Assessing batch effects of genotype calling algorithm BRLMM for the Affymetrix GeneChip Human Mapping 500 K array set using 270 HapMap samples

<p>Abstract</p> <p>Background</p> <p>Genome-wide association studies (GWAS) aim to identify genetic variants (usually single nucleotide polymorphisms [SNPs]) across the entire human genome that are associated with phenotypic traits such as disease status and drug response. Highly accurate and reproducible genotype calling are paramount since errors introduced by calling algorithms can lead to inflation of false associations between genotype and phenotype. Most genotype calling algorithms currently used for GWAS are based on multiple arrays. Because hundreds of gigabytes (GB) of raw data are generated from a GWAS, the samples are typically partitioned into batches containing subsets of the entire dataset for genotype calling. High call rates and accuracies have been achieved. However, the effects of batch size (i.e., number of chips analyzed together) and of batch composition (i.e., the choice of chips in a batch) on call rate and accuracy as well as the propagation of the effects into significantly associated SNPs identified have not been investigated. In this paper, we analyzed both the batch size and batch composition for effects on the genotype calling algorithm BRLMM using raw data of 270 HapMap samples analyzed with the Affymetrix Human Mapping 500 K array set.</p> <p>Results</p> <p>Using data from 270 HapMap samples interrogated with the Affymetrix Human Mapping 500 K array set, three different batch sizes and three different batch compositions were used for genotyping using the BRLMM algorithm. Comparative analysis of the calling results and the corresponding lists of significant SNPs identified through association analysis revealed that both batch size and composition affected genotype calling results and significantly associated SNPs. Batch size and batch composition effects were more severe on samples and SNPs with lower call rates than ones with higher call rates, and on heterozygous genotype calls compared to homozygous genotype calls.</p> <p>Conclusion</p> <p>Batch size and composition affect the genotype calling results in GWAS using BRLMM. The larger the differences in batch sizes, the larger the effect. The more homogenous the samples in the batches, the more consistent the genotype calls. The inconsistency propagates to the lists of significantly associated SNPs identified in downstream association analysis. Thus, uniform and large batch sizes should be used to make genotype calls for GWAS. In addition, samples of high homogeneity should be placed into the same batch.</p

Very Important Pool (VIP) genes – an application for microarray-based molecular signatures

<p>Abstract</p> <p>Background</p> <p>Advances in DNA microarray technology portend that molecular signatures from which microarray will eventually be used in clinical environments and personalized medicine. Derivation of biomarkers is a large step beyond hypothesis generation and imposes considerably more stringency for accuracy in identifying informative gene subsets to differentiate phenotypes. The inherent nature of microarray data, with fewer samples and replicates compared to the large number of genes, requires identifying informative genes prior to classifier construction. However, improving the ability to identify differentiating genes remains a challenge in bioinformatics.</p> <p>Results</p> <p>A new hybrid gene selection approach was investigated and tested with nine publicly available microarray datasets. The new method identifies a Very Important Pool (VIP) of genes from the broad patterns of gene expression data. The method uses a bagging sampling principle, where the re-sampled arrays are used to identify the most informative genes. Frequency of selection is used in a repetitive process to identify the VIP genes. The putative informative genes are selected using two methods, t-statistic and discriminatory analysis. In the t-statistic, the informative genes are identified based on p-values. In the discriminatory analysis, disjoint Principal Component Analyses (PCAs) are conducted for each class of samples, and genes with high discrimination power (DP) are identified. The VIP gene selection approach was compared with the p-value ranking approach. The genes identified by the VIP method but not by the p-value ranking approach are also related to the disease investigated. More importantly, these genes are part of the pathways derived from the common genes shared by both the VIP and p-ranking methods. Moreover, the binary classifiers built from these genes are statistically equivalent to those built from the top 50 p-value ranked genes in distinguishing different types of samples.</p> <p>Conclusion</p> <p>The VIP gene selection approach could identify additional subsets of informative genes that would not always be selected by the p-value ranking method. These genes are likely to be additional true positives since they are a part of pathways identified by the p-value ranking method and expected to be related to the relevant biology. Therefore, these additional genes derived from the VIP method potentially provide valuable biological insights.</p

Nuclear Factor-Kappa B Family Member RelB Inhibits Human Immunodeficiency Virus-1 Tat-Induced Tumor Necrosis Factor-Alpha Production

Human Immunodeficiency Virus-1 (HIV-1)-associated neurocognitive disorder (HAND) is likely neuroinflammatory in origin, believed to be triggered by inflammatory and oxidative stress responses to cytokines and HIV protein gene products such as the HIV transactivator of transcription (Tat). Here we demonstrate increased messenger RNA for nuclear factor-kappa B (NF-κB) family member, transcription factor RelB, in the brain of doxycycline-induced Tat transgenic mice, and increased RelB synthesis in Tat-exposed microglial cells. Since genetic ablation of RelB in mice leads to multi-organ inflammation, we hypothesized that Tat-induced, newly synthesized RelB inhibits cytokine production by microglial cells, possibly through the formation of transcriptionally inactive RelB/RelA complexes. Indeed, tumor necrosis factor-alpha (TNFα) production in monocytes isolated from RelB deficient mice was significantly higher than in monocytes isolated from RelB expressing controls. Moreover, RelB overexpression in microglial cells inhibited Tat-induced TNFα synthesis in a manner that involved transcriptional repression of the TNFα promoter, and increased phosphorylation of RelA at serine 276, a prerequisite for increased RelB/RelA protein interactions. The Rel-homology-domain within RelB was necessary for this interaction. Overexpression of RelA itself, in turn, significantly increased TNFα promoter activity, an effect that was completely blocked by RelB overexpression. We conclude that RelB regulates TNFα cytokine synthesis by competitive interference binding with RelA, which leads to downregulation of TNFα production. Moreover, because Tat activates both RelB and TNFα in microglia, and because Tat induces inflammatory TNFα synthesis via NF-κB, we posit that RelB serves as a cryoprotective, anti-inflammatory, counter-regulatory mechanism for pathogenic NF-κB activation. These findings identify a novel regulatory pathway for controlling HIV-induced microglial activation and cytokine production that may have important therapeutic implications for the management of HAND

Review of advanced road materials, structures, equipment, and detection technologies

As a vital and integral component of transportation infrastructure, pavement has a direct and tangible impact on socio-economic sustainability. In recent years, an influx of groundbreaking and state-of-the-art materials, structures, equipment, and detection technologies related to road engineering have continually and progressively emerged, reshaping the landscape of pavement systems. There is a pressing and growing need for a timely summarization of the current research status and a clear identification of future research directions in these advanced and evolving technologies. Therefore, Journal of Road Engineering has undertaken the significant initiative of introducing a comprehensive review paper with the overarching theme of “advanced road materials, structures, equipment, and detection technologies”. This extensive and insightful review meticulously gathers and synthesizes research findings from 39 distinguished scholars, all of whom are affiliated with 19 renowned universities or research institutions specializing in the diverse and multidimensional field of highway engineering. It covers the current state and anticipates future development directions in the four major and interconnected domains of road engineering: advanced road materials, advanced road structures and performance evaluation, advanced road construction equipment and technology, and advanced road detection and assessment technologies

Predictors of Disclosing Sexual Orientation to Parents, Classmates, and School Adults among Latinx Sexual Minority High School and College Youth

The current study examined predictors associated with the degree of sexual orientation disclosure across social contexts (parents, classmates, and school adults) and educational context (high school and college) among Latinx sexual minority youth (SMY; N = 238). Results revealed that perceptions of more supportive social attitudes to sexual minority communities were associated with higher levels of sexual orientation disclosure across social contexts, including parents, classmates, and school adults. Compared to monosexual Latinx SMY, plurisexual Latinx SMY reported lower levels of sexual orientation disclosure to parents and school adults but not to classmates. Sexual orientation identity centrality was only associated with sexual orientation disclosure to parents but not to classmates or school adults. Degree of romantic attraction to the same gender was not associated with sexual orientation disclosure. Findings provide preliminary support for critical nuances in sexual orientation disclosure across social and educational contexts among Latinx SMY. </jats:p

Spectrum sharing for secrecy performance enhancement in D2D-enabled UAV networks

Abstract With the assistance of device-to-device (D2D) communications, unmanned aerial vehicle (UAV) networks are anticipated to support widespread applications in fifth generation (5G) and beyond wireless systems, by providing seamless coverage, flexible deployment, and high channel rate. However, the networks face significant security threats from malicious eavesdroppers due to the inherent broadcast and openness nature of wireless channels. To ensure secure communications of such networks, physical layer security is a promising technique, which utilizes the randomness and noise of wireless channels to enhance secrecy performance. This article investigates physical layer security performance via spectrum sharing in D2D-enabled UAV networks. We first present two typical network architectures where each UAV serves as either a flying base station or an aerial user equipment. Then, we propose a spectrum sharing strategy to fully exploit interference incurred by spectrum reuse for improving secrecy performance. We further conduct two case studies to evaluate the spectrum sharing strategy in these two typical network architectures, and also show secrecy performance gains compared to traditional spectrum sharing strategy. Finally, we discuss some future research directions in D2D-enabled UAV networks

Seasonal variations in acute diverticular disease hospitalisations in New Zealand

Abstract Purpose Seasonal variation of acute diverticular disease is variably reported in observational studies. This study aimed to describe seasonal variation of acute diverticular disease hospital admissions in New Zealand. Methods A time series analysis of national diverticular disease hospitalisations from 2000 to 2015 was conducted among adults aged 30 years or over. Monthly counts of acute hospitalisations’ primary diagnosis of diverticular disease were decomposed using Census X-11 times series methods. A combined test for the presence of identifiable seasonality was used to determine if overall seasonality was present; thereafter, annual seasonal amplitude was calculated. The mean seasonal amplitude of demographic groups was compared by analysis of variance. Results Over the 16-year period, 35,582 hospital admissions with acute diverticular disease were included. Seasonality in monthly acute diverticular disease admissions was identified. The mean monthly seasonal component of acute diverticular disease admissions peaked in early-autumn (March) and troughed in early-spring (September). The mean annual seasonal amplitude was 23%, suggesting on average 23% higher acute diverticular disease hospitalisations during early-autumn (March) than in early-spring (September). The results were similar in sensitivity analyses that employed different definitions of diverticular disease. Seasonal variation was less pronounced in patients aged over 80 (p = 0.002). Seasonal variation was significantly greater among Māori than Europeans (p &lt; 0.001) and in more southern regions (p &lt; 0.001). However, seasonal variations were not significantly different by gender. Conclusions Acute diverticular disease admissions in New Zealand exhibit seasonal variation with a peak in Autumn (March) and a trough in Spring (September). Significant seasonal variations are associated with ethnicity, age, and region, but not with gender. </jats:sec