Antioxidative enzyme activities in human erythrocytes.

Reliable and standardized methods are necessary to determine the expression of antioxidative enzymes and their role in maintaining health. In addition, the variability of the enzyme activities within the general population caused by age, gender, and life-style factors must be described. This study describes methodological conditions that are suitable for analyzing copper–zinc superoxide dismutase (CuZn-SOD), glutathione peroxidase (GSH-Px), catalase (CAT), and glutathione reductase (GR) in human erythrocytes with a high degree of reproducibility. Intervals for the enzyme activities have been established in a randomly selected population of 220 individuals between 20 and 89 years of age. An age-related decrease was observed in CuZn-SOD and GR activities, whereas no age-related changes were demonstrated for GSH-Px and CAT. The GSH-Px activity was positively associated with the intake of dietary supplements and negatively correlated with tobacco consumption. These factors probably account for the fact that women tended to have higher GSH-Px activity

Bioethanol from Germinated Grains.

The most well-known way to produce bioethanol is by the enzymatic hydrolysis and fermentation of starch. In a new project “BioConcens” (2007) sponsored by DARCOF (DAnish Research Center for Organic Food and farming) one aim is to develop a combined ethanol and biogas production for use in organic farming using starch containing biomass. Natural enzymes from cereals will be used for hydrolysis of starch to glucose in accordance with technology in brewing technology. Commercial enzymes are often produced from gene-modified organisms and will therefore not be used in the suggested organic context or process. A preliminary study was performed in which grains of wheat, rye, and barley were germinated using traditional methods applied in malting for beer production. During malting the amylase enzymes present in the grain are activated (autoamylolytic effect). Three steps were applied in the malting process; steeping, germination, and drying of the grains. After malting the grains were milled and mixed with water to 13% DM, cooked at 57.5C for 2 hours (to activate the enzymes), and cooled to 30C before adding Bakers Yeast. The results of this study indicate that efficient hydrolysis of starch can be achieved by activation of autoamylolytic enzymes in cereal grains after a malting process. The ethanol yields obtained in the autoamylolytic hydrolysis was comparable (or slightly higher) to that of reference experiments using commercial enzymes (amylases). The highest ethanol yield was obtained with wheat (0.34 g/g DM grain), followed by barley (0.31 g/g DM grain), and rye (0.29 g/g DM grain)

Two-timescale carbon cycle response to an AMOC collapse

Atmospheric CO2 concentrations (pCO2) varied on millennial timescales in phase with Antarctic temperature during the last glacial period. A prevailing view has been that carbon release and uptake by the Southern Ocean dominated this millennial‐scale variability in pCO2. Here, using Earth System Model experiments with an improved parameterization of ocean vertical mixing, we find a major role for terrestrial and oceanic carbon releases in driving the pCO2 trend. In our simulations, a change in Northern Hemisphere insolation weakens the Atlantic Meridional Overturning Circulation (AMOC) leading to increasing pCO2 and Antarctic temperatures. The simulated rise in pCO2 is caused in equal parts by increased CO2 outgassing from the global ocean due to a reduced biological activity and changed ventilation rates, and terrestrial carbon release as a response to southward migration of the Intertropical Convergence Zone. The simulated terrestrial release of carbon could explain stadial declines in organic carbon reservoirs observed in recent ice core δ13C measurements. Our results show that parallel variations in Antarctic temperature and pCO2 do not necessitate that the Southern Ocean dominates carbon exchange; instead, changes in carbon flux from the global ocean and land carbon reservoirs can explain the observed pCO2 (and δ13C) changes

Involvement of a Natural Fusion of a Cytochrome P450 and a Hydrolase in Mycophenolic Acid Biosynthesis

Mycophenolic acid (MPA) is a fungal secondary metabolite and the active component in several immunosuppressive pharmaceuticals. The gene cluster coding for the MPA biosynthetic pathway has recently been discovered in Penicillium brevicompactum, demonstrating that the first step is catalyzed by MpaC, a polyketide synthase producing 5-methylorsellinic acid (5-MOA). However, the biochemical role of the enzymes encoded by the remaining genes in the MPA gene cluster is still unknown. Based on bioinformatic analysis of the MPA gene cluster, we hypothesized that the step following 5-MOA production in the pathway is carried out by a natural fusion enzyme MpaDE, consisting of a cytochrome P450 (MpaD) in the N-terminal region and a hydrolase (MpaE) in the C-terminal region. We verified that the fusion gene is indeed expressed in P. brevicompactum by obtaining full-length sequence of the mpaDE cDNA prepared from the extracted RNA. Heterologous coexpression of mpaC and the fusion gene mpaDE in the MPA-nonproducer Aspergillus nidulans resulted in the production of 5,7-dihydroxy-4-methylphthalide (DHMP), the second intermediate in MPA biosynthesis. Analysis of the strain coexpressing mpaC and the mpaD part of mpaDE shows that the P450 catalyzes hydroxylation of 5-MOA to 4,6-dihydroxy-2-(hydroxymethyl)-3-methylbenzoic acid (DHMB). DHMB is then converted to DHMP, and our results suggest that the hydrolase domain aids this second step by acting as a lactone synthase that catalyzes the ring closure. Overall, the chimeric enzyme MpaDE provides insight into the genetic organization of the MPA biosynthesis pathway

In situ metabolomic- and transcriptomic-profiling of the host-associated cyanobacteria Prochloron and Acaryochloris marina

© 2018 International Society for Microbial Ecology All rights reserved 1751-7362/18. The tropical ascidian Lissoclinum patella hosts two enigmatic cyanobacteria: (1) the photoendosymbiont Prochloron spp., a producer of valuable bioactive compounds and (2) the chlorophyll-d containing Acaryochloris spp., residing in the near-infrared enriched underside of the animal. Despite numerous efforts, Prochloron remains uncultivable, restricting the investigation of its biochemical potential to cultivation-independent techniques. Likewise, in both cyanobacteria, universally important parameters on light-niche adaptation and in situ photosynthetic regulation are unknown. Here we used genome sequencing, transcriptomics and metabolomics to investigate the symbiotic linkage between host and photoendosymbiont and simultaneously probed the transcriptional response of Acaryochloris in situ. During high light, both cyanobacteria downregulate CO 2 fixing pathways, likely a result of O 2 photorespiration on the functioning of RuBisCO, and employ a variety of stress-quenching mechanisms, even under less stressful far-red light (Acaryochloris). Metabolomics reveals a distinct biochemical modulation between Prochloron and L. patella, including noon/midnight-dependent signatures of amino acids, nitrogenous waste products and primary photosynthates. Surprisingly, Prochloron constitutively expressed genes coding for patellamides, that is, cyclic peptides of great pharmaceutical value, with yet unknown ecological significance. Together these findings shed further light on far-red-driven photosynthesis in natural consortia, the interplay of Prochloron and its ascidian partner in a model chordate photosymbiosis and the uncultivability of Prochloron

Consistent quantum mechanics admits no mereotopology

It is standardly assumed in discussions of quantum theory that physical systems can be regarded as having well-defined Hilbert spaces. It is shown here that a Hilbert space can be consistently partitioned only if its components are assumed not to interact. The assumption that physical systems have well-defined Hilbert spaces is, therefore, physically unwarranted.Comment: 10 pages; to appear in Axiomathe

Validation of nonlinear PCA

Linear principal component analysis (PCA) can be extended to a nonlinear PCA by using artificial neural networks. But the benefit of curved components requires a careful control of the model complexity. Moreover, standard techniques for model selection, including cross-validation and more generally the use of an independent test set, fail when applied to nonlinear PCA because of its inherent unsupervised characteristics. This paper presents a new approach for validating the complexity of nonlinear PCA models by using the error in missing data estimation as a criterion for model selection. It is motivated by the idea that only the model of optimal complexity is able to predict missing values with the highest accuracy. While standard test set validation usually favours over-fitted nonlinear PCA models, the proposed model validation approach correctly selects the optimal model complexity.Comment: 12 pages, 5 figure