A Detection of Sgr A* in the far infrared

We report the first detection of the Galactic Centre massive black hole, Sgr~A*, in the far infrared. Our measurements were obtained with PACS on board the \emph{Herschel} satellite at $100~\mathrm{\mu m}$ and $160~\mathrm{\mu m}$. While the warm dust in the Galactic Centre is too bright to allow for a direct detection of Sgr~A*, we measure a significant and simultaneous variation of its flux of $\Delta F_{\nu\widehat{=}160 ~\mathrm{\mu m}} = (0.27\pm0.06)~\mathrm{Jy}$ and $\Delta F_{\nu\widehat{=}100 ~\mathrm{\mu m}}= (0.16\pm0.10)~\mathrm{Jy}$ during one observation. The significance level of the $160 ~\mathrm{\mu m}$ band variability is $4.5\sigma$ and the corresponding $100 ~\mathrm{\mu m}$ band variability is significant at $1.6\sigma$. We find no example of an equally significant false positive detection. Conservatively assuming a variability of $25\%$ in the FIR, we can provide upper limits to the flux. Comparing the latter with theoretical models we find that 1D RIAF models have difficulties explaining the observed faintness. However, the upper limits are consistent with modern ALMA and VLA observations. Our upper limits provide further evidence for a spectral peak at $\sim 10^{12} ~ \mathrm{Hz}$ and constrain the number density of $\gamma \sim 100$ electrons in the accretion disk and or outflow.Comment: accepted for publication in AP

An integrated gene annotation and transcriptional profiling approach towards the full gene content of the Drosophila genome

BACKGROUND: While the genome sequences for a variety of organisms are now available, the precise number of the genes encoded is still a matter of debate. For the human genome several stringent annotation approaches have resulted in the same number of potential genes, but a careful comparison revealed only limited overlap. This indicates that only the combination of different computational prediction methods and experimental evaluation of such in silico data will provide more complete genome annotations. In order to get a more complete gene content of the Drosophila melanogaster genome, we based our new D. melanogaster whole-transcriptome microarray, the Heidelberg FlyArray, on the combination of the Berkeley Drosophila Genome Project (BDGP) annotation and a novel ab initio gene prediction of lower stringency using the Fgenesh software. RESULTS: Here we provide evidence for the transcription of approximately 2,600 additional genes predicted by Fgenesh. Validation of the developmental profiling data by RT-PCR and in situ hybridization indicates a lower limit of 2,000 novel annotations, thus substantially raising the number of genes that make a fly. CONCLUSIONS: The successful design and application of this novel Drosophila microarray on the basis of our integrated in silico/wet biology approach confirms our expectation that in silico approaches alone will always tend to be incomplete. The identification of at least 2,000 novel genes highlights the importance of gathering experimental evidence to discover all genes within a genome. Moreover, as such an approach is independent of homology criteria, it will allow the discovery of novel genes unrelated to known protein families or those that have not been strictly conserved between species

Overexpression of Inosine 5′-Monophosphate Dehydrogenase Type II Mediates Chemoresistance to Human Osteosarcoma Cells

overexpression in osteosarcoma patients with poor response to chemotherapy. The aim of this study was to provide evidence for direct involvement of IMPDH2 in the development of chemoresistance..IMPDH2 is directly involved in the development of chemoresistance in osteosarcoma cells, suggesting that targeting of IMPDH2 by RNAi or more effective pharmacological inhibitors in combination with chemotherapy might be a promising means of overcoming chemoresistance in osteosarcomas with high IMPDH2 expression

Replication and Virus-Induced Transcriptome of HAdV-5 in Normal Host Cells versus Cancer Cells - Differences of Relevance for Adenoviral Oncolysis

Adenoviruses (Ads), especially HAdV-5, have been genetically equipped with tumor-restricted replication potential to enable applications in oncolytic cancer therapy. Such oncolytic adenoviruses have been well tolerated in cancer patients, but their anti-tumor efficacy needs to be enhanced. In this regard, it should be considered that cancer cells, dependent on their tissue of origin, can differ substantially from the normal host cells to which Ads are adapted by complex virus-host interactions. Consequently, viral replication efficiency, a key determinant of oncolytic activity, might be suboptimal in cancer cells. Therefore, we have analyzed both the replication kinetics of HAdV-5 and the virus-induced transcriptome in human bronchial epithelial cells (HBEC) in comparison to cancer cells. This is the first report on genome-wide expression profiling of Ads in their native host cells. We found that E1A expression and onset of viral genome replication are most rapid in HBEC and considerably delayed in melanoma cells. In squamous cell lung carcinoma cells, we observed intermediate HAdV-5 replication kinetics. Infectious particle production, viral spread and lytic activity of HAdV-5 were attenuated in melanoma cells versus HBEC. Expression profiling at the onset of viral genome replication revealed that HAdV-5 induced the strongest changes in the cellular transcriptome in HBEC, followed by lung cancer and melanoma cells. We identified prominent regulation of genes involved in cell cycle and DNA metabolism, replication and packaging in HBEC, which is in accord with the necessity to induce S phase for viral replication. Strikingly, in melanoma cells HAdV-5 triggered opposing regulation of said genes and, in contrast to lung cancer cells, no weak S phase induction was detected when using the E2F promoter as reporter. Our results provide a rationale for improving oncolytic adenoviruses either by adaptation of viral infection to target tumor cells or by modulating tumor cell functions to better support viral replication

Genotypic resistance testing in HIV by arrayed primer extension

The analysis of mutations that are associated with the occurrence of drug resistance is important for monitoring the antiretroviral therapy of patients infected with human immunodeficiency virus (HIV). Here, we describe the establishment and successful application of Arrayed Primer Extension (APEX) for genotypic resistance testing in HIV as a rapid and economical alternative to standard sequencing. The assay is based on an array of oligonucleotide primers that are immobilised via their 5′-ends. Upon hybridisation of template DNA, a primer extension reaction is performed in the presence of the four dideoxynucleotides, each labelled with a distinct fluorophore. The inserted label immediately indicates the sequence at the respective position. Any mutation changes the colour pattern. We designed a microarray for the analysis of 26 and 33 codons in the HIV protease and reverse transcriptase, respectively, which are of special interest with respect to drug resistance. The enormous genome variability of HIV represents a big challenge for genotypic resistance tests, which include a hybridisation step, both in terms of specificity and probe numbers. The use of degenerated oligonucleotides resulted in a significant reduction in the number of primers needed. For validation, DNA of 94 and 48 patients that exhibited resistance to inhibitors of HIV protease and reverse transcriptase, respectively, were analysed. The validation included HIV subtype B, prevalent in industrialised countries, as well as non-subtype B samples that are more common elsewhere

First direct detection of an exoplanet by optical interferometry; Astrometry and K-band spectroscopy of HR8799 e

To date, infrared interferometry at best achieved contrast ratios of a few times $10^{-4}$ on bright targets. GRAVITY, with its dual-field mode, is now capable of high contrast observations, enabling the direct observation of exoplanets. We demonstrate the technique on HR8799, a young planetary system composed of four known giant exoplanets. We used the GRAVITY fringe tracker to lock the fringes on the central star, and integrated off-axis on the HR8799e planet situated at 390 mas from the star. Data reduction included post-processing to remove the flux leaking from the central star and to extract the coherent flux of the planet. The inferred K band spectrum of the planet has a spectral resolution of 500. We also derive the astrometric position of the planet relative to the star with a precision on the order of 100$\,\mu$as. The GRAVITY astrometric measurement disfavors perfectly coplanar stable orbital solutions. A small adjustment of a few degrees to the orbital inclination of HR 8799 e can resolve the tension, implying that the orbits are close to, but not strictly coplanar. The spectrum, with a signal-to-noise ratio of $\approx 5$ per spectral channel, is compatible with a late-type L brown dwarf. Using Exo-REM synthetic spectra, we derive a temperature of $1150\pm50$\,K and a surface gravity of $10^{4.3\pm0.3}\,$cm/s$^{2}$. This corresponds to a radius of $1.17^{+0.13}_{-0.11}\,R_{\rm Jup}$ and a mass of $10^{+7}_{-4}\,M_{\rm Jup}$, which is an independent confirmation of mass estimates from evolutionary models. Our results demonstrate the power of interferometry for the direct detection and spectroscopic study of exoplanets at close angular separations from their stars.Comment: published in A&

Identification of differentially expressed subnetworks based on multivariate ANOVA

<p>Abstract</p> <p>Background</p> <p>Since high-throughput protein-protein interaction (PPI) data has recently become available for humans, there has been a growing interest in combining PPI data with other genome-wide data. In particular, the identification of phenotype-related PPI subnetworks using gene expression data has been of great concern. Successful integration for the identification of significant subnetworks requires the use of a search algorithm with a proper scoring method. Here we propose a multivariate analysis of variance (MANOVA)-based scoring method with a greedy search for identifying differentially expressed PPI subnetworks.</p> <p>Results</p> <p>Given the MANOVA-based scoring method, we performed a greedy search to identify the subnetworks with the maximum scores in the PPI network. Our approach was successfully applied to human microarray datasets. Each identified subnetwork was annotated with the Gene Ontology (GO) term, resulting in the phenotype-related functional pathway or complex. We also compared these results with those of other scoring methods such as <it>t </it>statistic- and mutual information-based scoring methods. The MANOVA-based method produced subnetworks with a larger number of proteins than the other methods. Furthermore, the subnetworks identified by the MANOVA-based method tended to consist of highly correlated proteins.</p> <p>Conclusion</p> <p>This article proposes a MANOVA-based scoring method to combine PPI data with expression data using a greedy search. This method is recommended for the highly sensitive detection of large subnetworks.</p