A Serratia marcescens PigP Homolog Controls Prodigiosin Biosynthesis, Swarming Motility and Hemolysis and Is Regulated by cAMP-CRP and HexS

Swarming motility and hemolysis are virulence-associated determinants for a wide array of pathogenic bacteria. The broad host-range opportunistic pathogen Serratia marcescens produces serratamolide, a small cyclic amino-lipid, that promotes swarming motility and hemolysis. Serratamolide is negatively regulated by the transcription factors HexS and CRP. Positive regulators of serratamolide production are unknown. Similar to serratamolide, the antibiotic pigment, prodigiosin, is regulated by temperature, growth phase, HexS, and CRP. Because of this co-regulation, we tested the hypothesis that a homolog of the PigP transcription factor of the atypical Serratia species ATCC 39006, which positively regulates prodigiosin biosynthesis, is also a positive regulator of serratamolide production in S. marcescens. Mutation of pigP in clinical, environmental, and laboratory strains of S. marcescens conferred pleiotropic phenotypes including the loss of swarming motility, hemolysis, and severely reduced prodigiosin and serratamolide synthesis. Transcriptional analysis and electrophoretic mobility shift assays place PigP in a regulatory pathway with upstream regulators CRP and HexS. The data from this study identifies a positive regulator of serratamolide production, describes novel roles for the PigP transcription factor, shows for the first time that PigP directly regulates the pigment biosynthetic operon, and identifies upstream regulators of pigP. This study suggests that PigP is important for the ability of S. marcescens to compete in the environment. © 2013 Shanks et al

Modulation of the epithelial sodium channel (ENaC) by bacterial metalloproteases and protease inhibitors

The serralysin family of metalloproteases is associated with the virulence of multiple gram-negative human pathogens, including Pseudomonas aeruginosa and Serratia marcescens. The serralysin proteases share highly conserved catalytic domains and show evolutionary similarity to the mammalian matrix metalloproteases. Our previous studies demonstrated that alkaline protease (AP) from Pseudomonas aeruginosa is capable of activating the epithelial sodium channel (ENaC), leading to an increase in sodium absorption in airway epithelia. The serralysin proteases are often co-expressed with endogenous, intracellular or periplasmic inhibitors, which putatively protect the bacterium from unwanted or unregulated protease activities. To evaluate the potential use of these small protein inhibitors in regulating the serralysin induced activation of ENaC, proteases from Pseudomonas aeruginosa and Serratia marcescens were purified for characterization along with a high affinity inhibitor from Pseudomonas. Both proteases showed activity against in vitro substrates and could be blocked by near stoichiometric concentrations of the inhibitor. In addition, both proteases were capable of activating ENaC when added to the apical surfaces of multiple epithelial cells with similar slow activation kinetics. The high-affinity periplasmic inhibitor from Pseudomonas effectively blocked this activation. These data suggest that multiple metalloproteases are capable of activating ENaC. Further, the endogenous, periplasmic bacterial inhibitors may be useful for modulating the downstream effects of the serralysin virulence factors under physiological conditions. © 2014 Butterworth et al

Using EMG to deliver lumbar dynamic electrical stimulation to facilitate cortico-spinal excitability

Background: Potentiation of synaptic activity in spinal networks is reflected in the magnitude of modulation of motor responses evoked by spinal and cortical input. After spinal cord injury, motor evoked responses can be facilitated by pairing cortical and peripheral nerve stimuli. Objective: To facilitate synaptic potentiation of cortico-spinal input with epidural electrical stimulation, we designed a novel neuromodulation method called dynamic stimulation (DS), using patterns derived from hind limb EMG signal during stepping. Methods: DS was applied dorsally to the lumbar enlargement through a high-density epidural array composed of independent platinum-based micro-electrodes. Results: In fully anesthetized intact adult rats, at the interface array/spinal cord, the temporal and spatial features of DS neuromodulation affected the entire lumbosacral network, particularly the most rostral and caudal segments covered by the array. DS induced a transient (at least 1 min) increase in spinal cord excitability and, compared to tonic stimulation, generated a more robust potentiation of the motor output evoked by single pulses applied to the spinal cord. When sub-threshold pulses were selectively applied to a cortical motor area, EMG responses from the contralateral leg were facilitated by the delivery of DS to the lumbosacral cord. Finally, based on motor-evoked responses, DS was linked to a greater amplitude of motor output shortly after a calibrated spinal cord contusion. Conclusion: Compared to traditional tonic waveforms, DS amplifies both spinal and cortico-spinal input aimed at spinal networks, thus significantly increasing the potential and accelerating the rate of functional recovery after a severe spinal lesion

A novel algorithm for dynamic student profile adaptation based on learning styles

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.E-learning recommendation systems are used to enhance student performance and knowledge by providing tailor- made services based on the students’ preferences and learning styles, which are typically stored in student profiles. For such systems to remain effective, the profiles need to be able to adapt and reflect the students’ changing behaviour. In this paper, we introduce new algorithms that are designed to track student learning behaviour patterns, capture their learning styles, and maintain dynamic student profiles within a recommendation system (RS). This paper also proposes a new method to extract features that characterise student behaviour to identify students’ learning styles with respect to the Felder-Silverman learning style model (FSLSM). In order to test the efficiency of the proposed algorithm, we present a series of experiments that use a dataset of real students to demonstrate how our proposed algorithm can effectively model a dynamic student profile and adapt to different student learning behaviour. The results revealed that the students could effectively increase their learning efficiency and quality for the courses when the learning styles are identified, and proper recommendations are made by using our method

Effect of base–acid properties of the mixtures of water with methanol on the solution enthalpy of selected cyclic ethers in this mixture at 298.15 K

The enthalpies of solution of cyclic ethers: 1,4- dioxane, 12-crown-4 and 18-crown-6 in the mixture of water and methanol have been measured within the whole mole fraction range at T = 298.15 K. Based on the obtained data, the effect of base–acid properties of water– methanol mixtures on the solution enthalpy of cyclic ethers in these mixtures has been analyzed. The solution enthalpy of cyclic ethers depends on acid properties of water– methanol mixtures in the range of high and medium water contents in the mixture. Based on the analysis performed, it can be assumed that in the mixtures of high methanol contents, cyclic ethe

Computational Complexity of interacting electrons and fundamental limitations of Density Functional Theory

One of the central problems in quantum mechanics is to determine the ground state properties of a system of electrons interacting via the Coulomb potential. Since its introduction by Hohenberg, Kohn, and Sham, Density Functional Theory (DFT) has become the most widely used and successful method for simulating systems of interacting electrons, making their original work one of the most cited in physics. In this letter, we show that the field of computational complexity imposes fundamental limitations on DFT, as an efficient description of the associated universal functional would allow to solve any problem in the class QMA (the quantum version of NP) and thus particularly any problem in NP in polynomial time. This follows from the fact that finding the ground state energy of the Hubbard model in an external magnetic field is a hard problem even for a quantum computer, while given the universal functional it can be computed efficiently using DFT. This provides a clear illustration how the field of quantum computing is useful even if quantum computers would never be built.Comment: 8 pages, 3 figures. v2: Version accepted at Nature Physics; differs significantly from v1 (including new title). Includes an extra appendix (not contained in the journal version) on the NP-completeness of Hartree-Fock, which is taken from v