1000 resultados para 050199 Ecological Applications not elsewhere classified
Resumo:
Enhanced biological phosphorus removal (EBPR) is one of the best-studied microbially mediated industrial processes because of its ecological and economic relevance. Despite this, it is not well understood at the metabolic level. Here we present a metagenomic analysis of two lab-scale EBPR sludges dominated by the uncultured bacterium, Candidatus Accumulibacter phosphatis.'' The analysis sheds light on several controversies in EBPR metabolic models and provides hypotheses explaining the dominance of A. phosphatis in this habitat, its lifestyle outside EBPR and probable cultivation requirements. Comparison of the same species from different EBPR sludges highlights recent evolutionary dynamics in the A. phosphatis genome that could be linked to mechanisms for environmental adaptation. In spite of an apparent lack of phylogenetic overlap in the flanking communities of the two sludges studied, common functional themes were found, at least one of them complementary to the inferred metabolism of the dominant organism. The present study provides a much needed blueprint for a systems-level understanding of EBPR and illustrates that metagenomics enables detailed, often novel, insights into even well-studied biological systems.
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An innovative method for modelling biological processes under anaerobic conditions is presented and discussed. The method is based on titrimetric and off-gas measurements. Titrimetric data is recorded as the addition rate of hydroxyl ions or protons that is required to maintain pH in a bioreactor at a constant level. An off-gas analysis arrangement measures, among other things, the transfer rate of carbon dioxide. The integration of these signals results in a continuous signal which is solely related to the biological reactions. When coupled with a mathematical model of the biological reactions, the signal allows a detailed characterisation of these reactions, which would otherwise be difficult to achieve. Two applications of the method to the enhanced biological phosphorus removal processes are presented and discussed to demonstrate the principle and effectiveness of the method.
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There has been a great deal of discussion about the need for interdisciplinary, applied research to service the needs of the knowledge economy and to solve the broader complex theoretical problems of the twenty-first century. This is known as 'Mode 2' knowledge production. Yet, university research higher degree programs continue to be largely disciplinary-based. While there has been a rise in the number of research students working on industry-related, applied projects, very few research students gain exposure to interdisciplinary research processes. This paper explores several examples of interdisciplinary doctoral programs based in North America and Australia and seeks to draw upon examples of undergraduate interdisciplinary learning and epistemology. In reviewing this theoretical work and a number of strategies implemented at an Australian university, the paper begins to imagine an interdisciplinary doctoral pedagogy.
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Discrete stochastic simulations are a powerful tool for understanding the dynamics of chemical kinetics when there are small-to-moderate numbers of certain molecular species. In this paper we introduce delays into the stochastic simulation algorithm, thus mimicking delays associated with transcription and translation. We then show that this process may well explain more faithfully than continuous deterministic models the observed sustained oscillations in expression levels of hes1 mRNA and Hes1 protein.
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Background: The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. Results: We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. Conclusion: The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.
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Motivation: While processing of MHC class II antigens for presentation to helper T-cells is essential for normal immune response, it is also implicated in the pathogenesis of autoimmune disorders and hypersensitivity reactions. Sequence-based computational techniques for predicting HLA-DQ binding peptides have encountered limited success, with few prediction techniques developed using three-dimensional models. Methods: We describe a structure-based prediction model for modeling peptide-DQ3.2 beta complexes. We have developed a rapid and accurate protocol for docking candidate peptides into the DQ3.2 beta receptor and a scoring function to discriminate binders from the background. The scoring function was rigorously trained, tested and validated using experimentally verified DQ3.2 beta binding and non-binding peptides obtained from biochemical and functional studies. Results: Our model predicts DQ3.2 beta binding peptides with high accuracy [area under the receiver operating characteristic (ROC) curve A(ROC) > 0.90], compared with experimental data. We investigated the binding patterns of DQ3.2 beta peptides and illustrate that several registers exist within a candidate binding peptide. Further analysis reveals that peptides with multiple registers occur predominantly for high-affinity binders.
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Complement factor 5a (C5a) is formed upon complement system activation in response to infection, injury or disease. Whilst C5a is a potent mediator of immune and inflammatory processes, excessive production or inadequate regulation of C5a has been implicated in the pathogenesis of numerous immuno-inflammatory diseases, predominantly through experimental studies utilising animal models of disease. Both acute and chronic conditions may benefit from C5a inhibition, including rheumatoid arthritis, inflammatory bowel disease, asthma, psoriasis, haemorrhagic shock and neurodegenerative conditions. The potentially broad clinical application for treatments that inhibit the activity of C5a at C5a receptors and the large global market for anti-inflammatory therapeutics have made C5a and the C5a receptor attractive targets for academic and commercial drug development programmes. in the past 5 years, interest in C5a as a drug target has grown substantially, and this activity has resulted in a collection of patents and scientific papers reporting novel C5a and C5a receptor inhibitors and antagonists, and generated a secondary stream of patent applications broadly claiming the use of C5/C5a inhibitors as a method of treating various immune and inflammatory conditions. This paper will review the physiology and pathophysiology of C5a and discuss the development of C5a and C5a receptor inhibitors in light of the recent scientific and patent literature.
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Using in situ spectrometry data and visual system modeling, we investigate whether the colors conferred to the reef-building corals by GFP-like proteins would look colorful not only to humans, but also to fish occupying different ecological niches on the reef. Some GFP-like proteins, most notably fluorescent greens and nonfluorescent chromoproteins, indeed generate intense color signals. An unexpected finding was that fluorescent proteins might also make corals appear less colorful to fish, counterbalancing the effect of absorption by the photosynthetic pigments of the endosymbiotic algae, which might be a form of protection against herbivores. We conclude that GFP-determined coloration of corals may be an important factor in visual ecology of the reef fishes.
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Quantitatively predicting mass transport rates for chemical mixtures in porous materials is important in applications of materials such as adsorbents, membranes, and catalysts. Because directly assessing mixture transport experimentally is challenging, theoretical models that can predict mixture diffusion coefficients using Only single-component information would have many uses. One such model was proposed by Skoulidas, Sholl, and Krishna (Langmuir, 2003, 19, 7977), and applications of this model to a variety of chemical mixtures in nanoporous materials have yielded promising results. In this paper, the accuracy of this model for predicting mixture diffusion coefficients in materials that exhibit a heterogeneous distribution of local binding energies is examined. To examine this issue, single-component and binary mixture diffusion coefficients are computed using kinetic Monte Carlo for a two-dimensional lattice model over a wide range of lattice occupancies and compositions. The approach suggested by Skoulidas, Sholl, and Krishna is found to be accurate in situations where the spatial distribution of binding site energies is relatively homogeneous, but is considerably less accurate for strongly heterogeneous energy distributions.
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The wild mungbean, Vigna radiata ssp. sublobata, is an 'old world' tropical species indigenous throughout the better watered areas of northern Australia. Variation among 115 accessions, mainly from Australia, West Timor, and Papua New Guinea, was evaluated for several diverse traits. The plants were cultivated in the field at 2 sowing dates, at both a tropical and a subtropical location, with 6 accessions from India and a mungbean cultivar for comparison. Substantial variation was identified for traits of potential agronomic, adaptive, or taxonomic interest. For some traits, like phenology, the variation appeared to be systematic, with plausible underlying physiological and/or adaptive explanation. Among accessions, wild type traits, like prostrate habit, more gracile morphology, twining form, and small hard seeds, tended to be associated. There was a general geographic trend for lines collected from locations more remote from where mungbean has historically been cultivated to show greater expression of wild type traits, with few 'traits of domestication' evident in the Australian accessions. Some of the identified variation, e. g. higher seed protein content, hardseededness, and putative disease resistance, may be of value in mungbean variety improvement. A more targetted evaluation of the collection would likely reveal other adaptations, especially tolerance to environmental stresses. As such, the wild accessions are a potentially valuable if under-utilised germplasm resource.
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Due to complex field/tissue interactions, high-field magnetic resonance (MR) images suffer significant image distortions that result in compromised diagnostic quality. A new method that attempts to remove these distortions is proposed in this paper and is based on the use of transceiver-phased arrays. The proposed system uses, in the examples presented herein, a shielded four-element transceive-phased array head coil and involves performing two separate scans of the same slice with each scan using different excitations during transmission. By optimizing the amplitudes and phases for each scan, antipodal signal profiles can be obtained, and by combining both the images together, the image distortion can be reduced several fold. A combined hybrid method of moments (MoM)/finite element method (FEM) and finite-difference time-domain (FDTD) technique is proposed and used to elucidate the concept of the new method and to accurately evaluate the electromagnetic field (EMF) in a human head model. In addition, the proposed method is used in conjunction with the generalized auto-calibrating partially parallel acquisitions (GRAPPA) reconstruction technique to enable rapid imaging of the two scans. Simulation results reported herein for 11-T (470-MHz) brain imaging applications show that the new method with GRAPPA reconstruction theoretically results in improved image quality and that the proposed combined hybrid MoM/FEM and FDTD technique is. suitable for high-field magnetic resonance imaging (MRI) numerical analysis.
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Telemedicine conducted via prerecorded interaction is more convenient than that using realtime interaction. On the other hand, a realtime consultation allows an immediate result to be obtained and there is likely to be a strong educational component for the remote practitioner. The use of the telephone is under-rated in telemedicine. Telephones have been used in outpatient follow-up, mental health, help lines and support groups. Telephones (fixed and mobile) have also been used for data transfer (e.g. for transmission of electrocardiograms). Realtime transfer of still images has been used in telepathology for many years, and more recently for rapid assessment of injuries. Realtime transfer of video images has been widely explored, perhaps most successfully in telepsychiatry. Some realtime telemedicine applications have been taken up with enthusiasm, even if formal evidence of cost-effectiveness may be lacking. Teleradiology and telepsychiatry are two examples where widespread adoption is beginning to occur. Other forms of realtime telemedicine represent 'niche' applications. That is, they appear to be both successful and sustainable in the centres where they were pioneered, but have not been adopted elsewhere. Teledialysis and teleoncology are examples of this type. The patchy diffusion of telemedicine is something that is not yet well understood.
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The article argues that economics will have to become a complex systems science before economists can comfortably incorporate institutionalist and evolutionary economics into mainstream theory. The article compares the complex adaptive system of John Foster with that of standard economic theory and illustrates the difference through an examination of familiar production function. The place of neoclassical, Keynesian economics in complex systems is considered. The article concludes that convincing, multiple models have been made possible by the increase in widely available computing power available.
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Using only linear interactions and a local parity measurement we show how entanglement can be detected between two harmonic oscillators. The scheme generalizes to measure both linear and nonlinear functionals of an arbitrary oscillator state. This leads to many applications including purity tests, eigenvalue estimation, entropy, and distance measures-all without the need for nonlinear interactions or complete state reconstruction. Remarkably, experimental realization of the proposed scheme is already within the reach of current technology with linear optics.
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We investigate the gas-particle dynamics of a device designed for biological pre-clinical experiments. The device uses transonic/supersonic gas flow to accelerate microparticles such that they penetrate the outer skin layers. By using a shock tube coupled to a correctly expanded nozzle, a quasi-one-dimensional, quasi-steady flow (QSF) is produced to uniformly accelerate the microparticles. The system utilises a microparticle cassette (a diaphragm sealed container) that incorporates a jet mixing mechanism to stir the particles prior to diaphragm rupture. Pressure measurements reveal that a QSF exit period - suitable for uniformly accelerating microparticles - exists between 155 and 220 mus after diaphragm rupture. Immediately preceding the QSF period, a starting process secondary shock was shown to form with its (x,t) trajectory comparing well to theoretical estimates. To characterise the microparticle, flow particle image velocimetry experiments were conducted at the nozzle exit, using particle payloads with varying diameter (2.7-48 mu m), density (600-16,800 kg/m(3)) and mass (0.25-10 mg). The resultant microparticle velocities were temporally uniform. The experiments also show that the starting process does not significantly influence the microparticle nozzle exit velocities. The velocity distribution across the nozzle exit was also uniform for the majority of microparticle types tested. For payload masses typically used in pre-clinical drug and vaccine applications (