Simple acoustical technique for automated measurement of drift tube anode wire tension

We describe a simple and inexpensive acoustical technique that permits rapid, accurate and in-situ measurement of drift tube anode wire tensions even if the anode wire is electrically discontinuous.Comment: 5 text pages, 6 figures. fixed typo, minor content change in sec

Imaging X-Ray Polarimeter for Solar Flares (IXPS)

We describe the design of a balloon-borne Imaging X-ray Polarimeter for Solar flares (IX PS). This novel instrument, a Time Projection Chamber (TPC) for photoelectric polarimetry, will be capable of measuring polarization at the few percent level in the 20-50 keV energy range during an M- or X class flare, and will provide imaging information at the approx.10 arcsec level. The primary objective of such observations is to determine the directivity of nonthermal high-energy electrons producing solar hard X-rays, and hence to learn about the particle acceleration and energy release processes in solar flares. Secondary objectives include the separation of the thermal and nonthermal components of the flare X-ray emissions and the separation of photospheric albedo fluxes from direct emissions

A comparison of four clustering methods for brain expression microarray data

Background DNA microarrays, which determine the expression levels of tens of thousands of genes from a sample, are an important research tool. However, the volume of data they produce can be an obstacle to interpretation of the results. Clustering the genes on the basis of similarity of their expression profiles can simplify the data, and potentially provides an important source of biological inference, but these methods have not been tested systematically on datasets from complex human tissues. In this paper, four clustering methods, CRC, k-means, ISA and memISA, are used upon three brain expression datasets. The results are compared on speed, gene coverage and GO enrichment. The effects of combining the clusters produced by each method are also assessed. Results k-means outperforms the other methods, with 100% gene coverage and GO enrichments only slightly exceeded by memISA and ISA. Those two methods produce greater GO enrichments on the datasets used, but at the cost of much lower gene coverage, fewer clusters produced, and speed. The clusters they find are largely different to those produced by k-means. Combining clusters produced by k-means and memISA or ISA leads to increased GO enrichment and number of clusters produced (compared to k-means alone), without negatively impacting gene coverage. memISA can also find potentially disease-related clusters. In two independent dorsolateral prefrontal cortex datasets, it finds three overlapping clusters that are either enriched for genes associated with schizophrenia, genes differentially expressed in schizophrenia, or both. Two of these clusters are enriched for genes of the MAP kinase pathway, suggesting a possible role for this pathway in the aetiology of schizophrenia. Conclusion Considered alone, k-means clustering is the most effective of the four methods on typical microarray brain expression datasets. However, memISA and ISA can add extra high-quality clusters to the set produced by k-means, so combining these three methods is the method of choice

DAVID Bioinformatics Resources: expanded annotation database and novel algorithms to better extract biology from large gene lists

All tools in the DAVID Bioinformatics Resources aim to provide functional interpretation of large lists of genes derived from genomic studies. The newly updated DAVID Bioinformatics Resources consists of the DAVID Knowledgebase and five integrated, web-based functional annotation tool suites: the DAVID Gene Functional Classification Tool, the DAVID Functional Annotation Tool, the DAVID Gene ID Conversion Tool, the DAVID Gene Name Viewer and the DAVID NIAID Pathogen Genome Browser. The expanded DAVID Knowledgebase now integrates almost all major and well-known public bioinformatics resources centralized by the DAVID Gene Concept, a single-linkage method to agglomerate tens of millions of diverse gene/protein identifiers and annotation terms from a variety of public bioinformatics databases. For any uploaded gene list, the DAVID Resources now provides not only the typical gene-term enrichment analysis, but also new tools and functions that allow users to condense large gene lists into gene functional groups, convert between gene/protein identifiers, visualize many-genes-to-many-terms relationships, cluster redundant and heterogeneous terms into groups, search for interesting and related genes or terms, dynamically view genes from their lists on bio-pathways and more. With DAVID (http://david.niaid.nih.gov), investigators gain more power to interpret the biological mechanisms associated with large gene lists

Integrated Analysis of Multiple Microarray Datasets Identifies a Reproducible Survival Predictor in Ovarian Cancer

BACKGROUND: Public data integration may help overcome challenges in clinical implementation of microarray profiles. We integrated several ovarian cancer datasets to identify a reproducible predictor of survival. METHODOLOGY/PRINCIPAL FINDINGS: Four microarray datasets from different institutions comprising 265 advanced stage tumors were uniformly reprocessed into a single training dataset, also adjusting for inter-laboratory variation ("batch-effect"). Supervised principal component survival analysis was employed to identify prognostic models. Models were independently validated in a 61-patient cohort using a custom array genechip and a publicly available 229-array dataset. Molecular correspondence of high- and low-risk outcome groups between training and validation datasets was demonstrated using Subclass Mapping. Previously established molecular phenotypes in the 2(nd) validation set were correlated with high and low-risk outcome groups. Functional representational and pathway analysis was used to explore gene networks associated with high and low risk phenotypes. A 19-gene model showed optimal performance in the training set (median OS 31 and 78 months, p < 0.01), 1(st) validation set (median OS 32 months versus not-yet-reached, p = 0.026) and 2(nd) validation set (median OS 43 versus 61 months, p = 0.013) maintaining independent prognostic power in multivariate analysis. There was strong molecular correspondence of the respective high- and low-risk tumors between training and 1(st) validation set. Low and high-risk tumors were enriched for favorable and unfavorable molecular subtypes and pathways, previously defined in the public 2(nd) validation set. CONCLUSIONS/SIGNIFICANCE: Integration of previously generated cancer microarray datasets may lead to robust and widely applicable survival predictors. These predictors are not simply a compilation of prognostic genes but appear to track true molecular phenotypes of good- and poor-outcome

Gene expression analysis after receptor tyrosine kinase activation reveals new potential melanoma proteins

<p>Abstract</p> <p>Background</p> <p>Melanoma is an aggressive tumor with increasing incidence. To develop accurate prognostic markers and targeted therapies, changes leading to malignant transformation of melanocytes need to be understood. In the <it>Xiphophorus </it>melanoma model system, a mutated version of the EGF receptor Xmrk (<it>Xiphophorus </it>melanoma receptor kinase) triggers melanomagenesis. Cellular events downstream of Xmrk, such as the activation of Akt, Ras, B-Raf or Stat5, were also shown to play a role in human melanomagenesis. This makes the elucidation of Xmrk downstream targets a useful method for identifying processes involved in melanoma formation.</p> <p>Methods</p> <p>Here, we analyzed Xmrk-induced gene expression using a microarray approach. Several highly expressed genes were confirmed by realtime PCR, and pathways responsible for their induction were revealed using small molecule inhibitors. The expression of these genes was also monitored in human melanoma cell lines, and the target gene <it>FOSL1 </it>was knocked down by siRNA. Proliferation and migration of siRNA-treated melanoma cell lines were then investigated.</p> <p>Results</p> <p>Genes with the strongest upregulation after receptor activation were FOS-like antigen 1 (<it>Fosl1</it>), early growth response 1 (<it>Egr1</it>), osteopontin (<it>Opn</it>), insulin-like growth factor binding protein 3 (<it>Igfbp3</it>), dual-specificity phosphatase 4 (<it>Dusp4</it>), and tumor-associated antigen L6 (<it>Taal6</it>). Interestingly, most genes were blocked in presence of a SRC kinase inhibitor. Importantly, we found that <it>FOSL1</it>, <it>OPN</it>, <it>IGFBP3</it>, <it>DUSP4</it>, and <it>TAAL6 </it>also exhibited increased expression levels in human melanoma cell lines compared to human melanocytes. Knockdown of <it>FOSL1 </it>in human melanoma cell lines reduced their proliferation and migration.</p> <p>Conclusion</p> <p>Altogether, the data show that the receptor tyrosine kinase Xmrk is a useful tool in the identification of target genes that are commonly expressed in Xmrk-transgenic melanocytes and melanoma cell lines. The identified molecules constitute new possible molecular players in melanoma development. Specifically, a role of FOSL1 in melanomagenic processes is demonstrated. These data are the basis for future detailed analyses of the investigated target genes.</p

Functional Conservation of DNA Methylation in the Pea Aphid and the Honeybee

DNA methylation is a fundamental epigenetic mark known to have wide-ranging effects on gene regulation in a variety of animal taxa. Comparative genomic analyses can help elucidate the function of DNA methylation by identifying conserved features of methylated genes and other genomic regions. In this study, we used computational approaches to distinguish genes marked by heavy methylation from those marked by little or no methylation in the pea aphid, Acyrthosiphon pisum. We investigated if these two classes had distinct evolutionary histories and functional roles by conducting comparative analysis with the honeybee, Apis (Ap.) mellifera. We found that highly methylated orthologs in A. pisum and Ap. mellifera exhibited greater conservation of methylation status, suggesting that highly methylated genes in ancestral species may remain highly methylated over time. We also found that methylated genes tended to show different rates of evolution than unmethylated genes. In addition, genes targeted by methylation were enriched for particular biological processes that differed from those in relatively unmethylated genes. Finally, methylated genes were preferentially ubiquitously expressed among alternate phenotypes in both species, whereas genes lacking signatures of methylation were preferentially associated with condition-specific gene expression. Overall, our analyses support a conserved role for DNA methylation in insects with comparable methylation systems

Positional identification of variants of Adamts16 linked to inherited hypertension

A previously reported blood pressure (BP) quantitative trait locus on rat Chromosome 1 was isolated in a short congenic segment spanning 804.6 kb. The 804.6 kb region contained only two genes, LOC306664 and LOC306665. LOC306664 is predicted to translate into A Disintegrin-like and Metalloproteinase with Thrombospondin Motifs-16 (Adamts16). LOC306665 is a novel gene. All predicted exons of both LOC306664 and LOC306665 were sequenced. Non-synonymous variants were identified in only one of these genes, LOC306664. These variants were naturally existing polymorphisms among inbred, outbred and wild rats. The full-length rat transcript of Adamts16 was detected in multiple tissues. Similar to ADAMTS16 in humans, expression of Adamts16 was prominent in the kidney. Renal transcriptome analysis suggested that a network of genes related to BP was differential between congenic and S rats. These genes were also differentially expressed between kidney cell lines with or without knock-down of Adamts16. Adamts16 is conserved between rats and humans. It is a candidate gene within the homologous region on human Chromosome 5, which is linked to systolic and diastolic BP in the Quebec Family Study. Multiple variants, including an Ala to Pro variant in codon 90 (rs2086310) of human ADAMTS16, were associated with human resting systolic BP (SBP). Replication study in GenNet confirmed the association of two variants of ADAMTS16 with SBP, including rs2086310. Overall, our report represents a high resolution positional cloning and translational study for Adamts16 as a candidate gene controlling BP

Analysis of gene expression profiles in HeLa cells in response to overexpression or siRNA-mediated depletion of NASP

<p>Abstract</p> <p>Background</p> <p>NASP (Nuclear Autoantigenic Sperm Protein) is a linker histone chaperone required for normal cell division. Changes in NASP expression significantly affect cell growth and development; loss of gene function results in embryonic lethality. However, the mechanism by which NASP exerts its effects in the cell cycle is not understood. To understand the pathways and networks that may involve NASP function, we evaluated gene expression in HeLa cells in which NASP was either overexpressed or depleted by siRNA.</p> <p>Methods</p> <p>Total RNA from HeLa cells overexpressing NASP or depleted of NASP by siRNA treatment was converted to cRNA with incorporation of Cy5-CTP (experimental samples), or Cy3-CTP (control samples). The labeled cRNA samples were hybridized to whole human genome microarrays (Agilent Technologies, Wilmington, Delaware, USA). Various gene expression analysis techniques were employed: Significance Analysis of Microarrays (SAM), Expression Analysis Systematic Explorer (EASE), and Ingenuity Pathways Analysis (IPA).</p> <p>Results</p> <p>From approximately 36 thousand genes present in a total human genome microarray, we identified a set of 47 up-regulated and 7 down-regulated genes as a result of NASP overexpression. Similarly we identified a set of 56 up-regulated and 71 down-regulated genes as a result of NASP siRNA treatment. Gene ontology, molecular network and canonical pathway analysis of NASP overexpression demonstrated that the most significant changes were in proteins participating in organismal injury, immune response, and cellular growth and cancer pathways (major "hubs": TNF, FOS, EGR1, NFκB, IRF7, STAT1, IL6). Depletion of NASP elicited the changed expression of proteins involved in DNA replication, repair and development, followed by reproductive system disease, and cancer and cell cycle pathways (major "hubs": E2F8, TP53, FGF, FSH, FST, hCG, NFκB, TRAF6).</p> <p>Conclusion</p> <p>This study has demonstrated that NASP belongs to a network of genes and gene functions that are critical for cell survival. We have confirmed the previously reported interactions between NASP and HSP90, HSP70, histone H1, histone H3, and TRAF6. Overexpression and depletion of NASP identified overlapping networks that included TNF as a core protein, confirming that both high and low levels of NASP are detrimental to cell cycle progression. Networks with cancer-related functions had the highest significance, however reproductive networks containing follistatin and FSH were also significantly affected, which confirmed NASP's important role in reproductive tissues. This study revealed that, despite some overlap, each response was associated with a unique gene signature and placed NASP in important cell regulatory networks.</p