Topological and magnetic phase transitions in the bilayer Kitaev-Ising model

We investigate the phase diagram of a bilayer Kitaev honeycomb model with Ising interlayer interactions, deriving effective models via perturbation theory and performing Majorana mean-field theory calculations. We show that a diverse array of magnetic and topological phase transitions occur, depending on the direction of the interlayer Ising interaction and the relative sign of Kitaev interactions. When two layers have the same sign of the Kitaev interaction, a first-order transition from a Kitaev spin liquid to a magnetically ordered state takes place. The magnetic order points along the Ising axis and it is (anti)ferromagnetic for (anti)ferromagnetic Kitaev interactions. However, when two layers have opposite sign of the Kitaev interaction, we observe a notable weakening of magnetic ordering tendencies and the Kitaev spin liquid survives up to a remarkably larger interlayer exchange. Our mean-field analysis suggests the emergence of an intermediate gapped $\mathbb{Z}_2$ spin liquid state, which eventually becomes unstable upon vison condensation. The confined phase is described by a highly frustrated $120^\circ$ compass model. We furthermore use perturbation theory to study the model with the Ising axis pointing along $\hat{z}$-axis or lying in the $xy$-plane. In both cases, our analysis reveals the formation of 1D Ising chains, which remain decoupled in perturbation theory, resulting in a subextensive ground-state degeneracy. Our results highlight the interplay between topological order and magnetic ordering tendencies in bilayer quantum spin liquids.Comment: 10 pages, 5 figure

Association rule mining based study for identification of clinical parameters akin to occurrence of brain tumor

Healthcare sector is generating a large amount of information corresponding to diagnosis, disease identification and treatment of an individual. Mining knowledge and providing scientific decision-making for the diagnosis & treatment of disease from the clinical dataset is therefore increasingly becoming necessary. Aim of this study was to assess the applicability of knowledge discovery in brain tumor data warehouse, applying data mining techniques for investigation of clinical parameters that can be associated with occurrence of brain tumor. In this study, a brain tumor warehouse was developed comprising of clinical data for 550 patients. Apriori association rule algorithm was applied to discover associative rules among the clinical parameters. The rules discovered in the study suggests - high values of Creatinine, Blood Urea Nitrogen (BUN), SGOT & SGPT to be directly associated with tumor occurrence for patients in the primary stage with atleast 85% confidence and more than 50% support. A normalized regression model is proposed based on these parameters along with Haemoglobin content, Alkaline Phosphatase and Serum Bilirubin for prediction of occurrence of STATE (brain tumor) as 0 (absent) or 1 (present). The results indicate that the methodology followed will be of good value for the diagnostic procedure of brain tumor, especially when large data volumes are involved and screening based on discovered parameters would allow clinicians to detect tumors at an early stage of development

Characterization of Multi-Functional Properties and Conformational Analysis of MutS2 from Thermotoga maritima MSB8

The MutS2 homologues have received attention because of their unusual activities that differ from those of MutS. In this work, we report on the functional characteristics and conformational diversities of Thermotoga maritima MutS2 (TmMutS2). Various biochemical features of the protein were demonstrated via diverse techniques such as scanning probe microscopy (SPM), ATPase assays, analytical ultracentrifugation, DNA binding assays, size chromatography, and limited proteolytic analysis. Dimeric TmMutS2 showed the temperature-dependent ATPase activity. The non-specific nicking endonuclease activities of TmMutS2 were inactivated in the presence of nonhydrolytic ATP (ADPnP) and enhanced by the addition of TmMutL. In addition, TmMutS2 suppressed the TmRecA-mediated DNA strand exchange reaction in a TmMutL-dependent manner. We also demonstrated that small-angle X-ray scattering (SAXS) analysis of dimeric TmMutS2 exhibited nucleotide- and DNA-dependent conformational transitions. Particularly, TmMutS2-ADPnP showed the most compressed form rather than apo-TmMutS2 and the TmMutS2-ADP complex, in accordance with the results of biochemical assays. In the case of the DNA-binding complexes, the stretched conformation appeared in the TmMutS2-four-way junction (FWJ)-DNA complex. Convergences of biochemical- and SAXS analysis provided abundant information for TmMutS2 and clarified ambiguous experimental results

Gene-Trap Mutagenesis Identifies Mammalian Genes Contributing to Intoxication by Clostridium perfringens ε-Toxin

The Clostridium perfringens ε-toxin is an extremely potent toxin associated with lethal toxemias in domesticated ruminants and may be toxic to humans. Intoxication results in fluid accumulation in various tissues, most notably in the brain and kidneys. Previous studies suggest that the toxin is a pore-forming toxin, leading to dysregulated ion homeostasis and ultimately cell death. However, mammalian host factors that likely contribute to ε-toxin-induced cytotoxicity are poorly understood. A library of insertional mutant Madin Darby canine kidney (MDCK) cells, which are highly susceptible to the lethal affects of ε-toxin, was used to select clones of cells resistant to ε-toxin-induced cytotoxicity. The genes mutated in 9 surviving resistant cell clones were identified. We focused additional experiments on one of the identified genes as a means of validating the experimental approach. Gene expression microarray analysis revealed that one of the identified genes, hepatitis A virus cellular receptor 1 (HAVCR1, KIM-1, TIM1), is more abundantly expressed in human kidney cell lines than it is expressed in human cells known to be resistant to ε-toxin. One human kidney cell line, ACHN, was found to be sensitive to the toxin and expresses a larger isoform of the HAVCR1 protein than the HAVCR1 protein expressed by other, toxin-resistant human kidney cell lines. RNA interference studies in MDCK and in ACHN cells confirmed that HAVCR1 contributes to ε-toxin-induced cytotoxicity. Additionally, ε-toxin was shown to bind to HAVCR1 in vitro. The results of this study indicate that HAVCR1 and the other genes identified through the use of gene-trap mutagenesis and RNA interference strategies represent important targets for investigation of the process by which ε-toxin induces cell death and new targets for potential therapeutic intervention