Astrophysical Axion Bounds

Axion emission by hot and dense plasmas is a new energy-loss channel for stars. Observational consequences include a modification of the solar sound-speed profile, an increase of the solar neutrino flux, a reduction of the helium-burning lifetime of globular-cluster stars, accelerated white-dwarf cooling, and a reduction of the supernova SN 1987A neutrino burst duration. We review and update these arguments and summarize the resulting axion constraints.Comment: Contribution to Axion volume of Lecture Notes in Physics, 20 pages, 3 figure

Magnetic order in spin-1 and spin-3/2 interpolating square-triangle Heisenberg antiferromagnets

Using the coupled cluster method we investigate spin-$s$ $J_{1}$-$J_{2}'$ Heisenberg antiferromagnets (HAFs) on an infinite, anisotropic, triangular lattice when the spin quantum number $s=1$ or $s=3/2$. With respect to a square-lattice geometry the model has antiferromagnetic ($J_{1} > 0$) bonds between nearest neighbours and competing ($J_{2}' > 0$) bonds between next-nearest neighbours across only one of the diagonals of each square plaquette, the same one in each square. In a topologically equivalent triangular-lattice geometry, we have two types of nearest-neighbour bonds: namely the $J_{2}' \equiv \kappa J_{1}$ bonds along parallel chains and the $J_{1}$ bonds producing an interchain coupling. The model thus interpolates between an isotropic HAF on the square lattice at $\kappa = 0$ and a set of decoupled chains at $\kappa \rightarrow \infty$, with the isotropic HAF on the triangular lattice in between at $\kappa = 1$. For both the $s=1$ and the $s=3/2$ models we find a second-order quantum phase transition at $\kappa_{c}=0.615 \pm 0.010$ and $\kappa_{c}=0.575 \pm 0.005$ respectively, between a N\'{e}el antiferromagnetic state and a helical state. In both cases the ground-state energy $E$ and its first derivative $dE/d\kappa$ are continuous at $\kappa=\kappa_{c}$, while the order parameter for the transition (viz., the average on-site magnetization) does not go to zero on either side of the transition. The transition at $\kappa = \kappa_{c}$ for both the $s=1$ and $s=3/2$ cases is analogous to that observed in our previous work for the $s=1/2$ case at a value $\kappa_{c}=0.80 \pm 0.01$. However, for the higher spin values the transition is of continuous (second-order) type, as in the classical case, whereas for the $s=1/2$ case it appears to be weakly first-order in nature (although a second-order transition could not be excluded).Comment: 17 pages, 8 figues (Figs. 2-7 have subfigs. (a)-(d)

Imetelstat-mediated alterations in fatty acid metabolism to induce ferroptosis as a therapeutic strategy for acute myeloid leukemia

Telomerase enables replicative immortality in most cancers including acute myeloid leukemia (AML). Imetelstat is a first-in-class telomerase inhibitor with clinical efficacy in myelofibrosis and myelodysplastic syndromes. Here, we develop an AML patient-derived xenograft resource and perform integrated genomics, transcriptomics and lipidomics analyses combined with functional genetics to identify key mediators of imetelstat efficacy. In a randomized phase II-like preclinical trial in patient-derived xenografts, imetelstat effectively diminishes AML burden and preferentially targets subgroups containing mutant NRAS and oxidative stress-associated gene expression signatures. Unbiased, genome-wide CRISPR/Cas9 editing identifies ferroptosis regulators as key mediators of imetelstat efficacy. Imetelstat promotes the formation of polyunsaturated fatty acid-containing phospholipids, causing excessive levels of lipid peroxidation and oxidative stress. Pharmacological inhibition of ferroptosis diminishes imetelstat efficacy. We leverage these mechanistic insights to develop an optimized therapeutic strategy using oxidative stress-inducing chemotherapy to sensitize patient samples to imetelstat causing substantial disease control in AML

C-rasH and ornithine decarboxylase are induced by oestradiol-17β in the mouse uterine luminal epithelium independently of the proliferative status of the cell

AbstractOestradiol-17 β (E2) treatment of the ovariectomized mouse results in a synchronised wave of cell proliferation in the uterine luminal epithelium. At the peak of DNA synthesis the mRNA level of the c-rasH protooncogene and ornithine decarboxylase were significantly increased. Progesterone treatment completely inhibits the E2 induced wave of DNA synthesis but does not greatly influence the level of these 2 mRNAs. Thus in the uterine luminal epithelium E2 regulates the level of ornithine decarboxylase and c-rasH independently of cell proliferation

Bayesian Metanetwork for Context-Sensitive Feature Relevance

Abstract. Bayesian Networks are proven to be a comprehensive model to describe causal relationships among domain attributes with probabilistic measure of appropriate conditional dependency. However, depending on task and context, many attributes of the model might not be relevant. If a network has been learned across multiple contexts then all uncovered conditional dependencies are averaged over all contexts and cannot guarantee high predictive accuracy when applied to a concrete case. We are considering a context as a set of contextual attributes, which are not directly effect probability distribution of the target attributes, but they effect on a “relevance ” of the predictive attributes towards target attributes. In this paper we use the Bayesian Metanetwork vision to model such context-sensitive feature relevance. Such model assumes that the relevance of predictive attributes in a Bayesian network might be a random attribute itself and it provides a tool to reason based not only on probabilities of predictive attributes but also on their relevancies. According to this model, the evidence observed about contextual attributes is used to extract a relevant substructure from a Bayesian network model and then the predictive attributes evidence is used to reason about probability distribution of the target attribute in the extracted sub-network. We provide the basic architecture for such Bayesian Metanetwork, basic reasoning formalism and some examples.