933 resultados para Anaerobic methanotrophic archaea-1a, number of sequences


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A sequential design method is presented for the design of thermally coupled distillation sequences. The algorithm starts by selecting a set of sequences in the space of basic configurations in which the internal structure of condensers and reboilers is explicitly taken into account and extended with the possibility of including divided wall columns (DWC). This first stage is based on separation tasks (except by the DWCs) and therefore it does not provide an actual sequence of columns. In the second stage the best arrangement in N-1 actual columns is performed taking into account operability and mechanical constraints. Finally, for a set of candidate sequences the algorithm try to reduce the number of total columns by considering Kaibel columns, elimination of transfer blocks or columns with vertical partitions. An example illustrate the different steps of the sequential algorithm.

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We generated draft genome sequences for two cold-adapted Archaea, Methanogenium frigidum and Methanococcoides burtonii, to identify genotypic characteristics that distinguish them from Archaea with a higher optimal growth temperature (OGT). Comparative genomics revealed trends in amino acid and tRNA composition, and structural features of proteins. Proteins from the cold-adapted Archaea are characterized by a higher content of noncharged polar amino acids, particularly Gin and Thr and a lower content of hydrophobic amino acids, particularly Leu. Sequence data from nine methanogen genomes (OGT 15degrees-98degreesC) were used to generate IIII modeled protein structures. Analysis of the models from the cold-adapted Archaea showed a strong tendency in the solvent-accessible area for more Gin, Thr, and hydrophobic residues and fewer charged residues. A cold shock domain (CSD) protein (CspA homolog) was identified in M. frigidum, two hypothetical proteins with CSD-folds in M. burtonii, and a unique winged helix DNA-binding domain protein in M. burtonii. This suggests that these types of nucleic acid binding proteins have a critical role in cold-adapted Archaea. Structural analysis of tRNA sequences from the Archaea indicated that GC content is the major factor influencing tRNA stability in hyperthermophiles, but not in the psychrophiles, mesophiles or moderate thermophiles. Below an OGT of 60degreesC, the GC content in tRNA was largely unchanged, indicating that any requirement for flexibility of tRNA in psychrophiles is mediated by other means. This is the first time that comparisons have been performed with genome data from Archaea spanning the growth temperature extremes. from psychrophiles to hyperthermophiles

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Translational pausing may occur due to a number of mechanisms, including the presence of non-optimal codons, and it is thought to play a role in the folding of specific polypeptide domains during translation and in the facilitation of signal peptide recognition during see-dependent protein targeting. In this whole genome analysis of Escherichia coli we have found that non-optimal codons in the signal peptide-encoding sequences of secretory genes are overrepresented relative to the mature portions of these genes; this is in addition to their overrepresentation in the 5'-regions of genes encoding non-secretory proteins. We also find increased non-optimal codon usage at the 3' ends of most E. coli genes, in both non-secretory and secretory sequences. Whereas presumptive translational pausing at the 5' and 3' ends of E. coli messenger RNAs may clearly have a general role in translation, we suggest that it also has a specific role in sec-dependent protein export, possibly in facilitating signal peptide recognition. This finding may have important implications for our understanding of how the majority of non-cytoplasmic proteins are targeted, a process that is essential to all biological cells. (C) 2004 Elsevier Inc. All rights reserved.

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Background: Protein tertiary structure can be partly characterized via each amino acid's contact number measuring how residues are spatially arranged. The contact number of a residue in a folded protein is a measure of its exposure to the local environment, and is defined as the number of C-beta atoms in other residues within a sphere around the C-beta atom of the residue of interest. Contact number is partly conserved between protein folds and thus is useful for protein fold and structure prediction. In turn, each residue's contact number can be partially predicted from primary amino acid sequence, assisting tertiary fold analysis from sequence data. In this study, we provide a more accurate contact number prediction method from protein primary sequence. Results: We predict contact number from protein sequence using a novel support vector regression algorithm. Using protein local sequences with multiple sequence alignments (PSI-BLAST profiles), we demonstrate a correlation coefficient between predicted and observed contact numbers of 0.70, which outperforms previously achieved accuracies. Including additional information about sequence weight and amino acid composition further improves prediction accuracies significantly with the correlation coefficient reaching 0.73. If residues are classified as being either contacted or non-contacted, the prediction accuracies are all greater than 77%, regardless of the choice of classification thresholds. Conclusion: The successful application of support vector regression to the prediction of protein contact number reported here, together with previous applications of this approach to the prediction of protein accessible surface area and B-factor profile, suggests that a support vector regression approach may be very useful for determining the structure-function relation between primary sequence and higher order consecutive protein structural and functional properties.

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The aim of the study presented was to implement a process model to simulate the dynamic behaviour of a pilot-scale process for anaerobic two-stage digestion of sewage sludge. The model implemented was initiated to support experimental investigations of the anaerobic two-stage digestion process. The model concept implemented in the simulation software package MATLAB(TM)/Simulink(R) is a derivative of the IWA Anaerobic Digestion Model No.1 (ADM1) that has been developed by the IWA task group for mathematical modelling of anaerobic processes. In the present study the original model concept has been adapted and applied to replicate a two-stage digestion process. Testing procedures, including balance checks and 'benchmarking' tests were carried out to verify the accuracy of the implementation. These combined measures ensured a faultless model implementation without numerical inconsistencies. Parameters for both, the thermophilic and the mesophilic process stage, have been estimated successfully using data from lab-scale experiments described in literature. Due to the high number of parameters in the structured model, it was necessary to develop a customised procedure that limited the range of parameters to be estimated. The accuracy of the optimised parameter sets has been assessed against experimental data from pilot-scale experiments. Under these conditions, the model predicted reasonably well the dynamic behaviour of a two-stage digestion process in pilot scale. (C) 2004 Elsevier Ltd. All rights reserved.

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Starting with a UML specification that captures the underlying functionality of some given Java-based concurrent system, we describe a systematic way to construct, from this specification, test sequences for validating an implementation of the system. The approach is to first extend the specification to create UML state machines that directly address those aspects of the system we wish to test. To be specific, the extended UML state machines can capture state information about the number of waiting threads or the number of threads blocked on a given object. Using the SAL model checker we can generate from the extended UML state machines sequences that cover all the various possibilities of events and states. These sequences can then be directly transformed into test sequences suitable for input into a testing tool such as ConAn. As an illustration, the methodology is applied to generate sequences for testing a Java implementation of the producer-consumer system. © 2005 IEEE

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A detailed knowledge of the mapping between sequence and structure spaces in populations of RNA molecules is essential to better understand their present-day functional properties, to envisage a plausible early evolution of RNA in a prebiotic chemical environment and to improve the design of in vitro evolution experiments, among others. Analysis of natural RNAs, as well as in vitro and computational studies, show that certain RNA structural motifs are much more abundant than others, pointing out a complex relation between sequence and structure. Within this framework, we have investigated computationally the structural properties of a large pool (10 molecules) of single-stranded, 35 nt-long, random RNA sequences. The secondary structures obtained are ranked and classified into structure families. The number of structures in main families is analytically calculated and compared with the numerical results. This permits a quantification of the fraction of structure space covered by a large pool of sequences. We further show that the number of structural motifs and their frequency is highly unbalanced with respect to the nucleotide composition: simple structures such as stem-loops and hairpins arise from sequences depleted in G, while more complex structures require an enrichment of G. In general, we observe a strong correlation between subfamilies-characterized by a fixed number of paired nucleotides-and nucleotide composition. Our results are compared to the structural repertoire obtained in a second pool where isolated base pairs are prohibited. © 2008 Elsevier Ltd. All rights reserved.

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Background The HIV virus is known for its ability to exploit numerous genetic and evolutionary mechanisms to ensure its proliferation, among them, high replication, mutation and recombination rates. Sliding MinPD, a recently introduced computational method [1], was used to investigate the patterns of evolution of serially-sampled HIV-1 sequence data from eight patients with a special focus on the emergence of X4 strains. Unlike other phylogenetic methods, Sliding MinPD combines distance-based inference with a nonparametric bootstrap procedure and automated recombination detection to reconstruct the evolutionary history of longitudinal sequence data. We present serial evolutionary networks as a longitudinal representation of the mutational pathways of a viral population in a within-host environment. The longitudinal representation of the evolutionary networks was complemented with charts of clinical markers to facilitate correlation analysis between pertinent clinical information and the evolutionary relationships. Results Analysis based on the predicted networks suggests the following:: significantly stronger recombination signals (p = 0.003) for the inferred ancestors of the X4 strains, recombination events between different lineages and recombination events between putative reservoir virus and those from a later population, an early star-like topology observed for four of the patients who died of AIDS. A significantly higher number of recombinants were predicted at sampling points that corresponded to peaks in the viral load levels (p = 0.0042). Conclusion Our results indicate that serial evolutionary networks of HIV sequences enable systematic statistical analysis of the implicit relations embedded in the topology of the structure and can greatly facilitate identification of patterns of evolution that can lead to specific hypotheses and new insights. The conclusions of applying our method to empirical HIV data support the conventional wisdom of the new generation HIV treatments, that in order to keep the virus in check, viral loads need to be suppressed to almost undetectable levels.

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Bio-systems are inherently complex information processing systems. Furthermore, physiological complexities of biological systems limit the formation of a hypothesis in terms of behavior and the ability to test hypothesis. More importantly the identification and classification of mutation in patients are centric topics in today's cancer research. Next generation sequencing (NGS) technologies can provide genome-wide coverage at a single nucleotide resolution and at reasonable speed and cost. The unprecedented molecular characterization provided by NGS offers the potential for an individualized approach to treatment. These advances in cancer genomics have enabled scientists to interrogate cancer-specific genomic variants and compare them with the normal variants in the same patient. Analysis of this data provides a catalog of somatic variants, present in tumor genome but not in the normal tissue DNA. In this dissertation, we present a new computational framework to the problem of predicting the number of mutations on a chromosome for a certain patient, which is a fundamental problem in clinical and research fields. We begin this dissertation with the development of a framework system that is capable of utilizing published data from a longitudinal study of patients with acute myeloid leukemia (AML), who's DNA from both normal as well as malignant tissues was subjected to NGS analysis at various points in time. By processing the sequencing data at the time of cancer diagnosis using the components of our framework, we tested it by predicting the genomic regions to be mutated at the time of relapse and, later, by comparing our results with the actual regions that showed mutations (discovered at relapse time). We demonstrate that this coupling of the algorithm pipeline can drastically improve the predictive abilities of searching a reliable molecular signature. Arguably, the most important result of our research is its superior performance to other methods like Radial Basis Function Network, Sequential Minimal Optimization, and Gaussian Process. In the final part of this dissertation, we present a detailed significance, stability and statistical analysis of our model. A performance comparison of the results are presented. This work clearly lays a good foundation for future research for other types of cancer.^

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Large amounts of the greenhouse gas methane are released from the seabed to the water column where it may be consumed by aerobic methanotrophic bacteria. This microbial filter is consequently the last marine sink for methane before its liberation to the atmosphere. The size and activity of methanotrophic communities, which determine the capacity of the water column methane filter, are thought to be mainly controlled by nutrient and redox dynamics, but little is known about the effects of ocean currents. Here, we report measurements of methanotrophic activity and biomass (CARD-FISH) at methane seeps west of Svalbard, and related them to physical water mass properties (CTD) and modelled current dynamics. We show that cold bottom water containing a large number of aerobic methanotrophs was rapidly displaced by warmer water with a considerably smaller methanotrophic community. This water mass exchange, caused by short-term variations of the West Spitsbergen Current, constitutes a rapid oceanographic switch severely reducing methanotrophic activity in the water column. Strong and fluctuating currents are widespread oceanographic features common at many methane seep systems and are thus likely to globally affect methane oxidation in the ocean water column.

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Geological, mineralogical and microbiological aspects of the methane cycle in water and sediments of different areas in the oceans are under consideration in the monograph. Original and published estimations of formation- and oxidation rates of methane with use of radioisotope and isotopic methods are given. The role of aerobic and anaerobic microbial oxidation of methane in production of organic matter and in formation of authigenic carbonates is considered. Particular attention is paid to processes of methane transformation in areas of its intensive input to the water column from deep-sea hydrothermal sources, mud volcanoes, and cold methane seeps.

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Authigenic minerals can form in the water column and sediments of lakes, either abiotically or mediated by biological activity. Such minerals have been used as paleosalinity and paleoproductivity indicators and reflect trophic state and early diagenetic conditions. They are also considered potential indicators of past and perhaps ongoing microbial activity within sediments. Authigenic concretions, including vivianite, were described in late glacial sediments of Laguna Potrok Aike, a maar lake in southernmost Argentina. Occurrence of iron phosphate implies specific phosphorus sorption behavior and a reducing environment, with methane present. Because organic matter content in these sediments was generally low during glacial times, there must have been alternative sources of phosphorus and biogenic methane. Identifying these sources can help define past trophic state of the lake and diagenetic processes in the sediments. We used scanning electron microscopy, phosphorus speciation in bulk sediment, pore water analyses, in situ ATP measurements, microbial cell counts, and measurements of methane content and its carbon isotope composition (d13C CH4) to identify components of and processes in the sediment. The multiple approaches indicated that volcanic materials in the catchment are important suppliers of iron, sulfur and phosphorus. These elements influence primary productivity and play a role in microbial metabolism during early diagenesis. Authigenic processes led to the formation of pyrite framboids and revealed sulfate reduction. Anaerobic oxidation of methane and shifts in pore water ion concentration indicated microbial influence with depth. This study documents the presence of active microbes within the sediments and their relationship to changing environmental conditions. It also illustrates the substantial role played by microbes in the formation of Laguna Potrok Aike concretions. Thus, authigenic minerals can be used as biosignatures in these late Pleistocene maar sediments.

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Fluorescence in situ hybridization (FISH) with 16S rRNA-targeted oligonucleotide probes were used to investigate the phylogenetic composition of a marine Arctic sediment (Svalbard). Hybridization and microscopy counts of hybridized and 4',6'-diamidino-2-phenylindole (DAPI)-stained cells were performed as described previously from Snaidr et al. (1997, http://aem.asm.org/content/63/7/2884.full.pdf). Means were calculated from 10 to 20 randomly chosen fields on each filter section, corresponding to 800 to 1,000 DAPI-stained cells. Counting results were always corrected by subtracting signals observed with the probe NON338. Formamide concentrations are given in further details. FISH resulted in the detection of a large fraction of microbes living in the top 5 cm of the sediment. Up to 65.4% ± 7.5% of total DAPI cell counts hybridized to the bacterial probe EUB338, and up to 4.9% ± 1.5% hybridized to the archaeal probe ARCH915. Besides delta-proteobacterial sulfate-reducing bacteria (up to 16% 52) members of the Cytophaga-Flavobacterium cluster were the most abundant group detected in this sediment, accounting for up to 12.8% of total DAPI cell counts. Furthermore, members of the order Planctomycetales accounted for up to 3.9% of total cell counts. In accordance with previous studies, these findings support the hypothesis that these bacterial groups are not simply settling with organic matter from the pelagic zone but are indigenous to the anoxic zones of marine sediments. Members of the gamma-proteobacteria also constituted a significant fraction in this sediment (6.1% ± 2.5% of total cell counts). A new probe (GAM660) specific for sequences affiliated with free-living or endosymbiotic sulfur-oxidizing bacteria was developed. A significant number of cells was detected by this probe (2.1% ± 0.7% of total DAPI cell counts), showing no clear zonation along the vertical profile. Gram-positive bacteria and the beta-proteobacteria were near the detection limit in all sediments.

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The human activities responsible for the ambient degradation in the modern world are diverse. The industrial activities are preponderant in the question of the impact consequences for brazilian ecosystems. Amongst the human activities, the petroliferous industry in operation in Potiguar Petroliferous Basin (PPB) displays the constant risk of ambient impacts in the integrant cities, not only for the human populations and the environment, but also it reaches the native microorganisms of Caatinga ground and in the mangrove sediment. Not hindering, the elaboration of strategies of bioremediation for impacted areas pass through the knowledge of microbiota and its relations with the environment. Moreover, in the microorganism groups associated to oil, are emphasized the sulfate-reducing prokaryotes (SRP) that, in its anaerobic metabolism, these organisms participate of the sulfate reduction, discharging H2S, causing ambient risks and causing the corrosion of surfaces, as pipelines and tanks, resulting in damages for the industry. Some ancestries of PRS integrate the Archaea domain, group of microorganisms whose sequenced genomes present predominance of extremophilic adaptations, including surrounding with oil presence. This work has two correlated objectives: i) the detection and monitoring of the gene dsrB, gift in sulfate-reducing prokaryotes, through DGGE analysis in samples of mDNA of a mangrove sediment and semiarid soil, both in the BPP; ii) to relate genomic characteristics to the ecological aspects of Archaea through in silico studies, standing out the importance to the oil and gas industry. The results of the first work suggest that the petrodegraders communities of SRP persist after the contamination with oil in mangrove sediment and in semiarid soil. Comparing the populations of both sites, it reveals that there are variations in the size and composition during one year of experiments. In the second work, functional and structural factors are the probable cause to the pressure in maintenance of the conservation of the sequences in the multiple copies of the 16S rDNA gene. Is verified also the discrepancy established between total content GC and content GC of the same gene. Such results relating ribosomal genes and the ambient factors are important for metagenomic evaluations using PCR-DGGE. The knowledge of microbiota associated to the oil can contribute for a better destination of resources by the petroliferous industry and the development of bioremediation strategies. Likewise, search to lead to the best agreement of the performance of native microbiota in biogeochemical cycles in Potiguar Petroliferous Basin ecosystem

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Principal Topic High technology consumer products such as notebooks, digital cameras and DVD players are not introduced into a vacuum. Consumer experience with related earlier generation technologies, such as PCs, film cameras and VCRs, and the installed base of these products strongly impacts the market diffusion of the new generation products. Yet technology substitution has received only sparse attention in the diffusion of innovation literature. Research for consumer durables has been dominated by studies of (first purchase) adoption (c.f. Bass 1969) which do not explicitly consider the presence of an existing product/technology. More recently, considerable attention has also been given to replacement purchases (c.f. Kamakura and Balasubramanian 1987). Only a handful of papers explicitly deal with the diffusion of technology/product substitutes (e.g. Norton and Bass, 1987: Bass and Bass, 2004). They propose diffusion-type aggregate-level sales models that are used to forecast the overall sales for successive generations. Lacking household data, these aggregate models are unable to give insights into the decisions by individual households - whether to adopt generation II, and if so, when and why. This paper makes two contributions. It is the first large-scale empirical study that collects household data for successive generations of technologies in an effort to understand the drivers of adoption. Second, in comparision to traditional analysis that evaluates technology substitution as an ''adoption of innovation'' type process, we propose that from a consumer's perspective, technology substitution combines elements of both adoption (adopting the new generation technology) and replacement (replacing the generation I product with generation II). Based on this proposition, we develop and test a number of hypotheses. Methodology/Key Propositions In some cases, successive generations are clear ''substitutes'' for the earlier generation, in that they have almost identical functionality. For example, successive generations of PCs Pentium I to II to III or flat screen TV substituting for colour TV. More commonly, however, the new technology (generation II) is a ''partial substitute'' for existing technology (generation I). For example, digital cameras substitute for film-based cameras in the sense that they perform the same core function of taking photographs. They have some additional attributes of easier copying and sharing of images. However, the attribute of image quality is inferior. In cases of partial substitution, some consumers will purchase generation II products as substitutes for their generation I product, while other consumers will purchase generation II products as additional products to be used as well as their generation I product. We propose that substitute generation II purchases combine elements of both adoption and replacement, but additional generation II purchases are solely adoption-driven process. Extensive research on innovation adoption has consistently shown consumer innovativeness is the most important consumer characteristic that drives adoption timing (Goldsmith et al. 1995; Gielens and Steenkamp 2007). Hence, we expect consumer innovativeness also to influence both additional and substitute generation II purchases. Hypothesis 1a) More innovative households will make additional generation II purchases earlier. 1 b) More innovative households will make substitute generation II purchases earlier. 1 c) Consumer innovativeness will have a stronger impact on additional generation II purchases than on substitute generation II purchases. As outlined above, substitute generation II purchases act, in part like a replacement purchase for the generation I product. Prior research (Bayus 1991; Grewal et al 2004) identified product age as the most dominant factor influencing replacements. Hence, we hypothesise that: Hypothesis 2: Households with older generation I products will make substitute generation II purchases earlier. Our survey of 8,077 households investigates their adoption of two new generation products: notebooks as a technology change to PCs, and DVD players as a technology shift from VCRs. We employ Cox hazard modelling to study factors influencing the timing of a household's adoption of generation II products. We determine whether this is an additional or substitute purchase by asking whether the generation I product is still used. A separate hazard model is conducted for additional and substitute purchases. Consumer Innovativeness is measured as domain innovativeness adapted from the scales of Goldsmith and Hofacker (1991) and Flynn et al. (1996). The age of the generation I product is calculated based on the most recent household purchase of that product. Control variables include age, size and income of household, and age and education of primary decision-maker. Results and Implications Our preliminary results confirm both our hypotheses. Consumer innovativeness has a strong influence on both additional purchases (exp = 1.11) and substitute purchases (exp = 1.09). Exp is interpreted as the increased probability of purchase for an increase of 1.0 on a 7-point innovativeness scale. Also consistent with our hypotheses, the age of the generation I product has a dramatic influence for substitute purchases of VCR/DVD (exp = 2.92) and a strong influence for PCs/notebooks (exp = 1.30). Exp is interpreted as the increased probability of purchase for an increase of 10 years in the age of the generation I product. Yet, also as hypothesised, there was no influence on additional purchases. The results lead to two key implications. First, there is a clear distinction between additional and substitute purchases of generation II products, each with different drivers. Treating these as a single process will mask the true drivers of adoption. For substitute purchases, product age is a key driver. Hence, implications for marketers of high technology products can utilise data on generation I product age (e.g. from warranty or loyalty programs) to target customers who are more likely to make a purchase.