Wick's theorem for q-deformed boson operators

In this paper combinatorial aspects of normal ordering arbitrary words in the creation and annihilation operators of the q-deformed boson are discussed. In particular, it is shown how by introducing appropriate q-weights for the associated ``Feynman diagrams'' the normally ordered form of a general expression in the creation and annihilation operators can be written as a sum over all q-weighted Feynman diagrams, representing Wick's theorem in the present context.Comment: 9 page

Single Impurity Anderson Model with Coulomb Repulsion between Conduction Electrons on the Nearest-Neighbour Ligand Orbital

We study how the Kondo effect is affected by the Coulomb interaction between conduction electrons on the basis of a simplified model. The single impurity Anderson model is extended to include the Coulomb interaction on the nearest-neighbour ligand orbital. The excitation spectra are calculated using the numerical renormalization group method. The effective bandwidth on the ligand orbital, $D^{eff}$, is defined to classify the state. This quantity decreases as the Coulomb interaction increases. In the $D^{eff} > \Delta$ region, the low energy properties are described by the Kondo state, where $\Delta$ is the hybridization width. As $D^{eff}$ decreases in this region, the Kondo temperature $T_{K}$ is enhanced, and its magnitude becomes comparable to $\Delta$ for $D^{eff} \sim \Delta$. In the $D^{eff} < \Delta$ region, the local singlet state between the electrons on the $f$ and ligand orbitals is formed.Comment: 5 pages, 3 figures, LaTeX, to be published in J. Phys. Soc. Jpn Vol. 67 No.

Monomer transport limitations in emulsion polymerization

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Utility of network integrity methods in therapeutic target identification

Analysis of the biological gene networks involved in a disease may lead to the identification of therapeutic targets. Such analysis requires exploring network properties, in particular the importance of individual network nodes (i.e., genes). There are many measures that consider the importance of nodes in a network and some may shed light on the biological significance and potential optimality of a gene or set of genes as therapeutic targets. This has been shown to be the case in cancer therapy. A dilemma exists, however, in finding the best therapeutic targets based on network analysis since the optimal targets should be nodes that are highly influential in, but not toxic to, the functioning of the entire network. In addition, cancer therapeutics targeting a single gene often result in relapse since compensatory, feedback and redundancy loops in the network may offset the activity associated with the targeted gene. Thus, multiple genes reflecting parallel functional cascades in a network should be targeted simultaneously, but require the identification of such targets. We propose a methodology that exploits centrality statistics characterizing the importance of nodes within a gene network that is constructed from the gene expression patterns in that network. We consider centrality measures based on both graph theory and spectral graph theory. We also consider the origins of a network topology, and show how different available representations yield different node importance results. We apply our techniques to tumor gene expression data and suggest that the identification of optimal therapeutic targets involving particular genes, pathways and sub-networks based on an analysis of the nodes in that network is possible and can facilitate individualized cancer treatments. The proposed methods also have the potential to identify candidate cancer therapeutic targets that are not thought to be oncogenes but nonetheless play important roles in the functioning of a cancer-related network or pathway

Simulation-based homozygosity mapping with the GAW14 COGA dataset on alcoholism

BACKGROUND: We have developed a simulation-based approach to the analysis of shared homozygous chromosomal segments and have applied it to data on allele sharing among alcoholics in a single Collaborative Study on the Genetics of Alcoholism pedigree. Our assessment of sharing involved the use of a single-nucleotide polymorphism (SNP) marker map provided by Affymetrix. RESULTS: All 11 affected individuals in the selected pedigree shared 2 copies of an allele at 4 adjacent SNPs in a region on chromosome 5. Via simulation, we determined that the probability that such sharing is caused by mere chance is less than 0.0000001. After correcting for undocumented inbreeding, this probability rose to 0.0016. The probability that the shared segment emanates from a single ancestor and is unrelated to the affection status is less than 0.0000001 in the corrected pedigree. Haplotype association analysis and a search for a protective locus using unaffected individuals yielded no significant results. CONCLUSION: Homozygosity mapping results on chromosome 5 provide suggestive evidence of the region's role as one that may harbor a genetic determinant of alcoholism. Furthermore, the probabilities of chance homozygous allele sharing for the original and for the inbreeding-corrected pedigree provide insight into the impact that inbreeding can have on such calculations

Genetic structure of community acquired methicillin-resistant Staphylococcus aureus USA300.

BackgroundCommunity-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) is a significant bacterial pathogen that poses considerable clinical and public health challenges. The majority of the CA-MRSA disease burden consists of skin and soft tissue infections (SSTI) not associated with significant morbidity; however, CA-MRSA also causes severe, invasive infections resulting in significant morbidity and mortality. The broad range of disease severity may be influenced by bacterial genetic variation.ResultsWe sequenced the complete genomes of 36 CA-MRSA clinical isolates from the predominant North American community acquired clonal type USA300 (18 SSTI and 18 severe infection-associated isolates). While all 36 isolates shared remarkable genetic similarity, we found greater overall time-dependent sequence diversity among SSTI isolates. In addition, pathway analysis of non-synonymous variations revealed increased sequence diversity in the putative virulence genes of SSTI isolates.ConclusionsHere we report the first whole genome survey of diverse clinical isolates of the USA300 lineage and describe the evolution of the pathogen over time within a defined geographic area. The results demonstrate the close relatedness of clinically independent CA-MRSA isolates, which carry implications for understanding CA-MRSA epidemiology and combating its spread

The Kondo lattice model with correlated conduction electrons

We investigate a Kondo lattice model with correlated conduction electrons. Within dynamical mean-field theory the model maps onto an impurity model where the host has to be determined self-consistently. This impurity model can be derived from an Anderson-Hubbard model both by equating the low-energy excitations of the impurity and by a canonical transformation. On the level of dynamical mean-field theory this establishes the connection of the two lattice models. The impurity model is studied numerically by an extension of the non-crossing approximation to a two-orbital impurity. We find that with decreasing temperature the conduction electrons first form quasiparticles unaffected by the presence of the lattice of localized spins. Then, reducing the temperature further, the particle-hole symmetric model turns into an insulator. The quasiparticle peak in the one-particle spectral density splits and a gap opens. The size of the gap increases when the correlations of the conduction electrons become stronger. These findings are similar to the behavior of the Anderson-Hubbard model within dynamical mean-field theory and are obtained with much less numerical effort.Comment: 7 pages RevTeX with 3 ps figures, accepted by PR

Mechanisms of linezolid resistance among coagulase-negative staphylococci determined by whole-genome sequencing.

UnlabelledLinezolid resistance is uncommon among staphylococci, but approximately 2% of clinical isolates of coagulase-negative staphylococci (CoNS) may exhibit resistance to linezolid (MIC, ≥8 µg/ml). We performed whole-genome sequencing (WGS) to characterize the resistance mechanisms and genetic backgrounds of 28 linezolid-resistant CoNS (21 Staphylococcus epidermidis isolates and 7 Staphylococcus haemolyticus isolates) obtained from blood cultures at a large teaching health system in California between 2007 and 2012. The following well-characterized mutations associated with linezolid resistance were identified in the 23S rRNA: G2576U, G2447U, and U2504A, along with the mutation C2534U. Mutations in the L3 and L4 riboproteins, at sites previously associated with linezolid resistance, were also identified in 20 isolates. The majority of isolates harbored more than one mutation in the 23S rRNA and L3 and L4 genes. In addition, the cfr methylase gene was found in almost half (48%) of S. epidermidis isolates. cfr had been only rarely identified in staphylococci in the United States prior to this study. Isolates of the same sequence type were identified with unique mutations associated with linezolid resistance, suggesting independent acquisition of linezolid resistance in each isolate.ImportanceLinezolid is one of a limited number of antimicrobials available to treat drug-resistant Gram-positive bacteria, but resistance has begun to emerge. We evaluated the genomes of 28 linezolid-resistant staphylococci isolated from patients. Multiple mutations in the rRNA and associated proteins previously associated with linezolid resistance were found in the isolates investigated, underscoring the multifocal nature of resistance to linezolid in Staphylococcus. Importantly, almost half the S. epidermidis isolates studied harbored a plasmid-borne cfr RNA methylase gene, suggesting that the incidence of cfr may be higher in the United States than previously documented. This finding has important implications for infection control practices in the United States. Further, cfr is commonly detected in bacteria isolated from livestock, where the use of phenicols, lincosamides, and pleuromutilins in veterinary medicine may provide selective pressure and lead to maintenance of this gene in animal bacteria