Understanding and engineering beneficial plant–microbe interactions:Plant growth promotion in energy crops

Plant production systems globally must be optimized to produce stable high yields from limited land under changing and variable climates. Demands for food, animal feed, and feedstocks for bioenergy and biorefining applications, are increasing with population growth, urbanization and affluence. Low-input, sustainable, alternatives to petrochemical-derived fertilizers and pesticides are required to reduce input costs and maintain or increase yields, with potential biological solutions having an important role to play. In contrast to crops that have been bred for food, many bioenergy crops are largely undomesticated, and so there is an opportunity to harness beneficial plant–microbe relationships which may have been inadvertently lost through intensive crop breeding. Plant–microbe interactions span a wide range of relationships in which one or both of the organisms may have a beneficial, neutral or negative effect on the other partner. A relatively small number of beneficial plant–microbe interactions are well understood and already exploited; however, others remain understudied and represent an untapped reservoir for optimizing plant production. There may be near-term applications for bacterial strains as microbial biopesticides and biofertilizers to increase biomass yield from energy crops grown on land unsuitable for food production. Longer term aims involve the design of synthetic genetic circuits within and between the host and microbes to optimize plant production. A highly exciting prospect is that endosymbionts comprise a unique resource of reduced complexity microbial genomes with adaptive traits of great interest for a wide variety of applications

Coulomb effects in granular materials at not very low temperatures

We consider effects of Coulomb interaction in a granular normal metal at not very low temperatures suppressing weak localization effects. In this limit calculations with the initial electron Hamiltonian are reduced to integrations over a phase variable with an effective action, which can be considered as a bosonization for the granular metal. Conditions of the applicability of the effective action are considered in detail and importance of winding numbers for the phase variables is emphasized. Explicit calculations are carried out for the conductivity and the tunneling density of states in the limits of large $g\gg 1$ and small $g\ll 1$ tunnelling conductances. It is demonstrated for any dimension of the array of the grains that at small $g$ the conductivity and the tunnelling density of states decay with temperature exponentially. At large $g$ the conductivity also decays with decreasing the temparature and its temperature dependence is logarithmic independent of dimensionality and presence of a magnetic field. The tunnelling density of states for $g\gg 1$ is anomalous in any dimension but the anomaly is stronger than logarithmic in low dimensions and is similar to that for disordered systems. The formulae derived are compared with existing experiments. The logarithmic behavior of the conductivity at large $g$ obtained in our model can explain numerous experiments on systems with a granular structure including some high $T_{c}$ materials.Comment: 30 page

Spike timing-dependent plasticity induces non-trivial topology in the brain.

We study the capacity of Hodgkin-Huxley neuron in a network to change temporarily or permanently their connections and behavior, the so called spike timing-dependent plasticity (STDP), as a function of their synchronous behavior. We consider STDP of excitatory and inhibitory synapses driven by Hebbian rules. We show that the final state of networks evolved by a STDP depend on the initial network configuration. Specifically, an initial all-to-all topology evolves to a complex topology. Moreover, external perturbations can induce co-existence of clusters, those whose neurons are synchronous and those whose neurons are desynchronous. This work reveals that STDP based on Hebbian rules leads to a change in the direction of the synapses between high and low frequency neurons, and therefore, Hebbian learning can be explained in terms of preferential attachment between these two diverse communities of neurons, those with low-frequency spiking neurons, and those with higher-frequency spiking neurons

Pouvons-nous objectiver la raideur musculaire du patient fibromyalgique ?

Viscoelastic stiffness in the ankles of nine female subjects with fibromyalgia and nine control subjects was quantified by assessing passive sinusoidal movement. Increased elastic muscle stiffness in the ankles as well as different viscous muscle stiffness in the two ankles was observed in the subjects with fibromyalgia. In conclusion, measuring the resistance to the passive sinusoidal movement of the ankles could offer a valuable method of quantifying the subjective feeling of stiffness described by people with fibromyalgia