Yangian Symmetry for Bi-Scalar Loop Amplitudes

We establish an all-loop conformal Yangian symmetry for the full set of planar amplitudes in the recently proposed integrable bi-scalar field theory in four dimensions. This chiral theory is a particular double scaling limit of gamma-twisted weakly coupled N=4 SYM theory. Each amplitude with a certain order of scalar particles is given by a single fishnet Feynman graph of disc topology cut out of a regular square lattice. The Yangian can be realized by the action of a product of Lax operators with a specific sequence of inhomogeneity parameters on the boundary of the disc. Based on this observation, the Yangian generators of level one for generic bi-scalar amplitudes are explicitly constructed. Finally, we comment on the relation to the dual conformal symmetry of these scattering amplitudes.Comment: 40 pages, 20 figure

Causal Inference in Strategic Performance Measurement Systems and Its Effect on Performance Evaluations: A Laboratory Experiment

This study aims to test the effect of explicit representation of causal relationships in strategy map component of balanced scorecards BSC on performance evaluations outcomes. To address this aim, a 2 × 2 factorial design laboratory experiment was conducted, where the inclusion of graphical information supporting causal relationships between objectives in strategy maps, and performance outcome patterns (positive vs. negative) across performance measurement perspectives of BCSs were manipulated. The findings show that the observed performance evaluation scores are driven more significantly by the performance outcomes in the outer perspectives of BSCs (financial and learning & growth) than by inner perspectives (internal business processes and customer). It was also confirmed that the difference in performance evaluation scores between two identically structured BSCs with positive versus negative performance outcomes in the outer perspectives is relatively larger in the presence of the strategy map versus when the ordered strategic objective list is presented

Tumor promoter TPA activates Wnt/β-catenin signaling in a casein kinase 1-dependent manner.

The tumor promoter 12-O-tetra-decanoylphorbol-13-acetate (TPA) has been defined by its ability to promote tumorigenesis on carcinogen-initiated mouse skin. Activation of Wnt/β-catenin signaling has a decisive role in mouse skin carcinogenesis, but it remains unclear how TPA activates Wnt/β-catenin signaling in mouse skin carcinogenesis. Here, we found that TPA could enhance Wnt/β-catenin signaling in a casein kinase 1 (CK1) ε/δ-dependent manner. TPA stabilized CK1ε and enhanced its kinase activity. TPA further induced the phosphorylation of LRP6 at Thr1479 and Ser1490 and the formation of a CK1ε-LRP6-axin1 complex, leading to an increase in cytosolic β-catenin. Moreover, TPA increased the association of β-catenin with TCF4E in a CK1ε/δ-dependent way, resulting in the activation of Wnt target genes. Consistently, treatment with a selective CK1ε/δ inhibitor SR3029 suppressed TPA-induced skin tumor formation in vivo, probably through blocking Wnt/β-catenin signaling. Taken together, our study has identified a pathway by which TPA activates Wnt/β-catenin signaling

Multifactor Models and Their Consistency with the APT

We examine the consistency of several prominent multifactor models from the empirical asset pricing literature with the arbitrage pricing theory (APT) framework. We follow the APT-related literature and estimate the common factor structure from a rich cross-section (associated with 42 major CAPM anomalies) by employing the asymptotic principal components method. Our benchmark model contains six statistical factors and clearly dominates, in both economic and statistical terms, most of the empirical multifactor models proposed in the literature by a good margin. These results represent a critical challenge to the current workhorse models in terms of explaining large-scale equity risk premiums

Estimating species trees using multiple-allele DNA sequence data

Several techniques, such as concatenation and consensus methods, are available for combining data from multiple loci to produce a single statement of phylogenetic relationships. However, when multiple alleles are sampled from individual species, it becomes more challenging to estimate relationships at the level of species, either because concatenation becomes inappropriate due to conflicts among individual gene trees, or because the species from which multiple alleles have been sampled may not form monophyletic groups in the estimated tree. We propose a Bayesian hierarchical model to reconstruct species trees from multiple-allele, multilocus sequence data, building on a recently proposed method for estimating species trees from single allele multilocus data. A two-step Markov Chain Monte Carlo (MCMC) algorithm is adopted to estimate the posterior distribution of the species tree. The model is applied to estimate the posterior distribution of species trees for two multiple-allele datasets - yeast (Saccharomyces) and birds (Manacus - manakins). The estimates of the species trees using our method are consistent with those inferred from other methods and genetic markers, but in contrast to other species tree methods, it provides credible regions for the species tree. The Bayesian approach described here provides a powerful framework for statistical testing and integration of population genetics and phylogenetics. © 2008 The Author(s)

The role of human cytochrome P450 2E1 in liver inflammation and fibrosis.

Cytochrome P450 2E1 (CYP2E1) plays an important role in alcohol and toxin metabolism by catalyzing the conversion of substrates into more polar metabolites and producing reactive oxygen species. Reactive oxygen species-induced oxidative stress promotes hepatocyte injury and death, which in turn induces inflammation, activation of hepatic stellate cells, and liver fibrosis. Here, we analyzed mice expressing only the human CYP2E1 gene (hCYP2E1) to determine differences in hCYP2E1 versus endogenous mouse Cyp2e1 function with different liver injuries. After intragastric alcohol feeding, CYP2E1 expression was induced in both hCYP2E1 and wild-type (Wt) mice. hCYP2E1 mice had greater inflammation, fibrosis, and lipid peroxidation but less hepatic steatosis. In addition, hCYP2E1 mice demonstrated increased expression of fibrogenic and proinflammatory genes but decreased expression of de novo lipogenic genes compared to Wt mice. Lipidomics of free fatty acid, triacylglycerol, diacylglycerol, and cholesterol ester species and proinflammatory prostaglandins support these conclusions. Carbon tetrachloride-induced injury suppressed expression of both mouse and human CYP2E1, but again hCYP2E1 mice exhibited greater hepatic stellate cell activation and fibrosis than Wt controls with comparable expression of proinflammatory genes. By contrast, 14-day bile duct ligation induced comparable cholestatic injury and fibrosis in both genotypes. Conclusion: Alcohol-induced liver fibrosis but not hepatic steatosis is more severe in the hCYP2E1 mouse than in the Wt mouse, demonstrating the use of this model to provide insight into the pathogenesis of alcoholic liver disease. (Hepatology Communications 2017;1:1043-1057)