum during the acute stage of lethal CSFV infection, 5 of 10 pigs were inoculated with the virulent CSFV Shimen strain, the remainder serving as uninfected controls. A serum sample was taken at 3 days post-infection from each swine, at a stage when there were no clinical symptoms other than increased rectal temperatures (≥40°C). The samples were treated to remove serum albumin and immunoglobulin (IgG), and then subjected to two-dimension differential gel electrophoresis.</p> <p>Results</p> <p>Quantitative intensity analysis revealed 17 protein spots showing at least 1.5-fold quantitative alteration in expression. Ten spots were successfully identified by MALDI-TOF MS or LTQ MS. Expression of 4 proteins was increased and 6 decreased in CSFV-infected pigs. Functions of these proteins included blood coagulation, anti-inflammatory activity and angiogenesis.</p> <p>Conclusion</p> <p>These proteins with altered expression may have important implications in the pathogenesis of classical swine fever and provide a clue for identification of biomarkers for classical swine fever early diagnosis.</p