Vaccinia Scars Associated with Improved Survival among Adults in Rural Guinea-Bissau

BACKGROUND: In urban Guinea-Bissau, adults with a vaccinia scar had better survival but also a higher prevalence of HIV-2 infection. We therefore investigated the association between vaccinia scar and survival and HIV infection in a rural area of Guinea-Bissau. METHODOLOGY/PRINCIPAL FINDINGS: In connection with a study of HIV in rural Guinea-Bissau, we assessed vaccinia and BCG scars in 193 HIV-1 or HIV-2 infected and 174 uninfected participants. Mortality was assessed after 2½–3 years of follow-up. The analyses were adjusted for age, sex, village, and HIV status. The prevalence of vaccinia scar was associated with age, village, and HIV-2 status but not with sex and schooling. Compared with individuals without any scar, individuals with a vaccinia scar had better survival (mortality rate ratio (MR) = 0.22 (95% CI 0.08–0.61)), the MR being 0.19 (95% CI 0.06–0.57) for women and 0.40 (95% CI 0.04–3.74) for men. Estimates were similar for HIV-2 infected and HIV-1 and HIV-2 uninfected individuals. The HIV-2 prevalence was higher among individuals with a vaccinia scar compared to individuals without a vaccinia scar (RR = 1.57 (95% CI 1.02–2.36)). CONCLUSION: The present study supports the hypothesis that vaccinia vaccination may have a non-specific beneficial effect on adult survival

Misty Mountain clustering: application to fast unsupervised flow cytometry gating

<p>Abstract</p> <p>Background</p> <p>There are many important clustering questions in computational biology for which no satisfactory method exists. Automated clustering algorithms, when applied to large, multidimensional datasets, such as flow cytometry data, prove unsatisfactory in terms of speed, problems with local minima or cluster shape bias. Model-based approaches are restricted by the assumptions of the fitting functions. Furthermore, model based clustering requires serial clustering for all cluster numbers within a user defined interval. The final cluster number is then selected by various criteria. These supervised serial clustering methods are time consuming and frequently different criteria result in different optimal cluster numbers. Various unsupervised heuristic approaches that have been developed such as affinity propagation are too expensive to be applied to datasets on the order of 10⁶points that are often generated by high throughput experiments.</p> <p>Results</p> <p>To circumvent these limitations, we developed a new, unsupervised density contour clustering algorithm, called Misty Mountain, that is based on percolation theory and that efficiently analyzes large data sets. The approach can be envisioned as a progressive top-down removal of clouds covering a data histogram relief map to identify clusters by the appearance of statistically distinct peaks and ridges. This is a parallel clustering method that finds every cluster after analyzing only once the cross sections of the histogram. The overall run time for the composite steps of the algorithm increases linearly by the number of data points. The clustering of 10⁶data points in 2D data space takes place within about 15 seconds on a standard laptop PC. Comparison of the performance of this algorithm with other state of the art automated flow cytometry gating methods indicate that Misty Mountain provides substantial improvements in both run time and in the accuracy of cluster assignment.</p> <p>Conclusions</p> <p>Misty Mountain is fast, unbiased for cluster shape, identifies stable clusters and is robust to noise. It provides a useful, general solution for multidimensional clustering problems. We demonstrate its suitability for automated gating of flow cytometry data.</p

Identification of gene co-regulatory modules and associated cis-elements involved in degenerative heart disease

<p>Abstract</p> <p>Background</p> <p>Cardiomyopathies, degenerative diseases of cardiac muscle, are among the leading causes of death in the developed world. Microarray studies of cardiomyopathies have identified up to several hundred genes that significantly alter their expression patterns as the disease progresses. However, the regulatory mechanisms driving these changes, in particular the networks of transcription factors involved, remain poorly understood. Our goals are (A) to identify modules of co-regulated genes that undergo similar changes in expression in various types of cardiomyopathies, and (B) to reveal the specific pattern of transcription factor binding sites, <it>cis</it>-elements, in the proximal promoter region of genes comprising such modules.</p> <p>Methods</p> <p>We analyzed 149 microarray samples from human hypertrophic and dilated cardiomyopathies of various etiologies. Hierarchical clustering and Gene Ontology annotations were applied to identify modules enriched in genes with highly correlated expression and a similar physiological function. To discover motifs that may underly changes in expression, we used the promoter regions for genes in three of the most interesting modules as input to motif discovery algorithms. The resulting motifs were used to construct a probabilistic model predictive of changes in expression across different cardiomyopathies.</p> <p>Results</p> <p>We found that three modules with the highest degree of functional enrichment contain genes involved in myocardial contraction (n = 9), energy generation (n = 20), or protein translation (n = 20). Using motif discovery tools revealed that genes in the contractile module were found to contain a TATA-box followed by a CACC-box, and are depleted in other GC-rich motifs; whereas genes in the translation module contain a pyrimidine-rich initiator, Elk-1, SP-1, and a novel motif with a GCGC core. Using a naïve Bayes classifier revealed that patterns of motifs are statistically predictive of expression patterns, with odds ratios of 2.7 (contractile), 1.9 (energy generation), and 5.5 (protein translation).</p> <p>Conclusion</p> <p>We identified patterns comprised of putative <it>cis</it>-regulatory motifs enriched in the upstream promoter sequence of genes that undergo similar changes in expression secondary to cardiomyopathies of various etiologies. Our analysis is a first step towards understanding transcription factor networks that are active in regulating gene expression during degenerative heart disease.</p

Geminivirus-Mediated Delivery of Florigen Promotes Determinate Growth in Aerial Organs and Uncouples Flowering from Photoperiod in Cotton

This article discusses geminivirus-mediated delivery of florigen. Florigen acts as a general growth hormone, advancing determinate growth. The findings extend our understanding of florigen as a general growth hormone and could benefit crop management techniques

Inflammatory Gene Regulatory Networks in Amnion Cells Following Cytokine Stimulation: Translational Systems Approach to Modeling Human Parturition

A majority of the studies examining the molecular regulation of human labor have been conducted using single gene approaches. While the technology to produce multi-dimensional datasets is readily available, the means for facile analysis of such data are limited. The objective of this study was to develop a systems approach to infer regulatory mechanisms governing global gene expression in cytokine-challenged cells in vitro, and to apply these methods to predict gene regulatory networks (GRNs) in intrauterine tissues during term parturition. To this end, microarray analysis was applied to human amnion mesenchymal cells (AMCs) stimulated with interleukin-1β, and differentially expressed transcripts were subjected to hierarchical clustering, temporal expression profiling, and motif enrichment analysis, from which a GRN was constructed. These methods were then applied to fetal membrane specimens collected in the absence or presence of spontaneous term labor. Analysis of cytokine-responsive genes in AMCs revealed a sterile immune response signature, with promoters enriched in response elements for several inflammation-associated transcription factors. In comparison to the fetal membrane dataset, there were 34 genes commonly upregulated, many of which were part of an acute inflammation gene expression signature. Binding motifs for nuclear factor-κB were prominent in the gene interaction and regulatory networks for both datasets; however, we found little evidence to support the utilization of pathogen-associated molecular pattern (PAMP) signaling. The tissue specimens were also enriched for transcripts governed by hypoxia-inducible factor. The approach presented here provides an uncomplicated means to infer global relationships among gene clusters involved in cellular responses to labor-associated signals

Hippocampal IGF-1 expression, neurogenesis and slowed aging: clues to longevity from mutant mice

Recent studies point out the important role of IGF and insulin-related signaling pathways in the control of longevity of laboratory animals. The Ames dwarf mouse is a murine model of circulating GH and IGF-1 deficiency that exhibits dwarf phenotype characteristics and significantly extends lifespan. It is interesting to know that Ames dwarf mice do not experience an age-related decline in cognitive function when compared to their young counterparts. In this study, the most recent works on local GH and IGF-1 expression in the hippocampus of Ames mice are briefly reviewed