Antiferromagnetically coupled alternating spin chains

The effect of antiferromagnetic interchain coupling in alternating spin (1,1/2) chains is studied by mean of a spin wave theory and density matrix renormalization group (DMRG). In particular, two limiting cases are investigated, the two-leg ladder and its two dimensional (2D) generalization. Results of the ground state properties like energy, spin gap, magnetizations, and correlation functions are reported for the whole range of the interchain coupling $J_{\perp}$. For the 2D case the spin wave results predict a smooth dimensional crossover from 1D to 2D keeping the ground state always ordered. For the ladder system, the DMRG results show that any $J_{\perp}>0$ drives the system to a gapped ground state. Furthermore the behaviour of the correlation functions closely resemble the uniform spin-1/2 ladder. For $J_{\perp}$ lower than 0.3, however, the gap behaves quadratically as $\Delta\sim0.6 J^2_{\perp}$. Finally, it is argued that the behaviour of the spin gap for an arbitrary number of mixed coupled spin chains is analogous to that of the uniform spin-1/2 chains.Comment: 5 pages, 7 ps-figure

β-Cell Hyperplasia Induced by Hepatic Insulin Resistance: Role of a Liver-Pancreas Endocrine Axis Through Insulin Receptor A Isoform

Objective: Type 2 diabetes results from a combination of insulin resistance and impaired insulin secretion. To directly address the effects of hepatic insulin resistance in adult animals, we developed an inducible liver-specific insulin receptor knockout mouse (iLIRKO). Research Design and Methods: Using this approach, we were able to induce variable insulin receptor (IR) deficiency in a tissue-specific manner (liver mosaicism). Results: iLIRKO mice presented progressive hepatic and extrahepatic insulin resistance without liver dysfunction. Initially, iLIRKO mice displayed hyperinsulinemia and increased $\beta$-cell mass, the extent of which was proportional to the deletion of hepatic IR. Our studies of iLIRKO suggest a cause-and-effect relationship between progressive insulin resistance and the fold increase of plasma insulin levels and $\beta$-cell mass. Ultimately, the $\beta$-cells failed to secrete sufficient insulin, leading to uncontrolled diabetes. We observed that hepatic IGF-1 expression was enhanced in iLIRKO mice, resulting in an increase of circulating IGF-1. Concurrently, the IR-A isoform was upregulated in hyperplastic $\beta$-cells of iLIRKO mice and IGF-1–induced proliferation was higher than in the controls. In mouse $\beta$-cell lines, IR-A, but not IR-B, conferred a proliferative capacity in response to insulin or IGF-1, providing a potential explanation for the $\beta$-cell hyperplasia induced by liver insulin resistance in iLIRKO mice. Conclusions: Our studies of iLIRKO mice suggest a liver-pancreas endocrine axis in which IGF-1 functions as a liver-derived growth factor to promote compensatory pancreatic islet hyperplasia through IR-A

Lysine harvesting is an antioxidant strategy and triggers underground polyamine metabolism

Both single and multicellular organisms depend on anti-stress mechanisms that enable them to deal with sudden changes in the environment, including exposure to heat and oxidants. Central to the stress response are dynamic changes in metabolism, such as the transition from the glycolysis to the pentose phosphate pathway—a conserved first-line response to oxidative insults1,2. Here we report a second metabolic adaptation that protects microbial cells in stress situations. The role of the yeast polyamine transporter Tpo1p3,4,5 in maintaining oxidant resistance is unknown6. However, a proteomic time-course experiment suggests a link to lysine metabolism. We reveal a connection between polyamine and lysine metabolism during stress situations, in the form of a promiscuous enzymatic reaction in which the first enzyme of the polyamine pathway, Spe1p, decarboxylates lysine and forms an alternative polyamine, cadaverine. The reaction proceeds in the presence of extracellular lysine, which is taken up by cells to reach concentrations up to one hundred times higher than those required for growth. Such extensive harvest is not observed for the other amino acids, is dependent on the polyamine pathway and triggers a reprogramming of redox metabolism. As a result, NADPH—which would otherwise be required for lysine biosynthesis—is channelled into glutathione metabolism, leading to a large increase in glutathione concentrations, lower levels of reactive oxygen species and increased oxidant tolerance. Our results show that nutrient uptake occurs not only to enable cell growth, but when the nutrient availability is favourable it also enables cells to reconfigure their metabolism to preventatively mount stress protection

Potassium Starvation in Yeast: Mechanisms of Homeostasis Revealed by Mathematical Modeling

The intrinsic ability of cells to adapt to a wide range of environmental conditions is a fundamental process required for survival. Potassium is the most abundant cation in living cells and is required for essential cellular processes, including the regulation of cell volume, pH and protein synthesis. Yeast cells can grow from low micromolar to molar potassium concentrations and utilize sophisticated control mechanisms to keep the internal potassium concentration in a viable range. We developed a mathematical model for Saccharomyces cerevisiae to explore the complex interplay between biophysical forces and molecular regulation facilitating potassium homeostasis. By using a novel inference method (“the reverse tracking algorithm”) we predicted and then verified experimentally that the main regulators under conditions of potassium starvation are proton fluxes responding to changes of potassium concentrations. In contrast to the prevailing view, we show that regulation of the main potassium transport systems (Trk1,2 and Nha1) in the plasma membrane is not sufficient to achieve homeostasis

Inferring time-derivatives including cell growth rates using Gaussian processes

Often the time derivative of a measured variable is of as much interest as the variable itself. For a growing population of biological cells, for example, the population's growth rate is typically more important than its size. Here we introduce a non-parametric method to infer first and second time derivatives as a function of time from time-series data. Our approach is based on Gaussian processes and applies to a wide range of data. In tests, the method is at least as accurate as others, but has several advantages: it estimates errors both in the inference and in any summary statistics, such as lag times, and allows interpolation with the corresponding error estimation. As illustrations, we infer growth rates of microbial cells, the rate of assembly of an amyloid fibril and both the speed and acceleration of two separating spindle pole bodies. Our algorithm should thus be broadly applicable

Bumble bee parasite strains vary in resistance to phytochemicals

Nectar and pollen contain diverse phytochemicals that can reduce disease in pollinators. However, prior studies showed variable effects of nectar chemicals on infection, which could reflect variable phytochemical resistance among parasite strains. Inter-strain variation in resistance could influence evolutionary interactions between plants, pollinators, and pollinator disease, but testing direct effects of phytochemicals on parasites requires elimination of variation between bees. Using cell cultures of the bumble bee parasite Crithidia bombi, we determined (1) growth-inhibiting effects of nine floral phytochemicals and (2) variation in phytochemical resistance among four parasite strains. C. bombi growth was unaffected by naturally occurring concentrations of the known antitrypanosomal phenolics gallic acid, caffeic acid, and chlorogenic acid. However, C. bombi growth was inhibited by anabasine, eugenol, and thymol. Strains varied >3-fold in phytochemical resistance, suggesting that selection for phytochemical resistance could drive parasite evolution. Inhibitory concentrations of thymol (4.53-22.2 ppm) were similar to concentrations in Thymus vulgaris nectar (mean 5.2 ppm). Exposure of C. bombi to naturally occurring levels of phytochemicals—either within bees or during parasite transmission via flowers—could influence infection in nature. Flowers that produce antiparasitic phytochemical, including thymol, could potentially reduce infection in Bombus populations, thereby counteracting a possible contributor to pollinator decline