Thermal equation of state of polarized fermions in one dimension via complex chemical potentials

We present a nonperturbative computation of the equation of state of polarized, attractively interacting, nonrelativistic fermions in one spatial dimension at finite temperature. We show results for the density, spin magnetization, magnetic susceptibility, and Tan's contact. We compare with the second-order virial expansion, a next-to-leading-order lattice perturbation theory calculation, and interpret our results in terms of pairing correlations. Our lattice Monte Carlo calculations implement an imaginary chemical potential difference to avoid the sign problem. The thermodynamic results on the imaginary side are analytically continued to obtain results on the real axis. We focus on an intermediate- to strong-coupling regime, and cover a wide range of temperatures and spin imbalances.Comment: 14 pages, 19 figures; published versio

Simultaneous quantitative and allele-specific expression analysis with real competitive PCR

Background: For a diploid organism such as human, the two alleles of a particular gene can be expressed at different levels due to X chromosome inactivation, gene imprinting, different local promoter activity, or mRNA stability. Recently, imbalanced allelic expression was found to be common in human and can follow Mendelian inheritance. Here we present a method that employs real competitive PCR for allele-specific expression analysis. Results: A transcribed mutation such as a single nucleotide polymorphism ( SNP) is used as the marker for allele-specific expression analysis. A synthetic mutation created in the competitor is close to a natural mutation site in the cDNA sequence. PCR is used to amplify the two cDNA sequences from the two alleles and the competitor. A base extension reaction with a mixture of ddNTPs/ dNTP is used to generate three oligonucleotides for the two cDNAs and the competitor. The three products are identified and their ratios are calculated based on their peak areas in the MALDI-TOF mass spectrum. Several examples are given to illustrate how allele-specific gene expression can be applied in different biological studies. Conclusions: This technique can quantify the absolute expression level of each individual allele of a gene with high precision and throughput

Guanosine nucleotides regulate B2 kinin receptor affinity of agonists but not of antagonists: Discussion of a model proposing receptor precoupling to G protein

The effect of nucleotides on binding of the B2 kinin (BK) receptor agonist {[}H-3]BK and the antagonist {[}H-3]NPC17731 to particulate fractions of human foreskin fibroblasts was studied. At 0 degrees C, particulate fractions exhibited a single class of binding sites with a Kd of 2.3 nM for {[}H-3]BK and a K-d Of 3.8 nM for the antagonist {[}H-3]NPC17731. Incubation with radioligands at 37 degrees C for 5 min gave a reduction of agonist, as well as antagonist, binding that was between 0-40% depending on the preparation, even in the absence of guanosine nucleotides. As shown by Scatchard analysis, this reduction in specific binding was due to a shift in the affinity of at least a fraction of the receptors. The presence at 37 degrees C of the guanine nucleotides GTP, GDP and their poorly hydrolyzable analogs left {[}H-3]-NPC17731 binding unaffected, but reduced the receptor affinity for {[}H-3]BK to a K-d Of about 15 nM. The maximal number of receptors, however, was unchanged. This affinity change was strongly dependent on the presence of bivalent cations, in particular Mg2+. It was reversed by incubation at 0 degrees C, The rank order of the guanosine nucleotides for {[}H-3]BK binding reduction was GTP{[}gamma S] = Gpp{[}NH]p > GTP = GDP > GDP{[}beta S]. GMP, ATP, ADP and AMP showed no influence on agonist binding. A model for the interaction of the B2 kinin receptor with G proteins is discussed

Metabolomics Unravel Contrasting Effects of Biodiversity on the Performance of Individual Plant Species

In spite of evidence for positive diversity-productivity relationships increasing plant diversity has highly variable effects on the performance of individual plant species, but the mechanisms behind these differential responses are far from being understood. To gain deeper insights into the physiological responses of individual plant species to increasing plant diversity we performed systematic untargeted metabolite profiling on a number of herbs derived from a grassland biodiversity experiment (Jena Experiment). The Jena Experiment comprises plots of varying species number (1, 2, 4, 8, 16 and 60) and number and composition of functional groups (1 to 4; grasses, legumes, tall herbs, small herbs). In this study the metabolomes of two tall-growing herbs (legume: Medicago x varia; non-legume: Knautia arvensis) and three small-growing herbs (legume: Lotus corniculatus; non-legumes: Bellis perennis, Leontodon autumnalis) in plant communities of increasing diversity were analyzed. For metabolite profiling we combined gas chromatography coupled to time-of-flight mass spectrometry (GC-TOF-MS) and UPLC coupled to FT-ICR-MS (LC-FT-MS) analyses from the same sample. This resulted in several thousands of detected m/z-features. ANOVA and multivariate statistical analysis revealed 139 significantly changed metabolites (30 by GC-TOF-MS and 109 by LC-FT-MS). The small-statured plants L. autumnalis, B. perennis and L. corniculatus showed metabolic response signatures to increasing plant diversity and species richness in contrast to tall-statured plants. Key-metabolites indicated C- and N-limitation for the non-leguminous small-statured species B. perennis and L. autumnalis, while the metabolic signature of the small-statured legume L. corniculatus indicated facilitation by other legumes. Thus, metabolomic analysis provided evidence for negative effects of resource competition on the investigated small-statured herbs that might mechanistically explain their decreasing performance with increasing plant diversity. In contrast, taller species often becoming dominant in mixed plant communities did not show modified metabolite profiles in response to altered resource availability with increasing plant diversity. Taken together, our study demonstrates that metabolite profiling is a strong diagnostic tool to assess individual metabolic phenotypes in response to plant diversity and ecophysiological adjustment

Opioid receptor activation triggering downregulation of cAMP improves effectiveness of anti-cancer drugs in treatment of glioblastoma

Glioblastoma are the most frequent and malignant human brain tumors, having a very poor prognosis. The enhanced radio- and chemoresistance of glioblastoma and the glioblastoma stem cells might be the main reason why conventional therapies fail. The second messenger cyclic AMP (cAMP) controls cell proliferation, differentiation, and apoptosis. Downregulation of cAMP sensitizes tumor cells for anti-cancer treatment. Opioid receptor agonists triggering opioid receptors can activate inhibitory Gi proteins, which, in turn, block adenylyl cyclase activity reducing cAMP. In this study, we show that downregulation of cAMP by opioid receptor activation improves the effectiveness of anti-cancer drugs in treatment of glioblastoma. The µ-opioid receptor agonist D,L-methadone sensitizes glioblastoma as well as the untreatable glioblastoma stem cells for doxorubicin-induced apoptosis and activation of apoptosis pathways by reversing deficient caspase activation and deficient downregulation of XIAP and Bcl-xL, playing critical roles in glioblastomas' resistance. Blocking opioid receptors using the opioid receptor antagonist naloxone or increasing intracellular cAMP by 3-isobutyl-1-methylxanthine (IBMX) strongly reduced opioid receptor agonist-induced sensitization for doxorubicin. In addition, the opioid receptor agonist D,L-methadone increased doxorubicin uptake and decreased doxorubicin efflux, whereas doxorubicin increased opioid receptor expression in glioblastomas. Furthermore, opioid receptor activation using D,L-methadone inhibited tumor growth significantly in vivo. Our findings suggest that opioid receptor activation triggering downregulation of cAMP is a promising strategy to inhibit tumor growth and to improve the effectiveness of anti-cancer drugs in treatment of glioblastoma and in killing glioblastoma stem cells

Cell death sensitization of leukemia cells by opioid receptor activation

Cyclic AMP (cAMP) regulates a number of cellular processes and modulates cell death induction. cAMP levels are altered upon stimulation of specific G-protein-coupled receptors inhibiting or activating adenylyl cyclases. Opioid receptor stimulation can activate inhibitory Gi-proteins which in turn block adenylyl cyclase activity reducing cAMP. Opioids such as D,L-methadone induce cell death in leukemia cells. However, the mechanism how opioids trigger apoptosis and activate caspases in leukemia cells is not understood. In this study, we demonstrate that downregulation of cAMP induced by opioid receptor activation using the opioid D,L-methadone kills and sensitizes leukemia cells for doxorubicin treatment. Enhancing cAMP levels by blocking opioid-receptor signaling strongly reduced D,L-methadone-induced apoptosis, caspase activation and doxorubicin-sensitivity. Induction of cell death in leukemia cells by activation of opioid receptors using the opioid D,L-methadone depends on critical levels of opioid receptor expression on the cell surface. Doxorubicin increased opioid receptor expression in leukemia cells. In addition, the opioid D,L-methadone increased doxorubicin uptake and decreased doxorubicin efflux in leukemia cells, suggesting that the opioid D,L-methadone as well as doxorubicin mutually increase their cytotoxic potential. Furthermore, we found that opioid receptor activation using D,L-methadone alone or in addition to doxorubicin inhibits tumor growth significantly in vivo. These results demonstrate that opioid receptor activation via triggering the downregulation of cAMP induces apoptosis, activates caspases and sensitizes leukemia cells for doxorubicin treatment. Hence, opioid receptor activation seems to be a promising strategy to improve anticancer therapies