Real-time correlators in warped AdS/CFT correspondence

We study real-time correlators in the warped AdS/CFT correspondence. We apply the prescription used in the usual AdS/CFT correspondence and obtain the retarded Green's functions for the scalar and vector fields in the spacelike warped and the null warped black hole backgrounds. We find that the retarded Green's functions and the cross sections are well consistent with the predictions from dual CFT. Our results not only support strongly the conjectured warped AdS/CFT correspondence, but also show that the usual relativistic AdS/CFT prescription of obtaining the real-time correlators remain effective in more general backgrounds with anisotropic conformal infinity.Comment: 27 page

Photocurrent measurements of supercollision cooling in graphene

The cooling of hot electrons in graphene is the critical process underlying the operation of exciting new graphene-based optoelectronic and plasmonic devices, but the nature of this cooling is controversial. We extract the hot electron cooling rate near the Fermi level by using graphene as novel photothermal thermometer that measures the electron temperature ($T(t)$) as it cools dynamically. We find the photocurrent generated from graphene $p-n$ junctions is well described by the energy dissipation rate $C dT/dt=-A(T^3-T_l^3)$, where the heat capacity is $C=\alpha T$ and $T_l$ is the base lattice temperature. These results are in disagreement with predictions of electron-phonon emission in a disorder-free graphene system, but in excellent quantitative agreement with recent predictions of a disorder-enhanced supercollision (SC) cooling mechanism. We find that the SC model provides a complete and unified picture of energy loss near the Fermi level over the wide range of electronic (15 to $\sim$3000 K) and lattice (10 to 295 K) temperatures investigated.Comment: 7pages, 5 figure

The identification of informative genes from multiple datasets with increasing complexity

Background In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes. Results In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes. Conclusions We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events

Association between the c.*229C>T polymorphism of the topoisomerase IIb binding protein 1 (TopBP1) gene and breast cancer

Topoisomerase IIb binding protein 1 (TopBP1) is involved in cell survival, DNA replication, DNA damage repair and cell cycle checkpoint control. The biological function of TopBP1 and its close relation with BRCA1 prompted us to investigate whether alterations in the TopBP1 gene can influence the risk of breast cancer. The aim of this study was to examine the association between five polymorphisms (rs185903567, rs116645643, rs115160714, rs116195487, and rs112843513) located in the 30UTR region of the TopBP1 gene and breast cancer risk as well as allele-specific gene expression. Five hundred thirty-four breast cancer patients and 556 population controls were genotyped for these SNPs. Allele-specific Top- BP1 mRNA and protein expressions were determined by using real time PCR and western blotting methods, respectively. Only one SNP (rs115160714) showed an association with breast cancer. Compared to homozygous common allele carriers, heterozygous and homozygous for the T variant had significantly increased risk of breast cancer (adjusted odds ratio = 3.81, 95 % confidence interval: 1.63–8.34, p = 0.001). Mean TopBP1 mRNA and protein expression were higher in the individuals with the CT or TT genotype. There was a significant association between the rs115160714 and tumor grade and stage. Most carriers of minor allele had a high grade (G3) tumors classified as T2-T4N1M0. Our study raises a possibility that a genetic variation of TopBP1 may be implicated in the etiology of breast cancer

Observation of the nonlinear Hall effect under time reversal symmetric conditions

The electrical Hall effect is the production of a transverse voltage under an out-of-plane magnetic field. Historically, studies of the Hall effect have led to major breakthroughs including the discoveries of Berry curvature and the topological Chern invariants. In magnets, the internal magnetization allows Hall conductivity in the absence of external magnetic field. This anomalous Hall effect (AHE) has become an important tool to study quantum magnets. In nonmagnetic materials without external magnetic fields, the electrical Hall effect is rarely explored because of the constraint by time-reversal symmetry. However, strictly speaking, only the Hall effect in the linear response regime, i.e., the Hall voltage linearly proportional to the external electric field, identically vanishes due to time-reversal symmetry. The Hall effect in the nonlinear response regime, on the other hand, may not be subject to such symmetry constraints. Here, we report the observation of the nonlinear Hall effect (NLHE) in the electrical transport of the nonmagnetic 2D quantum material, bilayer WTe2. Specifically, flowing an electrical current in bilayer WTe2 leads to a nonlinear Hall voltage in the absence of magnetic field. The NLHE exhibits unusual properties sharply distinct from the AHE in metals: The NLHE shows a quadratic I-V characteristic; It strongly dominates the nonlinear longitudinal response, leading to a Hall angle of about 90 degree. We further show that the NLHE directly measures the "dipole moment" of the Berry curvature, which arises from layer-polarized Dirac fermions in bilayer WTe2. Our results demonstrate a new Hall effect and provide a powerful methodology to detect Berry curvature in a wide range of nonmagnetic quantum materials in an energy-resolved way

Proximity curves for potential-based clustering

YesThe concept of proximity curve and a new algorithm are proposed for obtaining clusters in a finite set of data points in the finite dimensional Euclidean space. Each point is endowed with a potential constructed by means of a multi-dimensional Cauchy density, contributing to an overall anisotropic potential function. Guided by the steepest descent algorithm, the data points are successively visited and removed one by one, and at each stage the overall potential is updated and the magnitude of its local gradient is calculated. The result is a finite sequence of tuples, the proximity curve, whose pattern is analysed to give rise to a deterministic clustering. The finite set of all such proximity curves in conjunction with a simulation study of their distribution results in a probabilistic clustering represented by a distribution on the set of dendrograms. A two-dimensional synthetic data set is used to illustrate the proposed potential-based clustering idea. It is shown that the results achieved are plausible since both the ‘geographic distribution’ of data points as well as the ‘topographic features’ imposed by the potential function are well reflected in the suggested clustering. Experiments using the Iris data set are conducted for validation purposes on classification and clustering benchmark data. The results are consistent with the proposed theoretical framework and data properties, and open new approaches and applications to consider data processing from different perspectives and interpret data attributes contribution to patterns

A physical organogel electrolyte: Characterized by in situ thermo-irreversible gelation and single-ion-predominent conduction

Electrolytes are characterized by their ionic conductivity (??i). It is desirable that overall ??i results from the dominant contribution of the ions of interest (e.g. Li+ in lithium ion batteries or LIB). However, high values of cationic transference number (t+) achieved by solid or gel electrolytes have resulted in low ??i leading to inferior cell performances. Here we present an organogel polymer electrolyte characterized by a high liquid-electrolyte- level ??i (???101 mS cm-1) with high t+ of Li+ (>0.8) for LIB. A conventional liquid electrolyte in presence of a cyano resin was physically and irreversibly gelated at 60 ??C without any initiators and crosslinkers, showing the behavior of lower critical solution temperature. During gelation, ??i of the electrolyte followed a typical Arrhenius-type temperature dependency, even if its viscosity increased dramatically with temperature. Based on the Li + -driven ion conduction, LIB using the organogel electrolyte delivered significantly enhanced cyclability and thermal stability.open5

Phenethyl isothiocyanate exhibits antileukemic activity in vitro and in vivo by inactivation of Akt and activation of JNK pathways

Effects of phenethyl isothiocyanate (PEITC) have been investigated in human leukemia cells (U937, Jurkat, and HL-60) as well as in primary human acute myeloid leukemia (AML) cells in relation to apoptosis and cell signaling events. Exposure of cells to PEITC resulted in pronounced increase in the activation of caspase-3, -8, -9, cleavage/degradation of PARP, and apoptosis in dose- and time-dependent manners. These events were accompanied by the caspase-independent downregulation of Mcl-1, inactivation of Akt, as well as activation of Jun N-terminal kinase (JNK). Inhibition of PI3K/Akt by LY294002 significantly enhanced PEITC-induced apoptosis. Conversely, enforced activation of Akt by a constitutively active Akt construct markedly abrogated PEITC-mediated JNK activation, Mcl-1 downregulation, caspase activation, and apoptosis, and also interruption of the JNK pathway by pharmacological or genetically (e.g., siRNA) attenuated PEITC-induced apoptosis. Finally, administration of PEITC markedly inhibited tumor growth and induced apoptosis in U937 xenograft model in association with inactivation of Akt, activation of JNK, as well as downregulation of Mcl-1. Taken together, these findings represent a novel mechanism by which agents targeting Akt/JNK/Mcl-1 pathway potentiate PEITC lethality in transformed and primary human leukemia cells and inhibitory activity of tumor growth of U937 xenograft model

Contribution of Cell Elongation to the Biofilm Formation of Pseudomonas aeruginosa during Anaerobic Respiration

Pseudomonas aeruginosa, a gram-negative bacterium of clinical importance, forms more robust biofilm during anaerobic respiration, a mode of growth presumed to occur in abnormally thickened mucus layer lining the cystic fibrosis (CF) patient airway. However, molecular basis behind this anaerobiosis-triggered robust biofilm formation is not clearly defined yet. Here, we identified a morphological change naturally accompanied by anaerobic respiration in P. aeruginosa and investigated its effect on the biofilm formation in vitro. A standard laboratory strain, PAO1 was highly elongated during anaerobic respiration compared with bacteria grown aerobically. Microscopic analysis demonstrated that cell elongation likely occurred as a consequence of defective cell division. Cell elongation was dependent on the presence of nitrite reductase (NIR) that reduces nitrite (NO2−) to nitric oxide (NO) and was repressed in PAO1 in the presence of carboxy-PTIO, a NO antagonist, demonstrating that cell elongation involves a process to respond to NO, a spontaneous byproduct of the anaerobic respiration. Importantly, the non-elongated NIR-deficient mutant failed to form biofilm, while a mutant of nitrate reductase (NAR) and wild type PAO1, both of which were highly elongated, formed robust biofilm. Taken together, our data reveal a role of previously undescribed cell biological event in P. aeruginosa biofilm formation and suggest NIR as a key player involved in such process

L-Ilf3 and L-NF90 Traffic to the Nucleolus Granular Component: Alternatively-Spliced Exon 3 Encodes a Nucleolar Localization Motif

Ilf3 and NF90, two proteins containing double-stranded RNA-binding domains, are generated by alternative splicing and involved in several functions. Their heterogeneity results from posttranscriptional and posttranslational modifications. Alternative splicing of exon 3, coding for a 13 aa N-terminal motif, generates for each protein a long and short isoforms. Subcellular fractionation and localization of recombinant proteins showed that this motif acts as a nucleolar localization signal. Deletion and substitution mutants identified four arginines, essential for nucleolar targeting, and three histidines to stabilize the proteins within the nucleolus. The short isoforms are never found in the nucleoli, whereas the long isoforms are present in the nucleoplasm and the nucleoli. For Ilf3, only the posttranslationally-unmodified long isoform is nucleolar, suggesting that this nucleolar targeting is abrogated by posttranslational modifications. Confocal microscopy and FRAP experiments have shown that the long Ilf3 isoform localizes to the granular component of the nucleolus, and that L-Ilf3 and L-NF90 exchange rapidly between nucleoli. The presence of this 13 aminoacid motif, combined with posttranslational modifications, is responsible for the differences in Ilf3 and NF90 isoforms subcellular localizations. The protein polymorphism of Ilf3/NF90 and the various subcellular localizations of their isoforms may partially explain the various functions previously reported for these proteins