Rupturing fungal cell walls for higher yield of polysaccharides: Acid treatment of the basidiomycete prior to extraction

The fungal cell wall of Agaricus bisporus powder was degraded by ethanol-acid treatment in order to improve the yield of the hot water extractions. Polysaccharides from multiple hot water extractions of treated and untreated mushroom were precipitated with ethanol and characterised separately. The treatment and the sequenced extractions changed the anomeric compositions, the molecular weights, and the sugar contents of the extracted polysaccharides. The total yield of the first extraction of treated A. bisporus increased by 46% with over 10 percentage points higher glucan content compared to untreated batch. Bioactivities were decreasing within the extraction batches and after the treatment. This was found to be connected to the amount of polysaccharides and the content of mannitol in the precipitates

Structural investigation of cell wall polysaccharides extracted from wild Finnish mushroom Craterellus tubaeformis (Funnel Chanterelle)

Craterellus tubaeformis (Funnel Chanterelle) is among the most abundant wild mushrooms in Finland. Three polysaccharide fractions were sequentially extracted from the fruiting bodies of C. tubaeformis, using hot water, 2% and 25% KOH solutions, respectively, and purified. The monomer composition, molecular weight, and chemical structure were determined using chromatographic and spectroscopic methods. Thermogravimetric analysis was performed as well. The hot water extract consisted mainly of high-molecular weight -> 2,6)-alpha-Man-(1 -> and -> 6)-alpha-Gal-(1 -> chains, covalently bound to proteins. The alkali extracts consisted of acidic -> 6)-beta-Glc-(1 ->, with branches of short -> 3)-beta-Glc-(1 -> chains or single beta-Glc residues. The use of alkali influenced the glycosidic linkages, molecular mass and thermal stability of the polysaccharide fractions. The use of KOH 2% increased the amount of low molecular weight polysaccharides, resulting in bimodal molecular weight distributions, with little impact on the thermal stability. Conversely, extraction with KOH 25% provided low molecular weight polysaccharides with substantially reduced thermal stability

Band-theoretical prediction of magnetic anisotropy in uranium monochalcogenides

Magnetic anisotropy of uranium monochalcogenides, US, USe and UTe, is studied by means of fully-relativistic spin-polarized band structure calculations within the local spin-density approximation. It is found that the size of the magnetic anisotropy is fairly large (about 10 meV/unit formula), which is comparable with experiment. This strong anisotropy is discussed in view of a pseudo-gap formation, of which crucial ingredients are the exchange splitting of U 5f states and their hybridization with chalcogen p states (f-p hybridization). An anomalous trend in the anisotropy is found in the series (US>>USe<UTe) and interpreted in terms of competition between localization of the U 5f states and the f-p hybridization. It is the spin-orbit interaction on the chalcogen p states that plays an essential role in enlarging the strength of the f-p hybridization in UTe, leading to an anomalous systematic trend in the magnetic anisotropy.Comment: 4 pages, 5 figure

Altered Metabolic Signature in Pre-Diabetic NOD Mice

Altered metabolism proceeding seroconversion in children progressing to Type 1 diabetes has previously been demonstrated. We tested the hypothesis that non-obese diabetic (NOD) mice show a similarly altered metabolic profile compared to C57BL/6 mice. Blood samples from NOD and C57BL/6 female mice was collected at 0, 1, 2, 3, 4, 5, 6, 7, 9, 11, 13 and 15 weeks and the metabolite content was analyzed using GC-MS. Based on the data of 89 identified metabolites OPLS-DA analysis was employed to determine the most discriminative metabolites. In silico analysis of potential involved metabolic enzymes was performed using the dbSNP data base. Already at 0 weeks NOD mice displayed a unique metabolic signature compared to C57BL/6. A shift in the metabolism was observed for both strains the first weeks of life, a pattern that stabilized after 5 weeks of age. Multivariate analysis revealed the most discriminative metabolites, which included inosine and glutamic acid. In silico analysis of the genes in the involved metabolic pathways revealed several SNPs in either regulatory or coding regions, some in previously defined insulin dependent diabetes (Idd) regions. Our result shows that NOD mice display an altered metabolic profile that is partly resembling the previously observation made in children progressing to Type 1 diabetes. The level of glutamic acid was one of the most discriminative metabolites in addition to several metabolites in the TCA cycle and nucleic acid components. The in silico analysis indicated that the genes responsible for this reside within previously defined Idd regions

Evaluation of O2PLS in Omics data integration

Background: Rapid computational and technological developments made large amounts of omics data available in different biological levels. It is becoming clear that simultaneous data analysis methods are needed for better interpretation and understanding of the underlying systems biology. Different methods have been proposed for this task, among them Partial Least Squares (PLS) related methods. To also deal with orthogonal variation, systematic variation in the data unrelated to one another, we consider the Two-way Orthogonal PLS (O2PLS): an integrative data analysis method which is capable of modeling systematic variation, while providing more parsimonious models aiding interpretation. Results: A simulation study to assess the performance of O2PLS showed positive results in both low and higher dimensions. More noise (50 % of the data) only affected the systematic part estimates. A data analysis was conducted using data on metabolomics and transcriptomics from a large Finnish cohort (DILGOM). A previous sequential study, using the same data, showed significant correlations between the Lipo-Leukocyte (LL) module and lipoprotein metabolites. The O2PLS results were in agreement with these findings, identifying almost the same set of co-varying variables. Moreover, our integrative approach identified other associative genes and metabolites, while taking into account systematic variation in the data. Including orthogonal components enhanced overall fit, but the orthogonal variation was difficult to interpret. Conclusions: Simulations showed that the O2PLS estimates were close to the true parameters in both low and higher dimensions. In the presence of more noise (50 %), the orthogonal part estimates could not distinguish well between joint and unique variation. The joint estimates were not systematically affected. Simultaneous analysis with O2PLS on metabolome and transcriptome data showed that the LL module, together with VLDL and HDL metabolites, were important for the metabolomic and transcriptomic relation. This is in agreement with an earlier study. In addition more gene expression and metabolites are identified being important for the joint covariation

Magnetocrystalline Anisotropy Energy of Transition Metal Thin Films: A Non-perturbative Theory

The magnetocrystalline anisotropy energy E(anis) of free-standing monolayers and thin films of Fe and Ni is determined using two different semi-empirical schemes. Within a tight-binding calculation for the 3d bands alone, we analyze in detail the relation between bandstructure and E(anis), treating spin-orbit coupling non-pertubatively. We find important contributions to E(anis) due to the lifting of band degeneracies near the Fermi level by SOC. The important role of degeneracies is supported by the calculation of the electron temperature dependence of the magnetocrystalline anisotropy energy, which decreases with the temperature increasing on a scale of several hundred K. In general, E(anis) scales with the square of the SOC constant. Including 4s bands and s-d hybridization, the combined interpolation scheme yields anisotropy energies that quantitatively agree well with experiments for Fe and Ni monolayers on Cu(001). Finally, the anisotropy energy is calculated for systems of up to 14 layers. Even after including s-bands and for multilayers, the importance of degeneracies persists. Considering a fixed fct-Fe structure, we find a reorientation of the magnetization from perpendicular to in-plane at about 4 layers. For Ni, we find the correct in-plane easy-axis for the monolayer. However, since the anisotropy energy remains nearly constant, we do not find the experimentally observed reorientation.Comment: 15 pages, Revtex, 15 postscript figure

Importance of Correlation Effects on Magnetic Anisotropy in Fe and Ni

We calculate magnetic anisotropy energy of Fe and Ni by taking into account the effects of strong electronic correlations, spin-orbit coupling, and non-collinearity of intra-atomic magnetization. The LDA+U method is used and its equivalence to dynamical mean-field theory in the static limit is emphasized. Both experimental magnitude of MAE and direction of magnetization are predicted correctly near U=4 eV for Ni and U=3.5 eV for Fe. Correlations modify one-electron spectra which are now in better agreement with experiments.Comment: 4 pages, 2 figure

Coulomb Correlations and Magnetic Anisotropy in ordered L10L1_0 CoPt and FePt alloys

We present results of the magneto-crystalline anisotropy energy (MAE) calculations for chemically ordered $L1_0$ CoPt and FePt alloys taking into account the effects of strong electronic correlations and spin-orbit coupling. The local spin density + Hubbard U approximation (LSDA+U) is shown to provide a consistent picture of the magnetic ground state properties when intra-atomic Coulomb correlations are included for both 3$d$ and 5$d$ elements. Our results demonstrate significant and complex contribution of correlation effects to large MAE of these material.Comment: revised version; 4 pages, 2 figure

Metabolic Signatures of Lung Cancer in Biofluids: NMR-Based Metabonomics of Blood Plasma

In this work, the variations in the metabolic profile of blood plasma from lung cancer patients and healthy controls were investigated through NMR-based metabonomics, to assess the potential of this approach for lung cancer screening and diagnosis. PLS-DA modeling of CPMG spectra from plasma, subjected to Monte Carlo Cross Validation, allowed cancer patients to be discriminated from controls with sensitivity and specificity levels of about 90%. Relatively lower HDL and higher VLDL + LDL in the patients' plasma, together with increased lactate and pyruvate and decreased levels of glucose, citrate, formate, acetate, several amino acids (alanine, glutamine, histidine, tyrosine, valine), and methanol, could be detected. These changes were found to be present at initial disease stages and could be related to known cancer biochemical hallmarks, such as enhanced glycolysis, glutaminolysis, and gluconeogenesis, together with suppressed Krebs cycle and reduced lipid catabolism, thus supporting the hypothesis of a systemic metabolic signature for lung cancer. Despite the possible confounding influence of age, smoking habits, and other uncontrolled factors, these results indicate that NMR-based metabonomics of blood plasma can be useful as a screening tool to identify suspicious cases for subsequent, more specific radiological tests, thus contributing to improved disease management.ERDF - Competitive Factors Thematic Operational ProgrammeFCT/PTDC/ QUI/68017/2006FCOMP-01-0124-FEDER-007439SFRH/BD/ 63430/2009National UNESCO Committee - L'Oréal Medals of Honor for Women in Science 200Portuguese National NMR Network - RNRM

Diagnostic properties of metabolic perturbations in rheumatoid arthritis

Introduction: The aim of this study was to assess the feasibility of diagnosing early rheumatoid arthritis (RA) by measuring selected metabolic biomarkers. Methods: We compared the metabolic profile of patients with RA with that of healthy controls and patients with psoriatic arthritis (PsoA). The metabolites were measured using two different chromatography-mass spectrometry platforms, thereby giving a broad overview of serum metabolites. The metabolic profiles of patient and control groups were compared using multivariate statistical analysis. The findings were validated in a follow-up study of RA patients and healthy volunteers. Results: RA patients were diagnosed with a sensitivity of 93% and a specificity of 70% in a validation study using detection of 52 metabolites. Patients with RA or PsoA could be distinguished with a sensitivity of 90% and a specificity of 94%. Glyceric acid, D-ribofuranose and hypoxanthine were increased in RA patients, whereas histidine, threonic acid, methionine, cholesterol, asparagine and threonine were all decreased compared with healthy controls. Conclusions: Metabolite profiling (metabolomics) is a potentially useful technique for diagnosing RA. The predictive value was without regard to the presence of antibodies against cyclic citrullinated peptides