303 research outputs found

    Magnetic Properties of the low dimensional spin system (VO)2_2P2_2O7_{7}: ESR and susceptibility

    Full text link
    Experimental results on magnetic resonance (ESR) and magnetic susceptibility are given for single crystalline (VO)2_2P2_2O7_{7}. The crystal growth procedure is briefly discussed. The susceptibility is interpreted numerically using a model with alternating spin chains. We determine JJ=51 K and δ\delta=0.2. Furthermore we find a spin gap of 6\approx 6meV from our ESR measurements. Using elastic constants no indication of a phase transition forcing the dimerization is seen below 300 K.Comment: 7 pages, REVTEX, 7 figure

    Unterschiede in Futteraufnahmeverhalten und Energieumsatz zwischen “genetisch schlanken” und “genetisch adipösen” Katern

    Full text link

    Melanocortin-4 receptor and proopiomelanocortin: Candidate genes for obesity in domestic shorthair cats

    Full text link
    Obesity is an escalating global health problem affecting both humans and companion animals. In cats it is associated with increased mortality and multiple diseases, including diabetes mellitus. Two genes coding for proteins known to play a critical role in energy homeostasis across species are the proopiomelanocortin (POMC) gene and the melanocortin-4 receptor (MC4R) gene. A missense variant in the coding sequence of the feline MC4R (MC4R:c.92C>T) has been reported to be associated with diabetes and overweight in domestic shorthair cats, and while variants in the POMC gene are known to cause obesity in humans and dogs, variants in POMC and their association with feline obesity and diabetes mellitus have not been investigated to date. The current study aimed to assess the association between the previously described MC4R variant and body condition score (BCS), as well as body fat content (%BF) in 89 non-diabetic domestic shorthair cats. Furthermore, we investigated the feline POMC gene as a potential candidate gene for obesity. Our results indicate that the MC4R:c.92C>T polymorphism is not associated with BCS or %BF in non-diabetic domestic shorthair cats. The mutation analysis of all POMC exons identified two missense variants, with a variant in exon 1 (c.28G>C; p.G10R) predicted to be damaging. The variant was subsequently assessed in all 89 cats, and cats heterozygous for the variant had a significantly increased body condition score (p = 0.03) compared with cats homozygous for the wild-type allele. Results from our study provide additional evidence that the previously described variant in MC4R is not associated with obesity in domestic shorthair cats. More importantly, we have identified a novel variant in the POMC gene, which might play a role in increased body condition score and body fat content in domestic shorthair cats

    Auswirkung der Fütterung von Springpferden auf Blutparameter des Energiestoffwechsels - Vergleich von Theorie und Praxis

    Full text link

    Monitoring of lung edema by microwave reflectometry during lung ischemia-reperfusion injury in vivo

    Get PDF
    It is still unclear whether lung edema can be monitored by microwave reflectometry and whether the measured changes in lung dry matter content (DMC) are accompanied by changes in PaO(2) and in pro-to anti-inflammatory cytokine expression (IFN-gamma and IL-10). Right rat lung hili were cross-clamped at 37 degrees C for 0, 60, 90 or 120 min ischemia followed by 120 min reperfusion. After 90 min (DMC: 15.9 +/- 1.4%; PaO(2): 76.7 +/- 18 mm Hg) and 120 min ischemia (DMC: 12.8 +/- 0.6%; PaO(2): 43 +/- 7 mm Hg), a significant decrease in DMC and PaO(2) throughout reperfusion compared to 0 min ischemia (DMC: 19.5 +/- 1.11%; PaO(2): 247 +/- 33 mm Hg; p < 0.05) was observed. DMC and PaO(2) decreased after 60 min ischemia but recovered during reperfusion (DMC: 18.5 +/- 2.4%; PaO(2) : 173 +/- 30 mm Hg). DMC values reflected changes on the physiological and molecular level. In conclusion, lung edema monitoring by microwave reflectometry might become a tool for the thoracic surgeon. Copyright (c) 2006 S. Karger AG, Basel

    Listen to genes : dealing with microarray data in the frequency domain

    Get PDF
    Background: We present a novel and systematic approach to analyze temporal microarray data. The approach includes normalization, clustering and network analysis of genes. Methodology: Genes are normalized using an error model based uniform normalization method aimed at identifying and estimating the sources of variations. The model minimizes the correlation among error terms across replicates. The normalized gene expressions are then clustered in terms of their power spectrum density. The method of complex Granger causality is introduced to reveal interactions between sets of genes. Complex Granger causality along with partial Granger causality is applied in both time and frequency domains to selected as well as all the genes to reveal the interesting networks of interactions. The approach is successfully applied to Arabidopsis leaf microarray data generated from 31,000 genes observed over 22 time points over 22 days. Three circuits: a circadian gene circuit, an ethylene circuit and a new global circuit showing a hierarchical structure to determine the initiators of leaf senescence are analyzed in detail. Conclusions: We use a totally data-driven approach to form biological hypothesis. Clustering using the power-spectrum analysis helps us identify genes of potential interest. Their dynamics can be captured accurately in the time and frequency domain using the methods of complex and partial Granger causality. With the rise in availability of temporal microarray data, such methods can be useful tools in uncovering the hidden biological interactions. We show our method in a step by step manner with help of toy models as well as a real biological dataset. We also analyse three distinct gene circuits of potential interest to Arabidopsis researchers

    Antidepressant effects of a single dose of ayahuasca in patients with recurrent depression: a preliminary report

    Get PDF
    Objectives: Ayahuasca (AYA), a natural psychedelic brew prepared from Amazonian plants and rich in dimethyltryptamine (DMT) and harmine, causes effects of subjective well-being and may therefore have antidepressant actions. This study sought to evaluate the effects of a single dose of AYA in six volunteers with a current depressive episode. Methods: Open-label trial conducted in an inpatient psychiatric unit. Results: Statistically significant reductions of up to 82% in depressive scores were observed between baseline and 1, 7, and 21 days after AYA administration, as measured on the Hamilton Rating Scale for Depression (HAM-D), the Montgomery-Åsberg Depression Rating Scale (MADRS), and the Anxious-Depression subscale of the Brief Psychiatric Rating Scale (BPRS). AYA administration resulted in nonsignificant changes in Young Mania Rating Scale (YMRS) scores and in the thinking disorder subscale of the BPRS, suggesting that AYA does not induce episodes of mania and/or hypomania in patients with mood disorders and that modifications in thought content, which could indicate psychedelic effects, are not essential for mood improvement. Conclusions: These results suggest that AYA has fast-acting anxiolytic and antidepressant effects in patients with a depressive disorder

    Electrochemical and immunoelectron microscopy evidence of lipid-protein interaction in Langmuir-Blodgett films of the human lung surfactant.

    No full text
    The extracellular lung surfactant surface film (ELSSF) which lines the mammalian lung alveoli at the alveolar air-aqueous cell surface interface is vital in both the breathing and the pulmonary defence processes. The molecular composition of, the structure of and the interaction in the ELSSF was studied, after the ELSSF of human lung lavages could be separated from the subphase and reassembled from its components by using the multicompartment Fromherz-type Langmuir-Blodgett trough. Transmission electron microscopy images of immunogold- labelled and negatively stained isolated film specimens were seen in a continuous layer of mostly phospholipid head groups surfactant-specific protein SpA molecules. Electrical double-layer capacitance and oxygen reduction potential measurements carried out by transferring the surface film from the air-water to a mercury-saline interface of a hanging mercury drop electrode revealed a strong lipid-protein SpA interaction. SpA molecules were partly squeezed out from the film by compression; a proteinless lipid film proved to be a condensed multilayer. Contact with SpA transformed the multilayer into a loose monomolecular film. It is suggested that SpA molecules play a lipid-transporting role, removing lipids in excess from the air-water interface into the aqueous subphase and vice versa. Lipid- protein interaction can be of importance in vivo. An explanation of how the surfactant film works during the two phases of breathing is proposed

    Learning causal networks from systems biology time course data: an effective model selection procedure for the vector autoregressive process

    Get PDF
    Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning these networks is challenging due to the low sample size and high dimensionality of genomic data. Results: We present a novel and highly efficient approach to estimate a VAR network. This proceeds in two steps: (i) improved estimation of VAR regression coefficients using an analytic shrinkage approach, and (ii) subsequent model selection by testing the associated partial correlations. In simulations this approach outperformed for small sample size all other considered approaches in terms of true discovery rate (number of correctly identified edges relative to the significant edges). Moreover, the analysis of expression time series data from Arabidopsis thaliana resulted in a biologically sensible network. Conclusion: Statistical learning of large-scale VAR causal models can be done efficiently by the proposed procedure, even in the difficult data situations prevalent in genomics and proteomics. Availability: The method is implemented in R code that is available from the authors on request

    Gene expression model (in)validation by Fourier analysis

    Get PDF
    The determination of the right model structure describing a gene regulation network and the identification of its parameters are major goals in systems biology. The task is often hampered by the lack of relevant experimental data with sufficiently low noise level, but the subset of genes whose concentration levels exhibit an oscillatory behavior in time can readily be analyzed on the basis of their Fourier spectrum, known to turn complex signals into few relatively noise-free parameters. Such genes therefore offer opportunities of understanding gene regulation quantitatively.Journal ArticleResearch Support, Non-U.S. Gov'tValidation StudiesSCOPUS: ar.jinfo:eu-repo/semantics/publishe