Electro-extractive fermentation for efficient biohydrogen production

Electrodialysis, an electrochemical membrane technique, was found to prolong and enhance the production of biohydrogen and purified organic acids via the anaerobic fermentation of glucose by Escherichia coli. Through the design of a model electrodialysis medium using cationic buffer, pH was precisely controlled electrokinetically, i.e. by the regulated extraction of acidic products with coulombic efficiencies of organic acid recovery in the range 50–70% maintained over continuous 30-day experiments. Contrary to\ud previous reports, E. coli produced H2 after aerobic growth in minimal medium without inducers and with a mixture of organic acids dominated by butyrate. The selective separation of organic acids from fermentation provides a potential nitrogen-free carbon source for further biohydrogen production in a parallel photofermentation. A parallel study incorporated this fermentation system into an integrated biohydrogen refinery (IBR) for the conversion of organic waste to hydrogen and energy

Left-right symmetry at LHC and precise 1-loop low energy data

Despite many tests, even the Minimal Manifest Left-Right Symmetric Model (MLRSM) has never been ultimately confirmed or falsified. LHC gives a new possibility to test directly the most conservative version of left-right symmetric models at so far not reachable energy scales. If we take into account precise limits on the model which come from low energy processes, like the muon decay, possible LHC signals are strongly limited through the correlations of parameters among heavy neutrinos, heavy gauge bosons and heavy Higgs particles. To illustrate the situation in the context of LHC, we consider the "golden" process $pp \to e^+ N$. For instance, in a case of degenerate heavy neutrinos and heavy Higgs masses at 15 TeV (in agreement with FCNC bounds) we get $\sigma(pp \to e^+ N)>10$ fb at $\sqrt{s}=14$ TeV which is consistent with muon decay data for a very limited $W_2$ masses in the range (3008 GeV, 3040 GeV). Without restrictions coming from the muon data, $W_2$ masses would be in the range (1.0 TeV, 3.5 TeV). Influence of heavy Higgs particles themselves on the considered LHC process is negligible (the same is true for the light, SM neutral Higgs scalar analog). In the paper decay modes of the right-handed heavy gauge bosons and heavy neutrinos are also discussed. Both scenarios with typical see-saw light-heavy neutrino mixings and the mixings which are independent of heavy neutrino masses are considered. In the second case heavy neutrino decays to the heavy charged gauge bosons not necessarily dominate over decay modes which include only light, SM-like particles.Comment: 16 pages, 10 figs, KL-KS and new ATLAS limits taken into accoun

Discrimination of low missing energy look-alikes at the LHC

The problem of discriminating possible scenarios of TeV scale new physics with large missing energy signature at the Large Hadron Collider (LHC) has received some attention in the recent past. We consider the complementary, and yet unexplored, case of theories predicting much softer missing energy spectra. As there is enough scope for such models to fake each other by having similar final states at the LHC, we have outlined a systematic method based on a combination of different kinematic features which can be used to distinguish among different possibilities. These features often trace back to the underlying mass spectrum and the spins of the new particles present in these models. As examples of "low missing energy look-alikes", we consider Supersymmetry with R-parity violation, Universal Extra Dimensions with both KK-parity conserved and KK-parity violated and the Littlest Higgs model with T-parity violated by the Wess-Zumino-Witten anomaly term. Through detailed Monte Carlo analysis of the four and higher lepton final states predicted by these models, we show that the models in their minimal forms may be distinguished at the LHC, while non-minimal variations can always leave scope for further confusion. We find that, for strongly interacting new particle mass-scale ~600 GeV (1 TeV), the simplest versions of the different theories can be discriminated at the LHC running at sqrt{s}=14 TeV within an integrated luminosity of 5 (30) fb^{-1}.Comment: 40 pages, 10 figures; v2: Further discussions, analysis and one figure added, ordering of certain sections changed, minor modifications in the abstract, version as published in JHE

A novel quantitative high-throughput screen identifies drugs that both activate SUMO conjugation via the inhibition of microRNAs 182 and 183 and facilitate neuroprotection in a model of oxygen and glucose deprivation

The conjugation/de-conjugation of Small Ubiquitin-like Modifier (SUMO) has been shown to be associated with a diverse set of physiologic/pathologic conditions. The clinical significance and ostensible therapeutic utility offered via the selective control of the global SUMOylation process has become readily apparent in ischemic pathophysiology. Herein, we describe the development of a novel quantitative high-throughput screening (qHTS) system designed to identify small molecules capable of increasing SUMOylation via the regulation/inhibition of members of the microRNA (miRNA)-182 family. This assay employs a SHSY5Y human neuroblastoma cell line stably transfected with a dual firefly-Renilla luciferase reporter system for identification of specific inhibitors of either miR-182 or miR-183. In this study, we have identified small molecules capable of inducing increased global conjugation of SUMO in both SHSY5Y cells and rat E18-derived primary cortical neurons. The protective effects of a number of the identified compounds were confirmed via an in vitro ischemic model (oxygen/glucose deprivation). Of note, this assay can be easily repurposed to allow high-throughput analyses of the potential drugability of other relevant miRNA(s) in ischemic pathobiology.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Intramural Research Program of the NINDS/NIH, an IRTA-OxCam Fellowship and by the Wellcome Trust [RRZA/057 and RG79423]

Signatures of arithmetic simplicity in metabolic network architecture

Metabolic networks perform some of the most fundamental functions in living cells, including energy transduction and building block biosynthesis. While these are the best characterized networks in living systems, understanding their evolutionary history and complex wiring constitutes one of the most fascinating open questions in biology, intimately related to the enigma of life's origin itself. Is the evolution of metabolism subject to general principles, beyond the unpredictable accumulation of multiple historical accidents? Here we search for such principles by applying to an artificial chemical universe some of the methodologies developed for the study of genome scale models of cellular metabolism. In particular, we use metabolic flux constraint-based models to exhaustively search for artificial chemistry pathways that can optimally perform an array of elementary metabolic functions. Despite the simplicity of the model employed, we find that the ensuing pathways display a surprisingly rich set of properties, including the existence of autocatalytic cycles and hierarchical modules, the appearance of universally preferable metabolites and reactions, and a logarithmic trend of pathway length as a function of input/output molecule size. Some of these properties can be derived analytically, borrowing methods previously used in cryptography. In addition, by mapping biochemical networks onto a simplified carbon atom reaction backbone, we find that several of the properties predicted by the artificial chemistry model hold for real metabolic networks. These findings suggest that optimality principles and arithmetic simplicity might lie beneath some aspects of biochemical complexity

NIBBS-Search for Fast and Accurate Prediction of Phenotype-Biased Metabolic Systems

Understanding of genotype-phenotype associations is important not only for furthering our knowledge on internal cellular processes, but also essential for providing the foundation necessary for genetic engineering of microorganisms for industrial use (e.g., production of bioenergy or biofuels). However, genotype-phenotype associations alone do not provide enough information to alter an organism's genome to either suppress or exhibit a phenotype. It is important to look at the phenotype-related genes in the context of the genome-scale network to understand how the genes interact with other genes in the organism. Identification of metabolic subsystems involved in the expression of the phenotype is one way of placing the phenotype-related genes in the context of the entire network. A metabolic system refers to a metabolic network subgraph; nodes are compounds and edges labels are the enzymes that catalyze the reaction. The metabolic subsystem could be part of a single metabolic pathway or span parts of multiple pathways. Arguably, comparative genome-scale metabolic network analysis is a promising strategy to identify these phenotype-related metabolic subsystems. Network Instance-Based Biased Subgraph Search (NIBBS) is a graph-theoretic method for genome-scale metabolic network comparative analysis that can identify metabolic systems that are statistically biased toward phenotype-expressing organismal networks. We set up experiments with target phenotypes like hydrogen production, TCA expression, and acid-tolerance. We show via extensive literature search that some of the resulting metabolic subsystems are indeed phenotype-related and formulate hypotheses for other systems in terms of their role in phenotype expression. NIBBS is also orders of magnitude faster than MULE, one of the most efficient maximal frequent subgraph mining algorithms that could be adjusted for this problem. Also, the set of phenotype-biased metabolic systems output by NIBBS comes very close to the set of phenotype-biased subgraphs output by an exact maximally-biased subgraph enumeration algorithm ( MBS-Enum ). The code (NIBBS and the module to visualize the identified subsystems) is available at http://freescience.org/cs/NIBBS

Peak plasma interleukin-6 and other peripheral markers of inflammation in the first week of ischaemic stroke correlate with brain infarct volume, stroke severity and long-term outcome

BACKGROUND: Cerebral ischaemia initiates an inflammatory response in the brain and periphery. We assessed the relationship between peak values of plasma interleukin-6 (IL-6) in the first week after ischaemic stroke, with measures of stroke severity and outcome. METHODS: Thirty-seven patients with ischaemic stroke were prospectively recruited. Plasma IL-6, and other markers of peripheral inflammation, were measured at pre-determined timepoints in the first week after stroke onset. Primary analyses were the association between peak plasma IL-6 concentration with both modified Rankin score (mRS) at 3 months and computed tomography (CT) brain infarct volume. RESULTS: Peak plasma IL-6 concentration correlated significantly (p < 0.001) with CT brain infarct volume (r = 0.75) and mRS at 3 months (r = 0.72). It correlated similarly with clinical outcome at 12 months or stroke severity. Strong associations were also noted between either peak plasma C-reactive protein (CRP) concentration or white blood cell (WBC) count, and all outcome measures. CONCLUSIONS: These data provide evidence that the magnitude of the peripheral inflammatory response is related to the severity of acute ischaemic stroke, and clinical outcome

Episodic formation of cometary material in the outburst of a solar-like young star

Our Solar System originated in interstellar gas and dust; the latter is in the form of amorphous silicate particles and carbonaceous dust. The composition of cometary material shows that a significant fraction of the amorphous silicates was transformed into crystalline form during the early evolution of the protosolar nebula. How and when this transformation happened has been controversial, with the main options being heating by the young Sun or shock heating. Here we report mid-infrared features in the outburst spectrum of the young solar-like star EX Lupi that were not present in quiescence. We attribute them to crystalline forsterite; the crystals were produced via thermal annealing in the surface layer of the inner disk by heat from the outburst, a process that has hitherto not been considered. The observed lack of cold crystals excludes shock heating at larger radii.Comment: 13 pages of PDF, including Supplementary Informatio