3,172 research outputs found

    Identification of furfural resistant strains of Saccharomyces cerevisiae and Saccharomyces paradoxus from a collection of environmental and industrial isolates

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    Background Fermentation of bioethanol using lignocellulosic biomass as a raw material provides a sustainable alternative to current biofuel production methods by utilising waste food streams as raw material. Before lignocellulose can be fermented it requires physical, chemical and enzymatic treatment in order to release monosaccharides, a process that causes the chemical transformation of glucose and xylose into the cyclic aldehydes furfural and hydroxyfurfural. These furan compounds are potent inhibitors of Saccharomyces fermentation, and consequently furfural tolerant strains of Saccharomyces are required for lignocellulosic fermentation. Results This study investigated yeast tolerance to furfural and hydroxyfurfural using a collection of 71 environmental and industrial isolates of the baker’s yeast Saccharomyces cerevisiae and its closest relative Saccharomyces paradoxus. The Saccharomyces strains were initially screened for growth on media containing 100 mM glucose and 1.5 mg ml-1 furfural. Five strains were identified that showed a significant tolerance to growth in the presence of furfural and these were then screened for growth and ethanol production in the presence of increasing amounts (0.1-4 mg ml-1) of furfural. Conclusions Of the five furfural tolerant strains S. cerevisiae NCYC 3451 displayed the greatest furfural resistance, and was able to grow in the presence of up to 3.0 mg ml-1 furfural. Furthermore, ethanol production in this strain did not appear to be inhibited by furfural, with the highest ethanol yield observed at 3.0 mg ml-1 furfural. Although furfural resistance was not found to be a trait specific to any one particular lineage or population, three of the strains were isolated from environments where they might be continually exposed to low levels of furfural through the on-going natural degradation of lignocelluloses, and would therefore develop elevated levels of resistance to these furan compounds. Thus these strains represent good candidates for future studies of genetic variation relevant to understanding and manipulating furfural resistance and in the development of tolerant ethanologenic yeast strains for use in bioethanol production from lignocellulose processing

    Signal Propagation in Feedforward Neuronal Networks with Unreliable Synapses

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    In this paper, we systematically investigate both the synfire propagation and firing rate propagation in feedforward neuronal network coupled in an all-to-all fashion. In contrast to most earlier work, where only reliable synaptic connections are considered, we mainly examine the effects of unreliable synapses on both types of neural activity propagation in this work. We first study networks composed of purely excitatory neurons. Our results show that both the successful transmission probability and excitatory synaptic strength largely influence the propagation of these two types of neural activities, and better tuning of these synaptic parameters makes the considered network support stable signal propagation. It is also found that noise has significant but different impacts on these two types of propagation. The additive Gaussian white noise has the tendency to reduce the precision of the synfire activity, whereas noise with appropriate intensity can enhance the performance of firing rate propagation. Further simulations indicate that the propagation dynamics of the considered neuronal network is not simply determined by the average amount of received neurotransmitter for each neuron in a time instant, but also largely influenced by the stochastic effect of neurotransmitter release. Second, we compare our results with those obtained in corresponding feedforward neuronal networks connected with reliable synapses but in a random coupling fashion. We confirm that some differences can be observed in these two different feedforward neuronal network models. Finally, we study the signal propagation in feedforward neuronal networks consisting of both excitatory and inhibitory neurons, and demonstrate that inhibition also plays an important role in signal propagation in the considered networks.Comment: 33pages, 16 figures; Journal of Computational Neuroscience (published

    Search for flavour-changing neutral currents in processes with one top quark and a photon using 81 fb−1 of pp collisions at s=13TeV with the ATLAS experiment

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    A search for flavour-changing neutral current (FCNC) events via the coupling of a top quark, a photon, and an up or charm quark is presented using 81 fb−1 of proton–proton collision data taken at a centre-of-mass energy of 13 TeV with the ATLAS detector at the LHC. Events with a photon, an electron or muon, a b-tagged jet, and missing transverse momentum are selected. A neural network based on kinematic variables differentiates between events from signal and background processes. The data are consistent with the background-only hypothesis, and limits are set on the strength of the tqγ coupling in an effective field theory. These are also interpreted as 95% CL upper limits on the cross section for FCNC tγ production via a left-handed (right-handed) tuγ coupling of 36 fb (78 fb) and on the branching ratio for t→γu of 2.8×10−5 (6.1×10−5). In addition, they are interpreted as 95% CL upper limits on the cross section for FCNC tγ production via a left-handed (right-handed) tcγ coupling of 40 fb (33 fb) and on the branching ratio for t→γc of 22×10−5 (18×10−5)

    Endemicity of Zoonotic Diseases in Pigs and Humans in Lowland and Upland Lao PDR: Identification of Socio-cultural Risk Factors

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    In Lao People's Democratic Republic pigs are kept in close contact with families. Human risk of infection with pig zoonoses arises from direct contact and consumption of unsafe pig products. This cross-sectional study was conducted in Luang Prabang (north) and Savannakhet (central-south) Provinces. A total of 59 villages, 895 humans and 647 pigs were sampled and serologically tested for zoonotic pathogens including: hepatitis E virus (HEV), Japanese encephalitis virus (JEV) and Trichinella spiralis; In addition, human sera were tested for Taenia spp. and cysticercosis. Seroprevalence of zoonotic pathogens in humans was high for HEV (Luang Prabang: 48.6%, Savannakhet: 77.7%) and T. spiralis (Luang Prabang: 59.0%, Savannakhet: 40.5%), and lower for JEV (around 5%), Taenia spp. (around 3%) and cysticercosis (Luang Prabang: 6.1, Savannakhet 1.5%). Multiple correspondence analysis and hierarchical clustering of principal components was performed on descriptive data of human hygiene practices, contact with pigs and consumption of pork products. Three clusters were identified: Cluster 1 had low pig contact and good hygiene practices, but had higher risk of T. spiralis. Most people in cluster 2 were involved in pig slaughter (83.7%), handled raw meat or offal (99.4%) and consumed raw pigs' blood (76.4%). Compared to cluster 1, cluster 2 had increased odds of testing seropositive for HEV and JEV. Cluster 3 had the lowest sanitation access and had the highest risk of HEV, cysticercosis and Taenia spp. Farmers which kept their pigs tethered (as opposed to penned) and disposed of manure in water sources had 0.85 (95% CI: 0.18 to 0.91) and 2.39 (95% CI: 1.07 to 5.34) times the odds of having pigs test seropositive for HEV, respectively. The results have been used to identify entry-points for intervention and management strategies to reduce disease exposure in humans and pigs, informing control activities in a cysticercosis hyper-endemic village
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