Abstract. We present PCR-GLOBWB 2, a global hydrology and water resources model. Compared to previous versions of PCR-GLOBWB, this version fully integrates water use. Sector-specific water demand, groundwater and surface water withdrawal, water consumption, and return flows are dynamically calculated at every time step and interact directly with the simulated hydrology. PCR-GLOBWB 2 has been fully rewritten in Python and PCRaster Python and has a modular structure, allowing easier replacement, maintenance, and development of model components. PCR-GLOBWB 2 has been implemented at 5 arcmin resolution, but a version parameterized at 30 arcmin resolution is also available. Both versions are available as open-source codes on https://github.com/UU-Hydro/PCR-GLOBWB_model (Sutanudjaja et al., 2017a). PCR-GLOBWB 2 has its own routines for groundwater dynamics and surface water routing. These relatively simple routines can alternatively be replaced by dynamically coupling PCR-GLOBWB 2 to a global two-layer groundwater model and 1-D–2-D hydrodynamic models. Here, we describe the main components of the model, compare results of the 30 and 5 arcmin versions, and evaluate their model performance using Global Runoff Data Centre discharge data. Results show that model performance of the 5 arcmin version is notably better than that of the 30 arcmin version. Furthermore, we compare simulated time series of total water storage (TWS) of the 5 arcmin model with those observed with GRACE, showing similar negative trends in areas of prevalent groundwater depletion. Also, we find that simulated total water withdrawal matches reasonably well with reported water withdrawal from AQUASTAT, while water withdrawal by source and sector provide mixed results.

The circadian oscillator of the cyanobacterium Synechococcus elongatus, like those in eukaryotes, is entrained by environmental cues. Inactivation of the gene cikA (circadian input kinase) shortens the circadian period of gene expression rhythms in S. elongatus by approximately 2 hours, changes the phasing of a subset of rhythms, and nearly abolishes resetting of phase by a pulse of darkness. The CikA protein sequence reveals that it is a divergent bacteriophytochrome with characteristic histidine protein kinase motifs and a cryptic response regulator motif. CikA is likely a key component of a pathway that provides environmental input to the circadian oscillator in S. elongatus.

SUMMARY This review summarizes recent aspects of (di)nitrogen fixation and (di)hydrogen metabolism, with emphasis on cyanobacteria. These organisms possess several types of the enzyme complexes catalyzing N2 fixation and/or H2 formation or oxidation, namely, two Mo nitrogenases, a V nitrogenase, and two hydrogenases. The two cyanobacterial Ni hydrogenases are differentiated as either uptake or bidirectional hydrogenases. The different forms of both the nitrogenases and hydrogenases are encoded by different sets of genes, and their organization on the chromosome can vary from one cyanobacterium to another. Factors regulating the expression of these genes are emerging from recent studies. New ideas on the potential physiological and ecological roles of nitrogenases and hydrogenases are presented. There is a renewed interest in exploiting cyanobacteria in solar energy conversion programs to generate H2 as a source of combustible energy. To enhance the rates of H2 production, the emphasis perhaps needs not to be on more efficient hydrogenases and nitrogenases or on the transfer of foreign enzymes into cyanobacteria. A likely better strategy is to exploit the use of radiant solar energy by the photosynthetic electron transport system to enhance the rates of H2 formation and so improve the chances of utilizing cyanobacteria as a source for the generation of clean energy.

BACKGROUND:Metabolomics is a valuable tool with applications in almost all life science areas. There is an increasing awareness of the essential need for high-quality biospecimens in studies applying omics technologies and biomarker research. Tools to detect effects of both blood and plasma processing are a key for assuring reproducible and credible results. We report on the response of the human plasma metabolome to common preanalytical variations in a comprehensive metabolomics analysis to reveal such high-quality markers.

An 8.9-kb segment with hydrogenase genes from the cyanobacterium Anabaena variabilis has been cloned and sequenced. The sequences show homology to the methyl-viologen-reducing hydrogenases from archaebacteria and, even more striking, to the NAD'-reducing enzymes from Alcaligenes eutrophus and Nocardia opaca as well as to the NADP' -dependent protein from Desulfovibrio fructosovorarzs. The cluster from A. variabilis contains genes coding for both the hydrogenase heterodimer (hoxH and hoxv and for the diaphorase moiety (hoxU and hoxfl described for the A. eurroplius enzyme. In A. variabilis the gene cluster is split by two open reading frames (between hoxY and hoxH and between hoxU and hoxl: respectively), and a probably non-coding 0.9-kb segment in an unusual way. The hoxH partial sequence from Anabaena 71 19 and Anucystis nidulan.7 was amplified by PCR. Using the labeled segment from A. 71 19 as probe, Southern analysis revealed homologous gene segments in the cyanobacteria A. 71 19, Anabaena cylindrica, Arzacystis nidulans and A. variabilis. The bidirectional hydrogenase from A. nidulans was purified and digests were sequenced. The amino acid sequences obtained showed partial identities to the amino acid sequences deduced from the DNA data of the 8.9-kb segment from A. variabilis. Therefore the 8.9-kb segment contains the genes coding for the bidirectional, reversible hydrogenase from cyanobacteria. Crude extracts from A. nidulans perform NAD(P)H-dependent H, evolution corroborating the molecular biological demonstration of the NAD(P)'.-dependent hydrogenase in cyanobacteria.

Process-based spatio-temporal models simulate changes over time using equations that represent real world processes. They are widely applied in geography and earth science. Software implementation of the model itself and integrating model results with observations through data assimilation are two important steps in the model development cycle. Unlike most software frameworks that provide tools for either implementation of the model or data assimilation, this paper describes a software framework that integrates both steps. The software framework includes generic operations on 2D map and 3D block data that can be combined in a Python script using a framework for time iterations and Monte Carlo simulation. In addition, the framework contains components for data assimilation with the Ensemble Kalman Filter and the Particle filter. Two case studies of distributed hydrological models show how the framework integrates model construction and data assimilation.

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive loss of cognitive functions. Today the diagnosis of AD relies on clinical evaluations and is only late in the disease. Biomarkers for early detection of the underlying neuropathological changes are still lacking and the biochemical pathways leading to the disease are still not completely understood. The aim of this study was to identify the metabolic changes resulting from the disease phenotype by a thorough and systematic metabolite profiling approach. For this purpose CSF samples from 79 AD patients and 51 healthy controls were analyzed by gas and liquid chromatography-tandem mass spectrometry (GC-MS and LC-MS/MS) in conjunction with univariate and multivariate statistical analyses. In total 343 different analytes have been identified. Significant changes in the metabolite profile of AD patients compared to healthy controls have been identified. Increased cortisol levels seemed to be related to the progression of AD and have been detected in more severe forms of AD. Increased cysteine associated with decreased uridine was the best paired combination to identify light AD (MMSE>22) with specificity and sensitivity above 75%. In this group of patients, sensitivity and specificity above 80% were obtained for several combinations of three to five metabolites, including cortisol and various amino acids, in addition to cysteine and uridine.

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