New Structure In The Shapley Supercluster

We present new radial velocities for 189 galaxies in a 91 sq. deg region of the Shapley supercluster measured with the FLAIR-II spectrograph on the UK Schmidt Telescope. The data reveal two sheets of galaxies linking the major concentrations of the supercluster. The supercluster is not flattened in Declination as was suggested previously and it may be at least 30 percent larger than previously thought with a correspondingly larger contribution to the motion of the Local Group.Comment: LaTex: 2 pages, 1 figure, includes conf_iap.sty style file. To appear in proceedings of The 14th IAP Colloquium: Wide Field Surveys in Cosmology, held in Paris, 1998 May 26--30, eds. S.Colombi, Y.Mellie

Development and Performance of the ACTS High Speed VSAT

The Advanced Communication Technology Satellite (ACTS), developed by the U.S. National Aeronautics and Space Administration (NASA) has demonstrated the breakthrough technologies of Ka-band, spot beam antennas, and on-board processing. These technologies have enabled the development of very small aperture terminals (VSAT) and ultra-small aperture terminals (USAT) which have capabilities greater than were previously possible with conventional satellite technologies. However, the ACTS baseband processor (BBP) is designed using a time division multiple access (TDMA) scheme, which requires each earth station using the BBP to transmit data at a burst rate which is much higher than the user throughput data rate. This tends to mitigate the advantage of the new technologies by requiring a larger earth station antenna and/or a higher-powered uplink amplifier than would be necessary for a continuous transmission at the user data rate. Conversely, the user data rate is much less than the rate that can be supported by the antenna size and amplifier. For example, the ACTS TI VSAT operates at a burst rate of 27.5 Mbps, but the maximum user data rate is 1.792 Mbps. The throughput efficiency is slightly more than 6.5%. For an operational network, this level of overhead will greatly increase the cost of the user earth stations, and that increased cost must be repeated thousands of times, which may ultimately reduce the market for such a system. The ACTS High Speed VSAT (HS VSAT) is an effort to experimentally demonstrate the maximum user throughput data rate which can be achieved using the technologies developed and implemented on ACTS. Specifically, this was done by operating the system uplinks as frequency division multiple access (FDMA), essentially assigning all available TDMA time slots to a single user on each of two uplink frequencies. Preliminary results show that using a 1.2-m antenna in this mode, the HS VSAT can achieve between 22 and 24 Mbps out of the 27.5 Mbps burst rate, for a throughput efficiency of 80-88%. This paper describes the modifications made to the TI VSAT to enable it to operate at high speed, including hardware considerations, interface modifications, and software modifications. In addition, it describes the results of NASA HS VSAT experiments, continuing work on an improved user interface, and plans for future experiments

Preferential regulation of stably expressed genes in the human genome suggests a widespread expression buffering role of microRNAs

In this study, we comprehensively explored the stably expressed genes (SE genes) and fluctuant genes (FL genes) in the human genome by a meta-analysis of large scale microarray data. We found that these genes have distinct function distributions. miRNA targets are shown to be significantly enriched in SE genes by using propensity analysis of miRNA regulation, supporting the hypothesis that miRNAs can buffer whole genome expression fluctuation. The expression-buffering effect of miRNA is independent of the target site number within the 3'-untranslated region. In addition, we found that gene expression fluctuation is positively correlated with the number of transcription factor binding sites in the promoter region, which suggests that coordination between transcription factors and miRNAs leads to balanced responses to external perturbations

SFSSClass: an integrated approach for miRNA based tumor classification

Background: MicroRNA (miRNA) expression profiling data has recently been found to be particularly important in cancer research and can be used as a diagnostic and prognostic tool. Current approaches of tumor classification using miRNA expression data do not integrate the experimental knowledge available in the literature. A judicious integration of such knowledge with effective miRNA and sample selection through a biclustering approach could be an important step in improving the accuracy of tumor classification. Results: In this article, a novel classification technique called SFSSClass is developed that judiciously integrates a biclustering technique SAMBA for simultaneous feature (miRNA) and sample (tissue) selection (SFSS), a cancer-miRNA network that we have developed by mining the literature of experimentally verified cancer-miRNA relationships and a classifier uncorrelated shrunken centroid (USC). SFSSClass is used for classifying multiple classes of tumors and cancer cell lines. In a part of the investigation, poorly differentiated tumors (PDT) having non diagnostic histological appearance are classified while training on more differentiated tumor (MDT) samples. The proposed method is found to outperform the best known accuracy in the literature on the experimental data sets. For example, while the best accuracy reported in the literature for classifying PDT samples is similar to 76.5%, the accuracy of SFSSClass is found to be similar to 82.3%. The advantage of incorporating biclustering integrated with the cancer-miRNA network is evident from the consistently better performance of SFSSClass (integration of SAMBA, cancer-miRNA network and USC) over USC (eg., similar to 70.5% for SFSSClass versus similar to 58.8% in classifying a set of 17 MDT samples from 9 tumor types, similar to 91.7% for SFSSClass versus similar to 75% in classifying 12 cell lines from 6 tumor types and similar to 382.3% for SFSSClass versus similar to 41.2% in classifying 17 PDT samples from 11 tumor types). Conclusion: In this article, we develop the SFSSClass algorithm which judiciously integrates a biclustering technique for simultaneous feature (miRNA) and sample (tissue) selection, the cancer-miRNA network and a classifier. The novel integration of experimental knowledge with computational tools efficiently selects relevant features that have high intra-class and low interclass similarity. The performance of the SFSSClass is found to be significantly improved with respect to the other existing approaches

Circulating microRNAs Reveal Time Course of Organ Injury in a Porcine Model of Acetaminophen-Induced Acute Liver Failure

Acute liver failure is a rare but catastrophic condition which can progress rapidly to multi-organ failure. Studies investigating the onset of individual organ injury such as the liver, kidneys and brain during the evolution of acute liver failure, are lacking. MicroRNAs are short, non-coding strands of RNA that are released into the circulation following tissue injury. In this study, we have characterised the release of both global microRNA and specific microRNA species into the plasma using a porcine model of acetaminophen-induced acute liver failure. Pigs were induced to acute liver failure with oral acetaminophen over 19h±2h and death occurred 13h±3h thereafter. Global microRNA concentrations increased 4h prior to acute liver failure in plasma (P<0.0001) but not in isolated exosomes, and were associated with increasing plasma levels of the damage-associated molecular pattern molecule, genomic DNA (P<0.0001). MiR122 increased around the time of onset of acute liver failure (P<0.0001) and was associated with increasing international normalised ratio (P<0.0001). MiR192 increased 8h after acute liver failure (P<0.0001) and was associated with increasing creatinine (P<0.0001). The increase in miR124-1 occurred concurrent with the pre-terminal increase in intracranial pressure (P<0.0001) and was associated with decreasing cerebral perfusion pressure (P<0.002)

Cepred: Predicting the Co-Expression Patterns of the Human Intronic microRNAs with Their Host Genes

Identifying the tissues in which a microRNA is expressed could enhance the understanding of the functions, the biological processes, and the diseases associated with that microRNA. However, the mechanisms of microRNA biogenesis and expression remain largely unclear and the identification of the tissues in which a microRNA is expressed is limited. Here, we present a machine learning based approach to predict whether an intronic microRNA show high co-expression with its host gene, by doing so, we could infer the tissues in which a microRNA is high expressed through the expression profile of its host gene. Our approach is able to achieve an accuracy of 79% in the leave-one-out cross validation and 95% on an independent testing dataset. We further estimated our method through comparing the predicted tissue specific microRNAs and the tissue specific microRNAs identified by biological experiments. This study presented a valuable tool to predict the co-expression patterns between human intronic microRNAs and their host genes, which would also help to understand the microRNA expression and regulation mechanisms. Finally, this framework can be easily extended to other species

Network Theory Analysis of Antibody-Antigen Reactivity Data: The Immune Trees at Birth and Adulthood

Motivation: New antigen microarray technology enables parallel recording of antibody reactivities with hundreds of antigens. Such data affords system level analysis of the immune system’s organization using methods and approaches from network theory. Here we measured the reactivity of 290 antigens (for both the IgG and IgM isotypes) of 10 healthy mothers and their term newborns. We constructed antigen correlation networks (or immune networks) whose nodes are the antigens and the edges are the antigen-antigen reactivity correlations, and we also computed their corresponding minimum spanning trees (MST) – maximal information reduced sub-graphs. We quantify the network organization (topology) in terms of the network theory divergence rate measure and rank the antigen importance in the full antigen correlation networks by the eigen-value centrality measure. This analysis makes possible the characterization and comparison of the IgG and IgM immune networks at birth (newborns) and adulthood (mothers) in terms of topology and node importance. Results: Comparison of the immune network topology at birth and adulthood revealed partial conservation of the IgG immune network topology, and significant reorganization of the IgM immune networks. Inspection of the antigen importance revealed some dominant (in terms of high centrality) antigens in the IgG and IgM networks at birth, which retain their importance at adulthood

Senescent Cells in Growing Tumors: Population Dynamics and Cancer Stem Cells

Tumors are defined by their intense proliferation, but sometimes cancer cells turn senescent and stop replicating. In the stochastic cancer model in which all cells are tumorigenic, senescence is seen as the result of random mutations, suggesting that it could represent a barrier to tumor growth. In the hierarchical cancer model a subset of the cells, the cancer stem cells, divide indefinitely while other cells eventually turn senescent. Here we formulate cancer growth in mathematical terms and obtain predictions for the evolution of senescence. We perform experiments in human melanoma cells which are compatible with the hierarchical model and show that senescence is a reversible process controlled by survivin. We conclude that enhancing senescence is unlikely to provide a useful therapeutic strategy to fight cancer, unless the cancer stem cells are specifically targeted