Adsorbate-induced electronic modification of alkali-metal overlayers

For submonolayer coverages of Cs on Ru(0001) surfaces, the Cs-Ru vibration is observed at 7.8 meV (63 cm−1) by means of high-resolution electron-energy-loss spectroscopy. At Cs coverages near the complete monolayer the adlayer becomes metallic as indicated by screening of the Cs-Ru vibration and the occurrence of an electronic excitation (plasmon) at 580 meV. Coadsorption of CO as well as of oxygen leads to the reappearance of the Cs-Ru vibration and the disappearance of the electronic excitation which is interpreted as a demetallization through chemical interaction with the coadsorbed species

Emission of exoelectrons during oxidation of Cs via thermal activation of a metastable O^-₂ surface species

Exposure of Cs surfaces to O2 causes the emission of exoelectrons. With a Cs monolayer on Ru(0001) the maximum yield is observed with an already partly oxidized surface on which a metastable O-2 species could be identified. Thermally activated transformation (with an activation energy of 0.8 eV) of this phase leads to dissociation accompanied by exoelectron emission via Auger deexcitation

Chromosome 20q Amplification Regulates in Vitro Response to Kinesin-5 Inhibitor

We identified gene expression signatures predicting responsiveness to a Kinesin-5 (KIF11) inhibitor (Kinesin-5i) in cultured colon tumor cell lines. Genes predicting resistance to Kinesin-5i were enriched for those from chromosome 20q, a region of frequent amplification in a number of tumor types. siRNAs targeting genes in this chromosomal region identified AURKA, TPX2 and MYBL2 as genes whose disruption enhances response to Kinesin-5i. Taken together, our results show functional interaction between these genes, and suggest that their overexpression is involved in resistance to Kinesin-5i. Furthermore, our results suggest that patients whose tumors overexpress AURKA due to amplification of 20q will more likely resist treatment with Kinesin-5 inhibitor, and that inactivation of AURKA may sensitize these patients to treatment

The Extremely High Energy Cosmic Rays

Experimental results from Haverah Park, Yakutsk, AGASA and Fly's Eye are reviewed. All these experiments work in the energy range above 0.1 EeV. The 'dip' structure around 3 EeV in the energy spectrum is well established by all the experiments, though the exact position differs slightly. Fly's Eye and Yakutsk results on the chemical composition indicate that the cosmic rays are getting lighter over the energy range from 0.1 EeV to 10 EeV, but the exact fraction is hadronic interaction model dependent, as indicated by the AGASA analysis. The arrival directions of cosmic rays are largely isotropic, but interesting features may be starting to emerge. Most of the experimental results can best be explained with the scenario that an extragalactic component gradually takes over a galactic population as energy increases and cosmic rays at the highest energies are dominated by particles coming from extragalactic space. However, identification of the extragalactic sources has not yet been successful because of limited statistics and the resolution of the data.Comment: The review paper including 21 figures. 39 pages: To be published in Journal of Physics

PPARα siRNA–Treated Expression Profiles Uncover the Causal Sufficiency Network for Compound-Induced Liver Hypertrophy

Uncovering pathways underlying drug-induced toxicity is a fundamental objective in the field of toxicogenomics. Developing mechanism-based toxicity biomarkers requires the identification of such novel pathways and the order of their sufficiency in causing a phenotypic response. Genome-wide RNA interference (RNAi) phenotypic screening has emerged as an effective tool in unveiling the genes essential for specific cellular functions and biological activities. However, eliciting the relative contribution of and sufficiency relationships among the genes identified remains challenging. In the rodent, the most widely used animal model in preclinical studies, it is unrealistic to exhaustively examine all potential interactions by RNAi screening. Application of existing computational approaches to infer regulatory networks with biological outcomes in the rodent is limited by the requirements for a large number of targeted permutations. Therefore, we developed a two-step relay method that requires only one targeted perturbation for genome-wide de novo pathway discovery. Using expression profiles in response to small interfering RNAs (siRNAs) against the gene for peroxisome proliferator-activated receptor α (Ppara), our method unveiled the potential causal sufficiency order network for liver hypertrophy in the rodent. The validity of the inferred 16 causal transcripts or 15 known genes for PPARα-induced liver hypertrophy is supported by their ability to predict non-PPARα–induced liver hypertrophy with 84% sensitivity and 76% specificity. Simulation shows that the probability of achieving such predictive accuracy without the inferred causal relationship is exceedingly small (p < 0.005). Five of the most sufficient causal genes have been previously disrupted in mouse models; the resulting phenotypic changes in the liver support the inferred causal roles in liver hypertrophy. Our results demonstrate the feasibility of defining pathways mediating drug-induced toxicity from siRNA-treated expression profiles. When combined with phenotypic evaluation, our approach should help to unleash the full potential of siRNAs in systematically unveiling the molecular mechanism of biological events

Clinicopathologic and gene expression parameters predict liver cancer prognosis

<p>Abstract</p> <p>Background</p> <p>The prognosis of hepatocellular carcinoma (HCC) varies following surgical resection and the large variation remains largely unexplained. Studies have revealed the ability of clinicopathologic parameters and gene expression to predict HCC prognosis. However, there has been little systematic effort to compare the performance of these two types of predictors or combine them in a comprehensive model.</p> <p>Methods</p> <p>Tumor and adjacent non-tumor liver tissues were collected from 272 ethnic Chinese HCC patients who received curative surgery. We combined clinicopathologic parameters and gene expression data (from both tissue types) in predicting HCC prognosis. Cross-validation and independent studies were employed to assess prediction.</p> <p>Results</p> <p>HCC prognosis was significantly associated with six clinicopathologic parameters, which can partition the patients into good- and poor-prognosis groups. Within each group, gene expression data further divide patients into distinct prognostic subgroups. Our predictive genes significantly overlap with previously published gene sets predictive of prognosis. Moreover, the predictive genes were enriched for genes that underwent normal-to-tumor gene network transformation. Previously documented liver eSNPs underlying the HCC predictive gene signatures were enriched for SNPs that associated with HCC prognosis, providing support that these genes are involved in key processes of tumorigenesis.</p> <p>Conclusion</p> <p>When applied individually, clinicopathologic parameters and gene expression offered similar predictive power for HCC prognosis. In contrast, a combination of the two types of data dramatically improved the power to predict HCC prognosis. Our results also provided a framework for understanding the impact of gene expression on the processes of tumorigenesis and clinical outcome.</p

PDlim2 Selectively Interacts with the PDZ Binding Motif of Highly Pathogenic Avian H5N1 Influenza A Virus NS1

The multi-functional NS1 protein of influenza A virus is a viral virulence determining factor. The last four residues at the C-terminus of NS1 constitute a type I PDZ domain binding motif (PBM). Avian influenza viruses currently in circulation carry an NS1 PBM with consensus sequence ESEV, whereas human influenza viruses bear an NS1 PBM with consensus sequence RSKV or RSEV. The PBM sequence of the influenza A virus NS1 is reported to contribute to high viral pathogenicity in animal studies. Here, we report the identification of PDlim2 as a novel binding target of the highly pathogenic avian influenza virus H5N1 strain with an NS1 PBM of ESEV (A/Chicken/Henan/12/2004/H5N1, HN12-NS1) by yeast two-hybrid screening. The interaction was confirmed by in vitro GST pull-down assays, as well as by in vivo mammalian two-hybrid assays and bimolecular fluorescence complementation assays. The binding was also confirmed to be mediated by the interaction of the PDlim2 PDZ domain with the NS1 PBM motif. Interestingly, our assays showed that PDlim2 bound specifically with HN12-NS1, but exhibited no binding to NS1 from a human influenza H1N1 virus bearing an RSEV PBM (A/Puerto Rico/8/34/H1N1, PR8-NS1). A crystal structure of the PDlim2 PDZ domain fused with the C-terminal hexapeptide from HN12-NS1, together with GST pull-down assays on PDlim2 mutants, reveals that residues Arg16 and Lys31 of PDlim2 are critical for the binding between PDlim2 and HN12-NS1. The identification of a selective binding target of HN12-NS1 (ESEV), but not PR8-NS1 (RSEV), enables us to propose a structural mechanism for the interaction between NS1 PBM and PDlim2 or other PDZ-containing proteins

Predictive Genes in Adjacent Normal Tissue Are Preferentially Altered by sCNV during Tumorigenesis in Liver Cancer and May Rate Limiting

Background: In hepatocellular carcinoma (HCC) genes predictive of survival have been found in both adjacent normal (AN) and tumor (TU) tissues. The relationships between these two sets of predictive genes and the general process of tumorigenesis and disease progression remains unclear. Methodology/Principal Findings: Here we have investigated HCC tumorigenesis by comparing gene expression, DNA copy number variation and survival using ~250 AN and TU samples representing, respectively, the pre-cancer state, and the result of tumorigenesis. Genes that participate in tumorigenesis were defined using a gene-gene correlation meta-analysis procedure that compared AN versus TU tissues. Genes predictive of survival in AN (AN-survival genes) were found to be enriched in the differential gene-gene correlation gene set indicating that they directly participate in the process of tumorigenesis. Additionally the AN-survival genes were mostly not predictive after tumorigenesis in TU tissue and this transition was associated with and could largely be explained by the effect of somatic DNA copy number variation (sCNV) in cis and in trans. The data was consistent with the variance of AN-survival genes being rate-limiting steps in tumorigenesis and this was confirmed using a treatment that promotes HCC tumorigenesis that selectively altered AN-survival genes and genes differentially correlated between AN and TU. Conclusions/Significance: This suggests that the process of tumor evolution involves rate-limiting steps related to the background from which the tumor evolved where these were frequently predictive of clinical outcome. Additionally treatments that alter the likelihood of tumorigenesis occurring may act by altering AN-survival genes, suggesting that the process can be manipulated. Further sCNV explains a substantial fraction of tumor specific expression and may therefore be a causal driver of tumor evolution in HCC and perhaps many solid tumor types. © 2011 Lamb et al.published_or_final_versio