331 research outputs found

    Optimisation of biomass, exopolysaccharide and intracellular polysaccharide production from the mycelium of an identified Ganoderma lucidum strain QRS 5120 using response surface methodology

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    Wild-cultivated medicinal mushroom Ganoderma lucidum was morphologically identified and sequenced using phylogenetic software. In submerged-liquid fermentation (SLF), biomass, exopolysaccharide (EPS) and intracellular polysaccharide (IPS) production of the identified G. lucidum was optimised based on initial pH, starting glucose concentration and agitation rate parameters using response surface methodology (RSM). Molecularly, the G. lucidum strain QRS 5120 generated 637 base pairs, which was commensurate with related Ganoderma species. In RSM, by applying central composite design (CCD), a polynomial model was fitted to the experimental data and was found to be significant in all parameters investigated. The strongest effect (p lt 0.0001) was observed for initial pH for biomass, EPS and IPS production, while agitation showed a significant value (p lt 0.005) for biomass. By applying the optimized conditions, the model was validated and generated 5.12 g/L of biomass (initial pH 4.01, 32.09 g/L of glucose and 102 rpm), 2.49 g/L EPS (initial pH 4, 24.25 g/L of glucose and 110 rpm) and 1.52 g/L of IPS (and initial pH 4, 40.43 g/L of glucose, 103 rpm) in 500 mL shake flask fermentation. The optimized parameters can be upscaled for efficient biomass, EPS and IPS production using G. lucidum

    Approaches in biotechnological applications of natural polymers

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    Natural polymers, such as gums and mucilage, are biocompatible, cheap, easily available and non-toxic materials of native origin. These polymers are increasingly preferred over synthetic materials for industrial applications due to their intrinsic properties, as well as they are considered alternative sources of raw materials since they present characteristics of sustainability, biodegradability and biosafety. As definition, gums and mucilages are polysaccharides or complex carbohydrates consisting of one or more monosaccharides or their derivatives linked in bewildering variety of linkages and structures. Natural gums are considered polysaccharides naturally occurring in varieties of plant seeds and exudates, tree or shrub exudates, seaweed extracts, fungi, bacteria, and animal sources. Water-soluble gums, also known as hydrocolloids, are considered exudates and are pathological products; therefore, they do not form a part of cell wall. On the other hand, mucilages are part of cell and physiological products. It is important to highlight that gums represent the largest amounts of polymer materials derived from plants. Gums have enormously large and broad applications in both food and non-food industries, being commonly used as thickening, binding, emulsifying, suspending, stabilizing agents and matrices for drug release in pharmaceutical and cosmetic industries. In the food industry, their gelling properties and the ability to mold edible films and coatings are extensively studied. The use of gums depends on the intrinsic properties that they provide, often at costs below those of synthetic polymers. For upgrading the value of gums, they are being processed into various forms, including the most recent nanomaterials, for various biotechnological applications. Thus, the main natural polymers including galactomannans, cellulose, chitin, agar, carrageenan, alginate, cashew gum, pectin and starch, in addition to the current researches about them are reviewed in this article.. }To the Conselho Nacional de Desenvolvimento Cientfíico e Tecnológico (CNPq) for fellowships (LCBBC and MGCC) and the Coordenação de Aperfeiçoamento de Pessoal de Nvíel Superior (CAPES) (PBSA). This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit, the Project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462) and COMPETE 2020 (POCI-01-0145-FEDER-006684) (JAT)

    A draft human pangenome reference

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    Here the Human Pangenome Reference Consortium presents a first draft of the human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individual

    Perspectives on the use of transcriptomics to advance biofuels

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    As a field within the energy research sector, bioenergy is continuously expanding. Although much has been achieved and the yields of both ethanol and butanol have been improved, many avenues of research to further increase these yields still remain. This review covers current research related with transcriptomics and the application of this high-throughput analytical tool to engineer both microbes and plants with the penultimate goal being better biofuel production and yields. The initial focus is given to the responses of fermentative microbes during the fermentative production of acids, such as butyric acid, and solvents, including ethanol and butanol. As plants offer the greatest natural renewable source of fermentable sugars within the form of lignocellulose, the second focus area is the transcriptional responses of microbes when exposed to plant hydrolysates and lignin-related compounds. This is of particular importance as the acid/base hydrolysis methods commonly employed to make the plant-based cellulose available for enzymatic hydrolysis to sugars also generates significant amounts of lignin-derivatives that are inhibitory to fermentative bacteria and microbes. The article then transitions to transcriptional analyses of lignin-degrading organisms, such as Phanerochaete chrysosporium, as an alternative to acid/base hydrolysis. The final portion of this article will discuss recent transcriptome analyses of plants and, in particular, the genes involved in lignin production. The rationale behind these studies is to eventually reduce the lignin content present within these plants and, consequently, the amount of inhibitors generated during the acid/base hydrolysis of the lignocelluloses. All four of these topics represent key areas where transcriptomic research is currently being conducted to identify microbial genes and their responses to products and inhibitors as well as those related with lignin degradation/formation.clos

    Evolving, dynamic clustering of spatio/spectro-temporal data in 3D spiking neural network models and a case study on EEG data

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    Clustering is a fundamental data processing technique. While clustering of static (vector based) data and of fixed window size time series have been well explored, dynamic clustering of spatiotemporal data has been little researched if at all. Especially when patterns of changes (events) in the data across space and time have to be captured and understood. The paper presents novel methods for clustering of spatiotemporal data using the NeuCube spiking neural network (SNN) architecture. Clusters of spatiotemporal data were created and modified on-line in a continuous, incremental way, where spatiotemporal relationships of changes in variables are incrementally learned in a 3D SNN model and the model connectivity and spiking activity are incrementally clustered. Two clustering methods were proposed for SNN, one performed during unsupervised and one—during supervised learning models. Before submitted to the models, the data is encoded as spike trains, a spike representing a change in the variable value (an event). During the unsupervised learning, the cluster centres were predefined by the spatial locations of the input data variables in a 3D SNN model. Then clusters are evolving during the learning, i.e. they are adapted continuously over time reflecting the dynamics of the changes in the data. In the supervised learning, clusters represent the dynamic sequence of neuron spiking activities in a trained SNN model, specific for a particular class of data or for an individual instance. We illustrate the proposed clustering method on a real case study of spatiotemporal EEG data, recorded from three groups of subjects during a cognitive task. The clusters were referred back to the brain data for a better understanding of the data and the processes that generated it. The cluster analysis allowed to discover and understand differences on temporal sequences and spatial involvement of brain regions in response to a cognitive task

    <i>Gaia</i> Data Release 1. Summary of the astrometric, photometric, and survey properties

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    Context. At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry for over 1 billion sources brighter than magnitude 20.7. Aims. A summary of Gaia DR1 is presented along with illustrations of the scientific quality of the data, followed by a discussion of the limitations due to the preliminary nature of this release. Methods. The raw data collected by Gaia during the first 14 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into an astrometric and photometric catalogue. Results. Gaia DR1 consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the HIPPARCOS and Tycho-2 catalogues – a realisation of the Tycho-Gaia Astrometric Solution (TGAS) – and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is the photometric data set, consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of ∼3000 Cepheid and RR-Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas yr−1 for the proper motions. A systematic component of ∼0.3 mas should be added to the parallax uncertainties. For the subset of ∼94 000 HIPPARCOS stars in the primary data set, the proper motions are much more precise at about 0.06 mas yr−1. For the secondary astrometric data set, the typical uncertainty of the positions is ∼10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to ∼0.03 mag over the magnitude range 5 to 20.7. Conclusions. Gaia DR1 is an important milestone ahead of the next Gaia data release, which will feature five-parameter astrometry for all sources. Extensive validation shows that Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important limitations to the data quality which should be carefully considered before drawing conclusions from the data

    Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

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    The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

    Evolutionary Processes Acting on Candidate cis-Regulatory Regions in Humans Inferred from Patterns of Polymorphism and Divergence

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    Analysis of polymorphism and divergence in the non-coding portion of the human genome yields crucial information about factors driving the evolution of gene regulation. Candidate cis-regulatory regions spanning more than 15,000 genes in 15 African Americans and 20 European Americans were re-sequenced and aligned to the chimpanzee genome in order to identify potentially functional polymorphism and to characterize and quantify departures from neutral evolution. Distortions of the site frequency spectra suggest a general pattern of selective constraint on conserved non-coding sites in the flanking regions of genes (CNCs). Moreover, there is an excess of fixed differences that cannot be explained by a Gamma model of deleterious fitness effects, suggesting the presence of positive selection on CNCs. Extensions of the McDonald-Kreitman test identified candidate cis-regulatory regions with high probabilities of positive and negative selection near many known human genes, the biological characteristics of which exhibit genome-wide trends that differ from patterns observed in protein-coding regions. Notably, there is a higher probability of positive selection in candidate cis-regulatory regions near genes expressed in the fetal brain, suggesting that a larger portion of adaptive regulatory changes has occurred in genes expressed during brain development. Overall we find that natural selection has played an important role in the evolution of candidate cis-regulatory regions throughout hominid evolution

    Heterologous Amyloid Seeding: Revisiting the Role of Acetylcholinesterase in Alzheimer's Disease

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    Neurodegenerative diseases associated with abnormal protein folding and ordered aggregation require an initial trigger which may be infectious, inherited, post-inflammatory or idiopathic. Proteolytic cleavage to generate vulnerable precursors, such as amyloid-β peptide (Aβ) production via β and γ secretases in Alzheimer's Disease (AD), is one such trigger, but the proteolytic removal of these fragments is also aetiologically important. The levels of Aβ in the central nervous system are regulated by several catabolic proteases, including insulysin (IDE) and neprilysin (NEP). The known association of human acetylcholinesterase (hAChE) with pathological aggregates in AD together with its ability to increase Aβ fibrilization prompted us to search for proteolytic triggers that could enhance this process. The hAChE C-terminal domain (T40, AChE575-614) is an exposed amphiphilic α-helix involved in enzyme oligomerisation, but it also contains a conformational switch region (CSR) with high propensity for conversion to non-native (hidden) β-strand, a property associated with amyloidogenicity. A synthetic peptide (AChE586-599) encompassing the CSR region shares homology with Aβ and forms β-sheet amyloid fibrils. We investigated the influence of IDE and NEP proteolysis on the formation and degradation of relevant hAChE β-sheet species. By combining reverse-phase HPLC and mass spectrometry, we established that the enzyme digestion profiles on T40 versus AChE586-599, or versus Aβ, differed. Moreover, IDE digestion of T40 triggered the conformational switch from α- to β-structures, resulting in surfactant CSR species that self-assembled into amyloid fibril precursors (oligomers). Crucially, these CSR species significantly increased Aβ fibril formation both by seeding the energetically unfavorable formation of amyloid nuclei and by enhancing the rate of amyloid elongation. Hence, these results may offer an explanation for observations that implicate hAChE in the extent of Aβ deposition in the brain. Furthermore, this process of heterologous amyloid seeding by a proteolytic fragment from another protein may represent a previously underestimated pathological trigger, implying that the abundance of the major amyloidogenic species (Aβ in AD, for example) may not be the only important factor in neurodegeneration

    A Directed Molecular Evolution Approach to Improved Immunogenicity of the HIV-1 Envelope Glycoprotein

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    A prophylactic vaccine is needed to slow the spread of HIV-1 infection. Optimization of the wild-type envelope glycoproteins to create immunogens that can elicit effective neutralizing antibodies is a high priority. Starting with ten genes encoding subtype B HIV-1 gp120 envelope glycoproteins and using in vitro homologous DNA recombination, we created chimeric gp120 variants that were screened for their ability to bind neutralizing monoclonal antibodies. Hundreds of variants were identified with novel antigenic phenotypes that exhibit considerable sequence diversity. Immunization of rabbits with these gp120 variants demonstrated that the majority can induce neutralizing antibodies to HIV-1. One novel variant, called ST-008, induced significantly improved neutralizing antibody responses when assayed against a large panel of primary HIV-1 isolates. Further study of various deletion constructs of ST-008 showed that the enhanced immunogenicity results from a combination of effective DNA priming, an enhanced V3-based response, and an improved response to the constant backbone sequences
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