290 research outputs found

    Including metabolite concentrations into flux balance analysis: thermodynamic realizability as a constraint on flux distributions in metabolic networks

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    <p>Abstract</p> <p>Background</p> <p>In recent years, constrained optimization – usually referred to as flux balance analysis (FBA) – has become a widely applied method for the computation of stationary fluxes in large-scale metabolic networks. The striking advantage of FBA as compared to kinetic modeling is that it basically requires only knowledge of the stoichiometry of the network. On the other hand, results of FBA are to a large degree hypothetical because the method relies on plausible but hardly provable optimality principles that are thought to govern metabolic flux distributions.</p> <p>Results</p> <p>To augment the reliability of FBA-based flux calculations we propose an additional side constraint which assures thermodynamic realizability, i.e. that the flux directions are consistent with the corresponding changes of Gibb's free energies. The latter depend on metabolite levels for which plausible ranges can be inferred from experimental data. Computationally, our method results in the solution of a mixed integer linear optimization problem with quadratic scoring function. An optimal flux distribution together with a metabolite profile is determined which assures thermodynamic realizability with minimal deviations of metabolite levels from their expected values. We applied our novel approach to two exemplary metabolic networks of different complexity, the metabolic core network of erythrocytes (30 reactions) and the metabolic network iJR904 of <it>Escherichia coli </it>(931 reactions). Our calculations show that increasing network complexity entails increasing sensitivity of predicted flux distributions to variations of standard Gibb's free energy changes and metabolite concentration ranges. We demonstrate the usefulness of our method for assessing critical concentrations of external metabolites preventing attainment of a metabolic steady state.</p> <p>Conclusion</p> <p>Our method incorporates the thermodynamic link between flux directions and metabolite concentrations into a practical computational algorithm. The weakness of conventional FBA to rely on intuitive assumptions about the reversibility of biochemical reactions is overcome. This enables the computation of reliable flux distributions even under extreme conditions of the network (e.g. enzyme inhibition, depletion of substrates or accumulation of end products) where metabolite concentrations may be drastically altered.</p

    Cationic Amino Acids Specific Biomimetic Silicification in Ionic Liquid: A Quest to Understand the Formation of 3-D Structures in Diatoms

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    The intricate, hierarchical, highly reproducible, and exquisite biosilica structures formed by diatoms have generated great interest to understand biosilicification processes in nature. This curiosity is driven by the quest of researchers to understand nature's complexity, which might enable reproducing these elegant natural diatomaceous structures in our laboratories via biomimetics, which is currently beyond the capabilities of material scientists. To this end, significant understanding of the biomolecules involved in biosilicification has been gained, wherein cationic peptides and proteins are found to play a key role in the formation of these exquisite structures. Although biochemical factors responsible for silica formation in diatoms have been studied for decades, the challenge to mimic biosilica structures similar to those synthesized by diatoms in their natural habitats has not hitherto been successful. This has led to an increasingly interesting debate that physico-chemical environment surrounding diatoms might play an additional critical role towards the control of diatom morphologies. The current study demonstrates this proof of concept by using cationic amino acids as catalyst/template/scaffold towards attaining diatom-like silica morphologies under biomimetic conditions in ionic liquids

    A Novel Multi-Antigen Virally Vectored Vaccine against Mycobacterium avium Subspecies paratuberculosis

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    BACKGROUND: Mycobacterium avium subspecies paratuberculosis causes systemic infection and chronic intestinal inflammation in many species including primates. Humans are exposed through milk and from sources of environmental contamination. Hitherto, the only vaccines available against Mycobacterium avium subspecies paratuberculosis have been limited to veterinary use and comprised attenuated or killed organisms. METHODS: We developed a vaccine comprising a fusion construct designated HAV, containing components of two secreted and two cell surface Mycobacterium avium subspecies paratuberculosis proteins. HAV was transformed into DNA, human Adenovirus 5 (Ad5) and Modified Vaccinia Ankara (MVA) delivery vectors. Full length expression of the predicted 95 kDa fusion protein was confirmed. PRINCIPAL FINDINGS: Vaccination of naïve and Mycobacterium avium subspecies paratuberculosis infected C57BL/6 mice using DNA-prime/MVA-boost or Ad5-prime/MVA-boost protocols was highly immunogenic resulting in significant IFN-gamma ELISPOT responses by splenocytes against recombinant vaccine antigens and a range of HAV specific peptides. This included strong recognition of a T-cell epitope GFAEINPIA located near the C-terminus of the fusion protein. Antibody responses to recombinant vaccine antigens and HAV specific peptides but not GFAEINPIA, also occurred. No immune recognition of vaccine antigens occurred in any sham vaccinated Mycobacterium avium subspecies paratuberculosis infected mice. Vaccination using either protocol significantly attenuated pre-existing Mycobacterium avium subspecies paratuberculosis infection measured by qPCR in spleen and liver and the Ad5-prime/MVA-boost protocol also conferred some protection against subsequent challenge. No adverse effects of vaccination occurred in any of the mice. CONCLUSIONS/SIGNIFICANCE: A range of modern veterinary and clinical vaccines for the treatment and prevention of disease caused by Mycobacterium avium subspecies paratuberculosis are needed. The present vaccine proved to be highly immunogenic without adverse effect in mice and both attenuated pre-existing Mycobacterium avium subspecies paratuberculosis infection and conferred protection against subsequent challenge. Further studies of the present vaccine in naturally infected animals and humans are indicated

    Functional analysis of frequently expressed Chinese rhesus macaque MHC class I molecules Mamu-A1*02601 and Mamu-B*08301 reveals HLA-A2 and HLA-A3 supertypic specificities

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    The Simian immunodeficiency virus (SIV)-infected Indian rhesus macaque (Macaca mulatta) is the most established model of HIV infection and AIDS-related research, despite the potential that macaques of Chinese origin is a more relevant model. Ongoing efforts to further characterize the Chinese rhesus macaques’ major histocompatibility complex (MHC) for composition and function should facilitate greater utilization of the species. Previous studies have demonstrated that Chinese-origin M. mulatta (Mamu) class I alleles are more polymorphic than their Indian counterparts, perhaps inferring a model more representative of human MHC, human leukocyte antigen (HLA). Furthermore, the Chinese rhesus macaque class I allele Mamu-A1*02201, the most frequent allele thus far identified, has recently been characterized and shown to be an HLA-B7 supertype analog, the most frequent supertype in human populations. In this study, we have characterized two additional alleles expressed with high frequency in Chinese rhesus macaques, Mamu-A1*02601 and Mamu-B*08301. Upon the development of MHC–peptide-binding assays and definition of their associated motifs, we reveal that these Mamu alleles share peptide-binding characteristics with the HLA-A2 and HLA-A3 supertypes, respectively, the next most frequent human supertypes after HLA-B7. These data suggest that Chinese rhesus macaques may indeed be a more representative model of HLA gene diversity and function as compared to the species of Indian origin and therefore a better model for investigating human immune responses

    Production of dust by massive stars at high redshift

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    The large amounts of dust detected in sub-millimeter galaxies and quasars at high redshift pose a challenge to galaxy formation models and theories of cosmic dust formation. At z > 6 only stars of relatively high mass (> 3 Msun) are sufficiently short-lived to be potential stellar sources of dust. This review is devoted to identifying and quantifying the most important stellar channels of rapid dust formation. We ascertain the dust production efficiency of stars in the mass range 3-40 Msun using both observed and theoretical dust yields of evolved massive stars and supernovae (SNe) and provide analytical expressions for the dust production efficiencies in various scenarios. We also address the strong sensitivity of the total dust productivity to the initial mass function. From simple considerations, we find that, in the early Universe, high-mass (> 3 Msun) asymptotic giant branch stars can only be dominant dust producers if SNe generate <~ 3 x 10^-3 Msun of dust whereas SNe prevail if they are more efficient. We address the challenges in inferring dust masses and star-formation rates from observations of high-redshift galaxies. We conclude that significant SN dust production at high redshift is likely required to reproduce current dust mass estimates, possibly coupled with rapid dust grain growth in the interstellar medium.Comment: 72 pages, 9 figures, 5 tables; to be published in The Astronomy and Astrophysics Revie

    Operation and performance of the ATLAS Tile Calorimeter in Run 1

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    The Tile Calorimeter is the hadron calorimeter covering the central region of the ATLAS experiment at the Large Hadron Collider. Approximately 10,000 photomultipliers collect light from scintillating tiles acting as the active material sandwiched between slabs of steel absorber. This paper gives an overview of the calorimeter’s performance during the years 2008–2012 using cosmic-ray muon events and proton–proton collision data at centre-of-mass energies of 7 and 8TeV with a total integrated luminosity of nearly 30 fb−1. The signal reconstruction methods, calibration systems as well as the detector operation status are presented. The energy and time calibration methods performed excellently, resulting in good stability of the calorimeter response under varying conditions during the LHC Run 1. Finally, the Tile Calorimeter response to isolated muons and hadrons as well as to jets from proton–proton collisions is presented. The results demonstrate excellent performance in accord with specifications mentioned in the Technical Design Report

    Combined measurement of differential and total cross sections in the H → γγ and the H → ZZ* → 4ℓ decay channels at s=13 TeV with the ATLAS detector

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    A combined measurement of differential and inclusive total cross sections of Higgs boson production is performed using 36.1 fb−1 of 13 TeV proton–proton collision data produced by the LHC and recorded by the ATLAS detector in 2015 and 2016. Cross sections are obtained from measured H→γγ and H→ZZ*(→4ℓ event yields, which are combined taking into account detector efficiencies, resolution, acceptances and branching fractions. The total Higgs boson production cross section is measured to be 57.0−5.9 +6.0 (stat.) −3.3 +4.0 (syst.) pb, in agreement with the Standard Model prediction. Differential cross-section measurements are presented for the Higgs boson transverse momentum distribution, Higgs boson rapidity, number of jets produced together with the Higgs boson, and the transverse momentum of the leading jet. The results from the two decay channels are found to be compatible, and their combination agrees with the Standard Model predictions

    Performance of missing transverse momentum reconstruction with the ATLAS detector using proton–proton collisions at √s = 13 TeV

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    The performance of the missing transverse momentum (EmissT) reconstruction with the ATLAS detector is evaluated using data collected in proton–proton collisions at the LHC at a centre-of-mass energy of 13 TeV in 2015. To reconstruct EmissT, fully calibrated electrons, muons, photons, hadronically decaying τ -leptons, and jets reconstructed from calorimeter energy deposits and charged-particle tracks are used. These are combined with the soft hadronic activity measured by reconstructed charged-particle tracks not associated with the hard objects. Possible double counting of contributions from reconstructed charged-particle tracks from the inner detector, energy deposits in the calorimeter, and reconstructed muons from the muon spectrometer is avoided by applying a signal ambiguity resolution procedure which rejects already used signals when combining the various EmissT contributions. The individual terms as well as the overall reconstructed EmissT are evaluated with various performance metrics for scale (linearity), resolution, and sensitivity to the data-taking conditions. The method developed to determine the systematic uncertainties of the EmissT scale and resolution is discussed. Results are shown based on the full 2015 data sample corresponding to an integrated luminosity of 3.2 fb−1
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